NS7a of SADS-CoV promotes viral infection via inducing apoptosis to suppress type III interferon production.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly discovered swine coronavirus with potential cross-species transmission risk. Although SADS-CoV-induced host cell apoptosis and innate immunity antagonization has been revealed, underlying signaling pathways remain obscure. Here, we demonstrated that infection of SADS-CoV induced apoptosis in vivo and in vitro, and that viral protein NS7a is mainly responsible for SADS-CoV-induced apoptosis in host cells. Furthermore, we found that NS7a interacted with apoptosis-inducing factor mitochondria associated 1 (AIFM1) to activate caspase-3 via caspase-6 in SADS-CoV-infected cells, and enhanced SADS-CoV replication. Importantly, NS7a suppressed poly(I:C)-induced expression of type III interferon (IFN-λ) via activating caspase-3 to cleave interferon regulatory factor 3 (IRF3), and caspase-3 inhibitor protects piglets against SADS-CoV infection in vivo. These findings reveal how SADS-CoV induced apoptosis to inhibit innate immunity and provide a valuable clue to the development of effective drugs for the clinical control of SADS-CoV infection.IMPORTANCEOver the last 20 years, multiple animal-originated coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV), middle east respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2, have caused millions of deaths, seriously jeopardized human health, and hindered social development, indicating that the study of animal-originated coronaviruses with potential for cross-species transmission is particularly important. Bat-originated swine acute diarrhea syndrome coronavirus (SADS-CoV), discovered in 2017, can not only cause fatal diarrhea in piglets, but also infect multiple human cells, with a potential risk of cross-species transmission, but its pathogenesis is unclear. In this study, we demonstrated that NS7a of SADS-CoV suppresses IFN-λ production via apoptosis-inducing factor mitochondria associated 1 (AIFM1)-caspase-6-caspase-3-interferon regulatory factor 3 (IRF3) pathway, and caspase-3 inhibitor (Z-DEVD-FMK) can effectively inhibit SADS-CoV replication and protect infected piglets. Our findings in this study contribute to a better understanding of SADS-CoV-host interactions as a part of the coronaviruses pathogenesis and using apoptosis-inhibitor as a drug as potential therapeutic approaches for prevention and control of SADS-CoV infection.

Seed and Soil: Consensus Molecular Subgroups (CMS) and Tumor Microenvironment Features Between Primary Lesions and Metastases of Different Organ Sites in Colorectal Cancer.

Purpose: Consensus molecular subtypes (CMS) are mainly used for biological interpretability and clinical stratification of colorectal cancer (CRC) in primary tumors (PT) but few in metastases. The heterogeneity of CMS distribution in metastases and the concordance of CMS between PT and metastases still lack sufficient study. We used CMS to classify CRC metastases and combine it with histopathological analysis to explore differences between PT and distant metastases. Patients and Methods: We obtained gene expression profiles for 942 PT samples from TCGA database (n=376) and GEO database (n=566), as well as 442 metastasis samples from GEO database. Among these, 765 PT samples and 442 metastasis samples were confidently identified with CMS using the "CMS classifier" and enrolled for analysis. Clinicopathological manifestation and CMS classification of CRC metastases were assessed with data from GEO, TCGA, and cBioPortal. Overall, 105 PT-metastasis pairs were extracted from 10 GEO datasets to assess CMS concordance. Tumor microenvironment (TME) features between PT and metastases were analyzed by immune-stromal infiltration with ESTIMATE and xCell algorithms. Finally, TME features were validated with multiplex immunohistochemistry in 27 PT-metastasis pairs we retrospectively collected. Results: Up to 64% of CRC metastases exhibited concordant CMS groups with matched PT, and the TME of metastases was similar to that of PT. For most common distant metastases, liver metastases were predominantly CMS2 and lung and peritoneal metastases were mainly CMS4, highlighting "seed" of tumor cells of different CMS groups had a preference for metastasis to "soil" of specific organs. Compared with PT, cancer-associated fibroblasts (CAF) reduced in liver metastases, CD4+T cells and M2-like macrophages increased in lung metastases, and M2-like macrophages and CAF increased in peritoneal metastases. Conclusion: Our findings underscore the importance of CMS-guided specific organ monitoring and treatment post-primary tumor surgery for patients. Differences in immune-stromal infiltration among different metastases provide targeted therapeutic opportunities for metastatic CRC.

LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach.

INTRODUCTION: Drug development is a challenging and costly process, yet it plays a crucial role in improving healthcare outcomes. Drug development requires extensive research and testing to meet the demands for economic efficiency, cures, and pain relief. METHODS: Drug development is a vital research area that necessitates innovation and collaboration to achieve significant breakthroughs. Computer-aided drug design provides a promising avenue for drug discovery and development by reducing costs and improving the efficiency of drug design and testing. RESULTS: In this study, a novel model, namely LSTM-SAGDTA, capable of accurately predicting drug-target binding affinity, was developed. We employed SeqVec for characterizing the protein and utilized the graph neural networks to capture information on drug molecules. By introducing self-attentive graph pooling, the model achieved greater accuracy and efficiency in predicting drug-target binding affinity. CONCLUSION: Moreover, LSTM-SAGDTA obtained superior accuracy over current state-of-the-art methods only by using less training time. The results of experiments suggest that this method represents a highprecision solution for the DTA predictor.

Cadmium tolerance in Elodea canadensis Michx: Subcellular distribution and metabolomic analysis.

The aquatic plant Elodea canadensis is considered a good candidate for ecotoxicological investigations. Cadmium (Cd) is a widespread contaminant in aquatic systems. In this study, to better elucidate the underlying tolerance mechanism and molecular impact of environmentally relevant Cd concentration in aquatic plants, subcellular distribution, chemical forms, and gas chromatography-mass spectrometry-based non-targeted metabolomics profiles were comprehensively analyzed in E. canadensis subjected to 0 and 10 µM Cd treatment for 5 d. Subcellular fractionation analysis of Cd-containing leaves showed that 67% of Cd was compartmentalized in cell wall followed by the soluble fraction (24 %) and organelles (9 %). The majority of Cd (90 %) was found in the extraction using 1 M NaCl. Metabolomic analysis using unsupervised principal component analyses and a supervised partial least squares discriminant analysis revealed clear differences in metabolic profiles between the two groups, demonstrating the metabolic effects of Cd. The 155 identified compounds altered by Cd were mainly from primary metabolism, including sugars, amino acids, organic acids, and their derivatives. Secondary metabolites such as polyphenols and phenolamides were also detected. The massive up-regulation of metabolites, including trehalose, proline, sarcosine, nicotianamine, putrescine, α-ketoglutaric acid, citric acid, and phytol might represent a detoxification mechanism. These findings highlighted the mechanistic strategies that E. canadensis employs to defend against Cd toxicity.

Expression of PmACRE1 in Arabidopsis thaliana enables host defence against Bursaphelenchus xylophilus infection.

BACKGROUND: Pine wilt disease (PWD) is a destructive disease that endangers pine trees, resulting in the wilting, with yellowing and browning of the needles, and eventually the death of the trees. Previous studies showed that the Avr9/Cf-9 rapidly elicited (PmACRE1) gene was downregulated by Bursaphelenchus xylophilus infection, suggesting a correlation between PmACRE1 expression and pine tolerance. Here, we used the expression of PmACRE1 in Arabidopsis thaliana to evaluate the role of PmACRE1 in the regulation of host defence against B. xylophilus infection. RESULTS: Our results showed that the transformation of PmACRE1 into A. thaliana enhanced plant resistance to the pine wood nematode (PWN); that is, the leaves of the transgenic line remained healthy for a longer period than those of the blank vector group. Ascorbate peroxidase (APX) activity and total phenolic acid and total flavonoid contents were higher in the transgenic line than in the control line. Widely targeted metabolomics analysis of the global secondary metabolites in the transgenic line and the vector control line showed that the contents of 30 compounds were significantly different between these two lines; specifically, the levels of crotaline, neohesperidin, nobiletin, vestitol, and 11 other compounds were significantly increased in the transgenic line. The studies also showed that the ACRE1 protein interacted with serine hydroxymethyltransferase, catalase domain-containing protein, myrosinase, dihydrolipoyl dehydrogenase, ketol-acid reductoisomerase, geranylgeranyl diphosphate reductase, S-adenosylmethionine synthase, glutamine synthetase, and others to comprehensively regulate plant resistance. CONCLUSIONS: Taken together, these results indicate that PmACRE1 has a potential role in the regulation of plant defence against PWNs.

