Pediatric Research

Objectives: Using a nationally representative database of U.S. hospitalizations, we aimed to (1) characterize contemporary trends in hypoxic-ischemic encephalopathy (HIE) prevalence by severity, therapeutic hypothermia (TH) utilization, and associated in-hospital mortality; and (2) examine the association between TH and mortality by HIE severity and gestational age (GA), focusing on 35- and 36-weeks GA. Methods: We analyzed newborn hospitalizations from the National Inpatient Sample, 2016-2023. Unspecified, mild, moderate, and severe HIE were identified using ICD-10-CM diagnosis codes P91.60-P91.63; and 35- and 36-weeks GA using codes P07.38-P07.39. TH was identified using ICD-10-PCS codes 6A4Z0ZZ and 6A4Z1ZZ. Survey-weighted multivariable generalized linear models with marginal standardization were used to estimate adjusted mortality risk differences (RD) with surprisal (S) values, and assess whether associations between TH and mortality differed by HIE severity across GA strata. Results: Among 29,767,238 hospital discharges, HIE was identified in 66,535 neonates (2.24 per 1,000), and TH used in 19.2% of HIE cases. In-hospital mortality was 9.74% among all HIE cases and 6.65% among TH-treated neonates. From 2016-23, HIE prevalence nearly doubled (1.58 to 3.01 per 1,000; p-for-trend <0.001) and TH utilization more than doubled (0.33 to 0.74 per 1,000; p-for-trend <0.001), while TH use as a proportion of HIE remained stable (17.8%-20.8%; p-for-trend=0.39). HIE severity distribution was: mild (15%), moderate (29.4%), severe (18.3%), and unspecified (37.3%), with moderate HIE increasing over time (22.3%-33.5%). Crude mortality was consistently highest for severe HIE (range: 33.65%-35.25%). Among infants with severe HIE, TH was associated with reduced mortality overall (RD -10.12%; 95% CI -14.86, -5.39; p<0.001; S=15.12), and specifically at 36-weeks GA (RD -21.98%; 95% CI -35.85, -8.12; p=0.002; S=9.06), but not at 35-weeks (RD -1.83%; 95% CI -21.2, 17.55; p=0.86; S=0.22). Conclusions: TH was associated with mortality reduction in severe HIE overall and at 36-weeks GA, but this benefit remains uncertain at 35-weeks GA.

OBJECTIVE: Sepsis-associated encephalopathy (SAE) and sepsis-associated delirium (SAD) lack confirmatory laboratory tests or biomarkers. We evaluated whether the Th17/interleukin (IL)-17 axis or neuroglial-injury biomarkers reflect acute brain dysfunction beyond systemic inflammation and whether biomarker profiles differ between these phenotypes. DATA SOURCES: EMBASE, MEDLINE/PubMed, and the Cochrane Library from inception to August 1, 2026, supplemented by backward and forward citation searching, following PRISMA 2020. STUDY SELECTION: Observational studies of adults with sepsis classified by SAE or SAD status and reporting circulating biomarker concentrations by neurological group or biomarker-outcome associations. Eighteen studies (2,388 participants; 1,863 with sepsis) were included. DATA EXTRACTION: Two reviewers independently extracted study, phenotype, assay, and outcome data. Risk of bias was assessed with the Newcastle-Ottawa Scale and certainty with GRADE. DATA SYNTHESIS: Random-effects models pooled standardized mean differences (SMDs) separately against non-septic and septic controls and odds ratios (ORs) for biomarker-outcome associations. IL-6 was the only mediator elevated in both comparative frameworks and associated with outcomes (non-septic controls: SMD, 0.54 [0.25-0.82]; septic controls: SMD, 1.05 [0.51-1.59]; OR, 1.85 [1.50-2.29]). S100B, neuron-specific enolase, IL-10, tumor necrosis factor; and interferon-gamma; were elevated versus septic controls, whereas IL-17 was modestly elevated only versus non-septic controls (SMD, 0.37 [0.01-0.73]). The IL-6 septic-control effect was concentrated in SAE (p<0.0001) and remained robust in leave-one-out and risk-of-bias sensitivity analyses. Certainty was low to very low, and all 14 computable prediction intervals included the null. CONCLUSIONS: IL-6 emerges as the leading circulating candidate biomarker of sepsis-associated brain dysfunction, while S100B and NSE capture neuroglial injury beyond sepsis. Current evidence does not establish a discriminating role for the Th17 axis. Future studies require standardized neurological phenotyping and appropriately matched septic controls to establish diagnostic value.

