A comprehensive review of bioinformatics tools for chromatin loop calling.

Precisely calling chromatin loops has profound implications for further analysis of gene regulation and disease mechanisms. Technological advances in chromatin conformation capture (3C) assays make it possible to identify chromatin loops in the genome. However, a variety of experimental protocols have resulted in different levels of biases, which require distinct methods to call true loops from the background. Although many bioinformatics tools have been developed to address this problem, there is still a lack of special introduction to loop-calling algorithms. This review provides an overview of the loop-calling tools for various 3C-based techniques. We first discuss the background biases produced by different experimental techniques and the denoising algorithms. Then, the completeness and priority of each tool are categorized and summarized according to the data source of application. The summary of these works can help researchers select the most appropriate method to call loops and further perform downstream analysis. In addition, this survey is also useful for bioinformatics scientists aiming to develop new loop-calling algorithms.

ClusterMatch aligns single-cell RNA-sequencing data at the multi-scale cluster level via stable matching.

MOTIVATION: Unsupervised clustering of single-cell RNA sequencing (scRNA-seq) data holds the promise of characterizing known and novel cell type in various biological and clinical contexts. However, intrinsic multi-scale clustering resolutions poses challenges to deal with multiple sources of variability in the high-dimensional and noisy data. RESULTS: We present ClusterMatch, a stable match optimization model to align scRNA-seq data at the cluster level. In one hand, ClusterMatch leverages the mutual correspondence by canonical correlation analysis and multi-scale Louvain clustering algorithms to identify cluster with optimized resolutions. In the other hand, it utilizes stable matching framework to align scRNA-seq data in the latent space while maintaining interpretability with overlapped marker gene set. Through extensive experiments, we demonstrate the efficacy of ClusterMatch in data integration, cell type annotation, and cross-species/timepoint alignment scenarios. Our results show ClusterMatch's ability to utilize both global and local information of scRNA-seq data, sets the appropriate resolution of multi-scale clustering, and offers interpretability by utilizing marker genes. AVAILABILITY AND IMPLEMENTATION: The code of ClusterMatch software is freely available at https://github.com/AMSSwanglab/ClusterMatch.

Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer.

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

Advances in the mechanisms of vascular calcification in chronic kidney disease.

Vascular calcification (VC) is common in patients with advanced chronic kidney disease (CKD).A series of factors, such as calcium and phosphorus metabolism disorders, uremic toxin accumulation, inflammation and oxidative stress and cellular senescence, cause osteoblast-like differentiation of vascular smooth muscle cells, secretion of extracellular vesicles, and imbalance of calcium regulatory factors, which together promote the development of VC in CKD. Recent advances in epigenetics have provided better tools for the investigation of VC etiology and new approaches for finding more accurate biomarkers. These advances have not only deepened our understanding of the pathophysiological mechanisms of VC in CKD, but also provided valuable clues for the optimization of clinical predictors and the exploration of potential therapeutic targets. The aim of this article is to provide a comprehensive overview of the pathogenesis of CKD VC, especially the new advances made in recent years, including the various key factors mentioned above. Through the comprehensive analysis, we expect to provide a solid theoretical foundation and research direction for future studies targeting the specific mechanisms of CKD VC, the establishment of clinical predictive indicators and the development of potential therapeutic strategies.

A deep learning model to identify gene expression level using cobinding transcription factor signals.

Gene expression is directly controlled by transcription factors (TFs) in a complex combination manner. It remains a challenging task to systematically infer how the cooperative binding of TFs drives gene activity. Here, we quantitatively analyzed the correlation between TFs and surveyed the TF interaction networks associated with gene expression in GM12878 and K562 cell lines. We identified six TF modules associated with gene expression in each cell line. Furthermore, according to the enrichment characteristics of TFs in these TF modules around a target gene, a convolutional neural network model, called TFCNN, was constructed to identify gene expression level. Results showed that the TFCNN model achieved a good prediction performance for gene expression. The average of the area under receiver operating characteristics curve (AUC) can reach up to 0.975 and 0.976, respectively in GM12878 and K562 cell lines. By comparison, we found that the TFCNN model outperformed the prediction models based on SVM and LDA. This is due to the TFCNN model could better extract the combinatorial interaction among TFs. Further analysis indicated that the abundant binding of regulatory TFs dominates expression of target genes, while the cooperative interaction between TFs has a subtle regulatory effects. And gene expression could be regulated by different TF combinations in a nonlinear way. These results are helpful for deciphering the mechanism of TF combination regulating gene expression.

