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PubMed2026

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↗

PubMed2026

Modulating sentence comprehension in people with aphasia through anodal tDCS: A double-blind randomized cross-over study.

This double-blind randomized cross-over study investigated the effects of perilesional anodal transcranial direct current stimulation (AtDCS) combined with speech-language therapy on sentence comprehension in eight individuals with chronic nonfluent agrammatic aphasia. The behavioral therapy consisted of an intensive comprehension treatment including drilling in sentence-to-picture matching and Mapping Therapy. Each participant underwent both the anodal tDCS and sham stimulation conditions (five received sham first followed by real stimulation, and the remaining three the reverse sequence), with each condition paired with the same behavioral treatment and separated by a four-month washout period. Stimulation was applied over the perilesional area (left BA6) for 20 min during daily 40-min therapy sessions over four consecutive weeks. Sentence comprehension was assessed with the RiComprendo battery and functional communication with the Communicative Effectiveness Index (CETI). Data were analyzed using paired t-tests, Bayesian analyses, and linear mixed-effects models to control for baseline performance and individual variability. Both stimulation conditions produced significant pre-to-post improvements in sentence comprehension, particularly for syntactically complex structures such as passives and center-embedded object relatives. However, gains were overall greater following AtDCS, as reflected in larger effect sizes, stronger Bayes factors, and a significant treatment effect in the mixed-effects models. Only the AtDCS condition yielded significant improvements in self-perceived comprehension abilities on the CETI. These findings suggest that AtDCS over perilesional cortical areas may boost the effects of traditional language therapy on sentence comprehension, supporting its feasibility and potential as an adjuvant intervention in post-stroke aphasia rehabilitation.

Humans↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans↗

PubMed2026

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one‑carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

Diagnostic accuracy of bronchoalveolar lavage fluid-based testing for pulmonary cryptococcosis: A systematic review and meta-analysis.

BACKGROUND: Pulmonary cryptococcosis(PC) presents diagnostic challenges because of its non-specific clinical and radiological manifestations. Bronchoalveolar lavage fluid (BALF)-based testing, which includes latex agglutination (LA) and lateral flow assay (LFA), offers a minimally invasive diagnostic method, yet its pooled diagnostic accuracy remains unclear. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Scopus from inception to May 2026. Studies evaluating BALF-based testing for PC with extractable 2 × 2 data were included. The methodological quality of relevant studies was assessed by the QUADAS-2 tool. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratio (DOR) were estimated using a bivariate random-effects model. Subgroup analyses were performed by testing method and reference standard type. Heterogeneity was evaluated through paired forest plots, HSROC visualization, and exploratory bivariate meta-regression. RESULTS: The pooled sensitivity was 0.87 (95% CI: 0.81-0.91), and the specificity was 0.99 (95% CI: 0.982 - 0.995). The pooled positive likelihood ratio (PLR) was 88.00 (95% CI: 47.39 - 163.42), the negative likelihood ratio (NLR) was 0.13 (95% CI: 0.09 -0.20), and the DOR was 658.50 (95% CI: 285.36-1519.55). No significant threshold effect or publication bias was detected. Exploratory meta-regression suggested a possible assay-method effect in the joint model (P = 0.03), mainly driven by specificity (P = 0.01). CONCLUSIONS: The study demonstrates the high accuracy of CrAg in BALF for the diagnosis of pulmonary cryptococcosis, supporting its role as an important adjunctive diagnostic tool, particularly when tissue biopsy is not feasible or rapid results are needed. Larger prospective studies with standardized protocols are needed to validate these estimates.

Humans↗

PubMed2026

The combined and independent influence of food texture and a 'mindful eating' instruction on eating rate and food intake among Dutch primary schoolchildren.

