Biomarkers in medicine最新文献

Objective: This study aimed to extract radiomics (Rad) and deep learning (DL) features from preoperative CT of patients with Non-Muscle Invasive Bladder Cancer (NMIBC) and develop models incorporating clinical characteristics to assess Human-Epidermal-Growth-Factor-Receptor-2 (HER2) expression status and prognosis in these patients.

Methods: From January 2019 to December 2024, 181 patients with NMIBC were retrospectively enrolled in this study. A deep learning radio-clinical signature model (DLCS) was created by integrating DL score, Rad score, and clinicopathologic features to predict HER2 expression in NMIBC and compared with a deep learning model, a radiomic model, and a Clinical model. An additional model was built to predict Recurrence-Free Survival (RFS) in NMIBC patients.

Results: 181 patients with NMIBC were divided into a training cohort (n = 126) and a test cohort (n = 55). The DLCS model achieved the highest area under the curve (AUC) for HER2 prediction in the test cohort (AUC = 0.894 (95% CI: 0.814-0.974)). The univariate and multivariate Cox regression analyses identified both the DL score and Rad score as independent risk factors for RFS (p < 0.05).

Conclusion: The DLCS model demonstrates good diagnostic performance in predicting HER2 expression, and the prognosis model can stratify the risk of tumor recurrence in patients with NMIBC.

Aims: This study tends to identify serum biomarkers for early diagnosis of treatment-resistant schizophrenia (TRS) and prediction of clozapine treatment response, given the heterogeneity of schizophrenia and limitations of antipsychotic treatment.

Patients & methods: Participants of this prospective cohort study (recruited at Shanghai Mental Health Center; 2020-2023) included 42 TRS patients (TRRIP criteria), 42 first-line antipsychotic responders (age/sex-matched 1:1 to TRS), and 70 age/sex-matched healthy controls. TRS patients were stratified post-clozapine into responders (TRS-R, n = 26) and ultra-treatment-resistant (UTRS, n = 16) subgroups. Symptom severity was assessed using PANSS. Serum neuregulin-1 (NRG-1) levels were quantified via ELISA.

Results: Healthy controls showed significantly higher NRG-1 levels than schizophrenia patients (F = 39.76, p < 0.001). TRS patients had lower NRG-1 than treatment responders (p < 0.001). Clozapine responders (TRS-R) exhibited increased NRG-1 post-treatment (t = -3.32, p < 0.001), unlike UTRS patients (t = -0.332, p = 0.745). NRG-1 negatively correlated with symptom severity in both TRS (r = -0.647, p < 0.001) and responders (r = -0.596, p < 0.001). NRG-1 demonstrated diagnostic utility for TRS (AUC = 0.827, 95% CI:0.741-0.914; specificity = 0.786, sensitivity = 0.786).

Conclusion: Serum NRG-1 shows significant promise as a potential biomarker for diagnosing TRS and monitoring clozapine treatment response, suggesting involvement in TRS pathophysiology.

Background: Postoperative recurrence remains a significant challenge in renal cell carcinoma (RCC). While circulating tumor cells (CTCs) have emerged as promising prognostic biomarkers, the predictive value of their subtypes (epithelial, hybrid, mesenchymal) and their dynamic changes over time for postoperative recurrence is not yet fully understood. This study aimed to analyze CTCs characteristics and develop a prognostic model for recurrence prediction.

Methods: We included 124 patients after RCC resection, collecting serial peripheral blood samples at regular intervals post-surgery to quantify CTCs subtypes using standardized enrichment and identification protocols. We extracted 54 variables, comprising 45 CTC characteristics and 9 clinical/pathological factors. Seven machine learning algorithms were trained to predict recurrence based on these features, with the SHAP (SHapley Additive exPlanations) framework applied to interpret the model.

Results: Over a median follow-up of 41 months, 24 patients experienced recurrence, while 100 remained recurrence-free. The Random Forest model demonstrated superior performance, achieving a training AUC of 0.84 and a validation AUC of 0.77. SHAP analysis identified key predictors, including pT stage, tumor size, and changes in mesenchymal and hybrid CTC counts.

Background: Neurotensin (NTS) is a critical neuropeptide involved in multiple pathways in the central nervous and peripheral systems. We assessed the possible functional relevance of NTS in SCZ pathogenesis by focusing on the rs139226362 (delGATT) located in the 3' untranslated region (UTR) of the NTS.

Methods: A total of 88 Turkish individuals with known genotypes for the delGATT allele were included in the study. Differences in NTS mRNA expression and circulating NTS protein levels were evaluated by RT-qPCR and ELISA, respectively. The stability of RNA secondary structures and the binding patterns of RNA-binding protein (RBPs) interactions were evaluated by in silico analysis.

Results: Plasma NTS protein levels were significantly higher (p = 0.0003) in SCZ patients carrying the delGATT variant compared to those with wild-type genotype. This genotype-protein association was not observed in healthy controls, indicating a disease-specific effect. Moreover, plasma NTS levels were correlated with PANSS scores (r = -0.290, p = 0.041) and BMI (r = 0.306, p = 0.031) in SCZ patients.

