SEARCH · Search PubMed

Results for “Predictive biomarkers”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

517 records · Page 12Linked to original sources

PubMed2026

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures↗

PubMed2026

Evaluation of pilocarpine effects on sweat proteome.

BACKGROUND: Sweat is increasingly recognized as a valuable, non-invasive biofluid for biomarker discovery, yet its composition depends on the stimulation method. This study aimed to determine how pharmacological induction with pilocarpine compares to physiologically induced sweat through exercise in shaping the sweat proteome. RESULTS: We analyzed thermoregulatory sweat from exercise, pilocarpine-induced sweat, and combined pilocarpine plus exercise sweat. Total protein concentrations were similar across conditions, but pilocarpine markedly increased proteomic diversity, with combined pilocarpine plus exercise sweat showing the highest number of identifications. The core sweat proteome remained stable, while pilocarpine selectively enriched low-abundance proteins involved in vesicular trafficking, cytoskeletal remodelling, and metabolism. Proteins linked to the canonical M3-Gq-PLC-Ca2+ pathway, including AQP5, CALML5, and CLIC1, were consistently enriched, confirming cholinergic activation. Pilocarpine-induced sweat also contained plasma-derived and immune-related proteins, reflecting enhanced secretion and reduced ductal reabsorption. CONCLUSIONS: Exercise yields a physiologically relevant but less complex proteome, pilocarpine-induced sweat produces a pharmacologically enriched yet biased profile, and combined pilocarpine plus exercise sweat maximizes protein detection at the expense of interpretability. These findings highlight the critical impact of stimulation paradigm on sweat proteomics and provide a reference framework for biomarker research. SIGNIFICANCE: This study employed LC-MS/MS to systematically characterize eccrine sweat and delineate how stimulation paradigms-exercise, pilocarpine, and their combination-shape its proteomic landscape. By demonstrating that pharmacological induction profoundly alters protein diversity and composition compared to physiologically induced sweat, these findings establish a critical benchmark for sweat-based biomarker research and highlight the need for paradigm-aware sampling strategies in clinical and translational contexts. Nonetheless, several methodological constraints warrant consideration: the limited sample size (five individuals per group), the exclusive inclusion of women under combined oral contraceptive treatment (21 active pills followed by 7 pill-free days), which restricts extrapolation to naturally cycling women, and the focus on healthy young adults (18-25 years), limiting generalizability to older or clinically heterogeneous populations. Despite these limitations, this work provides a foundational framework for optimizing sweat collection protocols and advancing precision approaches in non-invasive diagnostics.

Pilocarpine↗

PubMed2026

Analyzing salinity tolerance in grass carp (Ctenopharyngodon idella): Insights from genome-wide association study and genomic selection.

Grass carp (Ctenopharyngodon idella) is one of the most widely cultured freshwater fish species globally. However, the expansion of its farming scale faces severe limitation owing to freshwater scarcity; therefore, the development of strains with greater salinity tolerance is key for expanding production using brackish water resources. To investigate the genetic basis of salinity tolerance in grass carp, a genome-wide association study (GWAS) was conducted using 200 individuals representing extreme phenotypes, namely salinity-tolerant and salinity-sensitive groups. In total, 17 single nucleotide polymorphisms (SNPs) related to salinity tolerance were detected, which were distributed across 11 chromosomes. Through gene annotation, 38 candidate genes were obtained from these loci. Enrichment analysis revealed these candidate genes are primarily implicated in key biological processes, including osmotic regulation, energy metabolism, and stress responses. Analyses of different SNP densities revealed that the 5 K SNP density panel can balance prediction accuracy and computational efficiency. The BayesA model achieved the highest prediction accuracy under the GWAS_Evenly selection strategy, with substantial reductions in mean absolute error and mean square error. This study reveals the genetic mechanisms of salinity tolerance in grass carp, which might be optimized through genomic selection, and provides insights for selectively breeding new varieties with greater salinity tolerance.

Animals↗

PubMed2026

Accelerated Diagnostic Pathways for Suspected Acute Coronary Syndrome in Practice: A Randomized Trial of 0/1-Hour vs 0/3-Hour Troponin Testing.

