Addiction Neuroscience

Background and Aims: Synthetic opioids cause tens of thousands of deaths each year in North America, and there are indications that synthetic opioids are also becoming increasingly prevalent in the European drug market. This study aimed to examine high-risk substance use in the German drug-using community with a particular focus on the synthetic opioids fentanyl and nitazenes and related awareness, concerns, overdose experiences, and harm-reduction behavior. Design: Cross-sectional, observational online survey. Setting: Open drug-use scenes, addiction clinics, and substitution practices at numerous geographic locations throughout Germany, August to September 2025. Participants: 235 individuals aged 14+ from the drug using community (mean age 43.4 years; 57.9% male), 79.6% recruited by peers in open drug-use scenes. Measurements: The primary outcome was substances used within the past 12 months. In addition, sources, forms, routes of administration, and perceived changes in availability and price of (synthetic) opioids were assessed as well as risk perceptions, fears, harm-reduction behavior, and overdose-related experiences. Findings: 227 respondents reported substance use with an average of 6.2 substances, and 73.1% (95% confidence interval [CI] = 67.0-78.5%) had used at least one opioid in the past year. Synthetic opioids were consumed in many parts of Germany and across all age and gender groups. Among participants who experienced a shortage of their primary opioid in the past year, 25% (95% CI = 15.8-37.2%) reported having used fentanyl instead. 56.5% (95% CI = 36.8-74.3%) of individuals using synthetic opioids reported having experienced an overdose in the past twelve months. Most of the respondents perceived synthetic opioids as posing a high risk, and a substantial proportion expressed fear that they could be mixed into their own substances. However, only 9.9% (95% CI = 6.6-14.7%) use drug checking, although the vast majority stated they would use it if it were available to them. Conclusions: Synthetic opioids, including fentanyl and nitazenes, have entered the German drug scene, with users reporting high rates of overdose and limited access to harm reduction measures. Germany may be in an early phase of a synthetic opioid transition, warranting urgent expansion of surveillance, naloxone distribution, and drug checking services.

In a single-blind randomized controlled trial, we investigated the effectiveness of real-time fMRI neurofeedback delivered in 7 runs over three sessions across two weeks in N = 65 patients with alcohol use disorder. The intervention targeted modulation of ventral striatal cue reactivity to alcohol-related cues as well as enhancement of prefrontal control mechanisms in the right inferior frontal gyrus. The study design incorporate three experimental groups that either were instructed to downregulate a ventral striatum signal, upregulate the right inferior frontal gyrus, or upregulate negative functional connectivity between these two structures. In two active control groups participants were instructed to either up- or downregulate the primary auditory cortex. We did not find an effect of ventral striatal downregulation or negative connectivity feedback, and a reduced striatal activation in the right inferior frontal gyrus upregulation group was accompanied by concurrent lower activation in the target structure, suggesting that our intended modulation approaches were not effective. Identified problems that might have contributed to this unexpected outcome might have been the use of continuous feedback presentation that potentially confuses regulation target and reward processing in the ventral striatum, counterintuitive regulation directions, a lack of explicit strategy guidance and transparency about the targeted process, and generally the difficulty to recruit a sufficient number of eligible voluntary participants for a well-powered study with a complex design. These insights emphasize the complex challenges of real-time fMRI neurofeedback interventions for the treatment of substance use disorders and could provide guidance for the development of more effective future approaches.

