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Background: Frailty and stroke are strongly related to the health of older people. This study aimed to map the research hotspots and frontiers, as well as quantitatively and comprehensively characterize the landscapes of publications on frailty in stroke over past decades. Methods: The articles and reviews related to frailty in stroke, published from 2001 to 2023 were retrieved in the Web of Science Core Collection. CiteSpace and VOSviewer were used to identify the research hotspots, research frontiers, and the basic characteristics (such as top countries, institutions, journals and keywords) in this field. Results: The publications’ growth rate on frailty in stroke was increasing over time. Four research hotspot clusters (geriatric syndrome, adverse outcomes prediction, cognitive function and mental health, as well as cardiovascular diseases management) were identified for frailty in stroke research over the past decades. The burst detection analysis showed that recovery, body mass index and oropharyngeal dysphagia were the research trends. Conclusion: These findings will help scholars better understand current research progress and predict future directions related to frailty in stroke. Health providers could pay close attention to the development of scientific research in this field to maintain good health status of older people by geriatric care delivery.

Fractures play a crucial role in tight sandstone gas reservoirs with low permeability and low effective porosity. If open, they not only significantly increase the permeability of the reservoir but also serve as channels connecting the storage space. Among numerous fracture identification methods, seismic data provide unique advantages for fracture identification owing to the provision of three-dimensional information between wells. How to accurately identify the development of fractures in geological bodies between wells using seismic data is a major challenge. In this study, a tight sandstone gas reservoir in the Kuqa Basin (China) was used as an example for identifying reservoir fractures using deep-learning-based method. First, a feasibility analysis is necessary. Intersection analysis between the fracture density and seismic attributes (the characteristics of frequency, amplitude, phase, and other aspects of seismic signals) indicates that there is a correlation between the two when the fracture density exceeds a certain degree. The development of fractures is closely related to the lithology and structure, indirectly affecting differences in seismic attributes. This indicates that the use of seismic attributes for fracture identification is feasible and reasonable. Subsequently, the effective fracture density data obtained from imaging logging were used as label data, and the optimized seismic attribute near the well data were used as feature data to construct a fracture identification sample dataset. Based on a feed-forward neural network algorithm combined with natural fracture density and effectiveness control factor constraints, a trained identification model was obtained. The identification model was applied to seismic multi-attribute data for the entire work area. Finally, the accuracy of the results from the training, testing, and validation datasets were used to determine the effectiveness of the method. The relationship between the fracture identification results and the location of the fractures in the target reservoir was used to determine the reasonableness of the results. The results indicate that there is a certain relationship between multiple seismic attributes and fracture development, which can be established using deep learning models. Furthermore, the deep-learning-based seismic data fracture identification method can effectively identify fractures in the three-dimensional space of reservoirs.

Abstract Background Clear cell renal cell carcinoma (ccRCC) is characterized as one of the most common types of urological cancer with high degrees of malignancy and mortality. Due to the limited effectiveness of existing traditional therapeutic methods and poor prognosis, the treatment and therapy of advanced ccRCC patients remain challenging. Tryptophan metabolism has been widely investigated because it significantly participates in the malignant traits of multiple cancers. The functions and prognostic values of tryptophan metabolism-related genes (TMR) in ccRCC remain virtually obscure. Methods We employed the expression levels of 40 TMR genes to identify the subtypes of ccRCC and explored the clinical characteristics, prognosis, immune features, and immunotherapy response in the subtypes. Then, a model was constructed for the prediction of prognosis based on the differentially expressed genes (DEGs) in the subtypes from the TCGA database and verified using the ICGC database. The prediction performance of this model was confirmed by the receiver operating characteristic (ROC) curves. The relationship of Risk Score with the infiltration of distinct tumor microenvironment cells, the expression profiles of immune checkpoint genes, and the treatment benefits of immunotherapy and chemotherapy drugs were also investigated. Results The two subtypes revealed dramatic differences in terms of clinical characteristics, prognosis, immune features, and immunotherapy response. The constructed 6-gene-based model showed that the high Risk Score was significantly connected to poor overall survival (OS) and advanced tumor stages. Furthermore, increased expression of CYP1B1, KMO, and TDO2 was observed in ccRCC tissues at the translation levels, and an unfavorable prognosis for these patients was also found. Conclusion We identified 2 molecular subtypes of ccRCC based on the expression of TMR genes and constructed a prognosis-related model that may be used as a powerful tool to guide the prediction of ccRCC prognosis and personalized therapy. In addition, CYP1B1, KMO, and TDO2 can be regarded as the risk prognostic genes for ccRCC.

