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Diagnostic communication in functional neurological disorder: A systematic review and meta-analysis of patient acceptance and clinical outcomes.

OBJECTIVES: Diagnostic disclosure is a key therapeutic moment in Functional Neurological Disorder (FND). This systematic review aimed to evaluate quantitative evidence on diagnostic acceptance, understanding, satisfaction, symptom outcomes, and healthcare utilisation following diagnostic disclosure in FND, and to conduct a meta-analysis of diagnostic acceptance. METHODS: Systematic searches of PubMed, Scopus, PsycINFO, and Web of Science identified quantitative studies in adults with FND. Screening followed predefined inclusion criteria. Data were extracted using a structured template and risk of bias was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis of proportions was conducted using the Freeman-Tukey transformation. RESULTS: Fifteen studies were included, four of which contributed to the meta-analysis (n = 481). Reported diagnostic acceptance rates ranged from 38.7% to 90%, although the timing and method of assessment varied across studies. Pooled acceptance was 0.68 (95% CI 0.44-0.88), with substantial heterogeneity. Structured or reinforced communication was frequently associated with improved understanding and satisfaction, although its superiority for diagnostic acceptance was not established. In some studies, diagnostic acceptance was associated with more favourable clinical outcomes, although findings were inconsistent. Some studies reported reductions in healthcare utilisation or costs following satisfactory diagnostic explanation, whereas others found no sustained overall reduction. CONCLUSIONS: Diagnostic communication in FND is associated with differences in acceptance, understanding, and downstream clinical and healthcare outcomes. Approximately two-thirds of patients were reported as accepting the diagnosis following disclosure, although the timing and method of assessment varied substantially across studies. Empathic and evidence-informed communication may enhance understanding and engagement, although its effects on healthcare use and recovery remain uncertain. PRACTICE IMPLICATIONS: Diagnostic disclosure should be delivered clearly, empathically, and with reinforcement over time. Written information, reputable educational resources, and opportunities for follow-up clarification may support patient understanding and engagement, although stronger comparative evidence is needed.

Humans

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans

Updated adjunctive minocycline for schizophrenia: A systematic review and meta-analysis of clinical and cognitive outcomes.

BACKGROUND: Minocycline has been proposed as an adjunctive treatment for schizophrenia due to its anti-inflammatory and neuroprotective properties. However, evidence regarding its efficacy across clinical and cognitive outcomes remains inconsistent. METHODS: A systematic review and meta-analysis of double-blind RCTs was conducted following PRISMA guidelines. PubMed, Web of Science, Embase, Ovid MEDLINE, and the Cochrane Library were searched from January 2000 to August 2025. Eligible studies included patients with schizophrenia receiving adjunctive minocycline plus stable antipsychotics. Primary outcomes were PANSS total and subscale scores and overall cognitive performance. Secondary outcomes included SANS, CDS, CGI, GAF, and seven cognitive domains. Standardized mean differences (SMDs) with 95% CIs were calculated. RESULTS: Ten RCTs involving 895 participants were included. Adjunctive minocycline was associated with improvements in negative symptoms (PANSS negative: SMD = -0.55, 95% CI: -0.96 to -0.13; SANS: SMD = -0.75, 95% CI: -1.00 to -0.49) and overall psychopathology (PANSS total: SMD = -0.49, 95% CI: -0.80 to -0.18). Cognitive benefits were limited to a modest improvement in working memory (SMD = 0.24, 95% CI: 0.08 to 0.39), with no significant effects in other cognitive domains. Subgroup analyses suggested that illness stage, antipsychotic regimen, treatment duration, sample size, and geographic region may contribute to variability in treatment effects. Adverse event rates were comparable between groups. CONCLUSIONS: Adjunctive minocycline may improve negative symptoms and provide modest working memory benefits in schizophrenia. However, the evidence is limited by substantial heterogeneity, potential small-study effects, and inconsistent findings. Although short- to medium-term tolerability appeared comparable to placebo, larger, longer-term RCTs are needed to confirm its efficacy and safety.

Humans

An exploratory analysis of decision-making in population affinity estimation among forensic anthropology practitioners in the United States.