BACKGROUND: For suspected acute coronary syndrome (ACS), guidelines recommend using high-sensitivity troponins (hs-cTn) in accelerated diagnostic pathways (ADPs) with 0/1-hour recommended over 0/3-hour ADP. However, implementation of these ADPs, with universal use of hs-cTns, has not been directly compared in randomized trials OBJECTIVES: This study sought to compare the efficiency and safety of the European Society of Cardiology (ESC) 0/1-hour and a 0/3-hour ADP when implemented in real-world clinical practice. METHODS: This pragmatic, randomized, noninferiority implementation trial compared the safety and efficiency of clinician decision making using these 2 pathways. To prevent incorporation bias, an independent hs-cTnI was used for formal adjudication using the fourth universal definition of myocardial infarction (MI). Efficiency was judged by the proportion of patients discharged within 4 hours. The safety endpoint was major adverse cardiac events (MACE) within 30 days (adjudicated index or representation type 1 MI, cardiovascular death, and urgent coronary revascularization) for those who were considered not to have ACS and discharged. The noninferiority margin, for absolute difference in sensitivity, between the ESC 0/1-hour and the 0/3-hour ADP was set at 3%, assessed with a 1-sided 97.5% CI. RESULTS: From December 2021 to July 2024, of 13,983 screened 3,543 individual patients with suspected ACS were recruited and consented from 2 major emergency departments in North-West England, with 100% follow-up achieved for all representations to any national hospital. The median age was 60 years (IQR: 49.5-70.5 years), 53% were men, 6.7%, and 7.6% had adjudicated index type 1 MI and MACE within 30 days, respectively. The turnaround time from sample to result for central laboratory hs-cTnT was 81 minutes (IQR: 69-101 minutes). The proportion of patients discharged within 4 hours was relatively low and did not differ substantially (21.8% vs 19.2%, P = 0.07). In addition, the 0/1-hour pathway was noninferior for safety, in patients discharged, compared with the 0/3-hour pathway, absolute difference in sensitivity was +4.2% (1-sided 97.5% CI: -2.5) in favor of the 0/1-hour pathway. The calculated sensitivities were 93.7% (95% CI: 88.4%-97.1%) vs 89.5% (95% CI: 82.7%-94.3%), respectively. CONCLUSIONS: Implementation of the ESC 0/1-hour pathway failed to discharge significantly more patients within 4 hours of presentation compared with the 0/3-hour ADP. In addition, The ESC 0/1-hour was noninferior to the 0/3-hour hs-cTn pathway for safety of discharge, although safety for both pathways was less than that imputed by observational studies. This trial demonstrates that perceived benefits to emergency department efficiency of a reduced sampling interval are mitigated by central laboratory turnaround times as well as system constraints. (Pragmatic Randomised Trial of the ESC 0/1 Versus 0/3 Hour Troponin Pathway [MACROS2]; NCT05322395).

Acute Coronary Syndrome↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗

PubMed2026

Diagnostic utility of high-risk HPV polymerase chain reaction-based testing in head and neck FNA specimens with indeterminate cytomorphology.

BACKGROUND: Fine-needle aspiration (FNA) is critical in the initial diagnosis of many high-risk human papillomavirus (HR-HPV)-associated, metastatic oropharyngeal squamous cell carcinomas. Updated guidelines recommend HR-HPV-specific polymerase chain reaction (PCR) analysis over p16 immunohistochemistry on FNA specimens because p16 performs poorly on cytology material. PCR-based assays on liquid cytology material have demonstrated excellent analytic performance; however, the diagnostic utility of a positive HR-HPV PCR result in specimens with indeterminate cytomorphology remains uncharacterized. METHODS: The authors retrospectively identified 279 head and neck FNA specimens that had paired HR-HPV PCR testing on residual liquid cytology material over a 5-year period. The positive predictive value for histopathologically confirmed squamous cell carcinoma on surgical follow-up was calculated within each cytologic interpretive category. RESULTS: The HR-HPV PCR results were positive in 50.2% of specimens, negative in 40.9%, and indeterminate in 9.0%. The HR-HPV positivity rate ranged from 0% in specimens categorized as negative for malignancy to 57.3% in cytologically positive specimens, with 19.0%, 41.2%, and 50.0% positivity in the atypical, suspicious, and nondiagnostic categories, respectively. Among cytologically indeterminate specimens with positive HR-HPV PCR results (n = 14), the positive predictive value was 100% (95% confidence interval, 78.5%-100.0%). Blinded slide review additionally identified 15 cytologically positive specimens in which the definitive malignant interpretation depended substantially on HR-HPV positivity; all 15 were confirmed as squamous cell carcinoma. CONCLUSIONS: A positive HR-HPV PCR result on liquid cytology material carries a positive predictive value of 100% for malignancy in cytologically indeterminate head and neck FNA specimens. These findings support integrating HR-HPV PCR analysis into routine cytologic interpretation with the potential to upgrade some indeterminate specimens to malignant when HR-HPV is detected, expediting definitive treatment and sparing patients additional, invasive sampling.