Conclusions: These findings suggest that rs139226362 may influence post-transcriptional regulation, with the indel potentially associated with milder SCZ symptoms through altered molecular pathways. Further validation in experimental models may support the development of NTS-based personalized treatment strategies for SCZ management.

Inflammatory biomarkers are increasingly recognized as key tools in diagnosing, stratifying risk, and monitoring treatment in pericarditis, though their value is limited by non-specificity, variability, and treatment interactions. This narrative review integrates current evidence and recommendations from recent studies, as well as the 2025 ESC and ACC guidelines, focusing on conventional and emerging biomarkers across acute, recurrent, and chronic pericarditis. C-reactive protein remains the most practical biomarker for diagnosis and therapeutic monitoring, with persistent elevation linked to recurrence. Troponin identifies myocardial involvement, guiding follow-up but not adversely affecting outcomes in idiopathic cases. Erythrocyte sedimentation rate and white blood cell count add supportive yet nonspecific information. Exploratory markers - such as interleukins, soluble urokinase plasminogen activator receptor, microRNAs, and hematologic indices - show potential for refined risk prediction but remain investigational due to limited access and a lack of standardization. Imaging, particularly cardiac magnetic resonance, complements biomarker data and is particularly crucial in cases where biomarkers are negative. Biomarkers are central yet imperfect components of pericarditis management. Their future utility will rely on integration with imaging, composite marker panels, and artificial intelligence-based analytics, promoting precision medicine while current practice remains grounded in combined clinical, laboratory, and imaging assessment.

Aims: The no-reflow (NR) phenomenon is a serious complication of primary percutaneous coronary intervention (PCI) in ST-elevation myocardial infarction (STEMI), often reflecting distal embolization and microvascular obstruction, and representing a substrate for periprocedural (type 4a) myocardial infarction. NR has been linked to worse prognosis, including higher short- and long-term mortality. Inflammation is a key contributor to NR development. This study aimed to evaluate the relationship between the derived neutrophil-to-lymphocyte ratio (dNLR) and NR in STEMI patients undergoing PCI, and to assess its predictive value.

Methods: This retrospective, single-center observational study included consecutive STEMI patients undergoing primary PCI between May 2024 and May 2025. Patients were grouped based on post-procedural TIMI flow grade. Demographic, clinical, and laboratory parameters were compared. Regression and ROC analyses were performed.

Results: A total of 208 patients were analyzed, among whom no-reflow occurred in 26.4% (n = 55). The NR group had significantly higher dNLR, C-reactive protein (CRP), glucose, creatinine, and troponin levels, along with lower left ventricular ejection fraction (LVEF). dNLR, diabetes mellitus, CRP and LVEF were independent predictors of NR.

Conclusion: dNLR is a simple, cost-effective marker that may help identify patients at high risk of no-reflow in STEMI. Further prospective studies are warranted.

Aim: This study aimed to investigate the efficacy of long-acting growth hormone (GH) therapy at different doses in children with short stature and to explore its correlation with thyroid function indicators.

Patients & methods: A total of 192 children with short stature were enrolled and divided into three groups according to the treatment regimen. Group A received short-acting GH (daily injection), Group B received low-dose long-acting GH (weekly injection), and Group C received high-dose long-acting GH (weekly injection). Growth velocity (GV), serum bone formation markers (BAP, OC, NT-proCNP), metabolic indicators (FBG, IGF-1, IGF-1/BP3), thyroid hormones (TSH, FT3, FT4), adverse reactions, and treatment adherence were assessed at 3 and 6 months.

Results: After treatment, Groups B and C showed significantly greater GV, BAP, OC, NT-proCNP, and IGF-1 levels than Group A (p < 0.05). Group C exhibited the highest GV, bone metabolism markers, and IGF-1/IGF-1BP3 ratios among the three groups (p < 0.05). Treatment adherence in Groups B and C also exceeded that in Group (p < 0.05).

Conclusion: Long-acting GH demonstrates superior efficacy and compliance compared with short-acting GH in children with short stature, particularly at higher doses.

Cervical cancer remains a significant global health challenge, particularly in low-income regions, where incidence and fatality rates exceed WHO eradication limits. The miRNAs are emerging as crucial molecular markers in disease diagnostics and therapeutics. Their expression is influenced by Human Papillomavirus (HPV) infection leading to genomic instability and cervical carcinogenesis. The miRNA-based biomarkers exhibit potential for noninvasive identification in serum, urine, cervical mucus, exosomes, and tissue samples, and they also contribute to chemosensitization and resistance mechanisms. However, their clinical translation is hindered by multiple challenges. This review explores the mechanistic roles of miRNAs in HPV-mediated cervical cancer progression, their implications in diagnosis and therapy, and the barriers limiting their clinical application. Additionally, it outlines strategies to overcome translational hurdles, including combinatorial delivery, structural modifications, nanovehicles based delivery, viral vector systems, paving the way for miRNA-based interventions in cervical cancer management.