Expression and significance of SIRT6 in human peritoneal dialysis effluents and peritoneal mesothelial cells.

Sirtuin 6 (SIRT6) can inhibit the fibrosis of many organs. However, the relationship between SIRT6 and peritoneal fibrosis (PF) in peritoneal dialysis (PD) remains unclear. We collected 110 PD patients with a duration of PD for more than 3 months and studied the influence of PD duration and history of peritonitis on SIRT6 levels in PD effluents (PDEs). We also analyzed the relationship between SIRT6 levels in PDEs and transforming growth factor beta 1 (TGF-ß1), IL-6, PD duration, peritoneal function, PD ultrafiltration (UF), and glucose exposure. We extracted human peritoneal mesothelial cells (HPMCs) from PDEs and measured the protein and gene expression levels of SIRT6, E-cadherin, vimentin, and TGF-ß1 in these cells. Based on the clinical results, we used human peritoneal mesothelial cells lines (HMrSV5) to observe the changes in SIRT6 levels and mesothelial-to-mesenchymal transition (MMT) after intervention with PD fluid. By overexpressing and knocking down SIRT6 expression, we investigated the effect of SIRT6 expression on E-cadherin, vimentin, and TGF-ß1 expression to elucidate the role of SIRT6 in mesothelial-to-epithelial transition in PMCs. Results: (1) With the extension of PD duration, the influence of infection on SIRT6 levels in PDEs increased. Patients with the PD duration of more than 5 years and a history of peritonitis had the lowest SIRT6 levels. (2) SIRT6 levels in PDEs were negatively correlated with PD duration, total glucose exposure, TGF-ß1, IL-6 levels, and the dialysate-to-plasma ratio of creatinine (Cr4hD/P), but positively correlated with UF. This indicates that SIRT6 has a protective effect on the peritoneum. (3) The short-term group (PD ≤ 1 year) had higher SIRT6 and E-cadherin gene and protein levels than the mid-term group (1 year < PD ≤ 5 years) and long-term group (PD > 5 years) in PMCs, while vimentin and TGF-ß1 levels were lower in the mid-term group and long-term group. Patients with a history of peritonitis had lower SIRT6 and E-cadherin levels than those without such a history. (4) After 4.25% PD fluid intervention for HPMCs, longer intervention time resulted in lower SIRT6 levels. (5) Overexpressing SIRT6 can lead to increased E-cadherin expression and decreased vimentin and TGF-ß1 expression in HPMCs. Knocking down SIRT6 expression resulted in decreased E-cadherin expression and increased vimentin and TGF-ß1 expression in HPMCs. This indicates that SIRT6 expression can inhibit MMT in HPMCs, alleviate PF associated with PD, and have a protective effect on the peritoneum.

Integrative analysis of single-cell and bulk RNA-sequencing data revealed T cell marker genes based molecular sub-types and a prognostic signature in lung adenocarcinoma.

Immunotherapy has emerged as a promising modality for addressing advanced or conventionally drug-resistant malignancies. When it comes to lung adenocarcinoma (LUAD), T cells have demonstrated significant influence on both antitumor activity and the tumor microenvironment. However, their specific contributions remain largely unexplored. This investigation aimed to delineate molecular subtypes and prognostic indicators founded on T cell marker genes, thereby shedding light on the significance of T cells in LUAD prognosis and precision treatment. The cellular phenotypes were identified by scrutinizing the single-cell data obtained from the GEO repository. Subsequently, T cell marker genes derived from single-cell sequencing analyses were integrated with differentially expressed genes from the TCGA repository to pinpoint T cell-associated genes. Utilizing Cox analysis, molecular subtypes and prognostic signatures were established and subsequently verified using the GEO dataset. The ensuing molecular and immunological distinctions, along with therapy sensitivity between the two sub-cohorts, were examined via the ESTIMATE, CIBERSORT, and ssGSEA methodologies. Compartmentalization, somatic mutation, nomogram development, chemotherapy sensitivity prediction, and potential drug prediction analyses were also conducted according to the risk signature. Additionally, real-time qPCR and the HPA database corroborated the mRNA and protein expression patterns of signature genes in LUAD tissues. In summary, this research yielded an innovative T cell marker gene-based signature with remarkable potential to prognosis and anticipate immunotherapeutic outcomes in LUAD patients.

