Tag: News Approved

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Experimental investigation of sharp-tip microwire-based brain electrode buckling during implantation through dura and pia mater

IntroductionWide use of miniaturized and flexible microwire electrodes faces challenges of wire buckling against the brain membrane layers. The field lacks quantitative understanding of such buckling phenomena, especially on the effective length factor, which is required to determine the wire’s critical buckling load.MethodsThis study presents an experimental investigation into the buckling behavior of tungsten microwire electrodes during implantation through dura and pia mater layers using a validated multilayer brain-mimicking phantom. Microwires with three diameters (25.4, 50.8, and 76.2 µm) and different tip geometries—including blunt, beveled, and electrochemically (conical) sharpened profiles—were evaluated under controlled axial insertion. Critical buckling length, insertion outcomes (buckled/penetrated), and rupture/buckling force were quantified across the experimental dataset. Buckling behavior was analyzed using the Euler column framework with experimentally estimated effective length factors (Kˆ) to represent each unique membrane-wire tip boundary interaction.ResultsResults indicated that wire diameter strongly influences buckling resistance, with larger diameters yielding quartic (fourth order) higher critical buckling load of the electrode, whereas the corresponding membrane rupture force only increases linearly with the diameter. But smaller microwires tend to anchor better against the brain membrane, generating a more stable wire-membrane interface closer to the ideal pin end condition. Tip geometry also significantly affected rupture force and insertion stability; conical tips dramatically reduced the membrane rupture force with less variance. In general, tip sharpening choice for small microwires should focus on optimizing tips anchoring mechanism and minimizing rupture force uncertainty introduced by tip asymmetry while thick microwires mainly benefit from membrane rupture force reduction. For theoretical prediction of a microwire electrode’s critical buckling load based on Euler’s buckling equation, unlike conventional fixed-pinned assumption (K = 0.7), experimentally measured effective length factors ranged from approximately 0.72 – 0.82.DiscussionDesigning with ≈ 0.8 provides a conservative estimate that may reduce the risk of buckling under membrane penetration conditions compared to the commonly assumed fixed-pinned value of 0.7. These findings provide quantitative design guidance for optimizing microwire geometry and offer a validated benchtop framework for predicting buckling-limited insertion performance in neural interface applications.
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Oxygen extraction fraction is differentially associated with pathological biomarkers in Alzheimer’s disease and non-Alzheimer’s dementias

IntroductionWe aimed to understand the pathophysiological differences between 16 Alzheimer’s disease (AD) and 15 non-AD dementia patients by quantifying oxygen extraction fraction (OEF) in cortical (CGM) and deep gray matter (DGM) regions.MethodsTo achieve this, we used a novel MRI-based OEF mapping technique, QQ, which estimates OEF from routine multi-echo gradient echo data. Multiple linear regression analyses were performed to compare the associations between OEF and white matter hyperintensities (WMH) or cognitive impairment (measured by Montreal Cognitive Assessment (MoCA) between the two groups.ResultsIn the AD and non-AD group, OEF showed negative associations with WMH in DGM and positive associations with MoCA in DGM and CGM.DiscussionOur study suggests that QQ is a promising tool for differentiating between AD and non-AD dementias, by revealing abnormalities in tissue oxygen usage and their relationships to microvascular changes and cognitive impairment.
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Quality, reliability, and transparency of late-life depression videos on Chinese social media: a cross-sectional study of Douyin, Rednotes, and BiliBili

BackgroundLate-life depression is common in older adults and is often under-recognized. Short-video platforms have become a major source of mental health information. However, content quality and transparency remain uncertain.MethodsWe conducted a cross-sectional assessment of highly viewed videos on late-life depression on three Chinese platforms. We searched each platform using the keyword in Chinese “Late-life depression”. We selected the top 200 videos by view count on Douyin, Rednotes (Xiaohongshu), and BiliBili. After exclusions, 562 videos were included (Douyin, n=188; Rednotes, n=188; BiliBili, n=186). Two medically trained raters scored videos using the Global Quality Score (GQS), modified DISCERN (mDISCERN), and JAMA benchmark criteria. We also coded content categories and creator types. We assessed platform differences using non-parametric tests. We examined associations between a limited engagement proxy, defined as the comment-to-view ratio, and quality scores using Spearman correlation.ResultsVideo duration differed across platforms (p<0.001). Engagement indicators were higher on Douyin and Rednotes than on BiliBili. Symptoms were the most common topic on all platforms. Prevention and intervention ranked second on Douyin and Rednotes. On BiliBili, causes and case-based analysis were also common. Overall quality was moderate. Mean GQS ranged from 2.96 to 3.05. Transparency was limited. Mean JAMA ranged from 1.91 to 2.04. Reliability was slightly higher on BiliBili based on mDISCERN. Creator type was strongly associated with scores. Expert and institutional videos scored higher than general and marketing-oriented accounts. Correlations between visible audience interaction and quality were weak.ConclusionHighly viewed late-life depression videos on major Chinese platforms show moderate quality and limited transparency. Exposure does not reliably signal higher-quality information. Platforms and health authorities should strengthen source disclosure and promote evidence-based content from qualified creators.
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Scoping review of therapeutic approaches among individuals with secondary exercise addiction

