Search Results (5,746)

Background: Peritonitis in peritoneal dialysis and cirrhosis remains common and leads to morbidity. Neutrophil gelatinase-associated lipocalin (NGAL) has been evaluated as a rapid adjunctive biomarker. Methods: Following PRISMA-DTA and PROSPERO registration (CRD420251105563), we searched MEDLINE, Embase, Cochrane Library, LILACS, Scopus, and Web of Science from inception to 31 December 2024, and ran an update on 30 June 2025 (no additional eligible studies). Diagnostic accuracy studies measuring NGAL in peritoneal/ascitic fluid against guideline reference standards were included. When 2 × 2 data were not reported, we reconstructed cell counts from published metrics using a prespecified, tolerance-bounded algorithm (two studies). Accuracy was synthesized with a bivariate random effects (Reitsma) model; 95% prediction intervals (PIs) were used to express heterogeneity; small-study effects were assessed by Deeks’ test. Results: Thirteen studies were included qualitatively and ten were entered into a meta-analysis (573 cases; 833 controls). The pooled sensitivity was 0.95 (95% CI, 0.90–0.97) and specificity was 0.86 (0.70–0.94); likelihood ratios were LR+ ≈7.0 and LR− 0.06. Between-study variability was concentrated on specificity: the PI for a new setting was 0.75–0.98 for sensitivity and 0.23–0.99 for specificity. Deeks’ test showed evidence of small-study effects in the primary analysis; assay/platform and thresholding contributed materially to heterogeneity. Conclusions: NGAL in peritoneal/ascitic fluid demonstrates high pooled sensitivity but variable specificity across settings. Given the wide prediction intervals and the signal for small-study effects, NGAL should be interpreted as an adjunct to guideline-based criteria—not as a stand-alone rule-out test. Standardization of pre-analytics and assay-specific, locally verified thresholds, together with prospective multicenter validations and impact/economic evaluations, are needed to define its clinical role. Full article

The identification of germline BRCA1/2 (BRCA) mutations plays an important role in the treatment planning of high-risk breast cancer patients, but genetic testing may be costly or unavailable. The multiparametric breast MRI (mpMRI) features offer noninvasive imaging biomarkers that could support BRCA mutation prediction. In this study, we investigate whether mpMRI features can predict BRCA mutation status in high-risk breast cancer patients. We collected data from 231 consecutive patients (82 BRCA-positive, 149 BRCA-negative) who underwent BRCA mutation testing and preoperative MRI between 2013 and 2019. We used the mpMRI features, including computer-aided diagnosis (CAD)-derived kinetic features, morphologic features, and apparent diffusion coefficient (ADC) values from diffusion-weighted imaging (DWI). In the univariate analysis, higher CAD-derived washout component and peak enhancement, larger tumor size and angio-volume, peritumoral edema on T2-weighted imaging, axillary adenopathy, and minimal or mild background parenchymal enhancement (BPE) were significantly associated with BRCA mutation, while ADC values showed no significant differences. In the multivariate analysis, three significant predictors were washout component ≥ 19.5% (odds ratio [OR] = 3.89, p < 0.001), minimal or mild BPE (OR = 2.57, p = 0.004), and tumor size ≥ 2.5 cm (OR = 2.41, p = 0.004). Using these predictors, we compared the predictive performance of 13 ML models through 30 repeated runs and achieved the highest performance (AUC = 0.72). In conclusion, ML models integrating mpMRI features demonstrated good performance for predicting BRCA mutations in high-risk patients. This noninvasive approach may aid personalized treatment planning and genetic counseling. Full article

Obsessive–compulsive disorder (OCD) is a heterogeneous mental illness characterized by a variety of clinical manifestations and underlying neurobiological mechanisms. Modern research highlights the importance of identifying subtypes of OCD—separate categories that are characterized by specific phenotypic manifestations. This review provides a systematic integration of multi-level biomarker data (genetic, neuroimaging, neuropsychological) specifically aligned with the most consistently replicated, symptom-based subtypes of OCD. Our findings demonstrate that distinct OCD subtypes are underpinned by divergent neurobiological pathways, involving dysregulation across glutamatergic, serotonergic, dopaminergic, and neurotrophic systems, as well as distinct patterns of brain region engagement. The most extensive body of evidence currently exists for the contamination/cleaning and symmetry/ordering OCD subtypes. In contrast, other subtypes require more rigorous investigation. The findings from this study can provide theoretical prerequisites for future experimental studies involving larger cohorts of OCD patients, who can then be classified based on their detected biomarkers and tested accordingly. Full article

