SeqAFNet: A Beat-Wise Sequential Neural Network for Atrial Fibrillation Classification in Adhesive Patch-Type Electrocardiographs.

Due to their convenience, adhesive patch-type electrocardiographs are commonly used for arrhythmia screening. This study aimed to develop a reliable method that can improve the classification performance of atrial fibrillation (AF) using these devices based on the 2020 European Society of Cardiology (ESC) guidelines for AF diagnosis in clinical practice. We developed a deep learning model that utilizes RR interval frames for precise, beat-wise classification of electrocardiogram (ECG) signals. This model is specifically designed to sequentially classify each R peak on the ECG, considering the rhythms surrounding each beat. It features a two-stage bidirectional Recurrent Neural Network (RNN) with a many-to-many architecture, which is particularly optimized for processing sequential and time-series data. The structure aims to extract local features and capture long-term dependencies associated with AF. After inference, outputs which indicating either AF or non-AF, derived from various temporal sequences are combined through an ensembling technique to enhance prediction accuracy. We collected AF data from a clinical trial that utilized the MEMO Patch, an adhesive patch-type electrocardiograph. When trained on public databases, the model demonstrated high accuracy on the patch dataset (accuracy: 0.986, precision: 0.981, sensitivity: 0.979, specificity: 0.992, and F1 score: 0.98), maintaining consistent performance across public datasets. SeqAFNet was robust for AF classification, making it a potential tool in real-world applications.

SE-ResNet-ViT Hybrid Model for Noise Classification in Adhesive Patch-type Wearable Electrocardiographs.

In purpose of screening arrhythmia, wearable adhesive patch-type electrocardiographs that can measure electrocardiogram continuously for 14 days have been replacing the 24-hour Holter monitor. The reason for that is the patch-type electrocardiograph being smaller and lighter than the Holter monitor, making it more convenient for patients to coexist with in their daily lives. However, this type of electrocardiograph generates a lot of noise signals due to movements during various physical activities and extended wear time.While analyzing electrocardiograms automatically using software, noise signals make the analysis difficult and they may be misclassified as arrhythmia signals. These misclassified signals require a lot of effort and time from clinical technicians to reclassify them as noise. To resolve this problem, this study hypothesized that a deep learning algorithm could be used to screen noise signals. We used 7,467 noise signals and 15,638 ECG signals collected from arrhythmia patients and healthy people. The signals were divided into 10 seconds segments and labeled by cardiologists. We split the data into training and test datasets, ensuring no patient overlap.A hybrid noise classification model, Squeeze and Excitation - Residual Network - Vision Transformer (SE-ResNet-ViT) was developed using the training and validation datasets with an 8:2 ratio. We evaluated the performance of the model using a test dataset. The best F1 score was 0.964. The proposed model can effectively screen for noise signals and potentially reducing the time and effort required by clinical technicians.

Multilayer Coating with Red Ginseng Dietary Fiber Improves Intestinal Adhesion and Proliferation of Probiotics in Human Intestinal Epithelial Models.

To exert their beneficial effects, it is essential for the commensal bacteria of probiotic supplements to be sufficiently protected as they pass through the low pH environment of the stomach, and effectively colonize the intestinal epithelium downstream. Here, we investigated the effect of a multilayer coating containing red ginseng dietary fiber, on the acid tolerance, and the adhesion and proliferation capacities of three Lactobacillus strains (Limosilactobacillus reuteri KGC1901, Lacticaseibacillus casei KGC1201, Limosilactobacillus fermentum KGC1601) isolated from Panax ginseng, using HT-29 cells, mucin-coated plates, and human pluripotent stem cell-derived intestinal epithelial cells as in vitro models of human gut physiology. We observed that the multilayer-coated strains displayed improved survival rates after passage through gastric juice, as well as high adhesion and proliferation capacities within the various gut epithelial systems tested, compared to their uncoated counterparts. Our findings demonstrated that the multilayer coat effectively protected commensal microbiota and led to improved adhesion and colonization of intestinal epithelial cells, and consequently to higher probiotic efficacy.

Upregulation of extracellular proteins in a mouse model of Alzheimer's disease.

