Temporal lobe epilepsy (TLE) is frequently accompanied by disruptions to sleep and circadian rhythms, which substantially contribute to disease burden. Human studies are often confounded by antiseizure medications, limiting insight into underlying mechanisms. Animal models therefore provide critical opportunities to examine causal interactions, yet their translational validity has not been systematically evaluated. In this review, we first outline the relevance of rodent models for studying epilepsy- and sleep-related processes. We then examine current evidence for sleep and circadian disturbances across three commonly used TLE models: the pilocarpine (PILO) model, the kainic acid (KA) model, and the traumatic brain injury (TBI) model. We summarize circadian patterns of seizure occurrence, alterations in sleep–wake architecture, and changes in core circadian clock gene expression, as well as alterations in subcortical brain regions involved in sleep–wake regulation. Across models, sleep is consistently fragmented, and circadian molecular machinery is profoundly disrupted, although the direction and magnitude of changes vary by species, protocol, and epilepsy stage. By comparing findings across animal models and patient studies, this review highlights convergences, discrepancies, and key research gaps. Despite variability, animal models remain indispensable for probing the bidirectional links between epilepsy and sleep–circadian regulation.
Development and validation of machine learning models for predicting functional outcome after low-dose alteplase in the extended time window for acute ischemic stroke
BackgroundThis study aims to develop machine learning (ML) models to predict 90-day functional outcomes for acute ischemic stroke (AIS) patients receiving thrombolysis with low-dose alteplase at 0.6 mg/kg between 4.5 and 9 h after symptom onset.MethodsWe conducted a retrospective analysis of AIS patients receiving thrombolysis between August 1, 2019 and August 31, 2023. Eligible patients were randomly divided into training and validation sets in a 7:3 ratio. Good functional prognosis at 90 days were defined as modified Rankin scale score (mRS) ≤2. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select optimal features. Five ML algorithms were employed to construct prediction models. Model performance was evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC) value, decision curve analysis (DCA), and calibration curves. SHapley Additive exPlanations (SHAP) plot was applied to interpret the model predictions.ResultsA total of 202 patients were randomly divided into training (n = 142) and validation (n = 60) sets. The rate of poor functional prognosis at 90 days was 56.34% in the training set and 56.67% in the validation set. Random Forest (RF) model showed the best discriminative ability with the highest AUC of 0.854 in the validation set. Key predictive features included age, baseline systolic blood pressure, white blood cell count, baseline National Institutes of Health Stroke Scale (NIHSS) score, wake-up stroke, the absolute difference volume between the ischemic infarct and the penumbra, intracranial hemorrhage, hemorrhagic transformation classification, and occurrence of pneumonia.ConclusionThe RF-based ML model demonstrated clinical utility for post-intravenous thrombolysis risk stratification by identifying patients at higher risk of poor functional outcomes.
A multichannel MEG time–frequency analysis framework for detecting stage -specific effects of spatial distraction in visual-spatial working memory
IntroductionSpatial distraction can disrupt visual-spatial working memory (VSWM), but its stage-dependent effects on multichannel neural dynamics remain insufficiently characterized. This study presents a multichannel magnetoencephalography (MEG) time—frequency analysis framework to detect stage-specific oscillatory responses to spatial distraction during a VSWM task.MethodsMEG signals were recorded from healthy participants under Distractor and No-distractor conditions and analyzed across encoding, maintenance, and retrieval/decision epochs. Time–frequency power was estimated in the delta, theta, alpha, beta, and gamma bands, and condition differences were evaluated using sensor-level spatiotemporal cluster-based permutation testing and Bonferroni correction within each predefined epoch.ResultsThe proposed analysis revealed a clear stage-specific pattern, with the most prominent modulation occurring during maintenance. Specifically, distraction induced robust and sustained increases in theta-, alpha-, and beta-band power during the retention interval (all cluster-level p < 0.01). Theta activity increased rapidly after maintenance onset and remained elevated throughout the full maintenance period over bilateral temporal, and widespread parieto-occipital sensors, while alpha and beta enhancements also showed temporally continuous and spatially stable patterns across widespread sensor networks.DiscussionThese findings highlight sustained large-scale oscillatory modulation as a key neural signature of distraction during mnemonic maintenance. The study provides an interpretable multichannel signal-analysis perspective on distraction effects in working memory and offers a practical framework for stage-resolved analysis of brain dynamics in cognitive tasks.
