Hainan General Hospital

The authors declare no conflicts of interest. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/dom.70595. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. TABLE S1. Baseline characteristics. Table S2. Liner regression of aerobic exercise against ∆PFC, ∆LFC, ∆VAT, ∆SAT and metabolic outcomes (n = 86). Table S3. Mediation analysis of exercise-induced ectopic fat content changes on HOMA2-β improvement among individuals with type 2 diabetes. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease characterized by persistent mucosal inflammation and epithelial barrier disruption. Emerging evidence suggests that metabolic reprogramming plays a pivotal role in regulating immune responses and epithelial homeostasis in UC. However, the key metabolic-immune regulatory genes and their cellular mechanisms remain poorly defined. We integrated publicly available genome-wide association study (GWAS) summary statistics for UC (n = 394,626), along with expression quantitative trait loci (eQTL) resources and multiple independent bulk transcriptomic datasets (total n = 215 cases and 134 controls). Summary-based Mendelian randomization (SMR), genome-wide Mendelian randomization (MR), and transcriptomic analyses were performed to systematically identify causal genes associated with UC. Cross-validation was conducted using immune infiltration analyses and single-cell RNA sequencing (scRNA-seq) datasets from human UC colonic tissues (n = 18 cases and 12 controls), as well as a dextran sulfate sodium (DSS)-induced murine colitis model. Gene set enrichment and network analyses were applied to explore potential metabolic and immune pathways. Through integrative multi-omics analysis, we identified ACO2, KLF5, IMP4, and AGPS as key hub genes linking mitochondrial metabolism with immune regulation in UC. Among them, ACO2, KLF5, and IMP4 were consistently downregulated in UC tissues and negatively correlated with macrophage and dendritic cell infiltration. Although AGPS did not show consistent transcriptional changes across UC datasets, it may still contribute to lipid remodeling based on its metabolic function. Single-cell analyses revealed that ACO2 and KLF5 were primarily expressed in macrophage populations and markedly reduced in inflamed colonic regions, while IMP4 exhibited context- and cell-type-specific dynamics. In the DSS mouse model, Aco2 and Klf5 expression decreased progressively with disease severity, accompanied by metabolic pathway enrichment in oxidative phosphorylation and glycolysis. Our findings reveal a set of metabolic-immune regulatory genes that orchestrate mitochondrial function, epithelial integrity, and immune activation in UC. The integration of genetic, transcriptomic, and single-cell data highlights ACO2, KLF5, and IMP4 as promising biomarkers and potential therapeutic targets, offering novel insights into the immunometabolism mechanisms driving UC pathogenesis.

Patients with peripheral T cell lymphoma (PTCL) who achieved tumor response with first-line standard therapy were at high risk of disease relapse. We explored golidocitinib (150 mg once daily) as maintenance therapy for this group of patients (JACKPOT26, NCT06511869). This study included two cohorts: patients achieving a complete response (Cohort 1 (CR), N = 30) and a partial response (Cohort 2 (PR), N = 18) during induction stage. All enrolled patients were transplant ineligible or did not have a transplant plan. All dosed patients were included in the efficacy and safety analysis. In Cohort 1, the 24-month disease free survival (DFS) rate was 74.2% with golidocitinib treatment. In nodal subtypes (AITL, NOS, ALK- ALCL), the 24-month DFS rate was 62.7%. In Cohort 2, median progression free survival (PFS) was 17.4 months, and 24-month PFS rate was 48.6%. Nine out of 18 patients with initial PR achieved complete response, leading to a complete response rate of 50.0%, and median duration of response of 23.9 months. The most common ≥grade 3 treatment-related treatment-emergent adverse events (TRAEs) were hematological adverse events in nature, including neutrophil count decreased (47.9%), white blood cell count decreased (31.3%), lymphocyte count decreased (14.6%) and leukopenia (12.5%). The majority of these TRAEs were reversible and clinically manageable. TRAEs leading to treatment interruption and discontinuation occurred in 60.4% and 10% of patients, respectively. No TRAEs leading to fatal outcomes were reported. This study suggests the potential of golidocitinib as maintenance therapy for patients with PTCL.

Renal interstitial fibrosis (RIF) is the cardinal pathological hallmark of chronic kidney disease (CKD). Although the stem-cell factor (SCF)/c-kit axis has been implicated in kidney fibrogenesis, its cell-specific role and downstream mechanism in tubular epithelial cells (TECs) remain undefined. We investigated whether TEC-derived SCF/c-kit signaling propels RIF after unilateral ureteral obstruction (UUO) via Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells (NF-κB) activation. Using the Cre-loxP system, a renal tubular epithelial cell-specific c-kit gene knockout mouse model (Ggt1-Cre c-kit−/−) was established. Renal interstitial fibrosis was induced in both C57BL/6J (WT) and Ggt1-Cre c-kit−/− mice via UUO surgery. The extent of fibrosis was evaluated by assessing renal function indicators (serum creatinine and blood urea nitrogen), renal histopathology (PAS and Sirius red staining), and the expression of fibrosis markers (α-SMA, Vimentin, and Collagen I). Western blot and immunofluorescence techniques were employed to detect the expression of fibrosis markers, key proteins of the NF-κB pathway (p-p65, p65, p-IκBα, and IκBα), and inflammatory cytokines (Interleukin (IL)-6 and IL-1β). Primary renal tubular epithelial cells were isolated and cultured ex vivo, and treated with SCF and the NF-κB-specific inhibitor SC-75741 to evaluate the degree of cellular fibrosis and the activation status of the NF-κB pathway. Fourteen days after UUO, renal SCF and c-kit expression paralleled the rise in fibrotic markers. TEC‑specific deletion of c‑kit ameliorates the initial decline in renal function, attenuates tubular injury, reduces collagen deposition, and downregulates the expression of fibrotic proteins. Genetic deletion of c-kit significantly inhibits NF-κB phosphorylation and the expression of inflammatory cytokines IL-6 and IL-1β. In vitro, SCF provoked a fibrogenic phenotype in WT TECs that was abolished by either c-kit deletion or SC-75741. The SCF/c-kit signaling pathway in TECs promotes renal interstitial fibrosis in UUO mice via activation of the NF-κB pathway. Targeted inhibition of c-kit in TECs alleviates inflammatory responses and fibrosis, improves renal function, and may offer a novel therapeutic target for delaying the progression of CKD.

