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Статті в журналах з теми "Co-regulators"

Автор: Grafiati

Опубліковано: 15 лютого 2025

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1

Shibata, Hirotaka, Sakiko Kobayashi, Isao Kurihara, Ikuo Saito, and Takao Saruta. "Nuclear Receptors and Co-Regulators in Adrenal Tumors." Hormone Research in Paediatrics 59, no. 1 (2003): 85–93. http://dx.doi.org/10.1159/000067830.

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2

Shibata, Hirotaka, Sakiko Kobayashi, Isao Kurihara, Noriko Suda, Kenichi Yokota, Ayano Murai, Yayoi Ikeda, Ikuo Saito, William E. Rainey, and Takao Saruta. "COUP‐TF and Transcriptional Co‐Regulators in Adrenal Steroidogenesis." Endocrine Research 30, no. 4 (January 2004): 795–801. http://dx.doi.org/10.1081/erc-200044042.

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3

Mannervik, Mattias. "Control of Drosophila embryo patterning by transcriptional co-regulators." Experimental Cell Research 321, no. 1 (February 2014): 47–57. http://dx.doi.org/10.1016/j.yexcr.2013.10.010.

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4

Belkina, Anna C., and Gerald V. Denis. "BET domain co-regulators in obesity, inflammation and cancer." Nature Reviews Cancer 12, no. 7 (June 22, 2012): 465–77. http://dx.doi.org/10.1038/nrc3256.

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5

Lou, Yi, Yi-Dan Chen, Fu-Rong Sun, Jun-Ping Shi, Yu Song, and Jin Yang. "Potential Regulators Driving the Transition in Nonalcoholic Fatty Liver Disease: a Stage-Based View." Cellular Physiology and Biochemistry 41, no. 1 (2017): 239–51. http://dx.doi.org/10.1159/000456061.

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Background and Aim: The incidence of nonalcoholic fatty liver disease (NAFLD), ranging from mild steatosis to hepatocellular injury and inflammation, increases with the rise of obesity. However, the implications of transcription factors network in progressive NAFLD remain to be determined. Methods: A co-regulatory network approach by combining gene expression and transcription influence was utilized to dissect transcriptional regulators in different NAFLD stages. In vivo, mice models of NAFLD were used to investigate whether dysregulated expression be undertaken by transcriptional regulators. Results: Through constructing a large-scale co-regulatory network, sample-specific regulator activity was estimated. The combinations of active regulators that drive the progression of NAFLD were identified. Next, top regulators in each stage of NAFLD were determined, and the results were validated using the different experiments and bariatric surgical samples. In particular, Adipocyte enhancer-binding protein 1 (AEBP1) showed increased transcription activity in nonalcoholic steatohepatitis (NASH). Further characterization of the AEBP1 related transcription program defined its co-regulators, targeted genes, and functional organization. The dynamics of AEBP1 and its potential targets were verified in an animal model of NAFLD. Conclusions: This study identifies putative functions for several transcription factors in the pathogenesis of NAFLD and may thus point to potential targets for therapeutic interventions.

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6

Walther, Ansgar, and Lucy White. "Rules versus Discretion in Bank Resolution." Review of Financial Studies 33, no. 12 (March 12, 2020): 5594–629. http://dx.doi.org/10.1093/rfs/hhaa032.

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Abstract Recent reforms have given regulators broad powers to “bail-in” bank creditors during financial crises. We analyze efficient bail-ins and their implementation. To preserve liquidity, regulators must avoid signaling negative private information to creditors. Therefore, optimal bail-ins in bad times only depend on public information. As a result, the optimal policy cannot be implemented if regulators have wide discretion, due to an informational time-inconsistency problem. Rules mandating tough bail-ins after bad public signals, or contingent convertible (co-co) bonds, improve welfare. We further show that bail-in and bailout policies are complementary: if bailouts are possible, then discretionary bail-ins are more effective.

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7

Cerutti, Catherine, Jing-Ru Shi, and Jean-Marc Vanacker. "Multifaceted Transcriptional Network of Estrogen-Related Receptor Alpha in Health and Disease." International Journal of Molecular Sciences 24, no. 5 (February 21, 2023): 4265. http://dx.doi.org/10.3390/ijms24054265.

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Estrogen-related receptors (ERRα, β and γ in mammals) are orphan members of the nuclear receptor superfamily acting as transcription factors. ERRs are expressed in several cell types and they display various functions in normal and pathological contexts. Amongst others, they are notably involved in bone homeostasis, energy metabolism and cancer progression. In contrast to other nuclear receptors, the activities of the ERRs are apparently not controlled by a natural ligand but they rely on other means such as the availability of transcriptional co-regulators. Here we focus on ERRα and review the variety of co-regulators that have been identified by various means for this receptor and their reported target genes. ERRα cooperates with distinct co-regulators to control the expression of distinct sets of target genes. This exemplifies the combinatorial specificity of transcriptional regulation that induces discrete cellular phenotypes depending on the selected coregulator. We finally propose an integrated view of the ERRα transcriptional network.

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8

COEN, DAVID, and MARK THATCHER. "Network Governance and Multi-level Delegation: European Networks of Regulatory Agencies." Journal of Public Policy 28, no. 1 (April 2008): 49–71. http://dx.doi.org/10.1017/s0143814x08000779.