Abstract Background Clear-cell renal cell carcinoma (ccRCC) is one of prevalent kidney malignancies with an unfavorable prognosis. There is a need for a robust model to predict ccRCC patient survival and guide treatment decisions. Methods RNA-seq data and clinical information of ccRCC were obtained from the TCGA and ICGC databases. Expression profiles of genes related to natural killer (NK) cells were collected from the Immunology Database and Analysis Portal database. Key NK cell-related genes were identified using consensus clustering algorithms to classify patients into distinct clusters. A NK cell-related risk model was then developed using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression to predict ccRCC patient prognosis. The relationship between the NK cell-related risk score and overall survival, clinical features, tumor immune characteristics, as well as response to commonly used immunotherapies and chemotherapy, was explored. Finally, the NK cell-related risk score was validated using decision tree and nomogram analyses. Results ccRCC patients were stratified into 3 molecular clusters based on expression of NK cell-related genes. Significant differences were observed among the clusters in terms of prognosis, clinical characteristics, immune infiltration, and therapeutic response. Furthermore, six NK cell-related genes (DPYSL3, SLPI, SLC44A4, ZNF521, LIMCH1, and AHR) were identified to construct a prognostic model for ccRCC prediction. The high-risk group exhibited poor survival outcomes, lower immune cell infiltration, and decreased sensitivity to conventional chemotherapies and immunotherapies. Importantly, the quantitative real-time polymerase chain reaction (qRT-PCR) confirmed significantly high DPYSL3 expression and low SLC44A4 expression in ACHN cells. Finally, the decision tree and nomogram consistently show the dramatic prediction performance of the risk score on the survival outcome of the ccRCC patients. Conclusions The six-gene model based on NK cell-related gene expression was validated and found to accurately mirror immune microenvironment and predict clinical outcomes, contributing to enhanced risk stratification and therapy response for ccRCC patients.

The Bozi-Dabei area in the Kuqa Depression host high-quality reservoirs in the Bashijiqike Formation and Baxigai Formation sandstones of the Lower Cretaceous, in which reservoirs yield significant industrial gas flow despite being situated at a considerable burial depth of 8200 m. The geological history of the target formation involves multiple phases of tectonic movements, resulting in the development of multi-genetic fractures that enhance the reservoir's storage and seepage capacity. Based on the results of the drilling core, field profile survey, imaging logging, and experimental analysis, this study presents an analysis of fractures in the Lower Cretaceous dense sandstone reservoir of the Bozi-Dabei area, andclarifies the characteristics and controlling factors of the multi-genesis and multi-period fractures. Additionally, it proposes an effective fracture development model that accounts for geo-stress control. In the Bozi-Dabei area, the prevailing high extrusion stress environment has led to the development of predominantly regional tectonic fractures and fault-related fractures, with relatively gentle deformation-related fractures. The results of a combination of multi-attribute data determination techniques, including fracture filling, inter-cutting relationship, fracture filling isotope, inclusions, and cathode luminescence tests, this study reveals that the reservoir fractures have experienced three major periods of tectonic movement. The regional tectonic fracture development is mainly controlled by stratigraphic lithology and thickness, while the proximity influences fault co-derived fractures to the fault and the relative positions of the upper and lower plates of the fault. The shift in the direction of the late horizontal maximum principal stress leads to the opening or closing of early fractures under different conditions in the Bozi-Dabei area, consequently affecting the degree of fracture opening and effectiveness. Notably, when the horizontal maximum principal stress is deflected to intersect with early fractures at a smaller angle or even superimpose, the fracture effectiveness of the related group system in the deflection direction improves, resulting in an overall coordination. The distribution characteristics of the fracture system in this highly productive reservoir are the result of dominant configurations from multi-phases of geological activities.

Placental growth factor (PlGF) is a glycosylated dimeric protein that is homologous to vascular endothelial growth factor (VEGF). PlGF expression is upregulated in patients with bronchial asthma, suggesting that it plays a role in the pathogenesis of asthma. Bronchial asthma is characterized by chronic airway inflammation and airway hyperresponsiveness (AHR). After recurrent asthma attacks, pulmonary fibrosis develops and leads to airway remodeling and a further decline in lung function. In this review, we focused on the pivotal role of PlGF in chronic airway inflammation, AHR, and airway remodeling during bronchial asthma. Furthermore, we summarized data showing that PlGF may be a potential therapeutic target in bronchial asthma.

Podocyte injury is an important cause of proteinuria. Angiopoietin-like protein 4 (Angptl4) is a secreted glycoprotein and has a role in proteinuria. However, the exact role of Angptl4 in podocyte injury and its upstream regulators has not been clarified. In this study, we used lipopolysaccharide (LPS)-induced mice and cultured podocytes as podocyte injury models. Our results indicated that LPS increased the expression of podocyte Angptl4 in vivo and in vitro. Furthermore, we showed that Angptl4 overexpression deteriorated LPS-induced podocyte injury by inducing podocyte cytoskeleton rearrangement, reducing the expression of synaptopodin while Angptl4 knockdown alleviated LPS-induced podocyte injury. In addition, we found that inhibitors and siRNA targeting TLR4/MyD88/NF-κB signaling inhibited the upregulation of Angptl4 in LPS-induced podocytes. Moreover, inhibitors and siRNA targeting calcineurin/NFAT signaling also relieved LPS-induced Angptl4 expression and podocyte injury in vivo and in vitro. Taken together, our study has elucidated that both of the TLR4/MyD88/NF-κB and calcineurin/NFAT signaling mediate the upregulation of Angptl4 in LPS-induced podocytes, which has important implications for further understanding the molecular mechanism of LPS-induced podocyte injury.

