Artykuły w czasopismach na temat „Abnormal value removing”

To improve the accuracy of detecting soil total nitrogen (STN) content by an artificial olfactory system, this paper proposes a multi-feature optimization method for soil total nitrogen content based on an artificial olfactory system. Ten different metal–oxide semiconductor gas sensors were selected to form a sensor array to collect soil gas and generate response curves. Additionally, six features such as the response area, maximum value, average differential coefficient, standard deviation value, average value, and 15th-second transient value of each sensor response curve were extracted to construct an artificial olfactory feature space (10 × 6). Moreover, the relationship between feature space and soil total nitrogen content was used to establish backpropagation neural network (BPNN), extreme learning machine (ELM), and partial least squares regression (PLSR) models were used, and the coefficient of determination (R2), root mean square error (RMSE), and the ratio of performance to deviation (RPD) were selected as prediction performance indicators. The Monte Carlo cross-validation (MCCV) and K-means improved leave-one-out cross-validation (K-means LOOCV) were adopted to identify and remove abnormal samples in the feature space and establish the BPNN model, respectively. There were significant improvements before and after comparing the two rejection methods, among which the MCCV rejection method was superior, where values for R2, RMSE, and RPD were 0.75671, 0.33517, and 1.7938, respectively. After removing the abnormal samples, the soil samples were then subjected to feature-optimized dimensionality reduction using principal component analysis (PCA) and genetic algorithm-based optimization backpropagation neural network (GA-BP). The test results showed that after feature optimization the model indicators performed better than those of the unoptimized model, and the PLSR model with GA-BP for feature optimization had the best prediction effect, with an R2 value of 0.93848, RPD value of 3.5666, and RMSE value of 0.16857 in the test set. R2 and RPD values improved by 14.01% and 50.60%, respectively, compared with those before optimization, and RMSE value decreased by 45.16%, which effectively improved the accuracy of the artificial olfactory system in detecting soil total nitrogen content and could achieve more accurate quantitative prediction of soil total nitrogen content.

The scale of Software Defined Networks (SDN) is expanding rapidly and the demands for security reinforcement are increasing. SDN creates new targets for potential security threats such as the SDN controller and networking devices in the data plane. Violation of data plane integrity might lead to abnormal behaviors of the overall network. In this paper, we propose a new security approach for OpenFlow-based SDN in order to detect violation of switches flow tables integrity and successfully locate the compromised switches online. We cover all aspects of integrity violation including flow rule adding, modifying and removing by an unauthorized entity. We achieve this by using the cookie field in the OpenFlow protocol to put in a suitable digest (hash) value for each flow entry. Moreover, we optimize our method performance by calculating a global digest value for the entire switch’s flow table that decides whether a switch is suspected of being compromised. Our method is also able to determine and handle false alarms that affect the coherence of a corresponding table digest. The implementation is a reactive java module integrated with the Floodlight controller. In addition, we introduce a performance evaluation for three different SDN topologies.

Supplier concentration (SUC) has disadvantage of vulnerability along with cost savings and efficiency. While current scholarship focus on the vulnerability of firms with centralized suppliers during the COVID-19 epidemic, there is no empirical study that explores the impact of post-disaster SUC on firm value as countries removing regional isolation policy. I focus on the impact of COVID-19 reopening policy on investor attitudes towards SUC after the resolution of a supply chain disruption crisis. I try to examine whether investors still perceive SUC as a risk signal or as a positive signal for rapid recovery. Using the event shock of China’s reopening announcement and data on A-share listed companies, I find that SUC has a positive impact on cumulative abnormal returns at reopening. I also find that positive effect of SUC is more prominent for firms that benefit from a larger reduction in transaction costs due to the reopening policy. I also analyze the moderating effect and find that information intermediaries such as analysts and media attention amplify the positive effects of SUC. My research provides new perspective on achieving post-disaster value enhancement through SUC.

Existing distance-based outlier mining methods do not consider the impact of each attribute's importance degree, thereby resulting in poor mining accuracies. To address this problem, we propose a new outlier mining algorithm – Miner* – that makes use of information entropy and Weighted Distance Sum to substantially improve mining accuracies. Miner* employs information entropy to determine weight values indicating the importance degrees of data attributes. An input dataset is reduced by Miner* through the neighbour-radius-based pruning technologies. Thus, Miner* obtains a candidate outlier set by removing any data objects that are unlikely to be outliers. Miner* calculates the weighted distance sum value Wkof each object in the candidate outlier set; Wkvalue ranks the top n to be regarded as outliers. Due to the sum of distance, which takes full advantage of the clustering characteristics of the dataset, edge distribution data objects and local outliers can be effectively mined out. To demonstrate the effectiveness of the Miner* algorithm, we implement Miner* in a prototype system to detect star spectrum data objects with abnormal characteristic lines. Our experimental results show that the algorithm in Miner* achieves high accuracy, high scalability, and low man-made influence by utilizing UCI and star spectrum dataset. Our results also confirm that Miner* is feasible and effective in mining spectrum data with abnormal characteristic lines from massive star spectrum dataset.

This paper reports new findings from applying portfolio method, which shows a much bigger earnings impact on share prices (ERC) compared to the erstwhile reports of ERC using individual events, averaged over the sample. We estimate cumulative abnormal returns, CAR, across a test window for each quarterly earnings announcement event across one accounting year. The CARs are then regressed against earnings changes of individual firms and portfolios. The findings show a significant positive CAR when earnings increases; and a negative CAR if earnings declines. The ERC is very small in the test period of 2001-14, which is consistent with published results for years before 2000. The ERC size magnifies substantially due to the grouping effect used through portfolio formation. What is significant is that the use of portfolio method, by removing the idiosyncratic errors, show a price response very close to the size of earnings. The last evidence supports strongly the value relevance accounting theory that has not seen much support from averaging the price responses of individual event responses.

<span>This paper explores using cameras aimed at the accelerator and brake pedals during sudden unintended acceleration in cars, removing noise from captured images to determine driver incompetence. A car model was constructed using Raspberry Pi to simulate brake malfunction using random functions, increasing the revolutions per minute (RPM) to simulate sudden acceleration. By employing a DC encoder motor to measure the motor's rotational speed through waveform counts, the RPM was calculated. The study recognized sudden acceleration when the brake malfunctioned through the DC encoder motor, causing an abnormal RPM increase, allowing camera capture toward the accelerator and brake during sudden acceleration events. Precautions were taken for problems arising from noise in captured images. The Unix operating system was utilized to apply Gaussian filter image processing techniques for noise removal. While using an average value filter led to abrupt changes by replacing with the average of surrounding signals, resulting in an unsmooth image, a Gaussian filter was used in this study to decrease weights as distance from the center increased, mitigating these issues.</span>

This paper explores using cameras aimed at the accelerator and brake pedals during sudden unintended acceleration in cars, removing noise from captured images to determine driver incompetence. A car model was constructed using Raspberry Pi to simulate brake malfunction using random functions, increasing the revolutions per minute (RPM) to simulate sudden acceleration. By employing a DC encoder motor to measure the motor's rotational speed through waveform counts, the RPM was calculated. The study recognized sudden acceleration when the brake malfunctioned through the DC encoder motor, causing an abnormal RPM increase, allowing camera capture toward the accelerator and brake during sudden acceleration events. Precautions were taken for problems arising from noise in captured images. The Unix operating system was utilized to apply Gaussian filter image processing techniques for noise removal. While using an average value filter led to abrupt changes by replacing with the average of surrounding signals, resulting in an unsmooth image, a Gaussian filter was used in this study to decrease weights as distance from the center increased, mitigating these issues.

Abstract: Cervical cancer is a worldwide public health problem. Cervical cancer begins in the cervical tissues, specifically at the junction where the cervix links the lower part of the uterus that connects to the vagina. Small change in the DNA cell later they might cause the multiply growth of abnormal cell, this growth is called tumours. This are most difficult to diagnose because it starts from the cervix. It starts slowly and it risk if the infection goes long-lasting and it occurs usually people over age 30. This fungus is the type of Human Papilloma Virus (HPV), virus that passed from the one another. In past a small brush or spatula is inserted through the speculum to collect cells from the surface of the cervix. Removing abnormal cells can cause bleeding and kidney failure and microbiologist will get eye pain due to continuous work in microscope. A Pap smear test can be detected and examined in a lab. This risk can be reduced through regular screening tests and by receiving a vaccine to protect against HPV infection. If any cervical cancer found in early stage, then can be removed by the surgery, medicines, chemotherapy and radiation. Majority women are diagnosed between age 35 and 44. More than 15% occur in women over age 65. Approximately 92% of women facing cervical disease are likely to survive for nearly 5 years. Regular screening tests help reduce the occurrence of cervical disease. The output is presented as a confusion matrix. MATLAB's Squeeze Net can be utilized to classify abnormal cells by employing a deep learning model for feature extraction, training, and preprocessing the dataset through SIPaKMed. The model's performance is evaluated through training as well as testing to identify the model that is most appropriate for the given activity. This approach reduces both the time required for outcome and the value of diagnosis. With a comprehensive cervical cancer detection system, the workload of microbiologists can be significantly lessened.

Abstract Synthetic data augmentation holds substantial research and application value in scenarios characterized by limited samples and high dimensions. It enhances the analytical ability and efficiency of spectral analysis models. This paper proposes Autoencoder-Combined Boundary Equilibrium Generative Adversarial Networks (AE-BEGAN) as a new method for augmenting synthetic data in scenarios with limited samples and high dimensions, with a specific emphasis on near-infrared (NIR) spectral data. The spectral data first undergoes preprocessing procedures that encompass advanced noise reduction algorithms and techniques for removing abnormal samples, guaranteeing elimination of unwanted disturbances and outliers. Then, the pre-processed data is utilized to train the AE-BEGAN model, which generates augmented synthetic samples. Finally, real NIR spectral data obtained from lubricant samples exhibiting different water contents were employed to validate and test the performance of the model. The experimental results demonstrate that the AE-BEGAN model outperforms other GANs in generating synthetic data of high quality and diversity, as quantified by two evaluation metrics, α-Precision and β-Recall with scores of approximately 0.86 and 0.28, respectively. The application case study confirms that the AE-BEGAN model exhibits the capability to generate derived NIR spectra and expand the number of spectra in scenarios with limited samples and high dimensions.

Independent component analysis (ICA) has been proven to be a powerful tool for removing artifacts from electroencephalogram (EEG) recordings in the form of blind source separation (BSS). Independent components (ICs) come from undesired sources that are mixed with the useful signal, and the assessment of such ICs allows them to be detected. But the unwanted ICs also can contain some useful information. To overcome this problem, wavelet-enhanced ICA (wICA) can be used, and this method applies a wavelet threshold for each wavelet coefficient to suppress abnormal deformation in each wavelet coefficient. Using the wICA algorithm to suppress artifacts provides an EEG signal with less distortion in the amplitude and in the phase of the cerebral part of the EEG, and the cerebral part of the EEG can be estimated and obtained very similar to control conditions. However, the EEG signals are affected by various artifact components, and those that have the greatest influence are electromyography (EMG) and electrooculography (EOG). These artifacts may appear simultaneously, randomly or interruptedly, so a fixed threshold level is not really appropriate. We proposed a system including wICA integrated with an adaptive filter model, and this combination system can provide the best prediction of the impacts of artifacts to set up a threshold value that is adaptive and suitable. Our experimental results showed that are approach provided better rejection of artifacts than the wICA system.

Feature selection is the process of identifying and removing many irrelevant and redundant features. Irrelevant features, along with redundant features, severely affect the accuracy of the learning machines. In high dimensional space finding clusters of data objects is challenging due to the curse of dimensionality. When the dimensionality increases, data in the irrelevant dimensions may produce much noise. And also, time complexity is the major issues in existing approach. In order to rectify these issues our proposed method made use of efficient feature subset selection in high dimensional data. Here we are considering the input dataset is the high dimensional micro array dataset. Initially, we have to select the optimal features so that our proposed technique employed Modified Social Spider Optimization (MSSO) algorithm. Here the traditional Social Spider Optimization is modified with the help of fruit fly optimization algorithm. Next the selected features are the input for the classifier. Here the classification is performed using Optimized Radial basis Function based neural network (ORBFNN) technique to classify the micro array data as normal or abnormal data. The effectiveness of RBFNN is optimized by means of artificial bee colony algorithm (ABC). Experimental results indicate that the proposed classification framework have outperformed by having better accuracy for five benchmark dataset 93.66%, 97.09%, 98.66%, 98.28% and 98.93% which is minimum value when compared to the existing technique. The proposed method is executed in MATLAB platform.

In this paper, we focus on the medical imaging segmentation techniques which are used in the study of spine diseases. In the medical reports, it is shown that common people worry more about the spine diseases caused by the disc degeneration. Because of the complex composition of the spine, which includes the spine bones, cartilage, fat, water and soft tissue, it is hard to correctly and easily find out the position of each cartilage in the spine images. This above problem always causes over-segmentation or unability to extract the cartilages. Thus, we propose an accurate and automated method to detect the abnormal disc. We combine two standard models with the threshold value to accurately identify the cartilage. Among the processing, we also solve the noising problems of spine image through morphological methods, removing the noncartilage areas using our proposed method, and find out the average height of the cartilages. Therefore, we can easily determine whether the disc is degenerated or not. In the experimental result, the segmentation accuracy of the extracted region by the proposed approach is evaluated by two criterions. The first criterion is statistical evaluation indices of image segmentation. It is evaluated by professional physician's manual segmentation, and the results show that our proposed method is easily implemented and has high accuracy, with the highest rate reaching 99.88%. The second criterion is a comparison evaluation index evaluated by our proposed system and other existence system. From this result, we know that our proposed system is better than other existence system.

In this study, a TEC variation window value was selected based on the wavelet power spectrum method to analyze the seismic–ionospheric coupling relationship. In the full-time domain, a 27-day periodicity of the wavelet power spectrum was obtained that passed the 95% significance test. The sliding interquartile range method was used to analyze earthquakes above Mw6.5 in Japan from 2011 to 2022, excluding the hybrid effects between earthquakes close to one another. The sunspot number (SSN), 10.7 cm radio flux (F10.7), total solar irradiance (TSI), solar wind velocity (Vsw), geomagnetic activity index in the equatorial region (DST), and global geomagnetic activity index (KP) were used as indices representing solar and geomagnetic activity. After removing solar and geomagnetic interference from ionospheric anomaly changes using the sliding interquartile range method, the TEC anomaly changes before the earthquake were verified as being caused by the earthquake and analyzed. The statistical analysis of ionospheric total electron content (TEC) anomalies showed that earthquake magnitude was positively correlated with the amplitude of TEC anomalies but not linearly. The occurrence time of ionospheric anomalies lagged behind to some extent with the increase in earthquake magnitude. Additionally, abnormal changes on the 29th day (15 February 2022) before the 20th earthquake did not conform to previous research rules. According to the lithosphere–atmosphere–ionospheric coupling (LAIC) mechanism and global ionospheric map (GIM) studies, the TEC anomaly was consistent with the vertical projection of the epicenter with obvious regularity. The results show that these TEC anomalies may be related to earthquakes.

This paper considers the current market pace, which requires a corresponding competitive advantage. This study forecasted the cost of heavy machinery depending on geolocation and essential characteristics by the field of activity. This study analyzes specific categories of heavy machinery for important price characteristics. The study classified them by keywords in the text description as essential characteristics. Accordingly, a dataset was formed based on the data obtained. The research objective is to collect and structure data from web resources for the sale of heavy equipment. This paper describes in detail the preliminary data processing. The main stages of preprocessing are presented in detail: detection and processing of missing data, removing anomalous data, coding of categorical data, and scaling. The method of the average value of a specific grouped set was applied to fill in the gaps according to the characteristics and available data. The mode value from the grouped items was used to fill in the gaps. The interquartile range and standard deviation were used to detect anomalies. We used the Kolmogorov–Smirnov, KS_Test, and Lilliefors tests to check the data for normality. In this study, the assessment of abnormal data was applied separately to each set of grouped data with the same parameters. The study built and analyzed models using machine learning methods (linear and polynomial regression, decision trees, random forest, support vector machine, and neural network). Two data encoding methods were used to achieve maximum model accuracy: Label Encoder and One Hot Encoder. The work of each algorithm is considered on the example of the created dataset. In this study, the parameter used for coding was the geolocation of heavy equipment. The study pays additional attention to the specific characteristics of heavy machinery by the sector of the economy. The existing methods and tools for price forecasting, depending on the specific characteristics of the equipment, were analyzed. The practical significance of this work lies in developing an algorithm for predicting the cost of heavy machinery by assessing several parameters.