Various risk factors of Alzheimer's disease (AD) are known, such as advanced age, possession of certain genetic variants, accumulation of toxic amyloid-ß (Aß) peptides, and unhealthy lifestyle. An estimate of heritability of AD ranges from 0.13 to 0.25, indicating that its phenotypic variation is accounted for mostly by non-genetic factors. DNA methylation is regarded as an epigenetic mechanism that interfaces the genome with non-genetic factors. The Tg2576 mouse model has been insightful in AD research. These transgenic mice express a mutant form of human amyloid precursor protein linked to familial AD. At 9-13 months of age, these mice show elevated levels of Aß peptides and cognitive impairment. The current literature lacks integrative multiomics of the animal model. We applied transcriptomics and DNA methylomics to the same brain samples from ~ 11-month-old transgenic mice. We found that genes involved in extracellular matrix structures and functions are transcriptionally upregulated, and genes involved in extracellular protein secretion and localization are differentially methylated in the transgenic mice. Integrative analysis found enrichment of GO terms related to memory and synaptic functionability. Our results indicate a possibility of transcriptional modulation by DNA methylation underlying AD neuropathology.

Red ginseng dietary fiber promotes probiotic properties of Lactiplantibacillus plantarum and alters bacterial metabolism.

Korean red ginseng has been widely used as an herbal medicine. Red ginseng dietary fiber (RGDF) is a residue of the processed ginseng product but still contains bioactive constituents that can be applied as prebiotics. In this study, we evaluated changes on fermentation profiles and probiotic properties of strains that belong to family Lactobacillaceae with RGDF supplementation. Metabolomic analyses were performed to understand specific mechanisms on the metabolic alteration by RGDF and to discover novel bioactive compounds secreted by the RGDF-supplemented probiotic strain. RGDF supplementation promoted short-chain fatty acid (SCFA) production, carbon source utilization, and gut epithelial adhesion of Lactiplantibacillus plantarum and inhibited attachment of enteropathogens. Intracellular and extracellular metabolome analyses revealed that RGDF induced metabolic alteration, especially associated with central carbon metabolism, and produced RGDF-specific metabolites secreted by L. plantarum, respectively. Specifically, L. plantarum showed decreases in intracellular metabolites of oleic acid, nicotinic acid, uracil, and glyceric acid, while extracellular secretion of several metabolites including oleic acid, 2-hydroxybutanoic acid, hexanol, and butyl acetate increased. RGDF supplementation had distinct effects on L. plantarum metabolism compared with fructooligosaccharide supplementation. These findings present potential applications of RGDF as prebiotics and bioactive compounds produced by RGDF-supplemented L. plantarum as novel postbiotic metabolites for human disease prevention and treatment.

Probiotic Characteristics and Safety Assessment of Lacticaseibacillus casei KGC1201 Isolated from Panax ginseng.

Panax ginseng is one of the most important herbal medicinal plants consumed as health functional food and can be fermented to achieve better efficacy. Lacticaseibacillus, one of the representative genera among lactic acid bacteria (LAB), has also been used as a probiotic material for health functional foods due to its beneficial effects on the human body. To achieve a synergistic effect by using these excellent dietary supplement ingredients together, a novel LAB strain was isolated from the root of 6-year-old ginseng. Through similarity analysis of 16S rRNAs and whole-genome sequences, the strain was confirmed as belonging to the genus Lacticaseibacillus and was named L. casei KGC1201. KGC1201 not only met all safety standards as food, but also showed excellent probiotic properties such as acid resistance, bile salt resistance, and intestinal adhesion. In particular, KGC1201 exhibited superior acid resistance through morphological observation identifying that the cell surface damage of KGC1201 was less than that of the L. casei type strain KCTC3109. Gene expression studies were conducted to elucidate the molecular mechanisms of KGC1201's acid resistance, and the expression of the glycosyltransferase gene was found to be significantly elevated under acidic conditions. Exopolysaccharides (EPSs) biosynthesized by glycosyltransferase were also increased in KGC1201 compared to KCTC3109, which may contribute to better protection of KGC1201 cells from strong acidity. Therefore, KGC1201, with its increased acid resistance through molecular mechanisms and excellent probiotic properties, can be used in health functional foods to provide greater benefit to overall human health and well-being.

