BackgroundAneurysmal subarachnoid hemorrhage (aSAH) is a devastating cerebrovascular disease associated with high rates of mortality and long-term disability. Early risk stratification is essential to guide personalized management. Systemic inflammation plays a key role in secondary brain injury after aSAH. The systemic inflammation response index (SIRI), a novel inflammatory marker combining neutrophil, monocyte, and lymphocyte counts, has shown prognostic value in multiple disorders, but its long-term prognostic role in aSAH remains unclear.ObjectivesThis study aimed to investigate the association between admission SIRI and 12-month unfavorable functional outcomes (modified Rankin Scale [mRS] ≥ 3) in patients with aSAH, verify its independent prognostic value, and construct a clinically useful prediction nomogram.MethodsA retrospective cohort study was performed including 258 patients with aSAH admitted between January 2021 and December 2024. Patients were divided into a favorable prognosis group (mRS 0–2, n = 158) and an unfavorable prognosis group (mRS ≥ 3, n = 100). Baseline characteristics, imaging indices including modified Fisher scale, laboratory parameters, and treatment data were collected. Multivariate logistic regression with forced entry was used to identify independent prognostic factors. Restricted cubic spline (RCS) analysis was applied to explore the non-linear relationship between SIRI and prognosis. A prediction nomogram was constructed and validated using temporal validation (training cohort n = 170; validation cohort n = 88). Model performance was evaluated using discrimination, calibration, and decision curve analysis.ResultsSIRI was significantly higher in the unfavorable prognosis group (p < 0.001). Multivariate analysis confirmed that SIRI (OR = 1.20, 95% CI: 1.08–1.34, p = 0.001), age, hypertension, GCS score ≤ 8, modified Fisher scale, and treatment modality were independent prognostic factors. RCS analysis demonstrated a non-linear relationship (P for nonlinearity = 0.020), with a clear threshold at SIRI = 4.36; the risk of unfavorable outcomes rose steeply above this cutoff. The nomogram showed excellent discrimination (AUC = 0.881 in training; 0.919 in validation) and satisfactory calibration. Decision curve analysis confirmed favorable clinical utility.ConclusionAdmission SIRI is an independent predictor of 12-month unfavorable functional outcomes in patients with aSAH. A threshold value of 4.36 can effectively identify high-risk patients. The SIRI-integrated nomogram provides accurate and individualized prognosis prediction across both training and temporal validation cohorts. This validated tool provides robust evidence to support clinical risk stratification and personalized decision-making.
Infant traumatic brain injury with a biphasic clinical course and late diffusion restriction: a case report
Traumatic brain injury (TBI) in young children can rarely exhibit a biphasic clinical course with delayed neurological deterioration. We report a 2-year-old boy who fell from 50 cm and briefly lost consciousness with vomiting, initially found to have a right frontotemporoparietal acute subdural hematoma (SDH) with midline shift but no brain contusions. After transient stabilization, he developed new left-sided limb weakness and status epilepticus on day 3 post-injury. Follow-up diffusion-weighted magnetic resonance imaging (DWI) revealed a characteristic “bright tree” pattern of bilateral subcortical white matter diffusion restriction with corresponding decreased apparent diffusion coefficient (ADC) values. Electroencephalography showed generalized slowing with interictal focal epileptiform discharges. The patient was managed with antiepileptic therapy and supportive care. He demonstrated steady improvement and achieved near-complete neurological recovery by 9-month follow-up. This biphasic presentation—early trauma and late-onset seizures with diffusion restriction—is consistent with Traumatic brain injury with a biphasic clinical course and late reduced diffusion (TBIRD). Early recognition of TBIRD is crucial, as it resembles acute encephalopathy with biphasic seizures and late diffusion changes, and likely stems from secondary excitotoxic injury. Timely intervention in our case was associated with a favorable outcome, underscoring the importance of vigilant monitoring for delayed neurologic sequelae in pediatric TBI.
