BackgroundAnxiety and other non-motor symptoms can greatly diminish quality of life in people with Parkinson's Disease (PD). Yet, few randomized controlled trials (RCTs) have assessed accessible, non-pharmacological mental health treatments for people with PD.ObjectiveTo assess the feasibility and impact of brief, remotely-delivered meditation and breathwork on neuropsychiatric symptoms in people with PD.MethodsIn this 18-week RCT, intervention participants attended weekly webinars for six weeks, while waitlisted controls maintained their usual routine before crossing over at six weeks. Participants were assessed for weekly compliance trends (primary outcome) and changes in anxiety (primary outcome), depression, perceived stress, and other non-motor symptoms at 6-week intervals: baseline and weeks 6 (T2), 12 (T3), and 18 (T4). Weekly compliance was collected in each group for 12 weeks. Anxiety was measured using the Parkinson's Anxiety Scale.ResultsThere was a significant decrease in the primary outcome, anxiety, in the intervention group (n = 17) compared to the waitlist control (n = 21) after 6 weeks of meditation and breathwork practice (mean difference (MD)= -5.0, 95% CI [-9.5, -0.49], P = .03). Within-group analysis further confirmed a significant reduction in anxiety (MD = -4.7, 95% CI [2.10,7.33], P < .001) in the intervention group (n = 28). Thirty-one percent of participants met the compliance definition.ConclusionRemotely-delivered meditation and breathwork through the BSM program significantly reduced anxiety in individuals with PD in our study and may be a promising non-pharmacological therapy. A larger RCT with continuous wellness coaching is warranted to more rigorously assess efficacy and optimize protocols.Clinical trial registration: ClinicalTrials.gov, NCT05335850, https://clinicaltrials.gov/study/NCT05335850.

Artificial intelligence (AI) is reshaping clinical decision support systems (CDSSs). In acute and critical care, nurses provide continuous surveillance, recognise deterioration, coordinate escalation and translate protocols into bedside action. AI-CDSS may be particularly relevant when they support rather than replace clinical judgement.

To examine whether nurse-used AI-CDSS improve patient-important outcomes in acute and critical care contexts and summarise effects on care processes and nurse-reported outcomes.

Following PRISMA 2020 and a preregistered protocol, we searched eight databases and major trial registries for English-language studies from 1 January 2010 to 1 January 2026. Searches were conducted on 1 January 2026. We included randomised, quasi-experimental and adjusted cohort studies in which registered nurses or nursing teams were primary users of AI-CDSS generating patient-specific predictions or recommendations. Mortality was pooled using a random effects model; other outcomes were synthesised narratively.

Seven studies involving about 75 000 patients were included. Most evidence came from acute wards, intensive care units, sepsis, deterioration and delirium-prevention contexts, with additional home and palliative care evidence. Three mortality studies were pooled. Nurse-facing AI-CDSS were associated with lower hospital mortality (RR 0.68, 95% CI 0.53-0.87; I² = 24%), although the prediction interval included possible no effect. Length of stay and protocol adherence generally improved when tools were embedded in nursing workflows. Nurse-reported outcomes were sparse.

Nurse-facing AI-CDSS may strengthen acute and critical care nursing by improving surveillance, escalation and protocol delivery for patients at risk of deterioration. Evidence is promising but limited by small study numbers, heterogeneous interventions and sparse nurse-reported outcomes. Critical care implementation should prioritise nurse-centred design, alert burden, equity, safety monitoring and rigorous evaluation before scale-up.

Nurse-used AI-CDSS show potential to improve patient outcomes and care processes, but evidence remains limited and context dependent.

Dermoscopy enhances melanoma detection, but small-diameter melanomas (SDMs) remain diagnostically challenging. Convolutional neural networks (CNNs) may detect subtle patterns beyond human perception. This study evaluates how lesion diameter influences the diagnostic accuracy of dermatologists, with and without CNN support.

This multicenter cross-sectional study included 150 histopathologically verified lesions: 110 small lesions (70 SDM, 40 nevi) and 40 large-diameter melanomas (LDM > 5 mm). Dermatologists evaluated lesions at level: (I) dermoscopy, close-up image, and clinical metadata; (II) plus CNN predictions. Primary outcomes were sensitivity, specificity, and ROC-AUC.