Background and Aims: The North American overdose crisis is increasingly characterized by complex polysubstance use alongside a transition from injecting to smoking unregulated opioids. However, transitions involving multiple substances remain understudied. We characterized longitudinal transitions in the route of administration and frequency of heroin, fentanyl, and methamphetamine use and examined whether these transitions differed by multilevel factors hypothesized to influence patterns of polysubstance use and routes of administration over time. Design: People who inject drugs (PWID) enrolled in a cohort study completed baseline surveys (October 2020-2021) and three biannual follow-up visits (through April 2023). Setting: San Diego, California, and Tijuana, Baja California. Participants: Among 612 PWID, median age was 43 years; most were male (74%), Hispanic, Latino, or Mexican (72%), and San Diego residents (67%). Measurements: Based on past six-month substance use behaviors reported at each visit, we categorized participants according to six indicators over time: low- (< weekly) and high-frequency ([&ge;] weekly) smoking and injecting of heroin, fentanyl, and methamphetamine. We then used latent transition analysis (LTA) to identify distinct subgroups of participants with respect to these indicators at baseline and examine transitions between them over 18 months. We fit models with 2-5 subgroups, selecting the final model based on fit and interpretability and used multiple-groups LTA to examine differences in subgroup transitions by multilevel factors. Findings: We identified four subgroups: Subgroup 1 (Heroin-Methamphetamine Polyroute), characterized by high-frequency heroin and methamphetamine smoking and injection, included 22% of participants at baseline but 0% at 18 months. Subgroup 2 (Methamphetamine-dominant Smoking), characterized by high-frequency methamphetamine smoking, accounted for 14% of participants at baseline and 18 months. Subgroup 3 (Fentanyl-Methamphetamine Smoking), characterized by high-frequency fentanyl and methamphetamine smoking, included 4% of participants at baseline and 21% at 18 months. Subgroup 4 (Heroin-dominant Injecting), characterized by high-frequency heroin injection, included 61% of participants at baseline and 65% at 18 months. Participants in Subgroup 1 primarily transitioned to Subgroups 3 and 4 over time. Larger increases in Subgroup 3 prevalence occurred for participants who, at baseline, experienced homelessness, resided in San Diego (vs. Tijuana), received syringes from a syringe services program, and overdosed in the past six months. Conclusions: PWID in this region increasingly transitioned from high-frequency heroin and methamphetamine injection toward fentanyl and methamphetamine smoking, likely reflecting shifts in drug availability. Results highlight the need for multilevel interventions that address health harms resulting from polysubstance smoking alongside continued injection.

Background: Cannabis use is highly prevalent among emerging adults (18-25 years), a developmental period marked by ongoing neurodevelopment and heightened risk for cannabis use disorder (CUD). Structural alterations in the orbitofrontal cortex (OFC) and medial prefrontal/anterior cingulate cortex (mPFC/ACC) have been linked to cannabis use, though findings remain inconsistent in directionality. To address this, we examined cortical thickness and surface area of the OFC and mPFC/ACC subregions using the high-resolution Glasser atlas, allowing for more granular characterization of associations with CUD severity. Method: One hundred eleven emerging adults (41% male, aged=20.6{+/-}1.1 years) reporting significant alcohol and/or cannabis use completed clinical assessments and structural MRI. The OFC and mPFC/ACC were segmented into seven and six subregions per hemisphere, respectively. Multiple linear regressions tested associations between cortical thickness or surface area and DSM-5 CUD symptom count, controlling for alcohol use and intracranial volume. Subregions surviving false discovery rate correction were examined in relation to depression, trauma-related symptoms, impulsivity, and cannabis use motives. Results: Greater CUD severity was associated with lower cortical surface area and greater cortical thickness in OFC and mPFC/ACC subregions. Lower OFC surface area was correlated with coping- and enhancement-related cannabis use motives. Lower mPFC/ACC surface area and greater thickness were associated with more severe depression, trauma-related symptoms, and impulsivity. Conclusion: In high-risk emerging adults, greater CUD symptom burden is associated with lower surface area and greater thickness in OFC and mPFC/ACC subregions. Using the high-resolution Glasser atlas, these findings provide a more precise characterization of structural correlates of CUD and highlight potential neurobiological markers linked to affective and motivational processes underlying cannabis use.

Background: Prenatal substance exposure (PSE) occurs when an individual is exposed to substances in utero. PSEs may have lasting effects on mental health. We tested whether PSEs show threshold, cumulative, or individual substance associations with childhood psychiatric diagnoses. Methods: Clinical variables (demographics, ICD-9/10 diagnoses, PSE history) were extracted from electronic health records from the University of Minnesota Adoption Medicine Clinic. PSEs were identified from caregiver and child-protective-services narratives and/or toxicology (cord tissue/blood, meconium). For each ICD-9/10 diagnostic category, we fit logistic regression models comparing (1) exposure thresholds (0, 1, 2, 3, 4+ exposures), (2) a cumulative exposure count, and (3) individual substances to estimate marginal odds ratios (ORs) with 95% Confidence Intervals (CIs). Results: Psychiatric diagnoses increased with the number of PSEs. Relative to no exposure, odds of an Anxiety Disorder rose from OR 1.47 (95% CI 1.16-1.87) with one exposure to OR 2.03 (1.64-2.52) with >=4 exposures. Higher cumulative exposure scores were associated with Anxiety Disorders (OR 1.28, 1.18-1.38), Behavioral and Emotional Disorders (OR 1.42, 1.31-1.54), Substance Use Disorders (OR 1.52, 1.29-1.79), and Mood Disorders (OR 1.16, 1.04-1.30). Alcohol, tobacco, and marijuana exposures were associated with increased odds of at least one psychiatric diagnosis, and each substance showed at least one significant diagnostic cluster when modeled independently. Conclusion: Increasing numbers of PSEs were associated with higher odds of psychiatric diagnoses, with patterns varying by substance and outcome. These findings motivate research on exposure timing and combinations to support earlier identification and intervention for at-risk children.

