Role of N-acetylkynurenine in mediating the effect of gut microbiota on urinary tract infection: a Mendelian randomization study.

Introduction: This study explored the causal connections between gut microbiota (GM), urinary tract infection (UTI), and potential metabolite mediators using Mendelian randomization (MR). Methods: We utilized summary statistics from the most comprehensive and extensive genome-wide association studies (GWAS) available to date, including 196 bacterial traits for GM, 1,091 blood metabolites, 309 metabolite ratios, alongside UTI data from ukb-b-8814 and ebi-a-GCST90013890. Bidirectional MR analyses were conducted to investigate the causal links between GM and UTI. Subsequently, two MR analyses were performed to identify the potential mediating metabolites, followed by a two-step MR analysis to quantify the mediation proportion. Results: Our findings revealed that out of the total 15 bacterial traits, significant associations with UTI risk were observed across both datasets. Particularly, taxon g_Ruminococcaceae UCG010 displayed a causal link with a diminished UTI risk in both datasets (ukb-b-8814: odds ratio [OR] = 0.9964, 95% confidence interval [CI] = 0.9930-0.9997, P = 0.036; GCST90013890: OR = 0.8252, 95% CI = 0.7217-0.9436, P = 0.005). However, no substantial changes in g_Ruminococcaceae UCG010 due to UTI were noted (ukb-b-8814: ß = 0.51, P = 0.87; ebi-a-GCST90013890: ß = -0.02, P = 0.77). Additionally, variations in 56 specific metabolites were induced by g_Ruminococcaceae UCG010, with N-acetylkynurenine (NAK) exhibiting a causal correlation with UTI. A negative association was found between g_Ruminococcaceae UCG010 and NAK (OR: 0.8128, 95% CI: 0.6647-0.9941, P = 0.044), while NAK was positively associated with UTI risk (OR: 1.0009; 95% CI: 1.0002-1.0016; P = 0.0173). Mediation analysis revealed that the association between g_Ruminococcaceae UCG010 and UTI was mediated by NAK with a mediation proportion of 5.07%. Discussion: This MR study provides compelling evidence supporting the existence of causal relationships between specific GM taxa and UTI, along with potential mediating metabolites.

PanDepth, an ultrafast and efficient genomic tool for coverage calculation.

Coverage quantification is required in many sequencing datasets within the field of genomics research. However, most existing tools fail to provide comprehensive statistical results and exhibit limited performance gains from multithreading. Here, we present PanDepth, an ultra-fast and efficient tool for calculating coverage and depth from sequencing alignments. PanDepth outperforms other tools in computation time and memory efficiency for both BAM and CRAM-format alignment files from sequencing data, regardless of read length. It employs chromosome parallel computation and optimized data structures, resulting in ultrafast computation speeds and memory efficiency. It accepts sorted or unsorted BAM and CRAM-format alignment files as well as GTF, GFF and BED-formatted interval files or a specific window size. When provided with a reference genome sequence and the option to enable GC content calculation, PanDepth includes GC content statistics, enhancing the accuracy and reliability of copy number variation analysis. Overall, PanDepth is a powerful tool that accelerates scientific discovery in genomics research.

VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs.

Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and clustering analysis, and visualization based on VCF formatted SNPs. We implemented five Kinship estimation methods and three clustering methods for its users to choose from. Moreover, unlike other PCA tools, VCF2PCACluster possesses a clustering function based on PCA result, which enabling users to automatically and clearly know about population structure. We demonstrated the same accuracy but a higher performance of this tool in performing PCA analysis on tens of millions of SNPs compared to another popular PLINK2 software, especially in peak memory usage that is independent of the number of SNPs in VCF2PCACluster.

A calculation method for optical properties of yolk shell based on deep learning.

