• Journal of Food Hygiene and Safety
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• v.38 no.5
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• pp.279-286
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• 2023

Rapid and accurate detection of pathogenic bacteria is crucial for various applications, including public health and food safety. However, existing bacteria detection techniques have several drawbacks as they are inconvenient and require time-consuming procedures and complex machinery. Recently, the precision and versatility of CRISPR/Cas system has been leveraged to design biosensors that offer a more efficient and accurate approach to bacterial detection compared to the existing techniques. Significant research has been focused on developing biosensors based on the CRISPR/Cas system which has shown promise in efficiently detecting pathogenic bacteria or virus. In this review, we present a biosensor based on the CRISPR/Cas system that has been specifically developed to overcome these limitations and detect different pathogenic bacteria effectively including Vibrio parahaemolyticus, Salmonella, E. coli O157:H7, and Listeria monocytogenes. This biosensor takes advantage of the CRISPR/Cas system's precision and versatility for more efficiently accurately detecting bacteria compared to the previous techniques. The biosensor has potential to enhance public health and ensure food safety as the biosensor's design can revolutionize method of detecting pathogenic bacteria. It provides a rapid and reliable method for identifying harmful bacteria and it can aid in early intervention and preventive measures, mitigating the risk of bacterial outbreaks and their associated consequences. Further research and development in this area will lead to development of even more advanced biosensors capable of detecting an even broader range of bacterial pathogens, thereby significantly benefiting various industries and helping in safeguard human health

• Journal of Chest Surgery
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• v.57 no.2
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• pp.120-125
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• 2024

Background: This study aimed to assess the outcomes of patients with complex rib fractures undergoing operative or nonoperative management at our major trauma center. Methods: A retrospective review of all patients who were considered for surgical stabilization of rib fractures (SSRF) at a single major trauma center from May 2016 to September 2022 was performed. Results: In total, 352 patients with complex rib fractures were identified. Thirty-seven patients (11%) fulfilled the criteria for surgical management and underwent SSRF. The SSRF group had a significantly higher proportion of patients with flail chest (32 [86%] vs. 94 [27%], p<0.001) or Injury Severity Score (ISS) >15 (37 [100%] vs. 129 [41%], p<0.001). No significant differences were seen between groups for 1-year mortality. Patients who underwent SSRF within 72 hours were 6 times less likely to develop pneumonia than those in whom SSRF was delayed for over 72 hours (2 [18%] vs. 15 [58%]; odds ratio, 0.163; 95% confidence interval, 0.029-0.909; p=0.036). Prompt SSRF showed non-significant associations with shorter intensive care unit length of stay (6 days vs. 10 days, p=0.140) and duration of mechanical ventilation (5 days vs. 8 days, p=0.177). SSRF was associated with a longer hospital length of stay compared to nonoperative patients with flail chest and/or ISS >15 (19 days vs. 13 days, p=0.012), whilst SSRF within 72 hours was not. Conclusion: Surgical fixation of complex rib fractures improves outcomes in selected patient groups. Delayed surgical fixation was associated with increased rates of pneumonia and a longer hospital length of stay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.826-842
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• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• Korean Circulation Journal
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• v.53 no.9
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• pp.635-644
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• 2023