Background: Cervical intraepithelial neoplasia (CIN) is the potentially premalignant transformation and abnormal growth of surface epithelial cells of the cervix. CIN is a precancerous condition and curable. Loop electrosurgical excision procedure (LEEP) is a simple, outpatient procedure of removing the transformation zone of cervix. The aim of our study was to evaluate the efficacy of large loop electrosurgical excision procedure (LEEP) as a treatment procedure for cervical intraepiethelial neoplasia. Methods: This prospective observational study was conducted at Colposcopy clinic of Bangabandhu Sheikh Mujib Medical University (BSMMU) from June, 2017 to May, 2019. All consecutive patients having colposcopicaly and histopathologicaly proven high grade lesion by colposcopy directed punch biopsy were included in this study. All eligible patients with high grade lesion were underwent LEEP and followed up on 15 days post-procedure, 6 months, 12 months with colposcopy. Results: Sixty (60) cases were undergone LEEP, among them 48 (80%) cases were diagnosed as CIN2 and 12 (20%) cases were CIN3 by colposcopy- directed biopsy. One patient (1.7%) needed hospital admission to controll intra-operative bleeding and in postoperative period 7 (11.7%) patients had mild to moderate post-operative bleeding which was controlled well after application of morsel’s pastes and electro-cautery, one patient (1.7%) had pelvic infection. On 6 months follow-up, in case of CIN2 patients, cure rate was 93.5% (43 of 46) and 1 (2.2%) patient had persistent CIN-2. Patient with persistent CIN2 had re-excision and followed up at 12 month with colposcopy. Among case of CIN-3, the cure rate was 81.8% (9 of 11) and 1 (9.1%) case had CIN2. P-value was 0.244, which was not statistically significant. Overall cure rate on 6 month follow-up was 91.2%. On 12 months follow-up cure rate for CIN2 was 97.8% and for CIN3 was 90.9%. Overall cure rate was 96.5%. P-value was 0.352, which was not statistically significant. Conclusion: Loop electrosurgical excision procedure (LEEP) has a good outcome as a diagnostic and treatment procedure for cervical intraepithelial neoplasia. Bangladesh Medical Res Counc Bull 2023; 49(2): 113-119

Introduction: The role of complement is increasingly recognized in disease pathogenesis, however diagnostic assays are limited by low predictive value, technical requirements, and inability to assess relative contributions of each pathway of complement (classical, alternative, or lectin). The traditional mHam was developed as a functional assay of complement-mediated eukaryotic cell death in atypical hemolytic uremic syndrome (aHUS). However, broader use of the assay has been limited by inter-operator dependence and technical requirements. We have developed a bioluminescent mHam that is robust and easily performed (no cell washes or exogenous reagent addition) and utilizes an autonomously bioluminescent HEK293 cell line to allow for real-time assessment of changes in metabolic health due to complement activation. Given both HEK293 and endothelial cells lack complement receptor 1 (CR1), a crucial regulator of the classical pathway (CP), this assay measures complement activity of greater relevance to disease pathogenesis. Methods: The bioluminescent mHam uses LiveLight (LL) HEK293 cells (490 BioTech) engineered to stably express the bacterial luciferase ( lux) and flavin reductase genes ( luxF) to create autonomous bioluminescence. A PIGA null clone (LL PIGA- HEK293) was created through proaerolysin selection (removing GPI-anchored complement regulators CD55 and CD59). To perform the assay, 40,000 cells were harvested with trypsin/EDTA and plated as triplicates in gelatin veronal buffer (GVB ++,80 µL). Serum (20 µL) was added after specified treatments (heat inactivation or inhibitor addition). Activity was monitored by serial luminescence measurements every 5 min at 37 °C. A relative luminescence of <25% at one hour is designated as positive based upon lowest replicate of any healthy control. Results: The bioluminescent mHam, unlike the original mHam, provides continuous measurement of complement activity (example tracing Figure 1). The complement specificity of the luminescent changes were demonstrated with heat inactivation, terminal complement blockade with eculizumab, and calcium/magnesium dependence. The relative contribution of CP to changes in luminescence was confirmed with the specific CP inhibitor sutimlimab as well as use of pathway specific buffers. Healthy control (HC) samples show a relative luminescence of 53.7% (95%CI 44.0-63.4) with no difference observed in acute thrombotic thrombocytopenic purpura (TTP) (mean 56.2%, 95%CI 41.2-71.2, p=>0.9999). We next utilized samples of aHUS patients known to be in remission, off complement inhibitor therapy. A large proportion of these patients have ongoing assay positivity even in the traditional mHam (9 of 13 in one unpublished cohort). The bioluminescent mHam shows that 5 of 6 aHUS patients in remission have ongoing positivity (mean 17.56%, 95%CI -10.5-45.6, p=0.0131). An acute aHUS sample showed similar results (17.8% after plasmapheresis). Unexpectedly, the relative luminescence is rescued by addition of either C1s or C5 inhibitors, but use of alternative pathway (AP) inhibitors has no significant rescuing effect ( Figure 1-2). Of aHUS patients tested while on complement inhibition, 91% (10/11) show greater than 88% blockade ( Figure 2 aHUS on therapy) . Finally, in one cohort, the traditional mHam was positive in 52% (14/27) of primary antiphospholipid syndrome (PAPS) cases and 15% (10/66) of secondary APS (SAPS) (unpublished data). Thus far, the bioluminescent mHam shows abnormal complement activity in 92% (12/13) of PAPS and 17% (2/12) of patients in SAPS ( Figure 2). Again, complement inhibition with C1s or C5 inhibitors abrogated the effect in a dose dependent manner. Conclusions: The bioluminescent mHam test is an exquisitely sensitive real-time measure of abnormal complement activity. It is easy to perform, more closely approximates the complement regulators on renal endothelium, can be utilized for therapeutic monitoring, and has already offered novel disease insights through the use of specific pathway inhibitors. Although aHUS is traditionally categorized as a disorder of the AP, these results suggest the “trigger” mediating disease pathology is the classical pathway. Also, we show that a large proportion of primary APS patients have abnormal CP activation responsive to C1s and C5 inhibition, suggesting the disease may be responsive to complement-based therapeutics.

BackgroundSystemic sclerosis (SSc) is a systemic autoimmune disease characterized by microvascular damage, dysregulation of innate and adaptive immunity, and fibrosis in many organs[1]. Observational studies have suggested associations between SSc and cardiovascular diseases (CVD)[2]. However, this association is easily disturbed by confusion and reverse causality. In the study, we used Mendelian randomization (MR) to conduct a study on bidirectional causality to examine the relationship between SSc and CVD.ObjectivesThe study aims to evaluate the connection between SSc and CVD, and further to provide comprehensive CVD assessment and treatment for SSc patients.MethodsSummary-level statistical data for SSc were derived from a large meta-analysis of GWAS, including 55,114 cases and 482,295 controls. The summary data for 12 CVD were retrieved from genome-wide association studies (GWAS). In this study, we conducted MR analysis using the random-effects inverse-variance weighted (IVW) method as the primary method. The weighted median approach can yield consistent causal estimates, assessing these genetic variants’ horizontal pleiotropy and heterogeneity using the MR-Egger intercept test and Cochran’s Q test. In addition, we utilized the leave-one-out analysis to detect the robustness and consistency of the results.ResultsAtrial fibrillation(AF) increased the risk of SSc (IVW:OR = 1.428, 95% CI = 1.101-1.854, p = 0.007). Meanwhile, MR-Egger and weighted median pointed toward a similar direction of effect (weighted median: OR = 1.374; 95% CI=0.987-1.912; p = 0.063; MR-Egger: OR = 1.471, 95% CI=0.905-2.391, p=0.140). In the reverse MR, the results of IVW demonstrated that SSc was negatively correlated with the risk of hypertension after removing abnormal single nucleotide polymorphisms(SNPs) (IVW: OR: 0.996,95%CI: 0.993–1.000, p = 0.036). The heterogeneity test showed no significant heterogeneity among selected instrumental variables(IVs) (Q_p value >0.05) except for miocardial infarction(MI)(MR Egger: Q_p value=0.09974) and AF(MR Egger: Q_pval=0.00010; IVE: Q_pval=0.00021). Moreover, no significant evidence of horizontal pleiotropy was observed for IVs. There was no causal genetic relationship between SSc and other CVDs, such as coronary heart disease, heart failure, and pulmonary embolism.ConclusionWe verified that SSc could cause pathological hypertension processes. Furthermore, SSc may be causally impacted by AF. The main mechanism of this causal relationship may be conduction system ischemia and left ventricular systolic failure.References[1]Zhao, M., Wu, J., Wu, H., Sawalha, A. H. & Lu, Q. Clinical Treatment Options in Scleroderma: Recommendations and Comprehensive Review. Clin Rev Allergy Immunol 62, 273-291, doi:10.1007/s12016-020-08831-4 (2022).[2]Ngian, G. S. et al. Prevalence of coronary heart disease and cardiovascular risk factors in a national cross-sectional cohort study of systemic sclerosis. Ann Rheum Dis 71, 1980-1983, doi:10.1136/annrheumdis-2011-201176 (2012).Acknowledgements:NIL.Disclosure of InterestsNone Declared.

Background Abnormal expression of long non-coding RNAs (lncRNA) play a significant role in the incidence and progression of high-grade serous ovarian cancer (HGSOC), which is a leading cause of mortality among gynecologic malignant tumor patients. In this study, our aim is to identify lncRNA-associated competing endogenous RNA (ceRNA ) axes that could define more reliable prognostic parameters of HGSOC, and to investigate the lncRNAs’ potential mechanism of in lymphocyte infiltration. Methods The RNA-seq and miRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database; while for obtaining the differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs), we used edgeR, limma and DESeq2. After validating the RNA, miRNA and gene expressions, using integrated three RNA expression profiles (GSE18520, GSE27651, GSE54388) and miRNA profile (GSE47841) from the Gene Expression Omnibus (GEO) database, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analyses through ClusterProfiler. The prognostic value of these genes was determined with Kaplan–Meier survival analysis and Cox regression analysis. The ceRNA network was constructed using Cytoscape. The correlation between lncRNAs in ceRNA network and immune infiltrating cells was analyzed by using Tumor IMmune Estimation Resource (TIMER), and gene markers of tumor-infiltrating immune cells were identified using Spearman’s correlation after removing the influence of tumor purity. Results A total of 33 DELs (25 upregulated and eight downregulated), 134 DEMs (76 upregulated and 58 downregulated), and 1,612 DEGs (949 upregulated and 663 downregulated) were detected that could be positively correlated with overall survival (OS) of HGSOC. With the 1,612 analyzed genes, we constructed a ceRNA network, which indicated a pre-dominant involvement of the immune-related pathways. Furthermore, our data revealed that LINC00665 influenced the infiltration level of macrophages and dendritic cells (DCs). On the other hand, FTX and LINC00665, which may play their possible roles through the ceRNA axis, demonstrated a potential to inhibit Tregs and prevent T-cell exhaustion. Conclusion We defined several prognostic biomarkers for the incidence and progression of HGSOC and constructed a network for ceRNA axes; among which three were indicated to have a positive correlation with lymphocyte infiltration, namely: FTX-hsa-miR-150-5p-STK11, LINC00665-hsa-miR449b-5p-VAV3 and LINC00665-hsa-miR449b-5p-RRAGD.

The security of the underground mines must be increase because disasters in underground mines are very serious issues now days. The difficulties faced by miners working underground are gas explosion, temperature, etc. If any disaster occurs in mine and if miner gets injured, all the blame directly goes on supervisor. So there must be communication between miners, supervisor and control station. Therefore the purpose of the proposed system is to modify an existing mining safety. Helmet is one of the safety accessories miner should wear while mining. The aim is to make the helmet even safer by adding network. This added network is used to sense the environmental conditions around the miner working underground and all the real time values are wirelessly updated on the internet by using IoT so the control station get to know about the environmental conditions in which miner working and if any abnormal condition occur they are able to provide the rescue as early as possible. The system also includes the LCD and buzzer to let co-workers know if any unwanted event occurs with miner. The proposed system uses different sensors like Gas Sensor, dht11 Sensor, accelerometer, vibration and IR Sensor. Here the IR sensor is used as helmet removing sensor. And also in this system we use machine learning to analysis the employee health, Heart Disease is one among the major diseases affecting the individual around the world. There are several risk factors which leads to heart disease. The combination of logistic regression analysis and neural network provides a novel approach in predicting the heart disease. Initially logistic regression is applied to select the major risk factors for predicting the disease. It produces the significant risk factors that are useful in predicting the heart disease based on statistical p-value. The risk factors which are not having the significant impact are identified and removed. The resultant significant factors are provided as input to the neural network. Keywords: Underground Mines, Mining Safety, IoT (Internet of Things), Helmet Safety, Gas Explosion, Environmental Monitoring, Real-time Monitoring, Communication System, Machine Learning, Logistic Regression, Neural Network, Heart Disease Prediction, Risk Factor Analysis, Gas Sensor, DHT11 Sensor, Accelerometer, Vibration Sensor, IR Sensor, Helmet Removal Detection, Rescue Operation, Control Station, Buzzer Alert, LCD Display, Safety Equipment.

Abstract Polycythemia vera (PV), essential thrombocythemia (ET) and idiopathic myelofibrosis (IMF) can all be associated with the JAK2V617F gain of function mutation. MPDs are also associated with gross cytogenetic anomalies including genomic gain/loss or loss of heterozygosity (LOH) due to mitotic homologous recombination. To determine whether genomic anomalies may be associated with JAK mutation status/disease phenotype we subjected genomic DNA from the granulocytes of 87 patients with PV, ET or IMF to analysis using high resolution Affymetrix 250K Nsp SNP arrays with an average probe spacing of 12Kb. Firstly this analysis precisely mapped previously identified anomalies in MPD patients such as gain of chromosome 1q chromosome 9 (Chr9), chromosome 8, and deletion of 20q and 13q indicating the robustness of the technique. By removing genomic Copy Number Polymorphisms (CNPs) ascertained from 90 normal individuals from the HapMap dataset, we further detected a number of novel alterations such as frequent gain of Chr9p33–34 harboring among other genes, Notch1. MPD patients heterozygous for the JAK V617F mutation exhibited higher genomic instability than JAK2 V617 homozygous or wild type patients. IMF patients had overall more aberrations than PV or ET patients but unsupervised hierarchical clustering of chromosomal anomalies could not distinguish patients with PV, ET or IMF. Whole chromosomal gain or loss was equally frequent among the three diseases, however IMF patients had more frequent alteration of 10Mb or greater when compared to ET or PV (p<0.01) and ET and IMF patients both more frequently exhibited changes ranging from 1–10Mb in size than PV patients (p<0.01). Correlation of gene expression profiles from the granulocytes of 38 MPD patients with copy number profiles from DNA of the patients indicated that gene expression in regions of copy number gain or loss correlated with gene dosages in general. From 2493 genes residing in regions of copy number change region, 259 genes exhibited a positive correlation between copy number and gene expression. By calculating the t–statistics of expression values between samples with and without chromosomal aberrations we further identified 28 genes that showed a change of at least 1.5 fold (p<0.05), 27 of which were located on chromosome 9. Among these were Smarca2, NOTCH1 JAK2 itself. JAK2V617F expression was highly elevated by gain of Chr9 or Chr9p LOH. LOH on chr9p was detected in 16 patients, the majority of whom were confirmed as homozygous for JAK2V617F. To investigate how the over-expression of JAK2V617F might affect the expression of other genes and pathways, gene expression profiles of patients with Chr9 abnormality including Chr9 gain or Chr9p LOH were compared to samples with a normal copy number for Chr9. We identified 493 genes including 210 up-regulated and 283 down-regulated genes by at least 1.5 fold at a p value of 0.05 after multiple-testing correction. As a control gene expression patterns in JAK2-wildtype MPD granulocytes were compared to expression in normal granulocytes. This analysis identified an almost completely different set of genes; 441/493 (89%) of genes differentially expressed in Chr9 abnormal cases versus Chr9 normal cases were not found in the Chr9 normal versus normal control dataset. Up-regulated genes in Chr9 abnormal cases included CD177, CDK5RAP2, BIRC1, STAT5, TLR4 and down-regulated genes include KLRB1, Myc, RUNX3, P53CSV, Pathway analysis of dysregulated genes in Chr9 gain/LOH cases showed that genes involved in p38/MAP kinase, Toll-like receptor and Fc epsilon RI signaling were up-regulated and the genes involved in pathways of protein synthesis/translation and T cell receptor signaling were down-regulated. Collectively these findings suggest that MPD associated with Chr9 gain or 9pLOH and increased expression of JAK2V617F represents a distinct subset of MPD, characterized by less genomic instability than other cases. Furthermore, increased JAK2 and STAT5 expression and activity in these cases may induce distinct downstream pathways and alterations in gene expression.

Objective:Neuropsychological assessment is the cornerstone of concussion management, and the nature of its delivery can vary widely. While literature concerning post-concussion care typically revolves around in-person evaluation, the proliferation of computerized neuropsychological tests (CNTs) has allowed for some distance between concussion patients and the neuropsychologist. In the wake of a global pandemic, several papers describing the use of telehealth for concussion care have emerged; however, the small samples found in these studies may suggest that access to care remains an issue. Additionally, telehealth may not be a sustainable fee-for-service approach as CMS aims to curtail telehealth reimbursement for behavioral health clinicians. The objective of the present study is to describe a remote neuropsychological consultation model of concussion management and evaluate its productivity and impact in a rural setting.Participants and Methods:In this model, a neuropsychologist based at an academic medical center in the northeastern United States consulted to middle school, high school, and collegiate concussion management programs. Students typically were administered baseline ImPACT tests prior to participation in sports, and all students in the current sample completed post-injury ImPACT tests as part of return to play protocols. The neuropsychologist read test results through the test’s online portal, then communicated interpretation and recommendations via email or phone to the school’s representative (e.g., athletic trainer, athletic director, or school nurse). 837 unique concussions were recorded between 2019 and 2022. After removing abnormal cases (e.g., COVID-19 school closures, extended college breaks, non-concussions, and non-return to play decisions), 790 unique concussions (51.4% male) were included for analysis, with a mean age of 16.84 years (SD=2.17). Descriptive statistics were used to characterize the sample.Results:Across 790 unique concussions, 7 were middle school, 571 were high school, and 212 were college students. 1,750 total postinjury ImPACT tests were administered over the three-year period. Per concussion, an average of 2.22 (SD=0.90) tests were used. Average time to the last ImPACT given was 18.47 days (SD=16.59), with a median of 15 days. Ten concussions (1.27% of total concussions) occurred within 3 months of a previous injury. The distance between schools and the medical center ranged from 2.4 to 102 miles (M=60.29; SD=34.34).Conclusions:The current study suggests that there is value in a remote model of neuropsychological consultation for concussion management. While telehealth offers a promising method of evaluation for concussion, it may be inaccessible and present reimbursement challenges. The remote consultation model described here increases access to care by eliminating in-person visits, which decreases demand for physical space at medical centers and increases access to rural populations with seemingly no negative effect on care. This consultation model also allows neuropsychologists working in concussion management more flexibility, potentially increasing the volume of cases they can assess. This program evaluation suggests remote models have merit, but replication studies in different regions of the country are needed.

