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Abstract Background Metabolic dysfunction-associated steatohepatitis (MASH) is a growing global health concern with no effective pharmacological treatments. SNP-630, a newly developed synthetic molecule with multiple mechanisms of action, and a mixture of two of its active metabolites (SNP-630-MS) inhibit CYP2E1 expression to prevent reactive oxygen species generation, thereby reducing the accumulation of hepatic triglycerides and lowering chemokine levels. This study investigated the SNP-630’s potential to alleviate the liver injury in MASH and its efficacy in both a mouse model and patients with MASH to identify a drug candidate that targets multiple pathways implicated in MASH. Methods SNP-630 and SNP-630-MS were separately administered to the MASH mouse model. The tolerability, safety, and efficacy of SNP-630-MS were also evaluated in 35 patients with MASH. The primary endpoint of the study was assessment of the changes in serum alanine aminotransferase (ALT) levels from baseline to week 12, while the secondary endpoints included the evaluation of liver inflammation, steatosis, and fibrosis parameters and markers. Results SNP-630 treatment in mice improved inflammation, liver steatosis, and fibrosis compared with that in the MASH control group. Both SNP-630 and SNP-630-MS treatments markedly reduced ALT levels, hepatic triglyceride content, and the expression of inflammatory cytokines monocyte chemoattractant protein 1 and fibrotic collagen (i.e., Col1a1, Col3a1, and Timp1) in mice. In the clinical trial, patients treated with SNP-630-MS exhibited significant improvement in ALT levels at week 12 compared with baseline levels, with no reports of severe adverse events. This improvement in ALT levels surpassed that achieved with most other MASH candidates. SNP-630-MS demonstrated potential antifibrotic effects, as evidenced by a significant decrease in the levels of fibrogenesis-related biomarkers such as CCL4, CCL5, and caspase 3. Subgroup analysis using FibroScan measurements further indicated the efficacy of SNP-630-MS in ameliorating liver fibrosis. Conclusions SNP-630 and SNP-630-MS demonstrated favorable results in mice. SNP-630-MS showed excellent tolerability in mice and patients with MASH. Efficacy analyses indicated that SNP-630-MS improved liver steatosis and injury in patients with MASH, suggesting that SNP-630 and 630-MS are promising therapeutic options for MASH. Larger scale clinical trials remain warranted to assess the efficacy and safety of SNP-630 in MASH. Trial registration: ClinicalTrials.gov NCT03868566. Registered 06 March 2019-Retrospectively registered, https://clinicaltrials.gov/study/NCT03868566

Objectives Chest X-rays (CXRs) convey much illegible physiological information that deep learning model (DLM) has been reported interpreting successfully. Since the electrocardiogram age established by DLM was revealed as a heart biological marker, we hypothesize that CXR age has similar potential to describe the heart and lung states. Therefore, we developed a DLM to predict sex and age through CXR and analyzed its relation with future cardiovascular diseases (CVD). Methods A total of 90,396 CXRs aged 20 to 90 were collected and separated into a development set with 53,102 CXRs and demographic information pairs, a tuning set with 7073 pairs, an internal validation set with 17,364 pairs, and an external validation set with 12,857 pairs. The study trained DLM with development set for estimating age and sex and compared them to actual information. Results The mean absolute errors of predicted age were 4.803 and 4.313 years in the internal and external validation sets, respectively. The area under the curve of sex analysis was 0.9993 and 0.9988 in the internal and external validation sets, respectively. Patients whose CXR age was 5 years older than chronologic age lead to higher risk of all-cause mortality (hazard ratio (HR): 2.42, 95% confidence interval (CI): 2.00–2.92), cardiovascular (CV)-cause mortality (HR: 7.57, 95% CI: 4.55–12.60), new-onset heart failure (HR: 2.07, 95% CI: 1.56–2.76), new-onset chronic kidney disease (HR: 1.73, 95% CI: 1.46–2.05), new-onset acute myocardial infarction (HR: 1.80, 95% CI: 1.12–2.92), new-onset stroke (HR: 1.45, 95% CI: 1.10–1.90), new-onset coronary artery disease (HR: 1.26, 95% CI: 1.04–1.52), and new-onset atrial fibrillation (HR: 1.43, 95% CI: 1.01–2.02). Conclusions Using DLM to predict CXR age provided additional information for future CVDs. Older CXR age is an accessible risk classification tool for clinician use.

Background The electrocardiogram (ECG) may be the most popular test in the management of cardiovascular disease (CVD). Although wide applications of artificial intelligence (AI)-enabled ECG have been developed, an integrating indicator for CVD risk stratification was not investigated. Since mortality may be the most important global outcome, this study aimed to develop a survival deep learning model (DLM) to establish a critical ECG value and explore the associations with various CVD events. Methods We trained a DLM with 451,950 12-lead resting ECGs obtained from 210,552 patients, for whom 23,592 events occurred. The internal validation set included 27,808 patients with one ECG for each patient. The external validations were performed in a community hospital with 33,047 patients and two transnational data sets with 233,647 and 1631 ECGs. We distinguished the cause of mortality and additionally investigated CVD-related outcomes, including new-onset acute myocardial infarction (AMI), stroke (STK), and heart failure (HF). Results The DLM achieved C-indices of 0.858/0.836 in internal/external validation sets by using ECG over a 10-year period. The high-mortality-risk group identified by the proposed DLM presented a hazard ratio (HR) of 14.16 (95% confidence interval (CI): 11.33–17.70) compared to the low-risk group in the internal validation and presented a higher risk of cardiovascular (CV) mortality (HR: 18.50, 95% CI: 9.82–34.84), non-CV mortality (HR: 13.68, 95% CI: 10.76–17.38), AMI (HR: 4.01, 95% CI: 2.24–7.17), STK (HR: 2.15, 95% CI: 1.70–2.72), and HF (HR: 6.66, 95% CI: 4.54–9.77), which was consistent in an independent community hospital. The transnational validation also revealed HRs of 4.91 (95% CI: 2.63–9.16) and 2.29 (95% CI: 2.15–2.44) for all-cause mortality in the SaMi-Trop and Clinical Outcomes in Digital Electrocardiography 15% (CODE15) cohorts. Conclusions The mortality risk by AI-enabled ECG may be applied in passive electronic-health-record-based CVD risk screening, which may identify more asymptomatic and unaware high-risk patients.