Structural connectomics provides a means of characterising white matter (WM) network organisation using diffusion MRI (dMRI), but reconstructing neonatal structural connectomes remains challenging due to the immature and heterogeneous nature of the developing brain. Although recent neonatal studies have increasingly adopted approaches beyond conventional diffusion tensor imaging (DTI), there remains scope to incorporate more advanced tractography and streamline post-processing approaches within neonatal pipelines. Here, we propose a neonatal structural connectome pipeline integrating surface-based anatomical constraints, ensemble tractography, hierarchical anatomical refinement of pathways (HARP) filtering, and spherical-deconvolution informed filtering (SIFT2) reweighting. We acquired 3T MRI data from 300 neonates (185 preterm, 115 term-born) to assess the impact of pipeline configuration on network organisation. Mean gestational age (GA) at birth was 29.31 (23.43-32.86) weeks in preterm infants and 39.52 (37.00-42.43) weeks in term infants. At scan, mean GA was 40.85 (36.29-49.00) weeks in preterm infants and 42.06 (38.29-48.00) weeks in term infants. Four connectome variants were generated: raw surfaced-based tractograms, HARP-filtered, SIFT2-weighted, and combined HARP+SIFT2. Pipeline performance was primarily evaluated using an existing brain age prediction model: connectome-based predictive model (CPM) and our derived connectomes to estimate GA at scan in term and preterm infants. In addition, global graph theoretical metric analyses were conducted to provide a complementary assessment of pipeline configuration differences in network organisation. In total, seven graph theoretical metrics were calculated and evaluated: global efficiency, local efficiency, transitivity, modularity, assortativity, degree variance and statistical complexity. Across all configurations, connectomes supported accurate brain age prediction, with mean absolute errors (MAE) of 0.76-0.79 weeks in term infants and 1.00-1.06 weeks in preterm infants. Prediction error and brain age gap variability were greater in preterm than term infants across configurations, with HARP+SIFT2 achieving the lowest preterm MAE (1.00 weeks) and brain age gap (BAG) variability (SD = 1.38 weeks). However, differences in prediction performance across configurations were minimal, suggesting limited influence of pipeline choice on brain age prediction. However, analysis of global network metrics demonstrated that pipeline choice significantly influenced downstream measures of network organisation, with HARP+SIFT2 being the only configuration to identify significant preterm vs. term differences across all seven metrics examined. These findings demonstrate the importance of considering tractography and streamline-processing choices when constructing neonatal structural connectomes and provide a framework for more anatomically informed investigation of early brain development.

Introduction: Fighting the ventilator (FV) is characterized by a patients active counteraction of respiratory gas flow across multiple breaths during mechanical ventilation. An effective ventilation is prevented during such episodes. The objective of this exploratory study was to evaluate clinicians knowledge, perception and agreement regarding this condition. Methods: In a cross-sectional online survey, medical professionals with experience in intensive care medicine (mostly neonatal and pediatric patients) responded to 11 questions covering various clinical aspects of FV. Results: All respondents were familiar with the phenomenon and assessed it to be clinically relevant. Neonates were perceived to be predominantly affected. Promoting factors of FV included inadequate sedation and ventilation-associated factors. In clinical practice, the participants identified FV by clinical evaluation, analysis of ventilator waveforms and capnography and used both pharmacological and non-pharmacological intervention strategies. There was no consensus concerning the English terminology of the condition. Only few respondents were familiar with local guidelines to manage FV. Conclusion: Although there was consensus on the relevance of FV, diagnostics and management strategies were highly heterogeneous. Many participants agreed that poor patient-ventilator synchrony was an important cause of FV. Future work should focus on characterizing and generating evidence on FV.