BACKGROUND: In the age of modern medicine, thanks to the development of small-caliber nephroscope as well as various types of intracorporeal lithotripters, treatment options for renal stones have changed dramatically, and the area of percutaneous nephrolithotomy (PCNL) has expanded. Nowadays, PCNL is not only the first choice in the treatment of stones >2 cm, as well as complicated renal stones (staghorn stones, multiple stones, and stones associated with abnormal renal anatomy), but is also the method of optimal treatment for medium-sized stones not treated with other less invasive methods.
 AIM: The purpose of this study is to assess the efficacy and safety of PCNL as monotherapy in the treatment of renal stones larger than 15 mm.
 MATERIALS AND METHODS: This study presents a retrospectively prospective study of 14 (4 retrospective and 10 prospective) consecutive patients with renal stones larger than 15 mm treated with PCNL in the period from January 2020 to March 2020 at the GH “8 September” – Skopje. Pre-operative preparation of patients included: A history along with physical examination, a complete blood count and radiological examinations to assess the size of the stones, the anatomical features of the kidney and its function, and to accurately plan the operative approach. PCNL was performed in the prone-position; lithotripsy was performed with a double, pneumatic and ultrasonic intracorporeal lithotripter Swiss LithoClast Master with the use of the Karl Storz 24–26 fr nephroscope. Postoperatively, patients were monitored on the 1st, 7th, and 30th post-operative day, determining the demographic and clinical characteristics, the efficacy of PCNL, perioperative blood loss, the duration of the operative procedure, the duration of hospital stay, and the resulting intraoperative and post-operative complications.
 RESULTS: The study included eight men (57.1%) and six women (42.8%). The mean age of the patients was 52.35 ± 11.00. In 5 (35.71%) patients, the stones were localized in the left kidney, and in 9 (64.28%) patients in the right kidney. The average body mass index was 25.11 ± 3.92 kg/m². The average area of the stones was 371.24 ± 131.86 mm². Eleven (78.57%) patients had simplex stones, while 3 (21.42%) had complex stones (staghorn stones and multiple stones). The stones were localized in the renal pelvis, upper, middle, and lower calyx at 5 (35.71%), 2 (14.28%), 4 (28.57%), and 3 (21.42%) patients, respectively. The mean value of pre- and post-operative serum hemoglobin was 13.94 ± 1.00 g/dl and 11.77 ± 1.51 g/dl, respectively. The effectiveness of the procedure on the 1st post-operative day assessed by ultrasound diagnostics and kidney-ureter-bladder X-ray was 78.57%. The success rate on the 30th post-operative day after additional procedures was 92.85%. The average operating time in the entire series was 119.28 ± 9.42 min. The average hospital stay was 5.57 ± 1.11 days. The average operative blood loss was 2.19 ± 0.88 g/dl.
 CONCLUSION: The results of this retrospectively prospective study confirm that PCNL is a minimally invasive, safe, and effective method for removing renal stones. This method, with the development of new technologies, has an increasingly important role in the modern surgical treatment of nephrolithiasis. PCNL can also be performed in the early stages of the learning curve without compromising patient safety and treatment benefits. The procedure is safe and effective, performed even by less experienced urologists if the protocols established for this procedure are followed. This can achieve a rate of success comparable to most established standards without causing major complications.

Children with Down syndrome (DS), caused by constitutive trisomy of chromosome 21, have a 20-fold increased risk of acute lymphoblastic leukemia (DS-ALL) and 500-fold increased risk of acute megakaryoblastic leukemia (DS-AMKL). At least 10-15% of DS neonates are born with the pre-leukemic syndrome transient abnormal myelopoiesis (TAM). Trisomy 21 affects hematopoiesis and leukemia risk; however, the underlying mechanisms are not fully understood. Previous small-scale studies (sample N<30) revealed genome-wide epigenetic effects of trisomy 21. We conducted a comprehensive and multi-ethnic study of neonatal DNA methylation in DS. DNA was extracted from newborn dried bloodspots from 196 children born with DS and 442 non-DS controls from the California Biobank Program, and assayed using Illumina Infinium MethylationEPIC arrays containing >850,000 CpG probes. Data preprocessing was performed using the SeSAMe R package, and the conumee package confirmed trisomy 21 or euploidy in DS and non-DS subjects. Cell type deconvolution was performed, and blood cell proportions compared between DS and non-DS newborns using linear regression adjusting for covariates. ReFACTor principal components (PCs) were used to adjust for cell type heterogeneity and EPISTRUCTURE PCs to adjust for ancestry. Epigenome-wide association studies (EWAS) were performed overall, and stratified by ethnicity, using linear regression models adjusting for sex, plate, first six ReFACTor PCs, and first six ancestry-related PCs. Differentially methylated regions (DMRs) were evaluated using DMRcate and comb-p, with a consensus list of significant DMRs using the overlap. Deconvolution of blood cell proportions revealed highly significant (P<5x10-7) differences across most cell types, with lower B-cells, CD4 T-cells, monocytes, but higher CD8 T-cells and nucleated red blood cells (nRBCs) in DS than in non-DS newborns. Our EWAS of DS revealed 710 CpGs associated at genome-wide significant levels (P<5x10-8). CpGs in the hematopoietic transcription factor RUNX1 on chromosome 21 were highly significantly hypermethylated in DS neonates, including 2 of the top 3 CpG associations (with P<10-20). Significant CpGs were found in additional genes involved in hematopoiesis, including hypermethylation at the promoter of FLI1, which plays a critical role in megakaryopoiesis. Additionally, we identified 847 significant DMRs (containing two or more proximal CpGs with coordinate methylation status), with the top 2 DMRs residing in RUNX1 (DMRcate derived Stouffer-P=8.0x10-92) and FLI1 (P=1.6x10-79). The RUNX1 DMR, containing 16 CpGs, overlaps a super-enhancer in hematopoietic stem cells (HSCs) and demonstrated a profoundly increased mean beta value (+0.30) among DS compared to non-DS subjects. We also found significant enrichment for the overlap of hypermethylated DMRs with super-enhancers genome-wide in HSCs (P<10-20). EWAS and DMR results in ethnicity-stratified analyses were highly correlated between Latinos and non-Latino whites. Intriguingly, PC analysis and hierarchical clustering of DNA methylation data identified a subset of DS subjects (N=34/196, 17%) that clustered separately: these all had significantly higher nRBC proportions than other subjects and possibly represent DS neonates with TAM, although further investigation is needed for confirmation. Removing this cluster did not affect our main findings in our EWAS or DMR analyses. Constitutive trisomy 21 has profound effects on DNA methylation across the genome, in particular resulting in repression of known regulators of hematopoiesis including RUNX1 and FLI1. Our findings highlight potential mechanisms for the increased risk of both lymphoid and myeloid malignancies in children with DS. Disclosures No relevant conflicts of interest to declare.

Abstract INTRODUCTION: Epigenetic changes have proved increasingly important in the genesis of various tumors including acute and chronic lymphoid malignancies.Its basic features do not cause changes in the DNA sequence, but removing selective expression of genes dependent DNA packaging level. The histone methylation is one of the leading and most studied epigenetic events. SETD family of methyltransferases comprises 10 genes encoding proteins with SET domain. SETMAR encodes a protein that contains an N-terminal SET domain and a C-terminal mariner transposase domain. SETMAR-catalyzed methylation of H3K4 and H3K36 may lead to an open chromatin structure, which may facilitate its transposase-dependent processes. SETMAR was associated with carcinogenesis of acute myeloid leukemia by losing disjuntion checkpoint in cells treated with inhibitors of protein topo II. However, the role of SETMAR in CLL leukemogenesis remains unknown. METHODS: In the present study, we evaluated the relative expression of SETMAR between a group of 59 CLL patients and 10 healthy controls by real-time PCR. As normal controls, we used peripheral blood mononuclear cells (PBMC) from 10 age-matched hematological healthy donors (age 50 to 84 years).We analyzed the correlation between SETMAR expression patterns with CLL clinical characteristics such as chromosomal aberrations, ZAP-70 expression and white blood cell (WBC) count. Total RNA was isolated and cDNAs were synthesized. Quantification of SETMAR was performed by Real Time PCR (qPCR) and normalized to endogenous (beta-actin) expression. Results were analyzed by the comparative2-ΔΔCt method. The amount of target gene, normalized to the endogenous control gene and relative to a reference sample, was converted into relative quantification. Based on the continuous distribution of SETMAR expression on CLL samples, we adopted the median value as the cutoff to dichotomize CLL patients in "low" and "high" SETMAR expression. Clinical and laboratory information were then compared between groups. Statistical analysis was performed by GraphPad Prism version 5. The Mann-Whitney U-test was used to examine differences between SETMAR expression (low or high) groups versus platelets, WBC count and ZAP-70 status and also to compare the groups of CLL patients with normal versus abnormal karyotypes. Association of SETMAR expression profile with karyotype was done using Fisher's exact test. RESULTS: The clinical characteristics of CLL patient cohort used in this study is summarized in table 1. Initially, we compared SETMAR gene expression profiles between CLL patients and control samples, using the Mann-Whitney test. SETMAR gene expression was higher in CLL samples (p= 0.00117),with statistical difference (p<0.05) (Fig. 1). Table 1. Clinical and laboratorial characteristics of CLL patients. Characteristics PATIENTS (%) GENDER Male 24(40,7%) Female 35(59,3%) AGE 63 (32-98 years) TUMOR STAGE Binet A 39(66%) Binet B 13(22%) Binet C 7(12%) CYTOGENETIC ANALYSIS 13q deletion 5(8,3%) 17p deletion 4(6,7%) 12tryssomy 16(26,7%) Normal 15(25%) Others 20(33,3%) ZAP-70 expression >20% 39(67,2%) <20% 19(32,8%) CLL patients with lower expression of SETMAR had a higher WBC count and a higher incidence of cytogenetic abnormalities (CTG) (p=0.001) when compared to those with higher expression (p=0.0262) (Fig. 2). However, differential SETMAR expression had no impact on platelets count (p = 0.092), ZAP-70 protein expression (p = 0.25) and tumor stage of Binet (p= 0.38). Figure 2- A) SETMAR relative expression gene and cytogenetic abnormalities, with p=0,001 and B) SETMAR relative expression and WBC counts with p= 0,0262. The cohort of 59 clinical specimens of CLL patients used in the present study revealed quite heterogeneous patterns of SETMAR expression and its association with clinical variables. Future efforts will be necessary to increase the assessment of SETMAR expression in a larger number of CLL patients in order to evaluate its impact on survival, as well as to unveil its correlation with response to established cancer therapy and in the course of the disease. CONCLUSION: We observed that although the expression of SETMAR is elevated in the majority of CLL patients when compared to healthy controls, a lower expression of SETMAR in patients is associated with chromosomal instability and progression of the tumor mass (increased leukocytosis). Figure 2. Figure 2. Figure 3. Figure 3. Disclosures No relevant conflicts of interest to declare.

Abstract Abstract 1411 Von Willebrand Disease (VWD) is a relatively common bleeding disorder characterized by both quantitative and qualitative deficiencies in von Willebrand Factor. The correct diagnosis and classification of VWD is made on the basis of a personal and family bleeding history and the results of a panel of laboratory tests. Evaluations of both VWF antigen level and function are required. Most commonly VWF function is evaluated based on VWF binding to platelets through the platelet surface glycoprotein GPIba in a platelet aggregation assay (VWF:RCo). The VWF:RCo assay requires the use of the antibiotic ristocetin to induce a conformational change in VWF which allows VWF to bind to GPIba on the surface of fresh or fixed platelets in the absence of VWF denaturation. When evaluating 172 normal controls, Flood et. al. (Blood, 2010) elegantly demonstrated that 63% of African-American controls and 17% of Caucasian controls had a single nucleotide polymorphism, D1472H, which altered the ability of these individuals to bind ristocetin and resulted in abnormal VWF:RCo results in the absence of any bleeding abnormalities. GTI Diagnostics, Inc. (Waukesha, Wisconsin) has developed a ristocetin-independent fluorescent ELISA for the quantitative measurement of VWF activity in plasma, specifically VWF binding to immobilized GPIba. This VWF activity ELISA, referred to as the GTI IbCo Assay, uses microwells coated with recombinant GPIba containing two “gain-of-function” mutations. The mutant GPIba is capable of spontaneous binding to VWF in the absence of ristocetin or VWF denaturation (Flood et. al, Blood, 2010). A brief description of the assay follows. In the absence of ristocetin, calibrators, controls, and samples are added to the microwells and VWF binding to GPIba is allowed to take place. Unbound material is washed from the wells and a biotinylated anti-VWF detection antibody is added to the wells. The microwells are washed to remove any unbound detection antibody. A streptavidin-labeled horseradish peroxidase conjugate is added to the microwells and incubated. After a final wash step, a fluorescent peroxidase substrate is added to the wells. The reaction is quenched after 30 minutes and the fluorescence is read using an excitation wavelength between 315 and 340 nm and an emission wavelength between 370 and 470 nm. The reportable result (U/dL) of VWF binding to GPIba is determined from the standard curve. All assay incubation steps are 30 minutes and conducted at room temperature, therefore the assay can be completed in < 3 hours. A small scale method comparison study was conducted on 11 plasma samples purchased from George King Bio-Medical, Inc. The plasma samples are Factor Assay ConTrol (FACT) samples and extensively characterized by George King Bio-Medical, Inc for 25 different coagulation parameters including VWF:RCo using a Chrono-Log platelet aggregometer and Helena Laboratories lyophilized platelets. The 11 samples were tested in the GTI IbCo Assay and the results obtained were compared to those obtained with the comparative method, in this case the VWF:RCo values provided by the supplier. For standardization of the GTI IbCo Assay, a IbCo value of 100 U/dL was assigned to the ISTH Secondary Coagulation Standard Lot #3. As illustrated in the table below, the samples tested included samples with varying levels VWF:RCo activity. When the results were compared, there was good correlation and agreement between the two methods. Larger method comparison studies will be conducted. Based on this limited data set the GTI IbCo Assay demonstrated good correlation and agreement with the “gold standard” Ristocetin Cofactor Assay by platelet aggregation. The GTI IbCo Assay is able to measure the functional activity of VWF, specifically in regards to VWF binding to GPIba in the absence of ristocetin in a simple ELISA format. The GTI IbCo Assay removes the need for fresh or lyophilized platelets from the traditional assay and also eliminates the ristocetin dependence from the VWF activity measurement. By removing any dependence on ristocetin to induce the VWF to GPIba interaction we have also removed any possible assay discrepancies based on a patient's inability to interact with ristocetin. Disclosures: Stapleton: GTI Diagnostics: Employment. Bub:GTI Diagnostics: Employment. Chance:GTI Diagnostics, Inc: Employment.

This study aimed to improve the daytime fog detection algorithm GK2A_HR_FDA using the GEO-KOMPSAT-2A (GK2A) satellite by increasing the resolution (2 km to 500 m), improving predicted surface temperature by the numerical model, and optimizing some threshold values. GK2A_HR_FDA uses numerical model prediction temperature to distinguish between fog and low clouds and evaluates the fog detection level using ground observation visibility data. To correct the errors of the numerical model prediction temperature, a dynamic bias correction (DBC) technique was developed that reflects the geographic location, time, and altitude in real time. As the numerical model prediction temperature was significantly improved after DBC application, the fog detection level improved (FAR: −0.02–−0.06; bias: −0.07–−0.23) regardless of the training and validation cases and validation method. In most cases, the fog detection level was improved due to DBC and threshold adjustment. Still, the detection level was abnormally low in some cases due to background reflectance problems caused by cloud shadow effects and navigation errors. As a result of removing navigation errors and cloud shadow effects, the fog detection level was greatly improved. Therefore, it is necessary to improve navigation accuracy and develop removal techniques for cloud shadows to improve fog detection levels.

Endometrial cancer begins in the layer of cells that form the lining (endometrium) of the uterus. Endometrial cancer is often detected at an early stage because it frequently produces abnormal vaginal bleeding, which prompts women to see their doctors. If endometrial cancer is discovered early, removing the uterus surgically often cures endometrial cancer. The study included all patients who had been evaluated for vaginal bleeding in Obstetrics and Gynecology Department of Clinical Emergency County Hospital, Timisoara between 2016-2018. Of the 195 cases of uterus scraping, 19 cases were labelled as malignant endometrial pathology. For the statistical analysis we calculated some descriptive statistics for the age parameter and the BMI (body mass index) parameter in our disease sample and we compared the BMI values to the BMI values from the control sample As well, we tested to see if there is an association between the Ki-67 values and the HER-2 / neu status in patients with or without endometrial carcinoma. In order to test the significance we applied a Mann -Whitney test, for a = 0.05 set as a confidence level. Unfortunately, in the case of our study group, type 1 endometrial cancers are found in only 5 cases, unlike other countries where most of endometrial cancers are diagnosed early (80% in the first stage) and the 5-year survival rate is about 95%. In any case, the 5-year survival rate is much lower if there is involvement of regional lymph nodes or distant metastasis (68% and 17%, respectively) - as in our case where all cases were classified as Stage III and IV. By running the statistical test we obtained extremely significant differences in the BMI of our patients (p[0.001), the diseased patients tend to have higher BMI values. As well, when we tested the possible association between the Ki-67 values and the HER-2 / neu status in our two groups (patients with or without endometrial carcinoma) we obtained extremely significant differences (p[0.001). The Ki-67 values are increasing proportionally with the carcinoma staging. An endometrial biopsy is the most commonly used test for endometrial cancer and is very accurate in postmenopausal women.