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ABSTRACTEuropean networks of regulators in industries such as telecommunications, securities, energy and transport have been cited as important examples of the growth of network governance in Europe. Using a principal-agent perspective as a starting point, the article examines why a double delegation to networks of regulators has taken place. It looks at how and why the European Commission, national governments and independent regulatory agencies have driven the creation of networks, their institutional character and their implications for regulatory governance in Europe. It argues that problems of co-ordination were the main factor advanced to justify establishing networks of regulators. The new networks have been given a wide range of tasks and broad membership, but enjoy few formal powers or resources. They are highly dependent on the European Commission and face rivals for the task of co-ordinating European regulators. Thus in institutional terms the spread of network governance has in fact been limited.

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9

Saadoun, Samira, and Marios C. Papadopoulos. "Role of membrane complement regulators in neuromyelitis optica." Multiple Sclerosis Journal 21, no. 13 (February 19, 2015): 1644–54. http://dx.doi.org/10.1177/1352458515571446.

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Background: It is unclear why AQP4-IgG primarily causes central nervous system lesions by activating complement, but generally spares peripheral AQP4-expressing organs. Objectives: To determine whether peripheral AQP4-expressing cells are protected from complement-mediated damage by expressing complement regulators. Methods: Human tissue and cultured human cells were immunostained for aquaporin-4 (AQP4), CD46, CD55 and CD59. We also determined the vulnerability to AQP4-IgG and complement-mediated damage of astrocytes cultured alone or co-cultured with endothelial cells. Results: In normal brain, astrocyte end-feet express AQP4, but are devoid of CD46, CD55 and CD59. Immunoreactivity for CD46, CD55 and CD59 is not increased in or around neuromyelitis optica lesions. In kidney AQP4 is co-expressed with CD46 and CD55, in stomach AQP4 is co-expressed with CD46 and in skeletal muscle AQP4 is co-expressed with CD46. Astrocytes cultured alone co-express AQP4 and CD59 but, in astrocyte-endothelial co-cultures, AQP4 is found in cell processes devoid of CD59. Astrocytes co-cultured with endothelial cells are more vulnerable to AQP4-IgG and complement-mediated lysis than astrocytes cultured alone. Conclusions: Complement regulators protect peripheral organs, but not the central nervous system, from AQP4-IgG and complement-mediated damage. Our findings may explain why neuromyelitis optica primarily damages the central nervous system, but spares peripheral organs.

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10

Desai, M., J. K. Jellyman, G. Han, R. H. Lane та M. G. Ross. "Programmed regulation of rat offspring adipogenic transcription factor (PPARγ) by maternal nutrition". Journal of Developmental Origins of Health and Disease 6, № 6 (19 серпня 2015): 530–38. http://dx.doi.org/10.1017/s2040174415001440.

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We determined the protein expression of adipogenic transcription factor, peroxisome proliferator-activated receptor gamma (PPARγ) and its co-repressor and co-activator complexes in adipose tissue from the obese offspring of under- and over-nourished dams. Female rats were fed either a high-fat (60% kcal) or control (10% kcal) diet before mating, and throughout pregnancy and lactation (Mat-OB). Additional dams were 50% food-restricted from pregnancy day 10 to term [intrauterine growth-restricted (IUGR)]. Adipose tissue protein expression was analyzed in newborn and adult male offspring. Normal birth weight Mat-OB and low birth weight IUGR newborns had upregulated PPARγ with variable changes in co-repressors and co-activators. As obese adults, Mat-OB and IUGR offspring had increased PPARγ with decreased co-repressor and increased co-activator expression. Nutritionally programmed increased PPARγ expression is associated with altered expression of its co-regulators in the newborn and adult offspring. Functional studies of PPARγ co-regulators are necessary to establish their role in PPARγ-mediated programmed obesity.

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11

Ahmed, Mahmoud, Trang Huyen Lai, Trang Minh Pham, Sahib Zada, Omar Elashkar, Jin Seok Hwang, and Deok Ryong Kim. "Hierarchical regulation of autophagy during adipocyte differentiation." PLOS ONE 17, no. 1 (January 26, 2022): e0250865. http://dx.doi.org/10.1371/journal.pone.0250865.

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We previously showed that some adipogenic transcription factors such as CEBPB and PPARG directly and indirectly regulate autophagy gene expression in adipogenesis. The order and effect of these events are undetermined. In this study, we modeled the gene expression, DNA-binding of transcriptional regulators, and histone modifications during adipocyte differentiation and evaluated the effect of the regulators on gene expression in terms of direction and magnitude. Then, we identified the overlap of the transcription factors and co-factors binding sites and targets. Finally, we built a chromatin state model based on the histone marks and studied their relation to the factors’ binding. Adipogenic factors differentially regulated autophagy genes as part of the differentiation program. Co-regulators associated with specific transcription factors and preceded them to the regulatory regions. Transcription factors differed in the binding time and location, and their effect on expression was either localized or long-lasting. Adipogenic factors disproportionately targeted genes coding for autophagy-specific transcription factors. In sum, a hierarchical arrangement between adipogenic transcription factors and co-factors drives the regulation of autophagy during adipocyte differentiation.

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12

An, Sanqi, Wanxu Huang, Xiang Huang, Yixian Cun, Weisheng Cheng, Xiang Sun, Zhijun Ren, Yaxin Chen, Wenfang Chen, and Jinkai Wang. "Integrative network analysis identifies cell-specific trans regulators of m6A." Nucleic Acids Research 48, no. 4 (January 8, 2020): 1715–29. http://dx.doi.org/10.1093/nar/gkz1206.