Growth promotion effect of red ginseng dietary fiber to probiotics and transcriptome analysis of Lactiplantibacillus plantarum.

Background: Red ginseng marc, the residue of red ginseng left after water extraction, is rich in dietary fiber. Dietary fiber derived from fruits or vegetables can promote the proliferation of probiotics, and it is a key technology in the food industry to increase the productivity of probiotics by adding growth-enhancing substances such as dietary fiber. In this study, the effect of red ginseng dietary fiber (RGDF) on the growth of probiotic bacterial strains was investigated at the phenotypic and genetic levels. Methods: We performed transcriptome profiling of Lactiplantibacillus plantarum IDCC3501 in two phases of culture (logarithmic (L)-phase and stationary (S)-phase) in two culture conditions (with or without RGDF) using RNA-seq. Differentially expressed genes (DEGs) were identified and classified according to Gene Ontology terms. Results: The growth of L.plantarum IDCC3501 was enhanced in medium supplemented with RGDF up to 2%. As a result of DEG analysis, 29 genes were upregulated and 30 were downregulated in the RGDF-treated group in the L-phase. In the S-phase, 57 genes were upregulated and 126 were downregulated in the RGDF-treated group. Among the upregulated genes, 5 were upregulated only in the L-phase, 10 were upregulated only in the S-phase, and 3 were upregulated in both the L- and S-phases. Conclusions: Transcriptome analysis could be a valuable tool for elucidating the molecular mechanisms by which RGDF promotes the proliferation of L.plantarum IDCC3501. This growth-promoting effect of RGDF is important, since RGDF could be used as a prebiotic source without additional chemical or enzymatic processing.

Lightweight Convolutional Neural Network for Real-Time Arrhythmia Classification on Low-Power Wearable Electrocardiograph.

In this study, a lightweight CNN-based electrocardiogram (ECG) classification model is implemented to operate it on a wearable device for real-time arrhythmia detection by efficiently reducing the number of parameters of the model. Ten second-windowed ECGs from three different public ECG databases were used to learn and classify them into four classes: normal sinus rhythm, atrial fibrillation, atrial premature contraction, and ventricular premature contraction. The model implemented in the workstation environment was converted using the TensorFlow Lite framework and then imported into an ARM Cortex-M4 architecture-based nRF52840 microprocessor. The proposed model shows high performance (97.7% accuracy and 97.4% F1 score) with reasonable execution time: 298ms and current consumption: 3.55mA at optimized for speed and execution time: 480ms and current consumption: 3.82mA at optimized for size, respectively.

Anti-Inflammatory Effects of Limosilactobacillus fermentum KGC1601 Isolated from Panax ginseng and Its Probiotic Characteristics.

We investigated the potential probiotic properties of Limosilactobacillus fermentum KGC1601 isolated from Panax ginseng. Ginseng cultivated in an experimental field of the Korea Ginseng Research Institute was fermented, followed by single colony selection from MRS agar. We performed 16s-rRNA sequencing and whole-genome analysis to identify L. fermentum and evaluate the biosafety parameters of this strain, respectively. We confirmed this strain was susceptible to six antibiotics, as proposed by the European Food Safety Authority, did not produce biogenic amines, and did not exhibit any hemolytic activity. Acid resistance and bile salt tolerance, which are essential properties of a probiotic agent, were investigated. Notably, distinguishing properties of this strain were that it exhibited excellent bile salt tolerance and anti-inflammatory effects. The excellent bile salt tolerance was confirmed by scanning electron microscopy. Through qRT-PCR and ELISA studies, it was revealed that L. fermentum KGC1601 pre-treatment up-regulates anti-inflammatory cytokines and down-regulates pro-inflammatory cytokines in RAW 264.7 cells. Consequently, we suggested that L. fermentum KGC1601 can be safely used as a potential anti-inflammatory functional probiotic agent.

Compressed Deep Learning to Classify Arrhythmia in an Embedded Wearable Device.