BACKGROUND Traditional organ dysfunction classifications after severe trauma rely on binary categories (e.g., chronic critical illness [CCI] versus rapid recovery), which likely oversimplify the true heterogeneity of postinjury organ dysfunction trajectories and their underlying immune-biologic drivers. We hypothesized that severely injured trauma patients demonstrate multiple, distinct organ dysfunction phenotypes distinguished by unique immune signatures. METHODS We performed a prospective, longitudinal, observational cohort study of severely injured trauma patients at high risk for multiple organ dysfunction at a single Level 1 trauma center. Organ dysfunction was quantified daily through 28 days, death, or discharge using a trauma-specific modified Sequential Organ Failure Assessment (mSOFA) score excluding the neurologic subdomain to isolate systemic organ dysfunction from traumatic brain injury. We utilized group-based trajectory modeling to identify longitudinal mSOFA phenotypes. Plasma immune protein trajectories were compared across phenotypes using mixed-effects models with time interaction. RESULTS Sixty-nine patients were enrolled. Trajectory modeling identified five mSOFA phenotypes (c1-c5) with differences in resuscitation requirements, shock severity, and 28-day mortality, but not baseline demographics, injury severity, or early physiologic parameters. The phenotypes revealed organ dysfunction heterogeneity not fully captured by CCI/rapid recovery classification. Forty of 92 measured immune markers showed phenotype-differentiated trajectories (FDR<0.1). The most fulminant phenotype (c5) was distinguished by IL-17C, CXCL5, and CXCL6, implicating epithelial-barrier and neutrophil-trafficking mechanisms. The phenotype with highest CCI incidence (c3) was distinguished by rising CXCL9, ARTN, and TWEAK, implicating Th1 polarization and tissue-inflammation/repair signaling. The clinically distinct, older-age phenotype (c4) carried the largest differentiating signature (29 proteins), spanning renal injury/repair, endothelial activation, and adaptive lymphocyte modulation. CONCLUSIONS Organ dysfunction after severe trauma is more biologically heterogeneous than traditional clinical classifications suggest. Distinct mSOFA trajectory phenotypes correspond to distinct immune signatures, supporting separable pathobiology rather than a single axis of injury severity, with implications for phenotype-targeted precision immunomodulatory approaches in critical illness.

Incidence of ventilator-associated pneumonia (VAP) is increased in patients admitted for brain injury. Staphylococcus aureus appears to be a particularly common pathogen in these respiratory infections. Our aim was to confirm the extent of S. aureus involvement in VAP among patients with neurological injuries. We conducted a retrospective, multicenter study including patients with and without neurological injuries who developed VAP during their ICU stay. Among 15 702 patients admitted in the participant centers during the study period. 407 were finally included in the study. S. aureus was involved in 122 (61.6%) VAP in brain-injured patients and 63 (30.1%) of non-brain-injured patients. In brain-injured patients, multivariate analysis identified age (0.97 [0.95; 0.98]), antibioprophylaxis (0.31 [0.18; 0.53]; p < 0.0001), subarachnoid hemorrhage (2.18 [1.01; 4.68]; p=0.0461), lower Glasgow coma score (0.92 [0.87; 0.97]; p= 0.004) and SAPS II (0.98 [0.97; 1]; p=0.0174) as critical factors associated with the risk of S. aureus in VAP. In the non-brain-injured population, multivariate analysis identified antibioprophylaxis (0.38 [0.22; 0.65]; p=0.0006), age (0.96 [0.95; 0.98]; p<0.0001), SAPS II (0.98 [0.97; 1]; p=0.0265), thoracic surgery (0.21 [0.09; 0.48]; p=0.0002) and peripheral neurosurgery (1.95 [1.2; 3.19]; p=0.0076) as critical factors. A total of 172 patients (42.3%) died during their ICU stay and 90-days mortality was 194 (47.7%). No difference of mortality was noticed function of VAP-associated pathogen.