Abstract Abstract 4062 Poster Board III-997 Background Over 70% of deaths in regularly transfused patients with β-thalassemia major (TM) are related to iron-induced cardiomyopathy. Deferasirox (Exjade®), in a sub-study of the 1-year multicenter prospective EPIC trial, demonstrated efficacy in reducing myocardial iron in TM patients with mild, moderate and severe cardiac siderosis, as evidenced by a statistically significant improvement in myocardial T2*. We herein report the extension phase results from the same study in patients who have received up to 2 years of deferasirox therapy. Methods Patients aged ≥10 years with myocardial T2* >5–<20 ms (indicating cardiac siderosis) by cardiovascular magnetic resonance (CMR), left ventricular ejection fraction (LVEF) ≥56%, serum ferritin >2500 ng/mL, MR (R2) LIC >10 mg Fe/g dry weight (dw), and a lifetime minimum of 50 transfused blood units were included in the cardiac sub-study. Deferasirox was initiated at 30 mg/kg/day and increased to 40 mg/kg/day by the time patients had entered the 1-year extension. Dose decreases were allowed for safety reasons. The primary endpoint was change in myocardial T2* from baseline to 2 years. Results Out of 100 patients who entered the 1-year extension phase, 85 completed (85%); 24-month CMR data are available for 81 patients. Mean age was 20.6 ±7.3 years. Baseline cardiac T2* was <10 ms (severe cardiac siderosis) in 39 patients (39%) and 10–20 ms (mild-to-moderate cardiac siderosis) in 61 (61%). 67.0% had received prior deferoxamine (DFO) and 33.0% prior DFO/deferiprone combination therapy. Mean actual deferasirox dose increased from 33.1 ±3.7 mg/kg/day in the core 1-year phase to 36.1 ±7.4 mg/kg/day during the extension. Continued improvement in myocardial T2* was observed in the extension phase so that after 2 years of deferasirox treatment, T2* had significantly increased from a baseline geometric mean of 11.2 to 15.3 ms (P<0.001). Significant increases from 7.3 to 9.3 ms (P<0.001) and from 14.6 to 19.9 ms (P<0.001) were respectively noted in patients with baseline T2* <10 and 10–20 ms (Figure). LVEF remained stable in both subgroups throughout the 2-year follow up period. Both mean LIC and median serum ferritin were significantly reduced from baseline by 10.7 ± 12.8 mg Fe/g dw and 2343 ng/mL (range –12795 to 25127), respectively (P<0.001; based on last-observation-carried-forward analysis). Reasons for discontinuation were: unsatisfactory therapeutic effect (n=8), consent withdrawal (n=3), protocol violation (n=2), lost to follow up (n=1) and abnormal laboratory value (increased urinary protein/creatinine ratio) leading to consent withdrawal (n=1); no deaths were reported. Incidence of investigator-assessed drug-related AEs (≥5%) decreased overall from the core phase to the extension: increased blood creatinine (n=21 [21.0%] vs n=18 [18.0%]), rash (n=15 [15.0%] vs n=0), increased alanine aminotransferase (ALT) (n=6 [6.0%] vs n=4 [4.0%]) and increased aspartate aminotransferase (n=4 [4.0%] vs n=3 [3.0%]). There were no drug-related serious AEs over 2 years. In total, 4 patients (4.0%) had increased serum creatinine >33% above baseline and the upper limit of normal (ULN) on two consecutive visits; 3 patients (3.0%) during the core and 1 (1.0%) during the extension. 4 (4.0%) patients had increased ALT >10xULN on two consecutive visits; 2 patients (2.0%) during the core and 2 (2.0%) during the extension; levels were already >ULN at baseline in these patients. Conclusions This is the first large prospective study to report 2-year data on cardiac iron removal for any iron chelator. Results show that continued therapy with deferasirox for up to 2 years at doses 30–40 mg/kg/day was effective in removing iron from the heart in TM patients with mild, moderate and severe cardiac siderosis. Myocardial T2* continued to improve in year 2 and the statistically significant improvement from baseline was associated with maintenance of normal cardiac function and a concomitant decrease in hepatic and total body iron burden. Overall, deferasirox was well tolerated. Disclosures: Pennell: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Apopharma: Consultancy, Honoraria; Cardiovascular Imaging Solutions: Equity Ownership; Siemens: Research Funding. Off Label Use: THE SPECIFIC USE OF CHELATION FOR CARDIAC SIDEROSIS IS OFF-LABEL. Porter:Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Vifor International: Membership on an entity's Board of Directors or advisory committees. Cappellini:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genzyme: Membership on an entity's Board of Directors or advisory committees. Chan:Novartis: Honoraria, Research Funding. Aydinok:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Ibrahim:Novartis: Research Funding. Li:Novartis: Consultancy, Speakers Bureau. Viprakasit:Thai Government : Employment; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Government Pharmaceutical Organization of Thailand: Honoraria, Research Funding. Kattamis:Novartis: Consultancy, Honoraria, Speakers Bureau. Smith:Novartis Pharma AG: Consultancy, Employment at Royal Brompton Hospital funded by Novartis Pharma AG. Habr:Novartis Pharmaceuticals: Employment. Domokos:Novartis Pharma AG: Employment. Roubert:Novartis Pharma AG: Employment. Taher:Novartis: Honoraria, Research Funding.

Abstract. The photosynthetic performance of marine phytoplankton varies in response to a variety of factors, environmental and taxonomic. One of the aims of the MArine primary Production: model Parameters from Space (MAPPS) project of the European Space Agency is to assemble a global database of photosynthesis–irradiance (P-E) parameters from a range of oceanographic regimes as an aid to examining the basin-scale variability in the photophysiological response of marine phytoplankton and to use this information to improve the assignment of P-E parameters in the estimation of global marine primary production using satellite data. The MAPPS P-E database, which consists of over 5000 P-E experiments, provides information on the spatio-temporal variability in the two P-E parameters (the assimilation number, PmB, and the initial slope, αB, where the superscripts B indicate normalisation to concentration of chlorophyll) that are fundamental inputs for models (satellite-based and otherwise) of marine primary production that use chlorophyll as the state variable. Quality-control measures consisted of removing samples with abnormally high parameter values and flags were added to denote whether the spectral quality of the incubator lamp was used to calculate a broad-band value of αB. The MAPPS database provides a photophysiological data set that is unprecedented in number of observations and in spatial coverage. The database will be useful to a variety of research communities, including marine ecologists, biogeochemical modellers, remote-sensing scientists and algal physiologists. The compiled data are available at https://doi.org/10.1594/PANGAEA.874087 (Bouman et al., 2017).

Aims: To give researches on gastric interdigestive pressure activity, including gastrointestinal (GI) physiological motility recording method, data processing and analysis method, as well as to give reasonable interpretation on how to generate such gastric pressure activity. Study design: Basic application study. Place and Duration of Study: School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology (USST), between June 2010 and October 2011. Methodology: We introduced a telemetric method to get the gastric physiological pressure activity inside the GI tract and the general process for processing such gastric Migrating Motor Complex (MMC) pressure activity including the process of abnormal value removing, medians of five-three-Hanning (53H) weighted average smoothing, and the fluctuation frequency estimation. Results: Using the process of abnormal value removing, medians of five-three-Hanning (53H) weighted average smoothing, and the fluctuation frequency estimation, we well obtained gastric interdigestive pressure activity (MMC). Conclusion: The methods introduced in the paper including abnormal value removing, the 53H weighted average smoothing, and the fluctuation frequency estimation were helpful for researches on gastric interdigestive pressure activity.

Arctic sea ice is a key factor in high–latitude air–sea–ocean interactions. In recent decades, its extent has been decreasing in all seasons with large interannual variability, especially for the Northwind Ridge. After removing the trend in the changes during July 1979 to 2020, 2019 had an abnormally low value, while the following year, 2020, had an abnormally high value. The underlying processes driving this variability in July near the southern Northwind Ridge, which is one of the areas with the most drastic changes in Arctic, are not well understood. There, we demonstrated that the shortwave radiation anomaly in July is the direct reason for the sea ice anomaly in July 2019 and July 2020. Importantly, the total energy surplus in the spring of 2019 (enough to melt ∼18 cm of sea ice) and 2020 (potentially melting ∼11 cm of sea ice) indirectly influenced the sea ice. The abnormal change in moisture and its convergence mainly caused by atmospheric circulation were the main reasons for the longwave radiation and latent flux anomalies. Cloud water mainly affected shortwave radiation, including the positive net shortwave radiation anomaly in May 2019.

DAU (Daily Active User) is the number of daily active users, often used to reflect the operation of websites, Internet APPs and games [1]. DAU usually counts the number of users who have logged in or used a product (removing users who are repeatedly logged in) within one day (statistical day), which is similar to the concept of visitors (UV) in the traffic statistics tool. As we all know, the revenue source of some Internet applications lies in the revenue of advertising, and the amount of advertising revenue depends on the size of DAU. Therefore, the design strategy and algorithm to monitor the fluctuations of DAU can better help people analyze and improve our products, thus bringing improvements to the products. Therefore, this paper will design a variety of algorithm construction models to monitor the fluctuation of DAU, and achieve alarm announcement, analysis and location of the abnormal fluctuation of DAU, so as to explore of the value of DAU.

Abstract Battery health monitoring is influenced by environmental and human factors, resulting in the presence of abnormal and missing values in the detection data. These issues compromise the accuracy of subsequent life prediction and fault diagnosis. To address this problem, we propose a deep learning-based method for cleaning battery anomalies and imputing missing data. Initially, we optimize the Variational Modal Decomposition method using the Osprey Optimization Algorithm to minimize the influence of continuous discharge processes on local anomaly detection. This process allows us to obtain the trend of the time series, and subsequently, we determine the anomalies by using the interquartile range after removing the trend components. The identified anomalies are then converted into missing values for further processing. Next, we fill in these missing values by constructing a Generative Adversarial Network. The generator structure of the network combines the attention mechanism with the Gated Recurrent Unit. We validate our approach using a real vehicle dataset and subsequently perform prediction on the cleaned dataset. Our results demonstrate that the subsequent prediction model improves the RMSE value by approximately 35% and the MAPE value by roughly 42%. Thus, our method effectively enhances the quality of the original data.

Abnormal pigmentation in cutaneous wound healing has become a major cosmetic issue in the current society. Rising popularity of green labeled cosmetics which are environmentally sustainable with minimum side effects have greater demand in the world cosmetic market. Standardization of herbal formula is essential in order to assess the quality of drugs. Hence, the research study was designed to standardize the selected herbs based on comprehensive literary study on selected Varnaya Dravya (complexion promoting herbs) mentioned in Ayurveda authentic texts and Sri Lankan traditional manuscripts comprising of Terminalia chebula Retz, Terminalia belerica (Gaertn). Roxb, Phyllanthus emblica Linn, Rubia cordifolia Linn, Curcuma longa Trim, and Sesamum indicum Linn. Authentication of herbal ingreedients has been carried out at Bandaranayaka Memorial Ayurveda Research Institute, Nawinna, Sri Lanka. Microscopic identification, Moisture content, pH value, Total ash content and Colouring matter were tested determind through paper chromatography under WHO (2011) guidelines. Microscopic identification revealed that the poly herbal cosmetic formula in powder form contains yellow colour cells, stone cells, group of elongated stone cells, transparent cells, pitted vessels, spiral vessels, vessels filled with red, small fibers, oil globules, starch granules, needle shape crystals, hair and Trichoid. Moreover, moisture content of the formula was 6.3%, pH - 5.92 and total ash value - 4.45%. Determination of colouring matter indicated formula does not contain synthetic dyes. In addition, secondary plant metabolites like phenolic, tannins and saponins were present. Pharmacodynamics potential of the formula showed 25% kashaya (astringent) and tiktta (bitter) rasa (taste) accordingly. Further, 46% and 27% of formula showed ruksha (dryness) and laghu (lightness) guna (properties) along with 83% and 67% indicated ushna virya.
 (hot in potency) and madura (sweet) vipaka respectively. Due to presence of secondary metabolites, the poly herbal formula has anti-bacterial, anti-fungal and anti-oxidant potentials which will be favorable for skin complexion protection from bacteria and fungi. Moreover, Lekhana action gives scraping effect which is important for removing the scar.
 The study suggested that parameters found to be sufficient to evaluate the herbal cosmetic powder and could be used as reference standards and applicability of this formulae should be validated with a preclinical and clinical trials.

Abstract Background Cerebrospinal fluid (CSF) circulation is essential in removing metabolic wastes from the brain and is an integral component of the glymphatic system. Abnormal CSF circulation is implicated in neurodegenerative diseases. Low b-value magnetic resonance imaging quantifies the variance of CSF motion, or pseudodiffusivity. However, few studies have investigated the relationship between the spatial patterns of CSF pseudodiffusivity and cognition. Methods We introduced a novel technique, CSF-based spatial statistics (CBSS), to automatically quantify CSF pseudodiffusivity in each sulcus, cistern and ventricle. Using cortical regions as landmarks, we segmented each CSF region. We retrospectively analyzed a cohort of 93 participants with varying degrees of cognitive impairment. Results We identified two groups of CSF regions whose pseudodiffusivity profiles were correlated with each other: one group displaying higher pseudodiffusivity and near large arteries and the other group displaying lower pseudodiffusivity and away from the large arteries. The pseudodiffusivity in the third ventricle positively correlated with short-term memory (standardized slope of linear regression = 0.38, adjusted p < 0.001) and long-term memory (slope = 0.37, adjusted p = 0.005). Fine mapping along the ventricles revealed that the pseudodiffusivity in the region closest to the start of the third ventricle demonstrated the highest correlation with cognitive performance. Conclusions CBSS enabled quantitative spatial analysis of CSF pseudodiffusivity and suggested the third ventricle pseudodiffusivity as a potential biomarker of cognitive impairment.

Abstract Background Late-onset Pompe disease (LOPD) is an autosomal recessive lysosomal storage disorder that results in severe progressive proximal muscle weakness. Over time, reductions in muscle strength result in respiratory failure and a loss of ambulation. Delayed diagnosis of LOPD deprives patients of treatments that can enhance quality of life and potentially slow disease progression. The objective of this study is to determine if patients with a nonspecific diagnosis, such as muscle weakness, may be at risk for LOPD using retrospective chart review of patients seen at two centers: an academic center and a community health system. Results Initial data pulls identified 80,070 patients with one of the ICD-10 codes of interest. Chart review found 551 of these patients also had at least one lab value commonly abnormal in individuals with LOPD and of these 110 scored as “at-risk”. After removing phenocopies/other confirmed unrelated diagnoses, 46 individuals were contacted either directly or through their healthcare provider for genetic counseling. Three patients had pretest genetic counseling and were tested for decreased levels of acid-α-glucosidase. One patient was found to have deficient acid-α-glucosidase. Additionally, a physician educated through the program ordered LOPD testing for their patient and diagnosed them with LOPD. Conclusion This study confirms that a symptom-based scoring tool and chart review combined with provider education can identify patients who are at increased likelihood to have a missed LOPD diagnosis.

The hydrocarbon industry in Colombia is one of the principal pillars for the Colombian economy, representing around 5% of its gross domestic product. Since petroleum reserves have decreased, gas becomes one main alternative for economical growth. However, current gas pipelines have been in service for over 30 years and some of them are buried and phenomena, such as metal losses, corrosion, mechanical stress, strikes by excavation machinery, and another type of damages, are presented. The maintenance program of these structures is typically corrective type and is very expensive. To overcome this situation, the native research institute “Research Institute of Corrosion—Corporación para la Investigación de la Corrosión” recently developed an in-line inspection tool to be operated in Colombian gas pipelines to get valuable information of their current state along thousands of kilometers. A huge quantity of data is recorded (including tool movement, magnet, magnetic flow leakage, and caliper signals), which demand a high-computational cost and an adequate tool analysis to establish the current pipeline structural health condition. In this sense, authors have shown in several works that principal component analysis is an effective tool to detect and locate abnormal operational structural conditions from multidimensional data. In a previous analysis, multidimensional data were used to locate possible damages along the pipeline. However, most of the activated points belonged to weld points. Then, in this article, it is proposed to use the root mean square value of magnetic flux leakage signals to separate these points and to obtain sets of signals by sections removing the welds, and then multiway principal component analysis is applied for each set of signals of each gas pipeline section. The maximum values of damage indices ( Q and [Formula: see text]-statistics) of each section are conserved to activate the sections of the gas pipeline with more probability of damages and then, they must be evaluated by experts.

To assess the relative toxicity of a mixed series of 21(linear and branched-chain) alcohols and 9 normal aliphatic amines in terms of the 50% inhibitory growth concentration (IGC50) of Tetrahymena Pyriformis, a Quantitative Modeling study know as a Structure-Activity/property/Toxicity Relationship (QSAR/QSPR/QSTR) was conducted (20 training,10 tests). The used least squares LS method has been using MINITAB 16 Software and nom-parametric estimation (least absolute deviation LAD) (robust regression method) has been using Calculation Programs by MATLAB Software. The applied simple linear regression approach is based on theoretical H4p (GETAWAY descriptor) molecular descriptor from DRAGON software The performance of regression is better if the distribution of errors has normal, in this case we use the least squares LS method for statistical analysis. When the data does not have a natural assumption, we move to another method of analysis that is more robust and more frequent for the presence of the points of articulation, which is the least absolut deviation method (LAD). The findings of statistical analysis for the chosen model (QSAR) using simple linear Regression using the least Squares Method were R^2=97.39% ,Q^2=96.69% ,Q_bOOT^2=96.24%,Q_EXT^2=93.91% ,R_adj^2=97.24%, S=0.248 Anderson Darling (AD) test =1.57 >0.752 , symmetry coefficient (ou skeweness) (sk= 2.14>0 ) , flatness coefficient (Kurtosis) (ku=5.75>3) and Jarque and Bera Test (JB= 42.84>5.9942. the results did not follow the normal law (unnormal). The coefficient of determination and the value of standard deviation are both highly sensitive to the presence of aberrant compounds(abnormales), as the R^2value moved from 87, 96 % to 94.18 %, which increased by a value of 6.22% and the value of standard deviation (S) moved from 0.399 to 0.303, it increased by a value of 25 % after removing aberrant compound (abnormalie) are interpreted as better adjustment and they are positively. After removing the aberrant compound, we did not see any change in the lines coefficients, indicatting that the function’s graph is stable, demonstrating the LAD method and increased power, which are unaffected by the presence of aberrant compounds Consequently, which means that the model of one descriptor selected is good and statistically strong, Three influential compounds detected ((one compound of training, two compounds of Test) and important the model and absence of studied sample aberrants compounds.