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Abstract N6-methyladenosine (m6A) is a reversible and dynamic RNA modification in eukaryotes. However, how cells establish cell-specific m6A methylomes is still poorly understood. Here, we developed a computational framework to systematically identify cell-specific trans regulators of m6A through integrating gene expressions, binding targets and binding motifs of large number of RNA binding proteins (RBPs) with a co-methylation network constructed using large-scale m6A methylomes across diverse cell states. We applied the framework and successfully identified 32 high-confidence m6A regulators that modulated the variable m6A sites away from stop codons in a cell-specific manner. To validate them, we knocked down three regulators respectively and found two of them (TRA2A and CAPRIN1) selectively promoted the methylations of the m6A sites co-localized with their binding targets on RNAs through physical interactions with the m6A writers. Knockdown of TRA2A increased the stabilities of the RNAs with TRA2A bound near the m6A sites and decreased the viability of cells. The successful identification of m6A regulators demonstrates a powerful and widely applicable strategy to elucidate the cell-specific m6A regulators. Additionally, our discovery of pervasive trans-acting regulating of m6A provides novel insights into the mechanisms by which spatial and temporal dynamics of m6A methylomes are established.

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13

Astapova, Inna. "Role of co-regulators in metabolic and transcriptional actions of thyroid hormone." Journal of Molecular Endocrinology 56, no. 3 (April 2016): R73—R97. http://dx.doi.org/10.1530/jme-15-0246.

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Thyroid hormone (TH) controls a wide range of physiological processes through TH receptor (TR) isoforms. Classically, TRs are proposed to function as tri-iodothyronine (T3)-dependent transcription factors: on positively regulated target genes, unliganded TRs mediate transcriptional repression through recruitment of co-repressor complexes, while T3binding leads to dismissal of co-repressors and recruitment of co-activators to activate transcription. Co-repressors and co-activators were proposed to play opposite roles in the regulation of negative T3target genes and hypothalamic–pituitary–thyroid axis, but exact mechanisms of the negative regulation by TH have remained elusive. Important insights into the roles of co-repressors and co-activators in different physiological processes have been obtained using animal models with disrupted co-regulator function. At the same time, recent studies interrogating genome-wide TR binding have generated compelling new data regarding effects of T3, local chromatin structure, and specific response element configuration on TR recruitment and function leading to the proposal of new models of transcriptional regulation by TRs. This review discusses data obtained in various mouse models with manipulated function of nuclear receptor co-repressor (NCoR or NCOR1) and silencing mediator of retinoic acid receptor and thyroid hormone receptor (SMRT or NCOR2), and family of steroid receptor co-activators (SRCs also known as NCOAs) in the context of TH action, as well as insights into the function of co-regulators that may emerge from the genome-wide TR recruitment analysis.

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14

Jiang, Junfeng, Peilin Jia, Zhongming Zhao, and Bairong Shen. "Key regulators in prostate cancer identified by co-expression module analysis." BMC Genomics 15, no. 1 (2014): 1015. http://dx.doi.org/10.1186/1471-2164-15-1015.

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15

Levin, Barry E., and Thomas A. Lutz. "Amylin and Leptin: Co-Regulators of Energy Homeostasis and Neuronal Development." Trends in Endocrinology & Metabolism 28, no. 2 (February 2017): 153–64. http://dx.doi.org/10.1016/j.tem.2016.11.004.

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16

Takada, Ichiro, Naoya Tsuji, Min-Young Youn, Sally Fujiyama, Maiko Okada, Yuuki Imai, Shino Kondo, Hirochika Kitakawa, Hisataka Yasuda, and Shigeaki Kato. "Purification and identification of estrogen receptor alpha co-regulators in osteoclasts." Annals of the New York Academy of Sciences 1192, no. 1 (April 2010): 201–7. http://dx.doi.org/10.1111/j.1749-6632.2009.05215.x.

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17

Chatziantoniou, Angeliki, and Apostolos Zaravinos. "Signatures of Co-Deregulated Genes and Their Transcriptional Regulators in Lung Cancer." International Journal of Molecular Sciences 23, no. 18 (September 18, 2022): 10933. http://dx.doi.org/10.3390/ijms231810933.

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Despite the significant progress made towards comprehending the deregulated signatures in lung cancer, these vary from study to study. We reanalyzed 25 studies from the Gene Expression Omnibus (GEO) to detect and annotate co-deregulated signatures in lung cancer and in single-gene or single-drug perturbation experiments. We aimed to decipher the networks that these co-deregulated genes (co-DEGs) form along with their upstream regulators. Differential expression and upstream regulators were computed using Characteristic Direction and Systems Biology tools, including GEO2Enrichr and X2K. Co-deregulated gene expression profiles were further validated across different molecular and immune subtypes in lung adenocarcinoma (TCGA-LUAD) and lung adenocarcinoma (TCGA-LUSC) datasets, as well as using immunohistochemistry data from the Human Protein Atlas, before being subjected to subsequent GO and KEGG enrichment analysis. The functional alterations of the co-upregulated genes in lung cancer were mostly related to immune response regulating the cell surface signaling pathway, in contrast to the co-downregulated genes, which were related to S-nitrosylation. Networks of hub proteins across the co-DEGs consisted of overlapping TFs (SOX2, MYC, KAT2A) and kinases (MAPK14, CSNK2A1 and CDKs). Furthermore, using Connectivity Map we highlighted putative repurposing drugs, including valproic acid, betonicine and astemizole. Similarly, we analyzed the co-DEG signatures in single-gene and single-drug perturbation experiments in lung cancer cell lines. In summary, we identified critical co-DEGs in lung cancer providing an innovative framework for their potential use in developing personalized therapeutic strategies.

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18

Fan, Weiwei, Annette R. Atkins, Ruth T. Yu, Michael Downes, and Ronald M. Evans. "Road to exercise mimetics: targeting nuclear receptors in skeletal muscle." Journal of Molecular Endocrinology 51, no. 3 (December 2013): T87—T100. http://dx.doi.org/10.1530/jme-13-0258.