Methyltransferase Like-3-Mediated N6-Methyladenosine Modification of Long Noncoding RNA Hepatocyte Nuclear Factor 1a Antisense RNA 1/Hepatocyte Nuclear Factor 4a Antisense RNA 1 Regulates Cytochrome P450 Enzyme Expression.

Interindividual variations in the expression and activity of cytochrome P450 enzymes (CYPs) led to lower therapeutic efficacy or adverse drug events. We previously demonstrated that CYPs are regulated by the long noncoding RNAs (lncRNAs) hepatocyte nuclear factor 1a antisense RNA 1 (HNF1A-AS1) and HNF4A-AS1 via transcription factors (TFs) including hepatocyte nuclear factor 1a (HNF1A), hepatocyte nuclear factor 4a (HNF4A), and pregnane X receptor (PXR). However, the upstream mechanisms regulating HNF1A-AS1 and HNF4A-AS1 are poorly understood. N6-methyladenosine (m6A) is a prevalent epitranscriptomic modification in mammalian RNA. Therefore, the aim of this study was to investigate whether m6A modification regulates the expression of HNF1A-AS1 and HNF4A-AS1 and affects CYP expression in HepG2 and Huh7 cells. The methyltransferase-like 3 (METTL3) inhibitor, STM2457, significantly suppressed the expression of HNF1A-AS1 and induced HNF4A-AS1 expression. Consistent with this, a loss-of-function assay of METTL3 in the cell lines resulted in the downregulation of HNF1A-AS1 and its downstream HNF1A, PXR, and CYPs at the RNA level, as well as the downregulation of some CYPs proteins, and upregulation of HNF4A-AS1. The results of gain-of-function experiments showed the opposite trend. Mechanistically, subsequent RNA stability experiments confirmed that METTL3 affected the stability of both lncRNAs, but in opposite ways; that is, METTL3 reduced HNF1A-AS1 stability and increased HNF4A-AS1 stability. Rescue experiments confirmed that the regulation of METTL3 on TFs and CYPs may require the involvement of these two lncRNAs. Altogether, our study demonstrates that METTL3 is involved in TFs-mediated CYP expression by affecting HNF1A-AS1/HNF4A-AS1 stability. SIGNIFICANCE STATEMENT: Although the impact of long noncoding RNAs (lncRNAs) including hepatocyte nuclear factor 1a antisense RNA 1 (HNF1A-AS1) and hepatocyte nuclear factor 4a antisense RNA 1 (HNF4A-AS1) on the downstream transcription factor (TF) and cytochrome P450 enzyme (CYP) expression is well studied, the upstream regulation of these two lncRNAs by methyltransferase-like 3 (METTL3) remains unexplored. This study reveals that METTL3 is involved in the regulation of lncRNA-TF-CYP expression by affecting the stability of HNF1A-AS1 and HNF4A-AS1 in HepG2 and Huh7 cells.

Relationship between serum vitamin D levels and thyroid- and parathyroid-related diseases: a Mendelian randomisation study.

Previous studies have indicated an association between vitamin D and thyroid- and parathyroid-related diseases. However, it remains unclear whether it is a cause of the disease, a side effect of treatment or a consequence of the disease. The Mendelian randomisation (MR) study strengthens the causal inference by controlling for non-heritable environmental confounders and reverse causation. In this study, a two-sample bidirectional MR analysis was conducted to investigate the causal relationship between serum vitamin D levels and thyroid- and parathyroid-related diseases. Inverse variance weighted, weighted median and MR-Egger methods were performed, the Cochran Q test was used to evaluate the heterogeneity and the MR-PRESSO and MR-Egger intercepts were utilised to assess the possibility of pleiotropy. The Bonferroni-corrected significance threshold was 0·0038. At the Bonferroni-corrected significance level, we found that vitamin D levels suggestively decreased the risk of benign parathyroid adenoma (OR = 0·244; 95 % CI 0·074, 0·802; P = 0·0202) in the MR analyses. In the reverse MR study, a genetically predicted risk of thyroid cancer suggestively increased the risk of elevated vitamin D (OR = 1·007; 95 % CI 1·010, 1·013; P = 0·0284), chronic thyroiditis significantly increased the risk of elevated vitamin D (OR = 1·007; 95 % CI 1·002, 1·011; P = 0·0030) and thyroid nodules was significantly decreased the vitamin D levels (OR = 0·991; 95 % CI 0·985, 0·997; P = 0·0034). The findings might be less susceptible to horizontal pleiotropy and heterogeneity (P > 0·05). This study from a gene perspective indicated that chronic thyroiditis and thyroid nodules may impact vitamin D levels, but the underlying mechanisms require further investigation.

Two Stable Pillar-Layered Zn-LMOFs for Highly Fluorescence Sensing of Inorganic Pollutants and Nitro Aromatic Compounds in Water.

Luminescent metal-organic frameworks (LMOFs) are a potential class of functional materials for the photoluminescent detection of a wide range of analytes as well as for the detection of pollutants in wastewater. Herein, by using the pillar-layered strategy, two new luminescence Zn-LMOFs (JLU-MOF222 and JLU-MOF223) were successfully solvothermal synthesized. The 2D layers are both consisting of Zn2+ and TPHC [TPHC = (1,1':2',1″-terphenyl)-3,3″,4,4',4″,5'-hexacarboxylic acid] ligands and then pillared by the different N-donor ligands to form the 3D Zn-LMOFs with fsh topology. Benefiting from the uncoordinated carboxylate sites, uncoordinated N atom, or -NH2 group in the pillaring ligands and excellent stability in pH = 2-13 aqueous phase, JLU-MOF222 and JLU-MOF223 not only can sensitively detect trace amounts of inorganic pollutants (Fe3+, Cr2O72-) and nitro aromatic compounds TNP and 2,4-DNP (TNP = 2,4,6- trinitrophenol, 2,4-DNP = 2,4-dinitrophenol) through luminescence quenching but also exhibit high selectivity of other anti-interference competing analytes. The two new Zn-LMOFs can be used as potential luminescent sensors for pollutant detection in water due to their high KSV and low limit of detection (LOD).

Molecular Pathogenic Mechanisms of IgA Nephropathy Secondary to COVID-19 mRNA Vaccination.

INTRODUCTION: Accumulating evidence has disclosed that IgA nephropathy (IgAN) could present shortly after the second dose of COVID-19 mRNA vaccine. However, the undying mechanism remains unclear and we aimed to investigate the potential molecular mechanisms. METHODS: We downloaded gene expression datasets of COVID-19 mRNA vaccination (GSE201535) and IgAN (GSE104948). Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify co-expression modules related to the second dose of COVID-19 mRNA vaccination and IgAN. Differentially expressed genes (DEGs) were screened, and a transcription factor (TF)-miRNA regulatory network and protein-drug interaction were constructed for the shared genes. RESULTS: WGCNA identified one module associated with the second dose of COVID-19 mRNA vaccine and four modules associated with IgAN. Gene ontology (GO) analyses revealed enrichment of cell cycle-related processes for the COVID-19 mRNA vaccine hub genes and immune effector processes for the IgAN hub genes. We identified 74 DEGs for the second dose of COVID-19 mRNA vaccine and 574 DEGs for IgAN. Intersection analysis with COVID-19 vaccine-related genes led to the identification of two shared genes, TOP2A and CEP55. The TF-miRNA network analysis showed that hsa-miR-144 and ATF1 might regulate the shared hub genes. CONCLUSIONS: This study provides insights into the common pathogenesis of COVID-19 mRNA vaccination and IgAN. The identified pivotal genes may offer new directions for further mechanistic studies of IgAN secondary to COVID-19 mRNA vaccination.

Incarvine C and its analogues inhibit the formation of cell cytoskeleton by targeting Rac1.

Ras-related C3 botulinum toxin substrate 1 (Rac1) has emerged as a key regulator in the treatment of cancer metastasis because of its involvement in the formation of cell plate pseudopods and effects on cell migration. In this study, we found that incarvine C, a natural product isolated from Incarvillea sinensis, and its seven analogues exhibited antitumour activity by inhibiting cell cytoskeleton formation, with moderate cytotoxicity. Accordingly, these compounds inhibited the cytoskeleton-mediated migration and invasion of MDA-MB-231 cells, with inhibition rates ranging from 37.30 % to 69.72 % and 51.27 % to 70.90 % in vitro, respectively. Moreover, they induced G2/M phase cell cycle arrest in MDA-MB-231 cells. A pull-down assay revealed that the interaction between Rac1 and its downstream effector protein PAK1 was inhibited by these compounds and that the compound Ano-6 exhibited substantial activity, with an inhibition rate of more than 90 %. Molecular docking showed that incarvine C and its analogues could bind to the nucleotide-binding pocket of Rac1, maintaining high levels of inactivated Rac1. As Ano-6 exhibited significant activity in vitro, its anti-cancer activity was tested in vivo. Four weeks of oral treatment with Ano-6 was well-tolerated in mice, and it induced a potential anti-tumour response in xenografts of MDA-MB-231 cells. Further studies demonstrated that Ano-6 was enriched in tumour tissues after 2 h of administration and induced an increase in the number of dead tumour cells. In summary, these findings not only reveal the mechanism of incarvine C but also provide a new molecular template for Rac1 inhibitors and identify a promising candidate for breast cancer treatment.

An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been reported to effectively forecast severe mental distress. This study aimed to develop and validate an advanced AI tool for predicting the likelihood of severe mental distress in college students. METHODS: A total of 2088 college students from five universities were enrolled in this study. Participants were randomly divided into a training group (80%) and a validation group (20%). Various machine learning models, including logistic regression (LR), extreme gradient boosting machine (eXGBM), decision tree (DT), k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM), were employed and trained in this study. Model performance was evaluated using 11 metrics, and the highest scoring model was selected. In addition, external validation was conducted on 751 participants from three universities. The AI tool was then deployed as a web-based AI application. RESULTS: Among the models developed, the eXGBM model achieved the highest area under the curve (AUC) value of 0.932 (95% CI: 0.911-0.949), closely followed by RF with an AUC of 0.927 (95% CI: 0.905-0.943). The eXGBM model demonstrated superior performance in accuracy (0.850), precision (0.824), recall (0.890), specificity (0.810), F1 score (0.856), Brier score (0.103), log loss (0.326), and discrimination slope (0.598). The eXGBM model also received the highest score of 60 based on the evaluation scoring system, while RF achieved a score of 49. The scores of LR, DT, and SVM were only 19, 32, and 36, respectively. External validation yielded an impressive AUC value of 0.918. CONCLUSIONS: The AI tool demonstrates promising predictive performance for identifying college students at risk of severe mental distress. It has the potential to guide intervention strategies and support early identification and preventive measures.

Design of eco-friendly antifreeze peptides as novel inhibitors of gas-hydration kinetics.

In this study, peptides designed using fragments of an antifreeze protein (AFP) from the freeze-tolerant insect Tenebrio molitor, TmAFP, were evaluated as inhibitors of clathrate hydrate formation. It was found that these peptides exhibit inhibitory effects by both direct and indirect mechanisms. The direct mechanism involves the displacement of methane molecules by hydrophobic methyl groups from threonine residues, preventing their diffusion to the hydrate surface. The indirect mechanism is characterized by the formation of cylindrical gas bubbles, the morphology of which reduces the pressure difference at the bubble interface, thereby slowing methane transport. The transfer of methane to the hydrate interface is primarily dominated by gas bubbles in the presence of antifreeze peptides. Spherical bubbles facilitate methane migration and potentially accelerate hydrate formation; conversely, the promotion of a cylindrical bubble morphology by two of the designed systems was found to mitigate this effect, leading to slower methane transport and reduced hydrate growth. These findings provide valuable guidance for the design of effective peptide-based inhibitors of natural-gas hydrate formation with potential applications in the energy and environmental sectors.