Introduction and objectives Hydrocephalus is a common complication of aneurysmal subarachnoid haemorrhage. This is one of several standard indications for the insertion of an external ventricular drain, but there are no standard guidelines for timing of extraventricular drain discontinuation in this population. Therefore, the study aims were to examine the 1) factors associated with extraventricular drain duration in aneurysmal subarachnoid haemorrhage and 2) association between extraventricular drain duration and clinical and resource-based outcomes. Methods In this single centre retrospective cohort study, data for adult patients treated in the ICU between 2015-2023 with aneurysmal subarachnoid haemorrhage and requiring an extraventricular drain were analysed. Data were extracted from both a prospective patient registry and the electronic medical record. Linear regression modelling was used to identify the factors associated with extraventricular drain duration. Measures used to examine the association between extraventricular drain duration, and the outcomes of interest included hazard ratio, relative risk, and mean differences as appropriate for a specific outcome. Results Of the participants (n=205), 68% (n = 140) were female, mean age was 60.7 (SD 13.3) years and 71% (n = 145) had a modified Fisher score of 4. Mean extraventricular drain duration was 15.3 (SD 8.6) days. The number of days mechanically ventilated and extraventricular drain challenge by clamp trial were associated with an increased duration of extraventricular drain treatment. Increased extraventricular drain duration was associated with an increased incidence of ventriculoperitoneal shunt insertion, and an increase in ICU and hospital length of stay when extraventricular drain duration exceeded 20 days. Conclusion The factors associated with an increased duration of extraventricular drain treatment were a longer duration of mechanical ventilation. The outcomes associated with an increased duration of extraventricular drain treatment were an increased incidence of ventriculoperitoneal shunt insertion, an increased incidence of ventriculitis when extraventricular drain duration exceeded 20 days, and an increase in ICU length of stay. These study findings may inform the conduct of a larger multi-centre study to examine the factors associated with duration of treatment with extraventricular drain, and outcomes associated with extraventricular drain duration.

Sepsis is a global health problem. Patients in the Intensive Care Unit (ICU) are at risk of having sepsis because of their vulnerability and use of invasive medical devices. Emerging antimicrobial-resistance complicates treatment. Understanding bacterial profiles and antibiotic sensitivity patterns in the ICU plays an important role in managing sepsis, optimizing antimicrobial use, and improving patient outcomes. The aim of this study was to show bacterial profiles and antibiotic sensitivity patterns among patients who were admitted to the ICU at Mbeya Zonal Referral Hospital for 12 months. This was a prospective cross-sectional study among 187 sepsis-suspected patients. Data analysis was performed using SPSS Version 27. Categorical data were summarized by frequency and percentage. Fishers exact test, chi-square test, and modified Poisson regression were used to show the association between patients clinical variables and culture positivity at a 95% CI. Statistical significance was set at a p-value < 0.05. Out of 187 samples, 41.7% were culture positive. Gram-negative bacteria were commonly isolated (65.4%, with Klebsiella pneumoniae and Escherichia coli being commonly isolated. Commonly isolated Gram-positive bacteria were Coagulase-negative Staphylococcus species (19%). 100% of gram-positive bacteria and 96% of gram-negative bacteria were Multi-Drug Resistant (MDR), respectively. In multivariable analysis, patients who were intubated and mechanically ventilated (aPR = 2.208, 95% CI: 1.133-4.305, p = 0.020) and post-laparotomy patients (aPR = 3.241,95% CI: 1.320-7.958, p = 0.010) independently had a higher proportion of Gram-negative bacteria. The study reveals a high level of resistance to commonly used antimicrobials in our setting, necessitating strengthening of the antimicrobial stewardship program and routine surveillance of antimicrobial resistance patterns.