Eating rate (ER), the amount of food consumed per unit of time, is a key determinant of food intake, with faster ER associated with larger meal size. Research in adults has shown that both sensory properties like texture, and instructions can influence ER and intake. However, their independent and combined effect on ER and intake in children remain poorly understood. This study examined the effects of food texture and a 'mindful eating' instruction on ER and food intake in children. Children (N = 73), 38 boys, aged 4-12 years, participated in a 4-week cluster-randomized incomplete cross-over study conducted during regular school lunches. Using a 2×3 factorial design, children were exposed to two levels of food texture (softer vs. harder whole-grain buns) and three types of instructions (none, control, 'mindful'). Linear mixed models with repeated measures were used, adjusting for sex and group. As the interaction between food-texture and type of instructions was non-significant, it was excluded from the final models. Results revealed a strong main effect of food texture on ER and food intake (all p < 0.001), where compared with softer buns, harder buns were associated with a slower eating rate (Δ = -6.67 g/min, SE = 0.59) and reduced food intake (Δ = -70 g, SE = 8). In contrast, type of instruction had no significant effect on ER or intake (p = 0.85). Our findings demonstrate that food texture exerts a dominant influence on children's eating rate and food intake, highlighting texture modification as a potential leverage point for influencing ER and intake in children.

Humans↗

PubMed2026

Effectiveness and moderators of PE and CPT in adult PTSD treatment: a systematic review and meta-analysis.

Background: Posttraumatic Stress Disorder (PTSD) is a prevalent and debilitating condition that challenges mental health services worldwide. Effective psychological interventions are crucial for treatment, among which Prolonged Exposure (PE) and Cognitive Processing Therapy (CPT) are prominent. Comparative analyses of these treatments, considering moderators such as patient demographics and treatment specifics, are necessary to tailor interventions effectively.Objective: This meta-analysis synthesised findings from 175 treatment arms across 163 studies to evaluate the comparative effectiveness of PE and CPT for PTSD. Effect sizes were calculated as Hedges' g for between-group (treatment vs. control) and within-group (pre-post) comparisons.Results: Using a random-effects model, the overall pooled effect size was large (Hedges' g = 1.67, 95% CI [1.56, 1.79]), suggesting substantial treatment-related symptom improvement. Multivariate meta-regression revealed, across the full sample, none of the main effects or interactions was significant. A sensitivity analysis excluding 10 influential outliers reduced the overall effect size (g = 1.55), indicating that PE was associated with larger effects than CPT among non-military samples, and larger effects were observed in studies with a higher proportion of female participants, military samples, and samples with lower proportions of sexual trauma. Treatment-by-sample-characteristic interactions were not significant in the trimmed model.Conclusions: Findings suggest that PE and CPT produce large effects in reducing PTSD symptoms, with some variation across treatment type and sample characteristics. Results underscore the importance of examining contextual moderators such as treatment setting and population type and highlight the need for transparent reporting of key sample features to improve future meta-analytic precision.

Humans↗

PubMed2026

Estrone disrupts early reproductive development in juvenile male Siniperca chuatsi and is associated with brain and gonadal responses.

Whether estrone (E1)-associated disruption of early reproductive development in fish is accompanied by brain responses in addition to direct gonadal effects remains unclear. Here, juvenile Siniperca chuatsi, a non-model but economically important freshwater species, were exposed for 60 d to 0, 0.01, 0.1, and 1.0 μg/L E1, spanning environmentally reported and elevated concentrations. By integrating waterborne concentration monitoring, histopathology, transcriptomics, and quantitative real-time PCR (qPCR) validation, we evaluated E1-associated changes in brain and gonadal tissues during early reproductive development. Waterborne E1 concentrations remained generally stable throughout the exposure period. At the highest tested concentration (1.0 μg/L), E1 caused neuronal vacuolation and pyknosis in the hypothalamic region and induced distinct ovarian-like structures in the gonads of genetic males. In the brain, cyp19a1, crhr1, and adcy2a were significantly upregulated, whereas egr1 was significantly downregulated, indicating transcriptional changes in genes associated with local estrogen conversion, stress-response/cAMP signaling, and neuronal activity-related regulation within a broader injury/stress-response background. In the gonad, RNA-seq analysis showed significant downregulation of star2, hsd3b1, cyp17a1, and cyp11b and significant upregulation of hsd17b1, suggesting alterations in steroidogenesis-related gene expression at the transcriptomic level. qPCR analysis of selected gonadal candidate genes showed expression directions generally consistent with the RNA-seq results, and these molecular patterns were consistent with the feminized histological phenotype. Together, these results indicate that E1 can disrupt early reproductive development in juvenile S. chuatsi and support a cautious working model in which E1 exposure is accompanied by concurrent brain and gonadal responses. This study provides new evidence for understanding the toxic effects and ecological risk implications of natural estrogen E1 during early fish development.