Emodin from Aloe inhibits Swine acute diarrhea syndrome coronavirus in cell culture.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an emerging swine enteropathogenic coronavirus that causes severe diarrhea in neonatal piglets, leading to serious economic losses to the pig industries. At present, there are no effective control measures for SADS, making an urgent need to exploit effective antiviral therapies. Here, we confirmed that Aloe extract (Ae) can strongly inhibit SADS-CoV in Vero and IPI-FX cells in vitro. Furthermore, we detected that Emodin from Ae had anti-SADS-CoV activity in cells but did not impair SADS-CoV infectivity directly. The time-of-addition assay showed that Emodin inhibits SADS-CoV infection at the whole stages of the viral replication cycle. Notably, we found that Emodin can significantly reduce virus particles attaching to the cell surface and induce TLR3 (p < 0.001), IFN-λ3 (p < 0.01), and ISG15 (p < 0.01) expressions in IPI-FX cells, indicating that the anti-SADS-CoV activity of Emodin might be due to blocking viral attachment and the activation of TLR3-IFN-λ3-ISG15 signaling axis. These results suggest that Emodin has the potential value for the development of anti-SADS-CoV drugs.

Predicting recurrence and metastasis risk of endometrial carcinoma via prognostic signatures identified from multi-omics data.

Objectives: Endometrial carcinoma (EC) is one of the three major gynecological malignancies, in which 15% - 20% patients will have recurrence and metastasis. Though there are many studies on the prognosis on this cancer, the performances of existing models evaluating the risk of its recurrence and metastasis are yet to be improved. In addition, a comprehensive multi-omics analyses on the prognostic signatures of EC are on demand. In this study, we aimed to construct a relatively stable and reliable model for predicting recurrence and metastasis of EC. This will help determine the risk level of patients and choose appropriate adjuvant therapy, thereby avoiding improper treatment, and improving the prognosis of patients. Methods: The mRNA, microRNA (miRNA), long non-coding RNA (lncRNA), copy number variation (CNV) data and clinical information of patients with EC were downloaded from The Cancer Genome Atlas (TCGA). Differential expression analyses were performed between the recurrence or metastasis group and the non-recurrence/metastasis group. Then, we screened potential prognostic markers from the four kinds of omics data respectively and established prediction models using three classifiers. Results: We achieved differential expressed mRNAs, lncRNAs, miRNAs and CNVs between the two groups. According to feature selection scores by the random forest algorithm, 275 CNV features, 50 lncRNA features, 150 miRNA features and 150 mRNA features were selected, respectively. And the prediction model constructed by the features of lncRNA data using random forest method showed the best performance, with an area under the curve of 0.763, and an accuracy of 0.819 under 10-fold cross-validation. Conclusion: We developed a computational model using omics information, which is able to predicting recurrence and metastasis risk of EC accurately.

Ultrasound Image Classification of Thyroid Nodules Based on Deep Learning.

