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Background Optimal timing for initiating maintenance dialysis in patients with chronic kidney disease (CKD) stages 3–5 is challenging. This study aimed to develop and validate a machine learning (ML) model for early personalised prediction of maintenance dialysis initiation within 1-year and 3-year timeframes among patients with CKD stages 3–5.Methods Retrospective electronic health record data from the Taipei Medical University clinical research database were used. Newly diagnosed patients with CKD stages 3–5 between 2008 and 2017 were identified. The observation period spanned from the diagnosis of CKD stages 3–5 until the maintenance dialysis initiation or a maximum follow-up of 3 years. Predictive models were developed using patient demographics, comorbidities, laboratory data and medications. The dataset was divided into training and testing sets to ensure robust model performance. Model evaluation metrics, including area under the curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value and F1 score, were employed.Results A total of 6123 and 5279 patients were included for 1 year and 3 years of the model development. The artificial neural network demonstrated better performance in predicting maintenance dialysis initiation within 1 year and 3 years, with AUC values of 0.96 and 0.92, respectively. Important features such as baseline estimated glomerular filtration rate and albuminuria significantly contributed to the predictive model.Conclusion This study demonstrates the efficacy of an ML approach in developing a highly predictive model for estimating the timing of maintenance dialysis initiation in patients with CKD stages 3–5. These findings have important implications for personalised treatment strategies, enabling improved clinical decision-making and potentially enhancing patient outcomes.

Objective The objective of this paper is to provide a comprehensive overview of the development and features of the Taipei Medical University Clinical Research Database (TMUCRD), a repository of real-world data (RWD) derived from electronic health records (EHRs) and other sources.Methods TMUCRD was developed by integrating EHRs from three affiliated hospitals, including Taipei Medical University Hospital, Wan-Fang Hospital and Shuang-Ho Hospital. The data cover over 15 years and include diverse patient care information. The database was converted to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) for standardisation.Results TMUCRD comprises 89 tables (eg, 29 tables for each hospital and 2 linked tables), including demographics, diagnoses, medications, procedures and measurements, among others. It encompasses data from more than 4.15 million patients with various medical records, spanning from the year 2004 to 2021. The dataset offers insights into disease prevalence, medication usage, laboratory tests and patient characteristics.Discussion TMUCRD stands out due to its unique advantages, including diverse data types, comprehensive patient information, linked mortality and cancer registry data, regular updates and a swift application process. Its compatibility with the OMOP CDM enhances its usability and interoperability.Conclusion TMUCRD serves as a valuable resource for researchers and scholars interested in leveraging RWD for clinical research. Its availability and integration of diverse healthcare data contribute to a collaborative and data-driven approach to advancing medical knowledge and practice.

The molecular and genetic mechanisms underlying left atrial (LA) enlargement and atrial fibrosis following right ventricular (RV) dependent pacing remain unclear. Our objective was to investigate genetic expressions in the LA of pigs subjected to RV pacing for atrioventricular block (AVB), as well as to identify the differential gene expressions affected by biventricular (BiV) pacing. We established an AVB pig model and divided the subjects into three groups: a sham control group, an RV pacing group, and a BiV pacing group. Differential expression genes (DEGs) analyses conducted through next-generation sequencing (NGS) and enrichment analyses were employed to identify genes with altered expression in the LA myocardium. The RV pacing group showed a significant increase in extracellular fibrosis in the LA myocardium compared to the control group. NGS analysis revealed suppressed expression of the sirtuin signaling pathway in the RV pacing group. Among the DEGs within this pathway, GADD45G was found to be downregulated in the RV pacing group and upregulated in the BiV pacing group. Remarkably, the BiV pacing group exhibited elevated levels of GADD45G protein. In our study, we observed significant downregulation of SIRT1 and GADD45G genes, which are associated with the sirtuin signaling pathway, in the LA myocardium of the RV pacing group when compared to the control group. Moreover, these genes, which were downregulated in the RV pacing group, displayed a noteworthy upregulation in the BiV pacing group when compared to the RV pacing group.