The yolk shell is widely used in optoelectronic devices due to its excellent optical properties. Compared to single metal nanostructures, yolk shells have more controllable degrees of freedom, which may make experiments and simulations more complex. Using neural networks can efficiently simplify the computational process of yolk shell. In our work, the relationship between the size and the absorption efficiency of the yolk-shell structure is established using a backpropagation neural network (BPNN), significantly simplifying the calculation process while ensuring accuracy equivalent to discrete dipole scattering (DDSCAT). The absorption efficiency of the yolk shell was comprehensively described through the forward and reverse prediction processes. In forward prediction, the absorption spectrum of yolk shell is obtained through its size parameter. In reverse prediction, the size parameters of yolk shells are predicted through absorption spectra. A comparison with the traditional DDSCAT demonstrated the high precision prediction capability and fast computation of this method, with minimal memory consumption.

Climate warming impacts chewing Spodoptera litura negatively but sucking Corythucha marmorata positively on native Solidago canadensis.

Insect-plant interactions are among importantly ecological processes, and rapid environmental changes such as temperature and resource fluctuations can disrupt long-standing insect-plant interactions. While individual impacts of climate warming, atmospheric nitrogen (N) deposition, and plant provenance on insect-plant interactions are well studied, their joint effects on insect-plant interactions are less explored in ecologically realistic settings. To this end, we performed five experiments with native and invasive Solidago canadensis populations from home and introduced ranges and two insect herbivores (leaf-chewing Spodoptera litura and sap-sucking Corythucha marmorata) in the context of climate warming and N deposition. We determined leaf defensive traits, feeding preference, and insect growth and development, and quantified the possible associations among climate change, host-plant traits, and insect performance with structural equation modeling. First, native S. canadensis populations experienced higher damage by S. litura but lower damage by C. marmorata than invasive S. canadensis populations in the ambient environment. Second, warming decreased the leaf consumption, growth, and survival of S. litura on native S. canadensis populations, but did not affect these traits on invasive S. canadensis populations; warming increased the number of C. marmorata on native S. canadensis populations via direct facilitation, but decreased that on invasive S. canadensis populations via indirect suppression. Third, N addition enhanced the survival of S. litura on native S. canadensis populations, and its feeding preference and leaf consumption on invasive S. canadensis populations. Finally, warming plus N addition exhibited non-additive effects on insect-plant interactions. Based on these results, we tentatively conclude that climate warming could have contrasting effects on insect-plant interactions depending on host-plant provenance and that the effects of atmospheric N deposition on insects might be relatively weak compared to climate warming. Future studies should focus on the molecular mechanisms underlying these different patterns.

IgA nephropathy: gut microbiome regulates the production of hypoglycosilated IgA1via the TLR4 signaling pathway.

BACKGROUND: IgA nephropathy (IgAN) is a major cause of primary glomerulonephritis characterized by mesangial deposits of galactose-deficient IgA1 (Gd-IgA1). Toll-like receptors (TLRs), particularly TLR4 are involved in the pathogenesis of IgAN. The role of gut microbiota on IgAN patients was recently investigated. However, whether gut microbial modifications of Gd-IgA1 through TLR4 play a role in IgAN remains unclear. METHODS: We recruited subjects into four groups, including 48 patients with untreated IgAN, 22 treated IgAN patients (IgANIT), 22 primary membranous nephropathy (MN), and 31 healthy controls (HCs). Fecal samples were collected to analyze changes in gut microbiome. Gd-IgA1 levels, expression of TLR4, B-cell stimulators, and intestinal barrier function were evaluated in all subjects. C57BL/6 mice were treated with a broad-spectrum antibiotic cocktail to deplete the gut microbiota and then gavaged with fecal microbiota transplanted fromclinical subjects of every group. Gd-IgA1 and TLR4 pathway were detected in peripheral blood mononuclear cells (PBMCs) from IgAN and HCs co-incubated with Lipopolysaccharide (LPS) and TLR4 inhibitor. RESULTS: Compared with other three groups, different compositions and decreased diversity demonstrated gut dysbiosis in un-treated IgAN, especially the enrichment of Escherichia -Shigella. Elevated Gd-IgA1 levels were found in un-treated IgAN patients and correlated with gut dysbiosis, TLR4, B-cell stimulators, indexes of intestinal barrier damage, and proinflammatory cytokines. In vivo, mice colonized with gut microbiota from IgAN and IgANIT patients, copied the IgAN phenotype with the activation of TLR4/MyD88/NF-κB pathway, B-cell stimulators in the intestine, and complied with enhanced proinflammatory cytokines. In vitro, LPS activated TLR4/MyD88/NF-κB pathway, B-cell stimulators and proinflammatory cytokines in the PBMCs from IgAN patients, which resulted in overproduction of Gd-IgA1 and inhibited by TLR4 inhibitor. CONCLUSIONS: Our results illustrated that gut-kidney axis was involved in the pathogenesis of IgAN. Gut dysbiosis could stimulate the overproduction of Gd-IgA1 by TLR4 signaling pathway production and B-cell stimulators.