Summary Background We used sequential target trial emulation (TTE) to examine associations between opioid analgesic initiation and adverse maternal and neonatal outcomes while accounting for gestational timing, time at risk, and potential confounding. Methods Using the Early Life Course platform, comprising linked population-based data for births in New South Wales, Australia (2013-2019), we emulated a new trial at each gestational week, comparing women who initiated a prescribed opioid analgesic with eligible non-initiators. Baseline covariates were balanced using inverse probability weighting. Weighted logistic regression estimated odds ratios (ORs) for neonatal outcomes, postpartum haemorrhage, and severe maternal morbidity. Pooled logistic regression estimated hazard ratios (HRs) for other maternal outcomes, combined across gestational weeks using fixed-effects meta-analysis. Sensitivity analyses assessed unmeasured confounding, exposure misclassification, and potential reverse causation. Findings Among 511,357 pregnancies, over 80% of opioid initiators received only one dispensing. Opioid initiation was not associated with increased risks of placental abruption (HR 0.94, 95% CI 0.75-1.16), severe maternal morbidity (OR 1.05, 0.97-1.11), postpartum haemorrhage (OR 0.98, 0.95-1.02), low Apgar score (OR 0.99, 0.87-1.08), small for gestational age (OR 0.90, 0.85-0.95), or neonatal abstinence syndrome (OR 0.98, 0.72-1.30). Risks were elevated for PPROM (HR 1.10, 0.98-1.23), preterm birth (HR 1.26, 1.19-1.33), severe neonatal morbidity (OR 1.08, 1.02-1.17), and perinatal death (OR 1.29, 1.10-1.52). Perinatal death estimates attenuated in analyses addressing potential reverse causation. Interpretation Using a TTE approach that accounted for gestational timing and time at risk, we found no appreciable increase in most maternal or neonatal outcomes following predominantly short-term opioid initiation. Elevated risks of preterm birth, perinatal death, and third-trimester PPROM may reflect causal effects or confounding by pregnancy-related indications. Studies using time-appropriate designs and detailed information on prescribing indications and their timing are needed to clarify these associations.

Purpose Prescribing to lactating women is constrained by limited evidence. Published compatibility classifications provide clinical guidance and a discrete research comparator. How often prescribing diverges from that guidance, and what characteristics are associated with divergence, is unknown at national scale. Methods Retrospective analysis of prescriptions filled during lactation, identified in the 2012-2014 MarketScan Commercial Claims Database. Prescriptions were classified as concordant (Hale's lactation risk category L1-L3) or discordant (L4-L5). Multivariable logistic regression identified factors associated with concordance. Results Of 96,484 new prescriptions, 95,710 (99.2%) were concordant and 774 (0.8%) were discordant. Discordant prescriptions were filled later after delivery (median 59 vs 33 days) and had a day supply three times longer (30 vs 10 days). In multivariable analysis (N=28,732), concordant prescriptions were associated with maternal age under 35 (adjusted odds ratio (aOR)=1.34, 95% confidence interval (CI): 1.02-1.75) and chronic-condition medications (aOR=10.94, 95% CI: 6.47-18.50), and were less likely within 14 days of delivery (aOR=0.53, 95% CI: 0.38-0.73) and with each additional day of supply (aOR=0.96, 95% CI: 0.96-0.96). Compared with family practice, concordance did not differ for obstetric, internal medicine, or emergency medicine prescriptions, but prescriptions from other provider types had lower odds of concordance (aOR=0.57, 95% CI: 0.41-0.79). Conclusions Prescribing during lactation was overwhelmingly concordant with published compatibility guidance; the rare divergence was patterned by prescription and prescriber characteristics. Because the categories are an expert classification rather than consensus guidance, divergence should not be read as inappropriate prescribing.

Personalized medicine aims to tailor treatments to individual patients, but its implementation is limited by scarce clinical resources and heterogeneous treatment effects. Electronic health records now offer longitudinal data that can support data-driven therapy selection. We focus on SGLT2 inhibitors, medications with broad metabolic and cardiovascular benefits, whose clinical impact varies significantly based on individual patient profiles. We propose a counterfactual Structural Causal Model (SCM) to estimate individual treatment effects (ITE) of SGLT2 inhibitors from observational data. The model assumes counterfactual stability and uses a Gumbel-Max sampling mechanism to capture stochastic treatment assignment while enabling differentiable inference. Optimal treatments are defined by maximizing the counterfactual value of future diagnostic outcomes. We evaluate the Counterfactual Gumbel-Max SCM using a doubly robust value estimator and show that, across diagnostic categories, it outperforms real-world prescriptions in predicted treatment value, highlighting subpopulations where SGLT2 inhibitors yield superior outcomes. By integrating causal inference with electronic health data, this framework provides individualized counterfactual reasoning about SGLT2 treatment effects and can support clinicians in identifying optimal therapies for type 2 diabetes and comorbid conditions.

