Prediction of low-density lipoprotein cholesterol levels using machine learning methods.

OBJECTIVE: Low-density lipoprotein cholesterol (LDL-C) has been commonly calculated by equations, but their performance has not been entirely satisfactory. This study aimed to develop a more accurate LDL-C prediction model using machine learning methods. METHODS: The study involved predicting directly measured LDL-C, using individual characteristics, lipid profiles, and other laboratory results as predictors. The models applied to predict LDL-C values were multiple regression, penalized regression, random forest, and XGBoost. Additionally, a novel 2-step prediction model was developed and introduced. The machine learning methods were evaluated against the Friedewald, Martin, and Sampson equations. RESULTS: The Friedewald, Martin, and Sampson equations had root mean squared error (RMSE) values of 12.112, 8.084, and 8.492, respectively, whereas the 2-step prediction model showed the highest accuracy, with an RMSE of 7.015. The LDL-C levels were also classified as a categorical variable according to the diagnostic criteria of the dyslipidemia treatment guideline, and concordance rates were calculated between the predictive values obtained from each method and the directly measured ones. The 2-step prediction model had the highest concordance rate (85.1%). CONCLUSION: The machine learning method can calculate LDL-C more accurately than existing equations. The proposed 2-step prediction model, in particular, outperformed the other machine learning methods.

Prioritization of Injury Prevention and Management Programs and Research and Development (R&D) Projects: Survey Using the Delphi Technique and Analytic Hierarchy Process.

We prioritized injury prevention and management programs, and research and development (R&D) projects using the Delphi method and analytic hierarchy process (AHP) for national plan. We summarized 21 programs and 31 R&D projects based on opinions collected in the opinion survey and brainstorming. Expert panel evaluated program and project relevance in the two Delphi rounds to make consensus. Total scores were calculated by adding criterion weights calculated through the AHP multiplied by the average of scores for each program and project. The top three programs were "Integrated Management System for Injury Data," "Comprehensive Injury Surveillance System," and "Transport System Improvement Program for Major Trauma." The top three R&D projects were researches on "Identification of Vulnerable Workers Injuries to Strengthen Protections," "Data Integration on Injury and Disability," and "Using Public Health Big Data to Identify Injury Status and Risk Factors." Experts highly rated the programs to improve injury surveillance system.

Comparative genomics reveals the dynamic evolutionary history of cement protein genes of barnacles from intertidal to deep-sea hydrothermal vents.

Thoracican barnacles are a diverse group of marine organisms for which the availability of genome assemblies is currently limited. In this study, we sequenced the genomes of two neolepadoid species (Ashinkailepas kermadecensis, Imbricaverruca yamaguchii) from hydrothermal vents, in addition to two intertidal species. Genome sizes ranged from 481 to 1054 Mb, with repetitive sequence contents of 21.2% to 50.7%. Concordance rates of orthologs and heterozygosity rates were between 82.4% and 91.7% and between 1.0% and 2.1%, respectively, indicating high genetic diversity and heterozygosity. Based on phylogenomic analyses, we revised the nomenclature of cement genes encoding cement proteins that are not homologous to any known proteins. The major cement gene, CP100A, was found in all thoracican species, including vent-associated neolepadoids, and was hypothesised to be essential for thoracican settlement. Duplicated genes, CP100B and CP100C, were found only in balanids, suggesting potential functional redundancy or acquisition of new functions associated with the calcareous base. An ancestor of CP52 genes was duplicated dynamically among lepadids, pollicipedids with multiple copies on a single scaffold, and balanids with multiple sequential repeats of the conserved regions, but no CP52 genes were found in neolepadoids, providing insights into cement gene evolution among thoracican lineages. This study enhances our understanding of the adhesion mechanisms of thoracicans in underwater environments. The newly sequenced genomes provide opportunities for studying their evolution and ecology, shedding light on their adaptation to diverse marine environments, and contributing to our knowledge of barnacle biology with valuable genomic resources for further studies in this field.

Factors affecting patients who attempted suicide in the emergency department due to the prolonged pandemic of COVID-19.

