Academic literature on the topic 'PGA460 model'

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Journal articles on the topic "PGA460 model"

1

Dashper, S. G., A. Hendtlass, N. Slakeski, et al. "Characterization of a Novel Outer Membrane Hemin-Binding Protein of Porphyromonas gingivalis." Journal of Bacteriology 182, no. 22 (2000): 6456–62. http://dx.doi.org/10.1128/jb.182.22.6456-6462.2000.

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ABSTRACT Porphyromonas gingivalis is a gram-negative, anaerobic coccobacillus that has been implicated as a major etiological agent in the development of chronic periodontitis. In this paper, we report the characterization of a protein, IhtB (iron heme transport; formerly designated Pga30), that is an outer membrane hemin-binding protein potentially involved in iron assimilation by P. gingivalis. IhtB was localized to the cell surface of P. gingivalis by Western blot analysis of a Sarkosyl-insoluble outer membrane preparation and by immunocytochemical staining of whole cells using IhtB peptide-specific antisera. The protein, released from the cell surface, was shown to bind to hemin using hemin-agarose. The growth of heme-limited, but not heme-replete, P. gingivalis cells was inhibited by preincubation with IhtB peptide-specific antisera. TheihtB gene was located between an open reading frame encoding a putative TonB-linked outer membrane receptor and three open reading frames that have sequence similarity to ATP binding cassette transport system operons in other bacteria. Analysis of the deduced amino acid sequence of IhtB showed significant similarity to theSalmonella typhimurium protein CbiK, a cobalt chelatase that is structurally related to the ATP-independent family of ferrochelatases. Molecular modeling indicated that the IhtB amino acid sequence could be threaded onto the CbiK fold with the IhtB structural model containing the active-site residues critical for chelatase activity. These results suggest that IhtB is a peripheral outer membrane chelatase that may remove iron from heme prior to uptake byP. gingivalis.
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2

Bergman, M., N. Tundia, A. Bryant, et al. "POS0436 PATIENT CHARACTERISTICS AND OUTCOMES IN PATIENTS WITH RHEUMATOID ARTHRITIS TREATED WITH UPADACITINIB: THE OM1 RA REGISTRY." Annals of the Rheumatic Diseases 80, Suppl 1 (2021): 446.2–447. http://dx.doi.org/10.1136/annrheumdis-2021-eular.172.