The proliferation of gambling advertising has intensified concerns regarding its influence on vulnerable populations, yet the neural mechanisms underlying cue-reactivity to these stimuli remain underexplored in ecologically valid settings. This study protocol proposes a novel methodological framework to investigate prefrontal cortical responses to gambling advertisements in individuals with varying degrees of gambling experience. Materials and methods: This cross-sectional study will recruit 44 participants, divided into a clinical group (individuals with high-frequency gambling or gambling disorder) and a matched control group. Neural activity will be recorded using fNIRS while participants view gambling-related, neutral, violent, and sexual stimuli. Secondary measures include validated scales for gambling severity (SOGS), impulsivity, sensation seeking, and alexithymia. Data analysis will primarily utilize inter-subject correlation (ISC) to quantify neural synchronization and multiband frequency decomposition to capture dynamic affective processing. Advanced preprocessing, including short-channel regression, will be applied to ensure signal robustness. Discussion: By combining portable neuroimaging with a data-driven ISC approach, this study aims to identify objective neural markers of gambling vulnerability. The findings will provide novel insights into the idiosyncratic processing of commercial stimuli, potentially informing public health policies and the development of more effective evidence-based regulations for gambling marketing.

Forensic patients often have complex and costly healthcare needs, even following discharge from secure care. However, little is known about their health and justice outcomes after community reintegration. To address this gap in the literature, we conducted a systematic review and meta-analysis to estimate the incidence of key post-discharge outcomes among community-discharged forensic patients, including any reoffending, violent reoffending, reconvictions, readmissions, all-cause mortality, and suicide. We systematically searched PsycINFO, Embase, CINAHL, Medline, PubMed, and ProQuest Dissertations from database inception to May 2025 (PROSPERO CRD42024529265). Random-effect meta-analyses were used to generate pooled incidence estimates, with heterogeneity quantified using prediction intervals. A total of 49 studies met inclusion criteria (total patient n = 18,871) and contributed to the meta-analyses. The pooled incidence rate per 100,000 person-years was: any reoffending 3,889 (95% CI 2,055, 7,359; 95% PI 290, 52,136); violent reoffending 1,851 (95% CI 1,229, 2,789; 95% PI 201, 17,068); reconvictions 3,291 (95% CI 2,591, 4,179; 95% PI 950, 11,394); readmissions 7,945 (95% CI 5,507, 11,463; 95% PI 1,225, 51,548); all-cause mortality 1,789 (95% CI 1,341, 2,388; 95% PI 673, 4,756); and suicide 407 (95% CI 319, 519; 95% PI 225, 735). Overall, the reoffending rate for forensic patients discharged to the community was lower than that reported for other cohorts of people charged with general and violent offences. However, despite typically receiving long admission periods, discharged forensic patients continue to experience high rates of readmission, all-cause mortality, and suicide relative to other psychiatric patient groups in the community. Together, our findings highlight a need for enhanced post-discharge suicide support for forensic patients living in the community to better facilitate successful, long-term reintegration.

Amitriptyline is commonly prescribed for chronic pain, yet treatment response and tolerability vary substantially. Genetic variation in CYP2C19 and CYP2D6 influences amitriptyline metabolism, but evidence linking pharmacogene status to clinical outcomes in chronic pain is limited. Amitriptyline is typically prescribed for chronic pain at lower doses than for depression, which may reduce pharmacogenomic effects on clinical outcomes. We analysed 1,146 participants with chronic pain from the Australian Genetics of Depression Study who reported amitriptyline use, treatment outcomes, and genotype data. Metaboliser phenotypes were assigned using PharmCAT. Associations with self-reported effectiveness and discontinuation due to side effects were examined using regression models adjusted for age and sex. Only CYP2C19 intermediate metabolisers showed nominally lower odds of discontinuation and reduced likelihood of reporting moderate effectiveness. Overall, pharmacogenetic phenotypes were not significantly associated with patient-reported amitriptyline outcomes in chronic pain, potentially reflecting the lower doses typically prescribed for pain management.