Abstract Dyskalemias are common electrolyte disorders associated with high cardiovascular risk. Artificial intelligence (AI)-assisted electrocardiography (ECG) has been evaluated as an early-detection approach for dyskalemia. The aims of this study were to determine the clinical accuracy of AI-assisted ECG for dyskalemia and prognostic ability on clinical outcomes such as all-cause mortality, hospitalizations, and ED revisits. This retrospective cohort study was done at two hospitals within a health system from May 2019 to December 2020. In total, 26,499 patients with 34,803 emergency department (ED) visits to an academic medical center and 6492 ED visits from 4747 patients to a community hospital who had a 12-lead ECG to estimate ECG-K+ and serum laboratory potassium measurement (Lab-K+) within 1 h were included. ECG-K+ had mean absolute errors (MAEs) of ≤0.365 mmol/L. Area under receiver operating characteristic curves for ECG-K+ to predict moderate-to-severe hypokalemia (Lab-K+ ≤3 mmol/L) and moderate-to-severe hyperkalemia (Lab-K+ ≥ 6 mmol/L) were >0.85 and >0.95, respectively. The U-shaped relationships between K+ concentration and adverse outcomes were more prominent for ECG-K+ than for Lab-K+. ECG-K+ and Lab-K+ hyperkalemia were associated with high HRs for 30-day all-cause mortality. Compared to hypokalemic Lab-K+, patients with hypokalemic ECG-K+ had significantly higher risk for adverse outcomes after full confounder adjustment. In addition, patients with normal Lab-K+ but dyskalemic ECG-K+ (pseudo-positive) also exhibited more co-morbidities and had worse outcomes. Point-of-care bloodless AI ECG-K+ not only rapidly identified potentially severe hypo- and hyperkalemia, but also may serve as a biomarker for medical complexity and an independent predictor for adverse outcomes.

Background Artificial intelligence-enabled electrocardiogram has become a substitute tool for echocardiography in left ventricular ejection fraction estimation. However, the direct use of artificial intelligence-enabled electrocardiogram may be not trustable due to the uncertainty of the prediction. Objective The study aimed to establish an artificial intelligence-enabled electrocardiogram with a degree of confidence to identify left ventricular dysfunction. Methods The study collected 76,081 and 11,771 electrocardiograms from an academic medical center and a community hospital to establish and validate the deep learning model, respectively. The proposed deep learning model provided the point estimation of the actual ejection fraction and its standard deviation derived from the maximum probability density function of a normal distribution. The primary analysis focused on the accuracy of identifying patients with left ventricular dysfunction (ejection fraction ≤ 40%). Since the standard deviation was an uncertainty indicator in a normal distribution, we used it as a degree of confidence in the artificial intelligence-enabled electrocardiogram. We further explored the clinical application of estimated standard deviation and followed up on the new-onset left ventricular dysfunction in patients with initially normal ejection fraction. Results The area under receiver operating characteristic curves (AUC) of detecting left ventricular dysfunction were 0.9549 and 0.9365 in internal and external validation sets. After excluding the cases with a lower degree of confidence, the artificial intelligence-enabled electrocardiogram performed better in the remaining cases in internal (AUC = 0.9759) and external (AUC = 0.9653) validation sets. For the application of future left ventricular dysfunction risk stratification in patients with initially normal ejection fraction, a 4.57-fold risk of future left ventricular dysfunction when the artificial intelligence-enabled electrocardiogram is positive in the internal validation set. The hazard ratio was increased to 8.67 after excluding the cases with a lower degree of confidence. This trend was also validated in the external validation set. Conclusion The deep learning model with a degree of confidence can provide advanced improvements in identifying left ventricular dysfunction and serve as a decision support and management-guided screening tool for prognosis.

BACKGROUND: The B-type natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (pBNP) are predictors of cardiovascular morbidity and mortality. Since the artificial intelligence (AI)-enabled electrocardiogram (ECG) system is widely used in the management of many cardiovascular diseases (CVDs), patients requiring intensive monitoring may benefit from an AI-ECG with BNP/pBNP predictions. This study aimed to develop an AI-ECG to predict BNP/pBNP and compare their values for future mortality. METHODS: The development, tuning, internal validation, and external validation sets included 47,709, 16,249, 4001, and 6042 ECGs, respectively. Deep learning models (DLMs) were trained using a development set for estimating ECG-based BNP/pBNP (ECG-BNP/ECG-pBNP), and the tuning set was used to guide the training process. The ECGs in internal and external validation sets belonging to nonrepeating patients were used to validate the DLMs. We also followed-up all-cause mortality to explore the prognostic value. RESULTS: The DLMs accurately distinguished mild (≥500 pg/mL) and severe (≥1000 pg/mL) an abnormal BNP/pBNP with AUCs of ≥0.85 in the internal and external validation sets, which provided sensitivities of 68.0–85.0% and specificities of 77.9–86.2%. In continuous predictions, the Pearson correlation coefficient between ECG-BNP and ECG-pBNP was 0.93, and they were both associated with similar ECG features, such as the T wave axis and correct QT interval. ECG-pBNP provided a higher all-cause mortality predictive value than ECG-BNP. CONCLUSIONS: The AI-ECG can accurately estimate BNP/pBNP and may be useful for monitoring the risk of CVDs. Moreover, ECG-pBNP may be a better indicator to manage the risk of future mortality.

AimThis investigation explored the relationship between oral bacteria and metabolic syndrome (METS).Materials and MethodsThere were 4,882 subjects enrolled in this cross-sectional study from the NHANES III database. The severity of periodontitis was classified into mild, moderate and severe. We measured oral bacterial antibodies. We examined the relationship between serum immunoglobulin G (IgG) antibodies of oral bacteria and METS via performing multivariate regression analysis. Mediation analysis of oral bacteria on the correlation between periodontitis and METS was also executed.ResultsAfter adjusting for covariates, the serum IgG antibodies of P. nigrescens, E. corrodens, and E. nodatum were associated with the presence of METS (p = 0.006, p = 0.014 and p = 0.018, respectively). Furthermore, serum IgG antibodies of P. intermedia, T. forsythia and V. parvula were positively associated with the presence of METS (p = 0.001, p = 0.011, and p = 0.002, respectively) and ≥4 features of METS (p = 0.019, p = 0.025, and p = 0.02, respectively). P. intermedia IgG mediated 11.2% of the relationship between periodontitis and METS.ConclusionSerological markers of oral pathogens were correlated with the presence and the number of METS features after multivariable adjustment. Oral bacteria acted as a mediator of the correlation between periodontitis and METS. Our study provided a biologically plausible explanation for the association between periodontitis and METS, which provides a comprehensive evaluation of periodontitis.

