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Anti-interferon-γ autoantibodies (AIGAs) immunodeficiency syndrome is an emerging adult-onset immunodeficiency causing opportunistic infections. However, its comprehensive immune landscape remains elusive. This study presents the first single-cell RNA sequencing (scRNA-seq) analysis of AIGAs immunodeficiency syndrome, aiming to delineate its pathogenic mechanisms. We performed scRNA-seq on peripheral blood mononuclear cells (PBMCs) from 8 AIGAs immunodeficiency syndrome patients (4 infective, 4 stable phase) and 3 healthy controls. Findings were validated by flow cytometry in an expanded cohort (15 patients vs. 10 controls). Single-cell RNA sequencing of PBMCs from patients with AIGAs immunodeficiency syndrome identified a comprehensive immune subset profile, including effector memory CD4 T cells, naive CD4 T cells, regulatory T cells, GNLY CD8 Tem, GZMK CD8 Tem, naive CD8 T cells, naive B cells, memory B cells, plasma cells, ISG atypical B cells, monocytes, and NKT cells. ScRNA-seq analysis revealed a significantly higher proportion of Th1 cells (16.62% vs. 6.94% in controls) and ISG B cells (2.95% vs. 0.53%), alongside a lower proportion of plasma cells (9.30% vs. 17.79%) and memory B cells (9.54% vs. 27.35%). Flow cytometry consistently confirmed the increase in Th1 cells (21.84% [14.87-27.57] vs. 11.96% [7.19-15.74]) and decreases in marginal zone B cells (2.87% [1.71-4.45] vs. 8.60% [6.77-15.65]), memory B cells (13.85% [5.72-20.23] vs. 22.96% [16.39-33.83]), and class-switched B cells (6.11% [2.39-9.10] vs. 10.18% [5.35-15.77]). Transcriptome analysis demonstrated upregulated expression of interferon-response and HLA genes (e.g., HLA-DQB1, HLA-DQA1, HLA-DRB1), whereas IRF1 was downregulated across all subsets; functional enrichment analyses further highlighted significant activation in IFN signaling and B cell activation pathways. CellChat and pseudotime analyses indicated that CD4 Tem and CD14 monocytes drive sustained Th1 inflammation and monocyte hyperactivation through enhanced pro-inflammatory and antigen-presenting interactions, with T-cell differentiation skewed toward terminal effectors and B-cell development disrupted by ISG B cell emergence, premature plasma cell formation, and IGLC3-biased class switching, collectively delineating the interferon-mediated immunopathology of AIGAs immunodeficiency syndrome. In summary, this first single-cell atlas maps AIGAs immunodeficiency syndrome as a Th1-skewed, IFN-γ-driven disorder sustained by CD4 Tem-CD14 monocyte crosstalk. It combines T-cell activation, expanded Th1 and ISG B cells, and loss of memory/plasma B cells to drive autoantibody generation. Skewed T- and B-cell trajectories and polygenic up-regulation of interferon/HLA genes provide a clear mechanistic rationale for targeted therapy.

Background Obesity (waist circumference, body mass index (BMI)) and lifestyle factors (dietary habits, smoking, alcohol drinking, Sedentary behavior) have been associated with risk of benign prostatic hyperplasia (BPH) in observational studies, but whether these associations are causal is unclear. Methods We performed a univariable and multivariable Mendelian randomization study to evaluate these associations. Genetic instruments associated with exposures at the genome-wide significance level ( P  < 5 × 10 –8 ) were selected from corresponding genome-wide associations studies (n = 216,590 to 1,232,091 individuals). Summary-level data for BPH were obtained from the UK Biobank (14,126 cases and 169,762 non-cases) and FinnGen consortium (13,118 cases and 72,799 non-cases). Results from UK Biobank and FinnGen consortium were combined using fixed-effect meta-analysis. Results The combined odds ratios (ORs) of BPH were 1.24 (95% confidence interval (CI), 1.07–1.43, P  = 0.0045), 1.08 (95% CI 1.01–1.17, P  = 0.0175), 0.94 (95% CI 0.67–1.30, P  = 0.6891), 1.29 (95% CI 0.88–1.89, P  = 0.1922), 1.23 (95% CI 0.85–1.78, P  = 0.2623), and 1.04 (95% CI 0.76–1.42, P  = 0.8165) for one standard deviation (SD) increase in waist circumference, BMI, and relative carbohydrate, fat, protein and sugar intake, 1.05 (95% CI 0.92–1.20, P  = 0.4581) for one SD increase in prevalence of smoking initiation, 1.10 (95% CI 0.96–1.26, P  = 0.1725) and 0.84 (95% CI 0.69–1.02, P  = 0.0741) for one SD increase of log-transformed smoking per day and drinks per week, and 1.31 (95% CI 1.08–1.58, P  = 0.0051) for one SD increase in sedentary behavior. Genetically predicted waist circumference (OR = 1.26, 95% CI 1.11–1.43, P  = 0.0004) and sedentary behavior (OR = 1.14, 95% CI 1.05–1.23, P  = 0.0021) were associated with BPH after the adjustment of BMI. Conclusion This study supports independent causal roles of high waist circumference, BMI and sedentary behavior in BPH.

