Mental health issues, especially depressive symptoms, among young adults represent a public health challenge. Conventional psychological assessment tools have limited sensitivity and specificity for identifying individuals at risk. This study aims to develop an explainable machine learning-based model to stratify concurrent depression risk in young adults. This study included 100,257 college students and collected mental health variables including depression, anxiety, resilience, parent-child relationship, and duration of mobile phone usage. The screening capabilities of 13 machine learning algorithms were systematically evaluated and compared. The SHapley Additive exPlanations (SHAP) framework was employed for the interpretability of the final model. The median scores for parent-child relationship, resilience, anxiety, and mobile phone usage time was 42.0, 28.0, 1.0 and 28.0, respectively. Among the 13 machine learning algorithms, the XGBoost model demonstrated superior performance. The final multivariate screening model achieved an area under the curve (AUC) of 0.887, a sensitivity of 0.787, a specificity of 0.830, and an accuracy of 0.816 in classifying young adults' concurrent depression risk. The SHAP analysis showed the importance of each variable: anxiety (2.303) > resilience (0.774) > parent-child relationship (0.708) > mobile phone usage time (0.411). The final multivariate model exhibited stable performance during cross-validation (AUC = 0.885 ± 0.032), significantly better than the single-variable model (P < 0.001) and better screening reliability (Brier score 0.153). The final multivariate XGBoost model provides a highly accurate and interpretable approach for young adults' depression risk stratification. As the model was developed using cross-sectional data collected during the COVID-19 campus lockdown, prospective validation is required before clinical deployment. Notably, anxiety level emerged as the most influential risk factor, and resilience demonstrated a significant protective effect.

Addiction is a brain disorder marked by profound inter-individual heterogeneity, a factor that limits the clinical utility of group-level neuroimaging findings.

To address this, we constructed a precision neuroimaging framework to capture individual variability. We quantified gray matter volume (GMV) deviations in 464 individuals with five substance-related and addictive disorders using a normative model derived from over 1000 healthy controls. Subsequently, we applied a dimensionality reduction technique to decompose these individual deviations into distinct spatial patterns.

We observe a shared pattern involving the insula and prefrontal cortex that reflects common underlying biology across different addictions. In contrast, a pattern centered on the basal ganglia captures the differences between specific addiction types. Importantly, only transdiagnostic factors correlated with clinical measures, whereas the heterogeneity factor did not.

By resolving neurobiological heterogeneity into distinct, structural atrophy subtypes, this framework offers insights into understanding structural heterogeneity as a local effect of common networks.

Post-stroke fatigue (PSF) is a persistent and debilitating condition. Assessing its characteristics and severity accurately is important, but the suitability of existing fatigue instruments for use in stroke populations is uncertain. The Chalder Fatigue Questionnaire (CFQ) is a widely used generic measure capturing both mental and physical fatigue, but the dimensionality of the 11-item CFQ is debated. The objective of this study was to examine the best-fitting model for the CFQ and evaluate whether the addition of latent specific factors for the physical and mental items provided meaningful information beyond the latent general fatigue score.

We examined three competing measurement model of the CFQ - unidimensional, correlated two-factor (physical and mental fatigue) and a bi-factor model in a sample of 144 individuals at 4 years post-stroke. Furthermore, we investigated how other criterion-related variables correlated with the estimated CFQ factor scores compared with the simple CFQ.

The bi-factor measurement model had best fit. Partial correlation analyses indicated that a simple overall fatigue score aligns relatively well with the estimated general factor score, as does the physical sum score. This indicates that separate physical and mental sum scores provide no additional value, whereas their estimated latent specific factors contribute more information. Men reported less fatigue, and except for gender most of the demographic variables were not significantly correlated with the CFQ variables.

Despite best psychometric support for a bi-factor measurement model, a simple overall sum score may be used to assess fatigue severity satisfactorily. While separate physical and mental factors provide noteworthy nuance, their contribution is in practice limited. Future research should consider refining the mental fatigue items if a more precise assessment or a more nuanced clinical applicability of the physical-mental separation following stroke is needed.

Cannabis use is highly prevalent among people with bipolar disorder, potentially due to a desire to self-medicate against symptoms, such as racing thoughts and poor concentration. Such symptoms are associated with attention and inhibitory control deficits, functions that are regulated in-part by temporal perception. Temporal perception is impaired in BD and is slowed by acute cannabis exposure. The effects of cannabis use (CU) on temporal perception and its associated cognitive functions in people with BD remains unclear. Here, we conducted two studies to 1) test for associations between chronic CU and cognitive function (i.e., attention and inhibitory control) and temporal perception in people with BD and healthy comparison (HC) adults, and 2) investigate the impact of acute Δ9-tetrahydrocannabinol (THC) administration on such functions in a randomized clinical trial in non-CU people with BD and HC adults. Participants completed the Temporal Discrimination Task (TDT) and 5-Choice Continuous Performance Task (5C-CPT). In the chronic CU study, we observed that non-CU BD participants had significantly less precise timing compared to other groups, whereas BD + CU participants had comparable TDT performance to non-CU HC participants. Similarly, BD + CU, but not non-CU BD, participants had comparable 5C-CPT performance to non-CU HC. In the acute THC administration study, we observed faster timing in BD participants administered THC compared to placebo-treated HC participants. These data support that CU in people with BD reflect attempts to self-medicate. Future research will investigate whether cannabinoid-based treatments can remediate cognitive deficits in BD.