Brazil has one of the highest dengue burdens globally, with transmission influenced by climate events. Yet, the effects of compound climate extremes on dengue risk and prediction have not been quantified to date. Using a Bayesian spatiotemporal model of monthly dengue cases across 435 health regions from 2010 to 2025, we estimated relative risk associated with interacting long-lag and short-lag drought indicators and temperature anomalies across nine Koppen-Geiger climatic zones, adjusting for absolute temperature and El Nino-Southern Oscillation. Long-lag dry, mid-lag warm and short-lag wet conditions were associated with the highest relative risk in five climatic zones, with temperature anomalies modifying hydrometeorological dynamics more strongly in temperate than tropical areas. Climate covariates improved the prediction of case counts and outbreaks compared to baseline models at lead times of 1, 3, 6 and 12 months, and for the upcoming season 5 months ahead. Improvements were greatest in the Northeast, Southeast, and Midwest. Recent dengue incidence provided the greatest improvement at the 1-month lead, whereas combining incidence with climate information performed best at 3- and 6-month leads. We extended our framework to weekly state-level predictions of the season ahead to align with national public health planning. We proposed a multi-staged dengue forecasting approach to enhance early warning and response across Brazil.

Background: Added sugars during early development may influence adiposity, but whether associations vary by developmental timing and child sex is unclear. Objectives: To determine whether child sex modifies associations of added sugars and fructose exposure from pregnancy through 24 months with body composition at 24 months. Methods: This secondary longitudinal analysis included 130 mother-child dyads. Maternal diet was assessed during mid-pregnancy and child diet at 2wk and 6mo (infancy), and 12mo and 24mo (toddlerhood). Multivariable regression tested sex-by-exposure interactions for anthropometric outcomes; 42 children had usable dual-energy X-ray absorptiometry (DXA) data. Results: Prenatal added sugars were more positively associated with percentage body fat and total and regional fat mass in girls than in boys. Prenatal fructose was more positively associated with waist circumference in boys. During infancy, added sugars were more positively associated with percentage body fat and total and regional fat mass in boys, whereas fructose was more positively associated with fat-free mass in girls. Conclusions: Associations of early-life sugars exposure with body composition varied by developmental timing and child sex. Findings from the smaller DXA subset are exploratory and require replication but suggest that susceptibility to early dietary sugars may differ across developmental windows.

Polygenic scores (PGS) predict an individual's genetic value for a complex trait of interest by aggregating effect size estimates from genome-wide association studies (GWAS). While powerful, this approach assumes that genetic variants affect the phenotype in an additive way, which might be problematic when dominance is part of the genetic architecture. To address this limitation, we developed PGSa,d, a simple polygenic scoring framework, rooted in quantitative genetics theory, that incorporates both additive (a) and dominance effects (d) directly. We evaluated PGSa,d against the standard GWAS-based PGS (PGS{beta}) in simulations. The results showed that PGSa,d consistently achieved lower root mean squared error (RMSE) and progressively higher R2 as dominance contributed more to the genetic architecture. We then applied the method to 16 blood cell traits, height, and body mass index (BMI) from UK Biobank. PGSa,d showed comparable R2 to PGS{beta} for all traits (including height and BMI whose architecture is predominantly additive) and significantly lower RMSE for four traits after strict Bonferroni correction. Across traits, RMSE improvement from PGSa,d was positively associated with the magnitude of the estimated dominance effects, whereby traits with larger dominance effects displayed lower RMSE from PGSa,d. As a byproduct of our analysis, we also identified 141 variants in 39 genomic regions with significant dominance effects after Bonferroni correction across traits, recapitulating known associations and identifying novel ones. Together, these results show that explicitly modeling additive and dominance effects is a robust strategy that can improve individual-level predictions, especially when dominance contributes to complex trait architecture.