Abstract Background MicroRNAs are a group of small non-coding RNAs that are involved in development and diseases such as cancer. Previously, we demonstrated that miR-335 is crucial for preventing collagen type XI alpha 1 (COL11A1)-mediated epithelial ovarian cancer (EOC) progression and chemoresistance. Here, we examined the role of miR-509-3p in EOC. Methods The patients with EOC who underwent primary cytoreductive surgery and postoperative platinum-based chemotherapy were recruited. Their clinic-pathologic characteristics were collected, and disease-related survivals were determined. The COL11A1 and miR-509-3p mRNA expression levels of 161 ovarian tumors were determined by real-time reverse transcription-polymerase chain reaction. Additionally, miR-509-3p hypermethylation was evaluated by sequencing in these tumors. The A2780CP70 and OVCAR-8 cells transfected with miR-509-3p mimic, while the A2780 and OVCAR-3 cells transfected with miR-509-3p inhibitor. The A2780CP70 cells transfected with a small interference RNA of COL11A1, and the A2780 cells transfected with a COL11A1 expression plasmid. Site-directed mutagenesis, luciferase, and chromatin immunoprecipitation assays were performed in this study. Results Low miR-509-3p levels were correlated with disease progression, a poor survival, and high COL11A1 expression levels. In vivo studies reinforced these findings and indicated that the occurrence of invasive EOC cell phenotypes and resistance to cisplatin are decreased by miR-509-3p. The miR-509-3p promoter region (p278) is important for miR-509-3p transcription regulation via methylation. The miR-509-3p hypermethylation frequency was significantly higher in EOC tumors with a low miR-509-3p expression than in those with a high miR-509-3p expression. The patients with miR-509-3p hypermethylation had a significantly shorter overall survival (OS) than those without miR-509-3p hypermethylation. Mechanistic studies further indicated that miR-509-3p transcription was downregulated by COL11A1 through a DNA methyltransferase 1 (DNMT1) stability increase. Moreover, miR-509-3p targets small ubiquitin-like modifier (SUMO)-3 to regulate EOC cell growth, invasiveness, and chemosensitivity. Conclusion The miR-509-3p/DNMT1/SUMO-3 axis may be an ovarian cancer treatment target.

Background and Objectives: Left ventricular hypertrophy (LVH) represents a significant cardiovascular risk in patients undergoing chronic hemodialysis (CHD). A large inferior vena cava diameter (IVCD), potentially indicative of fluid overload and a contributing factor to elevated cardiovascular risk, has not been sufficiently explored. Therefore, our study aims to gain further insights into this aspect. Materials and Methods: A retrospective cohort study enrolled patients receiving CHD in a single medical center with available echocardiography from October to December 2018. They were categorized into four groups based on LVH geometry and IVCD. Cox proportional hazard models assessed the risk of major adverse cardiovascular effects (MACEs) and cardiovascular and overall mortality after multivariate adjustments. Kaplan–Meier analysis depicted MACE-free events and survival during the follow-up time. Results: Of the 175 CHD patients, 38, 42, 45, and 50 exhibited small IVCD with eccentric and concentric LVH and large IVCD with eccentric and concentric LVH, respectively. Compared to small IVCD and eccentric LVH, large IVCD and eccentric LVH had the highest risk of MACEs, followed by large IVCD and concentric LVH (aHR: 4.40, 3.60; 95% CI: 1.58–12.23, 1.28–10.12, respectively). As for cardiovascular mortality, large IVCD and concentric LVH had the highest risk, followed by large IVCD and eccentric LVH, and small IVCD and concentric LVH. (aHR: 14.34, 10.23, 8.87; 95% CI: 1.99–103.35, 1.41–74.33; 1.01–77.87). The trend in overall mortality risk among the groups was similar to that of cardiovascular mortality. Conclusions: LVH geometry and IVCD co-modify the risk of MACEs and cardiovascular and overall mortality in CHD patients. The highest risk of MACEs is associated with large IVCD and eccentric LVH, while the highest risk of cardiovascular and overall mortality is linked with large IVCD and concentric LVH.