A thyroid nodule, which is defined as abnormal growth of thyroid cells, indicates excessive iodine intake, thyroid degeneration, inflammation, and other diseases. Although thyroid nodules are always non-malignant, the malignancy likelihood of a thyroid nodule grows steadily every year. In order to reduce the burden on doctors and avoid unnecessary fine needle aspiration (FNA) and surgical resection, various studies have been done to diagnose thyroid nodules through deep-learning-based image recognition analysis. In this study, to predict the benign and malignant thyroid nodules accurately, a novel deep learning framework is proposed. Five hundred eight ultrasound images were collected from the Third Hospital of Hebei Medical University in China for model training and validation. First, a ResNet18 model, pretrained on ImageNet, was trained by an ultrasound image dataset, and a random sampling of training dataset was applied 10 times to avoid accidental errors. The results show that our model has a good performance, the average area under curve (AUC) of 10 times is 0.997, the average accuracy is 0.984, the average recall is 0.978, the average precision is 0.939, and the average F1 score is 0.957. Second, Gradient-weighted Class Activation Mapping (Grad-CAM) was proposed to highlight sensitive regions in an ultrasound image during the learning process. Grad-CAM is able to extract the sensitive regions and analyze their shape features. Based on the results, there are obvious differences between benign and malignant thyroid nodules; therefore, shape features of the sensitive regions are helpful in diagnosis to a great extent. Overall, the proposed model demonstrated the feasibility of employing deep learning and ultrasound images to estimate benign and malignant thyroid nodules.

Evaluating the Microsatellite Instability of Colorectal Cancer Based on Multimodal Deep Learning Integrating Histopathological and Molecular Data.

Microsatellite instability (MSI), an important biomarker for immunotherapy and the diagnosis of Lynch syndrome, refers to the change of microsatellite (MS) sequence length caused by insertion or deletion during DNA replication. However, traditional wet-lab experiment-based MSI detection is time-consuming and relies on experimental conditions. In addition, a comprehensive study on the associations between MSI status and various molecules like mRNA and miRNA has not been performed. In this study, we first studied the association between MSI status and several molecules including mRNA, miRNA, lncRNA, DNA methylation, and copy number variation (CNV) using colorectal cancer data from The Cancer Genome Atlas (TCGA). Then, we developed a novel deep learning framework to predict MSI status based solely on hematoxylin and eosin (H&E) staining images, and combined the H&E image with the above-mentioned molecules by multimodal compact bilinear pooling. Our results showed that there were significant differences in mRNA, miRNA, and lncRNA between the high microsatellite instability (MSI-H) patient group and the low microsatellite instability or microsatellite stability (MSI-L/MSS) patient group. By using the H&E image alone, one can predict MSI status with an acceptable prediction area under the curve (AUC) of 0.809 in 5-fold cross-validation. The fusion models integrating H&E image with a single type of molecule have higher prediction accuracies than that using H&E image alone, with the highest AUC of 0.952 achieved when combining H&E image with DNA methylation data. However, prediction accuracy will decrease when combining H&E image with all types of molecular data. In conclusion, combining H&E image with deep learning can predict the MSI status of colorectal cancer, the accuracy of which can further be improved by integrating appropriate molecular data. This study may have clinical significance in practice.

HAUS5 Is A Potential Prognostic Biomarker With Functional Significance in Breast Cancer.

