Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Purpose: This study aimed to investigate the effects of postnatal systemic corticosteroids on neurodevelopment in very low birth weight (VLBW) preterm infants. Methods: This was a population-based study of the Korean Neonatal Network of VLBW infant born at 23+0 and 31+6 weeks of gestation between 2013 and 2020. VLBW preterm infants assessed using the Bayley Scales of Infant and Toddler Development, third edition (BSID-III) at 18–24 months of corrected age and 3 years of age were enrolled. The primary outcomes were BSID-III scores and neurodevelopmental delays, with scores of <85. Socioeconomic status and clinical variables were adjusted for using multivariate regression analyses. Results: In total, 517 infants were enrolled in this study. Among the 216 (41.8%) infants who received postnatal systemic corticosteroids, the rate of cognitive delay was significantly higher at 18–24 months of corrected age than at 3 years of age. The rates of language and motor delays were significantly higher both at 18–24 months of corrected age and at 3 years of age. When multivariate logistic regression was performed, postnatal systemic corticosteroid use was significantly associated with cognitive delay at 18–24 months of corrected age, but not at 3 years of age. There was no significant association between postnatal systemic corticosteroid use and language or motor delay at 18-24 months of corrected age or at 3 years of age after multivariate logistic regression. Conclusion Postnatal systemic corticosteroid use in VLBW preterm infants increased the risk of cognitive delay at 18–24 months of corrected age, but not at 3 years.

Objective: This study hypothesized that physical status, temperament and characteristics, and neurocognitive functions of basketball players could predict the result of Korean Basketball League (KBL) draft selection. Methods: We recruited the number of 89 college elite basketball players (KBL selection, n=44; non-KBL selection, n=45), and the number of 82 age-matched healthy comparison subjects who major in sports education in college. All participants were assessed with the Temperament and Character Inventory, Sports Anxiety Scales, Beck Depression Inventory, Perceived Stress Scale-10, Trail Making Test, and Computerized Neuro-cognitive Test for Emotional Perception and Mental Rotation. Results: Current results showed that physical status, temperament and characteristics, and neurocognitive functions of college basketball players could predict the KBL draft selection. Among temperament and characteristics, novelty seeking and reward dependence were associated with KBL draft selection. The basketball performances including average scores and average rebound were associated with Emotional Perception and Mental Rotation. Conclusion In order to be a good basketball player for a long time, it was confirmed that temperamental factors and neurocognitive factors were very closely related. Furthermore, it is also judged that these results can be used as basic data to predict potential professional basketball players.

Purpose: The associated factors for hypertensive retinopathy (HTR) are rarely investigated. This study aimed to identify the associated factors for HTR using a systematic review. Methods: The review included cross-sectional, case-controlled, and cohort studies on HTR risk factors published in Korean and English with full texts available from PubMed, Embase, CINAHL, Web of Science, and Korean databases. Methodological quality was assessed using the Joanna Briggs Institute (JBI) checklist. Results: Eleven studies were finally selected, and three studies including patients with hypertension without diabetes mellitus, older age, male sex, alcohol consumption, the duration of hypertension, hyperglycemia, dyslipidemia, microalbuminuria, high creatinine levels, chronic kidney disease, and cardiovascular changes were identified as factors associated with HTR. Conversely, in the remaining eight studies, younger age, non-smoking status, and renal function indicators (albuminuria, high creatinine levels, chronic kidney disease, and uric acid) were identified as associated factors. Conclusions Regardless of the inclusion of patients with diabetes mellitus, impaired kidney functions were determined as significant factors associated with retinopathy in patients with HTR. However, considering a limited number of evidence and lack of evidence to confirm causality, we recommend further research on renal function and HTR.

Microglial activation during aging is associated with neuroinflammation and cognitive impairment. Galectin-3 plays a crucial role in microglial activation and phagocytosis. However, the role of galectin-3 in the aged brain is not completely understood. In the present study, we investigated aging-related mechanisms and microglial galectin-3 expression in the mouse hippocampus using female 6-, 12-, and 24-month-old C57BL/6 mice. Western blot analysis revealed neurodegeneration, blood-brain barrier leakage, and increased levels of neuroinflammation-related proteins in 24-month-old mice compared to 6- and 12-month-old mice. Immunohistochemistry revealed an increase in activated microglia in the hippocampus of 24-month-old mice compared to 6- and 12-month-old mice. Furthermore, we found more galectin-3 and triggering receptor expressed on myeloid cells-2-positive microglia in 24-month-old mice compared to 6- and 12-month-old mice. Using primary mouse microglial cells, galectin -3 was also increased by lipopolysaccharide treatment. These findings suggest that galectin-3 may play an important role in microglial activation and neuroinflammation during brain aging.