BackgroundAlbumin, an important component of fluid balance, is associated with kidney, liver, nutritional, and cardiovascular diseases (CVD) and is measured by blood tests. Since fluid balance is associated with electrocardiography (ECG) changes, we established a deep learning model (DLM) to estimate albumin via ECG.ObjectiveThis study aimed to develop a DLM to estimate albumin via ECG and explored its contribution to future complications.Materials and MethodsA DLM was trained for estimating ECG-based albumin (ECG-Alb) using 155,078 ECGs corresponding to albumin from 79,111 patients, and another independent 13,335 patients from an academic medical center and 11,370 patients from a community hospital were used for internal and external validation. The primary analysis focused on distinguishing patients with mild to severe hypoalbuminemia, and the secondary analysis aimed to provide additional prognostic value from ECG-Alb for future complications, which included mortality, new-onset hypoalbuminemia, chronic kidney disease (CKD), new onset hepatitis, CVD mortality, new-onset acute myocardial infarction (AMI), new-onset stroke (STK), new-onset coronary artery disease (CAD), new-onset heart failure (HF), and new-onset atrial fibrillation (Afib).ResultsThe AUC to identify hypoalbuminemia was 0.8771 with a sensitivity of 56.0% and a specificity of 90.7% in the internal validation set, and the Pearson correlation coefficient was 0.69 in the continuous analysis. The most important ECG features contributing to ECG-Alb were ordered in terms of heart rate, corrected QT interval, T wave axis, sinus rhythm, P wave axis, etc. The group with severely low ECG-Alb had a higher risk of all-cause mortality [hazard ratio (HR): 2.45, 95% CI: 1.81–3.33] and the other hepatorenal and cardiovascular events in the internal validation set. The external validation set yielded similar results.ConclusionHypoalbuminemia and its complications can be predicted using ECG-Alb as a novel biomarker, which may be a non-invasive tool to warn asymptomatic patients.

Abstract Background Longitudinal integrated clerkships (LICs) are a model of clinical education growing rapidly in Western contexts. LICs use educational continuity to benefits students’ clinical learning and professional identity formation. Patient-centered care is a core component of medical professionalism in the West. To support patient-centered care, education leaders in Taiwan restructured clinical education and implemented the first longitudinal integrated clerkship in East Asia. We aimed to investigate patients’ perceptions of longitudinal relationships with the LIC students within Taiwan’s Confucian cultural and social context. Methods We invited patients or their family members who were cared for longitudinally by a LIC student to participate in the study. Participating patients or their family members undertook semi-structured interviews. We analyzed data qualitatively using a general inductive approach to identify themes in the patients’ descriptions of their experiences interacting with the LIC students. Results Twenty-five patients and family members participated in interviews: 16 patients and 9 family members. Qualitative analysis of interview transcripts identified three themes from patients’ experience receiving care from their LIC students: care facilitation, companionship, and empathy. To provide care facilitation, LIC students served as a bridge between the physicians and patients. Students served patients by reminding, consulting, tracking disease progression, and researching solutions for problems. To provide companionship, students accompanied patients interpersonally like a friend or confidant who listens and provides a presence for patients. To provide empathy, patients reported that students showed sincere concern for patients’ experience, feelings, and mood. Conclusion In our study, Taiwanese patients’ perspectives of LIC students suggested the value of care facilitation, companionship, and empathy. We discuss these themes within the context of Confucian culture and the Taiwanese context of care.

BackgroundCertain variables reportedly are associated with a change in left ventricular ejection fraction (LVEF) in heart failure (HF) with reduced ejection fraction (HFrEF). However, literature describing the association between the recovery potential of LVEF and parameters of ventricular remodeling in echocardiography remains sparse.MethodsWe recruited 2,148 HF patients with LVEF < 35%. All patients underwent at least two echocardiographic images. The study aimed to compare LVEF alterations and their association with patient characteristics and echocardiographic findings.ResultsPatients with “recovery” of LVEF (follow-up LVEF ≥ 50%) were less likely to have prior myocardial infarction (MI), had a higher prevalence of atrial fibrillation (Af), were less likely to have diabetes and hypertension, and had a smaller left atrium (LA) diameter, left ventricular end-diastolic diameter (LVEDD) and left ventricular end-systolic diameter (LVESD), both in crude and in adjusted models (adjustment for age and sex). LVEDD cutoff values of 59.5 mm in men and 52.5 mm in women and LVESD cutoff values of 48.5 mm in men and 46.5 mm in women showed a year-to-year increase in the rate of recovery (follow-up LVEF ≥ 50%)/improvement (follow-up LVEF ≥ 35%), p-value < 0.05 in Kaplan–Meier estimates of the cumulative hazard curves.ConclusionsOur study shows that LVEDD and LVESD increments in echocardiography can be predictors of changes in LVEF in in HF patients with LVEF < 35%. They may be used to identify patients who require more aggressive therapeutic interventions.

BackgroundAge-related muscle mass and function decline are critical issues that have gained attention in clinical practice and research. Nevertheless, little is known regarding the time course of muscle health progression, and its determinants during this transition should be estimated.MethodsWe enrolled community-dwelling adults aged ≥65 years during their regular health checkup. The participants’ body composition and muscle function were measured annually from 2015 to 2021. Presarcopenia was characterized by the loss of muscle mass only; dynapenia was defined as low muscle function without changes in muscle mass; and sarcopenia was indicated as a decline in both muscle mass and muscle function. We observed the natural course of muscle health progression during aging. The relationship between muscle health decline and different determinants among old adults was examined.ResultsAmong 568 participants, there was 18.49%, 3.52%, and 1.06% of healthy individuals transited to dynapenia, presarcopenia, and sarcopenia, respectively. Significant positive correlations between age, fat-to-muscle ratio (FMR) and the dynapenia transition were existed [hazard ratio (HR) = 1.08 and HR = 1.73, all p < 0.05]. Serum albumin level had negative correlation with the dynapenia transition risk (HR = 0.30, p = 0.004). Participants with these three risk factors had the highest HR of dynapenia transition compared to those without (HR = 8.67, p = 0.001). A dose-response effect existed between risk factors numbers and the risk of dynapenia transition (p for trend < 0.001). This positive association and dose-response relationship remains after multiple covariates adjustment (HR = 7.74, p = 0.002, p for trend < 0.001). Participants with two or more than two risk factors had a higher risk of dynapenia transition than those with low risk factors (p = 0.0027), and the HR was 1.96 after multiple covariate adjustment (p = 0.029).ConclusionHealthy community-dwelling old adults tended to transit to dynapenia during muscle health deterioration. Individuals with older age, higher FMR, lower albumin level had a higher risk of dynapenia transition; and a positive dose-response effect existed among this population as well.