Can exercise combined with transcranial direct current stimulation improve cognitive function in older adults? A systematic review and meta-analysis
ObjectiveThis study investigated whether combining exercise with transcranial direct current stimulation (tDCS) improves overall cognition, memory, and executive function in older adults.MethodsFollowing PRISMA guidelines, we systematically searched databases including PubMed, Web of Science, CNKI, and Wan Fang for randomized controlled trials (RCTs) examining the combined effect of exercise and tDCS on cognitive function in older adults. Used RStudio (version 4.2.0) to merge effect sizes and represent them as SMD with a 95% confidence interval (CI). The main effects are synthesized using a random effects model, and heterogeneity sources are explored through subgroup regression and sensitivity analysis.ResultsThe combined exercise and tDCS intervention significantly improved global cognitive function in older adults (SMD = 0.62, 95% CI: 0.36 to 0.89, p < 0.0001). Significant enhancements were observed in executive function (SMD = 0.54, 95% CI: 0.16 to 0.92, p = 0.005) and general cognitive ability (SMD = 0.75, 95% CI: 0.21 to 1.30, p = 0.006), while memory showed a non-significant improvement (SMD = 0.58, 95% CI: −0.03 to 1.19, p = 0.063). Both interventions lasting less than 6 weeks (SMD = 0.94, 95% CI: 0.60 to 1.27, p < 0.0001) and those lasting 6 weeks or longer (SMD = 0.24, 95% CI: 0.10 to 0.37, p = 0.0006) positively impacted cognitive function. However, the effect size was larger for cognitively healthy older adults (SMD = 0.69, 95% CI: 0.20 to 1.18, p = 0.006) compared to those with cognitive impairment (SMD = 0.60, 95% CI: 0.29 to 0.92, p = 0.0002). The combination of tDCS and integrated exercise produced the largest effect size (SMD = 1.74), despite high heterogeneity, while the combination of tDCS and Tai Chi produced the smallest but most robust effect (SMD = 0.25, I 2 = 0%), indicating that exercise type significantly regulates the intervention effect of tDCS (p = 0.0015). Regression analysis shows that tDCS stimulation time has a significant positive regulatory effect on cognitive function in elderly people (p = 0.0002), while the combined intervention period (p = 0.030) and single exercise time (p = 0.034) both have a significant negative regulatory effect.ConclusionBased on limited evidence, we found that a combined intervention of exercise and tDCS is a potentially effective means of improving cognitive function in older adults. However, the extent of improvement varies with the cognitive domain, baseline performance level, and intervention plan.
Computer-based tree drawing test in adolescents and adults with depression
ObjectiveTo evaluate the value of the computer-based Tree Drawing Test in the auxiliary diagnosis of depressive disorders and to analyze the differences in the performance of adolescent and adult depression patients in the Tree Drawing Projection Test.MethodsThis study was conducted at Guo Yang County People’s Hospital in Anhui, China, and involved a total of 184 participants: 43 adults with depression, 82 adolescents with depression, and 59 healthy controls. The Tree Drawing Test and scale assessments were administered to patients with depressive disorders (adult group and adolescent group) and a control group. Computer image recognition and calculation techniques were used to analyze the results statistically.ResultsSignificant differences were observed between the adult depression group and the control group in terms of crown area, trunk area, total area, and HDRS scores (p < 0.001). Statistically significant differences were also found between the adult depression group and the adolescent depression group in terms of trunk area (p < 0.01), total area (p < 0.001), HDRS scores (p < 0.001), and HAMA scores (p < 0.01). The crown area (r = -0.261, p < 0.001), trunk area (r = -0.154, p = 0.037), total area (r = -0.285, p < 0.001), and HDRS scores in the Tree Drawing Test were significantly correlated.ConclusionThe computer-based Tree Drawing Test has certain value in the auxiliary diagnosis of depression. Future research should include larger sample sizes and participants from different regions and cultural backgrounds to further validate the generalizability and cultural adaptability of the Tree Drawing Test for depression assessment.
Development and validation of a comprehensive prevention-focused intervention package for problematic digital technology use among youth: a multi-site study protocol
BackgroundProblematic use of digital technology among children, adolescents, and young adults is associated with adverse health, behavioural, interpersonal, social, academic and vocational outcomes. Most existing research focuses on treatment oriented interventions. Prevention focused interventions are limited. This is especially true for the low- and middle-income countries. There is a need for structured prevention approaches that involve youth, parents, and teachers.ObjectivesThis study aims to develop and validate a comprehensive package of prevention-focused interventions targeted at problematic use of digital technology among youth.MethodsThe study will be conducted across six sites in India. It will use a sequential mixed-methods design. Literature review, stakeholder interviews, and expert consensus shall be used for intervention development. This will be guided by established frameworks for complex interventions. Validation will be carried out using a quasi-experimental pre–post design. Quantitative measures will assess changes in knowledge, skills, confidence, and decision-making, as well as feasibility and acceptability. Qualitative methods will be used to assess engagement, delivery quality, and contextual factors.Expected outcomesThe study will lead to a modular prevention-focused intervention package with evidence of feasibility and acceptability. Findings will inform future larger scale implementation and evaluations.ConclusionThis protocol outlines a structured approach to development of a prevention-focused intervention targeted at problematic digital technology use among youth. The focus on prevention, stakeholder involvement, and real-world settings supports relevance for public health practice and policy.Clinical trial registrationhttps://ctri.nic.in/Clinicaltrials/login.php, identifier CTRI2026/03/105278.
