Human umbilical cord mesenchymal stem cell-derived exosomes ameliorate renal fibrosis in diabetic nephropathy by targeting Hedgehog/SMO signaling.

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease globally. Currently, there are no effective drugs for the treatment of DN. Although several studies have reported the therapeutic potential of mesenchymal stem cells, the underlying mechanisms remain largely unknown. Here, we report that both human umbilical cord MSCs (UC-MSCs) and UC-MSC-derived exosomes (UC-MSC-exo) attenuate kidney damage, and inhibit epithelial-mesenchymal transition (EMT) and renal fibrosis in streptozotocin-induced DN rats. Strikingly, the Hedgehog receptor, smoothened (SMO), was significantly upregulated in the kidney tissues of DN patients and rats, and positively correlated with EMT and renal fibrosis. UC-MSC and UC-MSC-exo treatment resulted in decrease of SMO expression. In vitro co-culture experiments revealed that UC-MSC-exo reduced EMT of tubular epithelial cells through inhibiting Hedgehog/SMO pathway. Collectively, UC-MSCs inhibit EMT and renal fibrosis by delivering exosomes and targeting Hedgehog/SMO signaling, suggesting that UC-MSCs and their exosomes are novel anti-fibrotic therapeutics for treating DN.

scATAnno: Automated Cell Type Annotation for single-cell ATAC Sequencing Data.

Recent advances in single-cell epigenomic techniques have created a growing demand for scATAC-seq analysis. One key analysis task is to determine cell type identity based on the epigenetic data. We introduce scATAnno, a python package designed to automatically annotate scATAC-seq data using large-scale scATAC-seq reference atlases. This workflow generates the reference atlases from publicly available datasets enabling accurate cell type annotation by integrating query data with reference atlases, without the use of scRNA-seq data. To enhance annotation accuracy, we have incorporated KNN-based and weighted distance-based uncertainty scores to effectively detect cell populations within the query data that are distinct from all cell types in the reference data. We compare and benchmark scATAnno against 7 other published approaches for cell annotation and show superior performance in multiple data sets and metrics. We showcase the utility of scATAnno across multiple datasets, including peripheral blood mononuclear cell (PBMC), Triple Negative Breast Cancer (TNBC), and basal cell carcinoma (BCC), and demonstrate that scATAnno accurately annotates cell types across conditions. Overall, scATAnno is a useful tool for scATAC-seq reference building and cell type annotation in scATAC-seq data and can aid in the interpretation of new scATAC-seq datasets in complex biological systems.

Efficacy and safety of Ophiocordyceps sinensis in the treatment of Hashimoto's thyroiditis: a systematic review and meta-analysis.

Objective: To evaluate the efficacy and safety of Ophiocordyceps sinensis (OS) preparations for the treatment of Hashimoto's thyroiditis (HT). Methods: We searched eight databases to collect randomized controlled trials (RCTs) of OS combined with a low-iodine diet or levothyroxine for HT. The search period was from inception to June 2023. Meta-analysis was performed using Revman 5.3 software after two evaluators independently screened the literature, extracted data, and evaluated the risk of bias of the included studies. The GRADE system was used to assess the certainty of evidence. Results: A total of 14 RCTs involving 1,014 patients with HT were included. Meta-analysis showed that OS preparations combined with a low-iodine diet were more effective in reducing thyroid peroxidase antibody (TPOAb) [SMD = -3.81, 95% CI (-5.07, -2.54), p < 0.00001] and thyroglobulin antibody (TgAb) [SMD = -4.73, 95% CI (-6.86, -2.61), p < 0.00001] compared to a low-iodine diet. Compared with levothyroxine treatment alone, OS preparations combined with levothyroxine further reduced TPOAb [SMD = -2.04, 95% CI (-2.82, -1.26), p < 0.00001], TgAb [SMD = -2.01, 95% CI (-2.68, -1.33), p < 0.00001], tumor necrosis factor alpha (TNF-α) [SMD = -3.40, 95% CI (-5.66, -1.14), p = 0.003], interleukin-2 (IL-2) [SMD = -2.31, 95% CI (-3.98, -0.65), p = 0.006], and interleukin-6 (IL-6) [MD = -4.16, 95% CI (-6.17, -2.15), p < 0.0001], and elevated free thyroxine (FT4) [SMD = 1.34, 95% CI (0.59, 2.08), p = 0.0004], but no significant effect on free triiodothyronine (FT3) [SMD = 0.83, 95% CI (-0.12, 1.78), p = 0.09] and thyroid stimulating hormone (TSH) [SMD = -0.80, 95% CI (-1.71, 0.11), p = 0.08]. In terms of safety, three studies reported adverse reactions in 10 patients in each of the experimental and control groups. Conclusion: OS preparations in combination with other treatments (low-iodine diet or levothyroxine) may decrease thyroid autoantibodies and inflammatory responses in patients with HT. In HT patients with hypothyroidism, the combination of the OS preparations with levothyroxine also improved FT4. However, the quality of the included studies was generally low. Moreover, the safety of OS preparations remains unclear. Therefore, more high-quality, multicenter, large-sample RCTs are needed in the future to validate the efficacy and safety of OS preparations. Systematic Review Registration: https://www.crd.york.ac.uk/prospero, identifier CRD42023432663.