Background and Objectives: The History, Electrocardiography, Age, Risk factors, and Troponin (HEART) pathway was developed to identify patients at low risk of a major adverse cardiac event (MACE) among patients presenting with chest pain to the emergency department. Methods: We modified the HEART pathway by replacing the Korean cut-off of 25 kg/m² with the conventional threshold of 30 kg/m² in the definition of obesity among risk factors. The primary outcome was a MACE within 30 days, which included acute myocardial infarction, primary coronary intervention, coronary artery bypass grafting, and all-cause death. Results: Of the 1,304 patients prospectively enrolled, MACE occurred in 320 (24.5%). The modified HEART pathway identified 37.3% of patients as low-risk compared with 38.3% using the HEART pathway. Of the 500 patients classified as low-risk with HEART pathway, 8 (1.6%) experienced MACE, and of the 486 low-risk patients with modified HEART pathway, 4 (0.8%) experienced MACE. The modified HEART pathway had a sensitivity of 98.8%, a negative predictive value (NPV) of 99.2%, a specificity of 49.0%, and a positive predictive value (PPV) of 38.6%, compared with the original HEART pathway, with a sensitivity of 97.5%, a NPV of 98.4%, a specificity of 50.0%, and a PPV of 38.8%. Conclusions: When applied to Korean population, modified HEART pathway could identify patients safe for early discharge more accurately by using body mass index cut-off levels suggested for Koreans.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.35.1-35.11
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• 2023

Background: Cardio-cerebrovascular diseases (CVDs) are the most common cause of death worldwide. Various CVD risk assessment tools have been developed. In South Korea, the Korea Occupational Safety & Health Agency (KOSHA) and the National Health Insurance Service (NHIS) have provided CVD risk assessments with health checkups. Since 2018, the KOSHA guide has stated that NHIS CVD risk assessment tool could be used as an alternative of KOSHA assessment tool for evaluating CVD risk of workers. The objective of this study was to determine the correlation and agreement between the KOSHA and the NHIS CVD risk assessment tools. Methods: Subjects of this study were 17,485 examinees aged 20 to 64 years who had undergone medical examinations from January 2021 to December 2021 at a general hospital. We classified subjects into low-risk, moderate-risk, high-risk, and highest-risk groups according to KOSHA and NHIS's CVD risk assessment tools. We then compared them with cross-analysis, Spearman correlation analysis, and linearly weighted kappa coefficient. Results: The correlation between KOSHA and NHIS tools was statistically significant (p-value < 0.001), with a correlation coefficient of 0.403 and a kappa coefficient of 0.203. When we compared risk group distribution using KOSHA and NHIS tools, CVD risk of 6,498 (37.1%) participants showed a concordance. Compared to the NHIS tool, the KOSHA tool classified 9,908 (56.7%) participants into a lower risk category and 1,079 (6.2%) participants into a higher risk category. Conclusions: In this study, KOSHA and NHIS tools showed a moderate correlation with a fair agreement. The NHIS tool showed a tendency to classify participants to higher CVD risk group than the KOSHA tool. To prevent CVD more effectively, a higher estimation tool among verified CVD risk assessment methods should be selected and managements such as early intervention and treatment of risk factors should be performed targeting the high-risk group.

• Pediatric Infection and Vaccine
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• v.30 no.3
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• pp.180-187
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• 2023

In Korea, >90% of children and adolescents aged <19 years have been infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since 2020. Among confirmed cases of pediatric coronavirus disease 2019 (COVID-19), 40-60% of patients developed neurologic symptoms such as seizures, headache, and encephalitis. Herein, we report the case of a 3-year-old female patient with SARS-CoV-2 infection who presented with seizures and altered consciousness and was diagnosed with COVID-19 encephalitis. The patient recovered after treatment with intravenous immunoglobulin, high-dose steroids, anti-seizure drugs, and an anti-viral agent. She was discharged after regaining the ability to speak words and walk alone on hospital day 39. Complete recovery was observed at the 1-year follow-up. The findings in this case suggest that early detection and active intervention is associated with better outcomes in patients with COVID-19 encephalitis.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.23 no.2
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• pp.31-38
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• 2023