Humans↗

PubMed2026

Prognostic Value of Frailty in Aortic Surgery: A Systematic Review and Meta-Analysis Comparing Frailty Assessment Tools.

BACKGROUND: Frailty is increasingly recognized as an important determinant of outcomes after aortic vascular surgery, but assessment methods vary substantially and the optimal tool for risk stratification remains uncertain. This systematic review and meta-analysis evaluated the prognostic value of preoperative frailty and compared the predictive performance of different frailty instruments in aortic surgery. METHODS: PubMed, Embase, and Cochrane Library were searched from inception to April 27, 2026. Eligible studies included patients undergoing open, endovascular, or hybrid aortic procedures involving abdominal, thoracic, thoracoabdominal, arch, and proximal aortic diseases, including aneurysms and dissections, assessed frailty preoperatively, and reported postoperative outcomes. RESULTS: Thirty studies comprising 419,459 patients were included. Frailty was associated with higher early mortality (odds ratio [OR] 2.20; 95% confidence interval [CI] 1.54-3.14) and late mortality (hazard ratio 2.18; 95% CI 1.64-2.90). Frail patients also had increased risks of major complications (OR 2.52; 95% CI 1.22-5.19), acute kidney injury (OR 1.64; 95% CI 1.34-2.02), and nonhome discharge (OR 5.50; 95% CI 3.05-9.92). Associations were consistent across surgical approaches and aortic segments. Judgment-based or phenotype-like tools yielded higher effect estimates than deficit-accumulation indices, although differences were not statistically significant; among index-based tools, Modified Frailty Index (mFI)-11 outperformed mFI-5. CONCLUSION: Preoperative frailty strongly predicts mortality, morbidity, and loss of functional independence after open, endovascular, and hybrid aortic surgery across different aortic segments and pathologies, including aneurysmal and dissecting aortic disease. Routine frailty assessment may improve risk stratification and perioperative decision-making.

Humans↗

PubMed2026

Effects of six weeks of guanidinoacetic acid supplementation with and without creatine monohydrate on cognitive function and markers of health in healthy adults.