The CNN achieved a sensitivity of 62.7% (53.4%-71.2%), specificity of 80.0% (65.2%-89.5%), and ROC-AUC of 0.800 (0.723-0.876). Dermatologists performed higher at 71.8% (62.8%-79.4%), 82.5% (68.1%-91.3%), and 0.853 (0.794-0.912), improving slightly with CNN support to 72.7% (63.7%-80.2%), 85.0% (70.9%-92.9%), and 0.860 (0.796-0.923) (all p > 0.180). Subgroup analyses showed lower CNN performance in SDM, with sensitivity 48.6% (37.3%-60.1%) and ROC-AUC 0.740 (0.644-0.836), compared with LDM at 87.2% (73.3%-94.4%) and 0.904 (0.836-0.973). Dermatologists also reached their highest ROC-AUC in the LDM subgroup (0.925 [0.858-0.991]). Overall, CNN support led to slight, non-significant improvements, most notably in SDM (all p > 0.720).

Lesion size strongly influences melanoma diagnosis. CNN support offers modest, non-significant gains, with highest accuracy achieved by experts using AI assistance.

Glioblastoma is an aggressive primary brain tumor with poor survival. Depressive and anxiety symptoms and suicidality are common and impair quality of life and care. Prospective multicenter data using validated measures of suicidal ideation and behavior in German glioblastoma cohorts are scarce. We aim to quantify psychiatric symptom burden and suicidality and examine associations with demographic, clinical, and tumor-related characteristics.

SHINE-GLIO is a multicenter, cross-sectional observational study at German neuro-oncology centers. Adults with newly diagnosed isocitrate dehydrogenase wild-type glioblastoma after primary radiotherapy and before first recurrence are eligible. Exclusion criteria include clinically significant aphasia, other malignancies, and known tumor predisposition syndromes. At one outpatient visit, participants undergo physical examination and complete validated self-report questionnaires assessing suicidality (SSEV), depressive symptoms (PHQ-8), anxiety (GAD-7), social support (SUCE-4), and quality of life (EORTC QLQ-C30 and QLQ-BN20). Tumor characteristics, clinical history, and concomitant medications are extracted from medical records. Prespecified regression models will examine associations with suicidality while accounting for demographic, clinical, and tumor-related factors.

This study will provide a standardized multicenter assessment of suicidality and related psychiatric symptoms in German patients with glioblastoma. The findings may inform screening and referral pathways for mental health care.

ClinicalTrials.gov identifier: NCT07409584. First posted prospectively on February 12, 2026.

Intensive care unit-acquired weakness (ICUAW) is frequent in critically ill adults and is associated with adverse outcomes, but early recognition is difficult because standard diagnosis relies on volitional strength testing.

In this prospective multicentre cohort study across 16 tertiary ICUs in southwest China, adults expected to remain in the ICU for ≥ 3 days underwent quadriceps ultrasound and routine clinical assessment within 24 h of admission. ICUAW was defined by the first evaluable Medical Research Council (MRC) score during ICU stay. We developed and compared nine algorithms in a development cohort (n = 858) and performed temporal external validation in a later cohort (n = 345).

ICUAW occurred in 579/858 (67.5%) patients in the development cohort and 181/345 (52.5%) in the validation cohort. In external validation, a random forest model integrating unpressurised ultrasound and clinical features achieved an area under the receiver operating characteristic curve (AUC) of 0.810 (95% CI 0.765-0.855), with sensitivity 0.983 (0.952-0.997) and specificity 0.726 (0.651-0.792). The corresponding pressurised-ultrasound model showed lower discrimination (AUC 0.730 [0.676-0.783]) and specificity (0.506 [0.427-0.585]). Shapley additive explanations (SHAP) highlighted quadriceps muscle thickness, Sequential Organ Failure Assessment (SOFA) score, albumin, and inflammatory markers as key contributors. In additional incremental-value analyses using the General RF model as the reference, the unpressurised RF model improved risk reclassification and discrimination (cf-NRI 0.490, 95% CI 0.277-0.698; IDI 0.072, 95% CI 0.045-0.099), whereas the pressurised RF model showed a smaller cf-NRI improvement (0.231, 95% CI 0.011-0.463) with less consistent IDI improvement (0.019, 95% CI - 0.002 to 0.040).