Abstract Odontogenic rhinosinusitis is a subtype of rhinosinusitis associated with dental infection or dental procedures and has special bacteriologic features. Previous research on the bacteriologic features of odontogenic rhinosinusitis has mainly used culture-dependent methods. The variation of microbiota between odontogenic and nonodontogenic rhinosinusitis as well as the interplay between the involved bacteria have not been explored. Therefore, we enrolled eight odontogenic rhinosinusitis cases and twenty nonodontogenic rhinosinusitis cases to analyze bacterial microbiota through 16S rRNA sequencing. Significant differences were revealed by the Shannon diversity index (Wilcoxon test p = 0.0003) and PERMANOVA test based on weighted UniFrac distance (Wilcoxon test p = 0.001) between odontogenic and nonodontogenic samples. Anaerobic bacteria such as Porphyromonas, Fusobacterium, and Prevotella were significantly dominant in the odontogenic rhinosinusitis group. Remarkably, a correlation between different bacteria was also revealed by Pearson’s correlation. Staphylococcus was highly positively associated with Corynebacterium, whereas Fusobacterium was highly negatively correlated with Prophyromonas. According to our results, the microbiota in odontogenic rhinosinusitis, predominantly anaerobic bacteria, was significantly different from that in nonodontogenic rhinosinusitis, and the interplay between specific bacteria may a major cause of this subtype of rhinosinusitis.

Abstract The outcome of acute kidney injury (AKI) as a result of aminoglycosides (AGs) use remains uncertain in patients without prior chronic kidney disease (CKD). Therefore, we explored the outcomes of AGs use on AKI episodes associated with renal recovery and progress in patients without prior CKD in Taiwan. This was a retrospective cohort study by using the Taipei Medical University Research Database from January 2008 to December 2019. 43,259 individuals without CKD who had received parenteral AGs were enrolled. The exposed and unexposed groups underwent propensity score matching for age, gender, patients in intensive care unit/emergency admission, and covariates, except serum hemoglobin and albumin levels. We identified an exposed group of 40,547 patients who used AGs (median age, 54.4 years; 44.3% male) and an unexposed group of 40,547 patients without AG use (median age, 55.7 years; 45.5% male). There was the risk for AKI stage 1 (adjusted hazard ratio [HR] 1.34; 95% confidence interval [CI] 1.00–1.79; p = 0.05) in patients that used AGs in comparison with the control subjects. Moreover, patients using AGs were significantly associated neither with the progression to acute kidney disease (AKD) stages nor with the progression to end-stage renal disease (ESRD) on dialysis. Further analyzed, there was an increased risk of AKI episodes for serum albumin levels less than 3.0 g/dL and hemoglobin levels less than 11.6 g/dL. Among patients without prior CKD, AGs-used individuals were associated with AKI risks, especially those at relatively low albumin (

Abstract Background Approximately 25% of patients with early-stage breast cancer experience cancer progression throughout the disease course. Alterations in TMEM240 in breast cancer were identified and investigated to monitor treatment response and disease progression. Methods Circulating methylated TMEM240 in the plasma of breast cancer patients was used to monitor treatment response and disease progression. The Cancer Genome Atlas (TCGA) data in Western countries and Illumina methylation arrays in Taiwanese breast cancer patients were used to identify novel hypermethylated CpG sites and genes related to poor hormone therapy response. Quantitative methylation-specific PCR (QMSP), real-time reverse transcription PCR, and immunohistochemical analyses were performed to measure DNA methylation and mRNA and protein expression levels in 394 samples from Taiwanese and Korean breast cancer patients. TMEM240 gene manipulation, viability, migration assays, RNA-seq, and MetaCore were performed to determine its biological functions and relationship to hormone drug treatment response in breast cancer cells. Results Aberrant methylated TMEM240 was identified in breast cancer patients with poor hormone therapy response using genome-wide methylation analysis in the Taiwan and TCGA breast cancer cohorts. A cell model showed that TMEM240, which is localized to the cell membrane and cytoplasm, represses breast cancer cell proliferation and migration and regulates the expression levels of enzymes involved in estrone and estradiol metabolism. TMEM240 protein expression was observed in normal breast tissues but was not detected in 88.2% (67/76) of breast tumors and in 90.0% (9/10) of metastatic tumors from breast cancer patients. QMSP revealed that in 54.5% (55/101) of Taiwanese breast cancer patients, the methylation level of TMEM240 was at least twofold higher in tumor tissues than in matched normal breast tissues. Patients with hypermethylation of TMEM240 had poor 10-year overall survival (p = 0.003) and poor treatment response, especially hormone therapy response (p