Animals↗

PubMed2026

Novelty seeking and rapid symptom improvement across active and sham accelerated iTBS conditions: A pooled individual-patient data analysis.

INTRODUCTION: Major depressive disorder (MDD) is highly prevalent and often treatment-resistant. Accelerated intermittent theta burst stimulation (aiTBS) is a promising intervention for treatment-resistant depression (TRD), though outcomes vary. Personality traits have been examined in relation to rTMS outcomes, yet their role in aiTBS remains underexplored. This pooled individual-patient-data analysis of two randomized, sham-controlled trials examined associations between baseline Temperament and Character Inventory (TCI) traits and one-week symptom change, and whether they differed by condition. METHODS: The left dorsolateral prefrontal cortex was targeted for 20 sessions over 4 days. Personality was assessed with the TCI, depression severity with the 17-item Hamilton Depression Rating Scale (HDRS-17). TCI-symptom-change associations were examined with a robust linear mixed-effects model, adjusting for age, gender, repeated measurements, and study membership. RESULTS: 104 participants were included (M/F 45/59; mean age 40.9 ± 12.7; active/sham 50/54). The model yielded a Time × Novelty Seeking interaction (β = -1.70, p = 0.021): higher baseline Novelty Seeking was associated with faster symptom reduction, without a between-arm difference. However, the interaction did not survive Holm correction across 14 trait-interaction tests (adjusted p = 0.294) and is therefore exploratory. No other interaction reached the uncorrected threshold. CONCLUSIONS: Higher baseline Novelty Seeking showed a nominal association with faster symptom reduction, without a difference between active and sham conditions. Because it did not survive multiplicity correction and was not reproduced in within-arm analyses, it is preliminary and may reflect contextual or nonspecific processes. Independent replication is required before temperament assessment can be clinically informative.

Humans↗

PubMed2026

Oro-esophageal feeding for tracheostomized patients with severe traumatic brain injury: a randomized controlled trial.

BACKGROUND: This study reports the clinical effects of intermittent oro-esophageal tube feeding (IOE) versus nasogastric tube feeding (NGT) on nutritional status, aspiration pneumonia, decannulation, and level of consciousness in tracheostomized patients with severe traumatic brain injury (sTBI). METHODS: A randomized controlled trial was conducted between March 2024 and October 2025 in China and included tracheostomized patients with sTBI. Participants were randomized 1:1 to the intervention and control groups for 28-day interventions. IOE or NGT was used for nutritional supports, respectively. The primary outcome was nutritional status, including hemoglobin, albumin, prealbumin and body mass index. The secondary outcomes included aspiration pneumonia, decannulation, and level of consciousness assessed using the Glasgow Coma Scale (GCS). Generalized linear mixed-effects models, generalized estimating equations, and Cox regression were used for data analyze. RESULTS: A total of 104 participants were included in the analysis. After intervention, significant interaction effects were observed in hemoglobin (β = 5.272, 95% CI: 2.707, 7.837), albumin (β = 3.675, 95% CI: 1.854, 5.496), prealbumin (β = 11.835, 95% CI: 6.623, 17.047), body mass index (β = 1.719, 95% CI: 0.868, 2.569), the GCS (β = 0.981, 95% CI: 0.572, 1.390), and aspiration pneumonia (OR= 0.304, 95% CI: 0.133, 0.693). The Cox model revealed that group significantly influenced the decannulation outcomes [HR (95% CI) =5.556 (3.197, 9.657), p < 0.001]. CONCLUSIONS: In tracheostomized patients with sTBI who received routine treatment, IOE is more conducive to decannulation and the improvement in nutritional status, aspiration pneumonia, and level of consciousness than NGT. CLINICAL TRIAL REGISTRATION: Prospectively registered at ClinicalTrials.gov (NCT06328985, 03/18/2024, clinicaltrials.gov/study/NCT06328985).