Machine learning-based morphological brain analysis in schizophrenia and unaffected siblings: a multisite study of potential risk markers
Background and hypothesisAssessing schizophrenia risk factors is crucial for developing early preventive interventions. We hypothesized that unaffected siblings, who share high genetic risk, exhibit neuroanatomical signatures similar to affected patients, potentially reflecting early pathogenic processes.Study designTo overcome single-center limitations, we analyzed 1,018 participants from five independent, public databases. Brain MRIs were standardized via voxel-based morphometry, and covariate-adjusted z-scores were calculated for regional volumes. An ensemble support vector machine (SVM) approach, incorporating multiple models to ensure robustness, was employed to extract a multidimensional brain signature, from which a schizophrenia-like score (SPS) was derived.ResultsThe ensemble SVM achieved high classification performance (AUC = 0.99861). Across all databases, patients exhibited consistent volume reductions in frontal, temporal, insular, and thalamic regions, alongside globus pallidus enlargement. Notably, unaffected siblings were 3.8 times more likely to show brain morphological similarities to patients than were healthy controls. Furthermore, we identified a novel imaging phenotype in siblings: increased ventral striatal volume, which positively correlated with the SPS. This feature, absent in established schizophrenia, suggests a potential compensatory mechanism or a transient developmental marker of risk.ConclusionApplying machine learning to large-scale, multi-site neuroimaging data effectively identifies structural endophenotypes. Our findings highlight unique structural characteristics, specifically the enlarged ventral striatum, as a critical biological metric for identifying high-risk individuals before clinical onset.
Three factor delay learning rules for spiking neural networks
Spiking neural networks (SNNs) are hybrid dynamical systems that operate on spatiotemporal data, yet their learnable parameters are often limited to synaptic weights, contributing little to temporal pattern recognition. Learnable parameters that delay spike times can improve classification performance in temporal tasks, but existing methods rely on large networks and offline learning, making them unsuitable for real-time operation in resource-constrained environments. In this paper, we introduce synaptic and axonal delays to leaky integrate and fire (LIF)-based feedforward and recurrent SNNs, and propose three-factor learning rules to simultaneously learn weights and delays online. We employ a smooth Gaussian surrogate to approximate spike derivatives exclusively for the eligibility trace calculation, and together with a top-down error signal determine parameter updates. Our experiments show that incorporating delays improves accuracy by up to 18% over a weights-only baseline, and for networks with similar parameter counts, jointly learning weights and delays yields up to 14% higher accuracy. On the SHD speech recognition dataset, our method achieves similar accuracy to offline backpropagation-based approaches. Compared to state-of-the-art methods, it reduces model size by 6.6× and inference latency by 50%, with only a 2.5% drop in classification accuracy. Our findings would be beneficial for the design of power and area-constrained neuromorphic processors by enabling on-device learning and lowering memory requirements.
CDKL5 deficiency results in atypical subregion-specific expression of perineuronal nets during mouse visual critical period
Perineuronal nets (PNNs) in the primary visual cortex (V1) are specialized extracellular matrix structures that form predominantly on parvalbumin+ GABAergic neurons, marking the closure of visual critical period plasticity. More recently, PNNs are used to characterize deficits in critical period plasticity in mouse models for neurodevelopmental disorders such as Rett syndrome, Fragile X syndrome, and CDKL5 deficiency disorder. Within the mouse V1, studies typically focus on the expression and function of PNNs within the binocular zone, though PNNs are expressed in other subregions of the V1. The expression and role of these PNNs in other subregions are unknown. Here, we performed a systematic whole V1 characterization of PNN expression using Wisteria floribunda agglutinin (WFA) staining, with hemisphere-, subregion-, and anatomical axes- specificity, using a null male mouse model for CDKL5 deficiency disorder during the visual critical period. Patients with CDKL5 deficiency disorder often exhibit cerebral cortical visual impairment, though the underlying mechanisms are unclear. Compared to wild-type controls, Cdkl5-null males show regional-specific changes in WFA expression; specifically, decreased all-PNNs in V1M and increased high-intensity PNNs in V1B at P30, and increased WFA pixel intensities in all three V1 subregions at P15, suggesting precocious altered PNN expression in the Cdkl5-null V1. In both genotypes, the binocular zone has significantly higher density of PNNs at both ages, compared to the monocular zone and the rostral V1. These results lay the groundwork to probe the roles for PNNs beyond the binocular zone and cumulatively suggest that, during visual critical period, subregion-specific variations in PNN expression may lead to functional consequences within the Cdkl5-null cortex.