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Skeletal muscle is the largest organ in the human body and is the major site for energy expenditure. It exhibits remarkable plasticity in response to physiological stimuli such as exercise. Physical exercise remodels skeletal muscle and enhances its capability to burn calories, which has been shown to be beneficial for many clinical conditions including the metabolic syndrome and cancer. Nuclear receptors (NRs) comprise a class of transcription factors found only in metazoans that regulate major biological processes such as reproduction, development, and metabolism. Recent studies have demonstrated crucial roles for NRs and their co-regulators in the regulation of skeletal muscle energy metabolism and exercise-induced muscle remodeling. While nothing can fully replace exercise, development of exercise mimetics that enhance or even substitute for the beneficial effects of physical exercise would be of great benefit. The unique property of NRs that allows modulation by endogenous or synthetic ligands makes them bona fide therapeutic targets. In this review, we present an overview of the current understanding of the role of NRs and their co-regulators in skeletal muscle oxidative metabolism and summarize recent progress in the development of exercise mimetics that target NRs and their co-regulators.

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19

Frank, Filipp, Xu Liu, and Eric Ortlund. "Glucocorticoid Receptor Condensates Link DNA-Dependent Receptor Dimerization and Transcriptional Transactivation." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A809. http://dx.doi.org/10.1210/jendso/bvab048.1646.

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Abstract The glucocorticoid receptor (GR) is a ligand-regulated transcription factor (TF) that controls the tissue- and gene-specific transactivation and transrepression of thousands of target genes. Distinct GR DNA binding sequences with activating or repressive activities have been identified, but how they modulate transcription in opposite ways is not known. We show that GR forms phase-separated condensates that specifically concentrate known co-regulators via their intrinsically disordered regions (IDRs) in vitro. A combination of dynamic, multivalent (between IDRs) and specific, stable interactions (between LxxLL motifs and the GR ligand binding domain) control the degree of recruitment. Importantly, GR DNA-binding directs the selective partitioning of co-regulators within GR condensates such that activating DNAs cause enhanced recruitment of co-activators. Our work shows that condensation controls GR function by modulating co-regulator recruitment and provides a mechanism for the up- and down-regulation of GR target genes controlled by distinct DNA recognition elements.

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20

Yfantis, Angelos, Ilias Mylonis, Georgia Chachami, Marios Nikolaidis, Grigorios D. Amoutzias, Efrosyni Paraskeva, and George Simos. "Transcriptional Response to Hypoxia: The Role of HIF-1-Associated Co-Regulators." Cells 12, no. 5 (March 3, 2023): 798. http://dx.doi.org/10.3390/cells12050798.

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The Hypoxia Inducible Factor 1 (HIF-1) plays a major role in the cellular response to hypoxia by regulating the expression of many genes involved in adaptive processes that allow cell survival under low oxygen conditions. Adaptation to the hypoxic tumor micro-environment is also critical for cancer cell proliferation and therefore HIF-1 is also considered a valid therapeutical target. Despite the huge progress in understanding regulation of HIF-1 expression and activity by oxygen levels or oncogenic pathways, the way HIF-1 interacts with chromatin and the transcriptional machinery in order to activate its target genes is still a matter of intense investigation. Recent studies have identified several different HIF-1- and chromatin-associated co-regulators that play important roles in the general transcriptional activity of HIF-1, independent of its expression levels, as well as in the selection of binding sites, promoters and target genes, which, however, often depends on cellular context. We review here these co-regulators and examine their effect on the expression of a compilation of well-characterized HIF-1 direct target genes in order to assess the range of their involvement in the transcriptional response to hypoxia. Delineating the mode and the significance of the interaction between HIF-1 and its associated co-regulators may offer new attractive and specific targets for anticancer therapy.

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21

Du, Jing, Zhong-Ling Lang, Yuan-Yuan Ma, Hua-Qiao Tan, Bai-Ling Liu, Yong-Hui Wang, Zhen-Hui Kang, and Yang-Guang Li. "Polyoxometalate-based electron transfer modulation for efficient electrocatalytic carbon dioxide reduction." Chemical Science 11, no. 11 (2020): 3007–15. http://dx.doi.org/10.1039/c9sc05392a.

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22

Nair, R. R., and D. D. Boyd. "Expression cloning of novel regulators of 92 kDa type IV collagenase expression." Biochemical Society Transactions 33, no. 5 (October 26, 2005): 1135–36. http://dx.doi.org/10.1042/bst0331135.

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Overexpression of the 92 kDa type IV collagenase (MMP-9) contributes to cancer progression. However, to date, there are few known regulators of expression of this metalloproteinase. We employed an expression library comprising 500000 cDNA clones to screen for novel regulators of MMP-9 expression. HT1080 cells were transiently co-transfected with an MMP-9 promoter-luciferase reporter and pools of the cDNA expression library. Positive-scoring pools were subdivided in secondary and tertiary screens, after which the regulatory cDNAs were identified by DNA sequencing. This brief review illustrates the utility of expression cloning in identifying specific regulators of MMP-9 expression.

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23

Trigiano, R. N., and R. A. May. "LABORATORY EXERCISES ILLUSTRATING ORGANOGENESIS AND TRANSFORMATION USING CHRYSANTHEMUM CULTIVARS." HortScience 28, no. 5 (May 1993): 467d—467. http://dx.doi.org/10.21273/hortsci.28.5.467d.