Abstract Background and Purpose Although cytotoxic platinum‐based adjuvant chemotherapy (pACT) has been recommended for patients with completely resected early‐stage (ES) non–small‐cell lung cancer (ES‐NSCLC), therapeutic regimens for NSCLC have evolved in the past two decades. The study was aimed to examine the effectiveness of postoperative pACT for resected ES‐NSCLC patients with squamous cell carcinoma (SCC) or adenocarcinoma (ADC) according to real‐world data. Methods and Patients Inverse probability treatment weighting (IPTW) was used to adjust baseline characteristics between the group receiving pACT and those not receiving any treatment (observation, OBS) within 3 months after curative surgery. Cox regression models were used to compare overall survival (OS) and treatment failure‐free survival (TFS) between the groups. Results Of 31,208 patients with ES‐NSCLC, 4700 undergoing complete tumor resection were eligible, with a mean follow‐up period of 4.5 years. The pACT (n = 2347) and OBS (n = 2353) groups were well‐balanced after IPTW. The median OS differed between the pACT and OBS groups (77.2 vs. 75.5 months, adjusted hazard ratio [aHR] = 0.87, 95% confidence interval [CI] = 0.79–0.95, p = 0.003), and the 5‐year survival rates were 58.2% and 55.3%, respectively (p

Background: Mobile phones, laptops, and computers have become an indispensable part of our lives in recent years. Workers may have an incorrect posture when using a computer for a prolonged period of time. Using these products with an incorrect posture can lead to neck pain. However, there are limited data on postures in real-life situations. Methods: In this study, we used a common camera to record images of subjects carrying out three different tasks (a typing task, a gaming task, and a video-watching task) on a computer. Different artificial intelligence (AI)-based pose estimation approaches were applied to analyze the head’s yaw, pitch, and roll and coordinate information of the eyes, nose, neck, and shoulders in the images. We used machine learning models such as random forest, XGBoost, logistic regression, and ensemble learning to build a model to predict whether a subject had neck pain by analyzing their posture when using the computer. Results: After feature selection and adjustment of the predictive models, nested cross-validation was applied to evaluate the models and fine-tune the hyperparameters. Finally, the ensemble learning approach was utilized to construct a model via bagging, which achieved a performance with 87% accuracy, 92% precision, 80.3% recall, 95.5% specificity, and an AUROC of 0.878. Conclusions: We developed a predictive model for the identification of non-specific neck pain using 2D video images without the need for costly devices, advanced environment settings, or extra sensors. This method could provide an effective way for clinically evaluating poor posture during real-world computer usage scenarios.

Metabolic syndrome (MetS) includes several conditions that can increase an individual’s predisposition to high-risk cardiovascular events, morbidity, and mortality. Non-alcoholic fatty liver disease (NAFLD) is a predominant cause of cirrhosis, which is a global indicator of liver transplantation and is considered the hepatic manifestation of MetS. FibroScan® provides an accurate and non-invasive method for assessing liver steatosis and fibrosis in patients with NAFLD, via a controlled attenuation parameter (CAP) and liver stiffness measurement (LSM or E) scores and has been widely used in current clinical practice. Several machine learning (ML) models with a recursive feature elimination (RFE) algorithm were applied to evaluate the importance of the CAP score. Analysis by ANOVA revealed that five symptoms at different CAP and E score levels were significant. All eight ML models had accuracy scores > 0.9, while treebags and random forest had the best kappa values (0.6439 and 0.6533, respectively). The CAP score was the most important variable in the seven ML models. Machine learning models with RFE demonstrated that using the CAP score to identify patients with MetS may be feasible. Thus, a combination of CAP scores and other significant biomarkers could be used for early detection in predicting MetS.