Construction of hub transcription factor-microRNAs-messenger RNA regulatory network in recurrent implantation failure.

PURPOSE: Recurrent implantation failure (RIF) affects up to 10% of in vitro fertilization (IVF) patients worldwide. However, the pathogenesis of RIF remains unclear. This study was aimed at identifying hub transcription factors (TFs) of RIF in bioinformatics approaches. METHODS: The GSE111974 (mRNA), GSE71332 (miRNA), and GSE103465 (mRNA) datasets were downloaded from the Gene Expression Omnibus database from human endometrial tissue using R version 4.2.1 and used to identify differentially expressed TFs (DETFs), differentially expressed miRNAs, and differentially expressed genes for RIF, respectively. DETFs were subjected to functional enrichment analysis and the protein-protein interaction network analysis using the Search Tool for the Retrieval of Interacting Genes (version 11.5) database. Hub TFs were identified using the cytoHubb plug-in, after which a hub TF-miRNA-mRNA network was constructed using Cytoscape v3.8.2. RESULTS: Fifty-seven DETFs were identified, in which Gene Ontology analysis revealed to be mainly involved in the regulation of transcription. Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested that DETFs were enriched in transcriptional misregulation in cancer, aldosterone synthesis and secretion, AMPK signaling pathway, and cGMP-PKG signaling pathway. EOMES, NKX2-1, and POU5F1 were identified as hub TFs, and a hub TF-miRNA-mRNA regulatory network was constructed using these three hub TFs, four miRNAs, and four genes. CONCLUSION: Collectively, we identified three promising molecular biomarkers for the diagnosis of RIF, which may further be potential therapeutic targets. This study provides novel insights into the molecular mechanisms underlying RIF. However, further experiments are required to verify these results.

Puccinia suaveolens Causing Leaf Rust on Cirsium setosum in China.

Thistle, Cirsium setosum (Willd.) M. Bieb., is widely distributed in China as a common weed in fields. It is also used as a traditional Chinese medicine for cooling blood, stopping bleeding, dispelling stasis, detoxifying, and resolving carbuncle. In 2023, we found a rust disease on plants of Cirsium setosum in the experimental field of Hebei Agricultural University, Baoding, Hebei Province, China, with incidence of 15% - 25% (Fig. S1 A, B). The diseased leaves turned yellow, and the leaf edges were slightly rolled. The yellow, oil-like pycnia and pycniospores covered the baxial surface of leaves, and brown pustules were produced after 2-3 weeks. On the adaxial surface of the leaves, the brown rust pustules were mainly along the leaf veins. Stems were also be infected later, and dark pustules were scattered. The diseased plants were relatively short and small, and produced relatively small or no flowers compared to healthy plants. A total of 100 plants with typical leaf rust symptoms and signs were collected. To confirm the pathogenicity, healthy plants of thistle were sprayed with 5 ml of urediospores suspension (2.6×105/ml), and plants sprayed with sterile distilled water were treated as control. The sprayed plants were incubated under high moist conditions at 18°C for 24 h, and the inoculated plants were grown at 20°C in a greenhouse. Ten days after inoculation, the plants inoculated with urediniospores showed rust symptoms with uredinia and urediniospores on the leaves (Fig. S1 C), while the control plants were healthy. For morphological characterization, urediospores were picked from the naturally infected plants and placed in a drop of sterile water on a glass slide using a sterile needle, and observed and measured under a microscope. Urediospores were nearly spherical, brown-yellow, and measured 15 - 25 µm in diameter (n=100) (Fig. S1 D). Telia were scattered on the baxial surface of the naturally infected leaves, and teliospores were oval, yellow-brown, double-celled, with very short hyaline pedicels, and measured 15-20 × 15-30 µm (n=100) (Fig. S1 E). For molecular characterization, about 200 µg of urediniospores was collected and placed in a 1.5 ml sterile centrifuge tube, and genomic DNA was extracted using the cetyl-trimethylammonium bromide method (Gawel et al. 1991). The internal transcribed spacer (ITS) region of the rDNA and the D1/D2 domain were amplified using primer pairs ITS1/ITS4 (White et al. 1990) and NL1/NL4 (Borhani et al. 2013) in polymerase chain reaction (PCR), respectively. The PCR products were sequenced, and their sequences were aligned and compared with those deposited in GenBank. The obtained sequences were deposited in GenBank (OR600240 for ITS and OR598614 for D1/D2), which were 100% identical with 100% coverage to the ITS sequence (ON063373.1) and the D1/D2 sequence (ON063379.1) of Puccinia suaveolens (Menzies 1953). Based on the morphological characteristics and DNA sequences, the isolates were identified as P. suaveolens (Fig. S1 and Fig. S2). Thistle rust caused by Puccinia obtegens has been reported in some other parts of China (Zhang 2012). To the best of our knowledge, this is the first report of P. suaveolens causing leaf rust on C. setosum in China. This discovery is helpful for control of leaf rust on thistle grown for Chines medicine and other purposes, and the rust species could be used for biological control of thistle as a weed in crop fields.