BACKGROUND: Guanidinoacetic acid (GAA) supplementation has been reported to increase brain creatine content more effectively than creatine monohydrate (CrM). However, the effects on cognitive function are unclear. PURPOSE: The purpose of this proof-of-concept exploratory clinical trial was to determine whether GAA supplementation with and without CrM affects cognitive function and/or markers of health. METHODS: In a double-blind, randomized, and counterbalanced manner, 58 healthy and active adults (33 females, 35.5 ± 14 years, 76.2 ± 14 kg) ingested a PLA (PLA, 2 × 6 g/d maltodextrin), GAA (2 × 1 g/d) + PLA (2 × 5 g/d), or GAA (2 × 1 g/d) + CrM (2 × 5 g/d) for six weeks. The participants donated fasting blood samples and completed a battery of tests and questionnaires assessing various aspects of function, mood, stress, sleep quality, and markers of health at baseline and after six weeks of supplementation. Data were analyzed using General Linear Model (GLM) multivariate and univariate with repeated measures, and mean changes from baseline with 95% confidence intervals, and Chi-squared analysis, and considered significant when the probability of error was 0.05 or less, and approaching significance (p > 0.05-p < 0.10). RESULTS: GAA supplementation tended to improve overall reaction time (-241.8 ms [-533, 50], p = 0.10) while significant interaction effects were observed in overall reaction time (p = 0.031-330 ms [-629, -31]) and YES reaction time (-290 ms [-484, -96], p = 0.004) while recalled correct reaction time (-178 ms [-374, 21], p = 0.078) and recalled correct YES (7.4 % [-1, 15.8], p = 0.084) approached significance compared to PLA. Limited to no effects were observed on the Delayed Picture Recognition Task Test, Digit Vigilance Task Test, Corsi Block Task Test, or Stroop Color-Word Task Test. The amount of time engaged in moderate physical activity was significantly greater (p < 0.05) in the GAA group compared to PLA. Participants in the GAA group reported a lower frequency of controlling irritations (p = 0.036), and feeling like difficulties are mounting (p = 0.053) on the Perceived Stress Scale. Some positive and potentially undesirable effects were observed in sleep quality assessments. The quality of life assessment revealed that participants in the GAA group reported less frequent feelings of being worn out (p = 0.068) and that their health was excellent (p = 0.092) while those in the GAA + CrM group reported more frequent limitations when bending, kneeling, or stooping (p = 0.053), more often feeling full of life (p = 0.081), and less frequency in feeling downhearted and depressed (p = 0.066). No clinically meaningful changes were observed in blood markers or self-reported side effects among the groups. CONCLUSION: Dietary supplementation with GAA (2 g/d) and the combination of CrM (10 g/d + GAA 2 g/d) for six weeks improved delayed verbal episodic recognition memory and retrieval speed and some measures of perceived stress, sleep quality, and quality of life. However, most cognitive tests were not affected, particularly when comparing the GAA to the PLA group; there were some inconsistencies in the findings, and several differences only approached significance. Additional research is needed before conclusions can be drawn. Clinical trial registration: ISRCTN68542582.

Humans↗

PubMed2026

Effects of time-restricted eating on markers of glucose metabolism and regulation in individuals with prediabetes or type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials.

AIMS/HYPOTHESIS: This systematic review and meta-analysis aimed to investigate the effects of time-restricted eating (TRE) on glucose metabolism and regulation in individuals with prediabetes (fasting blood glucose of 5.6-6.9 mmol/l or HbA1c of 39-47 mmol/mol [5.7-6.4%]) or type 2 diabetes (fasting blood glucose ≥7 mmol/l or HbA1c ≥48 mmol/mol [6.5%]). METHODS: A literature search was performed in MEDLINE, Embase and CENTRAL from inception to 5 August 2025. Moreover, forward and backward citation searches were performed. Eligible studies were RCTs in adults with prediabetes or type 2 diabetes, lasting ≥2 weeks, reporting markers of glucose metabolism and regulation, comparing TRE (≤12 h eating window) with a non-time-restricted control diet. Studies involving pregnancy, other fasting regimens, or non-peer-reviewed publications were excluded. Data were pooled as weighted mean differences with 95% CIs using random-effects generic inverse variance models in Cochrane Review Manager Web, and results are presented as forest plots. The certainty of evidence was defined using Grading of Recommendations, Assessment, Development and Evaluations methodology, and risk of bias was estimated by using the Revised Cochrane risk-of-bias tool for randomised trials (RoB 2). RESULTS: Out of 2043 records identified through the database search, as well as 1249 from forward and backward citation searches, ten RCTs including 599 participants were included. The mean length of the studies was 4 months, and the eating windows ranged from 4 to 10 h per day. The pooled meta-analysis showed no overall effect of TRE on HbA1c (-3.33 mmol/mol; 95% CI -6.87, 0.20 (-0.30% points; -0.63, 0.02); p=0.06, moderate certainty). Nevertheless, following stratification by subgroups, TRE resulted in a reduction in HbA1c of 0.93 mmol/mol (-1.70, -0.17 [-0.09% points; -0.16, -0.02]; p=0.02) in individuals with prediabetes but not in individuals with type 2 diabetes (-4.68 mmol/mol; -10.08, 0.72 (-0.43% points; -0.92, 0.07); p=0.09). TRE reduced fasting blood glucose in the pooled analysis (-0.30 mmol/l; -0.53, -0.07; p<0.01, moderate certainty) as well as in the subgroup analyses in individuals with prediabetes (-0.14 mmol/l; -0.27, -0.01; p=0.03) and with type 2 diabetes (-0.48 mmol/l; -0.78, -0.17; p<0.01). Moreover, TRE lowered body weight by 1.6 kg (-2.2, -1.0; p<0.001) in the pooled analysis. The evidence was limited by imprecision arising from wide confidence intervals in some of the included studies, which may be due to small sample sizes. Lastly, the effects of TRE on markers of insulin sensitivity, beta cell function and continuous glucose monitoring measurements were inconclusive. CONCLUSIONS/INTERPRETATION: Moderate-certainty evidence indicates that TRE reduces fasting blood glucose but not HbA1c. The subgroup analyses revealed that TRE improved HbA1c and fasting glucose in individuals with prediabetes and improved fasting glucose in individuals with type 2 diabetes. Future large-scale studies should investigate long-term effects of TRE in prevention and treatment of type 2 diabetes. TRIAL REGISTRATION: PROSPERO CRD42024523591 FUNDING: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Three authors (JS, A-DT, THA) are employed at Steno Diabetes Center Copenhagen, a public hospital and research institution under the Capital Region of Denmark, partly funded by a grant from the Novo Nordisk Foundation.

