Transcriptomic analysis reveals the functions of H2S as a gasotransmitter independently of Cys in Arabidopsis

Numerous studies have revealed the gasotransmitter functions of hydrogen sulfide (H2S) in various biological processes. However, the involvement of H2S in sulfur metabolism and/or Cys synthesis makes its role as a signaling molecule ambiguous. The generation of endogenous H2S in plants is closely related to the metabolism of Cys, which play roles in a variety of signaling pathway occurring in various cellular processes. Here, we found that exogenous H2S fumigation and Cys treatment modulated the production rate and content of endogenous H2S and Cys to various degrees. Furthermore, we provided comprehensive transcriptomic analysis to support the gasotransmitter role of H2S besides as a substrate for Cys synthesis. Comparison of the differentially expressed genes (DEGs) between H2S and Cys treated seedlings indicated that H2S fumigation and Cys treatment caused different influences on gene profiles during seedlings development. A total of 261 genes were identified to respond to H2S fumigation, among which 72 genes were co-regulated by Cys treatment. GO and KEGG enrichment analysis of the 189 genes, H2S but not Cys regulated DEGs, indicated that these genes mainly involved in plant hormone signal transduction, plant-pathogen interaction, phenylpropanoid biosynthesis, and MAPK signaling pathway. Most of these genes encoded proteins having DNA binding and transcription factor activities that play roles in a variety of plant developmental and environmental responses. Many stress-responsive genes and some Ca2+ signal associated genes were also included. Consequently, H2S regulated gene expression through its role as a gasotransmitter, rather than just as a substrate for Cys biogenesis, and these 189 genes were far more likely to function in H2S signal transduction independently of Cys. Our data will provide insights for revealing and enriching H2S signaling networks

Geographical variations in maternal dietary patterns during pregnancy associated with birth weight in Shaanxi province, Northwestern China

The geographical variation of maternal dietary patterns related to birth outcomes is important for improving the health of mothers and children; however, it is currently unknown. Thus, the objective of the study was to investigate geographical variations of maternal dietary pattern during pregnancy, and evaluate the spatial varying association of maternal dietary patterns in pregnancy with abnormal birth weight. A population-based cross-sectional study was conducted in Shaanxi province in Northwest China in 2013 to evaluate the relationship between abnormal birth weight and dietary pattern using the Geographically Weighted Logistic Regression (GWLR). Three dietary patterns during pregnancy were extracted through factor analysis, explaining approximately 45.8% of the variability of food intake. Approximately 81.6% of mothers with higher scores on the equilibrium pattern was more unlikely to have small for gestational age (SGA) infants, with the lower OR observed in Central and South Shaanxi. The snacks pattern was positively associated with low birth weight (LBW) for 23.2% of participants, with the highest OR in Central Shaanxi. Among about 80.0% of participants with higher scores on the snacks pattern living in South and Central Shaanxi, there was a higher risk for SGA. The OR values tend to descend from South to North Shaanxi. The OR values of the negative association between prudent pattern and LBW decreased from South to North Shaanxi among approximately 59.3% of participants. The prudent pattern was also negatively associated with the increasing risk of fetal macrosomia among 19.2% of participants living mainly in South Shaanxi. The association of maternal dietary patterns during pregnancy with abnormal birth weight varied geographically across Shaanxi province. The findings emphasize the importance of geographical distribution to improve the dietary patterns among disadvantaged pregnant women

Effects of potential risk factors on the development of cardiometabolic multimorbidity and mortality among the elders in China

Objectives: To examine the impact of demographic, socioeconomic, and behavioral factors on the development of cardiometabolic multimorbidity and mortality in Chinese elders. Methods: Data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) 2002–2018 was used in the study. Cardiometabolic multimorbidity was defined as the presence of two or more cardiometabolic disorders, such as hypertension, diabetes, cardiovascular disease (CVD), heart disease, or stroke. Cox regression model and multi-state Markov model were developed to evaluate the association of the study factors with the progression of cardiometabolic conditions and mortality. The outcomes included three states (first cardiometabolic disease, cardiometabolic multimorbidity, and all-cause mortality) and five possible transitions among the three states. Results: Of the 13,933 eligible individuals, 7,917 (56.8%) were female, and 9,540 (68.50%) were over 80 years old. 2,766 (19.9%) participants had their first cardiometabolic disease, 975 (7.0%) participants suffered from cardiometabolic multimorbidity, and 9,365 (67.2%) participants died. The progression to cardiometabolic multimorbidity was positively associated with being female (HR = 1.42; 95%CI, 1.10 − 1.85), living in the city (HR = 1.41; 95%CI, 1.04 − 1.93), overweight (HR = 1.43; 95%CI, 1.08 − 1.90), and obesity (HR = 1.75; 95% CI, 1.03 − 2.98). A higher risk for the first cardiometabolic disease was associated with being female (HR = 1.26; 95% CI, 1.15 − 1.39), higher socioeconomic status (SES, HR = 1.17; 95%CI, 1.07 − 1.28), lack of regular physical activity (HR = 1.13; 95%CI, 1.04 − 1.23), smoking (HR = 1.20; 95%CI, 1.08 − 1.33), ≤ 5 h sleep time (HR = 1.15; 95%CI, 1.02 − 1.30), overweight (HR = 1.48; 95% CI, 1.32 − 1.66), and obesity (HR = 1.34; 95%CI, 1.06 − 1.69). It also should be noted that not in marriage, lower SES and unhealthy behavioral patterns were risk factors for mortality. Conclusion: This study emphasized the importance of lifestyle and SES in tackling the development of cardiometabolic conditions among Chinese elders and provided a reference for policy-makers to develop a tailored stage-specific intervention strategy

Loss of Angiopoietin-like 7 diminishes the regeneration capacity of hematopoietic stem and progenitor cells

© 2015 Xiao et al.; licensee Biomed Central. Successful expansion of hematopoietic stem cells (HSCs) would benefit the use of HSC transplants in the clinic. Angiopoietin-like 7 promotes the expansion of hematopoietic stem and progenitor cells (HSPC) in vitro and ex vivo. However, the impact of loss of Angptl7 on HSPCs in vivo has not been characterized. Here, we generated Angptl7-deficient mice by TALEN-mediated gene targeting and found that HSC compartments in Angptl7-null mice were compromised. In addition, wild type (WT) HSPCs failed to repopulate in the BM of Angptl7-null mice after serial transplantations while the engraftment of Angptl7-deficient HSPCs in WT mice was not impaired. These results suggest that Angptl7 is required for HSPCs repopulation in a non-cell autonomous manner.Link_to_subscribed_fulltex

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment