ObjectiveThe study aimed to systematically evaluate the effects of music intervention on outcomes related to the recovery of consciousness in patients with disorders of consciousness (DOC).MethodsDatabases including PubMed, Web of Science, Embase, the Cochrane Library, China National Knowledge Infrastructure (CNKI), and ProQuest were systematically searched from January 1970 to December 2025 to identify relevant randomized controlled trials (RCTs). The literature was screened based on pre-established inclusion and exclusion criteria, and the review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The methodological quality of the included studies was assessed using the Cochrane Risk of Bias tool (RoB 1).ResultsA total of 12 randomized controlled trials (RCTs) involving 926 patients with disorders of consciousness (DOC) were included. As the types of outcome indicators reported in the included studies varied, the number of studies included for each outcome also differed. Specifically, five studies were included in the analyses of Glasgow Coma Scale (GCS) scores and the GCS-based awakening rate, whereas two studies were included in the analyses of GCS scores of > 8, the Coma Recovery Scale-Revised (CRS-R), and the National Institutes of Health Stroke Scale (NIHSS). A meta-analysis showed that GCS scores were significantly higher in the music intervention group than in the control group (mean difference (MD) = 2.32). The analyses of GCS scores of > 8 showed that a higher proportion of patients in the music intervention group achieved a GCS score of > 8 (odds ratio (OR) = 5.98). The awakening rate also indicated that the music intervention group was significantly superior to the control group (OR = 3.76). For secondary outcomes, the music intervention group showed higher CRS-R scores (MD = 2.86) and lower NIHSS scores (MD = −1.24).ConclusionMusic intervention may help improve consciousness levels and awakening-related outcomes in patients with disorders of consciousness and may serve as a safe and non-invasive adjunctive measure in rehabilitation nursing care. However, more high-quality randomized controlled trials are needed to further verify its effects and mechanisms.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD420261354569, Identifier: CRD420261354569.
Identifying and investigating emergent behaviour in neural systems
The concept of emergence is key to understanding much of neurophysiology, neurodevelopment, and neurodegeneration. Many brain functions are underpinned by behaviour that emerges from interactions of components such as neurons, synapses, and glia. Perturbations such as ion channel mutations or trauma can lead to new types of, often detrimental, emergent behaviour. Typical approaches to neuroscience involve studying neural behaviour in a range of in vitro, in vivo, and in silico models designed to capture the key components of the brain region under investigation. Translating from these models back to the brain requires that the component interactions within the models can be mapped onto interactions in the brain. However, in many cases, this may not hold, leading to emergent behaviour that is not derivable from knowledge of the brain components in relative isolation. We thus need a framework that respects the prospective system-dependent differences in interactions. In this manuscript, we distil theoretical approaches to emergence into a practical framework for assessing system behaviour focussed on “novelty” as a necessary condition for emergence and identify a range of ways in which novelty can arise. We consider how different approaches for investigating system behaviour can be applied in different contexts and when these might fail. We provide examples of different forms of novelty in neuroscience contexts and then apply the framework to understanding the specific case of epilepsy. We end by outlining a set of guiding principles for designing experiments and models for understanding emergent behaviour in neural systems.
Identification and validation of mitophagy and astrocyte-related molecular signature in the pathogenesis of Alzheimer’s disease: evidence from ensemble learning-driven multi-omics and clinical validation
BackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder with limited diagnostic tools and therapeutic options. Dysregulated mitophagy in astrocytes plays a pivotal role in AD pathogenesis. This study aims to identify a mitophagy and astrocyte (MA)-associated molecular signature for AD diagnosis and therapeutic targeting.MethodsLimma, WGCNA, xCell, PPI network and integrated machine learning pipeline coupled with SHAP were deployed on AD patient hippocampal bulk profiles (GSE28146, GSE36980, GSE29378, GSE48350) for identification of MA-associated predictive model and hub gene. Next, astrocyte patten and MA-associated hub gene molecular performance were estimated in hippocampal single-cell profile of AD patients (GSE163577) via advanced analytical frameworks. In addition, active learning framework and molecular docking was deployed in GSE29378 for identification of therapeutic candidate for AD patients by targeting MA-associated hub gene. Furthermore, AD hippocampal tissues were collected, and then MA-associated hub gene expression was estimated.ResultsA core 8-gene MA signature (ITSN1, VLDLR, CYP7A1, SREBF2, RASL12, TPMT, CYP4X1, ARHGEF) was identified, which can guide the molecular subgroup identification and predictive model construction for AD patients. ITSN1 can be considered as the MA-associated hub gene in AD pathogenesis, which was up-regulated and predominantly expressed in astrocytes. Drug repositioning identified BRD-K10008415 as the potential compound predicted to reverse the AD signature by targeting ITSN1.ConclusionsThis study identified ITSN1 as a MA-associated critical hub potential connecting mitophagy dysregulation and astrocyte dysfunction in AD. We also identified MA-associated molecular signatures that can potentially elaborate predictive effects on AD pathogenesis. BRD-K10008415 can be considered as potential candidate for AD treatment by targeting ITSN1.