Accurate Classification and Prediction of Acute Myocardial Infarction through an ARMD Procedure.

The risk stratification of acute myocardial infarction (AMI) patients is of prime importance for clinical management and prognosis assessment. Thus, we propose an ensemble machine learning analysis procedure named ADASYN-RFECV-MDA-DNN (ARMD) to address sample-unbalanced problems and enable stratification and prediction of AMI outcomes. The ARMD analysis procedure was applied to the NMR data of sera from 534 AMI-related subjects in four categories with an extremely imbalanced sample proportion. Firstly, the adaptive synthetic sampling (ADASYN) algorithm was used to address the issue of the original sample imbalance. Secondly, the recursive feature elimination with cross-validation (RFECV) processing and random forest mean decrease accuracy (RF-MDA) algorithm was performed to identify the differential metabolites corresponding to each AMI outcome. Finally, the deep neural network (DNN) was employed to classify and predict AMI events, and its performance was evaluated by comparing the four traditional machine learning methods. Compared with the other four machine learning models, DNN presented consistent superiority in almost all of the model parameters including precision, f1-score, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and classification accuracy, highlighting the potential of deep learning in classification and stratification of clinical diseases. The ARMD analysis procedure was a practical analysis tool for supervised classification and regression modeling of clinical diseases.

Multi-omics profiling of cholangiocytes reveals sex-specific chromatin state dynamics during hepatic cystogenesis in polycystic liver disease.

BACKGROUND & AIMS: Cholangiocytes transit from quiescence to hyperproliferation during cystogenesis in polycystic liver disease (PLD), the severity of which displays prominent sex differences. Epigenetic regulation plays important roles in cell state transition. We aimed to investigate the sex-specific epigenetic basis of hepatic cystogenesis and to develop therapeutic strategies targeting epigenetic modifications for PLD treatment. METHODS: Normal and cystic primary cholangiocytes were isolated from wild-type and PLD mice of both sexes. Chromatin states were characterized by analyzing chromatin accessibility (ATAC sequencing) and multiple histone modifications (chromatin immunoprecipitation sequencing). Differential gene expression was determined by transcriptomic analysis (RNA sequencing). Pharmacologic inhibition of epigenetic modifying enzymes was undertaken in PLD model mice. RESULTS: Through genome-wide profiling of chromatin dynamics, we revealed a profound increase of global chromatin accessibility during cystogenesis in both male and female PLD cholangiocytes. We identified a switch from H3K9me3 to H3K9ac on cis-regulatory DNA elements of cyst-associated genes and showed that inhibition of H3K9ac acetyltransferase or H3K9me3 demethylase slowed cyst growth in male, but not female, PLD mice. In contrast, we found that H3K27ac was specifically increased in female PLD mice and that genes associated with H3K27ac-gained regions were enriched for cyst-related pathways. In an integrated epigenomic and transcriptomic analysis, we identified an estrogen receptor alpha-centered transcription factor network associated with the H3K27ac-regulated cystogenic gene expression program in female PLD mice. CONCLUSIONS: Our findings highlight the multi-layered sex-specific epigenetic dynamics underlying cholangiocyte state transition and reveal a potential epigenetic therapeutic strategy for male PLD patients. IMPACT AND IMPLICATIONS: In the present study, we elucidate a sex-specific epigenetic mechanism underlying the cholangiocyte state transition during hepatic cystogenesis and identify epigenetic drugs that effectively slow cyst growth in male PLD mice. These findings underscore the importance of sex difference in the pathogenesis of PLD and may guide researchers and physicians to develop sex-specific personalized approaches for PLD treatment.

