Glucose Sensing by Skeletal Myocytes Couples Nutrient Signaling to Systemic Homeostasis.

Skeletal muscle is a major site of postprandial glucose disposal. Inadequate insulin action in skeletal myocytes contributes to hyperglycemia in diabetes. Although glucose is known to stimulate insulin secretion by ß cells, whether it directly engages nutrient signaling pathways in skeletal muscle to maintain systemic glucose homeostasis remains largely unexplored. Here we identified the Baf60c-Deptor-AKT pathway as a target of muscle glucose sensing that augments insulin action in skeletal myocytes. Genetic activation of this pathway improved postprandial glucose disposal in mice, whereas its muscle-specific ablation impaired insulin action and led to postprandial glucose intolerance. Mechanistically, glucose triggers KATP channel-dependent calcium signaling, which promotes HDAC5 phosphorylation and nuclear exclusion, leading to Baf60c induction and insulin-independent AKT activation. This pathway is engaged by the anti-diabetic sulfonylurea drugs to exert their full glucose-lowering effects. These findings uncover an unexpected mechanism of glucose sensing in skeletal myocytes that contributes to homeostasis and therapeutic action.

A distinct role of STING in regulating glucose homeostasis through insulin sensitivity and insulin secretion.

Insulin resistance and ß-cell dysfunction are two main molecular bases yet to be further elucidated for type 2 diabetes (T2D). Accumulating evidence indicates that stimulator of interferon genes (STING) plays an important role in regulating insulin sensitivity. However, its function in ß-cells remains unknown. Herein, using global STING knockout (STING-/-) and ß-cell-specific STING knockout (STING-ßKO) mouse models, we revealed a distinct role of STING in the regulation of glucose homeostasis through peripheral tissues and ß-cells. Specially, although STING-/- beneficially alleviated insulin resistance and glucose intolerance induced by high-fat diet, it surprisingly impaired islet glucose-stimulated insulin secretion (GSIS). Importantly, STING is decreased in islets of db/db mice and patients with T2D, suggesting a possible role of STING in ß-cell dysfunction. Indeed, STING-ßKO caused glucose intolerance due to impaired GSIS, indicating that STING is required for normal ß-cell function. Islet transcriptome analysis showed that STING deficiency decreased expression of ß-cell function-related genes, including Glut2, Kcnj11, and Abcc8, contributing to impaired GSIS. Mechanistically, the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and cleavage under targets and tagmentation (CUT&Tag) analyses suggested that Pax6 was the transcription factor that might be associated with defective GSIS in STING-ßKO mice. Indeed, Pax6 messenger RNA and protein levels were down-regulated and its nuclear localization was lost in STING-ßKO ß-cells. Together, these data revealed a function of STING in the regulation of insulin secretion and established pathophysiological significance of fine-tuned STING within ß-cells and insulin target tissues for maintaining glucose homeostasis.

Sensitivity analysis with iterative outlier detection for systematic reviews and meta-analyses.

Meta-analysis is a widely used tool for synthesizing results from multiple studies. The collected studies are deemed heterogeneous when they do not share a common underlying effect size; thus, the factors attributable to the heterogeneity need to be carefully considered. A critical problem in meta-analyses and systematic reviews is that outlying studies are frequently included, which can lead to invalid conclusions and affect the robustness of decision-making. Outliers may be caused by several factors such as study selection criteria, low study quality, small-study effects, and so on. Although outlier detection is well-studied in the statistical community, limited attention has been paid to meta-analysis. The conventional outlier detection method in meta-analysis is based on a leave-one-study-out procedure. However, when calculating a potentially outlying study's deviation, other outliers could substantially impact its result. This article proposes an iterative method to detect potential outliers, which reduces such an impact that could confound the detection. Furthermore, we adopt bagging to provide valid inference for sensitivity analyses of excluding outliers. Based on simulation studies, the proposed iterative method yields smaller bias and heterogeneity after performing a sensitivity analysis to remove the identified outliers. It also provides higher accuracy on outlier detection. Two case studies are used to illustrate the proposed method's real-world performance.

Ripretinib inhibits HIV-1 transcription through modulation of PI3K-AKT-mTOR.

Despite the effectiveness of antiretroviral therapy (ART) in prolonging the lifespan of individuals infected with HIV-1, it does not offer a cure for acquired immunodeficiency syndrome (AIDS). The "block and lock" approach aims to maintain the provirus in a state of extended transcriptional arrest. By employing the "block and lock" strategy, researchers endeavor to impede disease progression by preventing viral rebound for an extended duration following patient stops receiving ART. The crux of this strategy lies in the utilization of latency-promoting agents (LPAs) that are suitable for impeding HIV-1 provirus transcription. However, previously documented LPAs exhibited limited efficacy in primary cells or samples obtained from patients, underscoring the significance of identifying novel LPAs that yield substantial outcomes. In this study, we performed high-throughput screening of FDA-approved compound library in the J-Lat A2 cell line to discover more efficacious LPAs. We discovered ripretinib being an LPA candidate, which was validated and observed to hinder proviral activation in cell models harboring latent infections, as well as CD4+ T cells derived from infected patients. We demonstrated that ripretinib effectively impeded proviral activation through inhibition of the PI3K-AKT-mTOR signaling pathway in the HIV-1 latent cells, thereby suppressing the opening states of cellular chromatin. The results of this research offer a promising drug candidate for the implementation of the "block and lock" strategy in the pursuit of an HIV-1 cure.

