Somatoform traits (e.g., health anxiety, somatic preoccupation, and bodily distress symptoms) are prevalent and pose challenges to clinical practice. Understanding their genetic basis could improve diagnostic and therapeutic approaches.

Using available summary statistics, we conducted a multivariate genome-wide association study (GWAS) and multi-omic analysis of four somatoform traits - fatigue, irritable bowel syndrome, pain intensity, and health satisfaction - in 799,429 individuals genetically similar to European reference panels.

The GWAS identified 134 loci associated with a somatoform common factor, including 44 loci not significant in the input GWAS and 8 novel loci for somatoform traits. Novel loci were mechanistically informative, mapping to the DNM1 gene and the protocadherin gene cluster (PCDHA1-4), which are involved in nociceptor sensitization and synaptogenesis, respectively. Gene-property analyses highlighted an enrichment of genes involved in synaptic transmission and enriched expression in 11 brain tissues and the pituitary. Across two brain transcriptomic datasets, we identified 16 high-confidence genes whose expression in enriched tissues was associated with somatoform traits. There was substantial polygenic overlap (76-83%) between the somatoform and externalizing, internalizing, and general psychopathology factors. Somatoform polygenic scores were associated with obesity, type 2 diabetes, and tobacco use disorder in independent biobanks. Drug repurposing analyses suggested potential therapeutic targets, including MEK inhibitors, while Mendelian randomization analyses indicated potentially protective effects of gut microbiota.

Consistent with emerging medical and genetic knowledge, somatoform traits have a shared etiology and considerable polygenic overlap with psychopathology. The biological insights from drug repurposing and Mendelian randomization analyses could provide promising avenues for treatment development.

Cognitive and functional impairments can both influence and result from deteriorating social health (SH), yet their interplay during aging remains poorly understood. This study investigated the concordance and discordance of trajectories in SH, cognitive, and daily functioning.

We analyzed 15-year follow-up data (2001-2015) from 2,848 initially dementia-free older adults in the Swedish National study on Aging and Care in Kungsholmen. Cognition and daily functioning were assessed with the Mini-Mental State Examination and activities of daily living (ADLs)/instrumental ADLs. SH encompassed indices of social participation, connections, and support. Trajectories across these five dimensions were identified using latent growth curve analyses, latent class growth analyses, and growth mixture models.

Two cognitive trajectories-relatively preserved (91%) and fast decline (9%)-and two daily functioning trajectories-stable (95%) and declining (5%)-were identified. SH trajectories included stable groups, gradually declining social participation (70%), and low initial social connections (29%). Social support showed stable (95%), declining (2%), and increasing (3%) trajectories. Women were more likely to belong to the initially low-stable social connections group, whereas higher education was linked to favorable trajectories across most dimensions but not social support. Concordance was observed among those with the lowest cognitive, daily functioning, and SH profiles. Notably, increasing social support was linked to low cognition but high daily functioning (odds ratios [OR] = 4.2, 95% CI: 2.3, 7.6).

Findings underscore the central role of SH in aging, particularly how dynamic changes in social participation, connections, and support relate to cognitive and functional outcomes.

Poor sleep quality and anxiety are prevalent among university students and pose growing public health concerns. Physical fitness is often assumed to be associated with better sleep and mental health outcomes; however, evidence based on objectively measured physical fitness in non-clinical student populations remains limited and inconsistent.

This study aimed to examine the associations between multiple objectively assessed physical fitness components and sleep quality as well as anxiety outcomes among undergraduate students.

A total of 50 undergraduate students (mean age: 20.3 ± 1.1 years; 26 males, 24 females) enrolled in general physical education courses participated in this cross-sectional study. Physical fitness was assessed using standardized tests, including vital capacity, 50-m sprint, standing long jump, and sit-and-reach. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI), and anxiety symptoms were assessed using the anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A). Outcomes were analyzed as both continuous scores and categorical risk indicators (sleep disturbance: PSQI > 5; elevated anxiety: HADS-A ≥ 8). Multivariable linear and binary logistic regression analyses were performed, adjusting for age and sex.

After adjustment for age and sex, none of the physical fitness measures were significantly associated with PSQI global score or HADS-A score in linear regression analyses (all p > 0.05). Similarly, binary logistic regression analyses revealed no significant associations between physical fitness components and sleep disturbance or elevated anxiety symptoms (all p > 0.05). These null findings were consistent across different fitness domains and analytical approaches.