This early ultrasound-clinical model may identify patients at high risk of ICUAW before strength testing becomes feasible and support earlier targeting of preventive and rehabilitation strategies. Trial registration Registered in the Chinese Clinical Trial Registry (ChiCTR2300075581) on September 8, 2023.

Individuals with substance use disorders (SUD) have poor metabolic and cardiovascular health and a high prevalence of depression and anxiety symptoms. Regular physical activity can improve both somatic and mental health. This study aimed to evaluate the feasibility of an aerobic physical activity intervention (Braining) in psychiatric care services specialized in SUD.

In this uncontrolled open trial with pre-, post-, and 12-month follow-up measures, 22 patients with SUD participated in a 12-week physical activity intervention. Recommended participation was three 30-45-min moderate-to-vigorous interval-based exercise sessions per week combining aerobic and body-weight strength exercises. No minimum session attendance was required for study participation. Feasibility was assessed through recruitment yield, number of exercise sessions attended, and adherence to study procedures. Satisfaction, acceptability, credibility, and negative effects were assessed using self-report questionnaires and adverse event reporting. Physical activity was measured using accelerometry (ActiGraph GT3X) and self-report. Patient-centered outcomes were summarized descriptively.

The mean number of attended exercise sessions was 9 (SD = 7.7). Adherence to ActiGraph measurements was 73% at baseline, 46% mid-intervention, and 32% post-intervention. Completion of self-report assessments was 100% at baseline, 86% post-intervention, and 77% at 12-month follow-up. The mean Client Satisfaction Questionnaire (CSQ-8) score was 27 (SD = 3.9), and no serious adverse events were reported. Descriptive trends suggested reductions in psychiatric symptoms and substance use and improvements in functional status and quality of life, whereas changes in somatic measures were limited.

Acceptability of the intervention was high in the target patient population; however, exercise attendance was low. Participants engaged adequately in study procedures, but adherence to accelerometer-based measurements was low. With further methodological refinements to enhance patient engagement and adaptations to how physical activity is measured in vulnerable patient populations, Braining remains a relevant intervention and warrants systematic evaluation in future large-scale controlled trials.

The study was registered on 25/12/2021 at ClinicalTrials.gov under ID NCT05186688.

This study investigates the predictive value of the newly identified factors Beliefs about working with health problems and Support at work for patients on sick leave due to common mental disorders. The aim was to explore the validity of the two factors in a new sample, investigating the factor structure, reliability and construct validity. Further the predictive value was assessed from pre-to post-treatment and at 6- and 12-months follow-up using sick leave data from national registries.

The study had a longitudinal design conducting secondary analyses with data from a randomised controlled trial (N = 236). The patients filled out self-report questionnaires and sick leave data were collected from national registries.

The principal component factor analysis identified the two factors, Beliefs about working with health problems and Support at work, with strong internal consistency α = 0.79 and 0.85 respectively. At pre-to post-treatment both factors separately predicted number of days on sick leave. Beliefs about working with health problems also predicted number of days on sick leave from post-treatment to 6- and 12-months follow-up.

These findings highlight key predictors for return to work. Beliefs about working with health problems is especially important, predicting up to 12-months post-treatment. These factors can easily be assessed and addressed in therapy and increased focus may help more patients return to work.

Psilocybin-assisted therapy may be a promising new treatment for treatment-resistant depression. We examined the feasibility of administering a single 25-mg dose of psilocybin or placebo with psychological support in a randomized controlled trial design with 6 weeks of follow-up. A two-arm, double-blind, randomized, placebo-controlled feasibility trial was conducted at one National Health Service (NHS) site in England. Eligible participants met Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for major depressive disorder and had an inadequate response to ≥2 antidepressant treatments or ≥1 antidepressant plus ≥1 psychotherapy. Participants received 25-mg psilocybin or placebo with preparation, dosing support and integration. Primary outcomes were recruitment, retention and estimation of the Montgomery-Åsberg Depression Rating Scale (MADRS) variance. A multilevel regression analysis with an intention-to-treat population was used. Sixty participants were randomized (1:1), balanced by age, sex and prior psilocybin exposure, and 59 of 60 participants completed the MADRS at all follow-up visits. The adjusted between-group difference at week 3 on the MADRS was -10.41 (95% confidence interval: -14.86 to -5.95; Cohen's d = -1.70), favoring psilocybin, which was sustained at week 6. In total, 123 and 164 nonserious adverse events occurred in the placebo and psilocybin arms, respectively. Findings support a future confirmatory trial. EudraCT no.: 2018-003573-97 .