Paeoniae radix Rubra is a traditional Chinese herbal medicine, which has the effect of clearing heat and cooling blood, activating blood and removing stasis. It has become popular in the Chinese market in recent years due to its extremely high medicinal value and showy flower color. In May 2021, typical symptoms of root rot were observed in a field (35°7′12″ N, 103°58′48″ E) in Dingxi, Gansu province, China. Approximately 10% of the plants in the field had typical root rot symptoms, and the root of each affected plant is at least 5% severe. The roots of the naturally infected plants in the field discolored and decayed with black brown spots on the surface of the root bark, the root bark detached from the phloem，and some leaves were chlorosis, shrunken and smaller, and the branches were dead and underdeveloped. In the transverse section, the xylem was black diffusion and abnormal odor. Three diseased plants with typical symptoms were chosen at random and brought back to the lab. Small pieces cut from the margins of lesions were surface disinfested with 75% ethanol for 15 s, and 0.5% NaClO solution for 30 s, rinsed three times in sterile distilled water, dried on sterile filter paper, plaed onto potato dextrose agar (PDA), and incubated at 25 ± 1℃ for 7 days in the dark. The pure cultures were obtained by single-spore isolation. All isolates produced wavy on the surface, radial from the inside out, initially white or milky white to orange colonies with abundant black brown oily conidiomata pycnidia on PDA at 25 ± 1℃ after 15 days in the dark. The conidiomata pycnidia is spherical to irregularly spherical, 231.5 to 512.4 μm, initially transparent with age turning brown, with a dark brown internal conidial mass inside, and with a 13.1 to 45.4 μ m wide ostiole central. Young conidia (n=100) developed from conidiogenous cells, which were simple, tapering, hyaline, smooth, and 12.3 to 18.0 × 2.5 to 4.6 μm, 1.0 to 1.5 µm wide at apex. Mature conidia (n=100) were ellipsoid, apices tapering, subobtusely rounded, brown, and 6.5 to 11.0 × 4.1 to 7.5 µm. The morphological characteristics of the isolates were consistent with previous descriptions of the genus Coniella (Crous et al., 2014). A representation isolate CS-1 was deposited in the Institute of Plant Protection, Gansu Academy of Agricultural Sciences and used for further studies. To confirm the identity of the causal fungus, the internal transcribed spacer (ITS), 28S large subunit of nuclear ribosomal RNA (LSU) and partial translation elongation factor 1-alpha (TEF1-α) gene of the representative isolate CS-1 were amplified and sequenced using primers ITS1/ITS4 (White et al., 1990), LROR/LR7 (Chethan et al., 2017) and EF1-728F/EF1-986R (Carbone and Kohn, 1999), respectively, and deposited on GenBank with accession numbers OP824764 (ITS), OP824767 (LSU)/span>and OP903926 (TEF1-α). Blastn analysis of all sequences resulted in E-value of 0.0 (ITS and LSU) and nearly 0.0 (TEF1-α), with Query cover values of 90% to 99% identity with C. fragariae, confirming the hypothesis based on morphological features examination. To conduct a pathogenicity test, three root segments of healthy plants were wounded using sterilized needles and inoculated by pipetting 10 μL of conidial suspension (1×107 conidia/mL) onto each wound, and controls were inoculated with 10 μL sterile distilled water. These root segments were kept in a moist chamber at 25°C in the dark. The experiment was repeated three times. After 14 days, root rot symptoms were observed on all of the inoculated root segments and identical to those observed in the field, whereas control root segments did not develop symptoms. The pathogen was re-isolated from the lesions of inoculated root segments, fulfilling Koch’s postulates. To the best of our knowledge, this is the first report of C. fragariae causing root rot on P. radix Rubra in China. This identification can aid in the selection of appropriate management measures for this disease.

ABSTRACTTrichobezoars are conglomerations of undigested foreign materials within the gastrointestinal tract (GIT). They are most commonly observed in young girls. Trichobezoars typically lodge in the stomach, but can extend further into the intestines in a condition called Rapunzel syndrome. The current patient, a young girl, complained of abdominal pain accompanied by diarrhea. She also had a history of bile vomiting 1 month prior and an abnormal craving for mud (PICA). Trichobezoars are often linked to hair‐pulling disorders or other mental health conditions, and symptoms can be vague for years before progressing to nausea, vomiting, weight loss, and even iron deficiency anemia. Treatment involves removing the hairball and addressing any underlying psychological issues. In the current case, we aimed to elucidate the diagnosis, management, and unique features of gastrointestinal tract trichobezoars, which are uncommon causes of gastrointestinal distress and iron deficiency anemia (IDA).

Addiction is an issue that has existed for some time but with the rise of new technologies, not only was valued the concept of dependency inherent in the pathological bond that develops between a subject and substance, new forms have emerged much more aggressive devious and dangerously addictive behaviors related to recurrence of circular and harmful to humans. The key to the problem is offered by the constant pursuit of pleasure which satisfaction and psychological well-being, hedonistic concept has always sought by humans. The transition from "normal" to "abnormal" is relative to the times, more and more short, in which the subject tends to reach a positive value, such as that of being, behaving this flattening imagination to reality and removing its true value. This article will focus precisely on the new forms of behavioral addiction, or the New Addiction. Among these will be discussed also a dependence little known in Italy but very developed in America: the Vigorexia (or addiction to sports), which can lead to the assumption of doping substances. Vigorexia doping and traveling on the same track and take pathological forms because it is closely related to the need to need welfare linked to the use of substances harmful to the body and recurrence of harmful behaviors. Will address the issue of doping in many sports fields, to hear the case Pantani. With the epilogue, we will try to propose a thesis useful in a possible liberation from these circular needs, through the implementation of an inner path directed to the use of the resources that nature offers us spontaneously: endorphins.
 Riassunto
 La dipendenza è un tema che esiste ormai da diverso tempo ma con l’aumento delle nuove tecnologie, non solo è stato valorizzato il concetto di dipendenza inerente il legame patologico che si instaura tra un soggetto e la sostanza, sono emerse nuove forme molto più aggressive e subdole di dipendenza pericolosamente connesse alla reiterazione di comportamenti circolari e deleteri per l’essere umano. La chiave di accesso alla problematica è offerta dalla costante ricerca del piacere quale soddisfazione del benessere psico-fisico, concetto edonistico da sempre ricercato dall’essere umano. Il passaggio dal “normale” al “patologico” è relativo ai tempi, sempre più brevi, in cui il soggetto tende a raggiungere un valore positivo, quale quello del benessere, comportando questo un appiattimento sull’immaginazione e togliendo alla realtà il suo vero valore. Il presente articolo vuole focalizzare l’attenzione proprio sulle nuove forme di dipendenza comportamentale, ovvero le New Addiction. Tra queste verrà discussa anche una dipendenza poco conosciuta in Italia ma molto sviluppata in America: la vigoressia (o dipendenza da sport), che può portare all’assunzione di sostanze dopanti. Vigoressia e doping viaggiano sullo stesso binario e assumono forme patologiche perché strettamente connesse al necessario bisogno di benessere legato all’uso di sostanze dannose per l’organismo e alla reiterazione di comportamenti nocivi. Verrà affrontato il problema del doping in numerosi ambiti sportivi, fino a trattare il caso Pantani. Con l’epilogo si tenterà di proporre una tesi utile a un possibile affrancamento da tali bisogni circolari, mediante la realizzazione di un percorso interiore diretto all’utilizzo delle risorse che la natura ci offre spontaneamente: le endorfine.
 
 Resumen La adicción es un problema que existe desde hace algún tiempo, pero con el surgimiento de las nuevas tecnologías, no solo se valoró el concepto de dependencia inherente al vínculo patológico que se desarrolla entre un sujeto y una sustancia, han surgido nuevas formas mucho más agresivas, tortuosas y peligrosamente adictivas. comportamientos relacionados con la recurrencia de circulares y perjudiciales para los humanos. La clave del problema la ofrece la búsqueda constante del placer que la satisfacción y el bienestar psicológico y el concepto hedonista siempre han buscado los humanos. La transición de "normal" a "anormal" es relativa a los tiempos, cada vez más cortos, en los que el sujeto tiende a alcanzar un valor positivo, como el de ser, comportando esta imaginación aplanada a la realidad y eliminando su verdadero valor. Este artículo se centrará precisamente en las nuevas formas de adicción conductual, o la Nueva Adicción. Entre estos se discutirá también una dependencia poco conocida en Italia, pero muy desarrollada en América: la Vigorexia (o adicción al deporte), que puede conducir a la asunción de sustancias antidopaje. La vigorexia dopa y viaja por el mismo camino y toma formas patológicas porque está estrechamente relacionada con la necesidad de necesitar bienestar relacionado con el uso de sustancias nocivas para el cuerpo y la recurrencia de comportamientos nocivos. Abordará el tema del dopaje en muchos campos deportivos, para escuchar el caso Pantani. Con el epílogo intentaremos proponer una tesis útil en una posible liberación circular de estas necesidades, a través de la implementación de un viaje interno mediante el uso directo de los recursos que la naturaleza nos ofrece de forma espontánea: las endorfinas.

Hyperlipidaemia is characterized by abnormally elevated levels of body’s plasma cholesterol and triacylglycerol. Objective: To find out the proximate composition of Nigella sativa L. and its hypolipidemic effect on blood lipid profile among hyperlipidaemic women. Methods: To determine the proximate composition of Nigella sativa seed the kjeldhah method, soxhlet extraction using petroleum ether, and AOAC procedure were used. For the identification of hypolipidemic impact, a total of 64 women with mild to moderate hyperlipidaemia, aged between 25-35 years were selected for the 8 weeks of study. The sample was selected from the University of Lahore Teaching Hospital, Lahore. After removing physical contaminants like dirt, dust, and other foreign grains black seeds were air dried. After drying, seeds were grounded into fine powder by using commercial blender. Each capsule was prepared with 500mg powder of N. sativa, and was transferred in air tight jars. After screening the participants of experimental group, they were advised to use 2 capsules of N. sativa supplement before breakfast and two capsules in the afternoon prior to their meal for 8 weeks. Participants were also advised to follow the given 7-day diet plan for 8 weeks. The anthropometric measurements, biochemical evaluation (lipid profile), and dietary intake data were collected. Results: The mean age group of Hyperlipidaemic patients enrolled in study was 32.5±0.34 years. There was a significant reduction in Low Density Lipoprotein (LDL), total cholesterol level, and triglyceride levels with p-value less than 0.05. High density lipoprotein levels were also improved from 49.5±8.38mg/dl to 51.81±10.21mg/dl. Conclusion: The study concluded that Nigella sativa L. seed powder supplementation showed a significant improvement in lipid profile of hyperlipidaemia patients. The study found an increase in high density lipoprotein among patients.