Purpose: Preclinical studies suggest that interleukin-1β (IL-1β) influences tumor behavior in non-small cell lung cancer (NSCLC). While the CANTOS trial demonstrated reduced lung cancer incidence with IL-1β inhibition, the CANOPY trials failed to show survival benefit when combined with chemoimmunotherapy. The role of IL-1β in NSCLC with oncogenic mutations remains unclear. We evaluated the prognostic and predictive significance of IL-1β expression across NSCLC subtypes. Methods: We analyzed 21,698 NSCLC tumors profiled by Caris Life Sciences using DNA and RNA next-generation sequencing. IL-1β expression was stratified into quartiles (Q1: lowest 25%, Q4: highest 25%). Real-world overall survival (OS) and time on treatment (TOT) were obtained from insurance claims. Statistical comparisons used Chi-square, Fisher’s exact, or Mann–Whitney U tests. Survival outcomes were assessed with Cox models. Results: Across unselected NSCLC patients, low IL-1β expression (Q1) was associated with modestly longer OS versus high expression (Q4) (median OS 19.5 vs. 17.4 months; HR 0.94; p < 0.0001). This effect was more pronounced in EGFR-mutant adenocarcinoma (36.7 vs. 27.2 months; HR 0.76; p < 0.001) and ALK fusion-positive NSCLC (53.0 vs. 35.2 months; HR 0.62; p = 0.002). In NSCLC without targetable mutations, IL-1β expression was not prognostic. In KRAS-mutant adenocarcinoma, high IL-1β expression was associated with modestly longer TOT on immunotherapy (7.4 vs. 6.4 months; HR 1.15; p = 0.041), but not OS. High IL-1β expression correlated positively with TP53 mutation, TMB-high, and PD-L1 expression and inversely with EGFR, KRAS, BRAF, ERBB2, KEAP1, and STK11 mutations. Conclusions: IL-1β expression is a potential prognostic and predictive biomarker in NSCLC, associated with survival outcomes in defined molecular subsets. These findings suggest that IL-1β-targeted strategies may be particularly relevant in EGFR- or ALK-altered tumors. Full article

Background: Schizophrenia is a complex neuropsychiatric disorder whose pathophysiology may involve oxidative stress-induced neuronal damage and inflammation. We conducted a cross-species study to elucidate oxidative stress dysregulation in schizophrenia. Methods: We measured peripheral oxidative stress biomarkers (malondialdehyde [MDA], nitric oxide [NO], reduced glutathione [GSH], superoxide dismutase [SOD], catalase [CAT], advanced protein oxidation products [APOP]), and C-reactive protein (CRP) in antipsychotic-naïve schizophrenia patients and matched controls. We also assayed liver enzymes (ALP, ALT, AST) as indicators of systemic metabolic stress. In parallel, we re-analyzed published single-cell RNA-sequencing data from a Setd1a^+/–^ mouse model of schizophrenia, focusing on prefrontal cortex (PFC) cell types and oxidative stress-related gene expression. Results: Patients with schizophrenia showed markedly elevated MDA and NO (indicators of lipid and nitrosative stress) and significantly reduced antioxidant defenses (GSH, SOD, CAT) versus controls (p < 0.01 for all comparisons). Notably, urban patients exhibited higher oxidative stress biomarker levels than rural patients, implicating environmental contributions. Liver function tests revealed increased ALT, AST, and ALP in schizophrenia, suggesting hepatic/metabolic dysregulation. Single-cell analysis confirmed dysregulated redox pathways in the schizophrenia model; PFC neurons from Setd1a^+/–^ mice displayed significantly lower expression of key antioxidant genes (e.g., Gpx4, Nfe2l2) compared to wild-type, indicating impaired glutathione metabolism. Conclusions: Our integrative data identify convergent oxidative stress imbalances in schizophrenia across species. These findings advance a mechanistic understanding of schizophrenia as a disorder of redox dysregulation and inflammation. They also have translational implications as augmenting antioxidant defenses (for example, with N-acetylcysteine or vitamins C/E) could mitigate oxidative injury and neuroinflammation in schizophrenia, representing a promising adjunct to antipsychotic therapy. Full article