Background and Objectives Transient ischemic attack (TIA) diagnosis is challenging because it relies mainly on clinical assessment and exclusion of common differential. Functional MRI (fMRI) may provide a diagnostic biomarker by detecting transient brain dysfunction not visible on conventional imaging. This pilot study aimed to characterize acute motor-task BOLD activation in patients with suspected DWI-negative TIA and compare functional patterns between confirmed TIA and alternative diagnoses. Secondary objectives were to assess longitudinal changes in activation and connectivity at 3 months. Methods In this prospective single-center study, adults presenting within 24 h of transient anterior-circulation neurological symptoms underwent conventional MRI and additional motor-task fMRI. Patients with acute DWI lesions were excluded. Final diagnosis was established after 3-month follow-up. Whole-brain analyses, individualized motor cortex region-of-interest (ROI) analyses, and generalized psychophysiological interaction (gPPI) connectivity analyses were performed during the acute phase and at 3 months. Results Eight patients were enrolled; six had complete longitudinal imaging data and were included in the final analyses. Final diagnoses were TIA (n=2), migraine aura (n=2), functional neurological disorder (n=1), and hypoglycemia (n=1). Whole-brain and ROI analyses showed reduced bilateral motor-related BOLD responses during the acute phase in both TIA patients and in the patient with hypoglycemia. In contrast, patients with migraine and functional neurological disorder exhibited less marked longitudinal changes. In TIA patients, motor cortex activation increased at 3 months, tending to normalize toward values observed in non-TIA participants. Connectivity analyses revealed heterogeneous patterns, but the 2 TIA patients demonstrated increased longitudinal connectivity between the motor cortex contralateral to symptoms and other sensorimotor regions, including supplementary motor, premotor, parietal, and postcentral cortices. Discussion These preliminary findings suggest that TIA may be associated with transient bilateral reductions in motor-network activity. Functional abnormalities appeared to improve over time, supporting the hypothesis of reversible network dysfunction. Although limited by the very small sample size, this study provides the first longitudinal assessment of emergency task-based fMRI in rigorously defined TIA and supports further investigation of acute functional MRI as a potential biomarker of transient cerebral dysfunction.

Chinese is one of the living languages with the highest homophone densities, making homophone processing a critical component of language comprehension and orthographic decoding, as well as an ideal model for examining its cognitive mechanisms. This study assessed mono- and bi-character homophone selection function in 129 Mandarin- and Cantonese-speaking participants, including 66 cognitively healthy individuals, 17 with semantic variant (sv) primary progressive aphasia (PPA), 23 with the nonfluent/agrammatic variant (nfv) PPA, and 23 with the logopenic variant (lv) PPA. All PPA variants showed impairment in homophone selection, with most significant deficits in svPPA and lvPPA. ROC analyses demonstrated its strong diagnostic utility for distinguishing PPA from controls. Voxel-based morphometry revealed that homophone performance correlated with gray-matter volume in left anterior and inferior temporal regions, with variant-specific patterns observed. These findings described the potential role of homophone selection in diagnosing PPA syndrome in Chinese speakers, illuminate crosslinguistic influences on language impairment in PPA, and provide novel insights into the cognitive processing of homophones.

Lesion network mapping (LNM) has provided a compelling framework in clinical neuroscience, linking focal brain damage at heterogeneous anatomical locations to shared functional networks across behavioural syndromes. Recently, the methodological specificity of LNM has come under discussion following observations that derived network maps tend to converge onto the normative connectome's generic degree distribution. While current efforts largely treat this convergence as a statistical inference challenge addressable via post-hoc spatial null models or individual-level analyses, we identify a foundational upstream measurement artifact operating within individual patients: the lesion "bystander effect". Because pathological lesions follow biological constraints rather than functional brain parcellations, a typical lesion encapsulates both a symptom-driving critical node and surrounding asymptomatic bystander tissue. By averaging connectivity profiles across the entire lesion mask, LNM mechanically dilutes focal clinical signals. Across empirical clinical cohorts, individual-level machine learning classifiers, synthetic within-cohort lesion unions, and whole-brain spherical simulations, we demonstrate that increasing lesion extent deterministically drives network maps toward the connectome degree vector following a mathematical power law. Fulfilling the clinical promise of LNM will therefore require computational strategies that isolate the causal functional core from surrounding bystander tissue prior to network projection.