Humans↗

PubMed2026

Exploring China's Clean Air Act and associated cardiovascular disease risk: a prospective, quasi-experimental, and causal inference modelling study.

BACKGROUND: Substantial improvements in air quality have been recorded following the implementation of China's Clean Air Act (CCAA) in 2013. However, the association between CCAA implementation and individual-level cardiovascular disease (CVD) risk remains unclear. We aimed to examine the long-term association between CCAA implementation and individual-level predicted CVD risk. METHODS: In this prospective, quasi-experimental study, we used data from the China Kadoorie Biobank, a prospective cohort study that recruited participants from five urban and five rural areas across China between 2004 and 2008, with three resurveys conducted after the baseline survey (in 2008, 2013-14, and 2020-21). We included 34 862 individuals (mean age 51·3 years) who participated in at least one resurvey and had no history of CVD at baseline. Participants were classified into intervention (n=25 497) and control (n=9365) groups based on the local government's targets for particulate matter reduction. We estimated the 10-year risk of incident CVD morbidity or mortality using a validated risk prediction model. We used a difference-in-difference model to assess the long-term association between CCAA implementation and predicted risk, with adjustments made for regional confounders and individual-level characteristics, including demographics, lifestyle factors, medical history, and indoor air pollution exposure. The relationship between changes in long-term exposure to PM2·5, PM10, and O3 and predicted risk after CCAA implementation was analysed using a linear model. The estimated risk differences associated with air pollutant changes were estimated based on the magnitude of changes and their corresponding effect sizes. FINDINGS: After the CCAA was implemented, PM2·5 and PM10 concentrations declined in both groups, but O3 concentrations increased. The intervention group showed a 3·95% (95% CI 3·18-4·72%) lower increase in predicted risk than the control group, with larger estimated differences under stricter enforcement. Between 2013 and 2021, each 10 μg/m3 change in PM2·5 concentration was positively associated with a 1·80 (1·34-2·27) percentage point change in predicted CVD risk, whereas each 10 μg/m3 change in PM10 concentration was associated with a 1·24 (0·84-1·63) percentage point change and each 10 μg/m3 change in O3 concentration with a 0·58 (0·33-0·83) percentage point change. Overall, the observed changes in air pollutants during the study period were associated with an average 6·6 percentage point reduction in predicted CVD risk. INTERPRETATION: The CCAA and improved air quality were associated with a slower increase in predicted CVD risk, supporting the necessity for stricter, multipollutant air quality policies to maximise public health benefits. FUNDING: National Natural Science Foundation of China, Kadoorie Charitable Foundation, Noncommunicable Chronic Diseases-National Science and Technology Major Project, National Key R&D Program of China, Chinese Ministry of Science and Technology, and UK Wellcome Trust.

Journal Article↗

PubMed2026

Synaptic vesicle glycoprotein 2A PET imaging in parkinsonian α-synucleinopathies: a systematic review.

