Purpose: Our study identified prognostic factors affecting visual outcomes in patients with unilateral indirect traumatic optic neuropathy (TON), determined the risk of legal blindness, and assessed changes in visual acuity, visual fields, retinal structure, and the therapeutic effect of high-dose corticosteroid treatment. Methods: We retrospectively reviewed the medical records of 52 patients (52 eyes) diagnosed with TON between 2014 and 2023. Patients were categorized into two groups according to the final best-corrected visual acuity (BCVA): Group 1 (BCVA ≥0.1) and Group 2 (BCVA <0.1). Prognostic factors were analyzed using logistic regression, and receiver operating characteristic curve analysis was performed to determine optimal cutoff values. Longitudinal changes in visual acuity, visual field index (VFI), and retinal structural parameters were assessed using a generalized linear mixed model. Results: Factors significantly associated with Group 1 included the absence of intracranial hemorrhage, administration of high-dose steroids within 24 h, and better logMAR visual acuity and VFI within 4 weeks post-trauma. In multivariate analysis, VFI within 4 weeks remained significantly associated with favorable visual outcomes (p = 0.008). The optimal VFI cutoff value for predicting a good prognosis was 13%, yielding a sensitivity of 90% and specificity of 93.3%. Visual acuity outcomes over time differed significantly according to the timing of high-dose steroid administration. Conclusions VFI within 4 weeks after injury was the most reliable prognostic indicator, demonstrating high sensitivity and specificity for predicting legal blindness. Early administration of high-dose steroids within 24 h helped prevent visual deterioration. These findings emphasize the importance of early quantitative assessment of visual function and prompt therapeutic intervention to guide treatment strategies in patients with TON.

Purpose: Preterm birth remains a leading cause of long-term neurodevelopmental impairment, yet early evaluations frequently underestimate subsequent deficits. This study examined longitudinal neurodevelopmental trajectories across gestational age groups and identified predictors of developmental delay. Methods: A retrospective cohort of 532 preterm children, stratified by gestational age, was followed from the neonatal period to early preschool age. Neurodevelopment was assessed using the Korean version of the Bayley Scales of Infant and Toddler Development, Third Edition at 8–12 months (n=481), 13–24 months (n=118), and 25–42 months (n=100). Longitudinal trajectories were analyzed using general linear models, and predictors of developmental delay were identified through multivariable logistic regression. Results: During the first year, motor scores differed significantly across gestational age groups, with extremely preterm infants showing the lowest values. By the third to fourth years of life, cognitive and language scores diverged markedly, with extremely preterm children exhibiting the steepest decline and additional deficits in motor and adaptive behavior domains. Lower gestational age remained an independent predictor of both cognitive and language delay at early preschool age, while no independent predictors were identified for motor, social-emotional, or adaptive behavior outcomes. Conclusion Neurodevelopmental outcomes in preterm children follow dynamic, domain-specific trajectories influenced by gestational age and developmental timing. Motor delays are most evident in infancy, whereas cognitive and language impairments emerge by early preschool age. Gestational age remains a consistent predictor of later delay, emphasizing the need for longitudinal, gestational age–stratified monitoring and early, targeted intervention.

Purpose: Skeletal muscle, accounting for approximately 40% of the total body mass, plays a critical role in movement, postural support, and metabolic homeostasis. Muscle mass is determined by the balance between protein synthesis and degradation, which is closely regulated by the mitochondrial function. Mitochondrial dysfunctions contribute to muscle loss by promoting oxidative stress and cellular damage. This study examined the effects of masutakeside I, a lignan glycoside derived from Styrax japonicus, on the mitochondrial function and muscle differentiation in C2C12 myoblasts. Methods: C2C12 myoblasts differentiated into myotubes in the presence of masutakeside I (0–10 ng/mL). Myogenic differentiation was assessed by myosin heavy chain (MHC) immunofluorescence, and multinucleated myotubes and relative diameters were quantified.The mitochondrial function was evaluated by measuring the mitochondrial reactive oxygen species (ROS), mitochondrial mass, and mitochondrial membrane potential using MitoSOX, MitoTracker Green, and JC-1 staining, respectively. Gene expression related to muscle differentiation, protein degradation, and the mitochondrial life cycle was analyzed using quantitative reverse transcription polymerase chain reaction. Results: Masutakeside I significantly increased the number of multinucleated (≥ 5 nuclei) MHC-positive myotubes and relative myotube diameter compared to the control. In addition, masutakeside I upregulated the myogenic markers, including phosphoinositide 3-kinase and MHC isoforms (Myh2, Myh4, and Myh7), while significantly downregulating protein degradation–related genes, including mothers against decapentaplegic homolog 2/3, forkhead box protein O1, atrogin-1, and muscle RING finger-1. Masutakeside I modulated the mRNA expression of the mitochondrial function and mitophagy-related markers, suggesting its potential involvement in mitochondrial quality control. Consistent with these effects, the mitochondrial ROS levels decreased, whereas mitochondrial mass and membrane potential increased. Conclusion These findings suggest that masutakeside I modulates the markers related to myogenic differentiation, muscle protein degradation, and mitochondrial function.