BackgroundAcute rejection is a determinant of prognosis following kidney transplantation. It is essential to search for novel noninvasive biomarkers for early diagnosis and prompt treatment.MethodsGene microarray data was downloaded from the Gene Expression Omnibus (GEO) expression profile database and the intersected differentially expressed genes (DEGs) was calculated. We conducted the DEGs with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Distribution of immune cell infiltration was calculated by CIBERSORT. A hub gene marker was identified by intersecting the rejection-related genes from WGCNA and a selected KEGG pathway—T cell receptor signaling pathway (hsa04660), and building a protein-protein interaction network using the STRING database and Cytoscape software. We performed flow-cytometry analysis to validate the hub gene.ResultsA total of 1450 integrated DEGs were obtained from five datasets (GSE1563, GSE174020, GSE98320, GSE36059, GSE25902). The GO, KEGG and immune infiltration analysis results showed that AR was mainly associated with T cell activation and various T-cell related pathways. Other immune cells, such as B cells, Macrophage and Dendritic cells were also associated with the progress. After utilizing the WGCNA and PPI network, PDCD1 was identified as the hub gene. The flow-cytometry analysis demonstrated that both in CD4+ and CD8+ T cells, PD1+CD57-, an exhausted T cell phenotype, were downregulated in the acute rejection whole blood samples.ConclusionsOur study illustrated that PDCD1 may be a candidate diagnostic biomarker for acute kidney transplant rejection via integrative bioinformatic analysis.

Background: Leukocyte telomere length shortening is a characteristic of premature senescence, a process that can be accelerated by oxidative stress. In general, patients with end-stage renal disease undergoing regular hemodialysis (HD) are repeatedly exposed to oxidative stress. Patients undergoing HD tend to have cardiovascular diseases associated with oxidative stress and inflammation. Therefore, we assumed that telomere length is associated with HD vintage and the degree of vascular calcification. Methods: A total of 144 patients undergoing regular HD before kidney transplantation and 62 patients on hemodialysis, but not undergoing kidney transplantation, were enrolled. We measured common laboratory values, such as calcium, phosphate, and hemoglobin levels, and assessed the degree of vascular calcification in the patients. The leukocyte telomere length was measured using reverse transcription polymerase chain reaction, and Spearman correlation was used for correlation analysis. Results: The leukocyte telomere length was negatively associated with age (rho = −0.306, P＜0.01); it was shorter in middle-aged patients than in young patients (13.48 ± 4.80 vs. 15.86 ± 4.51, P

BackgroundAcute allograft rejection (AR) following renal transplantation contributes to chronic rejection and allograft dysfunction. The current diagnosis of AR remains dependent on renal allograft biopsy which cannot immediately detect renal allograft injury in the presence of AR. In this study, sensitive biomarkers for AR diagnosis were investigated and developed to protect renal function.MethodsWe analyzed pre- and postoperative data from five databases combined with our own data to identify the key differently expressed genes (DEGs). Furthermore, we performed a bioinformatics analysis to determine the immune characteristics of DEGs. The expression of key DEGs was further confirmed using the real-time quantitative PCR (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), and immunohistochemical (IHC) staining in patients with AR. ROC curves analysis was used to estimate the performance of key DEGs in the early diagnosis of AR.ResultsWe identified glutamic-oxaloacetic transaminase 2 (GOT2) and syntaxin binding protein 3 (STXBP3) as key DEGs. The higher expression of STXBP3 and GOT2 in patients with AR was confirmed using RT-qPCR, ELISA, and IHC staining. ROC curve analysis also showed favorable values of STXBP3 and GOT2 for the diagnosis of early stage AR.ConclusionsSTXBP3 and GOT2 could reflect the immunological status of patients with AR and have strong potential for the diagnosis of early-stage AR.

BackgroundDiabetic kidney disease (DKD) is the primary cause of end-stage renal disease, raising a considerable burden worldwide. Recognizing novel biomarkers by metabolomics can shed light on new biochemical insight to benefit DKD diagnostics and therapeutics. We hypothesized that serum metabolites can serve as biomarkers in the progression of DKD.MethodsA cross-sectional study of 1,043 plasma metabolites by untargeted LC/MS among 89 participants identified associations between proteinuria severity and metabolites difference. Pathway analysis from differently expressed metabolites was used to determine perturbed metabolism pathways. The results were replicated in an independent, cross-sectional cohort of 83 individuals. Correlation and prediction values were used to examine the association between plasma metabolites level and proteinuria amount.ResultsDiabetes, and diabetic kidney disease with different ranges of proteinuria have shown different metabolites patterns. Cysteine and methionine metabolism pathway, and Taurine and hypotaurine metabolism pathway were distinguishable in the existence of DKD in DC (diabetes controls without kidney disease), and DKD with different ranges of proteinuria. Two interesting tetrapeptides (Asn-Met-Cys-Ser and Asn-Cys-Pro-Pro) circulating levels were elevated with the DKD proteinuria progression.ConclusionsThese findings underscore that serum metabolomics provide us biochemical perspectives to identify some clinically relevant physiopathologic biomarkers of DKD progression.