The development of young children's emotional competence not only affects their current mental health and well-being but also has a profound impact on their future socialization, learning ability, and overall quality of life, and the relationship between parenting styles and young children's emotional competence has attracted the attention of researchers. A total of 713 parents completed measures of parenting styles, toddler parent-child attachment, young children's working memory, and young children's emotional competence using questionnaires in this study. The mediating role of young children's working memory between parenting styles and young children's emotional competence and the moderating role of parent-child attachment quality therein were examined through the construction of a moderated mediation model. First, negative parenting styles (doting, permissive, authoritarian, and inconsistent) negatively predicted young children's emotional competence, and democratic parenting styles were significant positive predictors of young children's emotional competence; Second, young children's working memory plays a partial mediating role between parenting styles (doting, democratic, permissive, authoritarian, inconsistent) and young children's emotional competence; Third, parent-child attachment quality moderates the mediating pathway from negative parenting styles to young children's emotional competence through young children's working memory. That is, high parent-child attachment quality can somewhat mitigate the negative effects of negative parenting styles on young children's working memory capacity and young children's working memory on their own emotional capacity; However, when parents adopt a democratic parenting style, the second half of the mediating pathway is moderated by parent-child attachment quality. That is, low parent-child attachment quality reinforces the negative predictive effect of young children's working memory on their own emotional competence. The impact of parenting styles on young children's emotional competence and the importance of cognitive functioning and parent-child attachment in that relationship are emphasized. These findings provide ideas on how to promote emotional competence in young children from a cognitive and attachment perspective.

Post-COVID-19 syndrome (PCS) is an escalating global health concern, marked by persistent cognitive, neurological, and psychiatric symptoms following acute SARS-CoV-2 infection. Although its underlying mechanisms remain incompletely understood, mounting evidence implicates chronic neuroinflammation as a key driver. Sustained microglial and astrocyte activation, blood-brain barrier disruption, and aberrant cytokine signaling contribute to prolonged immune dysregulation within the central nervous system, promoting long-term brain dysfunction. In this expert review, we synthesize emerging insights into how neuroimmune processes impair brain function in PCS. We explore novel mechanistic pathways - including local sleep intrusions, impaired memory reconsolidation, and astrocyte-mediated destabilization of functional networks - that may underlie the syndrome's fluctuating and heterogeneous presentation. We evaluate fluid biomarkers of neuroinflammation, including glial fibrillary acidic protein (GFAP), soluble TREM2, S100β, and pro-inflammatory cytokines such as interleukin-6 and tumor necrosis factor-α. In parallel, we highlight converging neuroimaging biomarkers derived from PET and MRI studies. These include increased TSPO-PET binding in limbic and frontal regions, alterations in cerebral blood flow and oxygen metabolism, neurometabolic changes detected via MR spectroscopy (e.g., elevated myo-inositol and choline), and increased free water content on diffusion imaging - each suggestive of glial activation and network-level dysfunction. We propose a multiscale, longitudinal framework that integrates molecular, neuroimaging, and behavioral data to link immune dysregulation with brain network instability and symptom emergence. Such integrative approaches are critical for advancing precision diagnostics and informing the development of targeted, mechanism-based treatments for individuals affected by PCS.

Neurological and psychiatric disorders frequently arise from dysfunctional deep-brain circuits, yet targeting these subcortical structures with conventional non-invasive neuromodulation remains a significant challenge due to the lack of focal precision at depth. Temporal Interference (TI) stimulation has emerged as a transformative paradigm, leveraging the intersection of multiple high-frequency electric fields to generate a low-frequency amplitude-modulated envelope within deep-seated targets. This biophysical strategy enables the modulation of subcortical dynamics while minimizing the activation of overlying cortical tissues. Emerging preclinical evidence demonstrates that TI can robustly orchestrate neurotransmitter release, facilitate synaptic plasticity, and ameliorate deficits in both motor and cognitive domains. Preliminary clinical translations further underscore its potential in enhancing memory precision, accelerating motor skill acquisition, and suppressing epileptic biomarkers. The mechanistic understanding of TI has evolved from passive low-pass filtering to include nonlinear ion-channel rectification and, more recently, network-mediated inhibition-particularly the recruitment of parvalbumin-positive interneurons in superficial layers-as a critical determinant of spatial selectivity. Human intracranial studies have further refined this framework, revealing that TI operates in a subthreshold regime, produces carrier-independent deep modulation, and elicits a sustained carry-over effect absent from unmodulated kilohertz stimulation. The efficacy of TI is fundamentally governed by a complex interplay of controllable parameters-including carrier frequency offset (Δf), current intensity, electrode geometry, and timing-alongside uncontrollable factors such as individual anatomical heterogeneity and endogenous brain states. Furthermore, advanced computational modeling, particularly finite element simulations incorporating personalized head models, has become indispensable for characterizing electric field distributions and achieving individualized, high-precision targeting. This review provides a comprehensive synthesis of TI's mechanistic foundations, safety profiles, and therapeutic trajectory, while critically discussing the integration of closed-loop systems, multi-target paradigms, and patient-specific optimization as the next frontiers in non-invasive deep brain stimulation.

