Faculty Bibliography

BACKGROUND:Accurate and equitable prediction of trauma-related in-hospital mortality is critical for guiding clinical decisions and optimising trauma care resources. Traditional severity scoring systems like the Injury Severity Score (ISS) do not account for demographic factors, potentially limiting their fairness and generalisability across diverse populations. METHODS:We developed and externally validated an artificial intelligence (AI) model based on ISS and integrated demographic features (age and sex) to predict in-hospital mortality after trauma. Data from the Korean Trauma Data Bank were used for model development and internal validation, comprising 121,418 patients with trauma aged ≥15 years treated at 19 trauma centres in South Korea (2017-2022). External validation was performed on an independent cohort of 7458 patients from five trauma centres (four in South Korea and one in Australia, 2022-2024). The primary outcome was trauma-related in-hospital mortality. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, accuracy, and balanced accuracy. Fairness was evaluated by comparing AUROC differences across age (<65 vs ≥65 years) and sex (female vs male) subgroups. FINDINGS/RESULTS:The ISS-based AI model incorporating age and sex achieved high predictive performance (internal validation AUROC, 0.934; external validation AUROC range, 0.901-0.920), outperforming conventional ISS-based methods. The model also demonstrated improved fairness, showing reduced AUROC differences across subgroups (age: 0.068 vs 0.091; sex: 0.021 vs 0.046 for AI model vs ISS, respectively). INTERPRETATION/CONCLUSIONS:Scaling an ISS-based AI model through demographic integration yielded accurate, fair, and generalisable predictions of trauma-related in-hospital mortality. This approach may enhance trauma care decision-making and enable more equitable resource allocation across diverse clinical settings. FUNDING/BACKGROUND:This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2025-RS-2024-00438239) and the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (RS-2024-00509257, Global AI Frontier Lab). In addition, this research was supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (RS-2025-02220492).

Neuromodulatory subcortical systems (NSSs) are uniquely susceptible to dementia-related pathology, leading to frequent molecular and behavioral impairments associated with altered function of these nuclei. Some of these systems display clear sex-specific cytoarchitecture and signaling leading to distinct physiology and behavioral outputs in males and females, while other regions display nominal sex differences. However, the relevance of sex differences in modulating dysfunction of NSSs in Alzheimer's disease (AD) and related dementias is not well understood. This review is a joint effort by the Neuromodulatory Subcortical Systems and Sex and Gender Differences in Alzheimer's Disease Professional Interest Areas of the Alzheimer's Association. We review sex differences in NSSs, both in non-disease states and in AD models and patients. We highlight the possible role of NSSs in driving sex-specific AD susceptibility and potential footholds for sex-based interventions targeting these systems. We conclude by outlining immediate and long-term actions to address the intersection of NSSs, sex, and AD.

INTRODUCTION/BACKGROUND:Though brain fog is common in Long-coronavirus disease 2019 (Long-COVID), the incidence of mild cognitive impairment (MCI) is unknown. METHODS:In an observational cohort study, recovered COVID-positive, Long-COVID, and COVID-negative subjects underwent blinded evaluation using National Alzheimer's Coordinating Center (NACC) and National Institute on Aging (NIA) -Alzheimer's Association diagnostic criteria for dementia and MCI. The cumulative incidence of MCI was calculated for each group, and the hazard of MCI was compared between groups. RESULTS:Among 260 subjects, the cumulative incidence of MCI over 4.4 years was higher with Long-COVID (27%) versus recovered-COVID (5%) or COVID-negative status (1%). There was a higher hazard of MCI for patients with Long-COVID compared to those without (hazard ratio [HR] 3.93, 95% confidence interval [CI] 1.86-8.31, p < 0.001), and specifically for the Alzheimer's disease (AD) -related MCI subtype (HR 3.20, 95% confidence interval [CI] 1.14-9.00, p = 0.027). DISCUSSION/CONCLUSIONS:The cumulative incidence and adjusted hazard of MCI (and specifically AD-related MCI) at 4.4 years was significantly higher among Long-COVID patients compared to recovered-COVID and COVID-negative controls.

INTRODUCTION/BACKGROUND:We examined obstructive sleep apnea (OSA) severity's association with Alzheimer's disease (AD) plasma biomarkers, independent or synergistic with cerebrospinal fluid (CSF) amyloid, and as a proof of concept, whether plasma amyloid beta (Aβ)42/Aβ40 with OSA severity improves detection of amyloidosis and tau pathology. METHODS:In 120 cognitively normal older adults (70 with CSF data) from New York University sleep and aging studies (2013-2021), OSA severity was measured using apnea/hypopnea index with 4% desaturation; plasma Aβ40, Aβ42, tau, and neurofilament light chain (NfL) via single molecule array; CSF amyloid and tau via enzyme-linked immunosorbent assay. Associations evaluated adjusted correlations and generalized models; receiver operating characteristic analyses evaluated diagnostic accuracy. RESULTS:OSA severity correlated with plasma Aβ40 (r = 0.21), Aβ42 (r = 0.26), and Aβ42/Aβ40 (r = 0.20). Plasma tau and NfL associations depended on CSF-Aβ42. OSA severity with Aβ42/Aβ40 improved CSF amyloidosis (area under the curve [AUC] = 0.78) and tau pathology (AUC = 0.71) detection. DISCUSSION/CONCLUSIONS:OSA severity relates to elevated plasma Aβ and, with CSF amyloid, to tau/NfL. Combined plasma and OSA measures aid non-invasive AD associations' detection.