A kidney transplant is often the best treatment for end-stage renal disease. Although immunosuppressive therapy sharply reduces the occurrence of acute allograft rejection (AR), it remains the main cause of allograft dysfunction. We aimed to identify effective biomarkers for AR instead of invasive kidney transplant biopsy. We integrated the results of several proteomics studies related to AR and utilized public data sources. Gene ontology (GO) and pathway analyses were used to identify important biological processes and pathways. The performance of the identified proteins was validated using several public gene expression omnibus (GEO) datasets. Samples that performed well were selected for further validation through RNA sequencing of peripheral blood mononuclear cells of patients with AR (n = 16) and non-rejection (n = 19) from our medical center. A total of 25 differentially expressed proteins (DEPs) overlapped in proteomic studies of urine and blood samples. GO analysis showed that the DEPs were mainly involved in the immune system and blood coagulation. Pathway analysis showed that the complement and coagulation cascade pathways were well enriched. We found that immunoglobulin heavy constant alpha 1 (IGHA1) and immunoglobulin κ constant (IGKC) showed good performance in distinguishing AR from non-rejection groups validated with several GEO datasets. Through RNA sequencing, the combination of IGHA1, IGKC, glomerular filtration rate, and donor age showed good performance in the diagnosis of AR with ROC AUC 91.4% (95% CI: 82–100%). Our findings may contribute to the discovery of potential biomarkers for AR monitoring.

BackgroundAcute rejection (AR) in kidney transplantation is an established risk factor that reduces the survival rate of allografts. Despite standard immunosuppression, molecules with regulatory control in the immune pathway of AR can be used as important targets for therapeutic operations to prevent rejection.MethodsWe downloaded the microarray data of 15 AR patients and 37 non-acute rejection (NAR) patients from Gene Expression Omnibus (GEO). Gene network was constructed, and genes were classified into different modules using weighted gene co-expression network analysis (WGCNA). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cytoscape were applied for the hub genes in the most related module to AR. Different cell types were explored by xCell online database and single-cell RNA sequencing. We also validated the SLAMF8 and TLR4 levels in Raw264.7 and human kidney tissues of TCMR.ResultsA total of 1,561 differentially expressed genes were filtered. WGCNA was constructed, and genes were classified into 12 modules. Among them, the green module was most closely associated with AR. These genes were significantly enriched in 20 pathway terms, such as cytokine–cytokine receptor interaction, chemokine signaling pathway, and other important regulatory processes. Intersection with GS > 0.4, MM > 0.9, the top 10 MCC values and DEGs in the green module, and six hub genes (DOCK2, NCKAP1L, IL2RG, SLAMF8, CD180, and PTPRE) were identified. Their expression levels were all confirmed to be significantly elevated in AR patients in GEO, Nephroseq, and quantitative real-time PCR (qRT-PCR). Single-cell RNA sequencing showed that AR patient had a higher percentage of native T, CD1C+_B DC, NKT, NK, and monocytes in peripheral blood mononuclear cells (PBMCs). Xcell enrichment scores of 20 cell types were significantly different (p

Sepsis, a complex multisystem disorder, is among the top causes of hospitalization and mortality in older adults. However, the mechanisms underlying the disproportionate susceptibility to sepsis and worse outcomes in the elderly are not well understood. Recently, changes in DNA methylation have been shown to be linked to aging processes and age-related diseases. Thus, we postulated that age-related changes in DNA methylation may play a role in the onset and prognosis of sepsis in elderly patients. Here, we performed genome-wide methylation profiling of peripheral blood from patients with sepsis and controls. Among the CpG sites whose methylation changes may contribute to an increase in sepsis susceptibility or mortality, 241 sites that possessed age-related changes in DNA methylation in controls may partly explain the increased risk of sepsis in older adults, and 161 sites whose methylation significantly correlated with age in sepsis group may be the potential mechanisms underlying the worse outcomes of elderly septic patients. Finally, an independent cohort was used to validate our findings. Together, our study demonstrates that age-related changes in DNA methylation may explain in part the disproportionate susceptibility and worse outcomes of sepsis in older adults.