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A tissue culture laboratory exercise illustrating regeneration of whole plants from leaf segments of Chrysanthemum by organogenesis will be described. Using simple, common media, shoots can be generated in five weeks and rooted after an additional three weeks. Acclimatization of plants can be accomplished in a simple mistbed in the greenhouse. The exercise is adaptable to depict genotype differences among cultivars, optimization of shoot induction, effects of growth regulators, and experimental design. Callus is typically not formed during shoot formation; however, co-cultivation of leaf segments with a virulent strain of Agrobacterium tumefaciens produces callus autotrophic for growth regulators. Co-cultivation with a strain of disarmed A. tumefaciens harboring a NPTII construct affects regeneration of plants resistant to kanamycin.

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24

Nowak, Anna, and Jacek Wróbel. "Changes in the physiological activity of soybean (Glycine max L. Merr.) under the influence of exogenous growth regulators." Acta Agrobotanica 32, no. 2 (2015): 153–59. http://dx.doi.org/10.5586/aa.2015.012.

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In a two-year pot experiment (2008–2009) conducted at the Vegetation Hall, West Pomeranian University of Technology in Szczecin, we investigated the influence of exogenous growth regulators, i.e. indole-3-butyric acid (IBA) and 6-benzylaminopurine (BAP) and their mixture, on the activity of gas exchange and selected physiological features of soybeans (<em>Glycine max</em> L. Merr.). The experimental factors included the following Polish soybean cultivars: ‘Aldana’, ‘Progres’ and ‘Jutro’. During plant growth, CO<span><sub>2</sub></span> assimilation (A), transpiration rate (E), stomatal conductance (g<span><sub>s</sub></span>), and substomatal CO<span><sub>2</sub></span> concentration (c<span><sub>i</sub></span>) were determined. Two soybean cultivars, i.e. ‘Jutro’ and ‘Progres’, showed a significant increase in the intensity of assimilation and transpiration after using all kinds of growth regulators as compared with the control plants. It was found that the ‘Jutro’ cultivar, after using a mixture of growth regulators (IBA + BAP), was characterized by the significantly highest CO<span><sub>2</sub></span> assimilation (A) and transpiration (E) as well as the highest stomatal conductance (g<span><sub>s</sub></span>). The ‘Aldana’ cultivar, on the other hand, responded by a significant reduction in the transpiration rate, stomatal conductance and subsomatal CO<span><sub>2</sub></span> concentration. The spraying of the plants with exogenous growth regulators had a significant influence on the increase in the number of stomata and stomatal pore length, mostly on the lower epidermis of the lamina. It was also found that plants from the ‘Jutro’ and ‘Aldana’ cultivars sprayed with IBA and IBA + BAP were characterized by the highest yield, as compared with the control plants. In the case of the ‘Jutro’ cultivar, after using the growth regulators, a positive correlation was observed between the assimilation and transpiration rates and the length of stomata, which in consequence produced increased yields.

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25

Lee, Karen, and Derek Wilding. "Towards Responsiveness: Consumer and Citizen Engagement in Co-Regulatory Rule-Making in the Australian Communications Sector." Federal Law Review 49, no. 2 (February 18, 2021): 272–302. http://dx.doi.org/10.1177/0067205x21993148.

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This article begins the process of evaluating the adequacy of the procedural and substantive requirements that Australian communications regulators (and hence industry bodies) must satisfy before co-regulatory codes of practice can be registered. It considers if the procedural requirements relating to consumer and public consultation, included in the statutory frameworks that authorise and govern co-regulation in the media, online and telecommunications sectors, ensure co-regulatory rule-making is sufficiently responsive to the interests of consumers and citizens. Drawing on publicly available information about seven industry bodies that have drafted codes of practice and round table discussions with industry, consumers and regulators, the article highlights that the current engagement practices of industry bodies often fall short of the ‘democratic credentials’ of responsiveness. It suggests that the code registration criteria relating to consumer and public consultation must be overhauled if these weaknesses are to be rectified.

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26

Ioannou, Ioanna, Angeliki Chatziantoniou, Constantinos Drenios, Panayiota Christodoulou, Malamati Kourti, and Apostolos Zaravinos. "Signatures of Co-Deregulated Genes and Their Transcriptional Regulators in Kidney Cancers." International Journal of Molecular Sciences 24, no. 7 (March 31, 2023): 6577. http://dx.doi.org/10.3390/ijms24076577.

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There are several studies on the deregulated gene expression profiles in kidney cancer, with varying results depending on the tumor histology and other parameters. None of these, however, have identified the networks that the co-deregulated genes (co-DEGs), across different studies, create. Here, we reanalyzed 10 Gene Expression Omnibus (GEO) studies to detect and annotate co-deregulated signatures across different subtypes of kidney cancer or in single-gene perturbation experiments in kidney cancer cells and/or tissue. Using a systems biology approach, we aimed to decipher the networks they form along with their upstream regulators. Differential expression and upstream regulators, including transcription factors [MYC proto-oncogene (MYC), CCAAT enhancer binding protein delta (CEBPD), RELA proto-oncogene, NF-kB subunit (RELA), zinc finger MIZ-type containing 1 (ZMIZ1), negative elongation factor complex member E (NELFE) and Kruppel-like factor 4 (KLF4)] and protein kinases [Casein kinase 2 alpha 1 (CSNK2A1), mitogen-activated protein kinases 1 (MAPK1) and 14 (MAPK14), Sirtuin 1 (SIRT1), Cyclin dependent kinases 1 (CDK1) and 4 (CDK4), Homeodomain interacting protein kinase 2 (HIPK2) and Extracellular signal-regulated kinases 1 and 2 (ERK1/2)], were computed using the Characteristic Direction, as well as GEO2Enrichr and X2K, respectively, and further subjected to GO and KEGG pathways enrichment analyses. Furthermore, using CMap, DrugMatrix and the LINCS L1000 chemical perturbation databases, we highlight putative repurposing drugs, including Etoposide, Haloperidol, BW-B70C, Triamterene, Chlorphenesin, BRD-K79459005 and β-Estradiol 3-benzoate, among others, that may reverse the expression of the identified co-DEGs in kidney cancers. Of these, the cytotoxic effects of Etoposide, Catecholamine, Cyclosporin A, BW-B70C and Lasalocid sodium were validated in vitro. Overall, we identified critical co-DEGs across different subtypes in kidney cancer, and our results provide an innovative framework for their potential use in the future.