Pneumatosis cystoides intestinalis (PCI) poses a diagnostic challenge by radiographically mimicking surgical emergencies like perforation. This case highlights that while PCI itself may be benign, the decision for exploration must weigh the risk of missing a life-threatening condition or a coincident malignancy.

Background: This meta-analysis aimed to comprehensively assess the relationship between serum vascular endothelial growth factor (VEGF) levels and the prognosis of ovarian cancer. Recently, VEGF has been widely recognized as an important biomarker in tumorigenesis and development. Thus, this study aimed to clarify this association to provide evidence for clinical practice. Methods: A comprehensive literature search was conducted in PubMed, Wiley Library, Web of Science, Wanfang, VIP, and China National Knowledge Infrastructure (CNKI) databases from inception to June 30, 2024. A total of 2767 records were initially identified and screened; 9 studies met the inclusion criteria and were included in the meta-analysis. Data were analyzed using RevMan 5.3 and R 4.4.2 software. The quality of the included studies was assessed according to predetermined criteria. Results: This meta-analysis revealed that serum VEGF levels were significantly higher in ovarian cancer patients than in the normal control group (mean difference [MD] = 210.00; 95% confidence interval [CI]: 96.92–323.09). In addition, serum levels of VEGF were significantly higher in patients with advanced ovarian cancer compared with those with early-stage ovarian cancer (MD = –173.88, 95% CI: –290.28 to –57.49). Analysis of serum VEGF levels before and after surgical treatment showed a significant decrease after surgery (MD = 242.92, 95% CI: 154.66–331.17). Prognostic analysis showed a significant association between serum VEGF levels and overall survival (OS) (hazard ratio (HR) = 2.48, 95% CI: 1.84–3.34). However, the association with disease-free survival (DFS) was not statistically significant (HR = 1.29, 95% CI: 0.87–1.93). Conclusion: This meta-analysis demonstrates that elevated serum VEGF levels are associated with ovarian cancer progression and reduced overall survival. Although no significant association with DFS was found, serum VEGF levels remain a potential predictive biomarker worthy of further investigation. Future large-scale prospective studies are needed to confirm the clinical utility of serum VEGF in the management of ovarian cancer. Registration: The study has been registered on https://www.crd.york.ac.uk/prospero/ (registration number: CRD420251090777; registration link: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251090777).

Adding daratumumab to initial therapy in randomized controlled trials (RCTs) for newly diagnosed multiple myeloma (MM) enhances deep remission and prolongs progression-free survival (PFS). Given the differences between trial-eligible and real-world patients, and healthcare access variability in developing countries, real-world data are essential to complement RCT evidence. We analyzed 761 newly diagnosed MM patients treated with (n = 177) or without (n = 584) daratumumab as first-line therapy from 2017 to 2023 across southern China. Propensity score matching (PSM) generated cohorts of 158 and 278 patients, respectively, matched for stage, cytogenetic abnormalities, and regimen type. Responses were evaluated per International Myeloma Working Group criteria, and measurable residual disease (MRD) was assessed via next-generation multiparameter flow cytometry. The daratumumab group demonstrated significantly higher rates of ≥ very good partial response (85.0% vs. 61.3%; P < 0.001) and MRD negativity (73.0% vs. 51.9%; P = 0.024) at the end of induction. Additionally, 3-year PFS (75.6% vs. 55.0%, hazard ratio [HR] 0.49, 95% confidence interval [95% CI] 0.36-0.66, P < 0.001) and overall survival (OS) rates (78.3% vs. 74.4%; HR 0.56 [95% CI 0.36-0.86], P = 0.008) were superior in the daratumumab group, and these results remained consistent after PSM. Daratumumab improved PFS in patients with gain/amp(1q21) but not in those with del17p or t(4;14). Survival benefit was also observed in the addition of daratumumab to bortezomib/lenalidomide/dexamethasone combined treatment subgroup. In real-world settings, daratumumab-based first-line therapy improved the depth of response, PFS, and OS, though not all patients benefited.

Early and accurate diagnosis of mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease (AD), is critical for timely intervention and management. Nevertheless, effectively integrating heterogeneous multi-modal data for AD diagnosis remains worthy of further investigation. Therefore, we propose a supervised contrastive learning framework that integrates single nucleotide polymorphisms (SNPs), plasma proteomics, and T1-weighted structural magnetic resonance imaging (sMRI) from a biologically informed perspective, with SNPs influencing protein structure or gene expression levels, ultimately altering brain structure. Through a supervised contrastive learning mechanism, we construct a cross-modal feature space and introduce a similarity-based symmetrical attention mechanism to capture intermodal interactions and mitigate modality heterogeneity. We validate the proposed method on the Alzheimer's Disease Neuroimaging Initiative dataset, and experimental results demonstrate accuracy of 96.1%, 86.2%, and 86.1% for the AD-NC task, MCI-NC task, and AD-MCI task. In addition, the application of explainable methods to our model identified multi-modal biomarkers related to AD diagnosis. The experimental results validate the effectiveness of our model in the diagnosis of AD and MCI.