The importance of an embedded wearable device with automatic detection and alarming cannot be overstated, given that 15-30% of patients with atrial fibrillation are reported to be asymptomatic. These asymptomatic patients do not seek medical care, hence traditional diagnostic tools including Holter are not effective for the further prevention of associated stroke or heart failure. This is likely to be more so in the era of COVID-19, in which patients become more reluctant on hospitalization and checkups. However, little literature is available on this important topic. For this reason, this study developed efficient deep learning with model compression, which is designed to use ECG data and classify arrhythmia in an embedded wearable device. ECG-signal data came from Korea University Anam Hospital in Seoul, Korea, with 28,308 unique patients (15,412 normal and 12,896 arrhythmia). Resnets and Mobilenets with model compression (TensorFlow Lite) were applied and compared for the diagnosis of arrhythmia in an embedded wearable device. The weight size of the compressed model registered a remarkable decrease from 743 MB to 76 KB (1/10000), whereas its performance was almost the same as its original counterpart. Resnet and Mobilenet were similar in terms of accuracy, i.e., Resnet-50 Hz (97.3) vs. Mo-bilenet-50 Hz (97.2), Resnet-100 Hz (98.2) vs. Mobilenet-100 Hz (97.9). Here, 50 Hz/100 Hz denotes the down-sampling rate. However, Resnets took more flash memory and longer inference time than did Mobilenets. In conclusion, Mobilenet would be a more efficient model than Resnet to classify arrhythmia in an embedded wearable device.

Frailty and Biological Age.

A reliable model of biological age is instrumental in the field of geriatrics and gerontology. This model should account for the heterogeneity and plasticity of aging and also accurately predict aging-related adverse outcomes. Epigenetic age models are based on DNA methylation levels at selected genomic sites and can be significant predictors of mortality and healthy/unhealthy aging. However, the biological function of DNA methylation at selected sites is yet to be determined. Frailty is a syndrome resulting from decreased physiological reserves and resilience. The frailty index is a probability-based extension of the concept of frailty. Defined as the proportion of health deficits, the frailty index quantifies the progression of unhealthy aging. The frailty index is currently the best predictor of mortality. It is associated with various biological factors and provides insight into the biological processes of aging. Investigation of the multi-omics factors associated with the frailty index will provide further insight.

Decision making framework for the proactive policy conflict management: The case of new airport projects in South Korea.

We propose a decision-making framework on infrastructure policy conflict management based on a scientific approach. We developed a decision-making framework that consists of the systematic conflict structure diagnosis, decision-making accordingly, and feedback to be used consistently in the policy life cycle and applied it to new airport projects in South Korea. We suggested a model structure of conflict factors leading to the generation of conflict situations and damages in the process and developed the conflict level diagnosis table and the conflict level matrix formed of the possibility of conflict generation and the severity based on the table. We then implemented a decision-making framework that includes decision-making based on it. The case analysis results confirmed the need for a structural diagnosis of conflict and decision-making based on the framework. The developed framework is expected to have scalability for science progress on infrastructure policy conflict management.

Feature Selection Algorithms Enhance the Accuracy of Frailty Indexes as Measures of Biological Age.

Biological age captures some of the variance in life expectancy for which chronological age is not accountable, and it quantifies the heterogeneity in the presentation of the aging phenotype in various individuals. Among the many quantitative measures of biological age, the mathematically uncomplicated frailty/deficit index is simply the proportion of the total health deficits in various health items surveyed in different individuals. We used 3 different statistical methods that are popular in machine learning to select 17-28 health items that together are highly predictive of survival/mortality, from independent study cohorts. From the selected sets, we calculated frailty indexes and Klemera-Doubal's biological age estimates, and then compared their mortality prediction performance using Cox proportional hazards regression models. Our results indicate that the frailty index outperforms age and Klemera-Doubal's biological age estimates, especially among the oldest old who are most prone to biological aging-caused mortality. We also showed that a DNA methylation index, which was generated by applying the frailty/deficit index calculation method to 38 CpG sites that were selected using the same machine learning algorithms, can predict mortality even better than the best performing frailty index constructed from health, function, and blood chemistry.