The authors, Kosuke Kojo and Tomoko Oguri, contributed equally. This HTML edition is publicly accessible at the following URL:https://academic298uro.github.io/open-archive/2025/seminal-plasma-metallomics-new-horizon/ Abstract Seminal plasma contains a wide range of biomolecules&mdash;including inorganic elements&mdash;that may significantly influence male reproductive function. Historically, semen analysis has focused on sperm count and motility, while overlooking the diagnostic potential of this acellular fraction. This narrative review synthesizes historical perspectives on seminal plasma metallomics, elucidates the biological functions of its diverse elemental constituents, and critically evaluates methodological advancements in their detection. Furthermore, it examines future clinical and research directions by addressing key topics, including the evolution of multi-element analyses in seminal plasma, the interplay between metal exposure and male reproductive health, and the application of omics-based and machine-learning approaches in characterizing male infertility. Progress in analytical chemistry, particularly inductively coupled plasma mass spectrometry, now enables high-precision multi-element measurements in seminal plasma. The &ldquo;metallomic&rdquo; profiles reveal both essential elements&mdash;such as calcium, magnesium, potassium, sodium, zinc and selenium&mdash;and potentially toxic metals, including cadmium and lead, that reflect environmental exposures and may impair fertility. Seminal plasma metallomics also underscores fraction-specific differences between prostatic and seminal vesicular secretions, suggesting that certain chemicals may rise in seminal plasma before shifts appear in blood, thereby making it a promising biomarker for infertility risk assessment. Machine-learning approaches, such as clustering based on seminal plasma-to-serum ratios, offer new diagnostic insights by identifying subtypes of male infertility. By complementing traditional semen parameters and advanced biomarkers (<em>e.g.</em>, DNA fragmentation index), these integrative tools can refine diagnoses and guide interventions, including nutritional supplementation and avoidance of specific toxicants, potentially improving pregnancy outcomes. However, significant challenges remain: standardized protocols, validated reference ranges, and larger prospective studies are needed for clinical translation. Addressing these gaps is crucial for integrating metallomic analyses into routine evaluations of male infertility. As this field continues to evolve, it has the potential to reshape infertility assessments and foster more personalized and effective management strategies. Keywords: Male infertility; Seminal plasma; Metallomics; Trace elements; Environmental exposure; Machine learning; Personalized medicine; Semen analysis; Zinc; Phosphorus Original Publication <strong>Journal</strong>: <em>Revista Internacional de Androlog&iacute;a</em> <strong>Year</strong>: 2025 <strong>Volume</strong>: Published Ahead of Print <strong>Article Title</strong>: <em>Seminal plasma metallomics: a new horizon for diagnosing and managing male infertility</em> <strong>DOI</strong>:&nbsp;10.22514/j.androl.2025.013 License Statement Starting from Issue 1, 2024, all content in <em>Revista Internacional de Androlog&iacute;a</em> (REV INT ANDROL) is published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This <strong>unrestrictive license</strong> allows for unlimited copying, redistribution, remixing, transformation, and building upon the work, provided that proper credit is given to the original authors and source. Copyright &copy; 2025 The Author(s). Published by MRE Press.According to the journal&rsquo;s policy, <strong>the copyright is retained by the author(s)</strong>. Under the terms of CC BY 4.0, no additional permission is required to reuse or distribute this content, as long as appropriate credit is given. 1. Introduction Infertility in humans often occurs when an insufficient number of spermatozoa reaches the female oviduct following vaginal coitus or intrauterine insemination (IUI), thereby preventing fertilisation. Historically, semen analysis has primarily emphasised sperm count and motility to diagnose male infertility. However, seminal plasma (<em>i.e</em><em>.</em>, semen without cells) contains a myriad of lipids, inorganic ions, metabolites, nucleic acids, proteins and other biomolecules, the physiological roles of which remain underexplored [1&ndash;4]. In addition to its contribution to fertilisation, seminal plasma has gained attention as a potential reservoir of biomarkers relevant not only to fertility but also to genitourinary malignancies and infections [5, 6]. Metallomics is a branch of analytical chemistry that systematically investigates metals and metalloids in biological systems [7]. Seminal plasma metallomics specifically aims to characterise the inorganic constituents (<em>e.g</em><em>.</em>, metal ions and metal&ndash;protein complexes) in semen. In this review, we use the term &ldquo;metals&rdquo; broadly to encompass all inorganic elements relevant to metallomics, including certain metalloids and, on rare occasions, non-metals (<em>e.g.</em>, phosphorus). More than a century has passed since the initial suggestion that zinc is crucial for vertebrate reproduction. Recent omics-based approaches have widened the scope of the metals/metalloids under investigation. These developments have potentially transformed diagnostics in reproductive medicine by highlighting trace elements in seminal plasma that can affect sperm physiology or reflect environmental exposure. Building on previous studies that explored the clustering of male infertility subtypes using seminal plasma-to-serum trace element concentration ratios [8], we undertook this narrative review as part of a broader cross-sectional project aimed at developing new diagnostic strategies for male infertility. To identify relevant literature, we performed a focused search of PubMed and Google Scholar using terms such as &ldquo;male infertility&rdquo;, &ldquo;seminal plasma&rdquo;, &ldquo;trace elements&rdquo;, &ldquo;metallomics&rdquo; and &ldquo;environmental exposure&rdquo;. We also examined several specialized andrology textbooks to confirm certain historical milestones and methodological details. By incorporating these references into our broader search strategy, we aimed to capture both the foundational and the most current perspectives on seminal plasma metallomics in male infertility. Through this process, we synthesized historical perspectives on the field, examined the biological functions of various elemental constituents and evaluated methodological advancements in their detection. In the following sections, we address key topics such as the evolution of multi-element analyses in seminal plasma, the interplay between metal exposure and male reproductive health, and the potential of metallomics-based approaches to refine the classification and management of male infertility. 2. Historical perspectives on seminal plasma trace element research 2.1 Early observations: zinc and fertility (1920s&ndash;1970s) Initial hints of the relevance of trace elements in semen date back to the 1920s, when Bertrand and Vladesco proposed that zinc plays a role in vertebrate reproduction [9]. Research in subsequent decades has confirmed that zinc and other ions are present in male accessory gland secretions and influence sperm function. However, until the 1970s, analytical limitations restricted most investigations to measuring a small number of elements&mdash;primarily zinc, calcium and magnesium&mdash;in relation to spermatozoal parameters [10]. 2.2 Emergence of multi-element analytical techniques (1980s&ndash;2000s) In the 1980s, atomic absorption spectrometry and early inductively coupled plasma mass spectrometry (ICP-MS) expanded the range of elements detectable in semen [11]. Studies have begun to compare fertile and infertile men, with a focus on the detection of single heavy metals, such as lead or cadmium, along with essential elements. Despite technological advances, many surveys lack precise information regarding the exposure history or environmental confounders [12]. 2.3 Rise of metallomics and modern seminal plasma studies After 2010, advances in ICP-MS enabled simultaneous measurement of multiple ultra-trace elements, spurring integrative analyses of seminal plasma &ldquo;metallomes&rdquo; [13]. Researchers have increasingly recognised that many elements beyond zinc can influence sperm function, either as essential micronutrients or as toxicants. New high-throughput approaches allow investigators to examine previously unstudied metals in normal and abnormal semen, thereby offering a broader perspective on male reproductive function. 3. Biological significance of trace elements in seminal plasma 3.1 Intracellular vs. extracellular elemental concentrations Body fluids generally comprise cellular components and a fluid fraction. In blood, erythrocytes constitute about 40&ndash;45% of the total volume (roughly 4&ndash;6 &times; 10⁹ erythrocytes per mL), whereas the fluid component is plasma; in clinical practice, serum is derived by allowing blood to clot, thereby removing clotting factors (particularly fibrinogen) from the fluid component. Many electrolytes and trace elements&mdash;such as sodium, potassium, calcium, magnesium and zinc&mdash;are routinely measured in serum, reflecting extracellular concentrations. However, certain elements (<em>e.g.</em>, cadmium and lead) can accumulate within erythrocytes over their 120-day lifespan, making whole-blood analysis more appropriate for assessing chronic exposure in occupational or environmental contexts [14]. The standard concentrations of representative elements in whole blood, erythrocytes and serum are summarized in Table 1 (Ref. [14&ndash;16]). <strong>Table 1. Elemental concentrations in whole blood, serum and erythrocytes.</strong> Z Element Classification Concentration (mg/L) Whole blood Concentration (mg/L) Serum Concentration (mg/L) Erythrocyte 11 Sodium Light metal 1.7&times;10³&ndash;2.0&times;10³ [a] 3.0&times;10³&ndash;3.4&times;10³ [a] 1.8&times;10²&ndash;3.6&times;10² [b] 12 Magnesium Light metal 3.0&times;10¹&ndash;3.9&times;10¹ [a] 1.9&times;10¹&ndash;2.4&times;10¹ [a] 4.6&times;10¹&ndash;6.3&times;10¹ [a] 15 Phosphorus [c] Non-metal/Metalloid 3.2&times;10²&ndash;3.9&times;10² [a] 1.2&times;10²&ndash;1.8&times;10² [a] 5.6&times;10²&ndash;7.6&times;10² [a] 19 Potassium Light metal 1.5&times;10³&ndash;1.8&times;10³ [a] 1.5&times;10²&ndash;2.3&times;10² [a] 3.0&times;10³&ndash;4.0&times;10³ [a] 20 Calcium Light metal 4.8&times;10¹&ndash;6.0&times;10¹ [a] 8.8&times;10¹&ndash;1.0&times;10² [a] 6.3&times;10^&minus;1&ndash;5.2&times;10⁰ [b] 25 Manganese Heavy metal 5.0&times;10^&minus;3&ndash;1.4&times;10^&minus;2 [a] 4.0&times;10^&minus;4&ndash;6.0&times;10^&minus;4 [a] 8.9&times;10^&minus;3&ndash;2.9&times;10^&minus;2 [a] 26 Iron Heavy metal 4.0&times;10²&ndash;5.1&times;10² [a] 8.7&times;10^&minus;¹&ndash;1.9&times;10⁰ [b] 9.6&times;10²&ndash;1.2&times;10³ [a] 29 Copper Heavy metal 7.3&times;10^&minus;1&ndash;1.4&times;10⁰ [a] 8.0&times;10^&minus;¹&ndash;1.9&times;10⁰ [a] 5.4&times;10^&minus;1&ndash;7.5&times;10^&minus;1 [a] 30 Zinc Heavy metal 4.7&times;10⁰&ndash;6.7&times;10⁰ [a] 7.3&times;10^&minus;¹&ndash;1.1&times;10⁰ [a] 1.0&times;10¹&ndash;1.5&times;10¹ [a] 33 Arsenic Metalloid 7.0&times;10^&minus;5&ndash;3.4&times;10^&minus;3 [a] 3.0&times;10^&minus;5&ndash;1.7&times;10^&minus;3 [a] 1.6&times;10^&minus;4&ndash;5.8&times;10^&minus;3 [a] 34 Selenium Metalloid 8.5&times;10^&minus;2&ndash;1.3&times;10^&minus;1 [a] 7.0&times;10^&minus;2&ndash;1.1&times;10^&minus;1 [a] 1.1&times;10^&minus;1&ndash;1.9&times;10^&minus;1 [a] 48 Cadmium Heavy metal 1.3&times;10^&minus;4&ndash;1.7&times;10^&minus;3 [a] &lt;9.0&times;10^&minus;6&ndash;1.7&times;10^&minus;5 [a] 2.1&times;10^&minus;4&ndash;3.4&times;10^&minus;3 [a] 82 Lead Heavy metal 5.4&times;10^&minus;3&ndash;2.6&times;10^&minus;2 [a] 1.0&times;10^&minus;5&ndash;1.0&times;10^&minus;4 [a] 1.2&times;10^&minus;2&ndash;6.3&times;10^&minus;2 [a] Z, atomic number. [a] Values quoted from Heitland and K&ouml;ster (2021) [14], representing the 5th&ndash;95th percentile range (approximate values rounded to two significant figures). [b] Derived from the review by Iyengar <em>et al.</em> [15] (1978), showing the minimum and maximum among reported mean concentrations in the literature examined (approximate values rounded to two significant figures). [c] Phosphorus is widely recognized as a non-metal, although certain sources have classified it as a metalloid. The values here represent total phosphorus, encompassing not only inorganic phosphate but also phospholipids and other phosphorus-containing compounds, and thus differ from the inorganic phosphate typically measured in routine clinical practice [16]. A similar logic applies to semen: it has a cellular component (sperm) and a fluid component (seminal plasma). Yet sperm concentrations (up to~1 &times; 10⁸ per mL) are generally lower than erythrocytes counts in blood, meaning the impact of &ldquo;cell removal&rdquo; (<em>i.e.</em>, separating sperm) on trace element measurements can be less dramatic than that between whole blood and serum. Nevertheless, studies often prefer to measure seminal plasma specifically, in order to focus on the microenvironment that directly surrounds sperm. Unlike serum, methodological standardisation for electrolytes and trace elements in seminal plasma remains limited. Reported concentrations vary widely across investigations, potentially reflecting genuine differences in population, region, diet and environmental exposure, but also inconsistencies in sample processing or analytical protocols. Consequently, caution is warranted when comparing absolute values between studies. As an alternative, we and others have proposed ratio-based approaches (<em>e.g.</em>, &ldquo;seminal plasma-to-serum ratios&rdquo;) to help reduce inter-laboratory variability [8]. While some groups use serum and seminal plasma in parallel [17], other group simultaneously evaluated &ldquo;whole blood&rdquo; and &ldquo;whole semen,&rdquo; underscoring the importance of clarifying which compartments are being measured in reproductive toxicology research [18]. Table 2 (Ref. [8, 16, 19&ndash;22]) provides a concise overview of key trace elements in seminal plasma&mdash;including their typical distribution, primary glandular sources and reproductive roles&mdash;which will be referenced throughout this manuscript where relevant. <strong>Table 2. Seminal plasma trace elements: distribution, origins and roles.</strong> Z Element SP/Se ratio [a] Dominant glandular origin Potential role in seminal plasma [12, 19, 20] 11 Sodium 0.88&ndash;0.97 [b] Prostate [c] Maintains osmotic balance and membrane potential essential for sperm viability 12 Magnesium 2.9&ndash;7.3 [b] Prostate [c] Supports ejaculatory function and stabilizes sperm membranes 15 Phosphorus [d] 6.12&ndash;9.24 [b] Seminal vesicle [c] Contributes to energy metabolism and acid phosphatase activity, aiding sperm function 19 Potassium 5.37&ndash;9.00 [b] Prostate [c] Maintains osmotic balance and membrane potential essential for sperm viability 20 Calcium 2.18&ndash;4.55 [b] Prostate [c] Regulates sperm motility and acrosome reaction 25 Manganese 7&ndash;18 [b] Prostate [c] Acts as a cofactor in antioxidant defense; exact role in sperm function under investigation 26 Iron 0.08&ndash;0.16 [b] Prostate [c] No major direct role; may contribute to oxidative balance in seminal plasma 29 Copper 0.08&ndash;0.16 [b] Prostate [c] Acts as a cofactor for antioxidant enzymes; may indirectly influence sperm quality 30 Zinc 116&ndash;306 [b] Prostate [c] Stabilizes sperm chromatin and supports antioxidant defense 33 Arsenic 1.61&ndash;3.49 [b] Seminal vesicle [c] Non-essential; can disrupt sperm parameters when elevated 34 Selenium 0.37&ndash;0.61 [b] Prostate [c] Essential for selenoproteins; protects sperm from oxidative stress 48 Cadmium Unknown [e] Unknown [f] Non-essential; accumulates in tissues and may impair testicular function 82 Lead Unknown [e] Seminal vesicle? [f] Non-essential; interferes with reproductive hormones and sperm parameters Z, atomic numb; SP, seminal plasma; Se, serum. [a] The value indicates the relative concentration in seminal plasma when the serum concentration is set to 1. [b] These data refer to our findings in Tanaka (2024) [8]. Specifically, they represent the 25th&ndash;75th percentiles for men whose partners conceived within one year without undergoing in vitro fertilization or intracytoplasmic sperm injection. [c] Based on our own data in Tanaka (2024) [8] using split ejaculate sampling: elements showing higher concentrations in the early fraction were deemed prostate-dominant, whereas those showing higher concentrations in the later fraction were deemed seminal vesicle&ndash;dominant. [d] Here, the phosphorus values represent total phosphorus, encompassing not only inorganic phosphate but also phospholipids and other phosphorus-containing compounds, and thus differ from the inorganic phosphate typically measured in routine clinical practice [16]. [e] No systematic study has established SP/Se ratios for cadmium or lead. Althogh the data from Riaz (2016) [21] may be partially informative, they may overestimate serum concentrations compared with other studies. [f] Based on Pant (2003) [22], cadmium&rsquo;s lack of correlation with fructose or acid phosphatase leaves its origin unclear, whereas lead&rsquo;s positive correlation with fructose and negative correlation with acid phosphatase suggests the seminal vesicles as its likely dominant origin. 3.2 Essential elements Many essential elements are found in their ionic forms in seminal plasma and support sperm physiology [20] (Table 2). Calcium modulates sperm motility, hyperactivation, acrosome reaction and chemotaxis [23]. Magnesium is critical for the ejaculatory function and affects sperm membrane stability [24, 25]. Potassium and sodium are vital for membrane potential regulation via sodium&ndash;potassium adenosine triphosphatase (Na/K-ATPase) [26]. Zinc helps stabilise sperm chromatin, assists in antioxidant defense and supports spermatogenesis [27, 28]. Selenium is a cofactor in selenoproteins that protect cells from oxidative damage and is integral to sperm formation [29]. These elements often differ in absolute concentration between blood and seminal plasma. For example, prostatic fluid typically contains high levels of zinc, reflecting a specialized role in stabilizing sperm DNA and supporting accessory gland function. Assessing such elements in the reproductive tract&rsquo;s fluid fraction can thus provide information beyond conventional serum measurements alone. 3.3 Potentially toxic metals and metalloids Heavy metals, defined as inorganic elements with a density greater than 5 g/cm³ [30], are often associated with toxicity when present in excess (Tables 1 and 2). Examples include silver, arsenic, cadmium, chromium, cobalt, copper, lead, mercury, nickel and zinc. These metals are classified as non-essential or in cases where they may be biologically essential, can become harmful when their levels exceed the physiological requirements [31]. Certain heavy metals tend to accumulate in biological materials owing to the limited detoxification and excretion pathways in the body, making them reliable environmental exposure biomarkers for assessing health risks [32]. The reproductive system is particularly vulnerable to the adverse effects of heavy metals, which act through direct mechanisms, such as oxidative damage and gonadal toxicity, and indirect mechanisms, such as endocrine disruption [33]. Some trace elements, while necessary in small amounts, can exert toxic effects when concentrations exceed physiological thresholds. Additionally, certain metals, such as lead and cadmium, are endocrine-disrupting compounds that interfere with hormonal pathways and can alter reproductive health [34]. 3.4 Evidence of elemental exchange between sperm and seminal plasma Essential elements such as calcium, magnesium, potassium, sodium and zinc are present in seminal plasma, predominantly in the ionic form. Spermatozoa use supecialized ion channels and pumps to regulate intracellular and extracellular concentrations, ensuring optimal osmotic balance, pH, and membrane potential for motility and fertilization [35]. This dynamic exchange parallels that between erythrocytes and plasma in blood [36, 37], albeit on a smaller scale due to the lower cellular density in semen. In reproductive technology, the composition of semen simulants (artificial seminal plasma) injected into the vaginal environment is calibrated carefully to mimic the physiological levels of essential elements as closely as possible [38]. This is performed to optimise the conditions for sperm function and fertilisation. The distinction between intracellular and extracellular metal homeostasis highlights the precision with which these elements are regulated to support fertilisation. For example, zinc, potassium, calcium and magnesium concentrations in seminal plasma often significantly exceed those found in serum. Conversely, other elements such as copper and iron are consistently higher in the serum than in the seminal plasma [8, 17, 39] (Table 2). These differential patterns underscore the highly specialised microenvironment of the male reproductive tract, which is tailored to the needs of spermatozoa during their journey through the male and female reproductive systems [40]. The choice of whether to measure whole blood or serum (in the case of blood), and whole semen or seminal plasma (in the case of semen), depends on study objectives, exposure profiles, and the need to differentiate chronic from acute or localized effects. 4. Analytical approaches in seminal plasma metallomics 4.1 A key analytical technique: advantages and limitations Among the various methodologies for comprehensive profiling of both essential and ultratrace metals in seminal plasma, ICP-MS provides high sensitivity, a broad dynamic range, and the ability to measure multiple elements simultaneously [41]. These features make it especially suitable for the comprehensive profiling of both essential and ultratrace metals in seminal plasma. However, ICP-MS requires meticulous calibration and strict contamination control. Sample digestion protocols, which often employ nitric acid and hydrogen peroxide, are critical for obtaining consistent measurements [42]. 4.2 Comparison with other methods Although atomic absorption spectrometry remains a standard technique for single-element analysis, its throughput and sensitivity to ultratrace levels can be limited. Inductively coupled plasma optical emission spectrometry (ICP-OES) also offers multi-element capabilities by measuring the light emitted from excited atoms or ions in the ionized gas plasma (not to be confused with seminal plasma), but it generally provides higher detection limits (<em>i.e.