Perceived stress and mental health in perimenopausal women: a serial mediation study of psychological distress and social support
BackgroundThe perimenopausal phase is associated with a significantly higher prevalence of mental health disorders in women, with stress perception emerging as a pivotal risk factor. However, the psychological and social mechanisms through which stress perception influences women’s mental health during this period remain to be fully elucidated. This study aims to use a stress process model to examine how social support mediates the link between stress perception and psychological symptom severity during perimenopause.MethodsA cross-sectional survey design was used, and 549 Chinese perimenopausal women were surveyed through face-to-face questionnaires. The survey employed the Chinese Perceived Stress Scale, Kessler Psychological Distress Scale, Perceived Social Support Scale, and Psychological symptom severity (BSRS-5) to evaluate participants’ psychological symptom severity. The researchers used SPSS 26.0 for related analyses, PROCESS macro software for regression analyses, and applied the Bootstrap method to assess mediating effects.ResultsThe findings of the study indicate that perceived stress, psychological distress, and psychological symptom severity (BSRS-5) are significantly and positively correlated, and perceived social support is significantly and negatively correlated with these variables (P < 0.01). The study reveals that perceived stress significantly increases psychological symptom severity scores(BSRS-5) (effect size=0.493, 59.60%) after adjusting for confounding variables. Additionally, psychological distress and perceived social support independently mediate this relationship (effect sizes=0.204, 24.67% and 0.101, 12.21%, respectively). Additionally, perceived stress indirectly affects psychological symptom severity(BSRS-5) through the chain-mediated mediating pathway of “psychological distress → perceived social support” (effect size = 0.030, percentage = 3.62%).ConclusionStress can directly increase psychological symptom severity in perimenopausal women and indirect effects can be observed through mediating factors such as psychological distress, perceived social support, and the chain-mediated relationship between these two elements. Thus, reducing symptom severity is essential for improving mental health. The study indicates that enhancing the mental health of this group requires a multifaceted approach. This approach should focus on the alleviation of psychological distress and the promotion of social support systems. This will effectively disrupt the cycle of stress and psychological distress.
The many manifestations of magical thinking: a systematic review
Magical thinking (MT) involves beliefs that thoughts or actions can influence events in unrealistic ways. While MT is integral to obsessive compulsive disorder, and reflected in the cognitive features of schizophrenia, it is observable across the general population in various forms. Given its prevalence and potential relevance to a range of psychiatric conditions, understanding more about what may predispose an individual to MT, and how it may in some cases culminate in psychological distress or dysfunction would be helpful. This paper reports a systematic review of studies investigating MT, encompassing both magical ideation and thought-action fusion specifically, across the disciplines of psychiatry and psychology, to shed further light on the likely predisposing factors and behavioural consequences of MT, its potential neurobiological underpinnings, and role in psychiatric symptomatology. After exclusions, 191 studies were identified that explored MT in association with a diverse array of secondary topics, from gambling compulsions to childhood trauma, within both clinical and non-clinical samples, across a range of cultural contexts. On an intra-individual level, MT demonstrates numerous cognitive and emotional correlates, and on a societal level it may influence both social custom and religious tradition. A synthesis of the available evidence uncovers unexplored relationships with social cognition and mental health, and future research investigating its emerging relationships with stress, mood and social connection, may uncover functions beyond those exhibited by a simple marker of psychopathology.
Sleep quality and its associated factors among women of reproductive age in Ethiopia: a systematic review and meta-analysis
BackgroundQuality sleep is vital for women’s health during reproductive years, affecting both physical and mental well-being. In Ethiopia, socio-economic and cultural factors worsen sleep issues, but data on this demographic are scarce. This systematic review and meta-analysis assesses the prevalence of poor sleep quality among Ethiopian women and identifies contributing factors, aiming to inform interventions and policies to improve sleep health in low-resource settings.MethodThis systematic review followed PRISMA guidelines and searched PubMed, Scopus, and Web of Science for observational studies. We included studies utilizing the Pittsburgh Sleep Quality Index (PSQI), as it is the most widely validated tool for assessing subjective sleep quality across diverse populations. Reviewers independently screened articles using Rayyan and assessed study quality with the Joanna Briggs Institute tools. Data were analyzed using Stata version 17. To account for potential clinical and methodological variability across studies, a random-effects model was employed to pool results, with heterogeneity assessed using statistics and the Cochrane’s Q test. Publication bias and sensitivity analyses were also performed.ResultNine studies involving 4,376 women of reproductive age (15–49 years) in Ethiopia were included. The pooled prevalence of poor sleep quality was 49.17% (95% CI: 35.29, 63.08). Significant predictors of poor sleep quality included intimate partner violence (OR: 3.24), depression (OR: 3.37), unplanned pregnancy (OR: 2.71), multigravidity (OR: 2.61), and substance use (OR: 2.24).ConclusionA systematic review indicates that nearly half of Ethiopian women of reproductive age experience poor sleep quality. Key factors include unplanned pregnancies, substance use history, intimate partner violence, previous depression, stress, being in the third trimester, and comorbidities; these need urgent attention and the implementation of screening and preventive measures. Future research should focus on effective interventions to improve sleep quality in these populations.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023455867.