Humans↗

PubMed2026

Effects of CPAP on endothelial activation and fibrinolytic balance in coronary artery disease with obstructive sleep apnea: The RICCADSA randomized controlled trial.

BACKGROUND: Obstructive sleep apnea (OSA) promotes endothelial activation and a prothrombotic milieu through intermittent hypoxia, oxidative stress, and systemic inflammation, mechanisms closely linked to atherosclerosis progression. The vascular effects of continuous positive airway pressure (CPAP) therapy in patients with established coronary artery disease (CAD) remain incompletely understood. OBJECTIVE: To evaluate the longitudinal effects of CPAP treatment on endothelial adhesion molecules and fibrinolytic balance in patients with CAD and OSA. METHODS: In this randomized controlled analysis from the RICCADSA trial, 210 revascularized CAD patients with moderate-to-severe OSA were assigned to CPAP (n = 104) or no-CPAP (n = 106) and had available biomarker measurements at baseline and 12 months. Circulating intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), and plasminogen activator inhibitor-1 (PAI-1) were assessed. Linear mixed-effects models were used to examine longitudinal changes and time-by-treatment interactions adjusted for cardiometabolic covariates. RESULTS: For ICAM-1, no significant time-by-treatment interaction was observed. For PAI-1, a borderline time-by-treatment interaction suggested a numerically smaller increase in the CPAP group compared with no-CPAP (p = 0.09). CPAP treatment was associated with a significantly greater reduction in VCAM-1 over time compared with no-CPAP (time-by-treatment interaction p = 0.045 in adjusted models). CONCLUSIONS: CPAP treatment was associated with selective modulation of vascular biomarkers in patients with CAD and OSA, characterized by attenuation of endothelial activation reflected by reduced VCAM-1 levels, while fibrinolytic imbalance appeared largely resistant to intervention. These findings support pathway-specific vascular responses to CPAP and provide mechanistic insight into residual atherosclerotic risk in this high-risk population.

Aged↗

PubMed2026

A single session of high-definition transcranial direct current stimulation does not modulate effects of knee two-point discrimination training or sensorimotor function in healthy adults: Double-blind randomised controlled trial.

BACKGROUND: Benefits of sensory-training interventions on sensorimotor outcomes are inconsistent, and it is unclear whether transcranial direct current stimulation (tDCS) can enhance proprioception, which is fundamental to neuromuscular control. Existing evidence is dominated by upper-limb studies, so transferability to the knee is unclear. This study investigated whether a single session of anodal high-definition (HD)-tDCS, alone or combined with brief two-point discrimination (TPD) training, enhances knee sensorimotor function and performance in healthy adults. METHODS: In a double-blind randomised-controlled trial, 57 healthy participants received (1) 20-min, 1 mA anodal HD-tDCS over the knee primary somatosensory (S1) map or sham stimulation, and (2) 15-min knee TPD training or no training. Knee somatosensory, sensorimotor, and functional performance measures were assessed pre- and immediately post-intervention. Three-way mixed-design ANOVAs, equivalence testing (smallest effect size of interest η2 = 0.02), Bayes factors, and linear mixed-effects models quantified effects. RESULTS: HD-tDCS, TPD training, and their sequential combination had no effect on any outcome measure (p ≥ 0.05; η2 ≤ 0.015). Confidence intervals spanned equivalence bounds, and equivalence testing results were non-significant (p ≥ 0.05). Bayes factors (<0.33) showed moderate evidence for the null (no effect). Mixed-effects modelling attributed ≤8% of total variance to intervention fixed effects, with the remainder captured by participant-level random effects. CONCLUSION: A single 20-minute session of 1 mA HD-tDCS, with or without brief TPD training, does not acutely modify knee somatosensory, sensorimotor, or functional performance in healthy adults. Existing evidence at the hand may not translate to the lower limb. Future work should investigate higher-dose, multi-session, task-concurrent, or network-targeted strategies in clinical populations.