OBJECTIVE: This study examined the characteristics of patients who attempted suicide in the emergency department before and during the COVID-19 pandemic. METHODS: We compared data from patients in the emergency department following suicide attempts between January 2018 and December 2021. The patients were categorized into two groups: "pre-COVID-19" and "during COVID-19" pandemic. RESULTS: The findings revealed an increasing trend of suicide attempts during the study period. Suicide attempts were reported at 1,107 before the COVID-19 pandemic and 1,356 during the COVID-19 pandemic. Patients who attempted suicide during the COVID-19 pandemic were younger (38.0±18.5 years vs. 40.7±18.4 years, P<0.01), had a smaller proportion of men (36% vs. 44%, P<0.01), and had fewer medical comorbidities (20.2% vs. 23.6%, P<0.05). The group during the COVID-19 pandemic reported better hygiene conditions (50.5% vs. 40.8%, P<0.01) and lower alcohol consumption (27.7% vs. 37.6%, P<0.01). Patients who attempted suicide during the COVID-19 pandemic had higher rates of use of psychiatric medications and previous suicide attempts. The most common reasons for the suicide attempt were unstable psychiatric disorders (38.8%), poor interpersonal relationships (20.5%), and economic difficulties (14.0%). Drug poisoning (44.1%) was the most common method of suicide attempts. Subgroup analysis with patients who attributed their suicide attempts to COVID-19 revealed a higher level of education (30.8%) and employment status (69.2%), with economic difficulties (61.6%) being the primary cause of suicide attempts. CONCLUSION: These findings suggest that the prolonged duration of the COVID-19 pandemic and its effects on social and economic factors have influenced suicide attempts.

Machine learning approaches that use clinical, laboratory, and electrocardiogram data enhance the prediction of obstructive coronary artery disease.

Pretest probability (PTP) for assessing obstructive coronary artery disease (ObCAD) was updated to reduce overestimation. However, standard laboratory findings and electrocardiogram (ECG) raw data as first-line tests have not been evaluated for integration into the PTP estimation. Therefore, this study developed an ensemble model by adopting machine learning (ML) and deep learning (DL) algorithms with clinical, laboratory, and ECG data for the assessment of ObCAD. Data were extracted from the electronic medical records of patients with suspected ObCAD who underwent coronary angiography. With the ML algorithm, 27 clinical and laboratory data were included to identify ObCAD, whereas ECG waveform data were utilized with the DL algorithm. The ensemble method combined the clinical-laboratory and ECG models. We included 7907 patients between 2008 and 2020. The clinical and laboratory model showed an area under the curve (AUC) of 0.747; the ECG model had an AUC of 0.685. The ensemble model demonstrated the highest AUC of 0.767. The sensitivity, specificity, and F1 score of the ensemble model ObCAD were 0.761, 0.625, and 0.696, respectively. It demonstrated good performance and superior prediction over traditional PTP models. This may facilitate personalized decisions for ObCAD assessment and reduce PTP overestimation.

Production of Plant-Derived Japanese Encephalitis Virus Multi-Epitope Peptide in Nicotiana benthamiana and Immunological Response in Mice.

The current production of the Japanese encephalitis virus (JEV) vaccine is based on animal cells, where various risk factors for human health should be resolved. This study used a transient expression system to express the chimeric protein composed of antigenic epitopes from the JEV envelope (E) protein in Nicotiana benthamiana. JEV multi-epitope peptide (MEP) sequences fused with FLAG-tag or 6× His-tag at the C- or N-terminus for the purification were introduced into plant expression vectors and used for transient expression. Among the constructs, vector pSK480, which expresses MEP fused with a FLAG-tag at the C-terminus, showed the highest level of expression and yield in purification. Optimization of transient expression procedures further improved the target protein yield. The purified MEP protein was applied to an ICR mouse and successfully induced an antibody against JEV, which demonstrates the potential of the plant-produced JEV MEP as an alternative vaccine candidate.

Electrocardiogram-based deep learning algorithm for the screening of obstructive coronary artery disease.

