Subthreshold depressive symptoms significantly hinder functional recovery in bipolar disorder (BD). While most studies use a global score to assess the impact of these symptoms on functioning, this study examines which specific subthreshold depressive symptoms mostly impede functional recovery in patients with BD in remission.

The sample comprised a total of 413 patients with BD. Subthreshold depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale (HAM-D), and psychosocial functioning was measured with the Functioning Assessment Short Test (FAST). Bivariate analyses were performed to identify items from the HAM-D as well as other clinical and demographic variables associated with functional impairment. Multivariate linear regression analyses were conducted including the variables that demonstrated significant associations in the bivariate analyses.

The linear regression model for the FAST total score demonstrated that "psychomotor retardation" (item 8) had the strongest association on psychosocial functioning (β = 6,9; p < 0,001), followed by "feelings of guilt" (item 2) (β = 5,75; p < 0,001) "work and activities" (item 7) (β = 5,38; p < 0,001) and "somatic anxiety" (item 11) (β = 3,45; p < 0,001). Other significant clinical variables included antipsychotic use, older age, fewer years of education and male sex. This model explained 39,6% of the variance in the FAST total score (R² = 0,396; Adjusted R² = 0,375; F_(399,13) = 20,04; p < 0,001).

Specific subthreshold symptoms, including psychomotor retardation, apathy, guilt and somatic anxiety significantly influence psychosocial functioning. These findings highlight the importance of specifically targeting these symptoms to achieve functional recovery, even when patients are clinically stable.

A wide array of operational and management practices characterizes the dairy farming landscape in Canada. This heterogeneity poses challenges in understanding the full range of dairy farming systems, which can lead to incomplete representations and less effective interventions aimed at improving the well-being of dairy farmers. This study aimed to holistically explore the relationship between dairy farmers' well-being and farm management practices. A multiple factorial analysis was used to group dairy farmers based on various factors, including demographic characteristics, mental and physical health outcomes, farming responsibilities, work-life balance, social environment and support, animal housing and management, and concerns about various dairy-related stressors. The analysis identified 4 distinct clusters of farmers defined by 66 significant variables. Key factors influencing the differences among the surveyed dairy producers included age, concern about finances, drought, public perceptions of the dairy industry, policies and regulations, farm responsibilities, satisfaction with professional relationships (such as those with veterinarians and feed representatives), and mental health outcomes. Despite the variations among the clusters, a common theme emerged: most participants selected finding more time for enjoyable activities and reducing their workload as ways to improve their well-being. The findings suggest that the nature of dairy farming and its associated responsibilities may often hinder farmers from achieving a healthy work-life balance. Furthermore, this study highlights the distinct challenges faced by various groups of dairy farmers. The typologies established in this research offer a promising foundation for providing tailored resources and support.

Cognitive impairment is a key yet understudied component of normal pressure hydrocephalus (NPH). Although gait and radiological markers are routinely assessed, neuropsychological outcomes remain inconsistently reported, and no standardized cognitive battery exists for evaluating patients before and after CSF shunt. This systematic review synthesizes available evidence on the cognitive trajectories of adults with NPH and identifies the neuropsychological tests that are most sensitive and clinically informative for monitoring outcomes following ventriculo-peritoneal (VPS) and lumbo-peritoneal shunt (LPS).

A systematic search of PubMed/MEDLINE and Web of Science identified studies reporting standardized neuropsychological assessments in adult NPH. Ten studies met inclusion criteria. Because statistical reporting varied across studies (means/SD vs medians/IQR), non-parametric data were harmonized into estimated means and SDs using validated transformation methods. Weighted means and pooled SDs were computed for each test and follow-up interval (T0, 3, 6, 12, 24 months), enabling comparison of cognitive trajectories across domains, with values rounded according to appropriate significant digit conventions to enhance clinical interpretability.

Across 537 baseline assessments, the Mini-Mental State Examination (MMSE) was most frequently administered, followed by Trail Making Test A (TMT-A), Trail Making Test B (TMT-B), Digit Span, Verbal Fluency, and the Frontal Assessment Battery (FAB). Aggregated results revealed modest domain-specific and time-dependent postoperative improvements. Global cognition (MMSE) improved steadily up to 12 months, psychomotor speed and attention (TMT-A) improved early, and executive functions (TMT-B, FAB) showed later gains peaking at 12 months. Working memory (Digit Span) and verbal fluency improved more variably and often later. Variability across studies was reflected in pooled SDs. Across measures, MMSE, TMT-A, TMT-B, and Digit Span were the most robust and sensitive indicators of postoperative cognitive change.

Cognitive recovery after shunt in NPH follows a predominantly fronto-subcortical pattern, with the greatest improvements occurring within the first postoperative year. MMSE, TMT-A, TMT-B, and Digit Span represent the most reliable and informative neuropsychological tools for pre- and postoperative evaluation and should constitute the core of a standardized NPH-specific cognitive battery. Establishing uniform testing protocols and improving methodological consistency across studies will enhance diagnostic accuracy, surgical decision-making, and long-term monitoring of this treatable condition.

