Topological Susceptibility under Gradient Flow

We study the impact of the Gradient Flow on the topology in various models of lattice field theory. The topological susceptibility $\chi_{\rm t}$ is measured directly, and by the slab method, which is based on the topological content of sub-volumes ("slabs") and estimates $\chi_{\rm t}$ even when the system remains trapped in a fixed topological sector. The results obtained by both methods are essentially consistent, but the impact of the Gradient Flow on the characteristic quantity of the slab method seems to be different in 2-flavour QCD and in the 2d O(3) model. In the latter model, we further address the question whether or not the Gradient Flow leads to a finite continuum limit of the topological susceptibility (rescaled by the correlation length squared, $\xi^{2}$). This ongoing study is based on direct measurements of $\chi_{\rm t}$ in $L \times L$ lattices, at $L/\xi \simeq 6$.Comment: 8 pages, LaTex, 5 figures, talk presented at the 35th International Symposium on Lattice Field Theory, June 18-24, 2017, Granada, Spai

Activating transcriptional factor 4 correlated with obesity and insulin resistance in polycystic ovary syndrome

PCOS is a systemic disorder that is commonly characterized by insulin resistance (IR). ATF4 participates in the regulation of energy homeostasis and glucose metabolism, but its role in PCOS remains unclear. In this study, we found that ATF4 was highly expressed in human granulosa cells (hGCs) of PCOS patients with obesity and IR. Thus, we performed Spearman's correlation analysis to further investigate the correlation between ATF4 expression and obesity, lipometabolic disorders, or IR in PCOS. We found that increased ATF4 was an important trigger for lipid accumulation and abnormal insulin signal transduction in PCOS. In cultured KGN cells, insulin positively regulated the mRNA and protein abundance of ATF4. Overexpression of ATF4 significantly impaired insulin-stimulated phosphorylation of AKT. Collectively, our findings provided a novel insight into the molecular mechanisms underlying the occurrence and development of PCOS, implying that ATF4 may be a new molecular target for PCOS therapy.</p

Data_Sheet_1_Serum Sex Hormone Binding Globulin Concentration as a Predictor of Ovarian Response During Controlled Ovarian Hyperstimulation.docx

Purpose: Serum concentrations of sex hormone binding globulin (SHBG), a glycated homodimeric plasma transport protein, correlate positively with the total number of follicles in women with infertility. However, the relationship between serum SHBG concentrations and the ovarian response during controlled ovarian hyperstimulation (COH) and whether this relationship differs between women with and without polycystic ovary syndrome (PCOS) remains unclear.Methods: The study cohort included 120 participants (60 non-PCOS and 60 PCOS) undergoing in vitro fertilization. Serum samples were collected from each participant every 2–3 days during the COH cycle. The concentrations of serum SHBG and other sex hormones were determined to investigate the relationship between serum SHBG concentrations and the ovarian response in women with and without PCOS.Results: We found that the serum SHBG concentration was positively correlated with the ovarian response in non-PCOS patients but not in PCOS patients.Conclusion: The serum SHBG concentration may be clinically useful as a predictor of the ovarian response during COH in patients without PCOS.</p

Table_2_Polycystic Ovary Syndrome: Novel and Hub lncRNAs in the Insulin Resistance-Associated lncRNA–mRNA Network.docx

Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of the skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA–mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of lncRNA RP11-151A6.4 in ovarian granulosa cells was increased in patients with PCOS compared with that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, RP11-151A6.4 was identified as a hub lncRNA based on IRLMN and WGCNA and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess, and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.</p

Image_1_Continuous Light-Induced PCOS-Like Changes in Reproduction, Metabolism, and Gut Microbiota in Sprague-Dawley Rats.TIF