Population affinity estimation in forensic anthropology often involves the integration of multiple pieces of information, including visual (nonmetric) and metric data. This study examines how practitioners interpret and synthesize visual and metric information and their decision-making processes. A Qualtrics survey was developed using two cases: Case 1 presented clear nonmetric signal but ambiguous metric signal, while Case 2 showed more ambiguous nonmetric signal but clear metric signal. Practitioners were asked to estimate population affinity based on visual assessment, Fordisc data, and provide a final, integrated assessment. A total of 22 valid survey responses were received, with the majority of survey respondents reporting more than 10 years of forensic anthropology experience and holding a PhD degree. Results showed that there is substantial variability in Fordisc use and interpretation. Across both cases, participants synthesized conflicting visual and metric information, converged toward the stronger signal, and came to more consistent final estimates relative to the more ambiguous input. These findings highlight variability in practitioner decision-making but suggest that integration of nonmetric and metric information in population affinity estimation can moderate decision-making uncertainty. The results have implications for forensic anthropology education, training, and proficiency testing.

Humans

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans

Human iPSC-EV-loaded nanofiber stent coatings accelerate vascular repair by enhancing EGFR/HIF-1α signaling and suppressing ROCK1-mediated remodeling.

Arterial disease management is shifting from antiproliferative drug-eluting stents toward approaches that restore endothelial function and modulate smooth muscle cell (SMC) behavior. Stem cell-derived extracellular vesicles (EVs) carry miRNAs that promote endothelial proliferation and migration while restraining aberrant SMC growth and inflammation. Here, human induced pluripotent stem cell (iPSC)-derived EVs were collected by ultracentrifugation and incorporated into 50:50 poly (lactic-co-glycolic acid) (PLGA 503) core-shell nanofibrous membranes, which were fabricated as stent coatings for sustained release to overcome rapid clearance and poor tissue retention. EVs derived from three independent iPSC lines all enhanced tube formation in human umbilical vein endothelial cells (HUVECs) under hypoxic and serum-starved conditions and revealed a trend toward reduced platelet-derived growth factor-BB (PDGF-BB)-induced smooth muscle cell (SMC) migration. The fabricated core-shell nanofibers enabled sustained EV release, maintaining therapeutic efficacy for 28 days. Small RNA sequencing (NGS) analysis demonstrated that EVs from these independent iPSC lines shared miR-148a-3p and members of the miR-92 family, which collectively accounted for more than 75% of the reads within the 25 top-expressed miRNA set. In vitro, iPSC-EVs enhanced HUVEC proliferation and survival signaling by downregulating the negative regulators ERRFI1 and VHL, which are specific targets of miR-148a-3p and the miR-92 family, thereby activating the EGFR and HIF-1α axes and driving downstream ERK1/2 and VEGF expression under hypoxic and serum starvation stress conditions. Concurrently, iPSC-EVs prevented PDGF-BB-induced SMC phenotypic switching by downregulating ROCK1, a target of miR-148a-3p, thereby inhibiting downstream AKT and ERK signaling and preserving contractile markers while suppressing the synthetic phenotype. In vivo, the iPSC-EV-functionalized scaffolds significantly accelerated re-endothelialization and inhibited neointimal hyperplasia, evidenced by the upregulation of angiogenic factors (VEGF, CD31) and the concurrent suppression of pathological remodeling markers (α-SMA, MMPs) and inflammatory cytokines (IL-6, TGF-β1). Therefore, iPSC-EVs enriched with specific miRNAs and delivered via PLGA 503 core-shell nanofibers promote endothelial repair while suppressing SMC overgrowth, providing a promising strategy for vascular healing.

Core-shell nanofibers

Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.