BACKGROUND: Information on electrocardiogram (ECG) has not been quantified in obstructive coronary artery disease (ObCAD), despite the deep learning (DL) algorithm being proposed as an effective diagnostic tool for acute myocardial infarction (AMI). Therefore, this study adopted a DL algorithm to suggest the screening of ObCAD from ECG. METHODS: ECG voltage-time traces within a week from coronary angiography (CAG) were extracted for the patients who received CAG for suspected CAD in a single tertiary hospital from 2008 to 2020. After separating the AMI group, those were classified into ObCAD and non-ObCAD groups based on the CAG results. A DL-based model adopting ResNet was built to extract information from ECG data in the patients with ObCAD relative to those with non-ObCAD, and compared the performance with AMI. Moreover, subgroup analysis was conducted using ECG patterns of computer-assisted ECG interpretation. RESULTS: The DL model demonstrated modest performance in suggesting the probability of ObCAD but excellent performance in detecting AMI. The AUC of the ObCAD model adopting 1D ResNet was 0.693 and 0.923 in detecting AMI. The accuracy, sensitivity, specificity, and F1 score of the DL model for screening ObCAD were 0.638, 0.639, 0.636, and 0.634, respectively, while the figures were up to 0.885, 0.769, 0.921, and 0.758 for detecting AMI, respectively. Subgroup analysis showed that the difference between normal and abnormal/borderline ECG groups was not notable. CONCLUSIONS: ECG-based DL model showed fair performance for assessing ObCAD and it may serve as an adjunct to the pre-test probability in patients with suspected ObCAD during the initial evaluation. With further refinement and evaluation, ECG coupled with the DL algorithm may provide potential front-line screening support in the resource-intensive diagnostic pathways.

Impact of treatment adherence on the effectiveness and safety of oral anticoagulants in patients with atrial fibrillation: a retrospective cohort study.

AIMS: The impact of adherence to oral anticoagulation has not been reported in terms of absolute risk, which would enhance patients' understanding and treatment adherence. METHODS AND RESULTS: This retrospective cohort study analysed data from the National Health Insurance Database of Korea, from January 2010 to December 2018, on 84 227 patients with non-valvular atrial fibrillation (NVAF). The participants were analysed according to their overall adherence to oral anticoagulants (OACs) and further divided into four groups: non-vitamin K antagonist oral anticoagulant (NOAC) adherent, vitamin K antagonist (VKA) adherent, NOAC non-adherent, and VKA non-adherent. The incidence of ischaemic stroke, major bleeding, and death was compared between the four groups using risk difference, number needed to treat and number needed to harm. Among the participants, 50 178 were adherent to (OACs), while 34 049 were non-adherent. The incidence of major bleeding was higher in the adherent group (4.49%; 95% confidence interval, 4.11-4.85%) than in the non-adherent group (3.61%; 3.16-4.06%), and the incidence of ischaemic stroke was higher in the non-adherent group (7.68%; 7.08-8.33%) than in the adherent group (5.61%; 5.17-6.07%). In terms of risk difference, adherence to OACs increased the risk of major bleeding by 0.87% and decreased the risk of ischaemic stroke by 2.08%. This finding suggests that one additional major bleeding event occurred for every 115 adherent patients, and one additional ischaemic stroke event was prevented for every 48 adherent patients. CONCLUSION: The benefits of OAC adherence in NVAF patients for ischaemic stroke prevention exceeding the risk of bleeding are shown more clearly in terms of absolute risk.

Health-related quality of life using WHODAS 2.0 and associated factors 1 year after stroke in Korea: a multi-centre and cross-sectional study.

BACKGROUND: Little is known about the self-perceived level of disability of stroke survivors in the community. We aimed to characterise Health-related quality of life (HRQoL) 1 year after stroke and investigate how sociodemographic and stroke-related factors and medical adherence explain the self-perceived level of disability in a Korean stroke population. METHODS: This was a multicentre cross-sectional study. A total of 382 ischaemic stroke survivors at 1 year after onset from 11 university hospitals underwent a one-session assessment, including socioeconomic variables, the modified Rankin Scale (mRS), various neurological sequelae, the Morisky, Green and Levin-Medication Adherence Questionnaire (MGL), and the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) 36-items. The relationship between disability and different variables was analysed using ordinal logistic regression. RESULTS: The prevalence of disability based on global WHODAS 2.0 was 62.6% (mild, 41.6%; moderate, 16.0%; severe, 5.0%). The prevalence of severe disability was higher in participation in society (16.8%) and getting around (11.8%) than in other domains. Low MGL- motivation was the only factor determining a significant association between all six domains of disability after adjustment. Different predictors for specific domains were age, mRS, dysarthria, trouble seeing, cognition problems, and MGL-motivation for understanding and communicating; age, recurrent stroke, mRS, hemiplegia, facial palsy, general weakness, and MGL-motivation for getting around; age, education, mRS, hemiplegia, and MGL-motivation for self-care; education, recurrent stroke, hemiplegia, dysarthria, and MGL-motivation for getting along with people; age, education, income, mRS, hemiplegia, dysarthria, MGL-knowledge, and MGL-motivation for life activities; living without a spouse, mRS, hemiplegia, dysarthria, trouble seeing, cognition problems, general weakness, and MGL-motivation for participation in society. CONCLUSIONS: Self-perceived disability according to the WHODAS 2.0 at 1 year after stroke was highly prevalent. Each disability domain showed a different prevalence and associated factors. Interventions promoting medical adherence to motivation seemed to help achieve high HRQoL in all domains.