The interplay between genetic and environmental risk factors contributes to the pathogenesis of metabolic disease. Polycystic ovary syndrome (PCOS) is the most common endocrine and metabolic disorder in women of reproductive age. Circadian rhythm disruption is an important risk factor for PCOS. In this study, we evaluated the effect of circadian disorder on reproduction as well as metabolism, and determined its influence on gut microbiota in a rat model. Female Sprague Dawley (SD) rats were kept under continuous light exposure (12-h:12-h light/light cycle, L/L group) or a control cycle (12-h:12-h light/dark cycle, L/D group) for four consecutive weeks. Manifestations in endocrine hormones and metabolism were detected and gut microbiota were analyzed with the 16s rRNA gene sequencing technique. To our knowledge, this is the first study to report PCOS-like reproductive manifestation, such as anti-Müllerian hormone (AMH) elevation induced by continuous light exposure. Moreover, continuous light resulted in abnormal glucose metabolism and gut microbial community variations, including enrichment of the microbial genus of Parasutterella and reduced abundance of genus Corynebacterium, genus Odoribacter, and genus Acinetobacter. Increased Parasutterella abundance was positively correlated with serum testosterone level. A PICRUSt analysis revealed that reproductive and metabolic-related genes were enriched in rats of L/D group. In conclusion, the present study demonstrates that continuous light exposure, an important environmental factor, contributes to the occurrence and developmental progress of PCOS and changes in microbial component and structure. Continuous light exposure is one of vital causes of PCOS, which is closely related to microbial structure and functions.</p

Image_1_Polycystic Ovary Syndrome: Novel and Hub lncRNAs in the Insulin Resistance-Associated lncRNA–mRNA Network.jpg

Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of the skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA–mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of lncRNA RP11-151A6.4 in ovarian granulosa cells was increased in patients with PCOS compared with that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, RP11-151A6.4 was identified as a hub lncRNA based on IRLMN and WGCNA and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess, and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.</p

Table_3_Polycystic Ovary Syndrome: Novel and Hub lncRNAs in the Insulin Resistance-Associated lncRNA–mRNA Network.docx

Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of the skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA–mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of lncRNA RP11-151A6.4 in ovarian granulosa cells was increased in patients with PCOS compared with that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, RP11-151A6.4 was identified as a hub lncRNA based on IRLMN and WGCNA and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess, and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.</p

Data_Sheet_1_Continuous Light-Induced PCOS-Like Changes in Reproduction, Metabolism, and Gut Microbiota in Sprague-Dawley Rats.docx

The interplay between genetic and environmental risk factors contributes to the pathogenesis of metabolic disease. Polycystic ovary syndrome (PCOS) is the most common endocrine and metabolic disorder in women of reproductive age. Circadian rhythm disruption is an important risk factor for PCOS. In this study, we evaluated the effect of circadian disorder on reproduction as well as metabolism, and determined its influence on gut microbiota in a rat model. Female Sprague Dawley (SD) rats were kept under continuous light exposure (12-h:12-h light/light cycle, L/L group) or a control cycle (12-h:12-h light/dark cycle, L/D group) for four consecutive weeks. Manifestations in endocrine hormones and metabolism were detected and gut microbiota were analyzed with the 16s rRNA gene sequencing technique. To our knowledge, this is the first study to report PCOS-like reproductive manifestation, such as anti-Müllerian hormone (AMH) elevation induced by continuous light exposure. Moreover, continuous light resulted in abnormal glucose metabolism and gut microbial community variations, including enrichment of the microbial genus of Parasutterella and reduced abundance of genus Corynebacterium, genus Odoribacter, and genus Acinetobacter. Increased Parasutterella abundance was positively correlated with serum testosterone level. A PICRUSt analysis revealed that reproductive and metabolic-related genes were enriched in rats of L/D group. In conclusion, the present study demonstrates that continuous light exposure, an important environmental factor, contributes to the occurrence and developmental progress of PCOS and changes in microbial component and structure. Continuous light exposure is one of vital causes of PCOS, which is closely related to microbial structure and functions.</p

Table_4_Polycystic Ovary Syndrome: Novel and Hub lncRNAs in the Insulin Resistance-Associated lncRNA–mRNA Network.docx

Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of the skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA–mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of lncRNA RP11-151A6.4 in ovarian granulosa cells was increased in patients with PCOS compared with that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, RP11-151A6.4 was identified as a hub lncRNA based on IRLMN and WGCNA and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess, and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.</p

Table_5_Polycystic Ovary Syndrome: Novel and Hub lncRNAs in the Insulin Resistance-Associated lncRNA–mRNA Network.docx

Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of the skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA–mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of lncRNA RP11-151A6.4 in ovarian granulosa cells was increased in patients with PCOS compared with that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, RP11-151A6.4 was identified as a hub lncRNA based on IRLMN and WGCNA and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess, and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.</p