The piriform cortex (PCx), commonly considered to be the primary olfactory sensory cortex, differs from other mammalian sensory cortices by not displaying a stimulus-specific spatial organization but rather displaying widely distributed odor-evoked activity. However, there is evidence of a PCx spatial organization based on output neuron targeting. Here, we performed double-labeled retrograde tracing to reveal neuronal populations of PCx output neurons that project to two regions affiliated with different behavioral significance, the basolateral amygdala (BLA) and lateral orbitofrontal (LO) cortex networks. We found that PCx neurons projecting to BLA and LO are distinct in spatial distribution with minimal overlap, supporting the hypothesis that while odor input is distributed randomly across the PCx, PCx output neurons are organized into target-specific neuronal populations that potentially serve as functional units for odor encoding and odor-guided behavior.

Artificial intelligence (AI) and machine learning (ML) have seen remarkable growth in mental health applications over the past few decades, demonstrating significant potential to transform psychiatric care. Despite these advancements, the translation of AI systems into clinical practice remains fraught with challenges. This Perspective examines critical hurdles in psychiatric AI research, emphasizing limitations in research rigor, model reliability, interpretability, clinical utility, and ethical considerations. We argue that a human-assisted AI framework-incorporating incremental feedback, self-adaptation, and dynamic collaboration-can address biases, enhance transparency, and build trust in AI systems. Moreover, initiatives in clinical education, cultural adaptation, and data/software sharing are essential to fostering public engagement, data transparency, and research reproducibility. By focusing on these areas, we aim to bridge the gap between AI potential and its successful, ethical implementation in mental health care, guiding the development of trustworthy, effective, and culturally adaptive AI-powered psychiatric tools.

BACKGROUND:Hypercalciuria is a prominent characteristic in Dent disease type 1 (DD1) and is associated with kidney stones and nephrocalcinosis. The objectives of this study were to assess fibroblast growth factor 23 (FGF23) and 24,25-dihydroxyvitamin D (24,25(OH)2D) in DD1 patients and investigate the effects of phosphate supplementation on urinary calcium excretion. METHODS:Serum and 24-hour urine assessments from adult and pediatric DD1 patients (n=10 adults; n=9 pediatrics) were compared to adult control subjects with a history of idiopathic calcium kidney stones and hypercalciuria (n=9). Adult DD1 patients and control participants completed an oral phosphate supplementation intervention (1g/day x 14 days) with reassessment immediately following intervention. RESULTS:FGF23 was significantly lower in DD1 than in the control cohort (adults, p=0.006) and positively correlated with 24,25(OH)2D across all study cohorts. The concentrations of 24,25(OH)2D were low with conversion ratios (25-hydroxyvitamin D:24,25(OH)2D) exceeding the clinical reference limit for five of 10 adults and six of nine pediatric DD1 patients. The DD1 cohorts were then stratified by the 24,25(OH)2D ratio into "normal" and "low" 24,25(OH)2D. Adult DD1 patients with low 24,25(OH)2D (n=5) had lower FGF23, higher 1,25(OH)2D, greater urine calcium, and greater urine protein. Pediatric stratified data mirrored that in adults with the exception of no difference in serum 1,25(OH)2D. Phosphate supplementation was effective in decreasing urine calcium in both adult DD1 and control adult cohorts. CONCLUSIONS:Clinical measurement of 24,25(OH)2D is a novel and useful analysis for evaluating the severity of calcium and protein dysregulation in DD1. In addition, moderate phosphate supplementation effectively mitigates urine calcium excretion in DD1 adult patients.

Neuronal firing patterns have significant spatiotemporal variability with no agreed-upon theoretical framework. Using a combined experimental and modeling approach, we found that spike interval statistics of excitatory neurons in the mammalian forebrain are dominated by a universal low-rate ("ground state"; GS) mode, with irregular spiking at neuron-specific rates. In contrast, when firing rates are increased during intrinsic network patterns or in response to stimuli, spiking across neurons is temporally coordinated with more regular spiking patterns in a region- and brain-state-specific manner. We demonstrate the generality of this distinction in six forebrain areas and show that the majority of spikes in all regions are emitted in the GS mode, emphasizing its physiological importance. We hypothesize that GS spiking maintains persistent neuronal dynamics.