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27

Di Silvestre, Alessia, Marianna Lucafo, Sara De Iudicibus, Alessandro Ventura, Stefano Martelossi, Gabriele Stocco, and Giuliana Decorti. "Glucocorticoid Receptor Interacting Co-regulators: Putative Candidates for Future Drug Targeting Therapy." Mini-Reviews in Medicinal Chemistry 17, no. 8 (April 21, 2017): 657–66. http://dx.doi.org/10.2174/1389557516666161130094255.

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28

Gilad, Sharon. "Beyond Endogeneity: How Firms and Regulators Co-Construct the Meaning of Regulation." Law & Policy 36, no. 2 (February 20, 2014): 134–64. http://dx.doi.org/10.1111/lapo.12017.

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29

Di Gioia, Marco, and Ivan Zanoni. "Toll-like receptor co-receptors as master regulators of the immune response." Molecular Immunology 63, no. 2 (February 2015): 143–52. http://dx.doi.org/10.1016/j.molimm.2014.05.008.

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30

Grishin, Dmitry F., and Aleksey A. Moykin. "Quinones as co-initiators and regulators of the polymerisation of acrylic monomers." Mendeleev Communications 8, no. 1 (January 1998): 34–35. http://dx.doi.org/10.1070/mc1998v008n01abeh000830.

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31

Spears, Melanie, Steffi Oesterreich, Ilenia Migliaccio, Carolina Guiterrez, Susan Hilsenbeck, Mary Anne Quintayo, Johanna Pedraza, et al. "The p160 ER co-regulators predict outcome in ER negative breast cancer." Breast Cancer Research and Treatment 131, no. 2 (March 9, 2011): 463–72. http://dx.doi.org/10.1007/s10549-011-1426-1.

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32

Agatheeswaran, Subramaniam, and Soumen Chakraborty. "MEF2C and CEBPA: Possible co-regulators in chronic myeloid leukemia disease progression." International Journal of Biochemistry & Cell Biology 77 (August 2016): 165–70. http://dx.doi.org/10.1016/j.biocel.2016.06.007.

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33

Johnston, Calum, Hester J. Bootsma, Christine Aldridge, Sylvie Manuse, Nicolas Gisch, Dominik Schwudke, Peter W. M. Hermans, et al. "Co-Inactivation of GlnR and CodY Regulators Impacts Pneumococcal Cell Wall Physiology." PLOS ONE 10, no. 4 (April 22, 2015): e0123702. http://dx.doi.org/10.1371/journal.pone.0123702.

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34

Gramoun, Azza, Tetsuya Goto, Tommy Nordström, Ori D. Rotstein, Sergio Grinstein, Johan N. M. Heersche, and Morris F. Manolson. "Bone matrix proteins and extracellular acidification: Potential co-regulators of osteoclast morphology." Journal of Cellular Biochemistry 111, no. 2 (May 19, 2010): 350–61. http://dx.doi.org/10.1002/jcb.22705.

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35

Burakoff, Steven J., and Kevin J. Lafferty. "Transplantation editorial overview Antigen, co-stimulators and cytokines: regulators of allogeneic interactions." Current Opinion in Immunology 5, no. 5 (October 1993): 745–46. http://dx.doi.org/10.1016/0952-7915(93)90131-b.

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36

Minucci, Saverio, and Pier Giuseppe Pelicci. "Retinoid receptors in health and disease: co-regulators and the chromatin connection." Seminars in Cell & Developmental Biology 10, no. 2 (April 1999): 215–25. http://dx.doi.org/10.1006/scdb.1999.0303.

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37

Song, Won Min, Abdulkadir Elmas, Richard Farias, Peng Xu, Xianxiao Zhou, Benjamin Hopkins, Kuan-lin Huang, and Bin Zhang. "Abstract 6540: Multiscale protein networks: de novo aberrant protein interactions and oncogenic regulators in seven cancer types." Cancer Research 83, no. 7_Supplement (April 4, 2023): 6540. http://dx.doi.org/10.1158/1538-7445.am2023-6540.

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Abstract We conducted integrative proteomic network analyses of 687 cases across 7 cancer types including breast cancer (115 tumor samples), clear cell renal carcinoma (100 tumor samples), colorectal cancer (91 tumor samples), hepatocellular carcinoma (101 tumor samples), lung adenocarcinoma (104 tumor samples), stomach adenocarcinoma (80 tumor samples), and uterine corpus endometrial carcinoma (96 tumor samples). Using Multi-scale embedded gene co-expression network analysis (MEGENA), we constructed co-expression protein network for each cancer type, and interrogated the network topology and co-expressed protein modules. For each cancer type, we identified disease-associated pathways as co-expressed protein modules enriched for differentially expressed proteins in tumor. Comparing with respective cancer transcriptome network models, this systematically revealed proteome-specific cancer subnetworks associated with heme metabolism, DNA repair, spliceosome, oxidative phosphorylation and KRAS oncogenic signaling pahways in several cancer types. Cross-cancer comparison identified highly preserved protein modules showing robust pan-cancer interactions and identified endoplasmic reticulum-associated degradation (ERAD) and N-acetyltransferase activity as the central functional axes. Then, we utilized these network models to predict pan-cancer protein network regulators in the up-stream of disease-associated pathways. The predicted pan-cancer regulators were experimentally validated by loss-of-function to confer anti-tumor effects in diverse cancer types: lung (H847), colon (HCT116), fetal kidney (HEK293T) and breast (MDA-MB-231) cancer cells. Overall, the study was designed to provide tractable network models of cancer proteome, and unlock the further potentials to understand oncogenic regulators and mechanisms in different cancer types. Citation Format: Won Min Song, Abdulkadir Elmas, Richard Farias, Peng Xu, Xianxiao Zhou, Benjamin Hopkins, Kuan-lin Huang, Bin Zhang. Multiscale protein networks: de novo aberrant protein interactions and oncogenic regulators in seven cancer types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6540.