Energy metabolic reprogramming regulates programmed cell death of renal tubular epithelial cells and might serve as a new therapeutic target for acute kidney injury.

Acute kidney injury (AKI) induces significant energy metabolic reprogramming in renal tubular epithelial cells (TECs), thereby altering lipid, glucose, and amino acid metabolism. The changes in lipid metabolism encompass not only the downregulation of fatty acid oxidation (FAO) but also changes in cell membrane lipids and triglycerides metabolism. Regarding glucose metabolism, AKI leads to increased glycolysis, activation of the pentose phosphate pathway (PPP), inhibition of gluconeogenesis, and upregulation of the polyol pathway. Research indicates that inhibiting glycolysis, promoting the PPP, and blocking the polyol pathway exhibit a protective effect on AKI-affected kidneys. Additionally, changes in amino acid metabolism, including branched-chain amino acids, glutamine, arginine, and tryptophan, play an important role in AKI progression. These metabolic changes are closely related to the programmed cell death of renal TECs, involving autophagy, apoptosis, necroptosis, pyroptosis, and ferroptosis. Notably, abnormal intracellular lipid accumulation can impede autophagic clearance, further exacerbating lipid accumulation and compromising autophagic function, forming a vicious cycle. Recent studies have demonstrated the potential of ameliorating AKI-induced kidney damage through calorie and dietary restriction. Consequently, modifying the energy metabolism of renal TECs and dietary patterns may be an effective strategy for AKI treatment.

Safety assessment, whole genome sequence, and metabolome analysis of Streptococcus thermophilus CICC 20372 for bone cement fermentation.

Bone is a kind of meat processing by-product with high nutritional value but low in calorie, which is a typical food in China and parts of East Asian countries. Microbial fermentation by lactic acid bacteria showed remarkable advantages to increase the absorption of nutrients from bone cement by human body. Streptococcus thermophilus CICC 20372 is proven to be a good starter for bone cement fermentation. No genes encoding virulence traits or virulence factors were found in the genome of S. thermophilus CICC 20372 by a thorough genomic analysis. Its notable absence of antibiotic resistance further solidifies the safety. Furthermore, the genomic analysis identified four types of gene clusters responsible for the synthesis of antimicrobial metabolites. A comparative metabolomic analysis was performed by cultivating the strain in bone cement at 37 °C for 72 h, with the culture in de Man, Rogosa, and Sharpe (MRS) medium as control. Metabolome analysis results highlighted the upregulation of pathways involved in 2-oxocarboxylic acid metabolism, ATP-binding cassette (ABC) transporters, amino acid synthesis, and nucleotide metabolism during bone cement fermentation. S. thermophilus CICC 20372 produces several metabolites with health-promoting function during bone cement fermentation, including indole-3-lactic acid, which is demonstrated ameliorative effects on intestinal inflammation, tumor growth, and gut dysbiosis. In addition, lots of nucleotide and organic acids were accumulated at higher levels, which enriched the fermented bone cement with a variety of nutrients. Collectively, these features endow S. thermophilus CICC 20372 a great potential strain for bone food processing.

Identification of Cell-Cell Communications by Single-Cell RNA Sequencing in End Stage Renal Disease Provides New Insights into Immune Cell Heterogeneity.