Purpose: This study elucidates the mechanism of the physiological effect of cannabidiol (CBD) by assessing its impact on lipopolysaccharide (LPS)-induced inflammation in RWPE-1 cells and prostatitis-induced by 17β-estradiol and dihydrotestosterone in a rat model, focusing on its therapeutic potential for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Materials and Methods: RWPE-1 cells were stratified in vitro into three groups: (1) controls, (2) cells with LPS-induced inflammation, and (3) cells with LPS-induced inflammation and treated with CBD. Enzyme-linked immunosorbent assays and western blots were performed on cellular components and supernatants after administration of CBD. Five groups of six Sprague–Dawley male rats were assigned: (1) control, (2) CP/CPPS, (3) CP/CPPS and treated with 50 mg/kg CBD, (4) CP/CPPS and treated with 100 mg/kg CBD, and (5) CP/CPPS and treated with 150 mg/kg CBD. Prostatitis was induced through administration of 17β-estradiol and dihydrotestosterone. After four weeks of CBD treatment, a pain index was evaluated, and prostate tissue was collected for subsequent histologic examination and western blot analysis. Results: CBD demonstrated efficacy in vivo for CP/CPPS and in vitro for inflammation. It inhibited the toll-like receptor 4 (TLR4)uclear factor-kappa B (NF-κB) pathway by activating the CB2 receptor, reducing expression of interleukin-6, tumor necrosis factor-alpha, and cyclooxygenase-2 (COX2) (p<0.01). CBD exhibited analgesic effects by activating and desensitizing the TRPV1 receptor. Conclusions CBD inhibits the TLR4/NF-κB pathway by activating the CB2 receptor, desensitizes the TRPV1 receptor, and decreases the release of COX2. This results in relief of inflammation and pain in patients with CP/CPPS, indicating CBD as a potential treatment for CP/CPPS.

Latent tuberculosis infection (LTBI) is characterized by immune responses to Mycobacterium tuberculosis antigens without clinical symptoms or evidence of active tuberculosis. Effective LTBI management is crucial for tuberculosis elimination, requiring accurate diagnosis and treatment. In South Korea, LTBI guidelines have been updated periodically, the latest being in 2024. This review discusses the recent changes in the Korean guideline for the diagnosis and treatment of LTBI in adults.

Background: This study aimed to determine whether a shorter high-dose rifampicin regimen is non-inferior to the standard 6-month tuberculosis regimen. Methods: This multicenter, randomized, open-label, non-inferiority trial enrolled participants with respiratory specimen positivity by Xpert MTB/RIF assay or Mycobacterium tuberculosis culture without rifampicin-resistance. Participants were randomized at 1:1 to the investigational or control group. The investigational group received high-dose rifampicin (30 mg/kg/day), isoniazid, and pyrazinamide until culture conversion, followed by high-dose rifampicin and isoniazid for 12 weeks. The control group received the standard 6-month regimen. The primary outcome was the rate of unfavorable outcomes at 18 months post-randomization. The non-inferiority margin was set at <6% difference in unfavorable outcomes rates. The study is registered with ClinicalTrials.gov (NCT04485156) Results: Between 4 November 2020 and 3 January 2022, 76 participants were enrolled. Of these, 58 were included in the modified intention-to-treat analysis. Unfavorable outcomes occurred in 10 (31.3%) of 32 in the control group and 10 (38.5%) of 26 in the investigational group. The difference was 7.2% (95% confidence interval, ∞ to 31.9%), failing to prove non-inferiority. Serious adverse events and grade 3 or higher adverse events did not differ between the groups. Conclusion The shorter high-dose rifampicin regimen failed to demonstrate non-inferiority but had an acceptable safety profile.

Background: Kelch-like ECH-associated protein 1 (KEAP1)–nuclear factor erythroid- 2-related factor 2 (NRF2) pathway is a major regulator protecting cells from oxidative and metabolic stress. Studies have revealed that this pathway is involved in mediating resistance to cytotoxic chemotherapy and immunotherapy; however, its implications in oncogene-addicted tumors are largely unknown. This study aimed to elucidate whether this pathway could be a potential therapeutic target for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Methods: We measured the baseline expression of NRF2 using EGFR-mutant parental cells and acquired gefitinib resistant cells. We investigated whether NRF2 inhibition affected cell death in vitro and tumor growth in vivo using a xenograft mouse model, and compared the transcriptional changes before and after NRF2 inhibition. Results: Baseline NRF2 expression was enhanced in PC9 and PC9 with gefitinib resistance (PC9/GR) cells than in other cell lines, with a more prominent expression in PC9/ GR. The NRF2 inhibitor induced NRF2 downregulation and cell death in a dose-dependent manner. Cotreatment with an NRF2 inhibitor enhanced osimertinib-induced cell death in vitro, and potentiated tumor growth inhibition in a PC9/GR xenograft model. Finally, RNA sequencing revealed that NRF2 inhibition resulted in the altered expression of multiple genes involved in various signaling pathways. Conclusion We identified that NRF2 inhibition enhanced cell death and inhibited tumor growth in tyrosine kinase inhibitor (TKI)-resistant lung cancer with EGFR-mutation. Thus, NRF2 modulation may be a novel therapeutic strategy to overcome the resistance to EGFR-TKIs.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)