Objectively measured physical fitness was not significantly associated with sleep quality or anxiety outcomes among non-clinical undergraduate students. These findings suggest that general physical fitness alone may have limited explanatory value for sleep and anxiety in university populations and highlight the importance of considering broader psychosocial and behavioral factors when addressing student mental health.

Insomnia and chronic pain commonly co-occur, with Veterans more likely to experience both compared to the general population. As opioid prescribing practices change, there is growing interest in the use of cannabis for pain management and insomnia yet little data evaluating these potential associations.

405 Veterans recruited nationally who were prescribed long-term opioid therapy for chronic pain and had a positive urine drug screen for THC in the month prior were enrolled. Participants were stratified into "none" (n = 118), "mild" (n = 140), and "moderate/severe" (n = 147) insomnia groups via the Insomnia Severity Index. THC consumption over the prior ~3-6 months was determined from nail samples, assayed for Carboxy-THC (pg/mg) via liquid gas chromatography/mass spectroscopy.

Bivariate analyses compared demographic and clinical factors based on insomnia severity classifications. Relative to patients without impaired sleep, those classified as having mild insomnia had significantly worse pain interference, anxiety, depression, and PTSD symptom severity. These relationships were further amplified in the moderate/severe sleep impairment group, which also reported significantly greater pain intensity. However, no group differences were found related to Carboxy-THC concentration, reflecting previous consumption characteristics. Multivariable linear regression examined variables associated with insomnia severity; PTSD, depression, and pain interference were associated with insomnia, with no effect of cannabis consumption.

These findings suggest that in a sample of Veterans prescribed long-term opioid therapy with past month cannabis use, THC consumption may not be associated with insomnia symptoms. Future research should examine a possible threshold effect of cannabis dose on insomnia symptoms.

Existing mental health self-report measures have been criticized for over-simplification, lack of CF-specific focus, susceptibility to measurement reactivity bias, and conflation of symptoms of anxiety and/or depression with CF-related symptoms and/or treatment side effects. The CF Mental Health and Wellness Questionnaire (CFMHWQ) is a 25-item measure assessing CF-specific mental health burden symptoms.

To examine common underlying factors contributing to scores on the CFMHWQ, principal component analysis (PCA) was conducted of all 25 items. We conducted cross-validation of CFMHWQ principal components, examining unadjusted correlations between each principal component, demographic characteristics (age and biological sex), negative affect (mean rank global score combining BDI-II and BAI), psychological flexibility (mean rank global score combining AAQ-II and CFQ), and clinical characteristics.

One hundred twenty-three individuals contributed data for the PCA. A 5-factor model provided the most interpretable structure. Factors appeared to correspond to CF role-related concerns, CF symptomatic burden, social impairments due to CF, behavioral compliance, and coping/personality factors. Greater CF role impairments, behavioral adherence, symptom burden, social impairments, and poorer CF coping are all associated with greater negative affect. Similarly, greater levels of psychological flexibility are associated with lower CF role impairments, social impairments, behavioral adherence, and higher CF coping. Older age was associated with better behavioral adherence, but otherwise demographic factors were unrelated to CFMHWQ scores.

The CFMHWQ is a promising new self-report measure of CF-specific mental health burden, which associates with negative affect and psychological flexibility. Older age was associated with better behavioral adherence. Finally, more than half reported having undergone a medical procedure they experienced as traumatic, highlighting the importance of measuring the mental health burden of CF. Given the CF-specific nature of items and overfamiliarity with existing measures, we encourage the addition of the CFMHWQ by the CF community.

The number of people using medical cannabis has increased in the United States, but little is known about the prevalence or risk factors for Cannabis Use Disorder (CUD) in this population. We sought to estimate the prevalence of CUD and to identify individual characteristics and cannabis use patterns associated with CUD in a statewide sample of adults certified to use medical cannabis.