Multiple sclerosis (MS) is a chronic neuroinflammatory disease that significantly impairs quality of life (QoL). Emerging evidence suggests that dietary patterns, particularly the Mediterranean diet (MD), may offer neuroprotective and anti-inflammatory benefits. However, data on the effect of MD adherence on QoL in MS patients remain limited. This study aims to assess the impact of adherence to the MD adherence on the QoL of patients with MS following a three-month nutritional counselling program.

This prospective study included 50 adult MS patients recruited from the National Institute of Neurology in Tunis. Participants received individualized nutritional counselling based on the MD and were followed for three months. MD adherence was assessed using the 14-item PREDIMED score, and QoL was measured using the SF-36 questionnaire. Anthropometric and dietary data were collected at baseline and at three months.

Mean PREDIMED scores increased significantly from 7.12 ± 1.96 to 12.68 ± 3.20 (p=0.035), indicating improved MD adherence. QoL also improved significantly (SF-36 global score: 47.72 ± 21.48 to 52.99 ± 38.94; p=0.014), especially in mental health, vitality, role-emotional, and social functioning subscales. A positive correlation was observed between the changes in PREDIMED and SF-36 scores. Multivariate analysis identified increased intakes of vitamins C, D, E, B6, B9, B12 and minerals such as magnesium, selenium, and iron as independent factors associated with QoL improvement, whereas the significant increase in omega-3 fatty acid intake was not identified as a predictor. Significant reductions in body weight, body mass index, and waist circumference were also noted.

Improved MD adherence was associated with better QoL and nutritional status in patients with MS. These findings support the potential inclusion of nutritional counselling in the overall management of MS. Further randomized controlled trials are needed to confirm these results and establish causality.

To evaluate the diagnostic performance of a radiomics-based machine learning approach applied to corneal optical coherence tomography (OCT) images for detecting forme fruste keratoconus (FFKC).

Evaluation of machine learning diagnostic algorithms.

OCT images from 307 eyes (234 normal, 73 FFKC) were acquired along eight meridians (M1-M8). All images underwent preprocessing before texture-based radiomics feature extraction. Three machine learning classifiers-Random Forest, C5.0, and XGBoost-were trained using a feature subset selected by Recursive Feature Elimination (RFE). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.

A total of 3,752 features were extracted per eye, of which 41 were selected for model training. All three models demonstrated strong diagnostic performance in the test set (AUCs > 0.92), with no significant differences between models (p > 0.05). The XGBoost model achieved the highest performance (AUC = 0.93, 95% CI: 0.829-1.0, sensitivity 0.857, specificity = 0.978, accuracy = 0.950). Among the top 10 XGBoost features ranked by importance, a preferred meridional distribution was observed, with most features concentrated along M1-M3, corresponding to the inferotemporal corneal region.

Radiomics analysis of corneal OCT images combined with machine learning enables accurate FFKC detection using a single imaging device, providing diagnostic information beyond conventional morphological assessment and suggesting a potential imaging biomarker for early keratoconus screening.

Radiomics analysis of optical coherence tomography images captures microscopic corneal texture features that complement routine clinical examinations. Integrating these features into machine learning models enables accurate identification of forme fruste keratoconus. This single device, noninvasive approach supports earlier detection and introduces a new perspective for characterizing subclinical corneal ectasia based on corneal microstructural texture.

The ways cannabis is consumed, or modes of use, have increased and diversified in recent years, especially among young people. Associations of multimodal cannabis use (1, 2, or 3+ modes) with adverse events were examined among adolescents and young adults.

Data from the 2022-2023 National Survey of Drug Use and Health, including non-institutionalized US civilians aged 12-25 reporting past-year cannabis use (n=13,284), were used. Cannabis users were asked about the type (smoking, vaping, dabbing, eating/drinking, and other) and number of cannabis modes used in the past year. Multivariable-adjusted analyses assessed associations of number of modes with adverse events, adjusted for sociodemographic characteristics and frequency of use.

Among 51,435 individuals (45.8% adolescents, 51.0% female, 48.1% non-Hispanic white), 13,284 (26.1%) reported past-year cannabis use. Individuals more frequently used 3+ modes (37.5%) than one (34.0%) or two (28.5%), with the most common being smoking (83.9%) followed by vaping (53.3%), eating/drinking (47.6%), and dabbing (27.3%). Individuals using 3+ modes were significantly more likely than single mode users to meet criteria for past-year moderate/severe cannabis use disorder (adjusted odds ratio [aOR], 5.00 [95% confidence interval, 3.99-6.27]), other substance use disorders (aOR, 4.43 [3.59-5.47]), severe mental illness (aOR, 2.18 [1.71-2.78]), major depressive episode (aOR, 2.04 [1.74-2.40]), suicidal thoughts (aOR, 1.80 [1.45-2.23]) and attempts (aOR, 1.70 [1.10-2.61]), poor academic performance (aOR, 1.78 [1.06-2.99]), and delinquent behaviors, especially impaired driving (aOR, 4.92 [4.07-5.94]). With the exception of suicide attempts and academic performance, all associations remained significant after adjusting for frequency of use.

