MiR-150-5p Alleviates Renal Tubule Epithelial Cell Fibrosis via the Inhibition of Epithelial-Mesenchymal Transition by Targeting ZEB1.

INTRODUCTION: Although microRNA (miR)-150-5p participates in the progression of renal fibrosis, its mechanism of action remains elusive. METHODS: A mouse model of unilateral ureteral obstruction was used. The in vitro renal fibrosis model was established by stimulating human kidney 2 (HK-2) cells with transforming growth factor beta 1 (TGF-ß1). The expression profiles of miR-150-5p, zinc finger E-box binding homeobox 1 (ZEB1), and other fibrosis- and epithelial-mesenchymal transition (EMT)-linked proteins were determined using Western blot and quantitative reverse transcription polymerase chain reaction. The relationship between miR-150-5p and ZEB1 in HK-2 cells was confirmed by a dual-luciferase reporter assay. RESULTS: Both in vivo and in vitro renal fibrosis models revealed reduced miR-150-5p expression and elevated ZEB1 level. A significant decrease in E-cadherin levels, as well as increases in alpha smooth muscle actin (α-SMA) and collagen type I (Col-I) levels, was seen in TGF-ß1-treated HK-2 cells. The overexpression of miR-150-5p ameliorated TGF-ß1-mediated fibrosis and EMT. Notably, miR-150-5p acts by directly targeting ZEB1. A significant reversal of the inhibitory impact of miR-150-5p on TGF-ß1-mediated fibrosis and EMT in HK-2 cells was observed upon ZEB1 overexpression. CONCLUSION: MiR-150-5p suppresses TGF-ß1-induced fibrosis and EMT by targeting ZEB1 in HK-2 cells, providing helpful insights into the therapeutic intervention of renal fibrosis.

MiR-150-5p Alleviates Renal Tubular Epithelial Cell Fibrosis by Activating Autophagy via ß-catenin Signaling.

OBJECTIVE: To verify whether miR-150-5p modulates the development of renal fibrosis and its mechanism. METHODS: Transforming growth factor (TGF)-ß1 was implemented on HK-2 cells to construct a renal fibrosis in vitro model. Inhibition of autophagy was performed on HK-2 cells by treating with 3-methyladenine (3-MA, an inhibitor of autophagy). HK-2 cells experienced transfection by miR-150-5p mimics/inhibitor and pcDNA-ß-catenin plasmids, and the negative controls. Dual luciferase reporter gene assay was applied to validate the relationship between miR-150-5p and ß-catenin. Cell apoptosis exploration was implemented by flow cytometry assay. The level detection of CoII, α-SMA, miR-150-5p and ß-catenin was executed by real-time quantitative reverse transcription-polymerase chain reaction. The expression of CoII, α-SMA, LC3I, LC3II, Bax, Cleaved Caspase 3, Beclin 1, Bcl-2 and ß-catenin proteins was monitored by western blot. RESULTS: Autophagy was inhibited in TGF-ß1-induced HK-2 cells. MiR-150-5p alleviated fibrosis, enhanced autophagy, and inhibited apoptosis in TGF-ß1-induced HK-2 cells. ß-catenin was a target of miR-150-5p. Autophagy inhibition or ß-catenin partially counteracted miR-150-5p effect on TGF-ß1-induced fibrosis in HK-2 cells. CONCLUSIONS: MiR-150-5p alleviates renal tubular epithelial cell fibrosis by activating autophagy via ß-catenin signaling.

Laboratory indices in patients with osteonecrosis of the femoral head: a retrospective comparative study.

BACKGROUND: Osteonecrosis of the femoral head is a degenerative condition linked to corticosteroids, alcoholism, or trauma. With its rising prevalence due to increased hormone drug use and its debilitating effects on young to middle-aged individuals, understanding its association with specific laboratory indicators can aid early diagnosis and prevention. METHODS: Upon retrospective analysis of the clinical data pertaining to individuals diagnosed with femoral head necrosis, spanning from January 2016 to January 2022, a comprehensive evaluation was conducted within the same time frame. The study aimed to ascertain the presence of femoral head necrosis in a total of 1176 individuals. A total of 1036 healthy patients were recruited randomly, ensuring that their ages matched. The risk variables associated with the utilization of logistic regression analysis and analysis techniques are employed. The patient examines the age distribution within a specific age group. RESULTS: The levels of high-density lipoprotein, low-density lipoprotein A1, lipoprotein B1, total protein, albumin, globulin, and other lipophilic metabolism and coagulation markers exhibited a statistically significant increase compared to the control group. A multifactor logistic regression analysis was conducted to identify potential risk factors associated with femoral head necrosis in patients. CONCLUSION: Femoral head necrosis is associated with a range of variables including coagulation malfunction, lipid metabolic abnormalities, and inflammation.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Feline degenerative joint disease: a genomic and proteomic approach.

The underlying disease mechanisms for feline degenerative joint disease (DJD) are mostly unidentified. Today, most of what is published on mammalian arthritis is based on human clinical findings or on mammalian models of human arthritis. However, DJD is a common occurrence in the millions of domestic felines worldwide. To get a better understanding of the changes in biological pathways that are associated with feline DJD, this study employed a custom-designed feline GeneChip, and the institution's unique access to large sample populations to investigate genes and proteins from whole blood and serum that may be up- or down-regulated in DJD cats. The GeneChip results centered around three main pathways that were affected in DJD cats: immune function, apoptosis and oxidative phosphorylation. By identifying these key disease-associated pathways it will then be possible to better understand disease pathogenesis and diagnose it more easily, and to better target it with pharmaceutical and nutritional intervention.

Sequencing and comparative genomic analysis of 1227 Felis catus cDNA sequences enriched for developmental, clinical and nutritional phenotypes.

BACKGROUND: The feline genome is valuable to the veterinary and model organism genomics communities because the cat is an obligate carnivore and a model for endangered felids. The initial public release of the Felis catus genome assembly provided a framework for investigating the genomic basis of feline biology. However, the entire set of protein coding genes has not been elucidated. RESULTS: We identified and characterized 1227 protein coding feline sequences, of which 913 map to public sequences and 314 are novel. These sequences have been deposited into NCBI's genbank database and complement public genomic resources by providing additional protein coding sequences that fill in some of the gaps in the feline genome assembly. Through functional and comparative genomic analyses, we gained an understanding of the role of these sequences in feline development, nutrition and health. Specifically, we identified 104 orthologs of human genes associated with Mendelian disorders. We detected negative selection within sequences with gene ontology annotations associated with intracellular trafficking, cytoskeleton and muscle functions. We detected relatively less negative selection on protein sequences encoding extracellular networks, apoptotic pathways and mitochondrial gene ontology annotations. Additionally, we characterized feline cDNA sequences that have mouse orthologs associated with clinical, nutritional and developmental phenotypes. Together, this analysis provides an overview of the value of our cDNA sequences and enhances our understanding of how the feline genome is similar to, and different from other mammalian genomes. CONCLUSIONS: The cDNA sequences reported here expand existing feline genomic resources by providing high-quality sequences annotated with comparative genomic information providing functional, clinical, nutritional and orthologous gene information.