Background: Breast cancer (BRCA) has become the most frequently appearing, lethal, and aggressive cancer with increasing morbidity and mortality. Previously, it was discovered that the HAUS5 protein is involved in centrosome integrity, spindle assembly, and the completion of the cytoplasmic division process during mitosis. By encouraging chromosome misdivision and aneuploidy, HAUS5 has the potential to cause cancer. The significance of HAUS5 in BRCA and the relationship between its expression and clinical outcomes or immune infiltration remains unclear. Methods: Pan-cancer was analyzed by TIMER2 web and the expression differential of HAUS5 was discovered. The prognostic value of HAUS5 for BRCA was evaluated with KM plotter and confirmed with Gene Expression Omnibus (GEO) dataset. Following that, we looked at the relationship between the high and low expression groups of HAUS5 and breast cancer clinical indications. Signaling pathways linked to HAUS5 expression were discovered using Gene Set Enrichment Analysis (GSEA). The relative immune cell infiltrations of each sample were assessed using the CIBERSORT algorithm and ESTIMATE method. We evaluated the Tumor Mutation Burden (TMB) value between the two sets of samples with high and low HAUS5 expression, as well as the differences in gene mutations between the two groups. The proliferation changes of BRCA cells after knockdown of HAUS5 were evaluated by fluorescence cell counting and colony formation assay. Result: HAUS5 is strongly expressed in most malignancies, and distinct associations exist between HAUS5 and prognosis in BRCA patients. Upregulated HAUS5 was associated with poor clinicopathological characteristics such as tumor T stage, ER, PR, and HER2 status. mitotic prometaphase, primary immunodeficiency, DNA replication, cell cycle related signaling pathways were all enriched in the presence of elevated HAUS5 expression, according to GSEA analysis. The BRCA microenvironment's core gene, HAUS5, was shown to be related with invading immune cell subtypes and tumor cell stemness. TMB in the HAUS5-low expression group was significantly higher than that in the high expression group. The mutation frequency of 15 genes was substantially different in the high expression group compared to the low expression group. BRCA cells' capacity to proliferate was decreased when HAUS5 was knocked down. Conclusion: These findings show that HAUS5 is a positive regulator of BRCA progression that contributes to BRCA cells proliferation. As a result, HAUS5 might be a novel prognostic indicator and therapeutic target for BRCA patients.

PseUdeep: RNA Pseudouridine Site Identification with Deep Learning Algorithm.

Background: Pseudouridine (Ψ) is a common ribonucleotide modification that plays a significant role in many biological processes. The identification of Ψ modification sites is of great significance for disease mechanism and biological processes research in which machine learning algorithms are desirable as the lab exploratory techniques are expensive and time-consuming. Results: In this work, we propose a deep learning framework, called PseUdeep, to identify Ψ sites of three species: H. sapiens, S. cerevisiae, and M. musculus. In this method, three encoding methods are used to extract the features of RNA sequences, that is, one-hot encoding, K-tuple nucleotide frequency pattern, and position-specific nucleotide composition. The three feature matrices are convoluted twice and fed into the capsule neural network and bidirectional gated recurrent unit network with a self-attention mechanism for classification. Conclusion: Compared with other state-of-the-art methods, our model gets the highest accuracy of the prediction on the independent testing data set S-200; the accuracy improves 12.38%, and on the independent testing data set H-200, the accuracy improves 0.68%. Moreover, the dimensions of the features we derive from the RNA sequences are only 109,109, and 119 in H. sapiens, M. musculus, and S. cerevisiae, which is much smaller than those used in the traditional algorithms. On evaluation via tenfold cross-validation and two independent testing data sets, PseUdeep outperforms the best traditional machine learning model available. PseUdeep source code and data sets are available at https://github.com/dan111262/PseUdeep.

Donor-Acceptor Pairs in Covalent Organic Frameworks Promoting Electron Transfer for Metal-Free Photocatalytic Organic Synthesis.

The donor-acceptor-type covalent organic frameworks (COFs) have recently gained increasing interest in photocatalysis, but the photoinduced electron-transfer regimes in the COFs are underexplored. Herein, we demonstrate a designed porphyrinic COF possessing a donor-acceptor structure together with its photocatalytic performance in aerobic coupling of primary amines. The COF could be photoexcited by the full range of visible light to generate electron-hole pairs that could be separated by donor-acceptor pairs. Electron transfer as the mechanism of the reaction from anthracene unit to porphyrin unit was revealed by natural transition orbitals analyses. The electrons migrate to the adsorbed O2 to generate reactive oxidative species. The COF displays remarkable photocatalytic activities in the coupling of amines to imines, which can be explained mainly by the sufficient charge separation and mobility, benefiting from the donor-acceptor pairs in the COF and their interactions to the reactants and intermediates.

Mutations in the notch signalling pathway are associated with enhanced anti-tumour immunity in colorectal cancer.