Sighing has been proposed as a primary respiratory reset mechanism that is often linked to emotional regulation. However, evidence linking sighing to anxiety relies heavily on laboratory studies, which lack ecological validity. It remains unclear whether ambulatory sighing dynamics in free-living settings reflect momentary (state) symptom fluctuations or enduring (trait) pathology. Evidence from daily-life monitoring is needed to evaluate sighing dynamics as a candidate digital biomarker for anxiety disorders (ADs).

This study aimed to evaluate daily-life sighing dynamics as a candidate digital biomarker of anxiety by disentangling state and trait anxiety-sigh associations and comparing these dynamics between individuals with ADs and healthy controls (HCs). A secondary objective was to assess the feasibility, signal quality, and joint data coverage of a synchronized ecological momentary assessment (EMA) and respiratory inductance plethysmography (RIP) protocol.

We conducted an intensive longitudinal study integrating smartphone-based EMA with continuous RIP using a Hexoskin smart shirt. Thirty-eight adults were enrolled (n=15 with ADs; n=23 HCs) and completed four 36-hour intensive monitoring blocks distributed over 1 to 2 weeks. Participants wore the Hexoskin RIP smart shirt during each 36-hour block and completed 6 randomly timed EMA prompts per day during the daytime hours (9 AM to 9 PM). Sighs were operationally defined as breaths with tidal volume ≥2 × each participant's median tidal volume. Each EMA entry was linked to the preceding 5-minute respiratory window, and the primary outcome was sigh proportion (sigh breaths/total breaths) per window. Multilevel generalized linear mixed models were used to analyze anxiety-sigh coupling, decomposing anxiety into within-person (state) and between-person (trait) components.

The analysis included 1279 synchronized psychophysiological windows from 33 participants. Five participants were excluded due to insufficient valid synchronized windows. In the primary beta-binomial model of sigh proportion, higher between-person (trait) anxiety was significantly associated with a lower overall sigh proportion (odds ratio [OR] 0.80, 95% CI 0.74-0.87; P<.001), while HCs showed a lower baseline sigh probability than the anxiety disorder group (OR 0.78, 95% CI 0.65-0.93; P=.005). The within-person anxiety-by-group interaction was significant (OR 1.14, 95% CI 1.03-1.26; P=.01), indicating that sighing tended to increase with higher momentary anxiety in HCs but was attenuated in participants with ADs. Feasibility was high (EMA completion: 1626/2046, 79.5%; high-quality respiratory samples: 10.85/12.90 million, 84.1%; EMA-RIP linkage: 1319/1626, 81.1%).

Daily-life sighing dynamics showed a state-trait dissociation, with reduced state-dependent coupling in ADs versus HCs, supporting sighing as a candidate digital biomarker of anxiety. The synchronized EMA-RIP protocol was feasible and yielded high-integrity real-world data.

Behavioral dysfunction is a common characteristic of many neurodevelopmental and mental health disorders. While the causes of these disorders vary, aberrant behaviors may arise from alterations in transcriptional regulation during early neural development. Because transcription factors (TFs) often belong to families of closely related members, disruption of a single TF may indirectly influence the functionality of other family members. Consequently, mutations in TFs within the same family may lead to overlapping, yet distinct, phenotypes. This feature of TF function has important implications for understanding behavioral phenotypes, but detailed analyses across a single TF family are still lacking. In this study, we present a comprehensive behavioral analysis of adult zebrafish harboring mutations in individual members of the TALE and Hox TF families, that are essential for nervous system development. Using a battery of validated behavioral assays, we uncover elevated stress responses among all TF mutant lines, as well as TF-specific dysregulation in social interaction, locomotion, and endurance. The shared behavioral abnormalities across mutants suggest TF family members converge on core developmental pathways for stress-related behavioral regulation, while mutation-specific phenotypes indicate unique roles for individual TFs in fine-tuning neural function. Our findings provide a systematic behavioral characterization of TALE and Hox mutants in a vertebrate model and provide a framework for understanding how genetic variation within TF families may differentially contribute to vulnerability for neurodevelopmental and mental health disorders.