Background/purpose: Metabolites in blood have been found associated with the occurrence of vascular diseases, but its role in the functional recovery of stroke is unclear. The aim of this study is to investigate whether the untargeted metabolomics at the acute stage of ischemic stroke is able to predict functional recovery. Methods: One hundred and fifty patients with acute ischemic stroke were recruited and followed up for 3 months. Fasting blood samples within 7 days of stroke were obtained, liquid chromatography and mass spectrometry were applied to identify outcome-associated metabolites. The patients’ clinical characteristics and identified metabolites were included for constructing the outcome prediction model using machine learning approaches. Results: By using multivariate analysis, 220 differentially expressed metabolites (DEMs) were discovered between patients with favorable outcomes (modified Rankin Scale, mRS ≤ 2 at 3 months, n = 77) and unfavorable outcomes (mRS ≥ 3 at 3 months, n = 73). After feature selection, 63 DEMs were chosen for constructing the outcome prediction model. The predictive accuracy was below 0.65 when including patients' clinical characteristics, and could reach 0.80 when including patients' clinical characteristics and 63 selected DEMs. The functional enrichment analysis identified platelet activating factor (PAF) as the strongest outcome-associated metabolite, which involved in proinflammatory mediators release, arachidonic acid metabolism, eosinophil degranulation, and production of reactive oxygen species. Conclusion: Metabolomics is a potential method to explore the blood biomarkers of acute ischemic stroke. The patients with unfavorable outcomes had a lower PAF level compared to those with favorable outcomes.

ABSTRACT Enterococcus faecium is a clinically important pathogen that can cause significant morbidity and death. In this study, we aimed to develop a machine learning (ML) algorithm-based rapid susceptibility method to distinguish vancomycin-resistant E. faecium (VREfm) and vancomycin-susceptible E. faecium (VSEfm) strains. A predictive model was developed and validated to distinguish VREfm and VSEfm strains by analyzing the matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry (MS) spectra of unique E. faecium isolates from different specimen types. The algorithm used 5,717 mass spectra, including 2,795 VREfm and 2,922 VSEfm mass spectra, and was externally validated with 2,280 mass spectra of isolates (1,222 VREfm and 1,058 VSEfm strains). A random forest-based algorithm demonstrated overall good classification performances for the isolates from the specimens, with mean accuracy, sensitivity, and specificity of 0.78, 0.79, and 0.77, respectively, with 10-fold cross-validation, timewise validation, and external validation. Furthermore, the algorithm provided rapid results, which would allow susceptibility prediction prior to the availability of phenotypic susceptibility results. In conclusion, an ML algorithm designed using mass spectra obtained from the routine workflow may be able to rapidly differentiate VREfm strains from VSEfm strains; however, susceptibility results must be confirmed by routine methods, given the demonstrated performance of the assay. IMPORTANCE A modified binning method was incorporated to cluster MS shifting ions into a set of representative peaks based on a large-scale MS data set of clinical VREfm and VSEfm isolates, including 2,795 VREfm and 2,922 VSEfm isolates. Predictions with the algorithm were significantly more accurate than empirical antibiotic use, the accuracy of which was 0.50, based on the local epidemiology. The algorithm improved the accuracy of antibiotic administration, compared to empirical antibiotic prescription. An ML algorithm designed using MALDI-TOF MS spectra obtained from the routine workflow accurately differentiated VREfm strains from VSEfm strains, especially in blood and sterile body fluid samples, and can be applied to facilitate the rapid and accurate clinical testing of pathogens.

Abstract Background Weight‐reduction therapies, including bariatric surgery (BS), are standard treatments for severely obese patients with type 2 diabetes; however, the outcomes of these therapies are inconclusive for obese patients with chronic kidney disease (CKD). This study aimed to investigate the effects of BS or non‐surgical interventions on the estimated glomerular filtration rate (eGFR) and to determine whether BS can be recommended for renal function preservation based on body mass index (BMI) and eGFR changes in obese patients with CKD. Methods This study used data from the weight Reduction Intervention on GFR in Obese Patients with Renal Impairment‐Taipei Medical University (TMU) study, which was a large, long‐term, propensity score‐matched cohort study based on clinical data from patients who registered at weight‐reduction centres at TMU and its affiliated hospitals from 2008 to 2016. The patients were stratified according to whether they had undergone BS and into the mild, moderate, and high CKD risk groups using the Kidney Disease: Improving Global Outcomes guidelines. The primary outcome was the eGFR calculated using the Taiwan Chronic Kidney Disease‐Epidemiology Collaboration equation. Cox regression models were used to determine hazard ratios (HRs) for eGFR decreases ≥25%. Results A total of 4332 obese patients were enrolled in this study. After propensity score matching, 1620 patients, including 60.2% women, with a mean age of 36.5 (9.9) years were divided into BS or non‐surgery groups (n = 810 per group). The overall mean eGFRs increased by 4.4 (14) mL/min·1.73 m2 and decreased by 6.4 (16.0) mL/min·1.73 m2 in the BS and non‐surgery groups, respectively. The decrease in BMI in the BS and non‐surgery groups were 2.5 and 1.3 kg/m2, respectively. In the moderate/high CKD risk BS group, a significant correlation was evident between an increased eGFR and a reduced BMI (Spearman's correlation −0.229, P < 0.001). The Cox regression analysis showed that the BS group had a significantly lower risk of an eGFR decline ≥25% at 12 months [adjusted HR (aHR) 0.47, P = 0.03). After BS, obese patients with hypertension or albuminuria had significantly lower risks of eGFR declines ≥25% (aHR 0.37, P = 0.02 and aHR 0.13, P = 0.0018, respectively). Conclusions Bariatric surgery was associated with eGFR preservation in all obese patients and, particularly, in those with moderate‐to‐high CKD risks. A longer term outcome study is warranted to determine the benefits of BS for CKD patients.