ABSTRACT OBJECTIVE: We performed a systematic review and meta-analysis (SRMA) of post-surgical outcomes, comparing chlorhexidine gluconate (CHG) versus povidone iodine (PI) for vaginal antisepsis of major gynecologic procedures. DATA SOURCES: Ovid Medline, Embase, Scopus, Embase, Cochrane, and Clinicaltrials.gov were searched between 1986 and December 2023, for studies comparing CHG with PI for vaginal antisepsis of major gynecologic operations. STUDY ELIGIBILITY CRITERIA: We included Randomized Controlled Trials (RCTs) and non-RCTs comparing CHG to PI for vaginal antisepsis of major gynecologic operations. The primary outcome was surgical site infections (SSIs) and the secondary outcome was urinary tract infections (UTIs) and vaginal irritation. METHODS: Summary estimates were calculated by fixed effects models when I2 [&le;] 25% and by random effects models when I2 > 25%. Statistical analysis was performed using RevMan 5.4.1. The protocol for this systematic review was registered on PROSPERO (ID CRD42022378101). RESULTS: Nine studies met the inclusion criteria, four of which were randomized controlled trials (RCTs). 9538 patients were included, 4300 (45%) of whom were allocated to CHG and 5238 (55%) to PI. No statistically significant difference in SSI incidence was found for vaginal antisepsis with CHG versus PI in pooled analyses (n= 9538 patients; RR 1.20; 95% CI 0.92-1.57; I2 =0%). In contrast, a significantly higher risk of UTIs was observed for vaginal antisepsis with CHG than with PI (n=6061 patients; RR 1.48 95% CI 1.03-2.14; I2 = 0%). CONCLUSION: In our SRMA, there were no significant differences in SSI risk when either CHG or PI was utilized for antiseptic vaginal preparation. Interestingly, vaginal antisepsis with PI was associated with a lower incidence of post-operative UTIs following major gynecologic surgery. Our findings support current guidelines that form of vaginal antisepsis can be used for SSI prevention. They also suggest that PI may result in fewer postoperative UTIs but further randomized studies are needed to support these findings. Key words: surgical site infection, surgical wound infection, urinary tract infection, urogynecologic surgery, Chlorhexidine, Povidone Iodine, surgical antiseptic,

Background Artificial intelligence-enhanced electrocardiography (AI-ECG) enables scalable, low-cost cardiac dysfunction screening, but existing models are annotation-intensive and predominantly adult-derived, leaving paediatric generalizability uncertain. Paediatric cohorts exhibit highly variable cardiac morphology and function compared to adults, which may be useful for learning generalizable AI-ECG models. Methods We pretrained ECG-Fyler on a predominantly paediatric, all-age cohort at Boston Children's Hospital (1992-2023), annotated with a cardiology-specific coding system (Fyler codes), and evaluated it on assessments from echocardiography (echo) and cardiac magnetic resonance (CMR) studies. We validated on an external adult cohort from Columbia University Irving Medical Center. Performance was benchmarked against several AI-ECG foundation models by AUROC across age groups, lesion types, and limited-data scenarios. Findings The pretraining cohort comprised 782,138 ECGs from 255,271 patients (median age: 10.9 years, IQR: [2.8-16.8]). Internal evaluation included 178,495 ECG-echo pairs (median age: 10.9 [3.7-17.0]) and 8,584 ECG-CMR pairs (median age: 20.7 [15.6-29.6]). External validation included 82,543 ECG-echo pairs from adults (median age: 64.0 [52.0-74.0]). ECG-Fyler improved AUROC across biventricular dysfunction and dilation tasks, with the largest gains in low-data settings. In internal validation, ECG-Fyler detected low left ventricular ejection fraction (LVEF [&le;] 40%) from only 100 fine-tuning samples (AUROC: 0.80, 95% CI: [0.78-0.80]), outperforming other models (AUROC < 0.65) and improving with additional fine-tuning (AUROC: 0.94 [0.93-0.94]). Similar improvements were observed for CMR-derived LVEF, RVEF, and ventricular dilation. In external validation on adults, ECG-Fyler exhibited an AUROC of 0.83 (CI: [0.82-0.85]) for LVEF [&le;] 40%. After fine-tuning on less than 10% of external data, LVEF [&le;] 45% performance (AUROC: 0.87 [0.86-0.88]) outperformed a fully trained, site-specific prior model (AUROC: 0.85 [0.84-0.87]). Interpretation Pretraining on richly annotated, paediatric-dominant ECGs yields models that transfer efficiently across institutions and ages, supporting AI-ECG screening and triage when labels or imaging access are limited. Funding National Institutes of Health (R01LM012973); Kostin Innovation Fund, Boston Children's Hospital