Liquid biopsy epigenomic profiling for cancer subtyping.

Although circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1 ml of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling has the potential to unlock clinically actionable information that is currently accessible only via direct tissue sampling.

KDM6A epigenetically regulates subtype plasticity in small cell lung cancer.

Small cell lung cancer (SCLC) exists broadly in four molecular subtypes: ASCL1, NEUROD1, POU2F3 and Inflammatory. Initially, SCLC subtypes were thought to be mutually exclusive, but recent evidence shows intra-tumoural subtype heterogeneity and plasticity between subtypes. Here, using a CRISPR-based autochthonous SCLC genetically engineered mouse model to study the consequences of KDM6A/UTX inactivation, we show that KDM6A inactivation induced plasticity from ASCL1 to NEUROD1 resulting in SCLC tumours that express both ASCL1 and NEUROD1. Mechanistically, KDM6A normally maintains an active chromatin state that favours the ASCL1 subtype with its loss decreasing H3K4me1 and increasing H3K27me3 at enhancers of neuroendocrine genes leading to a cell state that is primed for ASCL1-to-NEUROD1 subtype switching. This work identifies KDM6A as an epigenetic regulator that controls ASCL1 to NEUROD1 subtype plasticity and provides an autochthonous SCLC genetically engineered mouse model to model ASCL1 and NEUROD1 subtype heterogeneity and plasticity, which is found in 35-40% of human SCLCs.

Association of Mitral Regurgitation with Postoperative Atrial Fibrillation in Critically Ill Noncardiac Surgery Patients: A Prospective Cohort Study.

Purpose: Atrial fibrillation (AF) is common in critically ill patients and can have serious consequences. Postoperative AF (POAF) in critically ill patients following noncardiac surgery has been understudied, contrary to cardiac procedures. Mitral regurgitation (MR) is associated with left ventricular dysfunction, which might contribute to the occurrence of AF in postoperative critically ill patients. This study aimed to investigate the association between MR and POAF in critically ill noncardiac surgery patients and establish a new nomogram for the prediction of POAF in critically ill noncardiac surgery patients. Patients and Methods: A prospective cohort of 2474 patients who underwent thoracic and general surgery was enrolled in this study. Data on preoperative transthoracic echocardiography (TTE), electrocardiogram (ECG), and several commonly utilized scoring systems (CHA2DS2-VASc, HATCH, COM-AF, HART, and C2HEST) and baseline clinical data were collected. Independent predictors were selected by univariate and multivariable logistic regression analysis, and a nomogram was constructed for POAF within 7 days after postoperative intensive care unit (ICU) admission. The ability of the MR-nomogram and other scoring systems to predict POAF was compared by receiver operator characteristic (ROC) curve analysis and decision curve analysis (DCA). Additional contributions were evaluated by integrated discrimination improvement (IDI) and net reclassification improvement (NRI) analysis. Results: A total of 213 (8.6%) patients developed POAF within 7 days after ICU admission. Compared to CHA2DS2-VASc, HATCH, COM-AF, HART, and C2HEST scoring systems, MR-nomogram showed better predictive ability for POAF with an area under the ROC curve of 0.824 (95% confidence interval: 0.805-0.842, p < 0.001). The improvement of the MR-nomogram in predictive value was supported by NRI and IDI analysis. The net benefit of the MR nomogram was maximal in DCA. Conclusion: MR is an independent risk factor of POAF in critically ill noncardiac surgery patients. The nomogram predicted POAF better than other scoring systems.

Binimetinib ameliorates the severity of septic cardiomyopathy by downregulating inflammatory factors.

BACKGROUND: Septic cardiomyopathy (SCM) has a worse prognosis with mortality rates of up to 70%. Most existing treatment is useless and no specific drug or treatment has been found in patients with myocardial hypofunction. METHODS: We explored the efficacy of the target drugs (Binimetinib) in SCM model in vivo based on high throughput sequencing and bioinformatics analysis. Firstly, a stable SCM mice model was constructed. Secondly, the hub genes of SCM were clarified by high throughput sequencing and bioinformatics analysis. The related pathways and biological process were revealed by Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) enrichment analysis. Thirdly, the target drugs of the hub genes were investigated by network pharmacology analysis. Fourthly, the curative effects and hub genes regulatory effects of Binimetinib were demonstrated by SCM mice model. Finally, the regulatory mechanism of the target drugs on the hub genes were analyzed by molecular docking. RESULTS: 109 CFU/ml P. aeruginosa daubed in wound could establish a stable SCM mice model. Il-6, Il-1ß and Tnf were the hub genes of SCM. Immune system process and inflammatory response were the main biological process. Binimetinib was the target drug of IL-6, IL-1ß and TNF-α. JUN and NFKB1 were the transcription factor (TFs) of hub genes and Binimetinib had the lowest binding energy with NFKB1. CONCLUSIONS: A stable SCM model was established by wound P. aeruginosa infection. Tnf, Il-1ß, Il-6 were the key genes of SCM. Binimetinib might be a drug for the treatment of SCM by downregulating the hub genes. Its active mechanism might be related to NFKB1.