The mutational landscape in chronic myelomonocytic leukemia and its impact on allogeneic hematopoietic cell transplantation outcomes: a Center for Blood and Marrow Transplantation Research (CIBMTR) analysis.

Somatic mutations are recognized as an important prognostic factor in chronic myelomonocytic leukemia (CMML). However, limited data are available regarding their impact on outcomes after allogeneic hematopoietic cell transplantation (HCT). In this registry analysis conducted in collaboration with the Center for International Blood and Marrow Transplantation Registry database/sample repository, we identified 313 adult patients with CMML (median age: 64 years, range, 28- 77) who underwent allogeneic HCT during 2001-2017 and had an available biospecimen in the form of a peripheral blood sample obtained prior to the start of conditioning. In multivariate analysis, a CMML-specific prognostic scoring system (CPSS) score of intermediate-2 (HR=1.46, P=0.049) or high (HR=3.22, P=0.0004) correlated significantly with overall survival. When the molecularly informed CPSS-Mol prognostic model was applied, a high CPSS-Mol score (HR=2 P=0.0079) correlated significantly with overall survival. The most common somatic mutations were in ASXL1 (62%), TET2 (35%), KRAS/NRAS (33% combined), and SRSF2 (31%). DNMT3A and TP53 mutations were associated with decreased overall survival (HR=1.70 [95% CI: 1.11-2.60], P=0.0147 and HR=2.72 [95% CI: 1.37-5.39], P=0.0042, respectively) while DNMT3A, JAK2, and TP53 mutations were associated with decreased disease-free survival (HR=1.66 [95% CI: 1.11-2.49], P=0.0138, HR=1.79 [95% CI: 1.06-3.03], P=0.0293, and HR=2.94 [95% CI: 1.50-5.79], P=0.0018, respectively). The only mutation associated with increased relapse was TP53 (HR=2.94, P=0.0201). Nonetheless, the impact of TP53 mutations specifically should be interpreted cautiously given their rarity in CMML. We calculated the goodness of fit measured by Harrell's C-index for both the CPSS and CPSS-Mol, which were very similar. In summary, via registry data we have determined the mutational landscape in patients with CMML who underwent allogeneic HCT, and demonstrated an association between CPSS-Mol and transplant outcomes although without major improvement in the risk prediction beyond that provided by the CPSS.

Analysis of complement system and its related factors in Alzheimer's disease.

Alzheimer's disease (AD) is a primary cause of dementia. The complement system is closely related to AD pathology and may be a potential target for the prevention and treatment of AD. In our study, we conducted a bioinformatics analysis to analyze the role of the complement system and its related factors in AD using Gene Expression Omnibus (GEO) data. We also conducted a functional analysis. Our study verified that 23 genes were closely related to differentially expressed complement system genes in diseases after intersecting the disease-related complement system module genes and differentially expressed genes. The STRING database was used to predict the interactions between the modular gene proteins of the differential complement system. A total of 21 gene proteins and 44 interaction pairs showed close interactions. We screened key genes and created a diagnostic model. The predictive effect of the model was constructed using GSE5281 and our study indicated that the predictive effect of the model was good. Our study also showed enriched negative regulation of Notch signaling, cytokine secretion involved in the immune response pathway, and cytokine secretion involved in immune response hormone-mediated apoptotic signaling pathway. We hope that our study provides a promising target to prevent and delay the onset, diagnosis, and treatment of AD.

Assessing the value of second-trimester nasal bone hypoplasia in predicting chromosomal abnormalities: a retrospective chromosomal microarray analysis of 351 fetuses.