The Epic Sepsis Model version 2 (ESMv2) is a prediction model embedded into the electronic medical record used to warn clinicians which hospitalized patients are at risk for sepsis. We conducted a retrospective cohort study of 31,951 hospitalizations of 25,760 patients to compare analyses conducted at the commonly used patient-level (where a maximum prediction prior to the onset of sepsis is used to measure performance) vs novel prediction-level (where each prediction is used to measure performance). Sepsis, defined by the Sepsis 3 criteria occurred during 1,049 hospitalizations (3.3%). Patient-level analyses suggested excellent discrimination AUC 0.86; [IQR 0.85, 0.87], whereas prediction-level analyses demonstrated lower performance AUC 0.62; [IQR 0.57, 0.65]. Low estimates of the positive predictive value (14.5% at the patient level vs 4% at the prediction level) imply a high number of false alerts. Common evaluation approaches may overstate the performance of dynamic prediction models and mislead clinical decision-making.

Background: Despite the success of combination antiretroviral therapy (cART), vascular comorbidities, including cerebrovascular disease, are more prominent in people living with HIV (PLWH) compared to people without HIV (PWOH). However, quantitative assessments of cerebrovascular morphometry and their associations with cognitive outcomes in the context of HIV are still limited. In this study, we explore this missing link. Methods: Magnetic Resonance Angiography (MRA) data, blood markers, and neurocognitive assessments were collected from 73 PWOH subjects (male: 57, female: 16; age: 53 {+/-} 16) and 99 PLWH subjects (male: 66, female: 30, age: 53 {+/-} 11). Vessel morphometric features were quantified using intraCranial Artery Feature Extraction (iCafe) to investigate associations between vessel morphometry, markers of monocytes, endothelial cell activation, and cognitive performance. Results: HIV status predicted a lower total number of branches ({beta} = -0.224, p = 0.001, d = -0.517) and shorter total distal length ({beta} = -0.173, p = 0.021, d = -0.370) with a moderate effect size. Total branch number was found to be negatively associated with plasma levels of monocyte markers (sCD14: r = -0.167, p = 0.033; sCD163: r = -0.157, p = 0.045) and positively correlated with white matter cerebral blood flow (r = 0.550; p [&le;] 0.05). HIV status was the strongest predictor of overall cognitive performance in ANCOVA model ({beta} = -0.219, p = 0.006, d = -0.453). Conclusions: Our results suggest that cognitive impairment in PLWH is associated with vessel morphology metrics. Monocyte immune activation may contribute to changes in vessel morphology.

Patients with primary immunodeficiency (PID) often face prolonged diagnostic delays and may increasingly turn to large language models (LLMs) to interpret their symptoms during this period. We evaluated whether an LLM could recognize PID from symptom descriptions derived from interviews with 21 PID patients. In a prior study, we showed that GPT-4o identified PID in 96% of cases when prompted with physician-written patient histories (Rider et al., JACI, 2024). Here, when prompted with symptom descriptions in patients' own words, GPT-5 identified PID in only 7 cases (33%), although it more broadly suggested immune system issues in 18 cases (81%). The gap between these findings indicates that LLMs are sensitive to the language and framing of symptom descriptions, performing substantially worse when patients describe their own symptoms in everyday language than when clinicians summarize patient histories in structured medical terms. This study underscores the need to carefully evaluate how LLMs are used in patient-facing applications.