BackgroundHeart failure (HF) is a global disease with increasing prevalence in an aging society. However, the survival rate is poor despite the patient receiving standard treatment. Early identification of patients with a high risk of HF is important but challenging. Left ventricular end-diastolic diameter (LV-D) increase was an independent risk factor of HF and adverse cardiovascular (CV) outcomes. In this study, we aimed to develop an artificial intelligence (AI) enabled electrocardiogram (ECG) system to detect LV-D increase early.ObjectiveWe developed a deep learning model (DLM) to predict left ventricular end-diastolic and end-systolic diameter (LV-D and LV-S) with internal and external validations and investigated the relationship between ECG-LV-D and echocardiographic LV-D and explored the contributions of ECG-LV-D on future CV outcomes.MethodsElectrocardiograms and corresponding echocardiography data within 7 days were collected and paired for DLM training with 99,692 ECGs in the development set and 20,197 ECGs in the tuning set. The other 7,551 and 11,644 ECGs were collected from two different hospitals to validate the DLM performance in internal and external validation sets. We analyzed the association and prediction ability of ECG-LVD for CV outcomes, including left ventricular (LV) dysfunction, CV mortality, acute myocardial infarction (AMI), and coronary artery disease (CAD).ResultsThe mean absolute errors (MAE) of ECG-LV-D were 5.25/5.29, and the area under the receiver operating characteristic (ROC) curves (AUCs) were 0.8297/0.8072 and 0.9295/0.9148 for the detection of mild (56 ≦ LV-D < 65 mm) and severe (LV-D ≧ 65 mm) LV-D dilation in internal/external validation sets, respectively. Patients with normal ejection fraction (EF) who were identified as high ECHO-LV-D had the higher hazard ratios (HRs) of developing new onset LV dysfunction [HR: 2.34, 95% conference interval (CI): 1.78–3.08], CV mortality (HR 2.30, 95% CI 1.05–5.05), new-onset AMI (HR 2.12, 95% CI 1.36–3.29), and CAD (HR 1.59, 95% CI 1.26–2.00) in the internal validation set. In addition, the ECG-LV-D presents a 1.88-fold risk (95% CI 1.47–2.39) on new-onset LV dysfunction in the external validation set.ConclusionThe ECG-LV-D not only identifies high-risk patients with normal EF but also serves as an independent risk factor of long-term CV outcomes.

Worldwide stroke is increasing in parallel with modernization, changes in lifestyle, and the growing elderly population. Our review is focused on the link between diet, as part of ‘modern lifestyle’, and health in the context of genetic predisposition of individuals to ‘unhealthy’ metabolic pathway activity. It is concluded that lifestyle including high sugar diets, alcohol and tobacco addiction or high fat diets as well as ageing, brain injury, oxidative stress and neuroinflammation, negatively influence the onset, severity and duration of neurodegenerative diseases. Fortunately, there are several healthy dietary components such as polyunsaturated fatty acids and the anti-oxidants curcumin, resveratrol, blueberry polyphenols, sulphoraphane, salvionic acid as well as caloric restriction and physical activity, which may counteract ageing and associated neurodegenerative diseases via increased autophagy or increased neurogenesis in the adult brain.

Background: Moderator effect assessment is important in personalized medicine. We mathematically prove that the average summary value is actually nonlinearly to logRR, and we assess the bias from linear meta-regression on logRR via simulation. Methods: In the meta-analysis of randomized controlled trials, the moderator effect is generally evaluated by the linear meta-regression of the logarithmic risk ratio (RR) versus the average summary value of the entire study population. Conclusions: We recommend using linear meta-regression on logarithmic odds ratio (logOR) since it has been shown that the average summary value is actually linear to logOR.

PurposeGenome-wide association studies have identified numerous genetic variants that are associated with osteoporosis risk; however, most of them are present in the non-coding regions of the genome and the functional mechanisms are unknown. In this study, we aimed to investigate the potential variation in runt domain transcription factor 2 (RUNX2), which is an osteoblast-specific transcription factor that normally stimulates bone formation and osteoblast differentiation, regarding variants within RUNX2 binding sites and risk of osteoporosis in postmenopausal osteoporosis (PMOP).MethodsWe performed bioinformatics-based prediction by combining whole genome sequencing and chromatin immunoprecipitation sequencing to screen functional SNPs in the RUNX2 binding site using data from the database of Taiwan Biobank; Case-control studies with 651 postmenopausal women comprising 107 osteoporosis patients, 290 osteopenia patients, and 254 controls at Tri-Service General Hospital between 2015 and 2019 were included. The subjects were examined for bone mass density and classified into normal and those with osteopenia or osteoporosis by T-scoring with dual-energy X-ray absorptiometry. Furthermore, mRNA expression and luciferase reporter assay were used to provide additional evidence regarding the associations identified in the association analyses. Chi-square tests and logistic regression were mainly used for statistical assessment.ResultsThrough candidate gene approaches, 3 SNPs in the RUNX2 binding site were selected. A novel SNP rs6086746 in the PLCB4 promoter was identified to be associated with osteoporosis in Chinese populations. Patients with AA allele had higher risk of osteoporosis than those with GG+AG (adjusted OR = 6.89; 95% confidence intervals: 2.23–21.31, p = 0.001). Moreover, the AA genotype exhibited lower bone mass density (p < 0.05). Regarding mRNA expression, there were large differences in the correlation between PLCB4 and different RUNX2 alleles (Cohen’s q = 0.91). Functionally, the rs6086746 A allele reduces the RUNX2 binding affinity, thus enhancing the suppression of PLCB4 expression (p < 0.05).ConclusionsOur results provide further evidence to support the important role of the SNP rs6086746 in the etiology of osteopenia/osteoporosis, thereby enhancing the current understanding of the susceptibility to osteoporosis. We further studied the mechanism underlying osteoporosis regulation by PLCB4.