Objective: Impaired immune system characterized by low-grade inflammation is closely associated with kidney chronic kidney disease (CKD) progression. To reveal the alterations of the function, component, and intercellular communication of immune cells during the progression of CKD. Patients and Methods: We conducted a case-control study enrolling regular hemodialysis patients and healthy controls. Clinical data, serum and peripheral blood mononuclear cell (PBMC) samples were collected. Flow cytometry and single-cell RNA sequencing were performed to quantitatively analyze the immune cell subsets and T-cell subsets of PBMCs. scRNA data of GSE140023 containing mouse unilateral ureteral obstruction (UUO) models were analyzed the heterogeneity of immune cells. Results: Overall reduction in peripheral blood lymphocyte subsets in patients with end-stage renal disease (ESRD) was observed. A higher ratio of Th17/Treg, Th1/Treg, and b-cell/Treg in the ESRD group was associated with a decrease in eGFR, PTH, and ferritin. Among T cell subsets identified by scRNA analysis, Th17 cells were significantly increased in the ESRD and UU0 group. TFH, Th1, and Th2 cells are located at the final stage in the developmental tree, while Treg and memory CD8+ T cells are at the beginning site. Early developmental differentiation of Th17, Th1, and Tfh cells was observed in the ESRD and UUO group. Analysis of intercellular communication between t-cell subpopulations identified two major input and output signaling pathways: the CD40 and macrophage inhibitory factor (MIF) pathways. The MIF signaling pathway primarily mediates intercellular communication among th17 effects, CD8+ t-cell, and Th17-Treg in the ESRD group, the serum level of MIF showed significant upregulation, which was closely related to Th17/Treg cells. Conclusions: A global immune imbalance was closely associated with the deterioration in renal function and complication development. The MIF signaling pathway mediates Th17/Treg communication and promotes the trans-differentiation of Treg cells to Th17 cells in CKD progression.

Antimycobacterial Activities of Hydroxamic Acids and Their Iron(II/III), Nickel(II), Copper(II) and Zinc(II) Complexes.

Hydroxamic acid (HA) derivatives display antibacterial and antifungal activities. HA with various numbers of carbon atoms (C2, C6, C8, C10, C12 and C17), complexed with different metal ions, including Fe(II/III), Ni(II), Cu(II) and Zn(II), were evaluated for their antimycobacterial activities and their anti-biofilm activities. Some derivatives showed antimycobacterial activities, especially in biofilm growth conditions. For example, 20-100 µM of HA10Fe2, HA10FeCl, HA10Fe3, HA10Ni2 or HA10Cu2 inhibited Mycobacterium tuberculosis, Mycobacterium bovis BCG and Mycobacterium marinum biofilm development. HA10Fe2, HA12Fe2 and HA12FeCl could even attack pre-formed Pseudomonas aeruginosa biofilms at higher concentrations (around 300 µM). The phthiocerol dimycocerosate (PDIM)-deficient Mycobacterium tuberculosis H37Ra was more sensitive to the ion complexes of HA compared to other mycobacterial strains. Furthermore, HA10FeCl could increase the susceptibility of Mycobacterium bovis BCG to vancomycin. Proteomic profiles showed that the potential targets of HA10FeCl were mainly related to mycobacterial stress adaptation, involving cell wall lipid biosynthesis, drug resistance and tolerance and siderophore metabolism. This study provides new insights regarding the antimycobacterial activities of HA and their complexes, especially about their potential anti-biofilm activities.

Acteoside protects podocyte against apoptosis through regulating AKT/GSK-3ß signaling pathway in db/db mice.

BACKGROUND: Podocyte apoptosis is one of the important pathological mechanisms of diabetic kidney disease (DKD). Acteoside (Act), a major active component of Rehmannia glutinosa leaves total glycoside, has a strong renoprotective action. Our study aims to demonstrate Act's renoprotective actions in db/db mice. METHODS: We adopted C57BLKS/J db/db mice as DKD animal models. After 8 weeks of Act administration, the 24-hour urine albumin, renal function index, and blood lipid levels were quantified using matching kits. Renal pathology was evaluated by HE and PAS staining. The podocyte damage and apoptosis-related signaling pathway were observed by using immunohistochemistry, western blot, and TUNEL staining. RESULTS: The albuminuria of db/db mice was reduced from 391 ug/24 h to 152 ug/24 h, and renal pathology changes were alleviated after Act administration. The western blot and immunohistochemistry showed that Act treatment upregulated the synaptopodin and podocin expression compared with db/db mice, while the TUNEL staining indicated podocyte apoptosis was inhibited. The B-cell lymphoma-2 (Bcl-2) level was upregulated in the Act group, but cleaved caspase-3 and Bcl-2 associated X protein (Bax) expression declined, while the protein kinase B/glycogen synthase kinase-3ß (AKT/GSK-3ß) signaling pathway was repressed. CONCLUSIONS: By inhibiting the AKT/GSK-3ß signaling pathway, Act protected podocytes from apoptosis, decreasing the urine albumin of db/db mice and delaying the course of DKD.