Secondary exercise addiction shows high comorbidity with eating and body image disorders. Despite its substantial impact on physical and mental health and daily functioning, evidence on effective therapeutic interventions remains limited. The aim of this scoping review was to identify and describe therapeutic interventions applied to adult individuals with secondary exercise addiction. This review followed the PRISMA Sc-R guidelines and covered the years 2002–2024. Ultimately, five studies were included (four randomized controlled trials and one quasi-experimental study). Three studies applied psychotherapeutic interventions based on cognitive-behavioral models (Cognitive Behavioral Therapy, Lifestyle, Exercise, Attitudes, and Relationships Program, Physical Exercise and Dietary Therapy), while two integrated physical or nutritional components. A secondary analysis published in 2024 based on the LEAP trial dataset was identified but not treated as an independent study to avoid duplication. EBSCOhost, Web of Science, PubMed, and Google Scholar were searched from January to May 2025 using terms related to exercise addiction, exercise abuse, psychotherapy, intervention, and treatment. English-language studies were eligible if they described an intervention with at least one treated group with pre- and post-test measures; the participants of the study were adult patients suffering from eating disorders and exercise addiction (the therapy programs involved one inpatient and four outpatient treatments) and therapeutic intervention was carried out with outcomes based on exercise addiction level data. Four out of five included studies reported improvements in variables related to compulsivity, although these did not always imply a reduction in the amount of exercise, indicating that qualitative changes may be more relevant. Longer interventions showed more consistent effects, but even brief treatments generated positive changes in non-clinical populations. The examination of the research revealed a gap in studies addressing interventions for those with secondary exercise addiction, especially highlighting the need for randomized controlled trials (RCTs) with proper randomization methods.
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Safety and preliminary efficacy of Aurora: a pilot, non-randomized clinical trial of a culturally adapted digital cognitive behavioral therapy intervention for anxiety and depression in Mexico

Background/objectiveAnxiety and depressive disorders are leading causes of disability worldwide, and access to evidence-based psychological treatment remains limited in many middle-income countries. Digital cognitive–behavioral therapy (CBT) interventions have emerged as scalable tools to address this treatment gap, yet few have undergone clinical evaluation in Latin American populations. This study aimed to assess the safety and preliminary efficacy of Aurora, a Spanish-language, culturally adapted digital CBT program, when used as an adjunct to pharmacotherapy in adults with generalized anxiety disorder.MethodsIn a multicenter, open-label, non-randomized pilot study, 34 adults diagnosed with generalized anxiety disorder receiving stable pharmacological treatment were assigned through pragmatic, convenience-based allocation either to an experimental group (Aurora plus medication; n = 24) or to a control group receiving medication alone (n = 10). The sample had a mean age of 39.85 ± 12.88 years, with a predominance of women (22/34). Participants were followed for 12 weeks with assessments at baseline and weeks 4, 8, and 12. Clinical outcomes included anxiety severity measured by the Generalized Anxiety Disorder-7 (GAD-7), pathological worry assessed by the Penn State Worry Questionnaire (PSWQ), and depressive symptoms evaluated using the Patient Health Questionnaire-9 (PHQ-9). Safety was monitored through structured adverse-event reporting. Statistical analyses included linear mixed-effects models for longitudinal outcomes, ordinal logistic regression for severity transitions, and negative binomial regression and Fisher’s exact test for adverse events, with false discovery rate correction applied where appropriate.ResultsAurora demonstrated a favorable safety profile, with no serious adverse events and comparable adverse-event incidence between groups under structured clinical monitoring at weeks 4, 8, and 12. Anxiety symptoms (GAD-7) showed a significant effect of time (F3,96 = 169.65; p < 0.001), indicating reductions across both groups. Pathological worry (PSWQ) demonstrated significant group (F1,31.12 = 6.96; p = 0.013) and group × time interaction effects (F3,93.4 = 7.86; p < 0.001), with greater reductions in the Aurora group, particularly at weeks 8 and 12. At week 12, ordinal analyses indicated higher odds of lower worry severity in the intervention group (β = 2.53; p = 0.004; OR = 12.5). Depressive symptoms decreased similarly in both groups. Positive effect increased progressively across intervention modules, and module-embedded cognitive measures of anxiety and depression showed significant reductions over time.ConclusionThis pilot study provides preliminary, hypothesis-generating evidence that a culturally adapted digital CBT intervention can be safely integrated with pharmacotherapy and may be associated with enhanced improvements in anxiety-related outcomes, particularly pathological worry, in a Mexican clinical population. However, the non-randomized design, small sample size, and baseline imbalances limit causal inference and generalizability, and findings should be interpreted with caution. Larger randomized controlled trials are needed to confirm efficacy, determine long-term clinical impact, and guide the implementation of digital therapeutics in Latin American mental health systems.
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Real-world effectiveness of medication-assisted treatment and psychotherapy for opioid use disorder: a national multi–health care organization analysis