Abstract Background A chronic inflammatory state is a prominent feature in patients with end-stage renal disease (ESRD). Nuclear factor-kappa B (NF-κB) is a transcription factor that regulates the expression of genes involved in inflammation. Some genetic studies have demonstrated that the NF-κB genetic mutation could cause kidney injury and kidney disease progression. However, the association of a gene polymorphism in the transcription factor binding site of NF-κB with kidney disease is not clear. Methods We used the Taiwan Biobank database, the University of California, Santa Cruz, reference genome, and a chromatin immunoprecipitation sequencing database to find single nucleotide polymorphisms (SNPs) at potential binding sites of NF-κB. In addition, we performed a case–control study and genotyped 847 patients with ESRD and 846 healthy controls at Tri-Service General Hospital from 2015 to 2016. Furthermore, we used the ChIP assay to identify the binding activity of different genotypes and used Luciferase reporter assay to examine the function of the rs9395890 polymorphism. Result The results of biometric screening in the databases revealed 15 SNPs with the potential binding site of NF-κB. Genotype distributions of rs9395890 were significantly different in ESRD cases and healthy controls (P = 0.049). The ChIP assay revealed an approximately 1.49-fold enrichment of NF-κB of the variant type TT when compared to that of the wild-type GG in rs9395890 (P = 0.027; TT = 3.20 ± 0.16, GT = 2.81 ± 0.20, GG = 1.71 ± 0.18). The luciferase reporter assay showed that the NF-κB binding site activity in T allele was slightly higher than that in G allele, though it is not significant. Conclusions Our findings indicate that rs9395890 is associated with susceptibility to ESRD in Taiwan population.

Klotho protein is an anti-aging protein and plays multiple roles in ion-regulation, anti-oxidative stress, and energy metabolism through various pathways. Metabolic syndrome is a combination of multiple conditions that compose of multiple risk factors of cardiovascular disease and type 2 diabetes. Gene regulation and protein expression are discovered associated with metabolic syndrome. We aimed to figure out the correlation between Klotho protein and metabolic syndrome in generally healthy adults. A cross-sectional study of 9976 respondents ≥ 18 years old from the US National Health and Nutrition Examination Survey (2007–2012) by utilizing their soluble Klotho protein concentrations. Multivariate linear regression models were used to analyze the effect of soluble Klotho protein on the prevalence of metabolic syndrome. Soluble Klotho protein concentration was inversely correlated with the presence of metabolic syndromes (p = 0.013) and numbers of components that met the definition of metabolic syndrome (p < 0.05). The concentration of Soluble Klotho protein was negatively associated with abdominal obesity and high triglyceride (TG) in the adjusted model (p < 0.05). Soluble Klotho protein is correlated with changing metabolic syndrome components in adults, especially central obesity and high TG levels. Despite conventional function as co-factor with fibroblast growth factor-23 (FGF23) that regulates phosphate and vitamin D homeostasis, FGF23-independent soluble Klotho protein may act on multiple signal pathways in different organs and tissue in roles of anti-aging and protection from metabolic syndrome.

Medical records scoring is important in a health care system. Artificial intelligence (AI) with projection word embeddings has been validated in its performance disease coding tasks, which maintain the vocabulary diversity of open internet databases and the medical terminology understanding of electronic health records (EHRs). We considered that an AI-enhanced system might be also applied to automatically score medical records. This study aimed to develop a series of deep learning models (DLMs) and validated their performance in medical records scoring task. We also analyzed the practical value of the best model. We used the admission medical records from the Tri-Services General Hospital during January 2016 to May 2020, which were scored by our visiting staffs with different levels from different departments. The medical records were scored ranged 0 to 10. All samples were divided into a training set (n = 74,959) and testing set (n = 152,730) based on time, which were used to train and validate the DLMs, respectively. The mean absolute error (MAE) was used to evaluate each DLM performance. In original AI medical record scoring, the predicted score by BERT architecture is closer to the actual reviewer score than the projection word embedding and LSTM architecture. The original MAE is 0.84 ± 0.27 using the BERT model, and the MAE is 1.00 ± 0.32 using the LSTM model. Linear mixed model can be used to improve the model performance, and the adjusted predicted score was closer compared to the original score. However, the project word embedding with the LSTM model (0.66 ± 0.39) provided better performance compared to BERT (0.70 ± 0.33) after linear mixed model enhancement (p < 0.001). In addition to comparing different architectures to score the medical records, this study further uses a mixed linear model to successfully adjust the AI medical record score to make it closer to the actual physician’s score.

Objective: Polycyclic aromatic hydrocarbons (PAHs) are not only natural but also anthropogenic contaminants that exist in many places in the environment. Human beings often accidentally ingest PAHs via smoking. Furthermore, smoking may increase the risk of bowel disorder, including diarrhea and other gastrointestinal problems. Therefore, PAH exposure is hypothesized to be related to diarrhea risk. This study discusses the association between diarrhea and PAH exposure in the United States adult population. Method: 10,537 participants from the National Health and Nutrition Examination Survey (NHANES 2001–2006) were involved in this cross-sectional analysis. Bowel disorders were assessed via examination of stool frequency and stool type. The concentrations of urinary PAH metabolites were used to evaluate PAH exposure. The association between bowel habits and PAH exposure was assessed using a multivariate logistic regression model with covariate assessment of gender, age, race, liver function, kidney function, and common chronic health diseases. Results: All PAH metabolites except 1-hydroxynaphthalene, 1-hydroxypyrene, and 9-hydroxyfluorene were substantially correlated with an increased risk of diarrhea (p < 0.05) after modification of relevant covariables. This study also revealed significant association in the group of females (p < 0.05). Furthermore, all PAH metabolites except 1-hydroxynaphthalene, 2-hydroxyphenanthrene, 1-hydroxypyrene, and 9-hydroxyfluorene show significantly positive association in the non-obesity group (BMI < 30, p < 0.05). Conclusions: PAH exposure is highly associated with risk of bowel disorders among the adult population in the United States, especially in female and non-obesity populations. More research is necessary to shed light on the pathophysiological mechanisms associated to PAH exposure and diarrhea.