The impact of overactive bladder on health-related quality of life in Korea: based on the results of a Korean Community Health Survey.

PURPOSE: This study aimed to assess the impact of overactive bladder on health-related quality of life (HRQoL) in a community-based sample of Korean population. METHODS: The data of adults aged 19 and over that who participated in the 2012 Korean Community Health Survey were analyzed. Overactive bladder severity was classified as normal, mild, moderate, or severe using the Overactive Bladder Symptom scores, and HRQoL was evaluated using EQ-5D-3L. Relations between HRQoL and the severities and symptoms of OAB were investigated. Sampling weighted adjusted multiple regression analysis was performed to determine the effect of OAB symptom severity on HRQoL. RESULTS: Of the 226,867 study subjects, 12,303 (5.4%) had OAB, and 552 (0.2%) had an OABSS of ≥ 12, indicating severe OAB. The problem -reporting rate significantly increased in all EQ-5D-3L dimensions as OAB severity increased. After adjusting for other variables, OAB severity had a significant effect on EQ-5D-3L index. Urge incontinence had greatest impact on quality of life. CONCLUSIONS: As the severity of OAB increased from mild to severe, quality of life decreased significantly. OAB was found to negatively affect HRQoL.

Strategic encoding and retrieval processes in verbal recall among middle-aged and older adults.

The authors used an analysis of individual differences to examine the role of executive control in strategic encoding and retrieval in verbal recall. Participants enrolled in the Louisiana Healthy Aging Study completed measures of working memory (WM), cognitive status, vocabulary, and free recall of words. Indices of clustering in free recall were calculated to permit inferences on strategic encoding and retrieval processes. We hypothesized that WM would be more strongly associated with strategic encoding and retrieval metrics than vocabulary based on the assumption that successful remembering requires executive control in WM. Regression analyses, together with a variance portioning procedure, confirmed that WM had comparable levels of unique and shared variance with the strategic encoding and retrieval metrics, and both exceeded vocabulary. Theoretical and clinical implications of these data are considered, with the suggestion of future research in lifespan samples as opposed to exclusively young adult or older adult samples.

Generation and Characterization of Monoclonal Antibodies to the Ogawa Lipopolysaccharide of Vibrio cholerae O1 from Phage-Displayed Human Synthetic Fab Library.

Vibrio cholerae, cause of the life-threatening diarrheal disease cholera, can be divided into different serogroups based on the structure of its lipopolysaccharide (LPS), which consists of lipid-A, corepolysaccharide and O-antigen polysaccharide (O-PS). The O1 serogroup, the predominant cause of cholera, includes two major serotypes, Inaba and Ogawa. These serotypes are differentiated by the presence of a single 2-O-methyl group in the upstream terminal perosamine of the Ogawa O-PS, which is absent in the Inaba O-PS. To ensure the consistent quality and efficacy of the current cholera vaccines, accurate measurement and characterization of each of these two serotypes is highly important. In this study, we efficiently screened a phage-displayed human synthetic Fab library by bio-panning against Ogawa LPS and finally selected three unique mAbs (D9, E11, and F7) that specifically react with Ogawa LPS. The mAbs bound to Vibrio cholerae vaccine in a dose-dependent fashion. Sequence and structure analyses of antibody paratopes suggest that IgG D9 might have the same fine specificity as that of the murine mAbs, which were shown to bind to the upstream terminal perosamine of Ogawa O-PS, whereas IgGs F7 and E11 showed some different characteristics in the paratopes. To our knowledge, this study is the first to demonstrate the generation of Ogawa-specific mAbs using phage display technology. The mAbs will be useful for identification and quantification of Ogawa LPS in multivalent V. cholerae vaccines.

The frequency of impairments in everyday activities due to the overuse of the internet, gaming, or smartphone, and its relationship to health-related quality of life in Korea.

