Young-Soo Kim’s research while affiliated with Gyeongsang National University Hospital and other places

Background Frailty is a state of vulnerability to poor homeostatic resolution of after a stressful event. The prevalence of frailty in patients with chronic kidney disease (CKD) is more common than in the general population. Frailty is associated with a poor clinical prognosis, malnutrition, and cognitive impairment; however, studies on these factors in patients with CKD are lacking. Therefore, we aimed to evaluate the relationship between CKD and frailty, nutritional status, and cognitive impairment and their influence on clinical outcomes. Methods We prospectively enrolled participants from June 2019 to December 2020 and divided them into three CKD groups according to kidney function (non-CKD, CKD stage 3–4, and CKD stage 5D). Clinical outcomes were defined as the composite outcomes of all-cause death, hospitalization, and cardiovascular outcomes, including nonfatal myocardial infarction, revascularization, or stroke. To calculate the relative risk of frailty, cognitive impairment, nutritional status, and clinical outcome, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression analysis. Result A total of 88 patients were included, of whom 30.7% had frailty and 17.0% had cognitive impairment. In the CKD stage 5D group, the prevalence of frailty (56.7%, n = 17) was significantly higher, and the nutritional quotient score was lower in the other groups. The Korean-Montreal Cognitive Assessment score was significantly lower in the CKD stage 5D group; however, cognitive impairment did not differ among the three groups. Frailty was significantly associated with cognitive impairment and CKD stage 5D group. Cognitive impairment was significantly associated with older age and higher BMI. Well-nourished status was significantly associated with BMI and CKD stage 5D group. Patients in the CKD 5D group were significantly more likely to have adverse clinical outcomes. Conclusions The prevalence of frailty increased significantly as the CKD stage progressed. Particularly, CKD stage 5D group correlated with frailty and nutritional status, leading to poor clinical outcomes.

Introduction Previous studies suggested that obstructive sleep apnea (OSA) can affect the autonomic nervous system. Patients with OSA appear to have a higher sympathetic component, a lower parasympathetic component, and greater autonomic nervous system (ANS) imbalance. We compared heart rate variability (HRV) with existing studies and confirmed classification accuracy through deep learning analysis (DLA), using electrocardiogram (ECG) data extracted from polysomnography (PSG). Methods We retrospectively surveyed people who underwent PSG at our hospital from January 2015 to March 2023. The diagnosis of OSA was classified into normal, mild, moderate, and severe based on AHI, and whether arrhythmia was identified during the test was also investigated. HRV analysis performed by frequency domain analysis of the tachogram. For DLA, the tachogram was converted to a Mel-spectrogram and a Convolutional Neuronal Network (CNN) was used to confirm the confusion matrix. Results Of a total of 1,806 PSG, 1,554 cases were selected, excluding 252 cases of arrhythmia. OSA confirmed by PSG was normal in 282 patients, mild in 334, moderate in 293, and severe in 645. When comparing the results of HRV divided into AHI below 15 and above, VLF power (ms2/Hz) was 940.78 ± 763.72 vs 1132.75 ± 1104.50 (p < 0.001), LF power (ms2/Hz) was 719.26 ± 734.71 vs. 724.46 ± 945.26 (p = 0.908), HF power (ms2/Hz) was 763.61 ± 1058.92 vs 595.53 ± 1386.75 (p = 0.011), and LF/HF ratio was 1.27 ± 0.74 vs 1.63 ± 1.02 (p < 0.001). As a result of DLA, the ROC AUC Score was confirmed to be 0.7077 and the F1 Score was 0.67. Conclusion As a result of HRV using ECG from PSG, OSA patients were found to have low HF power and high LF/HF ratio, similar to previous studies. Additionally, if tachogram's DLA accuracy can be improved through preprocessing and deep learning model improvements, it is expected that it can be used as a screening tool in various place. Support (if any) This work was partly supported by Institute of Information & Communications Technology Planning & Evaluation grant funded by the Korea government No.RS_2023_00227552, Development of artificial intelligence video background removal SaaS service using domestic semiconductor 64 TOPS.

Maesa Forssk. (Myrsinaceae) has approximately 200 species distributed in the tropics from southern Africa to East Asia. Among them, Maesa japonica (Thunb.) Moritzi ex Zoll. is distributed throughout China, Japan, Taiwan, Vietnam, and Korea. In Korea, this species is found only on Jejudo Island. In this study, we conducted whole-genome sequenc-ing of M. japonica chloroplast (cp). The complete cp genome sequence of M. japonica was found to be 157,189 bp in length, consisting of large (87,780 bp) and small (18,143 bp) single copy regions (LSC and SSC, respectively) and a pair of identical inverted repeats (IRs) (25,633 bp). The overall GC content of the cp genome was 38%, while those of the LSC, SSC, and each IR were 35.2%, 30.9%, and 43.1%, respectively. Furthermore, 130 genes consisting of 85 protein-coding genes, 37 transfer RNA genes and eight ribosomal RNA genes were identified in the cp genome. A phylogenetic analysis of 12 taxa inferred from the cp genome revealed a close relationship between M. salicifolia and M. japonica. The complete cp genome sequence of M. japonica provides valuable information for future evolutionary and phylogenetic studies of Maesa.

Chloroplast genomes are valuable for inferring evolutionary relationships. We report the complete chloroplast genomes of 36 Corydalis spp. and one Fumaria species. We compared these genomes with 22 other taxa and investigated the genome structure, gene content, and evolutionary dynamics of the chloroplast genomes of 58 species, explored the structure, size, repeat sequences, and divergent hotspots of these genomes, conducted phylogenetic analysis, and identified nine types of chloroplast genome structures among Corydalis spp. The ndh gene family suffered inversion and rearrangement or was lost or pseudogenized throughout the chloroplast genomes of various Corydalis species. Analysis of five protein-coding genes revealed simple sequence repeats and repetitive sequences that can be potential molecular markers for species identification. Phylogenetic analysis revealed three subgenera in Corydalis. Subgenera Cremnocapnos and Sophorocapnos represented the Type 2 and 3 genome structures, respectively. Subgenus Corydalis included all types except type 3, suggesting that chloroplast genome structural diversity increased during its differentiation. Despite the explosive diversification of this subgenus, most endemic species collected from the Korean Peninsula shared only one type of genome structure, suggesting recent divergence. These findings will greatly improve our understanding of the chloroplast genome of Corydalis and may help develop effective molecular markers.