The Notch signalling pathway is involved in the development of several cancers, including colorectal cancer (CRC). However, whether mutations in this pathway could alter the CRC immunophenotype remains unknown. Here, we investigated the relationship between Notch signalling pathway mutations and the tumour immune microenvironment by analysing gene expression data from the GSE108989 single T cell RNA sequencing data set and The Cancer Genome Atlas (TCGA) data set. We found that Notch signalling pathway mutations were associated with an increased number of tumour-specific CD8+ T cells and decreased number of inhibitory regulatory T (Treg) cells, representing an enhanced anti-tumour response in the GSE108989 data set. In TCGA data set, we also found that Notch signalling pathway mutations were associated with enrichment of genes associated with immune activation pathways and higher expressions of PDCD1, GZMB and PRF1. Although Notch signalling pathway mutations did not affect the overall survival and disease-free survival of CRC patients, they were associated with earlier disease stages and lower rates of metastasis. These results demonstrated that Notch signalling pathway mutations can enhance anti-tumour immunity in CRC, as validated by the two data sets, suggesting that they may be promising biomarkers for immune checkpoint blockade therapies for CRC patients.

First-generation species-selective chemical probes for fluorescence imaging of human senescence-associated ß-galactosidase.

Human senescence-associated ß-galactosidase (SA-ß-gal), the most widely used biomarker of aging, is a valuable tool for assessing the extent of cell 'healthy aging' and potentially predicting the health life span of an individual. Human SA-ß-gal is an endogenous lysosomal enzyme expressed from GLB1, the catalytic domain of which is very different from that of E. coli ß-gal, a bacterial enzyme encoded by lacZ. However, existing chemical probes for this marker still lack the ability to distinguish human SA-ß-gal from ß-gal of other species, such as bacterial ß-gal, which can yield false positive signals. Here, we show a molecular design strategy to construct fluorescent probes with the above ability with the aid of structure-based steric hindrance adjustment catering to different enzyme pockets. The resulting probes normally work as traditional SA-ß-gal probes, but they are unique in their powerful ability to distinguish human SA-ß-gal from E. coli ß-gal, thus achieving species-selective visualization of human SA-ß-gal for the first time. NIR-emitting fluorescent probe KSL11 as their representative further displays excellent species-selective recognition performance in biological systems, which has been herein verified by testing in senescent cells, in lacZ-transfected cells and in E. coli-ß-gal-contaminated tissue sections of mice. Because of our probes, it was also discovered that SA-ß-gal content in mice increased gradually with age and SA-ß-gal accumulated most in the kidneys among the main organs of naturally aging mice, suggesting that the kidneys are the organs with the most severe aging during natural aging.

Protection against oxidative stress and anti-aging effect in Drosophila of royal jelly-collagen peptide.

Dietary peptide has been of great interest because of its perspective in nutrition and health of human body. The aim of this study was to develop a dietary nutritional supplement exerting both antioxidant and anti-aging effects. Peptide, named as ERJ-CP, was prepared by mixing enzyme-treated royal jelly (ERJ) with collagen peptide (CP), showing stronger antioxidant activity in vitro. Drosophila was used as model animal to investigate anti-aging effect of ERJ-CP in vivo. ERJ-CP significantly prolonged the average life span of Drosophila treated with H2O2 and paraquat, reducing malondialdehyde (MDA) and protein carbonyl (PCO) levels in Drosophila. In addition, 3 mg/mL of ERJ-CP could prolong the lifespan of natural aging Drosophila by 11.16%. ERJ-CP could up-regulate the levels of total superoxide dismutase (T-SOD), glutathione peroxidase (GSH-Px), catalase (CAT) and down-regulate the contents of MDA and PCO. Moreover, the intake of ERJ-CP increased the food consumption, weight gain and exercise capacity of Drosophila. The results showed that ERJ-CP played a protective role in both antioxidant and anti-aging effects on Drosophila, and the anti-aging effect may be achieved by alleviating oxidative damage. It suggests that ERJ-CP could be developed as a health-promoting ingredient with antioxidant and anti-aging effects for human body.

A microRNA-30e/mitochondrial uncoupling protein 2 axis mediates TGF-ß1-induced tubular epithelial cell extracellular matrix production and kidney fibrosis.