Abstract Background Recent studies have proposed several gene signatures as biomarkers for different grades of gliomas from various perspectives. However, most of these genes can only be used appropriately for patients with specific grades of gliomas. Methods In this study, we aimed to identify survival-relevant genes shared between glioblastoma multiforme (GBM) and lower-grade glioma (LGG), which could be used as potential biomarkers to classify patients into different risk groups. Cox proportional hazard regression model (Cox model) was used to extract relative genes, and effectiveness of genes was estimated against random forest regression. Finally, risk models were constructed with logistic regression. Results We identified 104 key genes that were shared between GBM and LGG, which could be significantly correlated with patients’ survival based on next-generation sequencing data obtained from The Cancer Genome Atlas for gene expression analysis. The effectiveness of these genes in the survival prediction of GBM and LGG was evaluated, and the average receiver operating characteristic curve (ROC) area under the curve values ranged from 0.7 to 0.8. Gene set enrichment analysis revealed that these genes were involved in eight significant pathways and 23 molecular functions. Moreover, the expressions of ten (CTSZ, EFEMP2, ITGA5, KDELR2, MDK, MICALL2, MAP 2 K3, PLAUR, SERPINE1, and SOCS3) of these genes were significantly higher in GBM than in LGG, and comparing their expression levels to those of the proposed control genes (TBP, IPO8, and SDHA) could have the potential capability to classify patients into high- and low- risk groups, which differ significantly in the overall survival. Signatures of candidate genes were validated, by multiple microarray datasets from Gene Expression Omnibus, to increase the robustness of using these potential prognostic factors. In both the GBM and LGG cohort study, most of the patients in the high-risk group had the IDH1 wild-type gene, and those in the low-risk group had IDH1 mutations. Moreover, most of the high-risk patients with LGG possessed a 1p/19q-noncodeletion. Conclusion In this study, we identified survival relevant genes which were shared between GBM and LGG, and those enabled to classify patients into high- and low-risk groups based on expression level analysis. Both the risk groups could be correlated with the well-known genetic variants, thus suggesting their potential prognostic value in clinical application.

Background Dual antiplatelet therapy (DAPT) is currently the standard treatment for the prevention of ischemic events after stent implantation. However, the optimal DAPT duration remains elusive for patients with chronic kidney disease (CKD). Therefore, we aimed to compare the effectiveness and safety between long-term and short-term DAPT after coronary stenting in patients with CKD. Methods This retrospective cohort study analyze data from the Taipei Medical University (TMU) Institutional and Clinical Database, which include anonymized electronic health data of 3 million patients that visited TMU Hospital, Wan Fang Hospital, and Shuang Ho Hospital. We enrolled patients with CKD after coronary stenting between 2008 and 2019. The patients were divided into the long-term (>6 months) and short-term DAPT group (≤ 6 months). The primary end point was major adverse cardiovascular events (MACE) from 6 months after the index date. The secondary outcomes were all-cause mortality and Thrombolysis in Myocardial Infarction (TIMI) bleeding. Results A total of 1899 patients were enrolled; of them, 1112 and 787 were assigned to the long-term and short-term DAPT groups, respectively. Long-term DAPT was associated with similar risk of MACE (HR: 1.05, 95% CI: 0.65–1.70, P = 0.83) compare with short-term DAPT. Different CKD risk did not modify the risk of MACE. There was also no significant difference in all-cause mortality (HR: 1.10, 95% CI: 0.75–1.61, P = 0.63) and TIMI bleeding (HR 1.19, 95% CI: 0.86–1.63, P = 0.30) between groups. Conclusions Among patients with CKD and coronary stenting, we found that long-term and short-term DAPT tied on the risk of MACE, all-cause mortality and TIMI bleeding.