Background Atrial fibrillation (AF) is a leading cause of stroke, cardiovascular morbidity, and mortality. Atrial myopathy, characterized by progressive metabolic, electrical, and structural changes, creates the arrhythmogenic substrate that drives AF. Defining the key drivers of atrial myopathic processes is essential for targeted therapies that can mitigate AF progression. Here we explore how reduced ERBB4 expression contributes to the development of left atrial myopathy. Methods We analyzed the Cleveland Clinic Biobank to compare left atrial ERBB4 levels in patients grouped by AF diagnosis. To investigate the impact of reduced ERBB4 levels on atrial tissue substrate, we created mouse models of cardiac-specific Erbb4 deficiency using Mlc2a (myosin light chain 2a)-Cre. Comprehensive physiological assessments were performed. Transcriptomic analyses of the left atrium were performed in an Erbb4 haploinsufficient mouse model and compared with human atrial datasets. Molecular validation of key dysregulated pathways was performed. Results We found that left atrial ERBB4 levels are reduced in patients with AF. Adult cardiomyocyte-specific Erbb4 heterozygous (Erbb4fl/+;Mlc2a-Cre) mice exhibited prolonged P-wave duration in the absence of ventricular dysfunction. Left atrial transcriptomic analysis in Erbb4 haploinsufficient mice showed upregulation of pathways related to fibrosis, apoptosis, and coagulation, and downregulation of pathways related to fatty acid metabolism and mitochondrial function, mirroring changes observed in pressure overload mouse models. A cross-species transcriptomic comparison revealed significant overlap between ERBB4-correlated gene expression and functional pathways in adult human atria and mice with Erbb4 haploinsufficiency. Validating the transcriptomic data, protein and functional assays demonstrated increased fibrosis, apoptosis, and oxidative stress in the mutant left atrial tissue. Conclusion Left atrial ERBB4 levels are reduced in AF patients. A mouse model of Erbb4 deficiency and human atrial transcriptomic analyses highlight a role for ERBB4 in supporting normal atrial metabolism while protecting against inflammation, apoptosis, and fibrosis.

Intro: Characteristics of the pulse wave transmitted through the carotid arteries are predictive of cognitive decline and cerebrovascular health in humans. This study aimed to identify risk factor trajectories in childhood, adolescence and early adulthood that are associated with forward compression wave intensity (FCWI) in the common carotid artery in adults aged 28 years. Methods: Systolic blood pressure (SBP), body mass index (BMI) and fasting blood glucose (FBG) measured at multiple time-points when participants were aged between 8-20 years were included in a trajectory analysis. At age 28 years, FCWI was measured in 402 (M=206, F=196) participants who underwent a Duplex ultrasound assessment of the common carotid artery. Statistical analysis assessed differences in FCWI between each trajectory group for males and females separately. Results: In males, four trajectory groups were identified for BMI, three for SBP, and two for FBG. In females, three trajectory groups were identified for BMI, SBP, and FG. In males, having higher BMI (P=0.006), SBP (P=0.021) and FBG (P=0.002) from ages 8-20 years was associated with greater FCWI at age 28 years. In females, no associations were found between FCWI at age 28-years and trajectory groups for BMI (P=0.185), SBP (P=0.289) or FBG (P=0.070). Conclusion: Having high BMI, SBP and FBG throughout childhood, adolescence and early adulthood was associated with higher FCWI in the carotid artery at age 28 years in males, but not females. This may have a direct impact on the etiology of cognitive decline and cerebrovascular disease in later life.

Lead is a toxic metal ubiquitous in our environment. While dramatic reductions in lead sources have paralleled equivalent decreases in lead-poisoning rates, chronic lead exposure remains a critical public health concern. Childhood lead exposure (at its lowest levels) is liked to changes in cognitive development but less is known about lead's effects on children's brain structure, especially as a result of in utero exposure. We measured prenatal and early-postnatal lead exposure in shed deciduous teeth of 448 9- and 10-year-old children (from 20 United States cities) and linked those lead levels to childhood brain structure, cognition/behavior, and neighborhood- and family-level socioeconomic characteristics. Here we show negative associations between tooth-lead levels and the thickness of the brain's cortex, particularly in regions linked to language processing. With increasing tooth-lead levels, children of lower-income (versus higher-income) families showed steeper declines in receptive vocabulary. Caregiver-reported behavioral problems exhibited similar associations. With in utero exposure linked to adverse neurodevelopmental outcomes (well before lead exposure and its risks are evaluated by healthcare professionals), prenatal screening of maternal lead levels/exposure, coupled with recommended strategies to reduce its placental transmission, may help reduce lead's effects on future generations.