BackgroundHarm reduction strategies for opioid use disorder (OUD) emphasize pragmatic, evidence-based approaches that reduce overdose risk, relapse, and other adverse outcomes without requiring abstinence. Medication for opioid use disorder (MOUD) and structured psychotherapy represent core harm-reduction modalities, yet their real-world comparative effectiveness, alone and in combination, remains underexplored at scale.MethodsA retrospective cohort study was conducted using the TriNetX Research Network, comprising de-identified electronic health records from 112 U.S. health systems. 18,047 adults aged 18–45 were identified with a diagnosis of opioid dependence (ICD-10 F11.20) between 2016 and 2025. Subjects were assigned to eight mutually exclusive treatment cohorts: no treatment (Cohort 1); buprenorphine alone (Cohort 2); methadone alone (Cohort 3); psychotherapy alone (30 minutes (Cohort 4), 45 minutes (Cohort 5), or 60 minutes (Cohort 6)); buprenorphine + psychotherapy (Cohort 7); and methadone + psychotherapy (Cohort 8), with combination treatments defined within a ±30-day window. Cox proportional hazards models estimated adjusted hazard ratios (aHRs) for remission (F11.21, F11.11) within 12 months.ResultsBuprenorphine (aHR = 2.33; 95% CI: 1.85–2.94), methadone (aHR = 2.50; 95% CI: 2.05–3.04), and psychotherapy (30 min: aHR = 2.18; 45 min: aHR = 2.38) were each independently associated with significantly higher remission compared to no treatment. The combination of buprenorphine + psychotherapy yielded the strongest effect (aHR = 5.26; 95% CI: 2.68–10.32). Anxiety diagnoses and gabapentinoid prescriptions were positively associated with remission; benzodiazepine co-prescription was negatively associated.ConclusionsIn this first national-scale, multi–health-care-organization analysis, both pharmacologic and psychosocial harm-reduction interventions were independently associated with improved OUD remission, with additive benefit when integrated. These findings underscore the value of embedding comprehensive, multimodal harm-reduction services within routine care and support policies promoting equitable access to both MOUD and behavioral health supports across diverse health systems.
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A prospective cohort study on the incidence and influencing factors of subsyndromal delirium in ICU patients

BackgroundThis study aims to develop and validate a machine learning-based risk prediction model for subsyndromal delirium (SSD) in ICU patients, while identifying key risk factors.MethodThis study was a prospective study, selecting patients who were hospitalized in the ICU from October 2024 to May 2025. We compared seven machine learning algorithms: Random Forest (RF), Decision Tree (DT), K-Nearest Neighbor (KNN), Logistic Regression (LR), Elastic Network (EN), Extreme Gradient Enhancement (XGB), and Support Vector Machine (SVM).ResultIn our study, the prevalence rate of SSD was 37.158%. The comparative analysis shows that XGB is the best predictive model (AUC = 0.84). Feature importance analysis identified four significant predictive factors: Use of vasoactive drugs (0.412), Monthly household income (0.306), Undergone surgery (0.191) and Number of Medications (0.036).ConclusionThe prediction model based on XGB has a good effect in identifying the risk of SSD in ICU patients. These findings enable clinicians to stratify high-risk groups and implement timely and targeted intervention measures, effectively reducing the risk of adverse consequences. Future multicenter studies should validate these results in larger cohorts.