BACKGROUND: This study aimed to investigate the relationships between the frequency of impairments in daily activities due to the overuse of the Internet, gaming, or smartphones (IGS) and sociodemographic characteristics, social relationships (including family) & activities, psychosocial characteristics, health status, and health-related quality of life (HRQoL) of Korean adults. METHODS: Secondary data from the 2017 Community Health Survey, a large-scale sample survey conducted yearly in South Korea, were analyzed for 190,066 adults over 19 years of age. Three categories were created for impairment groups due to IGS overuse: No Impairment, Mild Impairment, and Moderate-to-Severe groups. And between-group differences were examined using a one-way ANOVA for health status measured with the EQ-5D-3 L and chi-square tests for all categorical dependent variables, which included sociodemographic characteristics, social relationships & activities, and psychosocial factors. The association between frequencies of daily activity impairments due to IGS overuse and the dependent variables were examined using a multivariate logistic regression analysis and a linear regression model. RESULTS: Approximately 21,345 (11.23%) of the 190,066 participants reported experiencing impairments in daily activities due to IGS overuse at least once in the previous year and the impairments were more severe in males than females. Participants experiencing impairments in daily activities contacted their friends a significantly higher number of times (4 times or more per month) and engaged in leisure activities more frequently (more than once per month) than those without impairments. There was also a significant positive relationship between IGS overuse and stress, depression, suicidal ideation, and suicide attempts. Among participants aged 19-64, impairments in daily activities due to IGS overuse were associated with a lower HRQoL. Conversely, for those aged 65 and over, mild and moderate-to-severe impairments due to IGS overuse were associated with a significantly higher HRQoL. CONCLUSIONS: Increased impairments in daily activities due to IGS overuse may negatively affect mental health. However, among older adults, the frequency of such impairments was positively associated with HRQoL. This finding could be considered to apply interventions with Internet usage or ICT devices for older adults to enhance their quality of life.

Association Between Lower Urinary Tract Symptoms and Falls in Adults Males: Based on the Korean Community Health Survey.

This study aimed to investigate the correlation between lower urinary tract symptoms (LUTSs) and falls considering places where falls can occur in adult males. We analyzed 101 862 males in the 2011 Korean Community Health Survey. LUTSs were assessed using the International Prostate Symptom Score system. The rate of total and indoor falls significantly increased with the LUTS severity, respectively. After adjusting for age and other confounding variables, the odds ratios (ORs) for total falls were significantly high for the mild (OR = 1.63, 95% confidence interval [CI] = 1.54-1.71), moderate (OR = 2.35, 95% CI = 2.16-2.56), and severe groups (OR = 2.83, 95% CI = 2.49-3.22), relative to the normal group. Indoor fall experience was the same for the mild (OR = 1.56, 95% CI = 1.36-1.79), moderate (OR = 2.37, 95% CI = 1.97-2.85), and severe groups (OR = 3.77, 95% CI = 3.00-4.72). Nocturia, hesitancy, and urgency were significantly associated with indoor falls. The association between falls and the degree of LUTS was observed in both the young and the elderly. Therefore, further studies are needed to determine the effects of treatment of LUTS on the risk of falls and the effectiveness of the fall prevention program.

Health-related quality of life in adult males with lower urinary tract symptoms.

PURPOSE: To assess the status and impact of lower urinary tract symptoms (LUTS) on health-related quality of life (HRQoL) in a community-based sample of Korean adult males. METHODS: We analyzed the data of 101,606 adult males aged ≥ 19 years of age obtained during the 2011 Korean Community Health Survey. Subject data were assessed for LUTS and HRQoL using international prostate symptom scores, and EuroQol-five-dimensions three-level version (EQ-5D-3L) and EuroQol-visual analogue scale (EQ-VAS) scores. RESULTS: Of the 101,606 subjects, 53,323 (52.5%) reported having at least one LUTS and 3116 (3.1%) had an IPSS of ≥ 20, indicating severe LUTS. In those aged 19-39 years, 28.7% (8343/29,072) reported they had mild to severe LUTS. The prevalence of LUTS was high among those aged 40-59 years (47.7%), 60-79 years (80.5%), and ≥ 80 years (91.2%). In addition, EQ-5D-3L and EQ-VAS scores decreased as LUTS severity and frequency increased. CONCLUSIONS: Adult men of all ages with mild to severe LUTS have poorer health statuses and quality of life. Even among young males, LUTS severity and was found to negatively affect HRQoL.