Background: Conventional psychiatric screening instruments summarize symptoms within individual scales and prioritize cases with high single-instrument additive score severity. This design treats items as independent within instruments and ignores cross-instrument covariance structure, making it insensitive to respondents whose responses are distributed across multiple domains in unusual combinations that remain below threshold on every individual scale. Methods: We analyzed two cohorts spanning older and younger adults. Item prompts from depression, stress, anxiety, and sleep instruments were embedded into a shared semantic space using a pretrained sentence encoder. Principal component analysis of the item-prompt embeddings alone---with no use of respondent data at this stage---was used to construct a low-dimensional subspace retaining 80\% of variance in the item embedding matrix. Normalized participant responses were then projected into this subspace, with Jaccard-based stability analysis used as a check on dimensional robustness. Multivariate deviation from the cohort norm was quantified with Mahalanobis distance using Ledoit-Wolf covariance regularization. Candidate outliers were defined by the empirical 95th percentile of the cohort-specific distance distribution. To isolate response configurations not already captured by conventional single-instrument extreme-value logic, we excluded all outlier respondents who had endorsed any individual item at the maximum value of its Likert scale on any instrument. For the remaining outliers, anomalous components were backtracked to their original item loadings for interpretation. Results: In the older-adult Health and Retirement Study (HRS) cohort, principal component analysis of 27 item-prompt embeddings showed that a 10-dimensional subspace provided a stable representation of cross-instrument semantic structure. In the younger-adult Xinxiang cohort the corresponding stable solution was 16-dimensional. In each cohort, seven respondents remained as multivariate outliers despite falling below every single-instrument extreme-value threshold. These cases were not characterized by uniformly severe symptom scores but by unusual cross-domain response configurations that became visible only in the shared semantic covariance subspace. The response structure of the retained configurations differed across cohorts: older-adult cases more often involved weak endorsement of mood-labeled items alongside nonzero body- and sleep-related responses, whereas younger-adult cases more often involved incomplete response configurations spanning mood, sleep, stress, and self-harm-related items. Conclusions: A semantically aligned, auditable covariance subspace provides a practical tool for flagging unusual multivariate response configurations that single-instrument additive screening may not flag. The method is interpretable at the level of original item contributions. It should be understood as a hypothesis-generating screen for unusual response configurations requiring further clinical assessment, not as a diagnostic instrument. Outcome validity remains to be established by prospective study.

Background: Frontotemporal dementia (FTD) lacks widely accessible disease-specific biomarkers. Optical coherence tomography (OCT) and OCT angiography (OCTA) may provide non-invasive measures of retinal changes associated with neurodegeneration. We conducted a systematic review and meta-analysis evaluating retinal biomarkers in FTD compared with Alzheimer disease (AD) and controls. Methods: A systematic search of PubMed and Embase was conducted through April 25, 2026 according to PRISMA guidelines. Studies evaluating OCT/OCTA biomarkers in FTD with comparator groups were included. Inverse weighted random-effects models, publication bias assessments, and meta-regressions were performed. Results: Ten studies involving 139 individuals with FTD, 87 with AD, 29 with mild cognitive impairment, 14 with TDP-43 proteinopathy, 5 with tauopathy, and 255 controls were included in the systematic review; five studies were eligible for meta-analysis. Compared with AD, individuals with FTD demonstrated significantly thinner retinal nerve fiber layer (RNFL) thickness (SMD = -0.61, 95% CI -0.98, -0.24). Compared with controls, individuals with FTD exhibited significantly thinner ganglion cell layer-inner plexiform layer (GCL-IPL) thickness (SMD = -0.55, 95% CI -1.02, -0.08), whereas pooled analyses across multiple retinal biomarkers were non-significant (SMD = -0.19, 95% CI -0.52, 0.14). RNFL thickness correlated negatively with female % in FTD and positively with age in both AD and controls. Conclusions: Individuals with FTD exhibit lower RNFL thickness than AD and lower GCL-IPL thickness than controls, suggesting retinal alterations may reflect neurodegeneration. However, larger longitudinal studies with standardized OCT/OCTA protocols are needed to determine the diagnostic and prognostic utility of retinal biomarkers in FTD

