Deciphering adipose development: Function, differentiation and regulation.

The overdevelopment of adipose tissues, accompanied by excess lipid accumulation and energy storage, leads to adipose deposition and obesity. With the increasing incidence of obesity in recent years, obesity is becoming a major risk factor for human health, causing various relevant diseases (including hypertension, diabetes, osteoarthritis and cancers). Therefore, it is of significance to antagonize obesity to reduce the risk of obesity-related diseases. Excess lipid accumulation in adipose tissues is mediated by adipocyte hypertrophy (expansion of pre-existing adipocytes) or hyperplasia (increase of newly-formed adipocytes). It is necessary to prevent excessive accumulation of adipose tissues by controlling adipose development. Adipogenesis is exquisitely regulated by many factors in vivo and in vitro, including hormones, cytokines, gender and dietary components. The present review has concluded a comprehensive understanding of adipose development including its origin, classification, distribution, function, differentiation and molecular mechanisms underlying adipogenesis, which may provide potential therapeutic strategies for harnessing obesity without impairing adipose tissue function.

Exosomes from hypoxia-pretreated adipose-derived stem cells attenuate ultraviolet light-induced skin injury via delivery of circ-Ash1l.

BACKGROUND: An increasing number of studies have reported that exosomes from adipose-derived stem cells (ADSCs) have antioxidant and anti-inflammatory properties. In the present study, we aimed at elucidating the potential therapeutic mechanism underlying ADSC exosomes in ultraviolet B-light (UVB)-induced skin injury. METHODS: We isolated the exosomes from ADSCs and hypoxia-pretreated ADSCs. High-throughput sequencing was applied to identify differential circRNA expression. Then, a UV-induced murine skin injury model was constructed and the therapeutic effect of exosomes was determined using immunofluorescence and ELISA. The regulatory mechanism was demonstrated using luciferase reporter analysis and an in vitro experiment. RESULTS: Exosomes from hypoxia-pretreated ADSCs inhibited UVB light-induced vascular injury by reversing ROS and inflammatory factor expression. High-throughput sequencing showed that exosomes from hypoxia-pretreated ADSCs (HExo) improved UV-induced skin damage via delivery of circ-Ash1l. Downregulation of circ-Ash1l inhibited the therapeutic effect of HExo on UV-induced skin damage. It was further shown that GPX4 and miR-700-5p were circ-Ash1l downstream targets. MiR-700-5p overexpression or GPX4 downregulation inhibited the circ-Ash1l protective effects of UV-induced endothelial progenitor cell (EPC) damage. CONCLUSION: Thus, exosomes from hypoxia-pretreated ADSCs attenuated UV light-induced skin injury via circ-Ash1l delivery and ferroptosis inhibition.

A Diagnostic Model for Alzheimer's Disease Based on Blood Levels of Autophagy-Related Genes.

Alzheimer's disease (AD) is a common neurodegenerative disease. The major problems that exist in the diagnosis of AD include the costly examinations and the high-invasive sampling tissue. Therefore, it would be advantageous to develop blood biomarkers. Because AD's pathological process is considered tightly related to autophagy; thus, a diagnostic model for AD based on ATGs may have more predictive accuracy than other models. We obtained GSE63060 dataset from the GEO database, ATGs from the HADb and screened 64 differentially expressed autophagy-related genes (DE-ATGs). We then applied them to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses as well as DisGeNET and PaGenBase enrichment analyses. By using the univariate analysis, least absolute shrinkage and selection operator (LASSO) regression method and the multivariable logistic regression, nine DE-ATGs were identified as biomarkers, which are ATG16L2, BAK1, CAPN10, CASP1, RAB24, RGS19, RPS6KB1, ULK2, and WDFY3. We combined them with sex and age to establish a nomogram model. To evaluate the model's distinguishability, consistency, and clinical applicability, we applied the receiver operating characteristic (ROC) curve, C-index, calibration curve, and on the validation datasets GSE63061, GSE54536, GSE22255, and GSE151371 from GEO database. The results show that our model demonstrates good prediction performance. This AD diagnosis model may benefit both clinical work and mechanistic research.