Dry Eye Disease (DED) is a complex, multifaceted ocular disease characterized by tear film instability and inflammation. It can sometimes be elusive to identify the type of DED in patients, given the overlapping symptoms with other conditions like allergies and the multitude of stimuli that might trigger DED onset. There is also difficulty due to limitations on the diagnostic testing available to clinicians, as poor reliability and a lack of standardization plague accurate diagnoses. Identified biomarkers can help identify DED pathophysiology and category, and these include molecular biomarkers like matrix metalloproteinase-9 (MMP-9), cytokines, lactotransferrin, and lacritin, as well as functional biomarkers such as tear osmolarity. Diagnostic tools, such as the InflammaDry and I-Pen Tear Osmolarity System, also now allow for point-of-care measurement of select biomarkers, including MMP-9 and osmolarity. Nonetheless, there remains a critical need for additional, reliable, and accurate diagnostic devices to better aid in the diagnosis and management of DED. This review uniquely combines a review on the current understanding of various biomarkers with an overview of the emerging technologies available to healthcare providers, aiding in better-informed diagnosis and treatment of DED. Full article

Global DNA methylation has been associated with numerous traits and conditions; however, its relationship with inflammation and oxidative stress biomarkers has not been fully elucidated. The objective of this study is to determine the correlation between inflammatory and oxidative stress markers with global DNA methylation after adjusting for personal, psychological, biochemical, anthropometric, and physiological variables in a non-representative sample of the Mexican population. An adult Mexican population was invited to participate and complete a questionnaire with personal and psychological variables. Additionally, anthropometric variables and blood pressure were measured in all the participants. Finally, general blood tests, global DNA methylation analysis, and measurements of inflammatory and oxidative stress markers were performed. A total of 157 participants were included, of which 83 (52.8%) were women, with a median age of 24 years and an age range of 18–58 years. In the comparison between sexes, men showed higher levels of global DNA methylation. In addition, men showed a higher number of correlations with this variable. The bivariate correlations showed low positive correlations of IL-8, IL-10, TNF-α, and 8-isoprostane with global DNA methylation in the total sample. In addition, BMI showed low negative and significant correlations with global DNA methylation in the total, women’s, and men’s samples, while blood pressure showed low negative correlations with global DNA methylation in the men’s sample. Men showed low negative correlations with personal and biochemical variables that were not found in the women’s group. In the multivariate analyses, the psychological variables (SOC-13 comprehensibility, perceived stress, and assertiveness) correlated negatively either in the total, or in men’s or women’s samples, and the daily intake of drugs correlated negatively with methylation in the women’s sample in the bivariate and multivariate analyses. In conclusion, global DNA methylation seems to be related to many variables, including the inflammatory and oxidative stress biomarkers, and this relationship is different in each sex. Full article

Background: Chronic kidney disease (CKD) is a progressive global health burden often diagnosed in late stages due to reliance on invasive and centralized blood and urine tests. Saliva, as a non-invasive diagnostic fluid, has emerged as a promising alternative for assessing renal function. This scoping review aims to evaluate the diagnostic accuracy of salivary biomarkers compared to traditional methods, and to explore the potential of emerging biosensing technologies for CKD detection and monitoring. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, Web of Science, and Cochrane Library up to 1 July 2025, following the PRISMA-ScR guidelines. Studies involving adult CKD patients and healthy controls that assessed the diagnostic performance of salivary biomarkers against validated reference standards (e.g., serum creatinine, eGFR) were included. A total of 29 eligible studies were selected after applying predefined inclusion and exclusion criteria. Results: Salivary creatinine and urea were the most frequently assessed biomarkers and demonstrated strong correlations with serum levels (AUCs up to 1.00; sensitivity and specificity frequently >85%). Several studies reported high diagnostic potential for novel salivary markers such as Trimethylamine N-oxide (TMAO), cystatin C, and amino acids. Technological innovations, including electrochemical biosensors and ATR-FTIR spectroscopy, showed promise for enhancing sensitivity and enabling point-of-care testing. However, heterogeneity in sampling protocols and limited data for early-stage CKD were notable limitations. Conclusions: Salivary diagnostics, supported by biosensor technologies, offer a feasible and non-invasive alternative for CKD screening and monitoring. Standardization, broader clinical validation, and integration into dental workflows are key to clinical implementation. Full article