Comparison of Factors Associated With Direct Versus Transferred-in Admission to Government-Designated Regional Centers Between Acute Ischemic Stroke and Myocardial Infarction in Korea.

BACKGROUND: There has been no comparison of the determinants of admission route between acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We examined whether factors associated with direct versus transferred-in admission to regional cardiocerebrovascular centers (RCVCs) differed between AIS and AMI. METHODS: Using a nationwide RCVC registry, we identified consecutive patients presenting with AMI and AIS between July 2016 and December 2018. We explored factors associated with direct admission to RCVCs in patients with AIS and AMI and examined whether those associations differed between AIS and AMI, including interaction terms between each factor and disease type in multivariable models. To explore the influence of emergency medical service (EMS) paramedics on hospital selection, stratified analyses according to use of EMS were also performed. RESULTS: Among the 17,897 and 8,927 AIS and AMI patients, 66.6% and 48.2% were directly admitted to RCVCs, respectively. Multivariable analysis showed that previous coronary heart disease, prehospital awareness, higher education level, and EMS use increased the odds of direct admission to RCVCs, but the odds ratio (OR) was different between AIS and AMI (for the first 3 factors, AMI > AIS; for EMS use, AMI < AIS). EMS use was the single most important factor for both AIS and AMI (OR, 4.72 vs. 3.90). Hypertension and hyperlipidemia increased, while living alone decreased the odds of direct admission only in AMI; additionally, age (65-74 years), previous stroke, and presentation during non-working hours increased the odds only in AIS. EMS use weakened the associations between direct admission and most factors in both AIS and AMI. CONCLUSIONS: Various patient factors were differentially associated with direct admission to RCVCs between AIS and AMI. Public education for symptom awareness and use of EMS is essential in optimizing the transportation and hospitalization of patients with AMI and AIS.

Forecasting of non-accidental, cardiovascular, and respiratory mortality with environmental exposures adopting machine learning approaches.

Environmental exposure constantly changes with time and various interactions that can affect health outcomes. Machine learning (ML) or deep learning (DL) algorithms have been used to solve complex problems, such as multiple exposures and their interactions. This study developed predictive models for cause-specific mortality using ML and DL algorithms with the daily or hourly measured meteorological and air pollution data. The ML algorithm improved the performance compared to the conventional methods, even though the optimal algorithm depended on the adverse health outcomes. The best algorithms were extreme gradient boosting, ridge, and elastic net, respectively, for non-accidental, cardiovascular, and respiratory mortality with daily measurement; they were superior to the generalized additive model reducing a mean absolute error by 4.7%, 4.9%, and 16.8%, respectively. With hourly measurements, the ML model tended to outperform the conventional models, even though hourly data, instead of daily data, did not enhance the performance in some models. The proposed model allows a better understanding and development of robust predictive models for health outcomes using multiple environmental exposures.

Comparisons of Prehospital Delay and Related Factors Between Acute Ischemic Stroke and Acute Myocardial Infarction.