Soluble Programmed Cell Death Protein 1 and Its Ligand: Potential Biomarkers to Predict Acute Kidney Injury After Surgery in Critically Ill Patients.

Purpose: Programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) have been detected in injury kidney. However, their expressions are unclear in mice kidneys under renal ischemia-reperfusion injury (IRI). In this study, we would observe the expressions of PD-1 and PD-L1 in kidney tissues and analyze the association between the concentrations of PD-1 and PD-L1 in mouse kidney homogenate and the corresponding concentrations of soluble PD-1 (sPD-1) and soluble PD-L1 (sPD-L1) in plasma after renal IRI. Further, we explored the predictive value of sPD-1 and sPD-L1 for acute kidney injury (AKI) in high-risk patients after surgery. Methods: This study established an AKI model induced by IRI in mice. Plasma, kidney samples, and homogenate were collected 0h, 24h, and 48h after surgery for immunohistochemistry and enzyme-linked immunosorbent assay. Then, we continuously enrolled 88 AKI high-risk patients who underwent noncardiac surgery. The biomarkers, including sPD-1, sPD-L1, and urine neutrophil gelatinase-associated lipocalin (NGAL), tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein 7 (IGFBP7), were detected immediately after surgery. Results: Our data revealed the concentrations of PD-1 and PD-L1 in kidney homogenate, and sPD-1 and sPD-L1 in plasma significantly increased at 0h, 24h, and 48h after IRI. A positive association was found between PD-1 and sPD-1 (r = 0.774, p < 0.001), and between PD-L1 and sPD-L1 (r = 0.881, p < 0.001). Compared to NGAL, [TIMP-2]*[IGFBP7], sPD-1 and sPD-L1 showed better predictive abilities for AKI with an area under the ROC curve of 0.856 (95% confidence interval [CI]: 0.825-0.958, p < 0.001) and 0.906 (95% CI: 0.764-0.921, p < 0.001). Conclusion: The increased expressions of PD-1 and PD-L1 in kidneys under IRI suggested they may play essential roles in AKI development. sPD-1 and sPD-L1 can indirectly reflect the expressions of PD-1 and PD-L1 in kidneys, respectively. sPD-1 and sPD-L1 showed excellent predictive ability for AKI in high-risk patients.

Opposite effects of miR-155 in the initial and later stages of lipopolysaccharide (LPS)-induced inflammatory response.

Although microRNA-155 (miR-155) is considered a pro-inflammatory mediator, cumulative evidence indicates that it also has anti-inflammatory effects in macrophages and dendritic cells. In this study, we identified the dramatic expression changes of more than half of potential miR-155-targeted genes upon lipopolysaccharide (LPS) stimulation; 223 genes were down-regulated and 85 genes were up-regulated, including suppressor of cytokine signaling 1 (SOCS1) and transforming growth factor-ß-activated kinase 1-binding protein 2 (TAB2), two well-known genes involved in miR-155-mediated regulation of the Toll-like receptor 4 (TLR4) signaling pathway. We also found that miR-155 acted as an anti-inflammatory mediator in the initial stage of LPS-induced inflammatory response mainly through repressing TAB2 protein translation, and as a pro-inflammatory mediator by down-regulating SOCS1 in the later stage. Meanwhile, overexpression of TAB2 3' untranslated region (UTR) in macrophages promoted the development of endotoxin tolerance by competing for binding with miR-155, which resulted in an elevated expression level of SOCS1 protein. These findings provide new insights for understanding the regulatory mechanisms in fine-tuning of LPS-induced innate immune response.

Plasma Endogenous Sulfur Dioxide: A Novel Biomarker to Predict Acute Kidney Injury in Critically Ill Patients.