Accessory sutures of the skull are uncommon anatomical variants that mimic fractures, especially in infants with incomplete ossification. Here, we report the case of a 6-month-old female infant who died after hospitalization for cardiac arrest. Postmortem computed tomography (PMCT) revealed a transverse linear lucency in the occipital bone accompanied by intracranial hemorrhage, initially raising the suspicion of a skull fracture and non-accidental injury. However, detailed examination at autopsy confirmed that the lucency represented an accessory occipital suture rather than a fracture and was unrelated to the intracranial hemorrhage. This case highlights that accurate interpretation of PMCT and autopsy findings requires knowledge of normal anatomical variants, especially in infant death investigations. Awareness of accessory sutures and the application of advanced computed tomography techniques, such as three-dimensional reconstruction, combined with histological confirmation, if necessary, are crucial to avoid diagnostic errors and unjust suspicion of child abuse.

Objective: To evaluate the accuracy and reasoning capabilities of large multimodal language models compared with those of neuroradiology subspecialty-trained radiologists in neuroradiology case interpretation. Materials and Methods: This experimental study used custom-made 401 radiologic quizzes derived from articles published in RadioGraphics covering neuroradiology and head and neck topics (October 2020 to February 2024). We prompted the GPT-4 Turbo with Vision (GPT-4V), GPT-4 Omni, Gemini Flash, and Claude models to provide the top three differential diagnoses with a rationale and describe examination characteristics such as imaging modality, sequence, use of contrast, image plane, and body part. The temperature was adjusted to 0 and 1 (T1). Two neuroradiologists answered the same questions.The accuracies of the large language models (LLMs) and the neuroradiologists were compared using generalized estimating equations. Three neuroradiologists assessed the rationale provided by the LLMs for their differential diagnoses using four-point scales, separately for specific lesion locations and imaging findings, and evaluated the presence of hallucinations and the overall acceptability of the responses. Results: Top-3 accuracy (i.e., correct answers present among top-3 differential diagnoses) of LLMs ranged from 29.9% (120 of 401) to 49.4% (198 of 401, obtained with GPT-4V in the T1 setting), while radiologists achieved 80.3% (322 of 401) and 68.3% (274 of 401), respectively (P < 0.001). Regarding the rationale for differential diagnoses, GPT-4V (T1) accurately identified both the specific lesion location and imaging findings in 30.7% (123 of 401) and 12.9% (16 of 124) of cases without textual clinical history. Hallucinations occurred in 4.5% (18 of 401), and only 29.4% (118 of 401) of the LLM-generated analyses were deemed acceptable. GPT-4V (T1) demonstrated high accuracy in identifying the imaging modality (97.4% [800 of 821]) and scanned body parts (92.2% [756 of 820]). Conclusion LLMs remarkably underperformed compared with neuroradiologists and showed unsatisfactory reasoning for their differential diagnoses, with performance declining further in cases without textual input of clinical history. These findings highlight the limitations of current multimodal LLMs in neuroradiological interpretation and their reliance on text input.

Biliary tract cancer (BTC) is an uncommon, heterogeneous malignancy with increasing incidence and mortality. Most patients present with advanced disease, which limits curative treatment options and contributes to a poor prognosis. Recent advances in molecular profiling and immuno-oncology have substantially reshaped the therapeutic landscape of BTC by providing deeper insight into its molecular and immunological features. In particular, the incorporation of immune checkpoint inhibitors, such as durvalumab and pembrolizumab, into first-line gemcitabine-cisplatin therapy has demonstrated clinically meaningful survival benefits. Phase III trials, including TOPAZ-1 and KEYNOTE-966, reported significant improvements in overall survival and progression-free survival compared with gemcitabine-cisplatin alone, establishing chemoimmunotherapy as a new standard of care for advanced BTC. The advent of targeted therapies has further expanded treatment options. Agents directed against fibroblast growth factor receptor 2 (FGFR2) fusions, isocitrate dehydrogenase 1 (IDH1) mutations, and human epidermal growth factor receptor 2 (HER2) overexpression have enabled precision-based approaches for patients harboring actionable molecular alterations. These developments highlight the critical role of comprehensive molecular profiling in guiding individualized treatment strategies. Despite these advances, important challenges remain, largely because of the relative rarity of BTC and the inherent limitations of small, heterogeneous study populations. Future research should prioritize large-scale, multicenter, prospective trials to optimize therapeutic sequencing and combination strategies. Furthermore, the routine integration of next-generation sequencing into clinical practice is essential to fully realize the potential of molecularly tailored therapies. This review summarizes the latest evidence on immunotherapy and targeted therapy for BTC and discusses their clinical implications for improving patient outcomes.

