Clinical and Experimental Medicine最新文献

Whipple's disease is a sporadic infectious condition, with an incidence rate of approximately 1 per million individuals. The causative agent is the gram-positive bacterium Tropheryma whipplei. The disease manifests with a wide range of clinical symptoms, including non-specific presentations such as diarrhea, arthralgia, and fever, as well as the more pathognomonic lipodystrophy. This diversity in presentation poses a significant diagnostic challenge even for experienced clinicians. Our review aims to provide an updated overview encompassing the latest insights into Whipple's disease, focusing on epidemiology, pathophysiology, genetic predisposition, clinical manifestations, diagnosis, immune reconstitution inflammatory syndrome, and treatment. Herein, we have additionally explored many of the confounding factors in the diagnosis and management of Whipple's disease, including the variable presentations among patients colonized by Trophyrema whipplei as well as the limitations of current treatment options, and underscore the need for further research and guidelines related to this complex disease process.

Cutaneous melanoma is an aggressive skin cancer characterized by high rates of recurrence and mortality, especially in its advanced stages. Ferroptosis, a distinct form of programmed cell death, has emerged as a promising therapeutic strategy for cancer. Nevertheless, the regulatory mechanisms underlying ferroptosis in melanoma remain poorly defined. In this study, we aimed to elucidate the role of USP36, a deubiquitinating enzyme that removes ubiquitin from substrate proteins, in the ferroptosis of melanoma cells. Using A375 and SK-MEL-28 melanoma cells treated with the ferroptosis inducer erastin, we analyzed USP36 expression and evaluated its functional role through both overexpression and knockdown experiments. Co-immunoprecipitation and ubiquitination assays demonstrated that USP36 stabilizes APEX1 through the cleavage of its K48-linked ubiquitin chains. We further employed USP36-deficient xenograft models to assess tumor growth and ferroptosis sensitivity. Our results indicate that erastin downregulates USP36, whereas overexpression of USP36 suppresses ferroptosis. Importantly, knockdown of APEX1 abolished the anti-ferroptotic effect of USP36. In addition, USP36-deficient tumors exhibited reduced proliferation and enhanced ferroptosis. Collectively, these findings establish USP36 as an oncogene in melanoma that inhibits ferroptosis through stabilization of APEX1. Therefore, targeting the USP36-APEX1 axis may represent a novel therapeutic approach for melanoma treatment.

Personalized therapy in neuro-oncology has traditionally relied on molecular profiling. However, clinical benefit has been scarce to date. Recently, in vitro drug sensitivity testing using patient-derived models-such as organoids and cell lines-has emerged as a promising strategy. We systematically reviewed evidence on the efficacy of in vitro drug screening in predicting treatment outcome for brain tumors, including but not limited to glioblastoma. PRISMA guidelines were followed. Fifteen studies were included, comprising 300 patients overall. Cohort studies built the largest group; only one randomized clinical trial was found. In vitro assays, using patient-derived stem cells, standardized assays ad the ChemoID, or tumor-derived organoids, were able to reliably predict treatment outcome. However, the overall quality of evidence was limited. These models may overcome limitations of molecular profiling, especially in glioblastoma, where driver mutations are often lacking and the molecular profile evolves at recurrence. Although initial results are promising, further validation is needed before clinical implementation.

Inflammatory Bowel Disease (IBD), driven by mucosal barrier dysfunction and immune regulation disruption, is characterized by chronic gastrointestinal inflammation and frequent disease relapse. While traditional therapies focus on immune suppression, recent evidence identifies ferroptosis-an iron-dependent form of regulated cell death-as a critical driver of intestinal epithelial injury. Central to this process are microRNAs (miRNAs), which act as post-transcriptional "switches" regulating the three metabolic axes of ferroptosis: antioxidant defense (GPX4, System Xc-), iron trafficking, and lipid peroxidation. This review synthesizes emerging evidence on the miRNA-ferroptosis network in IBD. We highlight how specific dysregulated miRNAs, such as miR-129-5p and the IRF7/miR-375 axis, strip the epithelium of its defenses, promoting lethal lipid peroxidation. Furthermore, we examine the clinical transformation of these insights into novel therapies, including the oral small molecule ABX464 (obefazimod) and bioengineered exosome delivery systems. By moving beyond broad immunosuppression to targeted metabolic reprogramming, miRNA-based interventions offer a promising frontier for overcoming resistance to current biologic therapies and achieving deep mucosal healing in IBD.

Alternative splicing (AS) plays critical roles in acute myeloid leukemia (AML), but the prognostic values of AS events are rarely studied. In this study, we performed comprehensive analysis in AS events of 126 AML patients from the Cancer Genome Altas (TCGA) database by using the TCGA Splice Seqdataset. Univariate Cox analysis was performed to identify prognosis-associated (PA) AS events. Then LASSO regression analysis was conducted to obtain appropriate PAAS events and multivariate Cox analysis was used to build the risk models of all PAAS events and seven individual PAAS events, which were verified by Kaplan-Meier plot and AUC curve. Later, the correlation between PAAS and splicing factors (SFs) was analyzed by Spearman's correlation analysis. Gene function analysis was used to explore the role of SFs in AML development. A total of 1,847 AS events were related to overall survival of AML patients. All risk score models that were constructed based on prognosis-associated (PA) AS events of different AS types showed superior accuracy in predicting 5-year survival, especially the model of alternative acceptor (one subtype of AS) with an area under the receiver operating characteristic (ROC) curve of 0.953. And the risk score turned out to be an independent prognostic factor in AML. Fifty-five differentially expressed splicing factors (SFs) were found and four (JUN, YBX3, HSPA1B and RNU5A-1) were correlated with PAASs as regulators. And YBX3 was considered the core SF as its prognostic value in patients with AML. Function prediction suggested YBX3 played key roles in AML differentiation. Notably, 75.7% of prognostic AS events showed differential splicing between AML and normal controls, supporting their biological relevance. Our findings revealed that AS events were excellent outcome predictors for AML patients and they provided clues of potential mechanisms and therapeutic targets of AML.