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Background:Upadacitinib (UPA) has demonstrated efficacy in the treatment of rheumatoid arthritis (RA) in randomized controlled trials,1-6 but there are limited data available on its real-world use and effectiveness in patients with RA.Objectives:To describe the characteristics and clinical outcomes at 3 months among real-world patients with RA initiating UPA.Methods:The data source for this study was the OM1 RA Registry, a subset of the OM1 Real-World Data Cloud (OM1, Inc, Boston, MA, US), a large, linked clinical and administrative dataset derived from medical and pharmacy claims, electronic medical record data, and death data. This analysis includes data collected in patients who initiated UPA during or after August 2019. Patients had ≥1 prescription for UPA (index date was first UPA prescription), were ≥18 years of age at index date, had ≥6 months of available data in the OM1 RA Registry prior to index date (ie, baseline period), ≥1 baseline disease activity measure, and ≥1 follow-up disease activity measure (3 or 6 months post-index). Disease activity was based on RAPID3 or CDAI. Multivariate analyses were conducted using a mixed-effects linear model adjusting for age, sex, and baseline scores. Outcomes were also assessed by therapy status (monotherapy or combination therapy) and targeted immunomodulator (TIM) use (naïve vs experienced).Results:Inclusion criteria were met by 1,102 patients, of whom 620 were on monotherapy and 482 were on combination therapy at index. Mean age was 57.7 years, 83% were female, 75% had prior treatment with a biologic, and 47% had prior treatment with a Janus kinase inhibitor. Of 651 patients with known disease activity category, 113 (17%) were in low disease activity (LDA)/remission. At baseline, overall mean±SD scores were 19.9±12.3 for CDAI, 4.5±2.4 for RAPID3, 5.7±2.8 for pain, 5.2±3.0 for fatigue, 3.1±2.7 for MDHAQ Physician Global Assessment (PGA), 5.2±2.8 for MDHAQ Patient Global Assessment (PtGA), and 3.1±2.3 for MDHAQ Functional Index. At 3 months post-UPA initiation, mean (95% CI) change in CDAI was –5.1 (–7.5 to –2.7) in the monotherapy group and –5.9 (–8.7 to –3.0) in the combination group. At 3 months, 29% (109/374) of patients were in LDA/remission and 32% (120/374) of patients showed improvement in disease activity. Of 94 patients with moderate disease at baseline, 34 (36%) were in LDA/remission at 3 months. Of 215 patients with high disease at baseline, 30 (14%) were in LDA/remission and 49 (23%) had moderate disease at 3 months. RAPID3 and other outcomes also improved at 3 months in the monotherapy and combination therapy groups (Figure 1). Improvements in disease activity were observed at 3 months and maintained at 6 months post-UPA initiation. Of 1,102 patients, 16% were TIM naïve and 84% TIM experienced. Both TIM-naïve and TIM-experienced patients achieved significant mean changes in CDAI (–5.7 [–10.8 to –0.6] and–5.0 [–7.0 to –3.0], respectively) and RAPID3 (–1.0 [–1.6 to –0.4] and –0.5 [–0.8 to –0.1]) at 3 months (Table 1). Improvements in clinical outcomes were maintained at 6 months in both TIM-naïve and TIM-experienced patients.Conclusion:Significant improvements in disease activity were consistently observed at 3 months and maintained at 6 months post-UPA initiation regardless of monotherapy, combination therapy, or prior TIM use.References:[1]Fleischmann R. Arthritis Rheumatol. 2019;71:1788–800.[2]Smolen JS. Lancet. 2019;393:2303–11.[3]Burmester GR. Lancet. 2018;382:2505–12.[4]Genovese MC. Lancet. 2018;391:2513–24.[5]van Vollenhoven R. Arthritis Rheumatol. 2020;72:1607–20.[6]Rubbert-Roth A. N Engl J Med. 2020;383:1511–21.Table 1.Change in clinical outcomes from baseline at 3 months: TIM-naïve and TIM-experienced groupsTIM naïve(N=179)TIM experienced(N=923)nMean changenMean changeCDAI36–5.7*160–5.0*RAPID367–1.0*189–0.5*Pain (VAS)76–1.5*237–0.9*Fatigue46–0.7149–0.5MDHAQ PGA65–0.7*251–0.7*MDHAQ PtGA97–0.6*383–0.3MDHAQ Functional Index72–0.7*215–0.2*Statistically significant change from baseline (P<0.05).Acknowledgements:Funding statement: Financial support for the study was provided by AbbVie. AbbVie participated in the interpretation of data, review, and approval of the abstract. All authors contributed to the development of the publication and maintained control over the final content.Acknowledgment:Medical writing services were provided by Joann Hettasch of Fishawack Facilitate Ltd, part of Fishawack Health, and funded by AbbVie.Disclosure of Interests:Martin Bergman Shareholder of: JNJ (parent of Janssen), Speakers bureau: AbbVie, Amgen, BMS, Genentech, Gilead, Janssen, Merck, Novartis, Pfizer, Regeneron, Sanofi, Sandoz, Consultant of: AbbVie, Amgen, BMS, Genentech, Gilead, Janssen, Merck, Novartis, Pfizer, Regeneron, Sanofi, Sandoz, Namita Tundia Shareholder of: AbbVie, Employee of: AbbVie, Allison Bryant: None declared, Ia Topuria: None declared, Tom Brecht: None declared, Kendall Dunlap Shareholder of: AbbVie, Employee of: AbbVie, Allan Gibofsky Shareholder of: AbbVie, Amgen, Horizon, J&J, Pfizer, Regeneron, Speakers bureau: AbbVie, Acquist, Amgen, Lilly, Merck, Pfizer, Sandoz, Samumed, Consultant of: AbbVie, Acquist, Amgen, Lilly, Merck, Pfizer, Sandoz, Samumed
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3

1Djumanov, Jamoljon Xudaykulovich 2Rajabov Farxat Farmanovich 3Jamolov Xudoyorxon Muzaffar o'g'li. "MASOFAVIY MA'LUMOT UZATISH QURILMASINI YARATISH ASOSIDA SUV RESURSLARI MONITORINGINI YURITISH APPARAT DASTURIY VOSITALARI." April 25, 2023. https://doi.org/10.5281/zenodo.7861795.

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<em>In this article, the PGA460-model equipment is used for the production of equipment in monitoring the distribution of water resources, the principle of connection and operation, installation and maintenance. Measuring systems and technologies in the production of constituent classifications and main criteria of water devices, measuring and verifying the reliability characteristics of meters - devices. Thus, the changes in this field are to achieve new results in the calculation of water resources data in innovative technologies of measurement and water management.</em>
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4

Siebinga, Olger, Arkady Zgonnikov, and David A. Abbink. "A model of dyadic merging interactions explains human drivers' behavior from control inputs to decisions." PNAS Nexus, September 24, 2024. http://dx.doi.org/10.1093/pnasnexus/pgae420.