Abstract Background In 2010, the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) was developed, based on the concept of the International Classification of Functioning, Disability and Health (ICF). The ICF provides a common language and framework for health and health-related status and attempts to integrate the biopsychosocial model as a multidimensional perspective in understanding functioning. Activities and participation (AP) is one salient component of the ICF refers to the execution of a task by an individual, and how such tasks are involved in their daily life. It is essential to examine the gap between the general adult population and adults with disabilities. This gap may be attributed to health status, personal factors, and natural and social environments, which include social and health services and policies. The purposes: (1) To develop a normative activity and participation (AP) value for the adult population and people with disabilities; and (2) to compare the gap in AP normative values between the two groups in Taiwan. Methods We use the WHODAS 2.0 to survey and develop a normative AP value for the general adult population, and used secondary data from National Disability Eligibility Determination System (NDEDS) of Taiwan to describe the AP functioning distribution of adult with disability. There were 1100 participants, selected by stratified proportional sampling from two cities. There were also 144,850 participants who were adults with disability, selected from the secondary database in Taiwan. Results and conclusions The AP curve for the disabled population increased rapidly at the beginning. The summary score was 13.21 in the performance at 90 percentile for the general population and 82.61 score for disabled adults that the similar gap in every domain, its means that there are significant functioning difference and health equality in general adults population and adults with disabilities. This presents a substantial challenge for both the government and the whole population of Taiwan, to begin considering how to reduce the gap in AP functioning and promote equality for people with disabilities, using social welfare policy. It is important to make sure disabled people have the same rights to be included in society as anybody else and better access to things in all areas of life that are according to Convention on the Rights of Persons with Disabilities (CRPD).

Background: The prevalence of diverticulosis has increased in our aging population, but the risk factors for diverticulosis are not fully understood. The role of hypertension in the risk of diverticulosis remains uncertain. This study investigated whether hypertension is associated with asymptomatic colorectal diverticulosis. Methods: This study enrolled asymptomatic patients who received a colonoscopy as part of a health check. Hypertension was defined by actual measured blood pressure. Logistic regression models were used to examine the relationship between hypertension and diverticulosis. In addition, we established three logistic regression models for covariate adjustment, and further stratified patients with hypertension into three subgroups based on their type of hypertension. Results: The study group consisted of 2748 participants, including 141 participants with diverticulosis and 2607 participants without diverticulosis. After adjustments for potential covariates, the odds ratio (OR) for having diverticulosis was 1.83 (95% confidence interval, 1.21–2.75, p = 0.004) in the hypertension group compared with the group without hypertension. In subgroup analyses, hypertension without antihypertensive medication use, and hypertension despite the use of antihypertensive medication were also significantly associated with the occurrence of asymptomatic diverticulosis (OR = 1.73, p = 0.028; OR = 2.07, p = 0.013, respectively). Current normal blood pressure under antihypertensive drug therapy was not associated with diverticulosis (OR = 1.74, p = 0.092). Conclusions: Our findings suggest a positive association between hypertension and diverticulosis. Participants with poorly controlled blood pressure were found to have a higher risk of asymptomatic diverticulosis. Our study presents epidemiologic evidence for future prevention strategies against diverticulosis.

Metabolic disorders are prevalent worldwide and have recently become public health problems recently. Previous studies have proposed different body composition indices for predicting future cardiovascular risks. We hypothesized an association among fat-to-muscle ratio (FMR), metabolic syndrome (MetS), hypertension (HTN), prediabetes, type 2 diabetes mellitus (DM), and cardiovascular risk in an adult population. A total of 66829 eligible subjects composed of 34182 males and 32647 females aged 20 years or older were obtained from health examinations in the Tri-Service General Hospital from 2011 to 2017. The body composition indices included fat and muscle mass measured by bioelectrical impedance analysis. A multivariable regression model was performed in a large population-based cross-sectional study. FMR was significantly associated with MetS, prediabetes, DM and HTN in all models of both genders. Based on quartile analysis, higher FMR had higher predictive ability for adverse health outcomes. The association between different definitions of MetS and the Framingham risk score was analyzed, and FMR-incorporated MetS was more useful for predicting higher Framingham risk scores than traditional definitions. FMR was a useful indicator for the presence of adverse cardiometabolic risks. Compared to traditional definition of MetS, FMR-incorporated MetS had a greater ability to predict incident cardiovascular risks. FMR seemed to be a simple and effective index for the early prevention and management of cardiometabolic events.

Emerging studies have shed light on the association between Helicobacter pylori (HP) infection and cardiometabolic risk. However, there is no evidence to support a causal link for the relationship in the general population. Our aim was to determine whether HP infection is associated with the risks of incident type II diabetes mellitus (DM) in a population-based cohort consisting of adults from the general population. A total of 69235 adults enrolled in the study obtained health examinations at the Tri-Service General Hospital in Taiwan from 2010 to 2016. HP infection detection was performed by rapid urease tests (RUTs), and endoscopic examinations were used to diagnose gastroesophageal reflux disease (GERD), gastric ulcers (GUs) and duodenal ulcers (DUs). Cross-sectional and longitudinal analyses were performed to examine the association between HP infection and cardiometabolic diseases using logistic regression and Cox regression in a large population-based study. HP infection was significantly associated with the presence of metabolic syndrome (MetS) (OR = 1.26, 95%CI: 1.00-1.57) and DM (OR = 1.59, 95%CI: 1.17-2.17) only in male subjects, and abnormal endoscopic findings were also correlated with cardiometabolic diseases. Our findings demonstrated that participants with HP infection had an elevated risk of developing incident DM (HR = 1.54, 95%CI: 1.11-2.13). In addition, endoscopic findings of a DU (HR = 1.63, 95%CI: 1.02-2.63), rather than GERD or a GU, were also predictive of incident DM. In this cohort, HP infection was a statistically significant predictor of incident DM among male population.