Background/Objectives: KRAS mutations are among the most prevalent oncogenic drivers in non-small cell lung cancer (NSCLC), with their impact on survival influenced by co-mutations. SMARCA4 mutations are increasingly associated with poor prognosis and can be classified as class 1 or class 2 mutations. This study evaluates the prognostic implications of KRAS and SMARCA4 mutations, including their co-mutations and their impact on NSCLC patients by utilizing real-world evidence. Methods: A retrospective analysis was conducted using the AACR GENIE Biopharma Collaborative (BPC) NSCLC 2.0 dataset. NSCLC patients with KRAS mutations, SMARCA4 mutations, or KRAS/SMARCA4 co-mutations were identified. Survival outcomes were assessed using univariate and multivariate Cox proportional hazards models, incorporating key clinical variables such as sex, race, smoking history, and stage. Results: Among 659 NSCLC patients with KRAS or SMARCA4 mutations analyzed, KRAS mutations were the most prevalent (79%, n = 518). SMARCA4 mutations were identified in 14% of cases (n = 95) across two classes. Six percent (n = 41) with class 1 mutations and 8% (n = 54) with class 2. Neither SMARCA4 class was associated with worse survival outcomes compared to KRAS-mutated patients (p = 0.438 & 0.720). Patients harboring KRAS/SMARCA4 class 1 co-mutations (3%, n = 18) had significantly worse overall survival compared to those with KRAS mutations alone (hazard ratio [HR] = 3.23, p < 0.001). In contrast, KRAS/SMARCA4 class 2 co-mutations (4%, n = 28) did not significantly impact survival compared to KRAS-mutated patients (HR = 1.34, p = 0.205). Conclusions: KRAS/SMARCA4 class 1 co-mutations are associated with significantly worse overall survival compared to KRAS-mutated NSCLC patients. Our multivariate analysis demonstrates the critical need to incorporate routine next-generation sequencing (NGS) testing in managing NSCLC patients at the time of metastatic diagnosis, with particular emphasis on identifying SMARCA4 mutation class as a potential prognostic biomarker in those with KRAS co-mutations. Full article

Background: As the growing global population continues to age, the risk of chronic metabolic diseases, including cardiovascular disease, neurodegenerative disorders, type 2 diabetes mellitus, and fatty liver disease, increases considerably. Driven largely by lifestyle factors and metabolic dysfunction, this escalating health crisis is placing mounting pressure on healthcare systems and contributing to significant economic costs. Insulin resistance and hyperinsulinaemia are major drivers of these disorders, emphasising the need for early detection and intervention. Changes in liver enzymes, such as alanine aminotransferase (ALT) and gamma-glutamyl transferase (GGT), commonly assessed in routine laboratory testing, can serve as biomarkers of early-stage insulin resistance, offering a potentially underutilised window for intervention and disease prevention. Correspondingly, low-carbohydrate ketogenic diets have shown to be effective in reversing insulin resistance, metabolic disease, and liver disease. Objectives: We chose to explore the relationship between suppressing ketosis and changes in liver enzymes in the Ketosis Suppression and Ageing cohort. Methods: Ten lean (BMI 20.5 kg/m² ± 1.4), healthy young women (age 32.3 ± 8.9 years) who habitually followed a ketogenic diet maintaining nutritional ketosis (NK) for an average of 3.9 years (±2.3) were exposed to a higher carbohydrate diet, in line with standard healthy eating guidelines for a 21-day phase and then transitioned back to a ketogenic diet. Results: Carbohydrate challenge and suppression of ketosis increased insulin resistance score HOMA-IR by 2.13-fold (p = 0.0008), GKI by 22.28-fold (p = 0.0024), and liver markers ALT by 1.85-fold (p = 0.0010), GGT, 1.29-fold (p = 0.0087) and the ALT/AST, 1.30-fold (p = 0.0266), reflecting an adverse pattern suggestive of hepatic insulin resistance. Conclusions: These results support the clinical utility of liver markers as early and directional signs of hyperinsulinaemia. Full article