The sample included 632 adults (median age 45, 63% female, 75% non-Hispanic White) certified and currently using medical cannabis in Florida. Participants were recruited from medical cannabis clinics and completed an online cross-sectional survey in 2022. The primary outcome, based on the 8-item Cannabis Use Disorder Identification Test-Revised (CUDIT-R), was categorized as possible CUD (CUDIT-R score ≥12), hazardous use (score ≥8), or non-hazardous use (<8). Independent variables included sociodemographics; mental health diagnoses; past-5-year substance use; cannabis use history, motives, and patterns; and concern about addiction or dependence. Bivariate analyses and multivariable logistic regression examined associations with possible CUD, with secondary analysis examining associations with any hazardous use.

Overall, 20% (95% CI: 17%-24%) had possible CUD) and 54% (95% CI: 50%-58%) had hazardous use. Possible CUD was significantly associated with younger age (aOR 0.98, 95% CI: 0.96-1.0), >1 year of daily marijuana use (1-5 years aOR 2.2 95% CI: 1.2-5.2; 6+ years aOR 3.1 95% CI: 1.5-7.2), lower preference for oral concentrates (aOR 0.29, 95% CI: 0.10-0.70), and self-reported recreational reasons for marijuana use (aOR 5.1, 95% 1.5-17.3). Possible CUD was not associated with sex, race/ethnicity, mental health conditions, or preferred THC percentage. Hazardous use was associated with >1 year of daily marijuana use, recreational reasons for use, younger age at marijuana use, greater preference for marijuana flower, and anxiety diagnosis. Few (4%) reported concern about addiction of dependence.

About 1 in 5 adults certified to use medical cannabis in Florida had possible CUD, and over half (54%) had hazardous use. Possible CUD was associated with younger age, prolonged daily use, lower preference for oral concentrates, and recreational motives for marijuana use.

Mental health services are facing unprecedented demand, placing significant pressure on clinicians to conduct timely and effective patient assessments. Rising staff turnover and burnout threatens service quality across many countries. This study examined whether providing clinical information, collected via an artificial intelligence (AI)-enabled decision support tool for mental health assessments in the UK's National Health Service (NHS), was associated with differences in clinician wellbeing and patient assessment performance.

In this observational study, we surveyed mental health clinicians (N = 131) from nine NHS Mental Health Talking Therapies services on how the information provided by an AI-based decision-support tool related to their experience with conducting clinical assessments. Clinicians reported on assessments where information from the AI tool was available, as well as when it was not (e.g., general practitioner referrals or telephone intakes). Outcomes included clinician wellbeing, task performance, and cognitive load during assessments, with additional analyses assessing the influence of moderating factors, such as clinician experience, workload, and exposure to the tool.

Relative to traditional methods, assessments supported by information provided by the AI tool were associated with significantly higher clinician wellbeing and task performance, and significantly lower cognitive load, irrespective of the clinician's experience. These associations were magnified by workload.

These findings provide preliminary evidence that AI-powered pre-assessment tools may be associated with differences in clinician experience including higher wellbeing, higher task performance, and lower cognitive burden. By targeting systemic drivers of burnout, such tools may represent a potentially scalable approach to support workforce sustainability and service quality in mental health care.

Mental health disorders are becoming increasingly prevalent, making early detection and intervention crucial. However, stigma remains a significant barrier to accessing mental healthcare services. This study aimed to translate and culturally adapt the Persian version of the Stigma and Self-Stigma Scales (SASS) to assess public attitudes toward mental health issues.

This methodological study was conducted from August to December 2023 with a sample of 962 Iranian participants. The research evaluated the psychometric properties of the SASS. The assessment included content validity, face validity, and construct validity (confirmatory factor analysis (CFA)) and reliability indices.

The Scale-Content Validity Index (S-CVI/Ave) for all SASS items was excellent at 0.963. Following psychometric evaluation, seven items were eliminated. Confirmatory factor analysis demonstrated adequate model fit, with key indices including: χ²/df = 3.325, RMSEA = 0.049, CFI = 0.912, GFI = 0.920, IFI = 0.912, PNFI = 0.777, PGFI = 0.759, TLI = 0.901, and AGFI = 0.903. The final validated scale comprised 29 items organized into six distinct factors: Stigma toward others (4 items), Social distance (6 items), Anticipated stigma (6 items), Self-stigma (6 items), Avoidant coping (3 items), Help-seeking behaviors (4 items). The Persian SASS demonstrated overall acceptable reliability across its subscales (Cronbach's α = 0.911, McDonald's ω = 0.925) and acceptable test-retest reliability (ICC = 0.677) except one of the subscales (help-seeking behaviours), which had inadequate reliability and is recommended not to be used.