Prognostic prediction of idiopathic membranous nephropathy using interpretable machine learning.

BACKGROUND: Established prognostic models of idiopathic membranous nephropathy (IMN) were limited to traditional modeling methods and did not comprehensively consider clinical and pathological patient data. Based on the electronic medical record (EMR) system, machine learning (ML) was used to construct a risk prediction model for the prognosis of IMN. METHODS: Data from 418 patients with IMN were diagnosed by renal biopsy at the Fifth Clinical Medical College of Shanxi Medical University. Fifty-nine medical features of the patients could be obtained from EMR, and prediction models were established based on five ML algorithms. The area under the curve, recall rate, accuracy, and F1 were used to evaluate and compare the performances of the models. Shapley additive explanation (SHAP) was used to explain the results of the best-performing model. RESULTS: One hundred and seventeen patients (28.0%) with IMN experienced adverse events, 28 of them had compound outcomes (ESRD or double serum creatinine (SCr)), and 89 had relapsed. The gradient boosting machine (LightGBM) model had the best performance, with the highest AUC (0.892 ± 0.052, 95% CI 0.840-0.945), accuracy (0.909 ± 0.016), recall (0.741 ± 0.092), precision (0.906 ± 0.027), and F1 (0.905 ± 0.020). Recursive feature elimination with random forest and SHAP plots based on LightGBM showed that anti-phospholipase A2 receptor (anti-PLA2R), immunohistochemical immunoglobulin G4 (IHC IgG4), D-dimer (D-DIMER), triglyceride (TG), serum albumin (ALB), aspartate transaminase (AST), ß2-microglobulin (BMG), SCr, and fasting plasma glucose (FPG) were important risk factors for the prognosis of IMN. Increased risk of adverse events in IMN patients was correlated with high anti-PLA2R and low IHC IgG4. CONCLUSIONS: This study established a risk prediction model for the prognosis of IMN using ML based on clinical and pathological patient data. The LightGBM model may become a tool for personalized management of IMN patients.

Identification and validation of a m7G-related lncRNA signature for predicting the prognosis and therapy response in hepatocellular carcinoma.

BACKGROUND: N7-methylguanosine (m7G) is one of the most common RNA posttranscriptional modifications; however, its potential role in hepatocellular carcinoma (HCC) remains unknown. We developed a prediction signature based on m7G-related long noncoding RNAs (lncRNAs) to predict HCC prognosis and provide a reference for immunotherapy and chemotherapy. METHODS: RNA-seq data from The Cancer Genome Atlas (TCGA) database and relevant clinical data were used. Univariate and multivariate Cox regression analyses were conducted to identify m7G-related lncRNAs with prognostic value to build a predictive signature. We evaluated the prognostic value and clinical relevance of this signature and explored the correlation between the predictive signature and the chemotherapy treatment response of HCC. Moreover, an in vitro study to validate the function of CASC19 was performed. RESULTS: Six m7G-related lncRNAs were identified to create a signature. This signature was considered an independent risk factor for the prognosis of patients with HCC. TIDE analyses showed that the high-risk group might be more sensitive to immunotherapy. ssGSEA indicated that the predictive signature was strongly related to the immune activities of HCC. HCC in high-risk patients was more sensitive to the common chemotherapy drugs bleomycin, doxorubicin, gemcitabine, and lenalidomide. In vitro knockdown of CASC19 inhibited the proliferation, migration and invasion of HCC cells. CONCLUSION: We established a 6 m7G-related lncRNA signature that may assist in predicting the prognosis and response to chemotherapy and immunotherapy of HCC.

Research Progress of Cordyceps sinensis and Its Fermented Mycelium Products on Ameliorating Renal Fibrosis by Reducing Epithelial-to-Mesenchymal Transition.