</em>, lower sensitivity) compared to ICP-MS, which detects ions based on their mass-to-charge ratio [16]. Given the wide range of metal concentrations in seminal plasma, ICP-MS has become the method of choice for advanced metallomic studies. 4.3 Sampling and pre-analytical considerations The proper collection and storage of seminal plasma samples are of paramount importance, as metal contamination can arise from containers or spermatozoa. Centrifugation to remove sperm, spermatogenic cells and other cellular and particulate debris [43] precedes storage at &minus;80 &deg;C in several protocols [44]. 4.4 Data interpretation and quality control Metals in seminal plasma often exhibit non-Gaussian distribution, and researchers should apply nonparametric statistics or data transformations to handle skewed data [45]. Moreover, external reference materials to analytical quality control for seminal plasma are scarce, which necessitates the reliance on serum-based or in-house calibrations [46, 47]. 5. Fractionation of the ejaculate: prostate <em>vs. </em>seminal vesicle contributions 5.1 Normal physiology of ejaculation and fraction dominance Semen primarily consists of secretions from the prostate and seminal vesicles, with minor contributions from other sources, such as the bulbourethral glands, epididymides and the testes. Understanding each gland&rsquo;s contribution is crucial for assessing male reproductive health [48, 49]. Theoretically, prostatic fluid can be obtained through prostatic massage [50], and seminal vesicular fluid is collected via aspiration under transrectal ultrasound guidance [51]. However, these methods are associated with significant invasiveness and a high risk of contamination, limiting their application to specialized contexts, such as pharmacokinetic studies or the evaluation of obstructive azoospermia in cases of male infertility. Given these challenges, there remains a clear need for less invasive and more precise techniques to evaluate the gland-specific contributions to semen [52]. Split ejaculation sampling, which involves collecting multiple fractions from a single ejaculation, is often employed as a noninvasive method to evaluate the dynamics of accessory gland secretions <em>in vivo</em> [53]. This sampling technique leverages the physiological property that approximately the first 30% of the ejaculate typically originates from the prostate, while the remaining two-thirds are primarily composed of seminal vesicular fluid [54]. Observational studies using transrectal ultrasound have further demonstrated that the timing of prostatic contractions differs from that of seminal vesicle contractions by at least several seconds [55]. Additionally, prostatic fluid is typically watery, while seminal vesicular fluid has a gel-like consistency [56, 57]. This difference in texture can serve as a helpful indicator of whether the ejaculate has been successfully fractionated during sampling. 5.2 Biochemical and elemental differences in early vs. subsequent fractions Fractionation studies in the 1970s showed that the initial portion of the ejaculate, dominated by prostatic fluid, generally has higher sperm concentration and motility, whereas seminal vesicular fluid contains only a small number of sperm [58]. Subsequent research further demonstrated that excessive exposure to seminal vesicular fluid can reduce sperm motility, shorten lifespan, compromise nuclear chromatin stability, and negatively affect sperm DNA integrity [59]. Chemically, the first fraction tends to have elevated levels of elements, such as zinc, calcium and magnesium, reflecting prostatic secretion [53, 56]. In contrast, the subsequent fraction is often more voluminous and enriched with phosphorus and arsenic [8, 53] (Table 2). Notably, it was already recognized in the 1990s that seminal vesicular fluid may contain prostaglandins, semenogelins, and other factors potentially capable of reducing sperm motility [60, 61]. In fact, significant progress has been made in elucidating the functions of numerous bioactive substances present in seminal vesicular fluid, and their contributions to sperm function regulation and modulation of the immune environment in the female reproductive tract are increasingly being understood [49, 62]. However, further research is required to comprehensively clarify the interactions of newly identified components and their physiological significance [63]. In addition, the use of split ejaculation sampling for trace element studies poses specific methodological challenges. Potential pitfalls include incomplete separation of fractions, cross-contamination between the initial and subsequent fractions, and an increased likelihood of contamination arising from multiple collection containers. Consequently, ensuring the reliability and accuracy of research designs employing this approach requires careful timing to capture the intermittent outflow from the urethra, as well as the standardization of protocols&mdash;including the use of low-contamination consumables. By addressing these factors, split ejaculation sampling can remain a valuable tool for elucidating gland-specific trace element distributions in semen. 5.3 Clinical implications of fractionation for fertility assessment Elucidating the secretory profiles of each accessory gland offers valuable insights into male fertility. In addition to testicular factors, the etiology of semen abnormalities also involves post-testicular contributors&mdash;namely epididymal and accessory gland functions&mdash;which remain relatively underexplored [64]. Seminal plasma is considered an optimal resource for investigating these factors because it reflects the local pathophysiology of the male reproductive organs [65]. A practical approach proposed more than half a century ago revealed that using only the initial fraction of ejaculate for IUI could result in higher pregnancy rates [66]. Similarly, the &ldquo;withdrawal coital method&rdquo;, wherein the initial fraction is ejaculated intravaginally while the remaining portion is expelled outside the vagina, can be viewed as an early technique that harnesses the distinct physiological effects of prostatic and seminal vesicular secretions on sperm to improve pregnancy outcomes [67]. From a diagnostic perspective, specific biomarkers in seminal plasma have long been used to evaluate glandular function. Zinc was identified in the 1980s as a marker of prostatic secretion [68], while fructose was used to assess seminal vesicular function [69]. By the 2000s, the use of prostate-specific antigen (PSA) in seminal plasma to evaluate prostatic secretory capacity had also been reported [52, 70]. Other established markers of prostatic activity include citric acid, &gamma;-glutamyl transpeptidase, and acid phosphatase [71, 72]. Additionally, parameters such as pH and viscosity have been proposed as potential indicators of seminal vesicular dysfunction [73]. Zinc, calcium and magnesium are well-known trace elements predominantly found in prostatic fluid [53]. Moreover, our previous research demonstrated that a wide range of elements&mdash;including lithium, sodium, sulfur, manganese, iron, cobalt, copper, zinc, selenium, rubidium, strontium, molybdenum, cesium, barium and thallium&mdash;are predominantly present in prostatic fluid [8]. In contrast, only two trace elements, phosphorus and arsenic, appear to be more concentrated in seminal vesicular fluid [8]. Building on earlier studies, which proposed combining fructose and PSA measurements to simultaneously quantify the relative contributions of the prostate and seminal vesicles to total semen volume [52], we have introduced a novel approach. Using ICP-MS to measure a broad spectrum of trace elements [16], we demonstrated its analytical advantage in assessing the imbalance between prostatic and seminal vesicular secretions. This method could serve as a foundation for developing superior diagnostic strategies. In addition, our earlier findings suggest that certain trace elements are maintained at higher or lower concentrations in seminal plasma than in serum, potentially reflecting active regulation by epithelial cells in the prostate or seminal vesicles [8]. Although the fundamental physiological rationale for maintaining divergent levels in seminal plasma remains unclear, the fact that seminal plasma-to-serum ratios vary significantly depending on the specific element indicates their potential value as biomarkers for evaluating post-testicular factors [17]. Overall, fractionation not only reveals the distinct biochemical signatures contributed by the prostate and seminal vesicles but also has meaningful clinical relevance. By understanding which glandular functions are compromised or exaggerated, targeted therapeutic interventions may be devised, such as adjusting supplementation to enhance prostatic support or addressing potential excess seminal vesicular components. Although epididymal fluid represents less than 10% of the total ejaculate volume [52], it remains pivotal for sperm maturation, with neutral &alpha;-glucosidase and L-carnitine serving as recognized functional markers [74, 75]. However, no specific trace element has yet been definitively linked to epididymal fluid, and it is unclear whether subtle variations in epididymal secretion significantly affect metallomic profiles. Empirical or supplemental therapies, including coenzyme Q10, vitamins, zinc and selenium, continue to be studied for their potential to improve sperm quality in men with unexplained male infertility [76]. Moreover, measuring seminal plasma biomarkers may identify subgroups of idiopathic&nbsp;oligoasthenoteratospermic men who could benefit from L-carnitine supplementation [75], suggesting a new avenue for personalized treatment approaches. Future work may clarify how post-testicular, epididymal and accessory gland contributions jointly influence male reproductive outcomes and guide more targeted interventions. 6. Environmental and occupational exposures to trace elements 6.1 Seminal plasma as a sensitive biomarker of environmental exposure Although blood and urine are conventional biomarkers, seminal plasma can be more specific for reproductive outcomes. High levels of certain toxicants in seminal plasma may cause infertility before overt changes appear in the blood [77]. This specificity stems from the role of accessory glands in excreting or concentrating certain metals [31]. 6.2 Regional pollution and male infertility Regions such as Campania (Italy) and Opole (Poland) have been associated with industrial contamination and diminished sperm quality [78, 79]. Similar associations have been noted in heavily industrialised parts of India and China, underscoring how local environmental factors can shape seminal plasma metallomic profiles [13]. 6.3 Regulatory thresholds and gaps in knowledge Despite the accumulating evidence, no universally accepted threshold values exist for &ldquo;toxic&rdquo; <em>vs.</em> &ldquo;safe&rdquo; levels of elements in seminal plasma. Establishing reference intervals for multiple metals remains a challenge [12], and researchers must disentangle chronic low-dose exposure, which may exert subtle but significant effects, from acute high-dose exposure. 7. Emerging trends: personalized medicine and machine learning 7.1 Clustering and other data-driven approaches in metallomics The ultimate goal of seminal plasma biomarker research in addressing male infertility is achieving partner pregnancy. To this end, two potential case-control study designs can be envisioned. One approach involves comparing fertile and infertile men, while the other focuses on examining differences in biomarker profiles to predict pregnancy outcomes in their partners. Both approaches, however, face limitations when relying on traditional statistical methods. This is due to the known correlations&mdash;both positive and negative&mdash;among the concentrations of seminal plasma biomarkers that reflect accessory gland secretory functions. For example, positive correlations have been reported between zinc and citric acid concentrations, while negative correlations exist between zinc and fructose concentrations [80]. Additionally, several studies have documented consistent positive correlations among heavy metals in seminal plasma [79, 81&ndash;86]. Given these complexities, machine learning techniques have emerged as promising tools in seminal plasma metallomics research. Specifically, studies comparing fertile and infertile men have utilized supervised machine learning methods, such as Bayesian kernel machine regression and weighted quantile sum models, to address the intricate multicollinearity among trace elements [86]. These approaches have demonstrated efficacy in distinguishing between fertile and infertile groups when clear classification is achievable. However, real-world challenges remain, including difficulty in definitively excluding female infertility as a factor, the possibility of spontaneous conception in men initially categorized as infertile, and the relatively large sample sizes required for supervised learning methods. To overcome these challenges, we explored the use of unsupervised machine learning techniques to maximize the utility of pilot data obtained from a relatively small-scale study [8]. This approach analyzed high-dimensional elemental data, aiming to identify latent subtypes within a population of male patients with infertility&mdash;defined as individuals whose fertility status cannot be clearly categorized as fertile or infertile. By clustering these patients based on the ratios of key elements in seminal plasma to serum, we identified distinct patterns reflecting &ldquo;prostatic fluid dominance&rdquo; and &ldquo;seminal vesicular fluid dominance&rdquo;. Our findings suggest that the subgroup characterized by &ldquo;prostatic fluid dominance&rdquo; may be associated with better pregnancy outcomes. 7.2 Integration with sperm analysis The DNA fragmentation index, recognized as an advanced biomarker, holds promise as a robust predictor of fertilization outcomes [87]. By integrating metallome profiles as a third pillar alongside traditional semen parameters, such as sperm concentration, motility and morphology, as well as advanced biomarkers, such as DNA fragmentation indices, we anticipate a more powerful framework for addressing the complex mechanisms of infertility. This integrative approach not only has the potential to enhance diagnostic precision but may also guide targeted therapeutic strategies, including nutritional supplementation and avoidance of specific toxicant exposure, thus paving the way for more effective interventions in the future. 7.3 Challenges and future directions Large-cohort studies, prospective designs and standardised sample handling are essential to validate these approaches. The high cost and limited accessibility of ICP-MS remain a barrier; moreover, as the reference intervals for seminal plasma metals remain poorly defined, clinicians must interpret results with caution. 8. Conclusions Seminal plasma metallomics studies highlight how inorganic elements shape male reproductive health. This field, galvanised by improvements in ICP-MS and machine learning, expands our understanding beyond semen analysis alone. Early versus subsequent fraction patterns, environmental exposure and personalised therapies converge to form a new paradigm in infertility research. Robust prospective studies with standardised protocols are required to validate and translate these findings into clinical practice. &nbsp; <strong>Availability of data and materials</strong> Not applicable. <strong>Author contributions</strong> KK and TO&mdash;designed the research study. KK and TTan&mdash;performed the experiments. MU, KY, AI, HNe, TTak, TK and HNi&mdash;provided assistance and advice. KK, TTan, AN and DN&mdash;analysed the data. KK and TO&mdash;wrote the manuscript. All authors contributed to the editorial changes in the manuscript. All the authors have read and approved the final version of the manuscript. <strong>Ethics approval and consent to participate</strong> Not applicable. <strong>Acknowledgment </strong> The authors express their sincere gratitude to Haruki Tsuchiya and Masahiro Kurobe for their invaluable support in managing the project. We also extend our appreciation to Daiki Numata, Mikiko Matsuoka, Yukiko Hara, Jun Itadani, Miki Takahashi, Tomoyasu Sakai, Mami Enjoji and Miki Muroi for their assistance with laboratory operations. Special thanks go to Yukinobu Haruyama and Yukinari Gunji for their guidance on serum sample handling. We are also deeply grateful to Takuya Shimizu, Shunsuke Fujimoto, Mitsuhiro Ueda, Katsura Kato, Naoyuki Okamoto, and Seiichi Inagaki of Renatech Co., Ltd., for their invaluable advice on project initiation and trace element measurement techniques. Lastly, we sincerely thank Yoshiyuki Nagumo, Tomokazu Kimura, Shuya Kandori, Kaoru Yanagida, and Teruaki Iwamoto for their support in reviewing the study design and manuscript preparation. <strong>Funding</strong> This research was funded by the Japan Society for the Promotion of Science KAKENHI under Grant Numbers 23K15756 and 21K16737 as well as the Japan Science and Technology Agency through Grant Number JPMJPF2017. <strong>Conflict of interest</strong> The authors declare no conflict of interest.&nbsp; <strong>References</strong> 1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Wang F, Yang W, Ouyang S, Yuan S. The vehicle determines the destination: The significance of seminal plasma factors for male fertility. Int J Mol Sci. 2020; 21: PubMed PMID: 33198061; PubMed Central PMCID: PMC7696680. Available from: https://doi.org/10.3390/ijms21228499 2.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Rodriguez-Martinez H, Martinez EA, Calvete JJ, Pena Vega FJ, Roca J. Seminal plasma: Relevant for fertility? Int J Mol Sci. 2021; 22: PubMed PMID: 33922047; PubMed Central PMCID: PMC8122421. Available from: https://doi.org/10.3390/ijms22094368 3.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Vashisht A, Gahlay GK. Understanding seminal plasma in male infertility: Emerging markers and their implications. Andrology. 2024; 12: 1058-1077. PubMed PMID: 38018348. Available from: https://doi.org/10.1111/andr.13563 4.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Moustakli E, Zikopoulos A, Skentou C, Stavros S, Sofikitis N, Georgiou I, et al. Integrative assessment of seminal plasma biomarkers: A narrative review bridging the gap between infertility research and clinical practice. J Clin Med. 2024; 13: PubMed PMID: 38892858; PubMed Central PMCID: PMC11173072. Available from: https://doi.org/10.3390/jcm13113147 5.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Drabovich AP, Saraon P, Jarvi K, Diamandis EP. Seminal plasma as a diagnostic fluid for male reproductive system disorders. Nat Rev Urol. 2014; 11: 278-288. PubMed PMID: 24709963. Available from: https://doi.org/10.1038/nrurol.2014.74 6.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Abdel-Naser MB, Altenburg A, Zouboulis CC, Wollina U. Schistosomiasis (bilharziasis) and male infertility. Andrologia. 2019; 51: e13165. PubMed PMID: 30276841. Available from: https://doi.org/10.1111/and.13165 7.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Vogiatzis CG, Zachariadis GA. Tandem mass spectrometry in metallomics and the involving role of icp-ms detection: A review. Anal Chim Acta. 2014; 819: 1-14. PubMed PMID: 24636405. Available from: https://doi.org/10.1016/j.aca.2014.01.029 8.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tanaka T, Kojo K, Nagumo Y, Ikeda A, Shimizu T, Fujimoto S, et al. A new clustering model based on the seminal plasma/serum ratios of multiple trace element concentrations in male patients with subfertility. Reprod Med Biol. 2024; 23: e12584. PubMed PMID: 38807752; PubMed Central PMCID: PMC11131575. Available from: https://doi.org/10.1002/rmb2.12584 9.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mann T. The biochemistry of semen. London, Methuen Publishing Ltd; New York: John Wiley &amp; Sons, Inc; 1954. Available from: https://archive.org/details/biochemistryofse00mann/page/88/ 10.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Wong WY, Flik G, Groenen PM, Swinkels DW, Thomas CM, Copius-Peereboom JH, et al. The impact of calcium, magnesium, zinc, and copper in blood and seminal plasma on semen parameters in men. Reprod Toxicol. 2001; 15: 131-136. PubMed PMID: 11297872. Available from: https://doi.org/10.1016/s0890-6238(01)00113-7 11.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Abou-Shakra FR, Ward NI, Everard DM. The role of trace elements in male infertility. Fertil Steril. 1989; 52: 307-310. PubMed PMID: 2753179. Available from: https://doi.org/10.1016/s0015-0282(16)60860-9 12.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Karabulut S, Korkmaz S, Gunes E, Kabil E, Keskin I, Usta M, et al. Seminal trace elements and their relationship with sperm parameters. Andrologia. 2022; 54: e14610. PubMed PMID: 36175375. Available from: https://doi.org/10.1111/and.14610 13.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Lopez-Botella A, Sanchez R, Paul R, Aizpurua J, Gomez-Torres MJ, Todoli-Torro JL. Analytical determination of heavy metals in human seminal plasma-a systematic review. Life (Basel). 2023; 13: PubMed PMID: 37109454; PubMed Central PMCID: PMC10145970. Available from: https://doi.org/10.3390/life13040925 14.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Heitland P, Koster HD. Human biomonitoring of 73 elements in blood, serum, erythrocytes and urine. J Trace Elem Med Biol. 2021; 64: 126706. PubMed PMID: 33352468. Available from: https://doi.org/10.1016/j.jtemb.2020.126706 15.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Iyengar GV, Kollmer WE, Bowen HJM. The elemental composition of human tissues and body fluids: A compilation of values for adults. Weinheim, Germany: Verlag Chemie; 1978. Available from: https://archive.org/details/elementalcomposi0000iyen_b1s1/ 16.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Kojo K, Oguri T, Tanaka T, Ikeda A, Shimizu T, Fujimoto S, et al. Inductively coupled plasma mass spectrometry performance for the measurement of key serum minerals: A comparative study with standard quantification methods. J Clin Lab Anal. 2024; e25140. PubMed PMID: 39716823. Available from: https://doi.org/10.1002/jcla.25140 17.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Feng RX, Lu JC, Zhang HY, Lu NQ. A pilot comparative study of 26 biochemical markers in seminal plasma and serum in infertile men. Biomed Res Int. 2015; 2015: 805328. PubMed PMID: 26539526; PubMed Central PMCID: PMC4619868. Available from: https://doi.org/10.1155/2015/805328 18.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Stojsavljevic A, Zecevic N, Mihailovic M, Jagodic J, Durdic S, Perovic M, et al. Elemental profiling of human semen with confirmed normozoospermia: Baseline levels for 44 elements. J Trace Elem Med Biol. 2022; 74: 127081. PubMed PMID: 36152465. Available from: https://doi.org/10.1016/j.jtemb.2022.127081 19.