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Abstract Safe and socially acceptable interactions with human-driven vehicles are a major challenge in automated driving. A good understanding of the underlying principles of such traffic interactions could help address this challenge. Particularly, accurate driver models could be used to inform automated vehicles in interactions. These interactions entail complex dynamic joint behaviors composed of individual driver contributions in terms of high-level decisions, safety margins, and low-level control inputs. Existing driver models typically focus on one of these aspects, limiting our understanding of the underlying principles of traffic interactions. Here, we present a communication-enabled interaction model based on risk perception, that does not assume humans are rational and explicitly accounts for communication between drivers. Our model can explain and reproduce observed human interactions in a simplified merging scenario on all three levels. Thereby improving our understanding of the underlying mechanisms of human traffic interactions and posing a step towards interaction-aware automated driving.
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5

Teslya, Alexandra, Hendrik Nunner, Vincent Buskens, and Mirjam E. Kretzschmar. "The effect of competition between health opinions on epidemic dynamics." PNAS Nexus, November 16, 2022. http://dx.doi.org/10.1093/pnasnexus/pgac260.

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Abstract Past major epidemic events showed that when an infectious disease is perceived to cause severe health outcomes, individuals modify health behavior affecting epidemic dynamics. To investigate the effect of this feedback relationship on epidemic dynamics, we developed a compartmental model that couples a disease spread framework with competition of two mutually exclusive health opinions (health-positive and health-neutral) associated with different health behaviors. The model is based on the assumption that individuals switch health opinions as a result of exposure to opinions of others through interpersonal communications. To model opinion switch rates, we considered a family of functions and identified the ones that allow health opinions to co-exist. Finally, the model includes assortative mixing by opinions. In the disease-free population, either the opinions cannot co-exist and one of them is always dominating (mono-opinion equilibrium) or there is at least one stable co-existence of opinions equilibrium. In the latter case, there is multistability between the co-existence equilibrium and the two mono-opinion equilibria. When two opinions co-exist, it depends on their distribution whether the infection can invade. If presence of the infection leads to increased switching to a health-positive opinion, the epidemic burden becomes smaller than indicated by the basic reproduction number. Additionally, a feedback between epidemic dynamics and health opinion dynamics may result in (sustained) oscillatory dynamics and a switch to a different stable opinion distribution. Our model captures feedback between spread of awareness through social interactions and infection dynamics and can serve as a basis for more elaborate individual-based models.
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del Rio-Chanona, R. Maria, Nadzeya Laurentsyeva, and Johannes Wachs. "Large language models reduce public knowledge sharing on online Q&A platforms." PNAS Nexus, September 11, 2024. http://dx.doi.org/10.1093/pnasnexus/pgae400.

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Abstract Large language models (LLMs) are a potential substitute for human-generated data and knowledge resources. This substitution, however, can present a significant problem for the training data needed to develop future models if it leads to a reduction of human-generated content. In this work, we document a reduction in activity on Stack Overflow coinciding with the release of ChatGPT, a popular LLM. To test whether this reduction in activity is specific to the introduction of this LLM we use counterfactuals involving similar human-generated knowledge resources that should not be affected by the introduction of ChatGPT to such extent. Within six months of ChatGPT's release, activity on Stack Overflow decreased by 25% relative to its Russian and Chinese counterparts, where access to ChatGPT is limited, and to similar forums for mathematics, where ChatGPT is less capable. We interpret this estimate as a lower bound of the true impact of ChatGPT on Stack Overflow. The decline is larger for posts related to the most widely used programming languages. We find no significant change in post quality, measured by peer feedback, and observe similar decreases in content creation by more and less experienced users alike. Thus, LLMs are not only displacing duplicate, low-quality, or beginner-level content. Our findings suggest that the rapid adoption of LLMs reduces the production of public data needed to train them, with significant consequences.
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Chatterjee, Sitangshu, Sylvia Tan, Changhyun Choi, et al. "Decoding roughness perception in distributed haptic devices." PNAS Nexus, October 16, 2024. http://dx.doi.org/10.1093/pnasnexus/pgae468.

