Construction of a cross-species cell landscape at single-cell level.

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging

Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma

Abstract Background Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated with radical cystectomy (RC). Methods We retrospectively collected demographic, pathological, imaging, and laboratory information of BUC patients who underwent RC and bilateral lymphadenectomy in our institution. Patients were randomly categorized into training set and testing set. Five ML algorithms were utilized to establish prediction models. The performance of each model was assessed by the area under the receiver operating characteristic curve (AUC) and accuracy. Finally, we calculated the corresponding variable coefficients based on the optimal model to reveal the contribution of each variable to LNM. Results A total of 524 and 131 BUC patients were finally enrolled into training set and testing set, respectively. We identified that the support vector machine (SVM) model had the best prediction ability with an AUC of 0.934 (95% confidence interval [CI]: 0.903–0.964) and accuracy of 0.916 in the training set, and an AUC of 0.855 (95%CI: 0.777–0.933) and accuracy of 0.809 in the testing set. The SVM model contained 14 predictors, and positive lymph node in imaging contributed the most to the prediction of LNM in BUC patients. Conclusions We developed and validated the ML models to preoperatively predict LNM in BUC patients treated with RC, and identified that the SVM model with 14 variables had the best performance and high levels of clinical applicability

Integrated Analysis and Identification of Critical RNA-Binding Proteins in Bladder Cancer

RBPs in the development and progression of BC remains unclear. Here, we elucidated the role of RBPs in predicting the survival of patients with BC. Clinical information and RNA sequencing data of the training and validation cohorts were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Survival-related differentially expressed RBPs were identified using Cox regression analyses. A total of 113 upregulated and 54 downregulated RBPs were observed, with six showing prognostic values (AHNAK, MAP1B, LAMA2, P4HB, FASN, and GSDMB). In both the GSE32548 and GSE31684 datasets, patients with low-risk scores in survival-related six RBPs-based prognostic model showed longer overall survival than those with high-risk scores. AHNAK, MAP1B, P4HB, and FASN expression were significantly upregulated in both BC tissues and cell lines. BC tissues from high-risk group showed higher proportions of naive CD4+ T cells, M0 and M2 macrophages, and neutrophils and lower proportions of plasma cells, CD8+ T cells, and T-cell follicular helper compared to low-risk group. AHNAK knockdown significantly inhibited the proliferation, invasion, and migration of BC cells in vitro and inhibited the growth of subcutaneous tumors in vivo. We thus developed and functionally validated a novel six RBPs-based prognostic model for BC

Lung tumor discrimination by deep neural network model CanDo via DNA methylation in bronchial lavage

Summary: Bronchoscopic-assisted discrimination of lung tumors presents challenges, especially in cases with contraindications or inaccessible lesions. Through meta-analysis and validation using the HumanMethylation450 database, this study identified methylation markers for molecular discrimination in lung tumors and designed a sequencing panel. DNA samples from 118 bronchial washing fluid (BWF) specimens underwent enrichment via multiplex PCR before targeted methylation sequencing. The Recursive Feature Elimination Cross-Validation and deep neural network algorithm established the CanDo classification model, which incorporated 11 methylation features (including 8 specific to the TBR1 gene), demonstrating a sensitivity of 98.6% and specificity of 97.8%. In contrast, bronchoscopic rapid on-site evaluation (bronchoscopic-ROSE) had lower sensitivity (87.7%) and specificity (80%). Further validation in 33 individuals confirmed CanDo’s discriminatory potential, particularly in challenging cases for bronchoscopic-ROSE due to pathological complexity. CanDo serves as a valuable complement to bronchoscopy for the discriminatory diagnosis and stratified management of lung tumors utilizing BWF specimens

Efficacy and safety of olmesartan medoxomil‐amlodipine besylate tablet in Chinese patients with essential hypertension: A prospective, single‐arm, multi‐center, real‐world study

Abstract There lacks real‐world study with a large sample size assessing olmesartan medoxomil‐amlodipine besylate (OM‐AML) tablet. Therefore, this study aimed to evaluate the efficacy and safety of OM‐AML tablet in patients with essential hypertension. Totally, 1341 patients from 36 medical centers with essential hypertension who took OM‐AML (20/5 mg) tablet were analyzed in the current prospective, single‐arm, multi‐center, real‐world study (SVK study). Seated systolic blood pressure (SeSBP) and seated diastolic blood pressure (SeDBP) at baseline, week (W)4 and W8 were measured. The mean (±SE) change of SeSBP/SeDBP was ‐10.8 ± 0.4/‐6.6 ± 0.3 mmHg at W4 and ‐12.7 ± 0.5/‐7.6 ± 0.3 mmHg at W8, respectively. At W4, 78.8% and 29.0% patients achieved BP target by China and American Heart Association (AHA) criteria; at W8, 84.7% and 36.5% patients reached blood pressure (BP) target by China and AHA criteria, accordingly. Meanwhile, 80.2% and 86.4% patients achieved BP response at W4 and W8, respectively. Home‐measured SeSBP and SeDBP decreased from W1 to W8 (both p < .001). Besides, patients’ and physicians’ satisfaction were elevated at W8 compared with W0 (both p < .001). The medication possession rate was 94.8% from baseline to W4 and 91.3% from baseline to W8. The most common drug‐related adverse events were nervous system disorders (4.6%), vascular disorders (2.6%), and general disorders and administration site conditions (2.3%) by system organ class, which were generally mild and manageable. In conclusion, OM‐AML tablet is one of the best antihypertensive agents in patients with essential hypertension