Humans↗

PubMed2026

Effects of intensive lifestyle interventions with calorie-carbohydrate-restricted diet versus time-restricted eating on appetite and binge eating in type 2 diabetes: A randomized controlled trial.

The impact of intensive lifestyle interventions on appetite regulation and binge eating in individuals with type 2 diabetes (T2D) remains unclear. This study evaluated the effects of combined lifestyle interventions on appetite responses and binge eating in overweight or obese adults with T2D. In a randomized trial, 120 participants with T2D were allocated to three groups (n = 40 each): (1) Calorie-carbohydrate restriction (CCR), (2) Time-restricted eating with CCR (TRE + CCR), or (3) Control. Intervention groups received structured exercise and behavioral education based on the Information-Motivation-Behavioral Skills model. Appetite perceptions (hunger, satiety, desire to eat, and prospective food consumption) and binge eating (Binge Eating Scale; BES and objective binge episodes) were evaluated at baseline, week 12, and week 24 using linear mixed models. Both CCR and TRE + CCR significantly improved subjective appetite compared with the control group at 12 and 24 weeks (all p < 0.01). At 24 weeks, hunger decreased by -24.1 mm (95% CI: -35.8, -12.5) in the CCR group and -32.7 mm (95% CI: -44.2, -21.3) in the TRE + CCR group. Satiety also increased by 21.7 mm (95% CI: 9.46, 33.9) and 29.4 mm (95% CI: 17.4, 41.4), respectively. Significant reductions were observed for desire to eat and prospective food consumption. In contrast, changes in BES and objective binge episodes were not significantly different between groups at any time point. No significant differences were detected between the CCR and the TRE + CCR groups. Intensive lifestyle interventions incorporating CCR or TRE + CCR effectively reduced appetite in adults with T2D but did not significantly affect binge eating. Future research should target individuals with higher baseline BES scores to clarify potential benefits for binge eating behavior.

Humans↗

PubMed2025

Global epidemiology of diabetes and prediabetes in lean or non-obese patients with NAFLD: a systematic review and meta-analysis.

BACKGROUND: The presence of diabetes increases the risk of adverse outcomes of patients with non-alcoholic fatty liver disease (NAFLD) even in those with lean or non-obese NAFLD. However, the epidemiological data regarding the prevalence of diabetes and prediabetes in lean or non-obese NAFLD populations remain limited. We assessed the global epidemiology of diabetes and prediabetes in lean or non-obese patients with NAFLD. METHODS: Published studies were searched in PubMed, EMBASE, Cochrane Library, and Web of Science databases from the inception of the databases to October 2024. The pooled global prevalence of diabetes or prediabetes in patients with NAFLD was evaluated using random-effects meta-analysis. Subgroup meta-analysis and meta-regression were used to investigate potential sources of heterogeneity. RESULTS: A total of 54 studies involving 146,714 patients with non-obese or lean NAFLD were included. The pooled global prevalence of diabetes among patients with lean or non-obese NAFLD was 15.6% (95% CI 10.8%-22.7%). Studies from South America reported the highest prevalence (41.3%, CI 39.1%-43.5%). Meta-regression models showed that geographic region and mean age (p < 0.05) were associated with the were associated with the prevalence of diabetes, jointly accounting for 51.61% of the heterogeneity. The global prevalence of prediabetes among patients with lean or non-obese NAFLD was 22.9% (95% CI 12.5%-41.9%) with the highest prevalence reported in studies from Europe (34.4%, CI 23.0%-51.4%). Meta-regression models showed that geographic region and country (p < 0.05) were associated with the prevalence of prediabetes, jointly accounting for 73.65% of the heterogeneity. CONCLUSION: The pooled global prevalence of diabetes and prediabetes were 15.6% and 22.9% in lean or non-obese patients with NAFLD, respectively. These findings suggest the importance of diabetes screening in these patients.

Humans↗

PubMed2026

Does impulsivity predict treatment outcomes in PTSD with borderline personality disorder features? Results from a randomized clinical trial.