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Abstract The ability to render realistic texture perception using haptic devices has been consistently challenging. A key component of texture perception is roughness. When we touch surfaces, mechanoreceptors present under the skin are activated and the information is processed by the nervous system, enabling perception of roughness/smoothness. Several distributed haptic devices capable of producing localized skin stretch have been developed with the aim of rendering realistic roughness perception; however, current state-of-the-art devices rely on device fabrication and psychophysical experimentation to determine whether a device configuration will perform as desired. Predictive models can elucidate physical mechanisms, providing insight and a more effective design iteration process. Since existing models (1, 2) are derived from responses to normal stimuli only, they cannot predict the performance of laterally actuated devices which rely on frictional shear forces to produce localized skin stretch. They are also unable to predict the augmentation of roughness perception when the actuators are spatially dispersed across the contact patch or actuated with a relative phase difference (3). In this study, we have developed a model that can predict the perceived roughness for arbitrary external stimuli and validated it against psychophysical experimental results from different haptic devices reported in literature. The model elucidates two key mechanisms: 1) The variation in the change of strain across the contact patch can predict roughness perception with strong correlation 2) The inclusion of lateral shear forces is essential to correctly predict roughness perception. Using the model can accelerate device optimization by obviating the reliance on trial-and-error approaches.
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Wei, Cao, Seyed Mostafa Jafari Raad, and Hassan Hassanzadeh. "Estimation of natural methane emissions from the largest oil sands deposits on earth." PNAS Nexus, August 11, 2023. http://dx.doi.org/10.1093/pnasnexus/pgad260.

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Abstract Worldwide methane emission by various industrial sources is one of the important human concerns due to its serious climate and air quality implications. This study investigates less-considered diffusive natural methane emissions from the world’s largest oil sands deposits. An analytical model, considering the first-order methane degradation, in combination with Monte Carlo Simulations, is used to quantitatively characterize diffusive methane emissions from Alberta’s oil sands formations. The results show that the average diffusive methane emissions from Alberta’s oil sands formations range from 1.20×10-5 to 1.56×10-4 kg/m2/year with a 90% cumulative probability. The results also indicate an annual diffusive methane emissions rate of 0.857±0.013 MtCO2e/year from Alberta’s oil sands formations. This finding suggests that natural diffusive leakages from the oil sands contribute an additional 1.659±0.025% and 5.194±0.079% to recent Canada’s 2019 and Alberta’s 2020 methane emissions estimates from the upstream oil and gas sector, respectively. The developed model combined with Monte Carlo Simulations can be used as a tool for assessing methane emissions and current inventories.
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Luo, Zhenyu, Tingkun He, Wen Yi, et al. "Advancing shipping NOx pollution estimation through a satellite-based approach." PNAS Nexus, December 11, 2023. http://dx.doi.org/10.1093/pnasnexus/pgad430.

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Abstract Estimating shipping nitrogen oxides (NOx) emissions and their associated ambient NO2 impacts is a complex and time-consuming task. In this study, a novel model called SAT-SHIP is developed to estimate regional shipping NOx emissions and their contribution to ambient NO2 concentrations in China. Unlike the traditional bottom-up approach, SAT-SHIP employs satellite observations with varying wind patterns to improve top-down emission inversion methods for individual sectors amidst irregular emission plume signals. Through SAT-SHIP, shipping NOx emissions for 17 ports in China are estimated. The results show that SAT-SHIP performed comparably to the bottom-up approach, with an R-squared value of 0.8. Additionally, SAT-SHIP reveals that the shipping sector in port areas contributes approximately 21% and 11% to NO2 concentrations in the Yangtze-River-Delta and Pearl-River-Delta areas of China, respectively, which is consistent with results from chemical transportation model simulations. This approach has practical implications for policymakers seeking to identify pollution sources and develop effective strategies to mitigate air pollution.
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Zou, Yuliang, Benjamin Maillet, Laurent Brochard, and Philippe Coussot. "Unveiling moisture transport mechanisms in cellulosic materials: Vapor vs. bound water." PNAS Nexus, December 20, 2023. http://dx.doi.org/10.1093/pnasnexus/pgad450.

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Abstract Natural textiles, hair, paper, wool, or bio-based walls possess the remarkable ability to store humidity from sweat or the environment through “bound water” absorption within nanopores, constituting up to 30% of their dry mass. The knowledge of the induced water transfers is pivotal for advancing industrial processes and sustainable practices in various fields such as wood drying, paper production and use, moisture transfers in clothes or hair, humidity regulation of bio-based construction materials, etc. However, the transport and storage mechanisms of this moisture remain poorly understood, with modeling often relying on an assumption of dominant vapor transport with an unknown diffusion coefficient. Our research addresses this knowledge gap, demonstrating the pivotal role of bound water transport within interconnected fiber networks. Notably, at low porosity, bound water diffusion supersedes vapor diffusion. By isolating diffusion processes and deriving diffusion coefficients through rigorous experimentation, we establish a comprehensive model for moisture transfer. Strikingly, our model accurately predicts the evolution of bound water's spatial distribution over time across varying porosities, as verified through Magnetic Resonance Imaging (MRI). Showing that bound water transport can be dominant over vapor transport, this work offers a change of paradigm and unprecedented control over humidity-related processes.
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