CYP3A4 and CYP3A5 Expression is Regulated by CYP3A4*1G in CRISPR/Cas9-Edited HepG2 Cells.

Functional CYP3A4*1G (G>A, rs2242480) in cytochrome P450 3A4 (CYP3A4) regulates the drug-metabolizing enzyme CYP3A4 expression. The objective of this study was to investigate whether CYP3A4*1G regulates both basal and rifampicin (RIF)-induced expression and enzyme activity of CYP3A4 and CYP3A5 in gene-edited human HepG2 cells. CYP3A4*1G GG and AA genotype HepG2 cells were established using the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) single nucleotide polymorphism technology and homology-directed repair in the CYP3A4*1G GA HepG2 cell line. In CYP3A4*1G GG, GA, and AA HepG2 cells, CYP3A4*1G regulated expression of CYP3A4 and CYP3A5 mRNA and protein in an allele-dependent manner. Of note, significantly decreased expression level of CYP3A4 and CYP3A5 was observed in CYP3A4*1G AA HepG2 cells. Moreover, the results after RIF treatment showed that CYP3A4*1G decreased the induction level of CYP3A4 and CYP3A5 mRNA expression in CYP3A4*1G AA HepG2 cells. At the same time, CYP3A4*1G decreased CYP3A4 enzyme activity and tacrolimus metabolism, especially in CYP3A4*1G GA HepG2 cells. In summary, we successfully constructed CYP3A4*1G GG and AA homozygous HepG2 cell models and found that CYP3A4*1G regulates both basal and RIF-induced expression and enzyme activity of CYP3A4 and CYP3A5 in CRISPR/Cas9 CYP3A4*1G HepG2 cells. SIGNIFICANCE STATEMENT: Cytochrome P450 (CYP) 3A4*1G regulates both basal and rifampicin (RIF)-induced expression and enzyme activity of CYP3A4 and CYP3A5. This study successfully established CYP3A4*1G (G>A, rs2242480), GG, and AA HepG2 cell models using CRISPR/Cas9, thus providing a powerful tool for studying the mechanism by which CYP3A4*1G regulates the basal and RIF-induced expression of CYP3A4 and CYP3A5.

Geranylgeranylacetone-induced heat shock protein70 expression reduces retinal ischemia-reperfusion injury through PI3K/AKT/mTOR signaling.

Retinal ischemia-reperfusion (I/R) injury is a common pathophysiological stress state connected to various diseases, including acute glaucoma, retinal vascular obstruction, and diabetic retinopathy. Recent studies have suggested that geranylgeranylacetone (GGA) could increase heat shock protein70 (HSP70) level and reduce retinal ganglion cells (RGCs) apoptosis in a rat retinal I/R model. However, the underlying mechanism remains unclear. Moreover, the injury caused by retinal I/R includes not only apoptosis but also autophagy and gliosis, and the effects of GGA on autophagy and gliosis have not been reported. Our study established a retinal I/R model by anterior chamber perfusion pressuring to 110 mmHg for 60 min, followed by 4 h of reperfusion. The levels of HSP70, apoptosis-related proteins, GFAP, LC3-II, and PI3K/AKT/mTOR signaling proteins were determined by western blotting and qPCR after treatment with GGA, HSP70 inhibitor quercetin (Q), PI3K inhibitor LY294002, and mTOR inhibitor rapamycin. Apoptosis was evaluated by TUNEL staining, meanwhile, HSP70 and LC3 were detected by immunofluorescence. Our results demonstrated that GGA-induced HSP70 expression significantly reduced gliosis, autophagosome accumulation, and apoptosis in retinal I/R injury, indicating that GGA exerted protective effects on retinal I/R injury. Moreover, the protective effects of GGA mechanistically relied on the activation of PI3K/AKT/mTOR signaling. In conclusion, GGA-induced HSP70 overexpression has protective effects on retinal I/R injury by activating PI3K/AKT/mTOR signaling.