Mitochondria dysfunction has been reported in various kidney diseases but how it leads to kidney fibrosis and how this is regulated is unknown. Here we found that mitochondrial uncoupling protein 2 (UCP2) was induced in kidney tubular epithelial cells after unilateral ureteral obstruction in mice and that mice with ablated UCP2 resisted obstruction-induced kidney fibrosis. We tested this association further in cultured NRK-52E cells and found that TGF-ß1 remarkably induced UCP2 expression. Knockdown of UCP2 largely abolished the effect of TGF-ß1, whereas overexpression of UCP2 promoted tubular cell phenotype changes. Analysis using a UCP2 mRNA-3'-untranslated region luciferase construct showed that UCP2 mRNA is a direct target of miR-30e. MiR-30e was downregulated in tubular cells from fibrotic kidneys and TGF-ß1-treated NRK-52E cells. A miR-30e mimic significantly inhibited TGF-ß1-induced tubular-cell epithelial-mesenchymal transition, whereas a miR-30e inhibitor imitated TGF-ß1 effects. Finally, genipin, an aglycone UCP2 inhibitor, significantly ameliorated kidney fibrosis in mice. Thus, the miR-30e/UCP2 axis has an important role in mediating TGF-ß1-induced epithelial-mesenchymal transition and kidney fibrosis. Targeting this pathway may shed new light for the future of fibrotic kidney disease therapy.

Genipin inhibits mitochondrial uncoupling protein 2 expression and ameliorates podocyte injury in diabetic mice.

Diabetic nephropathy (DN) is one of the most common causes of end stage renal disease (ESRD) in China, which requires renal replacement therapy. Recent investigations have suggested an essential role of podocyte injury in the initial stage of DN. This study investigated the potential therapeutic role of genipin, an active extract from a traditional Chinese medicine, on progression of DN in diabetic mice induced by intraperitoneally injection of streptozocin (STZ). In diabetic mice, orally administration of genipin postponed the progression of DN, as demonstrated by ameliorating body weight loss and urine albumin leakage, attenuating glomerular basement membrane thickness, restoring the podocyte expression of podocin and WT1 in diabetic mice. The protective role of genipin on DN is probably through suppressing the up-regulation of mitochondrial uncoupling protein 2 (UCP2) in diabetic kidneys. Meanwhile, through inhibiting the up-regulation of UCP2, genipin restores podocin and WT1 expression in cultured podocytes and attenuates glucose-induced albumin leakage through podocytes monolayer. Therefore, these results revealed that genipin inhibited UCP2 expression and ameliorated podocyte injury in DN mice.

The miR-200 family regulates TGF-ß1-induced renal tubular epithelial to mesenchymal transition through Smad pathway by targeting ZEB1 and ZEB2 expression.

Most chronic kidney injuries inevitably progress to irreversible renal fibrosis. Tubular epithelial-to-mesenchymal transition (EMT) is recognized to play pivotal roles in the process of renal fibrosis. However, a comprehensive understanding of the pathogenesis of renal scar formation and progression remains an urgent task for renal researchers. The endogenously produced microRNAs (miRNAs), proved to play important roles in gene regulation, probably regulate most genes involved in EMT. In this study, we applied microarray analysis to investigate the expression profiles of miRNA in murine interstitial fibrotic kidneys induced by unilateral ureteral obstruction (UUO). It was found that miR-200a and miR-141, two members of the miR-200 family, were downregulated at the early phase of UUO. In TGF-ß1-induced tubular EMT in vitro, it was also found that the members of the miR-200 family were downregulated in a Smad signaling-dependent manner. It was demonstrated that the miR-200 family was responsible for protecting tubular epithelial cells from mesenchymal transition by target suppression of zinc finger E-box-binding homeobox (ZEB) 1 and ZEB2, which are E-cadherin transcriptional repressors. The results suggest that downregulation of the miR-200 family initiates the dedifferentiation of renal tubules and progression of renal fibrosis, which might provide important targets for novel therapeutic strategies.