Acute rejection (AR) is closely associated with renal allograft dysfunction. Here, we utilised RNA sequencing (RNA-Seq) and bioinformatic methods to characterise the peripheral blood mononuclear cells (PBMCs) of patients with acute renal allograft rejection. Pretransplant blood samples were collected from 32 kidney allograft donors and 42 corresponding recipients with biopsies classified as T cell-mediated rejection (TCMR, n = 18), antibody-mediated rejection (ABMR, n = 5), and normal/non-specific changes (non-AR, n = 19). The patients with TCMR and ABMR were assigned to the AR group, and the patients with normal/non-specific changes (n = 19) were assigned to the non-AR group. We analysed RNA-Seq data for identifying differentially expressed genes (DEGs), and then gene ontology (GO) analysis, Reactome, and ingenuity pathway analysis (IPA), protein—protein interaction (PPI) network, and cell-type enrichment analysis were utilised for bioinformatics analysis. We identified DEGs in the PBMCs of the non-AR group when compared with the AR, ABMR, and TCMR groups. Pathway and GO analysis showed significant inflammatory responses, complement activation, interleukin-10 (IL-10) signalling pathways, classical antibody-mediated complement activation pathways, etc., which were significantly enriched in the DEGs. PPI analysis showed that IL-10, VEGFA, CXCL8, MMP9, and several histone-related genes were the hub genes with the highest degree scores. Moreover, IPA analysis showed that several proinflammatory pathways were upregulated, whereas antiinflammatory pathways were downregulated. The combination of NFSF14+TANK+ANKRD 33 B +HSPA1B was able to discriminate between AR and non-AR with an AUC of 92.3% (95% CI 82.8–100). Characterisation of PBMCs by RNA-Seq and bioinformatics analysis demonstrated gene signatures and biological pathways associated with AR. Our study may provide the foundation for the discovery of biomarkers and an in-depth understanding of acute renal allograft rejection.

Introduction:Acute kidney injury (AKI) after cardiac surgery is independently associated with a prolonged hospital stay, increased cost of care, and increased post-operative mortality. Delayed elevation of serum creatinine (SCr) levels requires novel biomarkers to provide a prediction of AKI after cardiac surgery. Our objective was to find a novel blood biomarkers combination to construct a model for predicting AKI after cardiac surgery and risk stratification.Methods:This was a case-control study. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to Gene Expression Omnibus (GEO) dataset GSE30718 to seek potential biomarkers associated with AKI. We measured biomarker levels in venous blood samples of 67 patients with AKI after cardiac surgery and 59 control patients in two cohorts. Clinical data were collected. We developed a multi-biomarker model for predicting cardiac-surgery-associated AKI and compared it with a traditional clinical-factor-based model.Results:From bioinformatics analysis and previous articles, we found 6 potential plasma biomarkers for the prediction of AKI. Among them, 3 biomarkers, such as growth differentiation factor 15 (GDF15), soluble suppression of tumorigenicity 2 (ST2, IL1RL1), and soluble urokinase plasminogen activator receptor (uPAR) were found to have prediction ability for AKI (area under the curve [AUC] > 0.6) in patients undergoing cardiac surgery. They were then incorporated into a multi-biomarker model for predicting AKI (C-statistic: 0.84, Brier 0.15) which outperformed the traditional clinical-factor-based model (C-statistic: 0.73, Brier 0.16).Conclusion:Our research validated a promising plasma multi-biomarker model for predicting AKI after cardiac surgery.

Lupus nephritis (LN) is a common and severe organ manifestation of systemic lupus erythematosus (SLE) and is a major cause of SLE related deaths. Early diagnosis is essential to improve the prognosis of patients with LN. To screen the potential biomarkers associated with LN, we downloaded the gene expression profile of GSE99967 from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was utilized to construct a gene co-expression network and identify gene modules associated with LN. Gene Ontology (GO) analysis was also applied to explore the biological function of genes and identify the key module. Differentially expressed genes (DEGs) were identified and Maximal Clique Centrality (MCC) values were calculated to screen hub genes. Furthermore, we selected promising biomarkers for real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) validation in independent cohorts. Our results indicated that five hub genes, including IFI44, IFIT3, HERC5, RSAD2, and DDX60 play vital roles in the pathogenesis of LN. Importantly, IFI44 may considered as a key biomarker in LN for its diagnostic capabilities, which is also a promising therapeutic target in the future.

Background: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease in China. Tubular injury contributes to the progression of DKD. Our study was conducted to explore the differential gene expression profiles between kidneys from patients with DKD and kidney living donors (LDs).Methods: In total, seven DKD and eighteen LD gene expression profiles from the GSE104954 dataset were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were analyzed in R with the limma package. DEGs were uploaded to the g:Profiler online database to explore the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Ingenuity pathway analysis (IPA) was carried out using online IPA software. Weighted gene co-expression network analysis (WGCNA) was performed using the WGCNA R package. By integrating DEGs and genes from the top 1 phenotype-gene associated module, we determined the hub gene. We next tested the hub gene, VCAN, in the GSE30122 dataset. We also validated the versican levels in human kidney tissues, explored immune cell type enrichment using an online database xCell, and investigated the correlation between cell types and VCAN expression.Results: A total of 563 DEGs was identified. A large number of pathways were involved in the immune response process according to the results of GO, KEGG, and IPA. Using WGCNA, we selected the lightcyan module in which genes showed the strongest correlation with the phenotype and smallest P-value. We also identified VCAN as a hub gene by integrating DEG analysis and WGCNA. Versican expression was upregulated in human diabetic kidney tissue. Moreover, versican was speculated to play a role in immune injury according to the enrichment of functions and signaling pathways. VCAN transcript levels correlate with the assembly of immune cells in the kidney.Conclusion: Immune processes played an essential role in DKD tubulointerstitium injury. The hub gene VCAN contributed to this process.