Depression is a leading cause of global disability, and identifying modifiable lifestyle factors is a public health priority. We conducted a systematic review and dose-response meta-analysis of prospective cohort studies examining the association between fruit and vegetable intake and incident depression. PubMed, Web of Science, Scopus, Embase, and Google Scholar were searched through November 2025. Data on study characteristics, dietary assessment, outcomes, effect estimates, and covariates were independently extracted by two reviewers. Random-effects models were used to calculate pooled relative risks (RRs), and linear and non-linear dose-response relationships were assessed. Heterogeneity was evaluated using I², and evidence certainty was rated with GRADE. Thirteen cohorts with 385,449 participants and 26,592 depression cases were included. Highest versus lowest combined fruit and vegetable intake was associated with a 37% lower risk of depression (RR: 0.63; 95% CI: 0.50, 0.80). Each 200 g/day increase corresponded to a 16% risk reduction (RR: 0.84; 95% CI: 0.74-0.94). Separate analyses showed that fruit and vegetable intake reduced depression risk by 16% and 12%, respectively, with a non-linear dose-response for vegetables. These findings indicate that higher consumption of fruits and vegetables is associated with lower depression risk, supporting dietary strategies as a potential approach for mental health prevention. However, given the observational nature of the included studies, these results should be interpreted with caution, as residual confounding may partially account for the observed associations. Registration: This study was registered at PROSPERO (CRD420261279998).

Vitamin B12 deficiency during pregnancy and lactation is common, yet its mechanistic impact on reproductive outcomes and offspring health remains poorly understood. Here, we show that maternal dietary vitamin B12 deprivation not only impairs maternal glucose metabolism and reproductive outcomes but also exacerbates high-fat-diet-induced obesity in offspring. These effects are mediated by gut microbiota and associated with a marked reduction of Bifidobacterium pseudolongum (B. pseudolongum) in both dams and their offspring. Maternal vitamin B12 deprivation limits early-life acquisition of B. pseudolongum in offspring during lactation, subsequently intensifying obesity and metabolic dysregulation. Early-life restoration of B. pseudolongum or its key metabolite, acetate, effectively ameliorates this aggravated obesity. Mechanistically, acetate acts through the Ffar2 receptor to upregulate Ehhadh expression. Together, these data establish that perinatal nutrition imprints long-term metabolic phenotypes in offspring via early-life acquisition of the gut microbiota, with a critical window during lactation.

Intrahospital transport (IHT) of critically ill patients for magnetic resonance (MR) imaging is a high-risk procedure that combines physiological vulnerability with MR-specific hazards. While technical guidelines and checklists exist, less is known about how MR safety is accomplished in everyday clinical practice when critically ill patients undergo MR imaging. This study aimed to explore how MR safety is enacted during IHT.

A multisite focused ethnographic design was employed. Fourteen in-person observations were conducted across eight hospitals in Sweden and Portugal. Observations followed critically ill patients from ICU preparation through transport, MR scanning, and return to the ICU. Data consisted of field notes and analysis was conducted using inductive thematic analysis.

MR safety emerged as a dynamic, context-dependent accomplishment rather than a fixed protocol. Three themes were identified: (1) the use of written, mental, and visual checklists and time-out procedures to coordinate safety work; (2) adaptation to spatial configurations and zoning practices shaping workflows and risk boundaries; and (3) managing uncertainty related to implants, devices, and incomplete information. Safety was continuously negotiated through interprofessional collaboration, experiential knowledge, and situational judgement, with gaps arising when communication, documentation, or MR-specific expertise were insufficient.

MR safety during IHT of critically ill patients is enacted through the integration of structured tools, tacit knowledge, team coordination, and spatial adaptation under conditions of uncertainty. Safety is achieved in action through collective, context-sensitive practices rather than sole reliance on protocols.

Radiographers play a central role in coordinating MR safety for critically ill patients. Strengthening layered safety strategies - combining checklists, time-outs, MR-specific education, and attention to spatial design - may reduce risk, support interprofessional collaboration, and enhance patient safety in MR practice.