Co-Housing and Fecal Microbiota Transplantation: Technical Support for TCM Herbal Treatment of Extra-Intestinal Diseases Based on Gut Microbial Ecosystem Remodeling.

Dysregulation of the gut microbial ecosystem (GME) (eg, alterations in the gut microbiota, gut-derived metabolites, and gut barrier) may contribute to the onset and progression of extra-intestinal diseases. Previous studies have found that Traditional Chinese Medicine herbs (TCMs) play an important role in manipulating the GME, but a prominent obstacle in current TCM research is the causal relationship between GME and disease amelioration. Encouragingly, co-housing and fecal microbiota transplantation (FMT) provide evidence-based support for TCMs to treat extra-intestinal diseases by targeting GME. In this review, we documented the principles, operational procedures, applications and limitations of the key technologies (ie, co-housing and FMT); furthermore, we provided evidence that TCM works through the GME, especially the gut microbiota (eg, SCFA- and BSH-producing bacteria), the gut-derived metabolites (eg, IS, pCS, and SCFAs), and intestinal barrier to alleviate extra-intestinal diseases. This will be beneficial in constructing microecological pathways for TCM treatment of extra-intestinal diseases in the future.

Disaster experience and resident risk preference: Evidence from China household finance survey.

China is one of the countries hardest hit by disasters. Disaster shocks not only cause a large number of casualties and property damage but also have an impact on the risk preference of those who experience it. Current research has not reached a consensus conclusion on the impact of risk preferences. This paper empirically analyzes the effects of natural and man-made disasters on residents' risk preference based on the data of the China Household Financial Survey (CHFS) in 2019. The results indicate that: (1) Both natural and man-made disasters can significantly lead to an increase in the risk aversion of residents, and man-made disasters have a greater impact. (2) Education background plays a negative moderating role in the impact of man-made disasters on residents' risk preference. (3) Natural disaster experiences have a greater impact on the risk preference of rural residents, while man-made disaster experiences have a greater impact on the risk preference of urban residents. Natural disaster experiences make rural residents more risk-averse, while man-made disaster experiences make urban residents more risk-averse. The results provide new evidence and perspective on the negative impact of disaster shocks on the social life of residents.

McAPRR2: The Key Regulator of Domesticated Pericarp Color in Bitter Gourd.

Pericarp color is a crucial commercial trait influencing consumer preferences for bitter gourds. However, until now, the gene responsible for this trait has remained unidentified. In this study, we identified a gene (McAPRR2) controlling pericarp color via a genome-wide association study (GWAS) utilizing the resequencing data of 106 bitter gourd accessions. McAPRR2 exhibits three primary haplotypes: Hap1 is a wild type with a green pericarp, Hap2 is a SA (South Asian) and SEA (Southeast Asia) type with a green pericarp, and Hap3 is primarily a SEA type with a light green pericarp. The McAPRR2 haplotype is significantly correlated with both pericarp color and ecological type. Importantly, McAPRR2 with the light green pericarp demonstrated premature termination due to a 15 bp sequence insertion. The phylogenetic tree clustered according to pericarp color and ecological type, using SNPs located in the McAPRR2 gene and its promoter. High πwild/SEA and πSA/SEA values indicate high nucleotide diversity between wild and SEA types and between SA and SEA types in the McAPRR2 gene. The haplotypes, phylogenetic tree, and nucleotide diversity of McAPRR2 suggest that McAPRR2 has undergone domestication selection. This study identifies McAPRR2 as the key gene determining pericarp color in bitter gourds and introduces a novel insight that McAPRR2 is subject to domestication selection.