The fermentation degree of heap-fermented grains in Jiangxiangxing Baijiu production is a critical factor influencing base Baijiu quality. However, conventional assessment methods largely rely on empirical experience and therefore suffer from limited objectivity and accuracy. In this study, integrated volatile profiling and metagenomic approaches were employed to investigate volatile characteristics and microbial functional potential differentiation in fermented grains with different fermentation degrees (under-fermented, normally fermented, and over-fermented). Significant differences in physicochemical properties were observed among fermentation degrees, particularly in acidity and reducing sugar content. Electronic nose analysis revealed distinct sensor response patterns among different fermentation degrees, indicating differences in overall volatile odor fingerprint patterns. A total of 81 volatile compounds were identified by HS-SPME-GC-MS, with aldehydes, ketones, and pyrazines showing pronounced variations among fermentation degrees, and acetaldehyde exhibiting strong discriminatory potential. LEfSe analysis identified 18 microbial taxa as potential biomarkers associated with different fermentation degrees, including Pichia kudriavzevii, Lentibacillus daiqui, and Acetobacter pasteurianus. Correlation analysis revealed significant positive associations between acetaldehyde levels and Acetobacter abundance. Furthermore, KEGG, CAZy, and eggNOG analyses revealed differentiated functional potentials among fermentation degrees, providing insights into the potential metabolic basis associated with flavor differentiation. Overall, these findings highlight that fermentation degree differentiation is closely associated with coordinated changes in physicochemical conditions, microbial communities, and functional potentials, providing ecological insights into flavor differentiation and theoretical support for objective fermentation degree evaluation and quality control of Jiangxiangxing Baijiu production.

Fermentation

Effects of blood flow restriction training combined with plyometric training on lower limb muscle strength and motor unit recruitment in basketball players: An experimental study.

OBJECTIVE: Previous studies have shown that plyometric training (PT) improves neuromuscular function and explosive power but not maximal strength. Blood flow restriction training (BFR) combined with low-intensity resistance training (RT) increases muscle mass and strength. This study investigated the effects of PT, and BFR combined with PT on lower-limb muscle function. METHODS: Twenty elite basketball players were randomly assigned to two groups: PT-alone group (PT, n&#x202f;=&#x202f;10) and BFR combine with PT group (PT-BFR, n&#x202f;=&#x202f;10). All participants underwent bodyweight-based plyometric training three times per week for eight weeks. Peak torque values for hip and knee flexion and extension, as well as root mean square (RMS) values derived from electromyography, were measured before and after the intervention. RESULTS: After the 8-week intervention, both groups showed significant improvements in knee flexion and extension peak torque at 180&#xb0;/s (all p&#x202f;<&#x202f;0.01). Between-group comparisons revealed greater gains in the PT-BFR group for hip extension and flexion at 60&#xb0;/s (p&#x202f;=&#x202f;0.036-0.002; &#x3b7;p2 = 0.225-0.233). RMS of the rectus femoris increased significantly more in the PT-BFR group than in the PT group (right: p&#x2009;=&#x2009;0.004, &#x3b7;p2 = 0.385; left: p&#x2009;=&#x2009;0.020, &#x3b7;p2 = 0.266), whereas no significant changes were observed in the gastrocnemius, tibialis anterior, or biceps femoris (all p&#x2009;>&#x2009;0.05). CMJ height also improved more in the PT-BFR group, with a significant group &#xd7;&#x2009;time interaction (p&#x2009;=&#x2009;0.042, &#x3b7;p2 = 0.210). CONCLUSION: Both training protocols enhanced bilateral lower-limb strength, with notable gains in the non-dominant leg; however, the magnitude did not differ substantially between groups. In contrast, compared with PT alone, BFR combined with PT produced superior enhancements in lower-limb muscle strength and neuromuscular recruitment. These findings suggest that when PT is employed to improve explosive power, it may be effectively combined with BFR to further augment muscular strength.

Humans

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&#xa0;% CI 0.85-0.94; 95&#xa0;% prediction interval 0.62-0.98), with sensitivity of 0.80 (95&#xa0;% CI 0.77-0.83) and specificity of 0.87 (95&#xa0;% 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

Perinatal depression, maternal thyroid status and fetus/infant health and development: A systematic review.