Urban airborne laser scanning (ALS) point clouds cover extensive geographical areas, rendering dense point-level annotation economically prohibitive and limiting the feasibility of fully supervised learning. In weakly supervised settings for urban ALS data, the natural long-tailed class distribution—where ground and building points dominate and smaller objects are rare—combined with the use of fixed pseudo-label thresholds under sparse annotations exacerbates confirmation bias and increases prediction uncertainty. This ultimately restricts the effective utilization of unlabeled data during training. To overcome these challenges, we propose a pseudo-label confidence-calibrated curriculum learning framework designed for weakly supervised ALS point cloud classification. The framework introduces a confidence-aware self-adaptive soft gating (CSS) mechanism that dynamically adjusts category-specific thresholds online using exponential moving average statistics and scene-aware normalization, eliminating the need for manual scheduling while improving pseudo-label quality. In addition, a reliability-driven soft selection (RSS) constraint is incorporated, in which each point is assigned a comprehensive reliability score that integrates prediction confidence, entropy clarity, and cross-augmentation consistency, enabling adaptive soft weighting to replace hard pseudo-label selection and achieve more balanced sample utilization. These components are further integrated into a unified pseudo-label confidence-calibrated curriculum learning framework (P3CL) that progressively shifts the model’s focus from high-certainty samples to more ambiguous ones, effectively mitigating confirmation bias. Extensive experiments on three public ALS benchmarks demonstrate that the proposed method consistently outperforms existing weakly supervised approaches and achieves competitive performance compared with several fully supervised models.

Sedentary behavior is widely recognized as a detriment to health. Limited conclusions have been drawn about the relationship between sitting time and biomarkers-measured aging. 12,504 eligible adults were included from the National Health and Nutrition Examination Survey (NHANES) 2007 to 2016. Weighted logistic regression, subgroup analysis, and restricted cubic spline regression were conducted to investigate the association and dose-response relationship between sitting time and phenotypic age acceleration (PhenoAgeAccel). The mediating effect of body mass index (BMI) on this correlation was revealed by mediation analysis. After adjusting for multiple covariates, longer sitting time (4–6 h: OR 1.30, 95%CI 1.06–1.58, p  = 0.013; 6–8 h: OR 1.25, 95%CI 1.01–1.55, p  = 0.038; ≥8 h: OR 1.58, 95%CI 1.33–1.88, p  < 0.001) significantly had higher risk of aging comparing to the reference (< 4 h). The dose-response relationship exhibited an approximately linear dependence. Additionally, BMI partially mediated the association between sitting time and PhenoAgeAccel by a 21.0% proportion. Our study revealed a strong, significant, independent, linear relationship between sitting time and phenotypic age. BMI served as a mediator of the correlation between sitting time and PhenoAgeAccel.

Backgrounds The study aimed to estimate bladder cancer burden and its attributable risk factors in China, Japan, South Korea, North Korea and Mongolia from 1990 to 2019, to discuss the potential causes of the disparities. Methods Data were obtained from the Global Burden of Disease Study 2019. The annual percent change (APC) and average annual percent change (AAPC) were calculated by Joinpoint analysis, and the independent age, period and cohort effects were estimated by age-period-cohort analysis. Results In 2019, the highest incidence (7.70 per 100,000) and prevalence (51.09 per 100,000) rates of bladder cancer were in Japan, while the highest mortality (2.31 per 100,000) and DALY rates (41.88 per 100,000) were in South Korea and China, respectively. From 1990 to 2019, the age-standardized incidence and prevalence rates increased in China, Japan and South Korea (AAPC > 0) and decreased in Mongolia (AAPC < 0), while mortality and DALY rates decreased in all five countries (AAPC < 0). Age effects showed increasing trends for incidence, mortality and DALY rates, while the prevalence rates increased first and then decreased in older groups. The cohort effects showed downward trends from 1914–1918 to 2004–2008. Smoking was the greatest contributor and males had the higher burden than females. Conclusion Bladder cancer was still a major public health problem in East Asia. Male and older population suffered from higher risk, and smoking played an important role. It is recommended that more efficient preventions and interventions should be operated among high-risk populations, thereby reduce bladder cancer burden in East Asia.