Background and aims: Currently, there are no definitive therapies for coronavirus disease 2019 (COVID-19). Gut microbial dysbiosis has been proved to be associated with COVID-19 severity and probiotics is an adjunctive therapy for COIVD-19. However, the potential benefit of probiotics in COVID-19 has not been studied. We aimed to assess the relationship of probiotics use with clinical outcomes in patients with COVID-19. Methods: We conducted a propensity-score matched retrospective cohort study of adult patients with COVID-19. Eligible patients received either probiotics plus standard care (probiotics group) or standard care alone (non-probiotics group). The primary outcome was the clinical improvement rate, which was compared among propensity-score matched groups and in the unmatched cohort. Secondary outcomes included the duration of viral shedding, fever, and hospital stay. Results: Among the propensity-score matched groups, probiotics use was related to clinical improvement rates (log-rank p = 0.028). This relationship was driven primarily by a shorter (days) time to clinical improvement [difference, −3 (−4 to −1), p = 0.022], reduction in duration of fever [−1.0 (−2.0 to 0.0), p = 0.025], viral shedding [−3 (−6 to −1), p

Sepsis is a heterogeneous syndrome induced by infection and results in high mortality. Even though more than 100 biomarkers for sepsis prognosis were evaluated, prediction of patient outcomes in sepsis continues to be driven by clinical signs because of unsatisfactory specificity and sensitivity of these biomarkers. This study aimed to elucidate the key candidate genes involved in sepsis response and explore their downstream effects based on weighted gene co-expression network analysis (WGCNA). The dataset GSE63042 with sepsis outcome information was obtained from the Gene Expression Omnibus (GEO) database and then consensus WGCNA was conducted. We identified the hub gene SDF4 (stromal cell derived factor 4) from the M6 module, which was significantly associated with mortality. Subsequently, two datasets (GSE54514 and E-MTAB-4421) and cohort validation (n=89) were performed. Logistic regression analysis was used to build a prediction model and the combined score resulting in a satisfactory prognosis value (area under the ROC curve=0.908). The model was subsequently tested by another sepsis cohort (n=70, ROC= 0.925). We next demonstrated that endoplasmic reticulum (ER) stress tended to be more severe in patients PBMCs with negative outcomes compared to those with positive outcomes and SDF4 was related to this phenomenon. In addition, our results indicated that adenovirus-mediated Sdf4 overexpression attenuated ER stress in cecal ligation and puncture (CLP) mice lung. In summary, our study indicates that incorporation of SDF4 can improve clinical parameters predictive value for the prognosis of sepsis, and decreased expression levels of SDF4 contributes to excessive ER stress, which is associated with worsened outcomes, whereas overexpression of SDF4 attenuated such activation.

MYH9-related disease or disorder (MYH9-RD) is an autosomal dominant disease caused by mutations in the MYH9 gene. Mutations in this gene initially affect the hemic system, and other manifestations may evolve with age. Here, we report the case of a 46-year-old Chinese woman with MYH9-RD who was primarily misdiagnosed with idiopathic thrombocytopenia purpura. Exome sequencing of the patient, and the mother and son of the patient revealed a deletion mutation c.5797delC (p. R1933Efs*15) in exon 41 (encoding non-helical tailpiece, NHT) of the MYH9 gene, which consequently led to a frameshift mutation. To the best of our knowledge, this mutation has been reported in Italy once, while the substitution mutation c.5797 C>T is the most frequent mutation. Mutations that affect the NHT region cause thrombocytopenia throughout life; however, our patient presented with a more severe phenotype than previously reported, including thrombocytopenia, inclusion bodies in neutrophils, sensorineural hearing loss, nephropathy, and abnormal liver enzymes. Our goal in the current case is to prevent further progression of renal involvement and to identify other affected members in this family to provide early intervention. This case may raise awareness of MYH9-RD when diagnosing thrombocytopenia and improve our understanding of this condition.