Renal fibrosis is a hallmark and common outcome of various chronic kidney diseases (CKDs) and manifests pathologically as accumulation and deposition of extracellular matrix (ECM) in the kidney. Epithelial-to-mesenchymal transition (EMT) has been shown to be an important mechanism involved in renal fibrosis. Cordyceps sinensis, a traditional Chinese medicine, has long been used for the treatment of renal fibrosis. As research on the mycelium of C. sinensis progressed, a variety of medicines developed from fermented mycelium were used to treat CKD. However, their efficacies and mechanisms have not been fully summarized. In this review, five medicines developed from fermented mycelium of C. sinensis are presented. The pharmacodynamic effects of C. sinensis on different animal models of renal fibrosis are summarized. The in vitro studies and related mechanisms of C. sinensis on renal cells are detailed. Finally, the application and efficacy of these five commercial medicines that meet national standards in different types of CKD are summarized. From this review, it can be concluded that C. sinensis can alleviate various causes of renal fibrosis to some extent, and its mechanism is related to TGF-ß1 dependent signaling, inhibition of inflammation, and improvement of renal function. Further research on rigorously designed, large-sample, clinically randomized controlled trial studies and detailed mechanisms should be conducted.

Nicotine promotes renal interstitial fibrosis via upregulation of XIAP in an alpha7-nAChR-dependent manner.

Renal fibrosis, characterized by excessive accumulation of the extracellular matrix in the renal tubulointerstitium, can lead to chronic kidney disease (CKD), resulting in a heavy burden on families and society. Clinical studies have shown that smoking is closely associated with CKD deterioration in patients with diabetes, hypertension, polycystic kidney disease, and kidney transplantation. However, the mechanism of action of nicotine in renal fibrosis pathogenesis remains largely unknown. X-linked inhibitor of apoptosis (XIAP), a member of the inhibitor of apoptosis protein (IAP) family, is involved in apoptosis, necroptosis, autophagy, and immune response. Here, the upregulated expression of XIAP and α7 nicotine acetylcholine receptor (α7-nAChR) was determined in the kidneys of the CKD smoking group in human and animal studies. A significant positive correlation between XIAP and cotinine was observed. In addition, the nuclear translocation and transcriptional activity of SP1 were promoted when nicotine bound to α7-nAChR, resulting in XIAP overexpression and renal interstitial fibrosis progression. This phenotype can be reversed by the nicotine receptor subtype α7-nAChR antagonists methyllycaconitine. Our results revealed the complex underlying mechanism of nicotine in promoting renal fibrosis by altering SP1 nucleocytoplasmic translocation and regulating XIAP expression. These results provide novel insights into the pathogenesis and treatment of CKD.

Alterations of gut microbiota in biopsy-proven diabetic nephropathy and a long history of diabetes without kidney damage.

The gut microbiota is closely related to parenteral noncommunicable diseases through intestinal immunity and plays an important role in the occurrence of diabetes and diabetic nephropathy. The aim of the study was to understand the gut-kidney axis by an analysis of gut microbiota composition among patients with biopsy-proven diabetic nephropathy (DN), patients with type 2 diabetes for more than 10 years without kidney damage (DM), and healthy controls (NC). Thirty-five DN patients, 40 DM patients and 40 healthy subjects matched by age and sex were enrolled between January 2022 and December 2022. Baseline information and clinical parameters were collected. 16S rDNA sequencing was performed to characterize the gut microbiome and identify gut microbes that were differentially abundant between patients and healthy controls. The relationship between the relative abundance of specific bacterial taxa in the gut and clinical phenotype and pathological indicators was evaluated. Substantial differences were found in the richness of the gut microbiota and the variation in the bacterial population among DN patients, DM patients and healthy controls. DM patients could be accurately distinguished from age- and sex-matched healthy controls by variations in g_Clostridium-XVIII (AUC = 0.929), and DN patients could be accurately distinguished from age- and sex-matched healthy controls by variations in g_Gemmiger (AUC = 0.842). DN patients could be accurately distinguished from age- and sex-matched DM patients by variations in g_Flavonifractor or g_Eisenbergiella (AUC = 0.909 and 0.886, respectively). The gut microbiota was also closely related to clinical phenotypes and pathological indicators. The study of gut microbiota composition was explored to determine its relationship to the occurrence of DN and a long history of diabetes without kidney damage. The renal pathological progression of DN may be delayed by regulating changes in the gut microbiota.