The associations between emotional neglect and positive mental health: the mediating role of stress-is-enhancing mindset and the moderating role of stress-is-debilitating mindset
ObjectiveThis study aimed to investigate the associations among emotional neglect (EN), stress-is-enhancing mindset (SIEM), stress-is-debilitating mindset (SIDM), and positive mental health (PMH).MethodsThe cross-sectional survey was employed in this study. A sample of 2150 college students (826 males) completed the emotional neglect subscale of the Childhood Trauma Questionnaire Short Form, the Stress Mindset Measure and the Positive Mental Health Scale. The PROCESS macro version 4.2 for SPSS was used to examine the moderated mediation model.ResultsEN negatively predicted PMH (p < 0.001). SIEM mediated the association between EN and PMH. Moreover, SIDM (β = 0.04, p < 0.001) not merely moderated the relationship between EN and PMH, but also moderated the link between EN and SIEM (β = 0.04, p < 0.001).ConclusionEN has a direct negative link to PMH and an indirect negative link to PMH through SIEM. Importantly, high SIDM mitigates the direct negative relation between EN and PMH. Moreover, the indirect negative effects of EN on PMH via SIEM diminish as SIDM increases, and the mediation pathway of SIEM is neutralized under high SIDM. These findings preliminary reveal the interplay between SIEM and SIDM in post-traumatic cognitive processing, offering new insights into the non-linear processes of psychological adaptation following early adversity.
Cross-national comparisons of adolescent mental health and suicidality in the Middle East: a cross-sectional secondary analysis of the global school-based student health survey
BackgroundAdolescent mental health and suicidality represent growing global public health concerns, yet comparative evidence from the Middle East remains limited. This study examined the prevalence and correlates of psychological distress and suicidal behaviors among adolescents across Middle Eastern countries using the Global School-based Student Health Survey (GSHS).MethodsA cross-sectional analysis of nationally representative GSHS datasets from 12 Middle Eastern countries collected between 2004 and 2017. The pooled sample included 90,573 school-attending adolescents aged 11–18 years. Multivariable logistic regression models assessed associations between psychosocial factors and suicidal behaviors while adjusting for age, sex, and country.ResultsSubstantial cross-country variation in mental health indicators and suicidality was observed. Loneliness ranged from 11.5% in Bahrain to over 50.0% among female adolescents in Tunisia and Morocco. Suicidal ideation affected 16.3% of adolescents overall, while suicide planning was reported by 13.4%. Suicide attempts were reported by 9.1% of adolescents at least once. Female adolescents consistently reported higher levels of loneliness and anxiety, whereas males showed slightly higher adjusted odds of suicidal ideation and attempts (OR = 1.2). Lack of parental support, low school connectedness, and fewer friendships were significantly associated with higher odds of suicidal ideation, planning, and attempts. Emotional symptoms such as loneliness (OR = 1.7) and anxiety (OR = 1.8) were also strongly associated with suicide attempts.ConclusionsPsychological distress and suicidality are prevalent among adolescents across the Middle East, with notable gender and cross-country differences. Strengthening family support, peer relationships, and school connectedness should be central to regional adolescent mental health and suicide prevention strategies.
NeuroCon-AutismNet: a privacy-preserving multimodal framework toward autism screening via diffusion-regularized EEG biomarkers and empathy-aware multilingual dialogue
IntroductionAutism Spectrum Disorder (ASD) screening requires multimodal biomarkers to capture the heterogeneous neurological and behavioral phenotypes. Current screening approaches remain siloed across EEG analysis and conversational assessment, limiting integrated diagnostic architecture. Privacy-preserving machine learning frameworks for mental health screening are underdeveloped, particularly for multilingual deployment contexts. This paper presents NeuroCon-AutismNet, a candidate multimodal architecture integrating diffusion-regularized EEG synthesis, multilingual conversational screening, and formal differential privacy as architectural proof-of-concept. No diagnostic discrimination capability is claimed; all validation is scoped to synthetic evaluation.MethodsNeuroCon-AutismNet comprises four modules: (1) Temporal Diffusion Biomarker Generator (TDBG), a latent diffusion model over VAE-encoded 19-channel EEG; (2) Multilingual Affective Dialogue Screening Network (MADSN), a fine-tuned GPT-2-small module deployed in English, Spanish, and Hindi; (3) Neuro-Linguistic Fusion Transformer (NLFT), enforcing positional alignment as a design prior rather than learned cross-modal association; and (4) Adaptive Mixture-of-Experts Layer (AMEL-X) for entropy-regularized multimodal fusion. Formal (ε, δ)-differential privacy (ε = 1.0, δ = 1e-5) is verified via DP-SGD RDP composition (σ = 1.2, q = 0.0914, T = 550 steps, verified ε = 0.97). Privacy verification establishes architectural readiness for future real-data deployment; no real patient records are present in the training set.Results and DiscussionWithin closed synthetic evaluation, held-out diagnostic AUC is 0.503 (95% CI: 0.487–0.519, DeLong p = 0.67), statistically indistinguishable from chance and the central limitation of this study. Two partial external benchmarks are provided. Spectral comparison against three independently published real ASD EEG studies yields Pearson r = 0.87 across five frequency bands; delta and alpha directions are reproduced, but theta and gamma reproduce poorly with large amplitude errors (delta MAE 14.79%, alpha MAE 11.57%). Expert evaluation of MADSN outputs by 50 annotators under single-blind protocol yields 90% empathy satisfaction and Cohen’s κ = 0.82, reflecting text quality rather than clinical screening validity. The null diagnostic AUC and synthetic-only evaluation prevent any current screening or clinical-utility claims. Real-data EEG validation, clinician-caregiver interaction studies for MADSN, and DP-protected training on real patient records are prerequisites for future clinical deployment.