Exosomes from human urine-derived stem cells carry NRF1 to alleviate bladder fibrosis via regulating miR-301b-3p/TGFßR1 pathway.

Bladder outlet obstruction (BOO) is a common disease that always make the bladder develops from inflammation to fibrosis. This study was to investigate the effect of exosomes from human urine-derived stem cells (hUSCs) on bladder fibrosis after BOO and the underlying mechanism. The BOO mouse model was established by inserting a transurethral catheter, ligation of periurethral wire, and removal of the catheter. Mouse primary bladder smooth muscle cells (BSMCs) were isolated and treated with TGFß1 to mimic the bladder fibrosis model in vitro. Exosomes from hUSCs (hUSC-Exos) were injected into the bladder of BOO mice and added into the culture of TGFß1-induced BSMCs. The associated factors in mouse bladder tissues and BSMCs were detected. It was confirmed that the treatment of hUSC-Exos alleviated mouse bladder fibrosis and down-regulated fibrotic markers (a-SMA and collagen III) in bladder tissues and TGFß1-induced BSMCs. Overexpression of NRF1 in hUSC-Exos further improved the effects of hUSC-Exos on bladder fibrosis both in vivo and in vitro. TGFßR1 was a target of NRF1 and miR-301b-3p, and miR-301b-3p was a target of NRF1. It was next characterized that hUSC-Exos carried NRF1 to up-regulate miR-301B-3p, thereby reducing TGFßR1level. Our results illustrated that hUSC-Exos carried NRF1 to alleviate bladder fibrosis through regulating miR-301b-3p/TGFßR1 pathway.

Three Robust Isoreticular Metal-Organic Frameworks with High-Performance Selective CO2 Capture and Separation.

Based on the hard-soft acid base (HSAB) theory, three robust isoreticular metal-organic frameworks (MOFs) with nia topology were successfully synthesized by solvothermal reaction {[In3O(BHB)(H2O)3]NO3·3DMA (JLU-MOF110(In)), [Fe3O(BHB)(H2O)3]NO3 (JLU-MOF110(Fe)), and [Fe2NiO(BHB)(H2O)3] (JLU-MOF110(FeNi)) (DMA = N,N-dimethylacetamide, H6BHB = 4,4″-benzene-1,3,5-triyl-hexabenzoic acid)}. Both JLU-MOF110(In) and JLU-MOF110(Fe) are cationic frameworks, and their BET surface areas are 301 and 446 m2/g, respectively. By modification of the components of metal clusters, JLU-MOF110(FeNi) features a neutral framework, and the BET surface area is increased up to 808 m2/g. All three MOF materials exhibit high chemical and thermal stability. JLU-MOF110(In) remains stable for 24 h at pH values ranging from 1 to 11, while JLU-MOF110(Fe) and JLU-MOF110(FeNi) persist to be stable for 24 h at pH from 1 to 12. JLU-MOF110(In) exhibits thermal stability up to 350 °C, whereas JLU-MOF110(Fe) and JLU-MOF(FeNi) can be stable up to 300 °C. Thanks to the microporous cage-based structure and abundant open metal sites, JLU-MOF110(In), JLU-MOF110(Fe), and JLU-MOF110(FeNi) have excellent CO2 capture capacity (28.0, 51.5, and 99.6 cm3/g, respectively, under 298 K and 1 bar). Interestingly, the ideal adsorption solution theory results show that all three MOFs exhibit high separation selectivity toward CO2 over N2 (35.2, 43.2, and 43.2 for CO2/N2 = 0.15/0.85) and CO2 over CH4 (14.4, 11.5, and 10.1 for CO2/CH4 = 0.5/0.5) at 298 K and 1 bar. Thus, all three MOFs are potential candidates for CO2 capture and separation. Among them, JLU-MOF110(FeNi) displays the best separation potential, as revealed by dynamic column breakthrough experiments.