Background: Although numerous studies have suggested that the gradually increasing selective preference for positive information over negative information in older adults depends on cognitive control processes, few have reported the characteristics of different attention stages in the emotional processing of older individuals. The present study used a real-time eye-tracking technique to disentangle the attentional engagement and disengagement processes involved in age-related positivity effect (PE).Methods: Eye movement data from a spatial-cueing task were obtained for 32 older and 32 younger healthy participants. The spatial-cueing task with varied cognitive loads appeared to be an effective way to explore the role of cognitive control during the attention engagement and disengagement stages of emotion processing.Results: Compared with younger adults, older participants showed more positive gaze preferences when cognitive resources were sufficient for face processing at the attention engagement stage. However, the age-related PE was not observed at the attention disengagement stage because older adults had more difficulty disengaging from fearful faces than did the younger adults due to the consumption of attention by the explicit target judgment.Conclusion: The present study highlights how cognitive control moderates positive gaze preferences at different attention processing stages. These findings may have far-reaching implications for understanding, preventing, and intervening in unsuccessful aging and, thus, in promoting active and healthy aging.

BackgroundIncreasing evidence shows that Angptl4 affects proteinuria in podocytes injured kidney disease, however, whether there is a relationship between Angptl4 and IgA nephropathy (IgAN) has not been studied yet.MethodsPlasma and urine samples were obtained from 71 patients with IgAN and 61 healthy controls. Glomeruli from six renal biopsy specimens (three IgAN patients and three healthy controls) were separated by RNA-Seq. Differentially expressed genes (DEGs) related to podocytes and Angptl4 between IgAN patients and healthy controls were performed using the Limma package. Gene set enrichment analysis was used to determine whether there was a statistically significant difference between the two groups. STRING was used to create a protein-protein interaction network of DEGs. Association analysis between Angptl4 levels and clinical features of IgAN was performed.ResultsThirty-three podocyte-related and twenty-three Angpt4-related DEGs were found between IgAN patients and healthy controls. By overlapping the genes, FOS and G6PC were found to be upregulated in IgAN patients, while MMP9 was downregulated in IgAN patients. Plasma and urine Angptl4 levels were closely related to the degree of podocyte injury and urine protein, but not to the protein-creatine ratio.ConclusionOur findings show that Angptl4 levels in plasma and urine are related to podocyte damage and, therefore, may be a promising tool for assessing the severity of IgAN patients to identify and reverse the progression to ESRD.

Organ dysfunction caused by sepsis is life-threatening and results in high mortality. Therapeutic options for sepsis are limited. Pathogenic factors are considered as components of environmental pressure that modify DNA methylation patterns thereby enhancing disease progression. Here, we found that sepsis patients exhibited higher levels of genomic DNA methylation patterns and hypermethylated genes associated with the NF-kB signaling pathway. Therefore, we hypothesized that a DNA methyl transferase inhibitor, Decitabine, may mitigate inflammation and improve survival by inhibiting the NF-κB signaling pathway. To test the hypothesis, mice challenged with caecal ligation and puncture (CLP) were subcutaneously injected with Decitabine solution (0.5, 1, and 1.5 mg/kg) 2 h following operation. Our results indicated that Decitabine reduces DNA methyltransferases (DNMTs), attenuates NF-κB activation, downregulates inflammatory cytokine levels, and inhibits the progression of sepsis. Thus, DNA methylation may be indispensable for sepsis and serve as a predicting factor. The use of Decitabine could represent a novel strategy in the treatment of sepsis.

Background/Aims: In view of the latest findings that matrix metalloproteinase-7 (MMP-7) acted as a vital marker and pathogenic mediator of renal fibrosis in a murine model, we hypothesized that serum MMP-7 level might serve as a noninvasive prognostic biomarker in IgA nephropathy (IgAN) patients. Methods: We conducted a retrospective follow-up study of 244 IgAN patients for a median of 81.9 months. Serum MMP-7 was detected at the time of diagnosis, and renal progression was assessed by Cox proportional hazards method. Results: Compared with healthy populations, the serum levels of MMP-7 were significantly elevated in IgAN patients. Besides, serum MMP-7 levels were well correlated with renal scarring lesions characterized by glomerular sclerosis and interstitial fibrosis. Follow-up analyses revealed that increased serum MMP-7 levels were linked with a greater risk of poor renal outcome with a hazard ratio of 1.898 per doubling MMP-7 concentration. By contrast with the first quartile, the risk of deterioration in renal function elevated such that the hazard ratio for the second quartile was 1.805, 3.383 for the third, and 5.173 for the fourth quartile of the MMP-7 level. Conclusions: This study showed that the higher serum MMP-7 levels were independently associated with renal fibrosis and poor prognosis in IgAN.

The complete mitogenome sequence of the ruby dragonet Synchiropus sycorax was first determined using next-generation sequencing strategy in this study. The circle genome was 16,656 bp in length and consisted of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes, and 1 control region. The mitochondrial gene arrangement of S. sycorax is similar to those of most other fish species. Results from neighbor-joining phylogenetic analysis showed that S. sycorax clustered with S. splendidus and other species of the family Callionymidae. This study will be valuable for phylogenetic analysis of the genus Synchiropus and the other genera of the order Syngnathiformes.