The 2019 coronavirus disease (COVID-19) outbreak caused by the SARS-CoV-2 virus is an ongoing global health emergency. However, the virus’ pathogenesis remains unclear, and there is no cure for the disease. We investigated the dynamic changes of blood immune response in patients with COVID-19 at different stages by using 5’ gene expression, T cell receptor (TCR), and B cell receptors (BCR) V(D)J transcriptome analysis at a single-cell resolution. We obtained single-cell mRNA sequencing (scRNA-seq) data of 341,420 peripheral blood mononuclear cells (PBMCs) and 185,430 clonotypic T cells and 28,802 clonotypic B cells from 25 samples of 16 patients with COVID-19 for dynamic studies. In addition, we used three control samples. We found expansion of dendritic cells (DCs), CD14+ monocytes, and megakaryocytes progenitor cells (MP)/platelets and a reduction of naïve CD4+ T lymphocytes in patients with COVID-19, along with a significant decrease of CD8+ T lymphocytes, and natural killer cells (NKs) in patients in critical condition. The type I interferon (IFN-I), mitogen-activated protein kinase (MAPK), and ferroptosis pathways were activated while the disease was active, and recovered gradually after patient conditions improved. Consistent with this finding, the mRNA level of IFN-I signal-induced gene IFI27 was significantly increased in patients with COVID-19 compared with that of the controls in a validation cohort that included 38 patients and 35 controls. The concentration of interferon-α (IFN-α) in the serum of patients with COVID-19 increased significantly compared with that of the controls in an additional cohort of 215 patients with COVID-19 and 106 controls, further suggesting the important role of the IFN-I pathway in the immune response of COVID-19. TCR and BCR sequences analyses indicated that patients with COVID-19 developed specific immune responses against SARS-CoV-2 antigens. Our study reveals a dynamic landscape of human blood immune responses to SARS-CoV-2 infection, providing clues for therapeutic potentials in treating COVID-19.

Indoor 3D point cloud semantic segmentation is a fundamental task for fine-grained scene understanding and intelligent perception. Due to the prohibitive cost of dense point-wise annotations, weakly supervised learning has emerged as a promising alternative for indoor point cloud segmentation. However, existing weakly supervised methods commonly rely on fixed confidence thresholds for pseudo-label selection, which exhibit limited generalization caused by threshold sensitivity, underutilization of informative low-confidence regions, and progressive noise accumulation during self-training. To address these issues, we propose TGR-T, a weakly supervised framework for indoor 3D point cloud semantic segmentation that incorporates truncated-Gaussian-weighted reliability with adaptive dynamic thresholding. Specifically, a reliability-adaptive dynamic thresholding strategy is introduced to guide pseudo-label selection based on the evolving confidence statistics of unlabeled mini-batches, with exponential moving average smoothing employed to produce stable global estimates and robust separation of reliable and ambiguous regions. To further exploit uncertain regions, a learnable truncated Gaussian weighting function is designed to explicitly model prediction uncertainty within the ambiguous set, providing soft supervision by assigning adaptive weights to low-confidence predictions during optimization. Extensive experimental results demonstrate that the proposed framework significantly enhances the exploitation of unlabeled data under extremely limited supervision: extensive experiments conducted on standard indoor 3D scene benchmarks demonstrate that TGR-T achieves competitive or superior segmentation performance under extremely sparse supervision and can even outperform several fully supervised baselines trained with dense annotations while using only 1% labeled points, thereby substantially narrowing the performance gap between weakly supervised and fully supervised 3D semantic segmentation methods.