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Combined with Multiple Machine Learning Identified a Novel Immune Signature in Diabetic Nephropathy.

Background: Increasing evidence suggests that immune modulation contributes to the pathogenesis and progression of diabetic nephropathy (DN). However, the role of immune modulation in DN has not been elucidated. The purpose of this study was to search for potential immune-related therapeutic targets and molecular mechanisms of DN. Methods: Gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. A total of 1793 immune-related genes were acquired from the Immunology Database and Analysis Portal (ImmPort). Weighted gene co-expression network analysis (WGCNA) was performed for GSE142025, and the red and turquoise co-expression modules were found to be key for DN progression. We utilized four machine learning algorithms, namely, random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), and k-nearest neighbor (KNN), to evaluate the diagnostic value of hub genes. Immune infiltration patterns were analyzed using the CIBERSORT algorithm, and the correlation between immune cell type abundance and hub gene expression was also investigated. Results: A total of 77 immune-related genes of advanced DN were selected for subsequent analyzes. Functional enrichment analysis showed that the regulation of cytokine-cytokine receptor interactions and immune cell function play a corresponding role in the progression of DN. The final 10 hub genes were identified through multiple datasets. In addition, the expression levels of the identified hub genes were corroborated through a rat model. The RF model exhibited the highest AUC. CIBERSORT analysis and single-cell sequencing analysis revealed changes in immune infiltration patterns between control subjects and DN patients. Several potential drugs to reverse the altered hub genes were identified through the Drug-Gene Interaction database (DGIdb). Conclusion: This pioneering work provided a novel immunological perspective on the progression of DN, identifying key immune-related genes and potential drug targets, thus stimulating future mechanistic research and therapeutic target identification for DN.

Exploratory metabolomic analysis based on UHPLC-Q-TOF-MS/MS to study hypoxia-reoxygenation energy metabolic alterations in HK-2 cells.

PURPOSE: Renal ischemia-reperfusion injury(IRI)is a major cause of acute kidney injury(AKI), the injury and repair of renal tubular epithelial cells play an important role in the pathological process of IR-AKI. Metabolomics was used to detect cell metabolism alterations and metabolic reprogramming in the initial injury, peak injury, and recovery stage of human renal proximal tubular cells (HK-2 cells) to provide insights into clinical prevention and treatment of IRI-induced AKI. METHODS: An in vitro ischemia-reperfusion (H/R) injury and the recovery model of HK-2 cells were established at different times of hypoxia/reoxygenation. Comprehensive detection of metabolic alterations in HK-2 cells after H/R induction by nontarget metabolomics. Interconversion of glycolysis and fatty acid oxidation (FAO) in HK-2 cells after H/R induction was examined by western blotting and qRT-PCR. RESULTS: Multivariate data analysis found significant differences among the groups, with significant changes in metabolites such as glutamate, malate, aspartate, and L-palmitoylcarnitine. Hypoxia-reoxygenated HK-2 cells are accompanied by altered metabolisms such as disturbance of amino acid and nucleotide metabolism, dysregulation of lipid metabolism, increased glycolysis, and metabolic reprogramming, which manifests as a shift in energy metabolism from FAO to glycolysis. CONCLUSION: The development of IRI-induced AKI in HK-2 cells is accompanied by the disturbance of amino acid, nucleotide, and tricarboxylic acid cycle metabolism and specifically metabolic reprogramming of FAO to glycolytic conversion. The timely recovery of energy metabolism in HK-2 cells is of great significance for treating and prognosis IRI-induced AKI.

Ghrelin attenuates inflammation in diabetic lung disease by TLR4 pathway in vivo and in vitro.