BACKGROUND: Thyroid hormones are known to influence both maternal depression and child developmental outcomes, while maternal depression independently affects child outcomes. The potential interaction between thyroid dysfunction and depression in shaping child development remains insufficiently explored. The present study addresses such interplay. METHODS: Following PRISMA 2020 and JBI guidelines, three databases were searched through December 2025 for primary studies on maternal thyroid status, perinatal depression, and child development. Risk of bias (RoB) was assessed using validated tools. Due to clinical and methodological heterogeneity, data were synthesized narratively following SWiM guidelines. RESULTS: Eleven studies were included. Beyond independent risks for preterm birth and behavioral problems, limited evidence supports a synergistic model, while most studies likely reflect the simple co-occurrence of risks. Maternal thyroid peroxidase antibodies (TPO-Ab) were associated with child externalizing problems exclusively in the presence of clinical depression. High depressive symptoms also attenuated the cognitive benefits of prenatal iodine supplementation. Thyroid status appears to function as a risk moderator rather than a mediator. However, 50% of observational studies presented high RoB, primarily due to participant attrition. CONCLUSION: Findings are still scarce to support a synergistic risk model where specific maternal thyroid parameters (i.e. thyroid autoimmunity and iodine status) may moderate the impact of depressive symptoms on child development. Despite the high RoB in half of the studies, results highlight the need for integrated screening protocols. Simultaneously assessing mental health and thyroid status may optimize risk stratification for high-risk mother-infant dyads.

Female

Genomic and One Health insights into Vibrio parahaemolyticus from environmental, seafood and clinical sources.

Vibrio parahaemolyticus is a leading cause of seafood-borne gastroenteritis worldwide, with climate warming facilitating its spread to high-latitude areas. In this study, we analyzed 212 genomes of environmental and seafood-associated isolates collected from seven cities in Zhejiang Province, China (2019-2024), alongside 228 clinical genomes from public databases. The 212 isolates were assigned to 172 sequence types (STs), with ST490 being the most frequent (5/212, 2.36%). Forty-four serotypes were identified, dominated by OL3:KUT (12.68%). High ST and serotype diversity were observed across different sample types and sources, with median pairwise single nucleotide polymorphisms (SNPs) ranging from 57,431 to 58,378, indicating comparable genetic diversity across groups. All isolates carried tlh and T3SS1 but lacked tdh and T3SS2. Resistance rates against ampicillin and cefazolin were 54.72% (116/212) and 44.34% (94/212), respectively, with multidrug resistance (MDR) detected in nine isolates, predominantly from seafood (7/9). A total of 63 distinct antimicrobial resistance genes (ARGs) spanning seven classes were identified. Isolates from aquaculture farms and wet markets exhibited greater resistance category diversity and higher ARG carriage than those from coastal or riverine sites. In contrast, the 228 clinical isolates harbored only 25 ARGs across two classes, with a significantly lower proportion of isolates carrying multiple ARG classes (0.44% vs. 6.13%, P&#xa0;<&#xa0;0.001). Human isolates formed tighter phylogenetic clusters, although a minority were closely related to environmental/foodborne strains. Overall, our findings demonstrate the genetic diversity and resistance potential of V. parahaemolyticus across environmental, seafood, and clinical sources, highlighting the importance of the One Health approach to comprehensive public health risk assessment.

Vibrio parahaemolyticus

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P&#xa0;=&#xa0;0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3&#xa0;&#xb0;C; +4.5&#xa0;&#xb0;C relative to CK_M), and its group-mean temperature remained &#x2265; 60&#xa0;&#xb0;C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

Bacillus

Multi-omics analysis reveals coordinated epigenetic dysregulation in atrazine-induced dopaminergic neurotoxicity.

Atrazine (ATR), a widely used triazine herbicide, has been linked to neurotoxicity, yet the epigenetic mechanisms underlying its dopaminergic effects remain unclear. This study investigated whether coordinated miRNA dysregulation and DNA methylation alterations contribute to ATR-induced Parkinson's disease (PD)-like neurotoxicity. Male Sprague-Dawley rats were administered ATR (50&#x202f;mg/kg/day) for 90 days, resulting in motor and cognitive deficits with dopaminergic dysfunction, including increased &#x3b1;-synuclein and reduced tyrosine hydroxylase expression. Small RNA sequencing identified 72 differentially expressed miRNAs in the substantia nigra, enriched in PI3K-Akt, MAPK, and Ras signaling pathways. In a cohort of six PD patients and six matched controls, genome-wide DNA methylation profiling revealed 4694 differentially methylated positions, predominantly hypomethylated, with overlapping enrichment in neuronal signaling pathways. Weighted gene co-expression network analysis identified a PD-associated module strongly correlated with disease status (r&#x202f;=&#x202f;-0.95, P&#x202f;<&#x202f;0.001). Multi-omics integration identified CASP3 as a central hub gene. External validation supported CASP3 relevance in PD (AUC&#x202f;=&#x202f;0.833), and molecular docking suggested potential ATR-CASP3 interaction. Further analysis predicted upregulated miR-3552 as a potential upstream regulator of CASP3. These findings indicate that ATR-induced neurotoxicity may be mediated through the miR-3552/CASP3 signaling axis, ultimately regulating apoptosis and contributing to neurodegeneration.