PURPOSE: To evaluate the value of fetal nasal bone hypoplasia and other prenatal risk factors in predicting chromosomal abnormalities. METHODS: In this retrospective cohort study, we collected data on singleton pregnancies diagnosed with fetal nasal bone hypoplasia during second-trimester ultrasound. Fetal karyotyping and chromosomal microarray analysis (CMA) were performed, and pregnancy outcomes were assessed. The association between fetal nasal bone hypoplasia and chromosomal abnormalities was evaluated according to whether other prenatal risk factors were observed. RESULTS: Our final analysis included 351 pregnancies, of which 62 (17.7%) fetuses had chromosomal abnormalities, including 36 cases of trisomy-21, six cases of trisomy-18, one case each of trisomy-13, and 47, XYY syndrome, and 18 cases of copy number variations (CNVs). Among the 243 cases of isolated nasal bone hypoplasia, 28 (11.5%) cases of chromosomal aberrations were identified. The incidence was significantly higher if other soft markers or structural abnormalities were simultaneously detected. Pregnancy was terminated in 43 aneuploid fetuses and nine fetuses detected with CNVs. The parents of the fetuses diagnosed with 47, XYY syndrome and the other nine CNVs chose to continue the pregnancy, and no abnormalities were detected in the newborns. Furthermore, we found that other prenatal risk factors should be considered in evaluating the likelihood of chromosomal abnormalities in fetuses with nasal bone hypoplasia. CONCLUSIONS: Nasal bone hypoplasia is a highly specific soft marker that is associated with multiple chromosomal abnormalities. The risk of chromosomal abnormalities increases when combined with structural abnormalities or increased nuchal translucency (NT). Chromosomal microarray analysis is a powerful prenatal test for chromosomal abnormalities, which may be warranted in fetuses with nasal bone hypoplasia.

THE EFFECT DIRECTION SHOULD BE TAKEN INTO ACCOUNT WHEN ASSESSING SMALL-STUDY EFFECTS.

OBJECTIVE: Studies with statistically significant results are frequently more likely to be published than those with non-significant results. This phenomenon leads to publication bias or small-study effects and can seriously affect the validity of the conclusion from systematic reviews and meta-analyses. Small-study effects typically appear in a specific direction, depending on whether the outcome of interest is beneficial or harmful, but this direction is rarely taken into account in conventional methods. METHODS: We propose to use directional tests to assess potential small-study effects. The tests are built on a one-sided testing framework based on the existing Egger's regression test. We performed simulation studies to compare the proposed one-sided regression tests, conventional two-sided regression tests, as well as two other competitive methods (Begg's rank test and the trim-and-fill method). Their performance was measured by type I error rates and statistical power. Three real-world meta-analyses on measurements of infrabony periodontal defects were also used to examine the various methods' performance. RESULTS: Based on simulation studies, the one-sided tests could have considerably higher statistical power than competing methods, particularly their two-sided counterparts. Their type I error rates were generally controlled well. In the case study of the three real-world meta-analyses, by accounting for the favored direction of effects, the one-sided tests could rule out potential false-positive conclusions about small-study effects. They also are more powerful in assessing small-study effects than the conventional two-sided tests when true small-study effects likely exist. CONCLUSION: We recommend researchers incorporate the potential favored direction of effects into the assessment of small-study effects.

Coupling of COPII vesicle trafficking to nutrient availability by the IRE1α-XBP1s axis.

The cytoplasmic coat protein complex-II (COPII) is evolutionarily conserved machinery that is essential for efficient trafficking of protein and lipid cargos. How the COPII machinery is regulated to meet the metabolic demand in response to alterations of the nutritional state remains largely unexplored, however. Here, we show that dynamic changes of COPII vesicle trafficking parallel the activation of transcription factor X-box binding protein 1 (XBP1s), a critical transcription factor in handling cellular endoplasmic reticulum (ER) stress in both live cells and mouse livers upon physiological fluctuations of nutrient availability. Using live-cell imaging approaches, we demonstrate that XBP1s is sufficient to promote COPII-dependent trafficking, mediating the nutrient stimulatory effects. Chromatin immunoprecipitation (ChIP) coupled with high-throughput DNA sequencing (ChIP-seq) and RNA-sequencing analyses reveal that nutritional signals induce dynamic XBP1s occupancy of promoters of COPII traffic-related genes, thereby driving the COPII-mediated trafficking process. Liver-specific disruption of the inositol-requiring enzyme 1α (IRE1α)-XBP1s signaling branch results in diminished COPII vesicle trafficking. Reactivation of XBP1s in mice lacking hepatic IRE1α restores COPII-mediated lipoprotein secretion and reverses the fatty liver and hypolipidemia phenotypes. Thus, our results demonstrate a previously unappreciated mechanism in the metabolic control of liver protein and lipid trafficking: The IRE1α-XBP1s axis functions as a nutrient-sensing regulatory nexus that integrates nutritional states and the COPII vesicle trafficking.

Molecular mechanism of islet ß-cell functional alternations during type 2 diabetes.

In recent years, the incidence rate of type 2 diabetes (T2D) has risen rapidly and has become a global health crisis. Recent experimental and clinical studies have shown that islet ß-cell dysfunction is an important cause of T2D and its related complications. ß-cells undergo dynamic compensation and decompensation in the course of T2D. In this process, metabolic stress responses, such as ER stress, oxidative stress and inflammation, are key regulators of ß-cell functional alternations. In this review, we summarize the research progress on the ß-cell functional dynamics in the course of T2D, in order to deepen the understanding of the molecular mechanism of T2D, and provide reference for its precise diagnosis and clinical intervention.