A Novel Approach for Dry Cutting Inconel 718 in a More Sustainable and Low-Cost Way by Actively and Purposely Utilizing the Built-Up Layer.

Due to its physical and mechanical properties, Inconel 718 remains a difficult-to-cut material and there is an urgent need to develop a more sustainable and low-cost way to machine it. A novel approach for dry cutting Inconel 718 by actively and purposely utilizing the built-up layer (BUL), which can be called the self-protective tool (SPT) method, is proposed and investigated in detail in this paper. Various cutting experiments were carried out using the age-treated Inconel 718 and uncoated cemented carbide tools. The formation condition of the BUL, its formation mechanism, its stability, and its protective effect were examined by measuring the tools after cutting using a scanning electron microscope (SEM) and laser confocal microscopy (LCM). The influences of BUL on the cutting process were investigated using cutting force analysis and surface roughness analysis. The results confirmed that the stability of the BUL is very high, and the BUL can not only significantly protect the tool from wear but also reduce friction at the tool-chip interface and maintain surface roughness. It also revealed that the height of the BUL can play a very important role in its protective effect. Comparative experiments verified the effectiveness and generalizability of the proposed SPT method.

Contrast-enhanced ultrasonography for identifying acute kidney injury in brain-dead donors.

Background: Acute kidney injury (AKI) is frequently found in deceased donors; however, few studies have reported the use of imaging to detect and identify this phenomenon. The purpose of this study was to detect renal microcirculatory perfusion in brain-dead donors using contrast-enhanced ultrasonography (CEUS), investigate the value of CEUS in identifying AKI, and analyze the correlation between CEUS and preimplantation biopsy results and early post-transplant renal function of grafts. Methods: This prospective study recruited 94 kidneys from brain-dead donors (AKI =44, non-AKI =50) from August 2020 to November 2022. The inclusion criteria were age ≥18 years and brain death. The exclusion criteria encompassed donors maintained with extracorporeal membrane oxygenation (ECMO) and the presence of irregular kidney anatomy. The mean age of the donors was 45.1±10.4 [standard deviation (SD)] years, and the majority were male (86.2%). CEUS was performed prior to organ procurement, and time-intensity curves (TICs) were constructed. The time to peak (TTP) and peak intensity (PI) of kidney segmental artery (KA), kidney cortex (KC), and kidney medulla (KM) were calculated using TIC analysis. Results: Arrival time (AT) of KA (P<0.001) and TTP of kidney cortex (TTPKC) (P<0.001) of the non-AKI group were significantly shorter than those of the AKI group. The PI of the KA (P=0.003), KM (P=0.005), and kidney cortex (PIKC; P<0.001) of the non-AKI group were significantly higher than those of the AKI group. Multivariable logistic regression analysis showed that serum creatinine [odds ratio (OR) =1.06; 95% CI: 1.03-1.1; P<0.001], TTPKC (OR =1.38; 95% CI: 1.03-1.84; P=0.03), and PIKC (OR =0.95; 95% CI: 0.91-1; P=0.046) were the independent factors of AKI. The area under the receiver operating characteristic curve (AUC) for identifying AKI for TTPKC and PIKC was 0.73 and 0.71, respectively. TTPKC showed a weak correlation with interstitial fibrosis (r=0.23; P=0.03), PIKC showed a weak correlation with arterial intimal fibrosis ((r=-0.29; P=0.004) and arteriolar hyalinosis (r=-0.27; P=0.008), and PIKC showed the strongest correlation with eGFR on postoperative day 7 (r=-0.46; P=0.046) in the donor kidneys with AKI. Conclusions: CEUS can be used to identify AKI in brain-dead donors. Furthermore, there is a correlation between CEUS-derived parameters and pretransplant biopsy results and early preimplantation renal function of grafts.

Contrast-enhanced ultrasonography-based renal blood perfusion in brain-dead donors predicts early graft function.

