Faculty Bibliography

In mice and many other species, aggression levels are low in virgin females but increase dramatically during lactation to protect vulnerable offspring. This aggression, aimed at protecting the young, is known as maternal aggression. It emerges abruptly after parturition, peaks during early lactation, and declines after weaning. Given its stereotyped temporal profile, hormones associated with pregnancy and lactation are believed to play critical roles in its rise and fall. In addition, maternal aggression diminishes within hours of pup separation and rapidly recovers upon pup reunion, indicating a secondary, pup-dependent regulation of its expression. Here, we review current knowledge of the female aggression circuit and the hormonal and neural mechanisms that reshape it during pregnancy and lactation. We propose a two-step model in which pregnancy-associated sex hormone surges refine the aggression circuit, while lactation-associated neuropeptide signals gate circuit output in response to the need to protect offspring.

Ion channels are the second most common clinical drug target besides G protein-coupled receptors. Aneurysmal diseases pose a significant threat to human life. Novel drug targets for its treatment remain to be explored. We investigated the role of an ion channel, calcium homeostasis modulators 5 (CALHM5), on the development of aortic aneurysms. We characterized CALHM5 as a plasma membrane ion channel abundant in smooth muscle cells of both humans and mice, playing a pivotal role in regulating calcium homeostasis. Notably, CALHM5 deficiency suppressed the transcription of the L-type calcium channel (LTCC) pore-forming subunit by downregulating cAMP-response element binding proteins. This in turn diminished blood vessel contractility and decreased blood flow. Intriguingly, CALHM5 expression is downregulated in smooth muscle tissues of aortic aneurysm patients. Furthermore, CALHM5 deficiency was observed to ameliorate the development of abdominal aortic aneurysms in mice, partly by stimulating smooth muscle cell proliferation. CALHM5 emerges as an ion channel prominently expressed in arterial smooth muscles, serving as a physiological regulator of smooth muscle contraction and presenting itself as a promising therapeutic target for aortic aneurysms.

UNLABELLED:= 123), we found that people’s willingness to exert effort is positively associated with outcome expected value under both risk and ambiguity. Additionally, people exert more effort when outcome distribution uncertainty increases in risky situations, but are insensitive to ambiguity, except when facing extreme ambiguity. Our results demonstrate an unexpected dissociation. Humans will engage in effort-based information-seeking, even for non-instrumental information, when facing risk. In contrast, they show a much lower willingness to expend effort to resolve non-instrumental ambiguity. SUPPLEMENTARY INFORMATION:The online version contains supplementary material available at 10.1038/s41598-026-43803-2.

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).

Ultrasound is the imaging study of choice for the initial diagnosis of autosomal dominant polycystic kidney disease (ADPKD) due to its high diagnostic accuracy and ability to detect kidney cysts as small as 2 to 3 mm. MRI of the kidneys is also highly sensitive at detecting small cysts and is an alternative to US. MRI is the preferred modality for determining total kidney volume (TKV). TKV can be used as an imaging biomarker to predict kidney function decline, track disease progression, and evaluate the effectiveness of treatment. CT abdomen and pelvis with contrast is the test of choice for detecting suspected complications such as renal cyst hemorrhage, rupture, or infection. MRI of the abdomen without and with contrast can also be used for diagnosing complications of ADPKD and is usually appropriate regardless of kidney function. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

The locus coeruleus (LC) plays important roles in sleep/wake regulation and cognitive functions. LC neurons may be particularly sensitive to neural injury and serve as an early site of accumulation pathological tau in Alzheimer's disease. Obstructive sleep apnea (OSA) creates both chronic intermittent hypoxia and sleep fragmentation as potential insults to differentially sensitive neural populations including the locus coeruleus (LC). Using high field 7T imaging in cognitively normal older adults, we demonstrate that time spent with an oxygen saturation below 90% (T90), a measure of OSA's hypoxic burden, inversely correlates with LC structural integrity and explains significant variance in LC structural integrity after controlling for age, sex, and BMI. In contrast, other sleep variables such as the apnea-hypopnea index (AHI), total sleep time, and sleep efficiency did not contribute significant variance in LC structural integrity in this model. Thus, in the diagnosis of OSA, attention to hypoxic burden variables may be important in risk stratification for LC neural injury. This observation may inform future work determining whether mitigation of the hypoxemic burden from OSA can slow deterioration in LC integrity.

Three-dimensional (3D) ex vivo imaging of cleared tissue from intact brains from animal models, human brain surgical specimens, and large postmortem human and non-human primate brain specimens is essential for understanding physiological neural connectivity and pathological alterations underlying neurological and neuropsychiatric disorders. Contemporary light-sheet microscopy enables rapid, high-resolution imaging of large, cleared samples but is limited by the orthogonal arrangement of illumination and detection optics, which constrains specimen size. Light-sheet theta microscopy (LSTM) overcomes this limitation by employing two oblique illumination paths while maintaining a perpendicular detection geometry. Here, we report the development of a next-generation, fully integrated and user-friendly LSTM system that enables uniform subcellular-resolution imaging (with subcellular resolution determined by the lateral performance of the system) throughout large specimens without constraining lateral (XY) dimensions. The system provides a seamless workflow encompassing image acquisition, data storage, pre- and post-processing, enhancement and quantitative analysis. Performance is demonstrated by high-resolution 3D imaging of intact mouse brains and human brain samples, including complete downstream analyses such as digital neuron tracing, vascular reconstruction and design-based stereological analysis. This enhanced and accessible LSTM implementation enables rapid quantitative mapping of molecular and cellular features in very large biological specimens.

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.

INTRODUCTION/BACKGROUND:Accurate preoperative evaluation of pancreatic cysts is essential. However, cytology and biochemical analysis are often limited by low cellularity, and risk stratification is critical for management. PancreaSeq Genomic Classifier (GC) analyzes cyst fluid for molecular alterations to aid diagnosis and risk assessment. MATERIALS AND METHODS/METHODS:We retrospectively analyzed 219 pancreatic cysts from 206 patients using PancreaSeq GC, integrating molecular findings with cytology, biochemical, imaging, surgical pathology, and follow-up. RESULTS:PancreaSeq GC successfully analyzed 216/219 cysts (99%) and detected alterations in 182 (83%). Among cases with both cytology and molecular data (n = 201), concordance was high in cytologically mucinous neoplasms (94%) and atypical cases (95%). Notably, among cases reported as negative for malignancy or nondiagnostic on cytology (n = 128), PancreaSeq GC identified mucinous neoplasms in 82 cases (64%), demonstrating added value in limited samples. Surgical pathology correlation (n = 24) showed excellent performance for distinguishing mucinous from nonmucinous cysts (area under the curve [AUC] = 0.94, P < 0.001). Risk stratification for detection of any dysplasia yielded an AUC of 0.78 (P = 0.006), and for high-grade dysplasia an AUC of 0.74 (P = 0.046). PancreaSeq GC reliably predicted neuroendocrine tumors, but the sensitivity for focal high-grade dysplasia in mucinous neoplasms and serous cystadenoma was limited. Compared with carcinoembryonic antigen (CEA), cyst fluid glucose showed higher sensitivity but lower specificity for mucinous cyst detection. CONCLUSIONS:PancreaSeq GC provides significant diagnostic and risk-stratification value that complements cytological evaluation, particularly in indeterminate or nondiagnostic cytology specimens and when biochemical data are unavailable. Integration of molecular findings improves cyst classification and dysplasia risk assessment. Multidisciplinary assessment remains essential, given the assay's limited sensitivity for focal high-grade dysplasia and serous cystadenomas.