Background: Non-communicable diseases (NCDs) represent a critical public health challenge in Kenya, responsible for over 50% of inpatient admissions and 40% of deaths. While digital health tools and artificial intelligence offer promising ways to improve prevention, diagnosis, and management, little is known about how these tools are perceived and used in practice. There is limited research exploring the views and lived experiences of young people in Kenya, who are a strategic priority for NCD prevention because behavioral risk factors are established in this window, and for Community Health Providers (CHPs) who provide health services within the community. This study aims to address this gap by examining the perspectives of the burden of non-communicable diseases and the potential role of digital health technologies, including artificial intelligence, for preventing and managing these conditions in these specific populations. Methods: A qualitative research design using focus group discussions (FGDs) was employed in Nairobi (urban) and Busia (rural) counties between March and July 2024. Eight FGDs were conducted with 60 participants purposively sampled from three stakeholder groups: community health promoters (CHPs), healthcare workers (HCWs), and youth aged 18-35 years. A semi-structured guide, co-developed with a Community Advisory Board, explored beliefs about NCDs, health-seeking behaviors, lifestyle practices, and attitudes toward digital health and AI. Audio recordings were transcribed verbatim, translated where necessary, and analyzed thematically using grounded theory principles on NVivo software (v12). Results: Six consolidated themes emerged: (1) understanding of NCDs and perceived risk; (2) barriers to NCD prevention and care; (3) the role of CHPs; (4) adoption of AI tools for NCD management; (5) trust, ethics and access concerns; and (6) community-driven recommendations for AI integration. Significant barriers including stigma, economic constraints, and barriers to care were documented alongside enthusiasm for AI tools among youth and CHPs in both urban and rural areas. Conclusion: This study shows that AI tools are being used for NCD prevention and management through spontaneous community adoption. However, it emphasizes the need for culturally relevant, equitable, and community-driven solutions. Effective scaling requires the identification and bridging of digital literacy gaps, the establishment of affordable infrastructure, the protection of data privacy, and the integration of artificial intelligence tools into existing community health frameworks. This process should involve the collaboration of trusted intermediaries, such as CHPs and community leaders, to ensure successful outcomes. Future initiatives should prioritize participatory design, policy frameworks for ethical governance, and targeted capacity building to enhance acceptance and sustainability of digital health innovations in low- and middle-income country settings.

Background: Thalamic low-intensity transcranial focused ultrasound (tFUS) has shown promise for increasing behavioral responsiveness in disorders of consciousness (DOC), but no study has examined whether it can causally modulate the well-validated behavioral, electrophysiological, and metabolic biomarkers of DOC impairment. Methods: Sixteen adult patients (44% Female; Age, M=37.81, SD=15.97) with a chronic DOC (Time Since Injury, M=3.39, SD=1.94 years) secondary to severe brain injury (TBI 44%, non-TBI 56%) underwent a 10-day inpatient, longitudinal, single-arm, open-label protocol. tFUS was delivered in a single session targeting the left central thalamus. Well-known behavioral (CRS-R), electrophysiological (EEG {delta}/{beta} ratio), metabolic (18F-FDG PET), and polysomnographic outcomes were assessed at baseline and after sonication. Results: The maximum CRS-R total score increased significantly following tFUS compared to baseline (M=13.27 vs. M=10.33; t(14)=7.407, p<0.001, d=1.913), as did the global EEG {delta}/{beta} ratio (N=14; W=17, p=0.025, r=0.68), with the degree of frontal slowing positively predicting behavioral gains ({tau}b=0.51, p=0.016). Glucose metabolism decreased bilaterally in thalamus and frontal, temporal, and parietal cortices at both post-tFUS timepoints compared to baseline. Finally, N2 sleep increased by 33% following tFUS (N=11; t(10)=2.386, p=0.038, d=0.72), though this did not survive correction. No severe adverse events were observed. Conclusion: Thalamic tFUS can causally modulate well-validated behavioral, electrophysiological, and metabolic biomarkers of DOC. The convergent inhibitory signature across these measures suggests a thalamocortical reset mechanism, complementing existing excitatory neuromodulation approaches and providing the mechanistic foundation for a large, randomized sham-controlled trial.