PURPOSE: The aim of this study was to quantify renal microcirculatory perfusion in braindead donors using contrast-enhanced ultrasonography (CEUS), and to establish an accurate, noninvasive, and convenient index for predicting delayed graft function (DGF) post-transplantation. METHODS: In total, 90 brain-dead donor kidneys (training group, n=60; validation group, n=30) examined between August 2020 and November 2022 were recruited in this prospective study. CEUS was performed on the kidneys of brain-dead donors 24 hours before organ procurement and time-intensity curves were constructed. The main measures were arrival time, time to peak, and peak intensity of the kidney segmental arteries, cortex, and medulla. Recipients were divided into DGF and non-DGF groups according to early post-transplant graft function. The area under the receiver operating characteristic curve (AUC) was used to assess diagnostic performance. RESULTS: The arrival time of the kidney segmental artery and cortex and the time interval between the time to peak of the segmental artery and cortex were identified as independent factors associated with DGF by multivariate stepwise regression analysis. A new index for the joint prediction model of three variables, the contrast-enhanced ultrasonography/Kidney Donor Profile index (CEUS-KDPI), was developed. CEUS-KDPI showed high accuracy for predicting DGF (training group: AUC, 0.91; sensitivity, 90.5%; specificity, 92.3%; validation group: AUC, 0.84; sensitivity, 75.0%; specificity, 92.3%). CONCLUSION: CEUS-KDPI accurately predicted DGF after kidney transplantation. CEUS may be a potential noninvasive tool for bedside examinations before organ procurement and may be used to predict early renal function after kidney transplants kidneys from donors after brain death.

NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes.

SUMMARY: Large-scale comparative genomic studies have provided important insights into species evolution and diversity, but also lead to a great challenge to visualize. Quick catching or presenting key information hidden in the vast amount of genomic data and relationships among multiple genomes requires an efficient visualization tool. However, current tools for such visualization remain inflexible in layout and/or require advanced computation skills, especially for visualization of genome-based synteny. Here, we developed an easy-to-use and flexible layout tool, NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats. AVAILABILITY AND IMPLEMENTATION: NGenomeSyn is freely available at GitHub (https://github.com/hewm2008/NGenomeSyn) and Zenodo (https://doi.org/10.5281/zenodo.7645148).

Guiding Drug Repositioning for Cancers Based on Drug Similarity Networks.

Drug repositioning aims to discover novel clinical benefits of existing drugs, is an effective way to develop drugs for complex diseases such as cancer and may facilitate the process of traditional drug development. Meanwhile, network-based computational biology approaches, which allow the integration of information from different aspects to understand the relationships between biomolecules, has been successfully applied to drug repurposing. In this work, we developed a new strategy for network-based drug repositioning against cancer. Combining the mechanism of action and clinical efficacy of the drugs, a cancer-related drug similarity network was constructed, and the correlation score of each drug with a specific cancer was quantified. The top 5% of scoring drugs were reviewed for stability and druggable potential to identify potential repositionable drugs. Of the 11 potentially repurposable drugs for non-small cell lung cancer (NSCLC), 10 were confirmed by clinical trial articles and databases. The targets of these drugs were significantly enriched in cancer-related pathways and significantly associated with the prognosis of NSCLC. In light of the successful application of our approach to colorectal cancer as well, it provides an effective clue and valuable perspective for drug repurposing in cancer.

Conditional TransGAN-Based Data Augmentation for PCB Electronic Component Inspection.

Automatic recognition and positioning of electronic components on PCBs can enhance quality inspection efficiency for electronic products during manufacturing. Efficient PCB inspection requires identification and classification of PCB components as well as defects for better quality assurance. The small size of the electronic component and PCB defect targets means that there are fewer feature areas for the neural network to detect, and the complex grain backgrounds of both datasets can cause significant interference, making the target detection task challenging. Meanwhile, the detection performance of deep learning models is significantly impacted due to the lack of samples. In this paper, we propose conditional TransGAN (cTransGAN), a generative model for data augmentation, which enhances the quantity and diversity of the original training set and further improves the accuracy of PCB electronic component recognition. The design of cTransGAN brings together the merits of both conditional GAN and TransGAN, allowing a trained model to generate high-quality synthetic images conditioned on the class embeddings. To validate the proposed method, we conduct extensive experiments on two datasets, including a self-developed dataset for PCB component detection and an existing dataset for PCB defect detection. Also, we have evaluated three existing object detection algorithms, including Faster R-CNN ResNet101, YOLO V3 DarkNet-53, and SCNet ResNet101, and each is validated under four experimental settings to form an ablation study. Results demonstrate that the proposed cTransGAN can effectively enhance the quality and diversity of the training set, leading to superior performance on both tasks. We have open-sourced the project to facilitate further studies.