Synaptic dysfunction is increasingly recognized as an early and biologically relevant component of α-synucleinopathies. However, conventional imaging biomarkers mainly assess dopaminergic dysfunction, glucose metabolism, or structural damage rather than presynaptic density itself. Synaptic vesicle glycoprotein 2A (SV2A) PET enables in vivo assessment of presynaptic terminal integrity and may provide complementary information in Parkinson's disease (PD), Parkinson's disease dementia/dementia with Lewy bodies (PDD/DLB), and multiple system atrophy (MSA). This systematic review synthesized the available evidence on SV2A-targeted PET in parkinsonian α-synucleinopathies, focusing on regional imaging patterns, clinical associations, longitudinal findings, and methodological determinants of interpretation. Seventeen reports were included. In PD, the most recurrent finding was reduced SV2A binding in the substantia nigra, although additional involvement of brainstem, caudate, striatal, thalamic, raphe, or cortical regions was reported in selected cohorts. In PDD/DLB, abnormalities appeared broader and more cortical, with evidence of association between cortical SV2A binding and cognitive performance. In MSA, one study suggested a distinct infratentorial and cerebellar pattern with potential relevance for phenotypic stratification. SV2A PET is a promising research biomarker for biological characterization of synucleinopathies. However, the field remains limited by small cohorts, methodological heterogeneity, variable quantification strategies, limited longitudinal evidence, and potential cohort overlap. Multicentre validation and harmonized protocols are required before clinical translation.

Humans↗

PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗

PubMed2026

Toward personalized interventions for preventing depression in primary care: Qualitative and quantitative findings from the e-predictD pilot study.

BACKGROUND: The predictD intervention, delivered by family physicians (FPs), has demonstrated effectiveness and cost-efficiency in preventing depression and anxiety. The e-predictD study aims to design, develop, and evaluate a novel personalized intervention for depression prevention by integrating information and communication technologies (ICTs), risk prediction algorithms, and decision support systems (DSS) for both patients and FPs. OBJECTIVE: To evaluate the satisfaction, usability, and acceptability, of a beta version of the e-predictD intervention in primary care settings. METHODS: The e-predictD intervention follows a biopsychosocial approach, including an initial patient-FP interview, specific FP training, and an app. A β-version was tested in a pilot study without a control group over three months. The app integrates a validated depression risk prediction algorithm, decision algorithms, and a monitoring system supporting the DSS. The DSS generates a personalized prevention plan (PPP) from eight intervention modules: physical exercise, social relationships, problem-solving, communication skills, decision-making, assertiveness, sleep improvement, and cognitive restructuring. Patients and FPs discussed the PPP in a 15-minute baseline interview, selecting modules for implementation over three months. Semi-structured interviews gathered feedback. Assessments included depression (PHQ-9), anxiety (GAD-7), quality of life (SF-12), and major depression risk (predictD algorithm). RESULTS: Six FPs from six Spanish cities enrolled 56 non-depressed patients at moderate-to-high risk of depression; 47 (84%) completed follow-up. The app was used for a median of six days (interquartile range: 1-30). Both FPs and patients expressed satisfaction, leading to incorporated improvements. After three months, significant reductions in major depression risk and anxiety symptoms were observed, alongside improved mental quality of life. However, no significant changes were found in depressive symptoms or physical quality of life. CONCLUSION: This pilot study supports the feasibility and acceptability of the e-predictD β-version, despite lower-than-expected app usability. Health improvements were observed, warranting confirmation in a randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03990792.

Adult↗

PubMed2026

Distress Intolerance, Social Anxiety, and Depressive Symptoms in Adolescents: Evidence from Random-Intercept Cross-Lagged Panel and Cross-Lagged Panel Network Analyses.