Infectious diseases present persistent and complex challenges to global public health, with conventional antibiotic therapies increasingly limited by antimicrobial resistance, microbiota disruption, and adverse effects. There is a critical need to explore complementary strategies that augment host defense mechanisms without exacerbating these limitations. Accumulating evidence underscores the integral role of the gut microbiota—a diverse microbial ecosystem within the gastrointestinal tract—in regulating systemic immunity and pathogen susceptibility. This review synthesizes recent advances from animal models to delineate the multi-faceted mechanisms by which commensal microbes and their metabolites confer protection against enteric and respiratory infections. Key processes include competitive exclusion for nutrients and ecological niches, production of antimicrobial compounds, reinforcement of intestinal barrier integrity, and orchestration of local and systemic immunity via gut–lung axes. We further discuss the potential of microbiota-targeted interventions to enhance treatment efficacy and patient outcomes. By integrating mechanistic insights with translational applications, this review aims to inform the rational design of next-generation anti-infective strategies grounded in microbial ecology and host immunobiology.

Background Long non-coding RNA 01116 (linc01116) has been shown to be dysregulated in many tumors, and is closely related to the prognosis. This meta-analysis aimed to examine the correlation between linc01116 expression and cancer prognosis. Methods Six electronic databases were searched, and eligible studies were screened based on the inclusion and exclusion criteria. Data including hazard ratios (HRs) and 95% confidence intervals (CIs), TNM stage, distant metastasis (DM) status, lymph node metastasis (LNM) status, and tumor size were extracted from the included studies. HRs and odds ratios (ORs) with their corresponding 95% CIs were separately pooled to assess the relationship between linc01116 expression and cancer prognosis. Sensitivity analysis and Begg’s test were performed to assess publication or other biases. Results A total of 12 studies involving 809 patients were included in this meta-analysis. Analysis of pooled HRs with 95% CIs showed that high linc01116 expression was significantly correlated with poor overall survival (OS) (HR = 2.096; 95% CI: 1.555–2.638), progression-free survival (PFS) (HR, 1.9314; 95% CI: 1.020–3.657), disease-free survival (DFS) (HR = 2.067; 95% CI: 1.0889–3.9238), an advanced TNM stage (OR, 1.803; 95% CI: 1.270–2.562), and a poor histological grade (OR, 1.968; 95% CI: 1.288–3.007). However, no significant correlation was observed between linc01116 expression and LNM (OR, 1.198; 95% CI: 0.831–1.728), DM (OR, 1.114; 95% CI: 0.757–1.638), tumor size (OR, 1.336; 95% CI: 0.989–1.804), depth of invasion (OR, 1.375; 95% CI: 0.756–2.501), age (OR, 0.976; 95% CI: 0.742–1.283), or sex (OR, 0.810; 95% CI: 0.599–1.094). Sensitivity analysis indicated that the overall results of OS analysis were reliable and robust. In addition, Begg’s test showed that none of the included studies had significant publication bias. Conclusion linc01116 is upregulated in most cancers, and this upregulation is associated with a poor prognosis. Therefore, linc01116 serves as a promising therapeutic target and prognostic biomarker for cancer.

Galanin, a neuropeptide, regulates immune and inflammatory responses via GALR1-3. GALRs have emerged as potential therapeutic targets for inflammatory bowel disease (IBD), yet their mechanistic roles remain unclear. Based on evolutionary analysis, we identified a long galanin isoform (GAL53), generated by alternative splicing in non-mammalian vertebrates. Here we show that the chicken ortholog cGAL53 is robustly expressed in colonic tissue but downregulated upon dextran sulfate sodium (DSS)-induced colitis. Administration of cGAL53 alleviates colitis-associated weight loss, colon shortening, bleeding, and inflammation in both chickens and mice. These effects are abolished in Galr2 -deficient mice, highlighting receptor dependency. Moreover, epithelial cell-specific Arrb2 and Gnaq knockout models demonstrate that cGAL53 protects the gut barrier and reduces inflammation by activating β-arrestin2-biased GALR2 signaling. Our findings reveal a naturally occurring long galanin peptide with potent anti-inflammatory activity and propose evolutionary medicine-guided biased GALR2 agonism as a therapeutic strategy for IBD. GALRs, receptors for the neuropeptide galanin, have emerged as potential therapeutic targets for inflammatory bowel disease. Here the authors report that GAL53, a long galanin peptide derived from non-mammalian vertebrates, alleviates induced colitis in preclinical models by engaging GALR2 and activating the β-arrestin2-biased signalling pathway.