Blood-based neurofilament light (NfL) is associated with all-cause mortality, but whether this reflects neuroaxonal injury or overlaps with cognitive and functional decline remains unclear. We followed 559 individuals aged 92-107 from three oldest-old cohorts for up to 16 years: cognitively healthy Dutch centenarians and two population-based Danish cohorts. Plasma biomarkers (A{beta}42/40, A{beta}40, A{beta}42, pTau-181, pTau-181/A{beta}42, NfL, and GFAP; Dutch cohort; NfL, Danish cohorts), cognition, and activities of daily living (ADL) were evaluated against mortality. NfL was the only biomarker consistently associated with mortality (HR 1.21-1.38), whereas AD-specific biomarkers did not predict mortality despite reflecting post-mortem AD neuropathology. NfL remained associated with mortality independently of cognition and ADL; ADL mediated 13-21% across cohorts and cognition 28%, only where cognitive impairment was widespread. Mortality at extreme age is more closely linked to neuroaxonal injury than to upstream AD pathology, with NfL capturing biological vulnerability beyond cognitive and functional decline.

Objectives: To determine how strongly clinical referral text, rather than image content, drives the decisions of multimodal large language models (LLMs) differentiating glioma from brain abscess on MRI. Materials and methods: This retrospective single-center study included 60 contrast-enhanced T1-weighted brain MRI examinations (30 gliomas, 30 abscesses; reference-standard diagnosis). One axial slice per case was paired with five referral texts (explicitly inflammatory to explicitly tumor-suggestive) under three prompt instructions and submitted 20 times each to GPT-4o, Claude Sonnet 5, Gemini 3.5 Flash, and Qwen 3.6 (72,000 answers). The primary outcome was the text-driven span (difference in tumor-call frequency between explicit inflammatory and explicit tumor text). Two blinded radiologists classified the images without text; sensitivity, specificity, and accuracy were compared descriptively. Results: Patients (29 women) had a mean age of 55.8 +/- 16.4 years. With neutral text, models answered tumor in 45-67% of queries (specificity, 0.38-0.78), versus 52% and 60% for radiologists (specificity, 0.77 and 0.63). The text-driven span was 0.79-1.00 (p < 0.001 for all models), whereas confirmed gliomas and abscesses differed by only 0.01-0.10 in three models and 0.25 in Gemini 3.5 Flash. Subtle wording produced at least 83% of the span in three models. An instruction to ignore the text reduced the span to 0.48-0.70 in three models and to 0.04 in Gemini 3.5 Flash, partly through reversion to a tumor default. Model accuracy was 0.52-0.73 versus 0.78 and 0.73 for radiologists. Conclusion: Multimodal LLMs deferred to referral text over imaging evidence in differentiating glioma from brain abscess, and prompt instructions did not reliably correct this.

Objective: Mental health challenges are highly prevalent in autism, but the degree to which they are similar in experience and etiology to the general population remains unclear. This study's objective was characterization of phenotypic and genetic architectures of psychiatric symptomatology in versus out-of-autism. Methods: Psychiatric symptoms were evaluated using the Child Behavior Checklist (CBCL) in 22,152 children (8-15 years): 11,111 autistic children with verbal abilities from SPARK and 11,041 non-autistic children from ABCD. The CBCL's canonical, population-wide factor structure and genetic associations were compared between cohorts. In parallel, exploratory factor analysis was conducted in SPARK, with resulting dimensions associated with key clinical phenotypes (cognitive ability, co-occurring neuropsychiatric diagnoses), polygenic scores (PGS) for psychiatric disorders, and de novo burden in autism-associated genes. Results: Confirmatory factor analysis supported the canonical structure in ABCD but not in SPARK. Psychiatric PGS associations with canonical CBCL subscales were weaker in SPARK than in ABCD, with the ADHD PGS association to Attention problems lower in SPARK ({beta}=0.05 [CI: 0.04,0.06] than in ABCD ({beta}=0.17 [0.13,0.21]). SPARK exploratory factor analysis replicated canonical internalizing factors while revealing other structural departures, including a distinct Developmental Delays factor and dispersion of social problems across multiple factors. The Developmental Delays factor had the strongest associations with de novo burden and lower cognitive ability but was weakly associated with psychiatric PGS. In contrast, common genetic variation explained larger proportions of variances in somatic and inattentive factors and had stronger PGS associations. Conclusions: Correlation structures and genetic architectures of psychiatric symptoms differed in autism compared to the broader population, emphasizing the need for autism-specific approaches in assessment and treatment.