Findings highlight a graded association between number of cannabis modes of use and adverse events. This association was independent of cannabis use frequency. In the context of increasing diversification of cannabis products, screening for number of modes of use may help identify young people at greater risk of cannabis-related harms.

Busy pediatric clinician educators face the dual challenge of staying current with evidence-based clinical practice and relevant medical education literature. To support them, there is a clear need for cohesive summaries of the current key studies in medical education that impact their teaching practices and/or their programmatic duties. In this narrative review, the Academic Pediatric Association Education Committee's Top Articles team summarizes high-yield articles from the medical education literature published in 2024 that have the potential to influence pediatric clinician educators' teaching and practice.

We applied a three-tiered screening approach utilizing a standardized, blinded rubric to identify the most impactful articles published from 19 journals that publish medical education research.

Of the 2491 articles reviewed, 10 (0.4%) were selected for inclusion. We categorized the final articles into six domains: Workforce, Undergraduate Medical Education Assessment, Graduate Medical Education Assessment, Bias, Mental Health, and Artificial Intelligence.

This review summarizes key findings from the 10 articles selected and describes implications for pediatric clinician-educator practice.

To assess and quantify the relationship between rumination and depression among adolescents, while also exploring the potential moderating factors that could influence this relationship.

PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang Data, CBM, and VIP were searched for records published from inception to February 28, 2024. Two researchers independently screened studies, extracted data, and assessed research quality. Meta-analysis was performed using Stata 17.0.

A total of 29 studies involving 24,087 adolescents were included. The meta-analysis, using a random-effects model, revealed a strong correlation of 0.61 (95% confidence interval [0.60, 0.62]) between rumination and depression. Subgroup analyses indicated that the correlation was stronger among middle school students, in female-dominated samples, in European studies, in developed countries, and in research published before 2015. In addition, studies with larger sample sizes showed a stronger correlation.

This meta-analysis confirms a significant correlation between rumination and depression in adolescents, suggesting that rumination may play a pivotal role in adolescent mental health. Findings provide crucial evidence for shaping effective prevention and intervention strategies aimed at mitigating depression in this vulnerable population.

Suicide is a major global problem, causing significant concern among adolescents and emphasising the urgent demand for effective prevention strategies. Adolescent suicide is also significantly influenced by risk factors such as parental involvement, alcohol consumption, and bullying. The purpose of this study was to examine the trends of suicidal behaviour among adolescents in the Philippines from 2011 to 2019, as well as the correlation between parental involvement, bullying, alcohol, and suicidal behaviour. The study included 21359 adolescents from three cross-sectional Global School-based Student Health Surveys (GSHS) in the Philippines (2011-2019). The findings indicated that the prevalence of suicidal ideation, suicide plans, and suicide attempts has increased from 2011 to 2019, and bullying victimisation and alcohol use are mediators in the relationship between parental involvement and suicidal behaviour. The study indicated that it is essential to implement mental health education programs in schools to decrease the risks related to suicide, bullying, and alcohol use among adolescents. Concurrently, the study also highlights the role of clinical psychologists and parents in the early intervention and prevention of suicidal behaviour and risk factors for adolescents.

CNS diseases are a prevailing cause of morbidity and mortality worldwide, and are influenced by environmental and biological factors, including genetic risk. Here, we generated genome-wide genetic data on a large cohort of brain tissue donors with in-depth clinical and neuropathological phenotyping, allowing for broad investigations into the risk and mechanisms of these neurological, neurodevelopmental, and psychiatric conditions. This resource consists of 9,663 donors with array-based genotyping and 9,543 donors with whole-genome sequencing completed. The clinical diagnoses of these donors include 148 central nervous system diseases clustered into 15 broad categories by International Classification of Diseases-10 (ICD-10) coding. These donors were collected by six repositories comprising the National Institutes of Health NeuroBioBank, with an average participant age of 60 years. While primarily older individuals of European descent, the cohort also contains younger donors and individuals from non-European backgrounds. Variants were detected in whole-genome sequencing (WGS), normalized and annotated to describe their functional impact, resulting in 171,121,209 unique variants and 1,078,774 non-silent variants. These raw and normalized data have been made available as a neurogenomics resource in the National Institute of Mental Health Data Archive (NIMH NDA) (nda.nih.gov), combined with donor-matched deep demographic and phenotypic data from the NeuroBioBank Portal (neurobiobank.nih.gov). To illustrate applications, we replicated the strong association observed in previous studies between pathogenic CAG nucleotide repeat expansions in the HTT gene with the clinical diagnosis of Huntington's disease, as well as associations of the APOE gene with Alzheimer's disease, and examined the association of polygenic risk scores with the three most common disease diagnoses in the cohort.