Neuropsychiatric systemic lupus erythematosus (NPSLE) remains challenging to diagnose because of heterogeneous clinical presentations, nonspecific findings, and the absence of definitive biomarkers. Artificial intelligence (AI) methods have been increasingly explored using neuroimaging and other biologically informative data to support identification of neuropsychiatric involvement in systemic lupus erythematosus (SLE). However, the reported performance and methodological robustness of these approaches have not been systematically characterized. To perform an exploratory meta-analysis describing reported diagnostic performance, heterogeneity, and methodological characteristics of AI-based models using neuroimaging and multimodal biomarkers for detecting neuropsychiatric involvement in SLE. We conducted a PRISMA-compliant systematic review of studies applying machine learning or deep learning models to neuroimaging or biologically informative modalities relevant to central nervous system involvement, including structural or functional MRI, magnetic resonance spectroscopy, spectroscopy-based molecular fingerprints, and CSF or serum biomarkers. PubMed, Scopus, and Web of Science were searched through August 2025. Given substantial heterogeneity in study design, model objectives, input modalities, and validation strategies, analyses were undertaken within an exploratory framework. Random-effects models were used to summarize reported area under the curve (AUC), accuracy, sensitivity, and specificity. Subgroup and leave-one-out sensitivity analyses were performed. Fourteen studies involving more than 800 participants were included. Most studies used neuroimaging, particularly resting-state functional MRI, while others incorporated non-imaging biomarkers. Reported performance metrics were generally high (pooled AUC 0.86; accuracy 0.87), but between-study heterogeneity was substantial. Sensitivity analyses demonstrated that pooled estimates were unstable and influenced by individual studies. No clear performance differences were observed between classical machine learning and deep learning approaches. External validation and formal explainable AI methods were uncommon. This exploratory synthesis indicates that AI-based models applied to neuroimaging and multimodal biomarkers have shown promising reported performance in NPSLE. However, marked heterogeneity, limited robustness, and poor interpretability currently preclude firm conclusions regarding clinical applicability. More standardized, externally validated, and interpretable studies are needed before translation into clinical practice.

Colorectal cancer remains a major global health burden, and treatment outcomes for advanced disease are still unsatisfactory. APG-115 is a next-generation small-molecule MDM2 inhibitor developed in China that restores wild-type p53 activity. However, its therapeutic potential in colorectal cancer has not been fully explored. APG-115's impact on colorectal cancer cells was evaluated through CCK-8 assays and AnnexinV-FITC/PI staining. The dependence of APG-115 activity on p53 status was assessed in p53-knockdown cell lines. In vivo, the antitumor efficacy and radiosensitizing effects of APG-115 were evaluated in nude-mouse xenograft models. APG-115 exerted a potent inhibitory effect on the proliferation of p53 wild-type colorectal cancer cell lines LOVO, RKO, and HCT116, while showed no significant impact on p53-mutant lines. In wild-type cells, APG-115 induced apoptosis in a dose-dependent manner and caused G0/G1 cell-cycle arrest. APG-115 significantly upregulated p53 and its downstream targets (MDM2, p21, PUMA), whereas these effects were absent in p53-mutant or p53-knockdown cells. In vivo, APG-115 suppressed RKO tumor growth in a dose-dependent manner, accompanied by increased p53, MDM2 and p21 expression and reduced Ki-67. Immunofluorescence further confirmed enhanced apoptosis following treatment. Importantly, the combination of APG-115 with radiotherapy significantly promoted apoptosis, decreased the S-phase proportion, and increased G2-phase arrest in p53 wild-type cells. Radiosensitization was abolished in p53-knockout RKO xenografts, confirming the requirement of an intact MDM2-p53 pathway. APG-115 effectively inhibits proliferation, induces apoptosis, and enhances radiosensitivity in p53 wild-type colorectal cancer. These findings support APG-115 as a promising therapeutic candidate for colorectal cancers retaining functional p53.

Metabolism Syndrome (MS) is strongly linked to tumorigenesis, yet its impact on gene mutations in hematologic tumors (HT) remains underexplored. This study aims to elucidate the effect of MS on HT gene mutations. Between 2021 and 2024, 229 HT patients were enrolled, including 113 with MS and 116 without. All patients underwent thorough clinical assessments and gene mutation analyses. Univariate and multivariate logistic regression were used to identify factors associated with HT gene mutations, while Spearman's correlation evaluated the ordinal relationship between HT and MS. HT patients with MS exhibited significantly higher gene mutation rates than those without MS (79.65% vs. 68.10%, p = 0.047). Multivariate logistic regression analysis revealed associations between HT gene mutations and age (OR = 1.058, 95%CI, 1.030-1.088, p < 0.001) and clinical stage (OR = 0.371, 95%CI, 0.145-0.949, p < 0.001). Subgroup analysis indicated that MS-comorbid HT patients under 60 years exhibited a notably higher mutation rate than their non-MS counterparts (72.22% vs. 50.00%, p = 0.036). Spearman's correlation analysis further confirmed a link between HT gene mutations and MS (R = - 0.131, p = 0.047). This real-world retrospective study suggests that MS may elevate gene mutation rates in HT patients, especially those under 60 years old. However, tumor gene mutations are likely influenced by multiple factors, warranting further research with a broader range of variables for a more comprehensive understanding.