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38

Yin, Wencheng, Luis Mendoza, Jimena Monzon-Sandoval, Araxi O. Urrutia, and Humberto Gutierrez. "Emergence of co-expression in gene regulatory networks." PLOS ONE 16, no. 4 (April 1, 2021): e0247671. http://dx.doi.org/10.1371/journal.pone.0247671.

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Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns of coordinated or synchronous expression across independent biological samples. The functional significance of these co-expression clusters is suggested by the fact that highly coexpressed groups of genes tend to be enriched in genes involved in common functions and biological processes. While gene co-expression is widely assumed to reflect close regulatory proximity, the validity of this assumption remains unclear. Here we use a simple synthetic gene regulatory network (GRN) model and contrast the resulting co-expression structure produced by these networks with their known regulatory architecture and with the co-expression structure measured in available human expression data. Using randomization tests, we found that the levels of co-expression observed in simulated expression data were, just as with empirical data, significantly higher than expected by chance. When examining the source of correlated expression, we found that individual regulators, both in simulated and experimental data, fail, on average, to display correlated expression with their immediate targets. However, highly correlated gene pairs tend to share at least one common regulator, while most gene pairs sharing common regulators do not necessarily display correlated expression. Our results demonstrate that widespread co-expression naturally emerges in regulatory networks, and that it is a reliable and direct indicator of active co-regulation in a given cellular context.

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39

Hindley, Christopher, and Anna Philpott. "Co-ordination of cell cycle and differentiation in the developing nervous system." Biochemical Journal 444, no. 3 (May 29, 2012): 375–82. http://dx.doi.org/10.1042/bj20112040.

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During embryonic development, cells must divide to produce appropriate numbers, but later must exit the cell cycle to allow differentiation. How these processes of proliferation and differentiation are co-ordinated during embryonic development has been poorly understood until recently. However, a number of studies have now given an insight into how the cell cycle machinery, including cyclins, CDKs (cyclin-dependent kinases), CDK inhibitors and other cell cycle regulators directly influence mechanisms that control cell fate and differentiation. Conversely, examples are emerging of transcriptional regulators that are better known for their role in driving the differentiated phenotype, which also play complementary roles in controlling cell cycle progression. The present review will summarise our current understanding of the mechanisms co-ordinating the cell cycle and differentiation in the developing nervous system, where these links have been, perhaps, most extensively studied.

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40

Ronald, James, and Seth J. Davis. "Making the clock tick: the transcriptional landscape of the plant circadian clock." F1000Research 6 (June 21, 2017): 951. http://dx.doi.org/10.12688/f1000research.11319.1.

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Circadian clocks are molecular timekeepers that synchronise internal physiological processes with the external environment by integrating light and temperature stimuli. As in other eukaryotic organisms, circadian rhythms in plants are largely generated by an array of nuclear transcriptional regulators and associated co-regulators that are arranged into a series of interconnected molecular loops. These transcriptional regulators recruit chromatin-modifying enzymes that adjust the structure of the nucleosome to promote or inhibit DNA accessibility and thus guide transcription rates. In this review, we discuss the recent advances made in understanding the architecture of the Arabidopsis oscillator and the chromatin dynamics that regulate the generation of rhythmic patterns of gene expression within the circadian clock.

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41

Chagas, Vinicius S., Clarice S. Groeneveld, Kelin G. Oliveira, Sheyla Trefflich, Rodrigo C. de Almeida, Bruce A. J. Ponder, Kerstin B. Meyer, Steven J. M. Jones, A. Gordon Robertson, and Mauro A. A. Castro. "RTNduals: an R/Bioconductor package for analysis of co-regulation and inference of dual regulons." Bioinformatics 35, no. 24 (June 28, 2019): 5357–58. http://dx.doi.org/10.1093/bioinformatics/btz534.

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Abstract Motivation Transcription factors (TFs) are key regulators of gene expression, and can activate or repress multiple target genes, forming regulatory units, or regulons. Understanding downstream effects of these regulators includes evaluating how TFs cooperate or compete within regulatory networks. Here we present RTNduals, an R/Bioconductor package that implements a general method for analyzing pairs of regulons. Results RTNduals identifies a dual regulon when the number of targets shared between a pair of regulators is statistically significant. The package extends the RTN (Reconstruction of Transcriptional Networks) package, and uses RTN transcriptional networks to identify significant co-regulatory associations between regulons. The Supplementary Information reports two case studies for TFs using the METABRIC and TCGA breast cancer cohorts. Availability and implementation RTNduals is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/RTNduals/. Supplementary information Supplementary data are available at Bioinformatics online.

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42

Gauthier-Coles, Gregory, and Jason M. Sheltzer. "Paralog Co-Targeting Identifies Selective Genetic Redundancies across Cancer Types." Cancer Discovery 14, no. 12 (December 2, 2024): 2312–14. https://doi.org/10.1158/2159-8290.cd-24-1349.