Group-based psychosocial interventions reduce internalized stigma in psychiatric disorders: ISMI-focused systematic review
BackgroundInternalized stigma negatively impacts recovery outcomes, quality of life, and self-concept among individuals with psychiatric diagnoses. Group-based psychosocial interventions have been proposed as effective stigma-reduction strategies, but their impact across diverse populations remains under-evaluated.ObjectiveThis systematic review synthesizes global evidence on the effectiveness of group-based interventions in reducing internalized stigma in adult psychiatric populations, with a focus on studies using the Internalized Stigma of Mental Illness (ISMI) scale.MethodsFollowing PRISMA 2020 guidelines, we searched PubMed, PsycINFO and Web of Science, and additionally screened full-text platforms (SpringerLink, ScienceDirect, SAGE Journals, and Wiley Online Library), for studies published between 2003 and 2025. Inclusion criteria required adult psychiatric populations, group-based interventions, and internalized stigma as a primary outcome. Study selection, risk of bias assessment, and data extraction were performed independently by two reviewers (US and GOC).ResultsTen studies [n= 1,088], across five countries, met inclusion criteria, including randomized controlled trials and pre-post designs. Most studies reported significant reductions in ISMI scores post-intervention, particularly in the domains of stereotype endorsement and social withdrawal. Culturally adapted interventions in China, Poland, and Spain demonstrated feasibility and impact, though subscale reliability varied regionally.ConclusionGroup-based psychosocial interventions may help reduce internalized stigma in psychiatric populations within an ISMI-based evidence base. The ISMI scale is, to this day, among the most frequently used instrument, though cultural adaptation of subscales such as stigma resistance remains a concern.
Detecting bipolarity using the Lebanese Arabic hypomania checklist (HCL-32): validation of shortened HCL versions
IntroductionDue to the under diagnosis of bipolar disorder, screening instruments such as the hypomania checklist 32 items (HCL-32) is used to differentiate between Bipolar Disorder (BD) and Major Depressive Disorder (MDD). However due to its lengthy format, efforts were done to validate a shorter alternative without compromising its ability to differentiate between BD and MDD. We aimed to shorten the HCL-32 and assess the screening performance of the three Lebanese Arabic abbreviated HCL versions (HCL-20, -16, and -8) relative to the full HCL-32 in a sample of clinically diagnosed patients with BD and MDD in Lebanon.MethodsIn a sample of 760 patients (BD-I=29, BD-II=142, MDD=589) clinically diagnosed with BD and MDD, the screening performance of the three Lebanese Arabic abbreviated HCL versions (HCL-20, -16, and -8) as well as the full HCL-32, was assessed, looking at the reliability, sensitivity, and specificity.ResultsAll the shortened HCL versions showed strong reliability (a=0.78-0.90.) They also demonstrated good screening ability (AUC=0.8520- 0.8835) in differentiating BD from MDD. For the sensitivities across the shortened versions, they were consistently higher in BD-II vs MDD compared to BD-I vs MDD across all scales showing that the shortened versions have the ability to detect BD-II cases much more effectively.DiscussionThis study is the first to validate the shortened HCL versions in an Arabic speaking population. The HCL- 16 appears to be the most optimal shortened scale for distinguishing between BD versus MDD. However, these findings should be interpreted in light of the study’s limitations including the use of retrospective data collection and item interdependence of the HCL-32.