Animals

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n&#x2009;=&#x2009;11), persistent FGR (n&#x2009;=&#x2009;9), and healthy controls (n&#x2009;=&#x2009;13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n&#x2009;=&#x2009;69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p&#x2009;<&#x2009;0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular&#xa0;signatures reflecting&#xa0;the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2

Comparing trajectories of cognitive functioning in treatment-resistant and non-resistant depression: a multicentre linear mixed-effects analysis.

BACKGROUND: Impaired cognitive functioning is a severe symptom in major depressive disorder (MDD). Recent evidence suggests it may be a central characteristic in its treatment resistant form (TRD), potentially constituting a clinical marker for treatment resistance and a target amenable to intervention. To date, cognitive functioning in TRD remains poorly understood and longitudinal investigations are scarce. METHODS: This observational prospective cohort study, including 320 patients diagnosed with MDD from the multicentre PROMPT study, examined differences in cognitive functioning between 118 TRD and 202 non-TRD patients over a period of twelve weeks in a real-world setting, using linear mixed modelling. Patients that failed to respond to at least two prior antidepressants trials at baseline were classified as TRD. RESULTS: TRD patients showed significantly poorer baseline performances than non-TRD patients in attention/processing speed (&#x3b2;&#xa0;=&#xa0;-0.45; 95%CI[-0.70, -0.19]; FDR-p&#xa0;=&#xa0;0.003) and verbal memory (&#x3b2;&#xa0;=&#xa0;-0.45; 95%CI[-0.72, -0.18]; FDR-p&#xa0;=&#xa0;0.003). Significant time &#xd7; group interactions were observed in motor speed and verbal fluency tasks. Post-hoc-analyses revealed stagnation in TRD patients and significant improvement in non-TRD patients. Across all other tasks improvement was observed in both groups, and random effects showed large heterogeneity between patients, indicating notable individual differences in cognitive performances. CONCLUSIONS: The results suggest distinct recovery patters between non-TRD and TRD patients, and diminished functioning in TRD patients at the domain level. However, intact and diminished performances likely occur in both groups, warranting further investigation of cognitive heterogeneity. These short-term findings highlight the need for more comprehensive longitudinal research on cognition in TRD.

Humans

CNNM2 in schizophrenia: multilevel evidence of genetic susceptibility, magnesium homeostasis, neurodevelopment and cognitive dysfunction.

Schizophrenia (SCZ) is a common psychiatric disorder with a complex, genetically and environmentally influenced etiology, but the specific pathogenesis remains unclear. In recent years, the SCZ susceptibility gene CNNM2 (encoding cyclin M2) located at the 10q24.32-33 locus has received widespread attention. The well-validated SCZ risk interval 10q24.32-33 harbors two independent risk variants: rs11191580 in NT5C2 (significantly associated with CNNM2 mRNA and protein levels) and rs7914558 in CNNM2. Results from functional genomic analyses indicate that lower CNNM2 expression is significantly associated with SCZ. Imaging genetics studies have demonstrated that carriers of risk alleles of CNNM2 SNPs exhibit alterations in brain structure. Animal model studies have revealed that Cnnm2 downregulation in mice leads to impairments in sensorimotor gating and cognitive function. As an Mg2+ transporter, CNNM2 primarily maintains systemic Mg2+ homeostasis. According to clinical studies, a proportion of patients with SCZ exhibit reduced Mg2+ concentrations in plasma and cerebrospinal fluid. CNNM2 dysfunction may contribute to the pathology of SCZ by disrupting Mg2+ homeostasis, thereby affecting neurodevelopment and synaptic plasticity. A systematic consolidation of current evidence supporting the involvement of CNNM2 in SCZ pathogenesis provides a direction for further investigation of the pathological mechanisms underlying this disease, and for identification of novel targets for clinical intervention..