Causal Effects of Specific Gut Microbiota on Chronic Kidney Diseases and Renal Function-A Two-Sample Mendelian Randomization Study.

BACKGROUND: Targeting the gut microbiota may become a new therapeutic to prevent and delay the progression of chronic kidney disease (CKD). Nonetheless, the causal relationship between specific intestinal flora and CKD is still unclear. MATERIALS AND METHOD: To identify genetically predicted microbiota, we used summary data from genome-wide association studies on gut microbiota in 18340 participants from 24 cohorts. Furthermore, we genetically predicted the causal relationship between 211 gut microbiotas and six phenotypes (outcomes) (CKD, estimated glomerular filtration rate (eGFR), urine albumin to creatinine ratio (UACR), dialysis, rapid progress to CKD, and rapid decline of eGFR). Four Mendelian randomization (MR) methods, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode were used to investigate the casual relationship between gut microbiotas and various outcomes. The result of IVW was deemed as the primary result. Then, Cochrane's Q test, MR-Egger, and MR-PRESSO Global test were used to detect heterogeneity and pleiotropy. The leave-one method was used for testing the stability of MR results and Bonferroni-corrected was used to test the strength of the causal relationship between exposure and outcome. RESULTS: Through the MR analysis of 211 microbiotas and six clinical phenotypes, a total of 36 intestinal microflora were found to be associated with various outcomes. Among them, Class Bacteroidia (=-0.005, 95% CI: -0.001 to -0.008, p = 0.002) has a strong causality with lower eGFR after the Bonferroni-corrected test, whereas phylum Actinobacteria (OR = 1.0009, 95%CI: 1.0003-1.0015, p = 0.0024) has a strong causal relationship with dialysis. The Cochrane's Q test reveals that there is no significant heterogeneity between various single nucleotide polymorphisms. In addition, no significant level of pleiotropy was found according to MR-Egger and MR-PRESSO Global tests. CONCLUSIONS: Through the two-sample MR analysis, we identified the specific intestinal flora that has a causal relationship with the incidence and progression of CKD at the level of gene prediction, which may provide helpful biomarkers for early disease diagnosis and potential therapeutic targets for CKD.

Yishen-Qingli-Huoxue formula attenuates renal fibrosis by inhibiting indoxyl sulfate via AhR/snai1 signaling.

BACKGROUND: Chronic kidney disease (CKD) is challenging to reverse and its treatment options are limited. Yishen-Qingli-Huoxue Formula (YQHF) is an effective treatment Chinese formula for CKD, as verified by clinical randomized controlled trial. However, the correlative YQHF therapeutic mechanisms are still unknown. PURPOSE: The current study aimed to investigate the potential anti-renal fibrosis effects of YQHF as well as the underlying mechanism. METHODS: After affirming the curative effects of YQHF on adenine-induced CKD rats, Masson staining, immunohistochemistry, and ELISA were used to assess the effects of YQHF on renal fibrosis. Subsequently, metabolomics and transcriptomics analyses were conducted to clarify the potential mechanisms. Furthermore, high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), molecular docking analysis and in vitro experiments were used to verify final mechanism of anti-fibrosis. RESULTS: Our results demonstrated that YQHF could improve renal morphology, decrease blood urea nitrogen (BUN), serum creatinine (Scr), and increase body weight gain of model rats. Masson staining, immunohistochemistry of collagen I, fibronectin (FN), α-smooth muscle actin (α-SMA), vimentin and E-cadherin showed that YQHF delayed CKD progression by alleviating renal fibrosis, and the expression of fibrotic factors smoc2 and cdh11 were obviously suppressed by YQHF. Metabolomic and transcriptomic measures discovered that indoxyl sulfate might be a crucial factor inducing renal fibrosis, and the antagonistic effect of YQHF on renal fibrosis may be exerted via AhR/snai1 signaling. Subsequently, western blot and immunohistochemical experiments revealed YQHF indeed inhibited AhR/snai1 signaling in adenine-induced renal fibrosis of CKD rat, which confirmed previous results. In addition, molecular docking and in vitro experiments further supported this conclusion, in which astilbin, the main compound identified YQHF, was certified to exert a significant effect on AhR. CONCLUSION: Our findings showed that YQHF can effectively treat CKD by antagonizing renal fibrosis, the potential mechanisms were relating with the regulation on AhR/snai1 signaling.