Background/Objectives: Despite advances in minimally invasive procedures, anastomotic leakages (ALs) after esophageal resections mark the most feared complication. Its early detection can lead to quick interventional treatment with improved survival. Nonetheless, early detection remains challenging, and scores are imprecise and complex. Methods: In our study we analyzed mediastinal drainage fluid to find parameters suggesting AL even before it became clinically evident and correlated them to routine biomarkers. All patients with AL after robotically assisted esophageal resections were included and matched 1:1 with uneventful controls. Additionally, transhiatal distal esophageal resections operated during this period were included. Drainage fluid was collected on postoperative days (PODs) 1–4 with consecutive blood gas analysis. Test quality was determined by the area under the curve (AUC) of the receiver operating characteristic curve (ROC). Results: In total, 40 patients were included, with 17 developing AL. There were no significant differences in gender, age, BMI or oncological treatment. The 30-day morbidity rate was 65.0%. The study was restricted to events in the first 12 days. While lactate value in drainage fluid differed significantly from POD 3 onwards in the two groups, serum CRP remained without significant differences. We developed the LacCRP score (CRP/30 + lactate/2). The AUC on POD 3 was 0.96, with a sensitivity and specificity of 100% and 75%, respectively. An estimator of 1.08 was found in multivariate analysis: one-point increase in the LacCRP score increases AL probability by 8%. Conclusions: This study demonstrates that postoperative lactate determinations in drainage fluid can predict AL after esophageal resection, and its combination with serum CRP results in a reliable LacCRP score. Full article

Elevated human epididymis protein 4 (HE4) levels decreased in patients with CF (pwCF) in response to CFTR-specific drugs and negatively correlated with FEV1% predicted values (ppFEV1). Objectives: Although elexacaftor/tezacaftor/ivacaftor (ETI, Kaftrio^®) demonstrates more substantial effectiveness than lumacaftor/ivacaftor (LUM/IVA, Orkambi^®) in pwCF, plasma biomarkers have not been used to compare treatment efficacy. Hence, our aim was to correlate the change in HE4 levels and the clinical effects of these CFTR modulators (CFTRm). Methods: Serum HE4 concentrations were measured in a total of 123 pwCF homozygous for the p.Phe508del-CFTR variant before treatment and 1–6 months after either ETI or LUM/IVA administration. A correlation between serum HE4 and ppFEV1 was assessed using the Spearman test. HE4 protein levels were also analyzed in the supernatants of p.Phe508del-CFTR CFBE 41o- cells before and after treatment with these CFTRm, and their direct effect on CFTR function was monitored by the whole-cell patch-clamp technique. Results: Serum HE4 levels were reduced below baseline after 3 months of either ETI or LUM/IVA (mean delta HE4: −38.5 vs. −18.5 pmol/L, respectively) when the mean change of ppFEV1 was 13.6 vs. 1.6% and remained decreased up to 6 months. A significant inverse correlation between HE4 and ppFEV1 was observed in both study cohorts (r = −0.537 and r = −0.575, respectively; p < 0.0001). In agreement with ex vivo results, the effect on p.Phe508del-CFTR was more pronounced by ETI than LUM/IVA in CFBE cells, showing a larger improvement in p.Phe508del-CFTR function and reductions in HE4 levels at 24 h. Conclusions: Serum HE4 negatively correlates with lung function improvement and monitors better drug efficacy in pwCF under ETI than LUM/IVA. Full article