Background: Heart rate variability (HRV) had been promoted for longer than half a century to monitor the activity of autonomic nerve systems. Previous studies have not clarified the relationship between HRV and prehypertension (pre-HTN) status compared with the normal group. We aimed to figure out the optimal model or cutoff point for predicting the possible pre-HTN status. Patients and Methods: We retrospectively collected and reviewed 2586 Asian people who had joined annual physical examination in Tri-Service General Hospital at 2013. The patient profiles such as age, gender, body height, body weight, body weight index, waist circumferences, and serological biochemistry data were analyzed and correlated with HRV parameter. Results: A total number of 909 patients were enrolled in our study. The physical stress index (PSI) owed a small but most significant Spearman's relation coefficient (r = 0.118, P< 0.001) among the other HRV parameters. Statistical significant parameters exist between the normal blood pressure group and pre-HTN group other than gender factor. The measured blood pressure increased with elevated PSI level. A PSI level ≥58.4 has a significant β coefficient in each linear regression model for systolic blood pressure and diastolic blood pressure with a P< 0.001 for trend. Conclusion: The PSI level gains a positive correlation to elevated blood pressure. Our study emphasized that PSI is an efficient HRV parameter which represents higher risks for pre-HTN status and elevated blood pressure while the PSI level is >58.4. Early intervention to these participants may decrease cardiovascular events in the coming future.

Objectives: In this study, we examined the possibility of using targeted antibodies and the potential of small molecular therapeutics (acetylcholine, nicotine and tacrine) to block the pro-inflammatory and adhesion-related properties of monomeric C-reactive protein (mCRP).Methods: We used three established models (platelet aggregation assay, endothelial leucocyte binding assay and monocyte inflammation via ELISA and Western blotting) to assess the potential of these therapeutics.Results: The results of this study showed that monocyte induced inflammation (raised tumor necrosis factor-alpha-TNF-α) induced by mCRP was significantly blocked in the presence of acetylcholine and nicotine, whilst tacrine and targeted antibodies (clones 8C10 and 3H12) had less of or no significant effects. Western blotting confirmed the ability of acetylcholine to inhibit mCRP-induced cell signaling phosphorylation of extracellular signal regulated kinase 1/2 (ERK1/2), p38 and nuclear factor-kappa B (NF-κB). There was no evidence of direct binding between small molecules and mCRP. mCRP also induced endothelial cell-monocyte adhesion in a dose dependent fashion, however, both acetylcholine and nicotine as well as targeting antibodies notably inhibited adhesion. Finally, we investigated their effects on mCRP-induced platelet aggregation. All three small molecules significantly attenuated platelet aggregation as did the antibody 8C10, although 3H12 had a weaker effect.Discussion: Acetylcholine and to a lesser extent nicotine show potential for therapeutic inhibition of mCRP-induced inflammation and cell and platelet adhesion. These results highlight the potential of targeted antibodies and small molecule therapeutics to inhibit the binding of mCRP by prevention of membrane interaction and subsequent activation of cellular cascade systems, which produce the pro-inflammatory effects associated with mCRP.

Circulating C-reactive protein (CRP) is a key acute-phase protein and one of the main clinical biomarkers for inflammation and infection. CRP is an important upstream mediator of inflammation and is associated with the onset of a number of important disease states including cardiovascular disease and neurodegenerative disorders such as Alzheimer’s disease. This pentraxin exerts pro-inflammatory properties via dissociation of the pentamer (pCRP) to a monomeric form (mCRP). This dissociation is induced by binding of pCRP to cell surface phosphocholine residues exposed by the action of phospholipase A2 (PLA2). Given the association of CRP with the onset of a range of serious disease states this CRP dissociation process is a tempting drug target for the development of novel small-molecule therapeutics. This review will discuss potential targets for chemotherapeutic intervention elucidated during studies of CRP-mediated inflammation and provide an up-to-date summary of the development of small molecules, not only targeted directly at inhibiting conversion of pCRP to mCRP, but also those developed for activity against PLA2, given the key role of this enzyme in the activation of CRP.

A growing amount of evidence suggests that thyroid-stimulating hormone (TSH) is associated with cardiometabolic risk. However, there have been few longitudinal studies. The aim of this study was to explore the causal relationship between TSH and metabolic syndrome (MetS) in a large population-based longitudinal study. From 2010 to 2016 at the Health Management Center at Tri-Service General Hospital, 25,121 eligible patients were enrolled in our cross-sectional analyses. Cox proportional hazard models were used to investigate the longitudinal association among hypertension (HTN), prediabetes (pre-DM), MetS, diabetes (DM) and TSH levels (N = 12,463). The average follow-up time was 7.2 years. In the cross-sectional analysis, the OR for MetS was 1.06 (95% CI = 1.03-1.09; P< 0.05), while the ORs for DM, pre-DM or HTN were not statistically significant (all P> 0.05). After dividing TSH levels into four quartiles, the ORs for the presence of MetS determined by comparing the highest TSH quartile with the lowest TSH quartile were 1.37 (95% CI = 1.18-1.60), 1.42 (95% CI = 1.20-1.67), and 1.44 (95% CI = 1.22-1.69) (all, P

Accumulated evidence has suggested associations between glucose abnormalities and insulin resistance with hepatitis C virus (HCV) and hepatitis B virus (HBV) infections. However, few studies have reported the effect of hepatitis virus infections on body composition. Our aim was to explore the association of hepatitis virus infections with percent body fat (PBF) in a cross-sectional analysis. A total of 69226 subjects obtained from the health examinations at Tri-Service General Hospital (TSGH) from 2010 to 2016 were enrolled in the study. Participants were divided into subgroups based on the presence of hepatitis B surface antigen (HBsAg) and anti-HCV. PBF was measured by bioelectrical impedance analysis (BIA). A multivariable linear regression model was applied to test the association of hepatitis virus infections with PBF and glycemic status. In male participants, hepatitis virus infections were closely associated with increased PBF, especially in those subjects with HCV/HBV coinfection. HCV/HBV coinfection was positively correlated with fasting plasma glucose and postprandial glucose while HCV and HBV mono-infection were not. The impact of hepatitis virus infection on increased PBF was observed in general population with gender difference. A further study on the treatment of hepatitis virus infection might help prevent the development of obesity-related diseases.