Jasmonates (JAs) regulate plant growth and defense responses. On perception of bioactive JAs, the JA receptor CORONATINE INSENSITIVE1 (COI1) recruits JA ZIM-domain (JAZ) proteins for degradation, and JAZ-targeted transcription factors are released to regulate JA responses. The subgroup IIId bHLH transcriptional factors, including bHLH17, bHLH13, bHLH3, and bHLH14, interact with JAZs and repress JA responses. In this study, we show that IIId bHLH factors form dimers via the C-terminus in yeast. N-terminus of bHLH13 is essential for its transcriptional repression function. bHLH13 overexpression inhibits Arabidopsis resistance to the necrotrophic fungi Botrytis cinerea and defense against the insect Spodoptera exigua . COI1 mutation disrupts the oversensitivity of the quadruple mutant bhlh3 bhlh13 bhlh14 bhlh17 in various JA responses, including anthocyanin accumulation, root growth inhibition, and defense against B cinerea and S exigua . Disruption of the TTG1/bHLH/MYB complex blocks anthocyanin accumulation of bhlh3 bhlh13 bhlh14 bhlh17 , whereas abolishment of MYC2 attenuates JA-inhibitory root growth of bhlh3 bhlh13 bhlh14 bhlh17 . These results genetically demonstrate that IIId bHLH factors function downstream of COI1 to inhibit distinctive JA responses via antagonizing different transcriptional activators.

The complete mitochondrial genome sequence of Stonogobiops yasha was first determined in this study. The circle genome was 16,566 bp long and consisted of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes, and 1 control region. The mitochondrial gene arrangement of S. yasha is similar to those of most other gobies. The phylogenetic analysis using the neighbor-joining method showed that the kinship between Stonogobiops and Acentrogobius is closer than those between Stonogobiops and other selected genera. This is the first record of the complete mitogenome for the genus Stonogobiops.

OBJECTIVES: Prior evidence suggests geographic disparities in the effect of maternal education on child nutritional status between countries, between regions and between urban and rural areas. We postulated its effect would also vary by micro-geographic locations (indicated by mountain areas, plain areas and the edge areas) in a Chinese minority area. METHODS: A cross-sectional study was conducted with a multistage random sample of 1474 school children aged 5-12 years in Guyuan, China. Child nutritional status was measured by height-for-age z scores (HAZ). Linear mixed models were used to examine its association with place of residence and maternal education. RESULTS: Micro-geographic disparities in child nutritional status and the level of socioeconomic composition were found. Children living in mountain areas had poorer nutritional status, even after adjusting for demographic (plain versus mountain, β = 0.16, P = 0.033; edge versus mountain, β = 0.29, P = 0.002) and socioeconomic factors (plain versus mountain, β = 0.12, P = 0.137; edge versus mountain, β = 0.25, P = 0.009). The disparities significantly widened with increasing years of mothers' schooling (maternal education*plain versus mountain: β = 0.06, P = 0.007; maternal education*edge versus mountain: β = 0.07, P = 0.005). Moreover, the association between maternal education and child nutrition was negative (β = -0.03, P = 0.056) in mountain areas but positive in plain areas (β = 0.02, P = 0.094) or in the edge areas (β = 0.04, P = 0.055). CONCLUSIONS: Micro-geographic disparities in child nutritional status increase with increasing level of maternal education and the effect of maternal education varies by micro-geographic locations, which exacerbates child health inequity. Educating rural girls alone is not sufficient; improving unfavorable conditions in mountain areas might make such investments more effective in promoting child health. Nutrition programs targeting to the least educated groups in plain and in edge areas would be critical to their cost-effectiveness.

Aim: We investigated the effect of lifespan cognitive reserve and its components on cognitive frailty among older adults. Methods: A total of 4922 participants aged =65 years were recruited in 2008 and were followed up in 2011 from the Chinese Longitudinal Healthy Longevity Survey. Cognitive frailty was determined through the simultaneous presence of physical frailty (pre-frailty or frailty) and mild cognitive impairment, excluding concurrent dementia. The assessment of physical frailty and mild cognitive impairment was based on the Fatigue, Resistence, Ambulation, Illness, Loss of weight (FRAIL) (Fatigue, Resistence, Ambulation, Illness, Loss) and Mini-Mental State Examination scale, respectively. The lifespan cognitive reserve consisted of education attainment, occupational complexity and later-life leisure activities. We used logistic regression models to estimate the risk of cognitive frailty associated with the lifespan cognitive reserve and its components. Results: A higher level of lifespan cognitive reserve, higher educational attainment or leisure activities engagement, but not occupational complexity, were associated with lower risk of incident cognitive frailty. Furthermore, cognitive, social and physical activities were associated with lower risk of incident cognitive frailty. Conclusion: Cognitive reserve, particularly educational attainment and leisure activities, can protect from cognitive frailty. This implicates that individuals should accumulate cognitive reserve in their lifespan, and older adults should actively participate in leisure activities to prevent cognitive frailty. [ABSTRACT FROM AUTHOR]