Background/Objectives: Sepsis is a high-mortality syndrome characterized by organ dysfunction resulting from a dysregulated host response to infection. This study aimed to evaluate the potential of growth differentiation factor 15 (GDF15), a stress-inducible cytokine, as a biomarker in patients diagnosed with urosepsis. Methods: A total of 13 patients diagnosed with urosepsis, based on an increase of ≥2 points in the Sequential Organ Failure Assessment (SOFA) score and positive urine culture, were included in the study. Daily blood samples were collected from patients for 10 days, and serum levels of GDF15, procalcitonin (PCT), and presepsin (P-SEP) were measured by ELISA. C-reactive protein (CRP), blood urea nitrogen (BUN), serum creatinine, estimated glomerular filtration rate (eGFR), hemoglobin, and neutrophil, lymphocyte, and platelet counts were determined using autoanalyzers. Temporal changes were analyzed using the Friedman test, and correlations were analyzed using Spearman’s test. Results: GDF15 levels began to decrease from Day 3, with a significant decline observed from Day 7 compared to Day 1 (p < 0.001). Similar decreasing trends were observed in CRP and PCT levels, whereas presepsin levels did not exhibit significant changes. Significant positive correlations were identified between GDF15 and CRP (r = 0.65, p = 0.015), BUN (r = 0.57, p = 0.041), and creatinine (r = 0.62, p = 0.024), and a significant negative correlation was observed with eGFR (r = −0.62, p = 0.024). No significant correlation was found between GDF15 and presepsin (p > 0.05). Conclusions: GDF15 is a biomarker sensitive to the resolution phase of inflammation and organ dysfunction in sepsis, demonstrating significant temporal changes. It holds potential as an indicator for monitoring clinical progression and assessing prognosis. Full article

Background and Objectives: Diagnosing the underlying cause of ascites remains complex, especially when cytology results are inconclusive. Measuring biomarkers directly in ascitic fluid may offer better diagnostic insight than serum testing alone. This review evaluated the clinical utility of tumor and inflammatory markers in ascitic fluid. Materials and Methods: A systematic search was conducted in PubMed and Scopus for studies published from January 2014 to December 2024, with the final search carried out in May 2025. The included studies were observational, comparative or biomarker validation studies evaluating ascitic fluid markers for diagnosing malignant and inflammatory ascites. The extracted outcomes included diagnostic accuracy metrics such as area under the curve (AUC), sensitivity and specificity. Risk of bias was evaluated using the ROBINS-I tool. Studies were excluded if they were case reports, animal studies, cytology-only analyses, or if they lacked biomarker data in ascitic or peritoneal fluid. Results: Forty-two studies met the inclusion criteria. CEA showed high diagnostic performance when measured in ascitic fluid. Combining markers or using ascitic-to-serum ratios improved diagnostic reliability. Inflammatory markers in ascitic fluid, such as CRP, IL-6 and VEGF added diagnostic value when cytology was inconclusive. Discussion and Conclusions: Evaluating biomarkers in ascitic fluid improved diagnostic accuracy. However, the included studies showed considerable methodological heterogeneity and moderate risk of bias. Full article

Background/Objectives: This study aims to build an interpretable and accurate predictive model for myocardial infarction (MI) using Explainable Boosting Machines (EBM), a state-of-the-art Explainable Artificial Intelligence (XAI) technique. The objective is to identify and rank clinically relevant biomarkers that contribute to MI diagnosis while maintaining transparency to support clinical decision making. Methods: The dataset comprises 1319 patient records collected in 2018 from a cardiology center in the Erbil region of Iraq. Each record includes eight routinely measured clinical and biochemical features, such as troponin, CK-MB, and glucose levels, and a binary outcome variable indicating the presence or absence of MI. After preprocessing (e.g., one-hot encoding, normalization), the EBM model was trained using 80% of the data and tested on the remaining 20%. Model performance was evaluated using standard metrics including AUC, accuracy, sensitivity, specificity, F1 score, and Matthews correlation coefficient. Feature importance was assessed to identify key predictors. Partial dependence analyses provided insights into how each variable affected model predictions. Results: The EBM model demonstrated excellent diagnostic performance, achieving an AUC of 0.980, an accuracy of 96.6%, sensitivity of 96.8%, and specificity of 96.2%. Troponin and CK-MB were identified as the top predictors, confirming their established clinical relevance in MI diagnosis. In contrast, demographic and hemodynamic variables such as age and blood pressure contributed minimally. Partial dependence plots revealed non-linear effects of key biomarkers. Local explanation plots demonstrated the model’s ability to make confident, interpretable predictions for both positive and negative cases. Conclusions: The findings highlight the potential of EBM as a clinically useful and ethical AI approach for MI diagnosis. By combining high predictive accuracy with transparency, EBM supports biomarker prioritization and clinical risk stratification, thus aligning with precision medicine and responsible AI principles. Future research should validate the model on multi-center datasets and explore additional features for broader clinical use. Full article