BACKGROUND: Trauma-focused psychotherapies are first-line treatments for posttraumatic stress disorder (PTSD). However, a substantial proportion of clients do not respond adequately or drop out of therapy prematurely. This has sparked interest in identifying individual-level predictors of treatment outcomes, including improvement in PTSD severity and dropout. Impulsivity may be a predictor because it may interfere with key therapeutic processes, such as cognitive restructuring and emotional processing. Consequently, we present a hypothesis-driven secondary analysis of a 15-month randomized clinical trial comparing Dialectical Behavior Therapy for PTSD (DBT-PTSD) and Cognitive Processing Therapy (CPT) in women with childhood abuse-related PTSD and borderline personality disorder features to test whether impulsivity, assessed at baseline, predicts PTSD improvement and dropout. We further explore whether the dimensions of impulsivity (non-planning, attentional impulsivity, and motor impulsivity) differentially affect the outcomes in DBT-PTSD vs. CPT. METHODS: A total of 193 cis women with PTSD related to childhood abuse and borderline personality disorder features were assessed using the Clinician-Administered PTSD Scale (CAPS) and the Barratt Impulsiveness Scale (BIS-10). Separate probit models and general linear models were applied to predict dropout and pre-to-post changes in PTSD severity (ΔCAPS) from total impulsivity and subscale scores, i.e. non-planning, attentional and motor impulsivity. RESULTS: Overall, dropout rates were higher for participants with higher baseline impulsivity scores (p = 0.049), particularly for those with higher non-planning impulsivity (p = 0.012). In participants randomized to CPT improvement in PTSD symptom severity (ΔCAPS) was negatively related to baseline total impulsivity (p = 0.021). In participants randomized to DBT-PTSD this relation was not significant. CONCLUSIONS: The results suggest that impulsivity may predict treatment outcomes. Specifically, patients with elevated impulsivity may be less likely to respond adequately to CPT. If replicated, these findings have implications for personalization of treatment.

Humans↗

PubMed2026

Effectiveness and implementation of task-sharing cognitive-behavioral interventions for perinatal mental health: A systematic review and meta-analysis.

OBJECTIVE: To evaluate the effectiveness of cognitive-behavioral interventions (CBIs) delivered by nonspecialist providers (NSPs) on perinatal depressive (PND) and anxiety symptoms, and to narratively synthesize their implementation processes and reported implementation outcomes, including acceptability, feasibility, fidelity, cost, and sustainability. METHODS: We systematically searched eight databases from inception to April 8, 2025. Eligible studies were randomised controlled trials (RCTs) assessing CBIs delivered by NSPs for PND and/or anxiety. Two reviewers independently screened, extracted, and assessed trials. Meta-analyses employed random-effects models, with subgroup, sensitivity, meta-regression, and publication bias analyses conducted in Stata 18.0. Implementation processes and outcomes were reported as frequencies or percentages across trials. RESULTS: A total of 47 trials (11, 357 participants) were included in the systematic review, of which 37 trials (8,709 participants) were included for meta-analyses. CBIs were conducted in 12 countries. Nurses and midwives delivered 45% of CBIs. CBIs were associated with reduced PND post-intervention compared with control conditions (standardized mean difference [SMD] -0.49, 95% CI -0.63 to -0.35; I² = 86.8%). Limited evidence from four trials suggested a small sustained effect at 12 months (SMD -0.14, 95% CI -0.27 to -0.02; I² = 26.4%). Reductions in anxiety symptoms were observed immediately post-intervention (SMD, -0.45, 95% CI -0.65 to -0.25; I²=81%), but evidence for longer-term effects was limited. Subgroup analyses confirmed consistent effects across diverse settings, populations, and intervention characteristics. Reporting of implementation processes (e.g., training, supervision, fidelity) was limited, with only 23.4% of trials assessing fidelity and 10.6% evaluating costs. CONCLUSIONS: NSP-delivered CBIs showed beneficial effects on PND and anxiety, with generally encouraging evidence for acceptability and feasibility. However, evidence for sustained effects beyond the immediate post-intervention period remains limited. Future studies should strengthen long-term follow-up and improve reporting of implementation processes and outcomes, particularly in rural and adolescent perinatal populations, to inform scalable and equitable task-sharing models.

Humans↗