From emotion regulation to suicide-specific coping: a qualitative study of self-regulatory processes in suicidal crises
IntroductionNegative affect is strongly associated with suicidal thoughts and behaviors (STBs). Accordingly, the ability to regulate intense negative affective states may be central to understanding the emergence and maintenance of STBs. However, very little is known about how individuals with lived experience regulate negative affect and cope with suicidal thoughts and urges. This study aimed to explore emotion-regulation strategies (ERS) and suicide-specific coping strategies (SCS) used during suicidal crises, their perceived effectiveness, and the situational and contextual factors influencing their selection.MethodsSemi-structured interviews were conducted with 12 individuals admitted to a psychiatric hospital due to an acute suicidal crisis. Data were analyzed using qualitative content analysis.ResultsBefore and during suicidal crises, participants predominantly used avoidance-oriented ERS that contributed to the maintenance of negative affect. With increasing distress, suicidal thoughts emerged as an additional ERS, providing short-term relief while contributing to the intensification of the suicidal crisis over time. A broad range of SCS was identified, differing in their motivational orientation toward suicidal behavior. Suicide-approach strategies (e.g., suppression, substance use, preparatory behaviors) often facilitated the escalation of the suicidal crisis, whereas suicide-avoidant strategies (e.g., seeking support, safety strategies) were context-dependent and not consistently effective. Strategy selection and effectiveness were shaped by situational and contextual factors.ConclusionSuicidal crises can be understood as dynamic, context-dependent self-regulatory processes characterized by escalating emotional distress, changes in strategy use, and dynamic regulatory resources. Interventions should focus on strengthening flexible coping repertoires and preserving self-regulatory capacity. Future research should further investigate these processes to improve prevention and intervention efforts.
Big Five personality profiles, self-reported distress, and resilience resources among adults in Italy after the acute COVID-19 emergency: a cross-sectional cluster-analytic study
IntroductionPsychological recovery after the acute COVID-19 emergency has been uneven, and brief non-diagnostic markers that stratify vulnerability may support public mental health monitoring. We examined whether person-centered Big Five profiles differentiated self-reported distress and resilience resources among adults living in Italy after the end of the World Health Organization-declared COVID-19 public health emergency.MethodsThis cross-sectional anonymous online survey included 2,169 adults assessed between 22 May 2023 and 23 December 2024. Participants completed the Big Five Inventory-10 (BFI-10), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Perceived Stress Scale-10 (PSS-10), and Resilience Scale for Adults-11 (RSA-11). Standardized Big Five scores were clustered using k-means, and the number of profiles was evaluated using elbow, silhouette, and hierarchical-clustering methods.ResultsA two-profile solution was retained, although separation was modest (average silhouette width = 0.185). Compared with the resourceful trait profile (n = 1,113), the vulnerable trait profile (n = 1,056), characterized especially by lower emotional stability and conscientiousness, reported higher anxiety symptoms (g = 0.74), depressive symptoms (g = 0.76), and perceived stress (g = 0.86), and lower resilience resources (g = −1.02; all p < 0.001).DiscussionBrief person-centered Big Five profiling differentiated adults with greater self-reported symptom burden and fewer resilience resources in a prolonged post-emergency context. These findings are non-diagnostic and do not establish COVID-specific causal mechanisms, but may inform vulnerability stratification during future prolonged crises.
AI-based clinician decision support system for diagnosis of inherited retinal diseases: a multicenter, randomized trial
Nature Medicine, Published online: 24 July 2026; doi:10.1038/s41591-026-04545-w
Retina4IRD, an AI-based clinician decision support system, enhances inherited retinal disease diagnosis through multimodal imaging and clinical data integration, achieving 88.5% accuracy in a randomized clinical trial.
Prospective validation of imaging and serum diagnostic biomarkers of steatohepatitis and fibrosis in MASLD: the LITMUS Imaging Study
Nature Medicine, Published online: 24 July 2026; doi:10.1038/s41591-026-04496-2
In the LITMUS study, serum biomarkers outperformed imaging for identifying patients at risk of MASH, whereas elastography was superior for staging advanced fibrosis and cirrhosis.