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Summary:In this issue, Klingbeil and colleagues deploy a paralog co-targeting strategy to reveal microtubule affinity–regulating kinases 2 and 3 as redundant negative regulators of the Hippo pathway and potentially actionable targets in YAP/TAZ-addicted tumors.See related article by Klingbeil et.al., p. 2471

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43

Kong, E. H., A. C. W. Pike, and R. E. Hubbard. "Structure and mechanism of the oestrogen receptor." Biochemical Society Transactions 31, no. 1 (February 1, 2003): 56–59. http://dx.doi.org/10.1042/bst0310056.

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We have determined the structures of the oestrogen receptor ligand-binding domain in complex with a range of ligands and with fragments of co-regulator proteins. These structures provide insights into the structural mechanisms underlying the receptor's complex pharmacological properties and how the conformation of the receptor modulates its ability to recruit co-regulators that are necessary for transcriptional activation.

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44

Paul, Aswathy Mary, Madhavan Radhakrishna Pillai, and Rakesh Kumar. "Prognostic Significance of Dysregulated Epigenomic and Chromatin Modifiers in Cervical Cancer." Cells 10, no. 10 (October 5, 2021): 2665. http://dx.doi.org/10.3390/cells10102665.

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To broaden the understanding of the epigenomic and chromatin regulation of cervical cancer, we examined the status and significance of a set of epigenomic and chromatin modifiers in cervical cancer using computational biology. We observed that 61 of 917 epigenomic and/or chromatin regulators are differentially upregulated in human cancer, including 25 upregulated in invasive squamous cell carcinomas and 29 in cervical intraepithelial neoplasia 3 (CIN3), of which 14 are upregulated in cervical intraepithelial neoplasia 2 (CIN2). Interestingly, 57 of such regulators are uniquely upregulated in cervical cancer, but not ovarian and endometrial cancers. The observed overexpression of 57 regulators was found to have a prognostic significance in cervical cancer. The collective overexpression of these regulators, as well as its subsets belonging to specific histone modifications and corresponding top ten positively co-overexpressed genes, correlated with reduced survival of patients with high expressions of the tested overexpressed regulators compared to cases with low expressions. Using cell-dependency datasets from human cervical cancer cells, we found that 20 out of 57 epigenomic and chromatin regulators studied here appeared to be essential genes, as the depletion of these genes was accompanied by the loss in cellular viability. In brief, the results presented here provide further insights into the role of epigenomic and chromatin regulators in the oncobiology of cervical cancer and broaden the list of new potential molecules of therapeutic importance.

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45

Battilana, Giusy, Francesca Zanconato, and Stefano Piccolo. "Mechanisms of YAP/TAZ transcriptional control." Cell Stress 5, no. 11 (November 8, 2021): 167–72. http://dx.doi.org/10.15698/cst2021.11.258.

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Dysregulated gene expression is intrinsic to cell transformation, tumorigenesis and metastasis. Cancer-specific gene-expression profiles stem from gene regulatory networks fueled by genetic and epigenetic defects, and by abnormal signals of the tumor microenvironment. These oncogenic signals ultimately engage the transcriptional machinery on the cis -regulatory elements of a host of effector genes, through recruitment of transcription factors (TFs), co-activators and chromatin regulators. That said, whether gene -expression in cancer cells is the chaotic product of myriad regulations or rather a relatively ordered process orchestrated by few TFs (master regulators) has long remained enigmatic. Recent work on the YAP/TAZ co-activators has been instrumental to break new ground into this outstanding issue, revealing that tumor cells hijack growth programs that are active during development and regeneration through engagement of a small set of interconnected TFs and their nuclear partners.

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46

Grasser, Klaus D. "Chromatin-associated HMGA and HMGB proteins: versatile co-regulators of DNA-dependent processes." Plant Molecular Biology 53, no. 3 (October 2003): 281–95. http://dx.doi.org/10.1023/b:plan.0000007002.99408.ba.

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47

Wang, Yixing, and Ming Yang. "In SilicoIdentification of Co-transcribed Core Cell Cycle Regulators and Transcription Factors inArabidopsis." Journal of Integrative Plant Biology 49, no. 8 (August 2007): 1253–60. http://dx.doi.org/10.1111/j.1672-9072.2007.00547.x.

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48

Koury, Elizabeth J., Aaron C. Pawlyk, Thomas J. Berrodin, Christa L. Smolenski, Sunil Nagpal, and Darlene C. Deecher. "Characterization of ligands for thyroid receptor subtypes and their interactions with co-regulators." Steroids 74, no. 2 (February 2009): 270–76. http://dx.doi.org/10.1016/j.steroids.2008.11.014.

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49

Bøyum, Arne, Knut Kristian Skrede, Oddvar Myhre, Vivi-Ann Tennfjord, Christine Gran Neurauter, Helge Tolleshaug, Eirunn Knudsen, Per Kristian Opstad, Magnar Bjørås, and Haakon B. Benestad. "Calprotectin (S100A8/S100A9) and Myeloperoxidase: Co-Regulators of Formation of Reactive Oxygen Species." Toxins 2, no. 1 (January 20, 2010): 95–115. http://dx.doi.org/10.3390/toxins2010095.

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50

Alsaleh, Ibrahim, and Lingling Fan. "Multi-Time Co-optimization of Voltage Regulators and Photovoltaics in Unbalanced Distribution Systems." IEEE Transactions on Sustainable Energy 12, no. 1 (January 2021): 482–91. http://dx.doi.org/10.1109/tste.2020.3007045.

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