Background: Lapsi (Choerospondias axillaris), a plant native to Nepal, has been traditionally used in Asian countries to treat cardiovascular conditions. However, its effects on immune regulatory function remain largely unexplored.This study aimed to in vivo evaluate the immunoregulatory properties of Lapsi fruit extract in mice on immunotoxic responses with analysis on in vitro mechanism for immune suppression, oxidative stress, and inflammatory response.Male Balb/c mice were intragastrically administered various doses of the extract for 21 days. In some mice, immune suppression was induced with cyclophosphamide, and subsequent immune recovery was assessed. In addition, RAW264.7 cells and THP-1-derived macrophages were treated in vitro with lipopolysaccharide and different concentrations of the extract. Results: Administration of extract increased the IgG2a/IgG1 ratio while reducing serum IgE and IgG1 level compared with control mice. Tumor necrosis factor (TNF)-α and interleukin (IL)-17 levels were lower in splenic culture supernatants of mice administered extract. Lapsi extract also effectively reversed cyclophosphamide (CP)-induced immunosuppression by enhancing serum levels of IgA and IgG2a, of interferon-γ and interleukin (IL)-4 secreted by splenic T cells, and of IgG1 and IgG2a secreted by B cells, as well as by increasing immune cell counts. In cell cultures, the extract decreased the levels of inflammation markers, including nitric oxide, reactive oxygen species, prostaglandin E2, and pro-inflammatory cytokines (IL-6, TNF-α, and IL-1β). Mechanistic analysis showed that Lapsi extract modulated the NF-κB p65, MAPK, and inflammasome pathways. Conclusions Lapsi extract may act as both an immunostimulatory and anti-inflammatory agent, indicating its potential as a candidate immunomodulatory activity under polyclonal and CP-suppressed conditions; however, further disease-specific studies, along with isolation and characterization of active phytochemicals, are warranted to evaluate its therapeutic applicability.

Background: Baricitinib is one of the front-runners among targeted agents for the treatment of atopic dermatitis (AD). Although many studies have been conducted on the real-world use of baricitinib, the sample size is often small and data is focused primarily on Caucasians. Objective: The objective of this study was to demonstrate the real-world itch-relieving property of baricitinib in adult AD patients in South Korea. Methods: Electronic medical records of AD patients treated with baricitinib at the National Medical Center in Korea from May 2021 to April 2023 were analyzed retrospectively. Results: Seventy patients completed 16 to 52 weeks of baricitinib treatment, with most patients showing mild-to-moderate baseline lesions and moderate-to-severe baseline itch. At Week 16 of baricitinib treatment, there was a 50% reduction in Itch numerical rating scale from baseline, and 50.7% of patients showed 50% improvement in Eczema Area and Severity Index score.The efficacy of baricitinib was also reflected in the patient reported outcomes, with 55%–58% improvements in Patient-Oriented Eczema Measure, Atopic Dermatitis Control Tool, and Dermatology Life Quality Index scores seen within 2 weeks of treatment. No new safety signals were detected in this study. Conclusion Baricitinib treatment for 52 weeks in Korean patients with itch dominant AD confirmed long term effectiveness and safety.

Purpose: Neoadjuvant treatment (NAT) is now the standard for borderline resectable pancreatic cancer (RPC) and is being considered for RPC. Early recurrence after curative surgery in RPC is often seen as a treatment failure, prompting considerations for NAT. Our goal was to develop an artificial intelligence (AI)-based predictive model utilizing preoperatively available factors to forecast early recurrences of resected RPC. Methods: This study included 469 patients who underwent surgery for RPC between 2011 and 2019. Clinicopathologic and oncologic data were retrospectively reviewed. Preoperative variables, including laboratory data and imaging findings, were collected. Early recurrence was defined as recurrence occurring within a year after surgery. Deep neural networks were then used to select variables by assessing their importance. A new model predicting early recurrence of RPC was subsequently developed. Results: Of the patients evaluated, 199 (42.4%) experienced early recurrence. The predictive model included 14 preoperative variables: CA 19-9, preoperative pancreatitis, serum albumin, platelet count, lymphocyte count, the American Society of Anesthesiologists physical status classification, tumor size, monocyte count, age, body mass index, CRP, hemoglobin, WBC count, and CEA. The area under the curve for the model was 0.786 in the training set and 0.734 in the test set. Conclusion We developed an AI-based model to predict the early recurrence of RPC using preoperative parameters. By identifying patients at risk of early recurrence, optimal individualized treatments such as NAT can be considered. Future prospective studies are crucial to establish clear indications for NAT in RPC.