INTRODUCTION: Diabetic lung disease is already known as one of the diabetes complications, but report on its therapeutic strategy is rare. The present study aimed to add novel therapeutic strategy for diabetic lung disease, to reveal the protective effect of ghrelin on diabetic lung disease both in vivo and in vitro, and to discuss its probable molecular mechanism. RESEARCH DESIGN AND METHODS: Diabetic mice and 16HBE cells were our research objects. We surveyed the effect of ghrelin on streptozotocin-induced lung tissue morphology changes by H&E staining. Furthermore, the changes of proinflammatory cytokines (interleukin-1ß (IL-1ß) and tumor necrosis factor-α (TNF-α)) were detected by ELISA. To expound the molecular mechanism, we detected critical proteins of TLR4 pathway and observed their changes by immunohistochemistry (IHC), real-time PCR and western blot analysis in vivo and in vitro, respectively. RESULTS: The results of H&E staining showed that pathological alterations of the lung induced by hyperglycemia were ameliorated by ghrelin. The results of ELISA demonstrated that the elevated levels of IL-1ß and TNF-α induced by hyperglycemia turned to decrease in the lung after ghrelin treatment. In the results of IHC, real-time PCR and western blot analysis, we found that the TLR4 pathway was elevated by hyperglycemia or high glucose and is remarkably inhibited by the treatment of ghrelin both in vivo and in vitro. CONCLUSIONS: Ghrelin could inhibit inflammation of diabetic lung disease by regulating the TLR4 pathway. This study might affect research on diabetic lung disease, and the therapeutic potential of ghrelin for diabetic lung disease is worth considering.

Identification and verification of prognostic cancer subtype based on multi-omics analysis for kidney renal papillary cell carcinoma.

Background: Identifying Kidney Renal Papillary Cell Carcinoma (KIRP) patients with high-risk, guiding individualized diagnosis and treatment of patients, and identifying effective prognostic targets are urgent problems to be solved in current research on KIRP. Methods: In this study, data of multi omics for patients with KIRP were collected from TCGA database, including mRNAs, lncRNAs, miRNAs, data of methylation, and data of gene mutations. Data of multi-omics related to prognosis of patients with KIRP were selected for each omics level. Further, multi omics data related to prognosis were integrated into cluster analysis based on ten clustering algorithms using MOVICS package. The multi omics-based cancer subtype (MOCS) were compared on biological characteristics, immune microenvironmental cell abundance, immune checkpoint, genomic mutation, drug sensitivity using R packages, including GSVA, clusterProfiler, TIMER, CIBERSORT, CIBERSORT-ABS, quanTIseq, MCPcounter, xCell, EPIC, GISTIC, and pRRophetic algorithms. Results: The top ten OS-related factors for KIRP patients were annotated. Patients with KIRP were divided into MOCS1, MOCS2, and MOCS3. Patients in the MOCS3 subtype were observed with shorter overall survival time than patients in the MOCS1 and MOCS2 subtypes. MOCS1 was negatively correlated with immune-related pathways, and we found global dysfunction of cancer-related pathways among the three MOCS subtypes. We evaluated the activity profiles of regulons among the three MOCSs. Most of the metabolism-related pathways were activated in MOCS2. Several immune microenvironmental cells were highly infiltrated in specific MOCS subtype. MOCS3 showed a significantly lower tumor mutation burden. The CNV occurrence frequency was higher in MOCS1. As for treatment, we found that these MOCSs were sensitive to different drugs and treatments. We also analyzed single-cell data for KIRP. Conclusion: Based on a variety of algorithms, this study determined the risk classifier based on multi-omics data, which could guide the risk stratification and medication selection of patients with KIRP.

Randomized Phase 2 Trial of Telitacicept in Patients With IgA Nephropathy With Persistent Proteinuria.

Introduction: To date, no specific therapies have been approved for immunoglobulin A nephropathy (IgAN) treatment. Telitacicept is a fusion protein composed of transmembrane activator and calcium-modulating cyclophilin ligand interactor and fragment crystallizable portion of immunoglobulin G (IgG), which neutralizes the B lymphocyte stimulator and a proliferation-inducing ligand. Methods: This phase 2 randomized placebo-controlled trial aimed to evaluate the efficacy and safety of telitacicept in patients with IgAN. Participants with an estimated glomerular filtration rate (eGFR) >35 ml/min per 1.73 m2 and proteinuria ≥0.75 g/d despite optimal supportive therapy, were randomized 1:1:1 to receive subcutaneous telitacicept 160 mg, telitacicept 240 mg, or placebo weekly for 24 weeks. The primary end point was the change in 24-hour proteinuria at week 24 from baseline. Results: Forty-four participants were randomized into placebo (n = 14), telitacicept 160 mg (n = 16), and telitacicept 240 mg (n = 14) groups. Continuous reductions in serum IgA, IgG, and IgM levels were observed in the telitacicept group. Telitacicept 240 mg therapy reduced mean proteinuria by 49% from baseline (change in proteinuria vs. placebo, 0.88; 95% confidence interval, -1.57 to -0.20; P = 0.013), whereas telitacicept 160 mg reduced it by 25% (-0.29; 95% confidence interval, -0.95 to 0.37; P = 0.389). The eGFR remained stable over time. Adverse events (AEs) were similar in all groups. Treatment-emergent AEs were mild or moderate, and no severe AEs were reported. Conclusion: Telitacicept treatment led to a clinically meaningful reduction in proteinuria in patients with IgAN in the present phase 2 clinical trial. This effect is indicative of a reduced risk for future kidney disease progression.

Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma.

BACKGROUND: Necroptosis is a necrotic programmed cell death with potent immunogenicity. Due to the dual effects of necroptosis on tumor growth, metastasis and immunosuppression, we evaluated the prognostic value of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC). METHODS: We first analyzed RNA sequencing and clinical HCC patient data obtained to develop an NRG prognostic signature based on the TCGA dataset. Differentially expressed NRGs were further evaluated by GO and KEGG pathway analyses. Next, we conducted univariate and multivariate Cox regression analyses to build a prognostic model. We also used the dataset obtained from the International Cancer Genome Consortium (ICGC) database to verify the signature. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the immunotherapy response. Furthermore, we investigated the relationship between the prediction signature and chemotherapy treatment response in HCC. RESULTS: We first identified 36 differentially expressed genes out of 159 NRGs in hepatocellular carcinoma. Enrichment analysis showed that they were mainly enriched in the necroptosis pathway. Four NRGs were screened by Cox regression analysis to establish a prognostic model. The survival analysis revealed that the overall survival of patients with high-risk scores was significantly shorter than that of patients with low-risk scores. The nomogram demonstrated satisfactory discrimination and calibration. The calibration curves validated a fine concordance between the nomogram prediction and actual observation. The efficacy of the necroptosis-related signature was also validated by an independent dataset and immunohistochemistry experiments. TIDE analysis revealed that patients in the high-risk group were possibly more susceptible to immunotherapy. Furthermore, high-risk patients were found to be more sensitive to conventional chemotherapeutic medicines such as bleomycin, bortezomib, and imatinib. CONCLUSION: We identified 4 necroptosis-related genes and established a prognostic risk model that could potentially predict prognosis and response to chemotherapy and immunotherapy in HCC patients in the future.

A Multifactorial Risk Score System for the Prediction of Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus.

Purpose: In-depth investigations of risk factors for the identification of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) are rare. We aimed to investigate the risk factors for developing DKD from multiple types of clinical data and conduct a comprehensive risk assessment for individuals with diabetes. Methods: We carried out a case-control study, enrolling 958 patients to identify the risk factors for developing DKD in T2DM patients from a database established from inpatient electronic medical records. Multivariable logistic regression was applied to develop a prediction model and the performance of the model was evaluated using the area under the curve (AUC) and calibration curve. A multifactorial risk score system was established according to the Framingham Study risk score. Results: DKD accounted for 34.03% of eligible patients in total. Twelve risk factors were selected in the final prediction model, including age, duration of diabetes, duration of hypertension, fasting blood glucose, fasting C-peptide, insulin use, systolic blood pressure, low-density lipoprotein, γ-glutamyl transpeptidase, platelet, uric acid, and thyroid stimulating hormone; and one protective factor, serum albumin. The prediction model showed an AUC of 0.862 (95% Confidence Interval (CI) 0.834-0.890) with an accuracy of 81.5% in the derivation dataset and an AUC of 0.876 (95% CI 0.825-0.928) in the validation dataset. The calibration curves were excellent and the estimated probability of DKD was more than 80% when the cumulative score for risk factors reached 17 points. Conclusion: Newly recognized risk factors were applied to assess the development of DKD in T2DM patients and the established risk score system was a reliable and feasible tool for assisting clinicians to identify patients at high risk of DKD.