Genome-wide association study analysis to resolve the key regulatory mechanism of biomineralization in Pinctada fucata martensii.

Biomineralization-controlled exo-/endoskeleton growth contributes to body growth and body size diversity. Molluscan shells undergo ectopic biomineralization to form the exoskeleton and biocalcified "pearl" involved in invading defence. Notably, exo-/endoskeletons have a common ancestral origin, but their regulation and body growth are largely unknown. This study employed the pearl oyster, Pinctada fucata marntensii, a widely used experimental model for biomineralization in invertebrates, to perform whole-genome resequencing of 878 individuals from wild and breeding populations. This study characterized the genetic architecture of biomineralization-controlled growth and ectopic biomineralization. The insulin-like growth factor (IGF) endocrine signal interacted with ancient single-copy transcription factors to form the regulatory network. Moreover, the "cross-phylum" regulation of key long noncoding RNA (lncRNA) in bivalves and mammals indicated the conserved genetic and epigenetic regulation in exo-/endoskeleton growth. Thyroid hormone signal and apoptosis regulation in pearl oysters affected ectopic biomineralization in pearl oyster. These findings provide insights into the mechanism underlying the evolution and regulation of biomineralization in exo-/endoskeleton animals and ectopic biomineralization.

Acupuncture in treating cardiovascular disease complicated with depression: A systematic review and meta-analysis.

Background: Depression is a serious risk for cardiovascular disease (CVD). Improving depression can alleviate cardiac symptoms and improve quality of life. Studies have shown that acupuncture has a positive effect on depression and CVD. This systematic review and meta-analysis will evaluate the efficacy and safety of acupuncture in the treatment of depression complicated with CVD. Methods: We searched PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP, and China Biomedical Literature databases. Randomized controlled trials of acupuncture vs. standard care or sham acupuncture or antidepressants were included. The retrieval time is from database construction to 07 April 2022. We used the "risk of bias" tool of Cochrane Collaboration, and the Review Manager (RevMan.) Version 5.4.1 for statistics analysis. Primary outcomes included Hamilton scale for depression (HAMD), self-rating depression scale (SDS), and the effective rate of depression. Secondary outcomes included frequency of angina pectoris and visual analogue scale (VAS) scores for angina pain. Results: A total of 2,366 studies were screened based on the search strategy. Twelve eligible studies with a total of 1,203 participants have been identified. The result showed that acupuncture reduced the HAMD score [weighted mean difference (WMD): -3.23; 95% confidence interval (CI): -5.38 to -1.09; P = 0.003] and the SDS score (WMD: -1.85; 95% CI: -2.14 to -1.56; P < 0.00001) in patients with depression complicated with CVD. Acupuncture also improved the effective rate of depression (risk ratio: 1.15; 95% CI: 1.03 to 1.29; P = 0.01). The result also showed that acupuncture reduced the attack frequency of angina pectoris (WMD: -4.54; 95% CI: -5.96 to -3.11; P < 0.00001) and the VAS score for angina pain (WMD: -0.72; 95% CI: -1.06 to -0.38; P < 0.0001). This article reviewed the significant advantages of acupuncture for depression and the superiority of acupuncture over no-intervention therapy, antidepressant therapy, and psychotherapy in reducing angina frequency and pain intensity in patients with CVD. Conclusion: This systematic review suggested that acupuncture was a good complementary and alternative therapy for CVD complicated with depression. Considering the limitations of the included research literature, it is still necessary to perform multi-center, large-sample, and double-blind high-quality studies to provide higher-level evidence in the later stage. Systematic review registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42022304957].