Social anxiety and depressive symptoms frequently co-occur during adolescence, yet the mechanisms underlying their longitudinal associations remain insufficiently understood. Distress intolerance has been proposed as a transdiagnostic risk factor implicated across internalizing symptoms. However, it remains unclear whether distress intolerance is predicted by social anxiety and depressive symptoms, as well as the underlying mechanisms among these three constructs. The specific symptoms most centrally involved in these cross-domain associations remain poorly understood. The present study investigated the longitudinal associations among distress intolerance, social anxiety, and depressive symptoms using a dual-method framework combining random-intercept cross-lagged panel models (RI-CLPM) and cross-lagged panel network (CLPN) analyses. A total of 1,378 Chinese adolescents (Mage = 12.57, SDage = 0.63; 50.4% female) were assessed at three time points with six-month intervals between waves. The RI-CLPM analyses revealed that higher distress intolerance prospectively predicted subsequent increases in both social anxiety and depressive symptoms, whereas elevated social anxiety and depressive symptoms in turn predicted subsequent increases in distress intolerance. Moreover, distress intolerance mediated the longitudinal associations between social anxiety and depressive symptoms. Additionally, distress intolerance was also indirectly associated with its own subsequent levels through social anxiety and depressive symptoms. The CLPN analyses revealed that fear of negative evaluation and fatigue were the strongest predictors of other network nodes from T1 to T2 and from T2 to T3, respectively. In contrast, distress intolerance symptoms were predominantly predicted by other nodes in both cross-lagged networks. These findings extend prior views of distress intolerance as a unidirectional vulnerability by showing that distress intolerance is also predicted by social anxiety and depressive symptoms and accounts for part of their longitudinal associations across adolescence.

Humans↗

PubMed2026

Ensemble DNA methylation clock demonstrates Immune-metabolic aging signatures associated with mortality.

Aging is a multifactorial process that is best described in terms of the progressive acquisition of multiple layers of phenotypic changes, such as epigenetic modifications, inflammation, and metabolic dysregulation. DNA methylation clocks have been extensively used to construct epigenetic clocks based on the DNAm profiles that can be used to estimate biological age and predict age-associated outcomes. Nevertheless, the vast majority of clocks constructed so far have been based on linear models, which are unlikely to fully account for the heterogeneity and non-linearity of survival-related DNAm signatures. In this work, we constructed a heterogeneous stacked ensemble survival model based on DNAm data obtained from the Framingham Heart Study. We first identified 190 CpG loci using elastic net Cox regression and subsequently constructed a survival prediction model based on the fusion of five complementary survival models by means of a neural network meta-learner. The prediction power of the survival model was evaluated in an external validation cohort, where we observed strong performance for predicting all-cause mortality that significantly exceeded PhenoAge and was statistically comparable to GrimAge. These performance estimates were derived in cohorts of European ancestry and externally validated in postmenopausal women aged 50-79 years, and should therefore be interpreted as applicable only to demographically similar populations.

Humans↗

PubMed2026

Longitudinal Relations among Perceived Economic Stress, Teacher-Student Relationships, and Cybervictimization: Exploring Within-Person Links.

Family economic hardship has been identified as a risk factor for adolescents' cybervictimization. Nevertheless, existing studies have primarily focused on objective economic conditions, and little is known about the within-person association between perceived economic stress and adolescents' cybervictimization and the mediating mechanisms underlying this association. To fill these gaps, the random intercept cross-lagged model was employed to examine the dynamic relations among perceived economic stress, teacher-student relationships, and cybervictimization. The data were obtained from a sample of 2407 Chinese adolescents (Mage = 12.75, SD = 0.58, 50.23% girls at baseline) recruited from seven schools and assessed at three time points over one year. At the between-person level, there were no significant associations among perceived economic stress, teacher-student relationships, and cybervictimization. At the within-person level, perceived economic stress positively predicted later cybervictimization over time, and this effect was unidirectional. The bidirectional relations between perceived economic stress and teacher-student relationships remained stable over time. Cybervictimization significantly and negatively predicted subsequent teacher-student relationships across time, indicating a unidirectional predictive effect. Additionally, perceived economic stress indirectly predicted cybervictimization through teacher-student relationships. The findings highlight the importance of distinguishing within-person from between-person processes and shed light on the longitudinal role of teacher-student relationships in the association between perceived economic stress and cybervictimization.

Humans↗

PubMed2026

Immune dysregulation in depression and psychosis: summary of current evidence and future perspectives.

Despite compelling epidemiological, genetic and cellular evidence linking immune dysregulation to depression and schizophrenia (and other psychotic disorders), causality remains contested and no immune biomarker has yet demonstrated robust clinical utility. Emerging methodological approaches - from target trial emulation on observational data to functional genomics - offer a potential path towards precision immunopsychiatry and stratified immunomodulatory treatment.

Neuroimmunology↗