The Persian adaptation of the SASS was successfully validated as a 29-item instrument comprising six clinically relevant dimensions. This culturally adapted tool demonstrates acceptable psychometric properties for comprehensive stigma assessment in Persian-speaking populations. Its multidimensional structure makes it particularly valuable for: Baseline evaluation prior to anti-stigma interventions, Measuring specific stigma components in clinical and research settings and Tracking changes in public attitudes toward mental health.

Whether intravenous tenecteplase prior to endovascular treatment (EVT) for ischemic stroke reduces disability in the late time window is unclear.

To investigate the adverse events and efficacy of tenecteplase prior to EVT in patients 4.5 to 24 hours after ischemic stroke onset due to proximal middle cerebral artery (MCA) occlusion.

Multicenter, phase 3, randomized, open-label, blinded end point, superiority trial conducted at 40 centers in China. Adult (≥18 years) patients with acute ischemic stroke 4.5 to 24 hours after last known to be well due to MCA-M1 or proximal M2 occlusion with salvageable brain tissue (ischemic core volume <70 mL, mismatch ratio ≥1.8, and mismatch volume ≥15 mL) identified on computed tomography-perfusion or magnetic resonance-perfusion-diffusion imaging were enrolled from January 25, 2024, through July 21, 2025, and followed up for 90 days. Final follow-up occurred on October 14, 2025.

Eligible patients were randomly assigned in a 1:1 ratio to receive intravenous tenecteplase (0.25 mg/kg; maximum dose, 25 mg) before EVT (n = 199) or EVT alone (n = 192).

The primary outcome was functional independence, defined as a score of 0 to 2 on the modified Rankin Scale (range, 0-6, with higher scores indicating greater disability) at 90 days. Adverse events outcomes included symptomatic intracranial hemorrhage and death.

All of the 391 patients enrolled (median age, 68 years [IQR, 59-75]; 155 [39.6%] females) completed the trial. Functional independence at 90 days occurred in 88 patients (44.2%) in the tenecteplase before EVT group and 83 patients (43.2%) in the EVT alone group (adjusted relative rate, 1.01 [95% CI, 0.83-1.24]; P = .89; risk difference, 0.99% [95% CI, -8.84% to 10.83%]). Mortality within 90 days was 12.7% (25/197) in the tenecteplase before EVT group and 14.2% (27/190) in the EVT alone group. Symptomatic intracranial hemorrhage within 36 hours was 5.1% (10/197) and 2.6% (5/190), respectively.

In patients presenting to EVT-capable centers 4.5 to 24 hours after stroke onset with proximal MCA occlusion, intravenous tenecteplase before EVT did not improve clinical outcomes vs EVT alone.

ClinicalTrials.gov Identifier: NCT06221371.

The therapeutic effects of rTMS may be mediated, at least in part, by the neuroendocrine mechanism. The present study was designed to investigate whether baseline hormone concentrations predict clinical response to rTMS in schizophrenia.

This is a secondary analysis of 84 patients with schizophrenia enrolled in a previously published randomized, sham-controlled trial. All participants completed 30 sessions of highfrequency rTMS applied to the left dorsolateral prefrontal cortex. We assessed cognitive functioning before and after prefrontal rTMS intervention. Blood hormone levels were determined in the hospital laboratory.

High-frequency rTMS showed a significant improvement in immediate memory relative to sham. At baseline, there was no difference in hormone levels between the real and sham rTMS groups. However, baseline prolactin (PRL) levels were positively associated with rTMS efficacy in the real rTMS group, and patients with higher baseline PRL levels showed greater improvement in immediate memory than those with lower levels. Linear regression analysis adjusting for age, symptom severity, baseline immediate memory, antipsychotic dosage, and types revealed that PRL at baseline was a predictor of the response to rTMS in patients with schizophrenia. No other hormone predicted cognitive outcome.

Our findings suggest a potential role for PRL levels in predicting rTMS efficacy, particularly in improving immediate memory in patients with schizophrenia, providing further evidence for the individualisation of future rTMS treatments.

Our findings suggest a potential role for PRL levels in predicting rTMS efficacy, particularly in improving immediate memory in patients with sc.