Schizophrenia

Determination of 13 per- and polyfluoroalkyl substances in human plasma samples using LC-MS/MS: application to capillary microsamples.

Per- and polyfluoroalkyl substances (PFAS) are chemicals widely applied in industrial processes and highly persistent in the environment, whose extensive use has been linked to adverse health effects. Venous plasma is the conventional matrix for PFAS assessment in blood, and LC-MS/MS is the most used quantification technique. Despite the relevance of this topic, biomonitoring data on human exposure to PFAS in Brazil remain limited. This study validated an LC-MS/MS method for determination of 13 PFAS in human plasma. Blood samples were collected from volunteers by phlebotomy, followed by protein precipitation with acetonitrile containing 1% formic acid (v/v) and solid-phase extraction. Chromatographic separation was achieved on an Acquity UPLC HSS T3 column. The assay was linear over a calibration range of 0.2-20&#xa0;ng/mL. Intra- and inter-assay precision (CV%) were within the ranges of 2.06-12.0% and 0.25-10.7%, respectively. As for accuracy, results were 89.0-112.9%. Matrix effect ranged from -1.31 to 0.05%. Stability after four freeze/thaw cycles and under autosampler conditions were also confirmed for all analytes. The method was applied to 40 paired venous and capillary plasma samples. Both measures exhibited high correlation (r&#xa0;=&#xa0;0.926). PFOS was the only compound detected at concentrations &#x2265;0.2&#xa0;ng/mL (LLOQ) in all samples, with capillary plasma concentrations of 0.85-13.50&#xa0;ng/mL. In summary, the method showed good validation performance and demonstrated the suitability of capillary plasma samples as an alternative matrix for PFAS quantification.

Humans
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WorkPublishedSource identifierSource
Diagnostic communication in functional neurological disorder: A systematic review and meta-analysis of patient acceptance and clinical outcomes.2026-08-17PMID 42632320pubmed
Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.2026-08-17PMID 42641254pubmed
Updated adjunctive minocycline for schizophrenia: A systematic review and meta-analysis of clinical and cognitive outcomes.2026-08-17PMID 42641306pubmed
An exploratory analysis of decision-making in population affinity estimation among forensic anthropology practitioners in the United States.2026-08-17PMID 42680455pubmed
Quantitative assessment of the fingerprint evidential value using machine learning.2026-08-17PMID 42680471pubmed
Human iPSC-EV-loaded nanofiber stent coatings accelerate vascular repair by enhancing EGFR/HIF-1&#x3b1; signaling and suppressing ROCK1-mediated remodeling.2026-08-17PMID 42699659pubmed
Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.2026-08-17PMID 42705715pubmed
Effects of blood flow restriction training combined with plyometric training on lower limb muscle strength and motor unit recruitment in basketball players: An experimental study.2026-08-16PMID 42604665pubmed
Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.2026-08-16PMID 42617201pubmed
Perinatal depression, maternal thyroid status and fetus/infant health and development: A systematic review.2026-08-16PMID 42623836pubmed
Genomic and One Health insights into Vibrio parahaemolyticus from environmental, seafood and clinical sources.2026-08-16PMID 42705734pubmed
Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.2026-08-16PMID 42705761pubmed
Multi-omics analysis reveals coordinated epigenetic dysregulation in atrazine-induced dopaminergic neurotoxicity.2026-08-15PMID 42600914pubmed
Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.2026-08-15PMID 42603261pubmed
Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.2026-08-15PMID 42603344pubmed
Comparing trajectories of cognitive functioning in treatment-resistant and non-resistant depression: a multicentre linear mixed-effects analysis.2026-08-15PMID 42603560pubmed
CNNM2 in schizophrenia: multilevel evidence of genetic susceptibility, magnesium homeostasis, neurodevelopment and cognitive dysfunction.2026-08-15PMID 42603609pubmed
Determination of 13 per- and polyfluoroalkyl substances in human plasma samples using LC-MS/MS: application to capillary microsamples.2026-08-15PMID 42607347pubmed

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