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tvrd&aacute; E, Sikeli P, Luk&aacute;čov&aacute; J, Mass&aacute;nyi P, Luk&aacute;č N. Mineral nutrients and male fertility. Journal of Microbiology, Biotechnology and Food Science. 2013; 3: 1-14. Available from: https://office2.jmbfs.org/index.php/JMBFS/article/view/7068 20.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mirnamniha M, Faroughi F, Tahmasbpour E, Ebrahimi P, Beigi Harchegani A. An overview on role of some trace elements in human reproductive health, sperm function and fertilization process. Rev Environ Health. 2019; 34: 339-348. PubMed PMID: 31203261. Available from: https://doi.org/10.1515/reveh-2019-0008 21.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Riaz M, Mahmood Z, Shahid M, Saeed MU, Tahir IM, Shah SA, et al. Impact of reactive oxygen species on antioxidant capacity of male reproductive system. Int J Immunopathol Pharmacol. 2016; 29: 421-425. PubMed PMID: 26684624; PubMed Central PMCID: PMC5806750. Available from: https://doi.org/10.1177/0394632015608994 22.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Pant N, Banerjee AK, Pandey S, Mathur N, Saxena DK, Srivastava SP. Correlation of lead and cadmium in human seminal plasma with seminal vesicle and prostatic markers. Hum Exp Toxicol. 2003; 22: 125-128. PubMed PMID: 12723892. Available from: https://doi.org/10.1191/0960327103ht336oa 23.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Antonouli S, Di Nisio V, Messini C, Samara M, Salumets A, Daponte A, et al. Sperm plasma membrane ion transporters and male fertility potential: A perspective under the prism of cryopreservation. Cryobiology. 2024; 114: 104845. PubMed PMID: 38184269. Available from: https://doi.org/10.1016/j.cryobiol.2023.104845 24.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Galeska E, Wrzecinska M, Kowalczyk A, Araujo JP. Reproductive consequences of electrolyte disturbances in domestic animals. Biology (Basel). 2022; 11: PubMed PMID: 36101387; PubMed Central PMCID: PMC9312130. Available from: https://doi.org/10.3390/biology11071006 25.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Chao HH, Zhang Y, Dong PY, Gurunathan S, Zhang XF. Comprehensive review on the positive and negative effects of various important regulators on male spermatogenesis and fertility. Front Nutr. 2022; 9: 1063510. PubMed PMID: 36726821; PubMed Central PMCID: PMC9884832. Available from: https://doi.org/10.3389/fnut.2022.1063510 26.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Jimenez T, McDermott JP, Sanchez G, Blanco G. Na,k-atpase alpha4 isoform is essential for sperm fertility. Proc Natl Acad Sci U S A. 2011; 108: 644-649. PubMed PMID: 21187400; PubMed Central PMCID: PMC3021039. Available from: https://doi.org/10.1073/pnas.1016902108 27.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Beigi Harchegani A, Dahan H, Tahmasbpour E, Bakhtiari Kaboutaraki H, Shahriary A. Effects of zinc deficiency on impaired spermatogenesis and male infertility: The role of oxidative stress, inflammation and apoptosis. Hum Fertil (Camb). 2020; 23: 5-16. PubMed PMID: 30129823. Available from: https://doi.org/10.1080/14647273.2018.1494390 28.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Marin de Jesus S, Vigueras-Villasenor RM, Cortes-Barberena E, Hernandez-Rodriguez J, Montes S, Arrieta-Cruz I, et al. Zinc and its impact on the function of the testicle and epididymis. Int J Mol Sci. 2024; 25: PubMed PMID: 39201677; PubMed Central PMCID: PMC11354358. Available from: https://doi.org/10.3390/ijms25168991 29.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Yuan S, Zhang Y, Dong PY, Chen Yan YM, Liu J, Zhang BQ, et al. A comprehensive review on potential role of selenium, selenoproteins and selenium nanoparticles in male fertility. Heliyon. 2024; 10: e34975. PubMed PMID: 39144956; PubMed Central PMCID: PMC11320318. Available from: https://doi.org/10.1016/j.heliyon.2024.e34975 30.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Kim JJ, Kim YS, Kumar V. Heavy metal toxicity: An update of chelating therapeutic strategies. J Trace Elem Med Biol. 2019; 54: 226-231. PubMed PMID: 31109617. Available from: https://doi.org/10.1016/j.jtemb.2019.05.003 31.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fashola MO, Ngole-Jeme VM, Babalola OO. Heavy metal pollution from gold mines: Environmental effects and bacterial strategies for resistance. Int J Environ Res Public Health. 2016; 13: PubMed PMID: 27792205; PubMed Central PMCID: PMC5129257. Available from: https://doi.org/10.3390/ijerph13111047 32.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Abd Elnabi MK, Elkaliny NE, Elyazied MM, Azab SH, Elkhalifa SA, Elmasry S, et al. Toxicity of heavy metals and recent advances in their removal: A review. Toxics. 2023; 11: PubMed PMID: 37505546; PubMed Central PMCID: PMC10384455. Available from: https://doi.org/10.3390/toxics11070580 33.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fan Y, Jiang X, Xiao Y, Li H, Chen J, Bai W. Natural antioxidants mitigate heavy metal induced reproductive toxicity: Prospective mechanisms and biomarkers. Crit Rev Food Sci Nutr. 2024; 64: 11530-11542. PubMed PMID: 37526321. Available from: https://doi.org/10.1080/10408398.2023.2240399 34.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Wdowiak N, Wojtowicz K, Wdowiak-Filip A, Pucek W, Wrobel A, Wrobel J, et al. Environmental factors as the main hormonal disruptors of male fertility. J Clin Med. 2024; 13: PubMed PMID: 38610751; PubMed Central PMCID: PMC11012640. Available from: https://doi.org/10.3390/jcm13071986 35.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Dai P, Zou M, Cai Z, Zeng X, Zhang X, Liang M. Ph homeodynamics and male fertility: A coordinated regulation of acid-based balance during sperm journey to fertilization. Biomolecules. 2024; 14: PubMed PMID: 38927088; PubMed Central PMCID: PMC11201807. Available from: https://doi.org/10.3390/biom14060685 36.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Quinn PJ, White IG, Wirrick BR. Studies of the distribution of the major cations in semen and male accessory secretions. J Reprod Fertil. 1965; 10: 379-388. PubMed PMID: 5851440. Available from: https://doi.org/10.1530/jrf.0.0100379 37.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Alavi SM, Cosson J. Sperm motility in fishes. (ii) effects of ions and osmolality: A review. Cell Biol Int. 2006; 30: 1-14. PubMed PMID: 16278089. Available from: https://doi.org/10.1016/j.cellbi.2005.06.004 38.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Rastogi R, Su J, Mahalingam A, Clark J, Sung S, Hope T, et al. Engineering and characterization of simplified vaginal and seminal fluid simulants. Contraception. 2016; 93: 337-346. PubMed PMID: 26585883; PubMed Central PMCID: PMC4863460. Available from: https://doi.org/10.1016/j.contraception.2015.11.008 39.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Rosecrans RR, Jeyendran RS, Perez-Pelaez M, Kennedy WP. Comparison of biochemical parameters of human blood serum and seminal plasma. Andrologia. 1987; 19: 625-628. PubMed PMID: 3434852. Available from: https://doi.org/10.1111/j.1439-0272.1987.tb01913.x 40.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fernandez-Fuertes B. Review: The role of male reproductive tract secretions in ruminant fertility. Animal. 2023; 17 Suppl 1: 100773. PubMed PMID: 37567680. Available from: https://doi.org/10.1016/j.animal.2023.100773 41.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Clases D, Gonzalez de Vega R. Facets of icp-ms and their potential in the medical sciences-part 1: Fundamentals, stand-alone and hyphenated techniques. Anal Bioanal Chem. 2022; 414: 7337-7361. PubMed PMID: 36028724; PubMed Central PMCID: PMC9482897. Available from: https://doi.org/10.1007/s00216-022-04259-1 42.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Binder GA, Metcalf R, Atlas Z, Daniel KG. Evaluation of digestion methods for analysis of trace metals in mammalian tissues and nist 1577c. Anal Biochem. 2018; 543: 37-42. PubMed PMID: 29175137. Available from: https://doi.org/10.1016/j.ab.2017.11.016 43.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Jecht EW, Poon CH. Preparation of sperm-free seminal plasma from human semen. Fertil Steril. 1975; 26: 1-5. PubMed PMID: 1109935. Available from: https://doi.org/10.1016/s0015-0282(16)40868-x 44.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Padilla L, Barranco I, Parrilla I, Lucas X, Rodriguez-Martinez H, Roca J. Measurable cytokine concentrations in pig seminal plasma are modified by semen handling and storage. Biology (Basel). 2020; 9: PubMed PMID: 32906591; PubMed Central PMCID: PMC7565580. Available from: https://doi.org/10.3390/biology9090276 45.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mendiola J, Moreno JM, Roca M, Vergara-Juarez N, Martinez-Garcia MJ, Garcia-Sanchez A, et al. Relationships between heavy metal concentrations in three different body fluids and male reproductive parameters: A pilot study. Environ Health. 2011; 10: 6. PubMed PMID: 21247448; PubMed Central PMCID: PMC3036599. Available from: https://doi.org/10.1186/1476-069X-10-6 46.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Živković T, Tariba B, Pizent A. Multielement analysis of human seminal plasma by octopole reaction cell icp-ms. J Anal At Spectrom. 2014; 29: 2114-2126. Available from: https://doi.org/10.1039/c4ja00166d 47.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Hamdi SM, Sanchez E, Garimbay D, Albarede S. External quality assessment program for biochemical assays of human seminal plasma: A french 6-years experience. Basic Clin Androl. 2020; 30: 18. PubMed PMID: 33292159; PubMed Central PMCID: PMC7670731. Available from: https://doi.org/10.1186/s12610-020-00116-2 48.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Verze P, Cai T, Lorenzetti S. The role of the prostate in male fertility, health and disease. Nat Rev Urol. 2016; 13: 379-386. PubMed PMID: 27245504. Available from: https://doi.org/10.1038/nrurol.2016.89 49.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Noda T, Ikawa M. Physiological function of seminal vesicle secretions on male fecundity. Reprod Med Biol. 2019; 18: 241-246. PubMed PMID: 31312102; PubMed Central PMCID: PMC6613004. Available from: https://doi.org/10.1002/rmb2.12282 50.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Drake RR, White KY, Fuller TW, Igwe E, Clements MA, Nyalwidhe JO, et al. Clinical collection and protein properties of expressed prostatic secretions as a source for biomarkers of prostatic disease. J Proteomics. 2009; 72: 907-917. PubMed PMID: 19457353; PubMed Central PMCID: PMC2720443. Available from: https://doi.org/10.1016/j.jprot.2009.01.007 51.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Healy MW, Yauger BJ, James AN, Jezior JR, Parker P, Dean RC. Seminal vesicle sperm aspiration from wounded warriors. Fertil Steril. 2016; 106: 579-583. PubMed PMID: 27341990. Available from: https://doi.org/10.1016/j.fertnstert.2016.05.028 52.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ndovi TT, Parsons T, Choi L, Caffo B, Rohde C, Hendrix CW. A new method to estimate quantitatively seminal vesicle and prostate gland contributions to ejaculate. Br J Clin Pharmacol. 2007; 63: 404-420. PubMed PMID: 17076697; PubMed Central PMCID: PMC2203235. Available from: https://doi.org/10.1111/j.1365-2125.2006.02791.x 53.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Valsa J, Skandhan KP, Khan PS, Sumangala B, Gondalia M. Split ejaculation study: Semen parameters and calcium and magnesium in seminal plasma. Cent European J Urol. 2012; 65: 216-218. PubMed PMID: 24578965; PubMed Central PMCID: PMC3921810. Available from: https://doi.org/10.5173/ceju.2012.04.art7 54.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bjorndahl L. What is required for better progress in clinical and scientific andrology involving sperm assessments? Asian J Androl. 2024; 26: 229-232. PubMed PMID: 38265240; PubMed Central PMCID: PMC11156447. Available from: https://doi.org/10.4103/aja202380 55.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Nagai A, Watanabe M, Nasu Y, Iguchi H, Kusumi N, Kumon H. Analysis of human ejaculation using color doppler ultrasonography: A comparison between antegrade and retrograde ejaculation. Urology. 2005; 65: 365-368. PubMed PMID: 15708054. Available from: https://doi.org/10.1016/j.urology.2004.09.016 56.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bjorndahl L, Kvist U. Sequence of ejaculation affects the spermatozoon as a carrier and its message. Reprod Biomed Online. 2003; 7: 440-448. PubMed PMID: 14656406. Available from: https://doi.org/10.1016/s1472-6483(10)61888-3 57.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Anamthathmakula P, Winuthayanon W. Mechanism of semen liquefaction and its potential for a novel non-hormonal contraceptiondagger. Biol Reprod. 2020; 103: 411-426. PubMed PMID: 32529252; PubMed Central PMCID: PMC7523691. Available from: https://doi.org/10.1093/biolre/ioaa075 58.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Lindholmer C. Survival of human spermatozoa in different fractions of split ejaculate. Fertil Steril. 1973; 24: 521-526. PubMed PMID: 4715227. Available from: https://doi.org/10.1016/S0015-0282(16)39792-8 59.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Hebles M, Dorado M, Gallardo M, Gonzalez-Martinez M, Sanchez-Martin P. Seminal quality in the first fraction of ejaculate. Syst Biol Reprod Med. 2015; 61: 113-116. PubMed PMID: 25547665. Available from: https://doi.org/10.3109/19396368.2014.999390 60.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Pourian MR, Kvist U, Bjorndahl L, Oliw EH. Rapid and slow hydroxylators of seminal e prostaglandins among men in barren unions. Andrologia. 1995; 27: 71-79. PubMed PMID: 7598230. Available from: https://doi.org/10.1111/j.1439-0272.1995.tb01075.x 61.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Robert M, Gagnon C. Purification and characterization of the active precursor of a human sperm motility inhibitor secreted by the seminal vesicles: Identity with semenogelin. Biol Reprod. 1996; 55: 813-821. PubMed PMID: 8879494. Available from: https://doi.org/10.1095/biolreprod55.4.813 62.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Smyth SP, Nixon B, Anderson AL, Murray HC, Martin JH, MacDougall LA, et al. Elucidation of the protein composition of mouse seminal vesicle fluid. Proteomics. 2022; 22: e2100227. PubMed PMID: 35014747. Available from: https://doi.org/10.1002/pmic.202100227 63.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Yamasaki K, Yoshida K, Yoshiike M, Shimada K, Nishiyama H, Takamizawa S, et al. Relationship between semenogelins bound to human sperm and other semen parameters and pregnancy outcomes. Basic Clin Androl. 2017; 27: 15. PubMed PMID: 28794880; PubMed Central PMCID: PMC5547539. Available from: https://doi.org/10.1186/s12610-017-0059-6 64.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Elzanaty S, Richthoff J, Malm J, Giwercman A. The impact of epididymal and accessory sex gland function on sperm motility. Hum Reprod. 2002; 17: 2904-2911. PubMed PMID: 12407047. Available from: https://doi.org/10.1093/humrep/17.11.2904 65.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Preiano M, Correnti S, Butt TA, Viglietto G, Savino R, Terracciano R. Mass spectrometry-based untargeted approaches to reveal diagnostic signatures of male infertility in seminal plasma: A new laboratory perspective for the clinical management of infertility? Int J Mol Sci. 2023; 24: PubMed PMID: 36901856; PubMed Central PMCID: PMC10002484. Available from: https://doi.org/10.3390/ijms24054429 66.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Amelar RD, Hotchkiss RS. The split ejaculate: Its use in the management of male infertility. Fertil Steril. 1965; 16: 46-60. PubMed PMID: 14256101. Available from: https://doi.org/10.1016/S0015-0282(16)35466-8 67.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Amelar RD, Dubin L. A new method of promoting fertility. Obstet Gynecol. 1975; 45: 56-59. PubMed PMID: 1110820. Available from: https://journals.lww.com/greenjournal/abstract/1975/01000/a_new_method_of_promoting_fertility.13.aspx 68.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Johnsen O, Eliasson R. Evaluation of a commercially available kit for the colorimetric determination of zinc in human seminal plasma. Int J Androl. 1987; 10: 435-440. PubMed PMID: 3610354. Available from: https://doi.org/10.1111/j.1365-2605.1987.tb00216.x 69.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Van Dreden P, Richard P, Gonzales J. Fructose and proteins in human semen. Andrologia. 1989; 21: 576-579. PubMed PMID: 2619103. Available from: https://doi.org/10.1111/j.1439-0272.1989.tb02474.x 70.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Laffin RJ, Chan DW, Tanasijevic MJ, Fischer GA, Markus W, Miller J, et al. Hybritech total and free prostate-specific antigen assays developed for the beckman coulter access automated chemiluminescent immunoassay system: A multicenter evaluation of analytical performance. Clin Chem. 2001; 47: 129-132. PubMed PMID: 11148190. Available from: https://doi.org/10.1093/clinchem/47.1.129 71.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Comhaire FH, Vermeulen L, Pieters O. Study of the accuracy of physical and biochemical markers in semen to detect infectious dysfunction of the accessory sex glands. J Androl. 1989; 10: 50-53. PubMed PMID: 2565326. Available from: https://doi.org/10.1002/j.1939-4640.1989.tb00060.x 72.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Lu JC. [automatic detection and clinical application of semen biochemical markers]. Zhonghua Nan Ke Xue. 2018; 24: 291-296 (In Chinese). PubMed PMID: 30168946. Available from: https://doi.org/10.13263/j.cnki.nja.2018.04.001 73.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Andrade-Rocha FT. Physical analysis of ejaculate to evaluate the secretory activity of the seminal vesicles and prostate. Clin Chem Lab Med. 2005; 43: 1203-1210. PubMed PMID: 16232086. Available from: https://doi.org/10.1515/CCLM.2005.208 74.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Zhang H, Zhou XP. The effect of neutral alpha-glucosidase on semen parameters. Urol Int. 2024; 108: 479-486. PubMed PMID: 38735284. Available from: https://doi.org/10.1159/000539218 75.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Yuan Q, Hong R, Ni Y, Jiang M, Liu J, Chen Z, et al. Correlation between seminal plasma biochemical markers and semen parameters in idiopathic oligoasthenoteratospermia: Identification of biomarkers for l-carnitine therapy. Front Endocrinol (Lausanne). 2024; 15: 1330629. PubMed PMID: 38532897; PubMed Central PMCID: PMC10963428. Available from: https://doi.org/10.3389/fendo.2024.1330629 76.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Smits RM, Mackenzie-Proctor R, Yazdani A, Stankiewicz MT, Jordan V, Showell MG. Antioxidants for male subfertility. Cochrane Database Syst Rev. 2019; 3: CD007411. PubMed PMID: 30866036; PubMed Central PMCID: PMC6416049. Available from: https://doi.org/10.1002/14651858.CD007411.pub4 77.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bergamo P, Volpe MG, Lorenzetti S, Mantovani A, Notari T, Cocca E, et al. Human semen as an early, sensitive biomarker of highly polluted living environment in healthy men: A pilot biomonitoring study on trace elements in blood and semen and their relationship with sperm quality and redox status. Reprod Toxicol. 2016; 66: 1-9. PubMed PMID: 27592743. Available from: https://doi.org/10.1016/j.reprotox.2016.07.018 78.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Lettieri G, Marra F, Moriello C, Prisco M, Notari T, Trifuoggi M, et al. Molecular alterations in spermatozoa of a family case living in the land of fires. A first look at possible transgenerational effects of pollutants. Int J Mol Sci. 2020; 21: PubMed PMID: 32933216; PubMed Central PMCID: PMC7555199. Available from: https://doi.org/10.3390/ijms21186710 79.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Guzikowski W, Szynkowska MI, Motak-Pochrzest H, Pawlaczyk A, Sypniewski S. Trace elements in seminal plasma of men from infertile couples. Arch Med Sci. 2015; 11: 591-598. PubMed PMID: 26170853; PubMed Central PMCID: PMC4495155. Available from: https://doi.org/10.5114/aoms.2015.52363 80.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Chen G, Feng Y, Yang R, Li H, Huang Z, Li Z, et al. Association between zinc ion concentrations in seminal plasma and sperm quality: A chinese cross-sectional study. Biol Trace Elem Res. 2024; PubMed PMID: 39361119. Available from: https://doi.org/10.1007/s12011-024-04370-7 81.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Chiba M, Shinohara A. [trace elements and reproduction]. Journal of the Vitamin Society of Japan. 2008; 82: 25-33 (In Japanese). Available from: https://doi.org/10.20632/vso.82.1_25 82.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Slivkova J, Popelkova M, Massanyi P, Toporcerova S, Stawarz R, Formicki G, et al. Concentration of trace elements in human semen and relation to spermatozoa quality. J Environ Sci Health A Tox Hazard Subst Environ Eng. 2009; 44: 370-375. PubMed PMID: 19184704. Available from: https://doi.org/10.1080/10934520802659729 83.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Minguez-Alarcon L, Mendiola J, Roca M, Lopez-Espin JJ, Guillen JJ, Moreno JM, et al. Correlations between different heavy metals in diverse body fluids: Studies of human semen quality. Adv Urol. 2012; 2012: 420893. PubMed PMID: 22312326; PubMed Central PMCID: PMC3270542. Available from: https://doi.org/10.1155/2012/420893 84.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Abed A, Jarad A. Significance of some trace elements in semen of infertile men. Ibnosina Journal of Medicine and Biomedical Sciences. 2022; 06: 145-151. Available from: https://doi.org/10.4103/1947-489x.210375 85.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Waheed MM, Meligy A, Alhaider AK, Ghoneim IM. Relation of seminal plasma trace mineral in the arabian stallion's semen with the semen characteristics and subsequent fertility. Heliyon. 2022; 8: e11128. PubMed PMID: 36303913; PubMed Central PMCID: PMC9593185. Available from: https://doi.org/10.1016/j.heliyon.2022.e11128 86.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Yin T, Ji D, Su X, Zhou X, Wang X, He S, et al. Using bayesian and weighted regression to evaluate the association of idiopathic oligoastenoteratozoospermia with seminal plasma metal mixtures. Chemosphere. 2024; 351: 141202. PubMed PMID: 38237779. Available from: https://doi.org/10.1016/j.chemosphere.2024.141202 87.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Liu K, Mao X, Pan F, Chen Y, An R. Correlation analysis of sperm DNA fragmentation index with semen parameters and the effect of sperm dfi on outcomes of art. Sci Rep. 2023; 13: 2717. PubMed PMID: 36792684; PubMed Central PMCID: PMC9931767. Available from: https://doi.org/10.1038/s41598-023-28765-z