Maple syrup urine disease (MSUD) is an autosomal recessive metabolic disorder caused by a deficiency in branched chain α-keto acid dehydrogenase (BCKAD). Between 1997, when Korea's MSUD case was first reported, and 2023, 14 cases were reported in the literature. 29% of the cases experienced developmental delay, and 29% expired. The prevalence of MSUD in Korea was estimated to be 1 in 230,000. Of 21 MSUD patients currently being treated at the Korea Genetics Research Center, 19 were detected through newborn screening program, and 2 were diagnosed by the symptoms. 14 MSUD patients had confirmed genetic mutations; 6 (43%) were BCKDHA and 8 (57%) were BCKDHB. In one case, a large deletion was observed. 4 patients had leucine levels above 2,000 (umo/L), and post-dialysis diet therapy was initiated in the newborn period. No patient required further dialysis as diet therapy and regular monitoring proved highly effective. Most MSUD patients were growing normally; weight and height growth were above the 50th percentile in 76% of the cases while BMI values were higher than normal in 71% of cases. Developmental delays were observed only in 2 cases (10%) and anticonvulsant use in 3 cases (14%). With newborn screening available to all Korean infants, early diagnosis and intervention should allow most patients to remain asymptomatic. However, ongoing surveillance, dietary management and continued patient compliance as well as rapid correction of acute metabolic decompensations remain critical to a favorable long-term prognosis.

• The korean journal of orthodontics
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• v.54 no.4
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• pp.229-238
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• 2024

Objective: The study aimed to assess the prevalence of dental malocclusion, orthodontic parameters, and parafunctional habits in children with developmental dyslexia (DD). Methods: Forty pediatric patients (67.5% boys and 32.5% girls, mean age: 11.02 ± 2.53 years, range: 6-15 years) with DD were compared with 40 age- and sex-matched healthy participants for prevalence of dental malocclusion, orthodontic parameters, and parafunctional habits. Dental examinations were performed by an orthodontist. Results: Pediatric patients with DD exhibited a significantly higher prevalence of Angle Class III malocclusion (22.5% vs. 5.0%, P = 0.024), deep bite (27.5% vs. 7.5%, P = 0.019), midline deviation (55.0% vs. 7.5%, P < 0.0001), midline diastemas (32.5% vs. 7.5%, P = 0.010), wear facets (92.5% vs. 15.0%, P < 0.0001), self-reported nocturnal teeth grinding (82.5% vs. 7.5%, P < 0.0001), nail biting (35.0% vs. 0.0%, P < 0.0001), and atypical swallowing (85.0% vs. 17.5%, P < 0.0001) compared to that in healthy controls. Conclusions: Pediatric patients with DD showed a higher prevalence of Class III malocclusion, greater orthodontic vertical and transverse discrepancies, and incidence of parafunctional activities. Clinicians and dentists should be aware of the vulnerability of children with dyslexia for exhibiting malocclusion and encourage early assessment and multidisciplinary intervention.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.146-160
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• 2024

Background and Purpose: The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia. Methods: Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition. Results: Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%. Conclusions: The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

• The Journal of Korean society of community based occupational therapy
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• v.1 no.2
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• pp.21-30
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• 2011

The previous studies were prevalent a study of treatment like a environmental modification or compensative approach and intervention which used in today to paralyzed patients. These interventions were related with occupational therapy widely. The purpose of this study is to provide a basic datum for environmental modification, compensative approach, and intervention observing physiological changes which is shown in early paralyze patients. The subjects were 40 students who were 20 female and 20 male in a college. The students were devided into hemiplegic and paraplegic model. The model was designed using a experimental cloths. A instrument to measure body composition was a precision instrument. The results of the study were as follow: First, there was no different homogeneity between activity daily of living of hemiplegic and paraplegic model. Second, there was a significant different body water and basal metabolic rate between before and after activity daily of living of hemiplegic model. Third, there was a significant different body water and basal metabolic rate between before and after activity daily of living of paraplegic model. Forth, there were no significant different physiological change between after activity daily of living of hemiplegic model and paraplegic model. We observed early changes of body composition using a hemiplegic and paraplegic model. We could know it was reduced body water rate and basal metabolic rate in regardless of type of paralysis. Therefore, it is important to know these physiological changes of paralyzed patients and improve body water and basal metabolic rate of the patients.