Background Prehospital delay is an important contributor to poor outcomes in both acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We aimed to compare the prehospital delay and related factors between AIS and AMI. Methods and Results We identified patients with AIS and AMI who were admitted to the 11 Korean Regional Cardiocerebrovascular Centers via the emergency room between July 2016 and December 2018. Delayed arrival was defined as a prehospital delay of >3 hours, and the generalized linear mixed-effects model was applied to explore the effects of potential predictors on delayed arrival. This study included 17 895 and 8322 patients with AIS and AMI, respectively. The median value of prehospital delay was 6.05 hours in AIS and 3.00 hours in AMI. The use of emergency medical services was the key determinant of delayed arrival in both groups. Previous history, 1-person household, weekday presentation, and interhospital transfer had higher odds of delayed arrival in both groups. Age and sex had no or minimal effects on delayed arrival in AIS; however, age and female sex were associated with higher odds of delayed arrival in AMI. More severe symptoms had lower odds of delayed arrival in AIS, whereas no significant effect was observed in AMI. Off-hour presentation had higher and prehospital awareness had lower odds of delayed arrival; however, the magnitude of their effects differed quantitatively between AIS and AMI. Conclusions The effects of some nonmodifiable and modifiable factors on prehospital delay differed between AIS and AMI. A differentiated strategy might be required to reduce prehospital delay.

Phylogeny and shell form evolution of the hydrothermal vent asymmetrical barnacles (Cirripedia, Thoracicalcarea, Neoverrucidae).

Imbricaverruca and Neoverruca are two genera of hydrothermal vent asymmetrical barnacles in Neoverrucidae, but found in vents of the Southwest Pacific and Northwest Pacific Oceans, respectively. Imbricaverruca has a flattened operculum and the shell base with multiple whorls of imbricating plates, while Neoverruca has an inclined operculum and the shell base with fewer developed imbricating plates. It has been hypothesized that Imbricaverruca has apomorphic shell characters in Neoverrucidae. Although the monophyletic relationship of the vent barnacle members in the superfamily Neolepadoidea were confirmed based on molecular phylogeny, the relationships between Neobrachylepadidae and Neoverrucidae, and between Neoverruca and Imbricaverruca have not been determined because there are no molecular data on Imbricaverruca. In this study, we sequenced three nuclear (18S rDNA, 28S rDNA, histone 3) and one mitochondrial (CO1) genes of I. yamaguchii from the Southwest Pacific. Our phylogenetic results showed that Neobrahchylepadidae is the sister taxon to Neoverrucidae (Imbricaverruca + Neoverruca), and Imbricaverruca and Neoverruca are monophyletic sister taxa each other, which not supporting the previous hypothesis that Neoverruca is sister to the clade containing Neobrahchylepadidae and Neolepadidae. These implied that the differences in shell forms between Neoverruca and Imbricaverruca are a result of independent divergent evolution in different deep-sea basins.

Joinpoint Regression About Injury Mortality and Hospitalization in Korea.

BACKGROUND: Injury is a social problem that causes health and property losses, and it is important to identify the size and trend of injury for efficient prevention and management. Therefore, this study analyzed the trends in injury mortality and hospitalization rates from 2005 to 2019 in Korea. METHODS: Using mortality data by Statistics Korea and Korea National Hospital Discharge In-depth injury survey by the Korea Disease Control and Prevention Agency (KDCA), age standardized rates were calculated for death and hospitalization to analyze trends and annual changes with the joinpoint regression model. In addition, annual changes in the hospitalization rate of the transport accident and fall injuries by age group were analyzed, which are the major causes of injuries. RESULTS: From 2005 to 2019, the injury mortality rate has been on the decline, but the injury hospitalization rate has been on the rise. The annual rate of change varied depending on the injury mechanism, but the mortality rate tended to decrease or remain similar level, while the rate of hospitalization has steadily increased. In addition, by age group, injury mortality and hospitalization rates were high in the elderly. In particular, the hospitalization rate of the elderly was higher when comparing the hospitalization rate of the children in transport accidents and falls. Pedestrian transport accidents tended to decrease under the age of 15, but remained similar for those aged 65 and older, and bicycle accidents tended to increase in both groups. In addition, hospitalization rates were higher in the fall, with both groups showing a statistically significant increase in hospitalization rates caused by falls. CONCLUSION: This study analyzed the trend of injury mortality and hospitalization and found that transport accidents and falls may vary depending on the means or age of the accident. Since injury is a big social problem that is a burden of disease, safety education and legal sanctions for injury prevention should be further improved in the future, especially by prioritizing vulnerable groups by age and detailed mechanisms of injury.

mHealth Interventions for Lifestyle and Risk Factor Modification in Coronary Heart Disease: Randomized Controlled Trial.