ADOPT model combined with structured health education alleviates the preoperative anxiety of patients undergoing preventive ileostomy
ObjectiveThis study aimed to evaluate the efficacy of the ADOPT (Attitude-Definition-Openmind-Plan-Try it out) model combined with structured health education in alleviating preoperative anxiety in patients undergoing preventive ileostomy for rectal cancer.MethodsThis is a randomized controlled trial. A total of 60 patients scheduled for temporary ileostomy were randomly assigned to either the control group (routine care) or the research group (ADOPT model combined with science popularization interventions). The research group received structured education via a multimedia resource library, including preoperative, intraoperative, and postoperative care guidance, alongside interactive support from a specialized healthcare team. Anxiety levels were assessed with the State-Trait Anxiety Inventory (STAI) at admission and preoperatively.ResultsAt baseline, no significant differences were observed in gender (P = 0.202), age (P = 0.052), or BMI (P = 0.798) between the two groups. Both groups exhibited comparable anxiety levels at admission. However, one hour before surgery, the research group showed significantly lower state anxiety (S-AI) scores and total anxiety scores compared to the control group (20 ± 0.48 vs 23 ± 0.37, p<0.001), while trait anxiety (T-AI) scores remained similar (p<0.05).ConclusionThe integration of the ADOPT model with structured health education effectively reduces preoperative anxiety in ileostomy patients, highlighting its potential as a standardized nursing intervention.
Virtual reality-based inhibition training influences food-related responses: no additional effects of repetitive transcranial magnetic stimulation
Combining cognitive inhibition training with brain stimulation techniques has received increasing attention as a potential approach to modulating maladaptive food craving and food intake. Building on previous work in this line of research, the current study examined whether virtual reality (VR)-based no-go inhibition training paired with repetitive transcranial magnetic stimulation (rTMS) modulates implicit food-related attitudes, craving and food-choice behaviors. Healthy women with high trait food cravings and a preference for high-calorie foods were assigned to one of four groups in a 2 (rTMS: active vs. sham) × 2 (training: no-go vs. neutral) between-subjects design. High-frequency rTMS was applied over the left dorsolateral prefrontal cortex (DLPFC), and no-go training was implemented in a VR environment using food stimuli tailored to participants’ self-reported preferences. Implicit attitudes and food craving were assessed before and after the intervention, while food choice was measured post-intervention only. Following training, the no-go group showed reduced positive implicit attitudes toward high-calorie foods and increased craving for low-calorie foods compared to pre-training levels, whereas no such changes were observed in the neutral group. Moreover, compared to the neutral group, the no-go group made healthier food choices. No-go training effects on food choice were more pronounced among individuals with low-to-moderate baseline preferences for high-calorie foods. In contrast, no significant main effects or additive effects of rTMS were observed. The present study demonstrates that VR-based no-go training can effectively regulate food-related responses and extends earlier work by demonstrating robust inhibition training effects across implicit and explicit measures, while highlighting the importance of considering individual differences in future research.
Adaptation of behavioural activation for adolescents with mild to moderate intellectual disabilities and depression
IntroductionAdolescents with intellectual disabilities are at increased risk for mental health problems and depression. Despite this, there is currently no evidence for effective psychological interventions for treating low mood and depression in this population. Behavioural activation has been identified as an effective intervention for treating depression in autistic adolescents and for adults with intellectual disabilities and may therefore also be suitable for use with adolescents with intellectual disabilities.MethodThe current paper describes an approach taken to adapting an existing behavioural activation intervention used with adults with intellectual disabilities (Beat-It) to be suitable for adolescents, named Beat-Depression (Beat-D). An iterative, three-phase approach was adopted for the adaptation process. The first phase involved review of the Beat-It manual and proposed adaptations by the project team, followed by a second phase consisting of consultations with parents of adolescents with intellectual disabilities and professionals with experience in the field.ResultsThe outcomes from phases one and two were incorporated into a final adapted manual for the Beat-D intervention. The intervention is described following the principles of the Template for Intervention Description and Replication (TIDieR) checklist.DiscussionImplications for using this adaptation approach more broadly to ensure psychological interventions used with adolescents with intellectual disabilities are suitable and accessible are discussed along with future plans for the evaluation of Beat-D.
The aging scientific workforce collides with rising fabricating citations in medical journals
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