PURPOSE: Sulfur dioxide (SO2) is a novel gaseous signaling molecule that plays an important role in inflammation, which contributes the pathogenesis of acute kidney injury (AKI). The aim of this study was to explore the predictive value of plasma SO2 for AKI in high-risk patients. PATIENTS AND METHODS: A prospective cohort of 167 patients who underwent major noncardiac surgery was enrolled in the study. Plasma SO2, urine neutrophil gelatinase-associated lipocalin (NGAL), tissue inhibitor of metalloproteinase-2 (TIMP-2), and insulin-like growth factor-binding protein 7 (IGFBP7) levels were detected immediately after the operation. The primary endpoint was new-onset AKI within 72 h after admission. The ability of biomarkers including SO2 and a clinical risk model to predict AKI was compared by receiver operator characteristic (ROC) curve analysis and decision curve analysis (DCA), additional contributions were evaluated by integrated discrimination improvement (IDI) and net reclassification improvement (NRI) analyses. RESULTS: A total of 61 (36.5%) patients developed AKI within 72 h of surgery. Compared to NGAL and [TIMP-2]·[IGFBP7], SO2 showed better predictive ability for new-onset AKI with an area under the ROC curve of 0.771 (95% confidence interval: 0.700-0.832, p<0.001). The improvement in predictive value by including SO2 in the clinical risk model was supported by NRI (0.28; P=0.04) and IDI (0.15; P<0.001) analyses. The net benefit of the combination of SO2 and clinical variables was the max in DCA. CONCLUSION: Plasma SO2 shows a useful value for predicting new-onset AKI, and improved AKI prediction based on clinical variables, which can guide the implementation of preventive measures for high-risk patients.

Prognostic value of dynamic plasma endostatin for the prediction of mortality in acute kidney injury: A prospective cohort study.

OBJECTIVE: The aim of the current study was to evaluate the value of plasma endostatin for predicting 30-day mortality of patients with acute kidney injury (AKI). METHODS: Patients who underwent non-cardiac major surgery and developed AKI in the first 48 hours after admission to the intensive care unit were consecutively included. Concentrations of plasma neutrophil gelatinase-associated lipocalin (NGAL), cystatin C (Cys C), and endostatin were measured at three time points: 0, 24, and 48 hours after the AKI diagnosis. Clinical patient characteristics were recorded after AKI was diagnosed. RESULTS: A total of 256 new-onset AKI patients were enrolled. Of these, 48 (18.7%) patients died within 30 days. The difference in plasma endostatin values between 0 and 24 hours (ΔEndostatin-24h) yielded the best area under the curve (AUC) of 0.747 for predicting 30-day mortality in AKI patients; NGAL and Cys C achieved AUC of 0.672 and 0.647, respectively. The predictive AUC increased to 0.833 when ΔEndostatin-24h was combined with sequential organ failure assessment score and AKI classification. CONCLUSION: Dynamic plasma endostatin is useful for predicting 30-day mortality in AKI patients. The predictive power of dynamic plasma endostatin can be significantly improved when it is combined with clinical patient data.

Derivation and validation of plasma endostatin for predicting renal recovery from acute kidney injury: a prospective validation study.

BACKGROUND: Acute kidney injury (AKI) is associated with high morbidity and mortality in surgical patients. Nonrecovery from AKI may increase mortality and early risk stratification seems key to improving clinical outcomes. The aim of the current study was to explore and validate the value of endostatin for predicting failure to recover from AKI. METHODS: We conducted a prospective cohort study of 198 patients without known chronic kidney disease who underwent noncardiac major surgery and developed new-onset AKI in the first 48 h after admission to the ICU. The biomarkers of plasma endostatin, neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C were detected immediately after AKI diagnosis. The primary endpoint was nonrecovery from AKI (within 7 days). Cutoff values of the biomarkers for predicting nonrecovery were determined in a derivation cohort (105 AKI patients). Predictive accuracy was then analyzed in a validation cohort (93 AKI patients). RESULTS: Seventy-six of 198 (38.4%) patients failed to recover from AKI onset, with 41 in the derivation cohort and 35 in the validation cohort. Compared with NGAL and cystatin C, endostatin showed a better prediction for nonrecovery, with an area under the receiver operating characteristic curve (AUC) of 0.776 (95% confidence interval (CI) 0.654-0.892, p < 0.001) and an optimal cutoff value of 63.7 ng/ml. The predictive ability for nonrecovery was greatly improved by the prediction model combining endostatin with clinical risk factors of Sequential Organ Failure Assessment (SOFA) score and AKI classification, with an AUC of 0.887 (95% CI 0.766-0.958, p < 0.001). The value of the endostatin-clinical risk prediction model was superior to the NGAL-clinical risk and cystatin C-clinical risk prediction models in predicting failure to recover from AKI, which was supported by net reclassification improvement and integrated discrimination improvement. Further, the endostatin-clinical risk prediction model achieved sensitivity and specificity of 94.6% (76.8-99.1) and 72.7% (57.2-85.0), respectively, when validated in the validation cohort. CONCLUSION: Plasma endostatin shows a useful value for predicting failure to recover from AKI. The predictive ability can be greatly improved when endostatin is combined with the SOFA score and AKI classification.