BACKGROUND: Self-management of lifestyle and cardiovascular disease risk factors is challenging in older patients with coronary heart disease (CHD). SMS text messaging could be a potential support tool for self-management and the most affordable and accessible method through a mobile phone. High-quality evidence had been lacking, and previous studies evaluated the effects of SMS text messaging on the subjective measures of short-term outcomes. Recently, a large-sized randomized controlled trial in Australia reported promising findings on the objective measures upon 6-month follow-up. However, an examination of the effectiveness of such interventions in an Asian population with unique demographic characteristics would be worthwhile. OBJECTIVE: This study examined the effectiveness of a 1-way SMS text messaging program to modify the lifestyle and cardiovascular disease risk factors of patients who underwent the first percutaneous coronary intervention (PCI). METHODS: A parallel, single-blinded, 1:1 random allocation clinical trial was conducted with 879 patients treated through PCI. They were recruited during hospital admission from April 2017 to May 2020 at 2 university hospitals in the Republic of Korea. In addition to standard care, the intervention group received access to a supporting website and 4 SMS text messages per week for 6 months regarding a healthy diet, physical activity, smoking cessation, and cardiovascular health. Random allocation upon study enrollment and SMS text messaging after hospital discharge were performed automatically using a computer program. The coprimary outcomes were low-density-lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), and BMI. The secondary outcomes were change in lifestyle and adherence to the recommended health behaviors. RESULTS: Of the eligible population, 440 and 439 patients who underwent PCI were assigned to the intervention and control groups, respectively. The 1-way SMS text messaging program significantly enhanced physical activity (P=.02), healthy diet (P<.01), and medication adherence (P<.04) among patients with CHD. Hence, more people were likely to control their cardiovascular disease risk factors per the recommendations. The intervention group was more likely to control all 5 risk factors by 62% (relative risk 1.62, 95% CI 1.05-2.50) per the recommendations. On the other hand, physiological measures of the primary outcomes, including LDL-C levels, SBP, and BMI, were not significant. Most participants found the SMS text messaging program useful and helpful in motivating lifestyle changes. CONCLUSIONS: Lifestyle-focused SMS text messages were effective in the self-management of a healthy diet, exercise, and medication adherence, but their influence on the physiological measures was not significant. One-way SMS text messages can be used as an affordable adjuvant method for lifestyle modification to help prevent the recurrence of cardiovascular disease. TRIAL REGISTRATION: Clinical Research Information Service (CRiS) KCT0005087; https://cris.nih.go.kr/cris/search/detailSearch.do/19282.

Did inter-hospital transfer reduce mortality in patients with acute myocardial infarction in the real world? A nationwide patient cohort study.

INTRODUCTION: Inter-hospital transfer (IHT) and primary percutaneous coronary intervention (PCI) are preferred over onsite thrombolysis when provided expeditiously. On the other hand, its benefit has not been evaluated in a real-world situation. This study examined the effects of IHT on the short- and long-term mortality in patients with acute myocardial infarction (AMI) and compared the reperfusion treatments and resources between the referring and receiving hospitals. METHODS: Patients newly diagnosed with AMI and admitted to hospital were selected from the national health insurance database from 2004 to 2018. The 30-day and one-year mortality in the transferred and non-transferred patients were estimated and compared using stabilized inverse probability of treatment weighting to account for confounding bias. RESULTS: Of the 258,291 participants, 10,158 were transferred to one or more hospitals. IHT was more likely to occur to older or more comorbid people, patients in rural areas, and those whose insurance was medical aid. The 30-day and one-year mortality of the non-IHT group was 9.7% and 15.8%, respectively, whereas the figure was 11.4% and 20.5% in the IHT group. After balancing the baseline characteristics, the transferred patients were 1.12 (95% CI: 1.06-1.20) and 1.25 (95% CI: 1.20-1.31) times more likely to die during the subsequent 30 days and one year, respectively, than those treated solely at the presenting hospital. In ST-segment elevation myocardial infarction (STEMI), the hazard ratios of the 30-day and 1-year mortality were 1.14 (95% CI: 0.97-1.35) and 1.31 (95% CI: 1.15-1.49) in the transferred patients after balancing cardiogenic shock and cardiac arrest. On-site thrombolysis was rarely performed in the referring hospitals. CONCLUSION: Patients transferred for the treatment of AMI experienced higher short- and long-term mortality. Therefore, onsite thrombolysis and the estimated time delay to PCI should be considered in regional hospitals to reduce mortality with the organization of STEMI treatment networks.

Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction.

Machine learning (ML) has been suggested to improve the performance of prediction models. Nevertheless, research on predicting the risk in patients with acute myocardial infarction (AMI) has been limited and showed inconsistency in the performance of ML models versus traditional models (TMs). This study developed ML-based models (logistic regression with regularization, random forest, support vector machine, and extreme gradient boosting) and compared their performance in predicting the short- and long-term mortality of patients with AMI with those of TMs with comparable predictors. The endpoints were the in-hospital mortality of 14,183 participants and the three- and 12-month mortality in patients who survived at discharge. The performance of the ML models in predicting the mortality of patients with an ST-segment elevation myocardial infarction (STEMI) was comparable to the TMs. In contrast, the areas under the curves (AUC) of the ML models for non-STEMI (NSTEMI) in predicting the in-hospital, 3-month, and 12-month mortality were 0.889, 0.849, and 0.860, respectively, which were superior to the TMs, which had corresponding AUCs of 0.873, 0.795, and 0.808. Overall, the performance of the predictive model could be improved, particularly for long-term mortality in NSTEMI, from the ML algorithm rather than using more clinical predictors.

Diversity and characterization of bacterial communities of five co-occurring species at a hydrothermal vent on the Tonga Arc.

Host-symbiont relationships in hydrothermal vent ecosystems, supported by chemoautotrophic bacteria as primary producers, have been extensively studied. However, the process by which densely populated co-occurring invertebrate hosts form symbiotic relationships with bacterial symbionts remains unclear. Here, we analyzed gill-associated symbiotic bacteria (gill symbionts) of five co-occurring hosts, three mollusks ("Bathymodiolus" manusensis, B. brevior, and Alviniconcha strummeri) and two crustaceans (Rimicaris variabilis and Austinograea alayseae), collected together at a single vent site in the Tonga Arc. We observed both different compositions of gill symbionts and the presence of unshared operational taxonomic units (OTUs). In addition, the total number of OTUs was greater for crustacean hosts than for mollusks. The phylogenetic relationship trees of gill symbionts suggest that γ-proteobacterial gill symbionts have coevolved with their hosts toward reinforcement of host specificity, while campylobacterial Sulfurovum species found across various hosts and habitats are opportunistic associates. Our results confirm that gill symbiont communities differ among co-occurring vent invertebrates and indicate that hosts are closely related with their gill symbiont communities. Considering the given resources available at a single site, differentiation of gill symbionts seems to be a useful strategy for obtaining nutrition and energy while avoiding competition among both hosts and gill symbionts.

The mitochondrial genome of hydrothermal vent barnacle Eochionelasmus coreana (Cirripedia: Thoracica) from the Indian Ocean.

Balanomorph Eochionelasmus species are hydrothermal vent endemic barnacles. In the genus Eochionelasmus, three species are known to date and they distribute at three different vent fields in Pacific and Indian Oceans, E. ohtai in the Southwest Pacific Ocean, E. paquensis in the East Pacific Ocean, and E. coreana in the Indian Ocean. Therefore, Eochionelasmus species are considered to be a meaningful model taxon to elucidate the evolutionary history of vent organism in relation to geotectonic events. Here, we characterized the partial mitogenome of a newly described vent barnacle Eochionelasmus coreana Chan et al., 2020 from the Solitaire vent field in the Indian Ocean. The length of mitogenome was 16,804 bp with 64.0% AT content. Its gene content and organization was identical to those of E. ohtai. There was one significant part in the mitogenome of E. coreana, which was a long intergenic region over 2 kb found between tRNAPro and tRNAThr. The phylogenetic tree suggested the monophyly of E. ohtai and E. coreana with high supporting values. In the future, additional mitogenome analysis of the last Eochionelasmus species, E. paquensis, could expand our understanding about the speciation and global distribution of Eochionelasmus species.