OBJECTIVE:The effect of obesity-induced metabolic abnormalities on bone mineral density (BMD) and osteoporosis are well established. However, the association between metabolically healthy obesity (MHO) and BMD remains unclear. Our aim was to investigate whether different obesity phenotypes in MHO were associated with BMD in a cross-sectional study. METHODS:All eligible adults receiving a health examination at the Tri-Service General Hospital from 2010 to 2016 were included. They were categorized based on body mass index (BMI) or percentage body fat (PBF). The associations between BMI or PBF and BMD were analyzed by adjusting for pertinent covariables. RESULTS:Males with normal weight and overweight and females with underweight and normal weight were associated with reduced BMD (β = 0.221, 95%CI = -0.354, -0.088; β = -0.155, 95%CI = -0.286, -0.023) (β = -0.736, 95%CI = -1.043, 0.429; β = -0.340, 95%CI = -0.567, -0.112), respectively. Females in Q1 had close to significant associations with reduced BMD (β = -0.253, 95%CI = -0.465, -0.041). Normal weight, overweight, Q2, and Q3 had stronger prediction of low BMD with ORs of 0.402 (95%CI = 0.204-0.791), 0.539 (95%CI = 0.321-0.905), 0.694 (95%CI = 0.490-0.982), and 0.466 (95%CI = 0.342-0.636), respectively. The relationship remained significant in male population that PBF was associated with reduced BMD with ORs of 0.435 (95%CI = 0.203, 0.935), 0.494 (95%CI = 0.247, 0.991), 0.268 (95%CI = 0.120, 0.597) in Q1, Q2, Q3 respectively. CONCLUSION:Increased PBF had a significant association with low BMD in the MHO population. Obesity defined by PBF might be a useful indicator for low BMD. The association between body fat and bone health deserves further investigation regarding the potential pathophysiological mechanisms.

Adverse systemic effect caused by betel nut had been reported for decades. Our aim was to determine whether betel nut had detrimental impact on the development of colorectal polyps in general population. Participants who attended health examinations at the Tri-Service General Hospital (TSGH) from 2010 to 2016 were included in the study. The habit of betel nut chewing was obtained from a self-reported questionnaire. Colorectal polyps were diagnosed by colonoscopies operated by experienced physicians. A logistic regression model was used for the association between betel nut chewing with the presence of colorectal polyps. After adjustment for pertinent information such as age, gender, biochemistry data and personal history, the odd ratios (ORs) of colorectal polyps among betel nut chewers was 1.49 (95%CI: 1.14-1.94). Besides, betel nut chewers in the higher percentage body fat (PBF) group had higher risk for developing colorectal polyps with ORs of 2.07 (95%CI:1.23-3.47). Subjects with habit of betel nut chewing were associated with an increased risk of colorectal polyps in Taiwanese general population. Screening for betel nut chewing history and encouraging cessation might offer improved quality of life. A further research for this association was warranted.

Background: This study analyzes the prognostic factors affecting the survival rate of root-resected molars by using a representative population-based dataset. Materials and Methods: A total of 635,216 eligible patients were enrolled from a representative cohort composed of one million of Taiwan′s population. The tooth-related factors influencing the survival rates of root-resected teeth were examined on 516 molars, in 492 patients. Cox regression was performed to statistically analyze the factors. Results: The overall survival rate for the root-resected molars was 91.7%. Of the analyzed factors with respect to root-resection procedures, whether or not concomitant flap surgery was performed in the medical institutions, the dental arch and tooth location demonstrated a considerable influence on the treatment and decision-making. The main reasons and results of root-resected molars receiving root-resection therapy in hospitals were the periodontal-compromised conditions, whereas, the root-resected molars that received root-resection therapy in private practice clinics were caused by caries/endodontic reasons. After adjusting for other factors, in the outcome of root-resected molars, a higher risk of extraction occurrence was seen in hospitals than in private practice clinics (hazard ratio = 2.03; 95% CI = 1.04 to 3.98; P = 0.039). Conclusions: Of the analyzed prognostic factors, medical institutions significantly affect the treatment decision and survival of root-resected molars. Therefore, a comprehensive evaluation, risk assessment, and treatment plan should be executed before the root-resection procedure is performed.

Background: Purple urine bag syndrome (PUBS), an uncommon phenomenon that turns urine tubes or bags purple or blue, can be encountered in long-term-care facilities. A thorough literature review shows that East Asia has a high incidence of PUBS. It is important to recognize the clinical features and risk factors of this phenomenon. The aim of this study is to explore the characteristics of patients with PUBS and correlate the onset of PUBS symptoms with risk factors. Materials and Methods: We reported nine cases of clinically confirmed PUBS between January 2009 and June 2013. Pertinent clinical information was collected, including age, feeding type, renal function, type of Foley catheter, urine analysis, and bacteriological data. Results: All of patients with PUBS presented with stable vital signs without evidence of clinical infection, such as fever or chills. The mean age of the patients was 86.6 ± 10.1 years, with a preponderance of females (77%). Five PUBS patients (55%) had a history of chronic renal insufficiency. Six patients (66%) had constipation. A logistic regression univariate analysis demonstrated a statistically significant urine pH in patients with PUBS [odds ratio (OR), 3.078; P = 0.036]. Risk factors, such as gender, were found to be significant using logistic regression multivariate analysis (OR, 0.031; P = 0.021). During the follow-up, all of the patients had Foley catheters re-inserted, and all of the patients received health education. Conclusion: The incidence of PUBS in the elderly population is associated with asymptomatic bacteriuria, urine pH, and gender but not renal function, type of feeding, or type of Foley catheter used. To understand PUBS and maintain urological hygiene, it is important to educate families and health care workers about PUBS and to recognize that PUBS is not regarded as a symptom of severe disease.

The potential use of stem cells as therapeutics in disease has gained momentum over the last few years and recently phase-I clinical trials have shown favourable results in treatment of a small cohort of acute stroke patients. Similarly, they have been used in preclinical models drug-loaded for the effective treatment of solid tumours. Here we have characterized uptake and release of a novel p5-cyclin-dependent kinase 5 (CDK5) inhibitory peptide by mesenchymal stem cells and showed release levels capable of blocking aberrant cyclin-dependent kinase 5 (CDK5) signaling pathways, through phosphorylation of cyclin-dependent kinase 5 (CDK5) and p53. These pathways represent the major acute mechanism stimulating apoptosis after stroke and hence its modulation could benefit patient recovery. This work indicates a potential use for drug-loaded stem cells as delivery vehicles for stroke therapeutics and in addition as anticancer receptacles particularly, if a targeting and/or holding mechanism can be defined.