PurposeTo compare the risk of neurodevelopmental disorders in children conceived via intracytoplasmic sperm injection (ICSI) and those conceived naturally.Materials and methodsA population-based cohort study using data retrieved from the Taipei Medical University Research Database (TMURD) from January, 2004 to August, 2016. The data included maternal pregnancy history, perinatal history and developmental follow up of their babies up to 5 years of age. The study included 23885 children, of whom 23148 were naturally conceived and 737 were conceived via ICSI. Neurodevelopmental disorders defined by 21 ICD-9-CM codes.ResultsOf the 23885 children enrolled for analysis, 2778 children were included for further subgrouping analysis after propensity matching to reduce bias from maternal factors. The single-birth group included 1752 naturally conceived (NC) children and 438 ICSI children. The multiple-birth group included 294 NC and 294 ICSI children. The risk of neurodevelopmental disorders was not increased for ICSI children in both groups (single birth: adjusted hazard ratio aHR = 0.70, 95% CI = 0.39-1.27, p = 0.243; multiple-birth group aHR = 0.77, 95% CI = 0.43-1.35, p = 0.853). In the single-birth group, multivariate analyses showed that male sex (aHR = 1.81, 95% CI = 1.29-2.54, p < 0.001), and intensive care unit (ICU) admission (aHR = 3.10, 95% CI = 1.64-5.86, p < 0.001) were risk factors for neurodevelopmental disorders. In the multiple-birth group, multivariate analyses demonstrated that ICU admission (aHR = 3.58, 95% CI = 1.82-7.04, p < 0.001), was risk factor for neurodevelopmental disorders.ConclusionOur study indicated that the use of ICSI does not associated with higher risk of neurodevelopmental disorders in the offspring. But male sex, and ICU admission do have increased risk of neurodevelopmental disorders. However, long term follow up of this cohort on health outcomes in adolescence and adulthood will strengthen the conclusions that ICSI is safe regarding offspring long term outcome.

Objectives To investigate the effect of the Early Chronic Kidney Disease (CKD) Care Programme on CKD progression in patients with CKD stage I–IIIa.Design Observational cohort study.Setting Taipei Medical University Research Database from three affiliated hospitals.Participants Adult non-pregnant patients with CKD stage I–IIIa from Taipei Medical University Research Database between 1 January 2012 and 31 August 2017 were recruited. These patients were divided into Early CKD Care Programme participants (case) and non-participants (control). The models were matched by age, sex, estimated glomerular filtration rate and CKD stage with 1:2 propensity score to reduce bias between two groups.Outcome measures The risks of CKD stage I–IIIa progression to IIIb between Early CKD Care Programme participants and non-participants.Results Compared with the control group, the case group demonstrated more comorbidities and higher proportions of hypertension, diabetes mellitus, gout, dyslipidaemia, heart disease and cerebrovascular disease, but had lower risk of progression to CKD stage IIIb before and (HR 0.72; 95% CI 0.61 to 0.85) and after (adjusted HR (aHR) 0.67; 95% CI 0.55 to 0.81) adjustments. Moreover, Kaplan-Meier analysis revealed the cumulative incidence of CKD stage IIIb was significantly lower in the case group than in the control group. Finally, the programme was an independent protective factor against progression to stage IIIb, especially in patients with CKD stage IIIa before (HR 0.72; 95% CI 0.61 to 0.85) and after (aHR 0.67; 95% CI 0.55 to 0.81) adjustments.Conclusions The Early CKD Care Programme is an independent protective factor against progression of early CKD.

Abstract Background One of the most common and recurrent vaginal infections is bacterial vaginosis (BV). The diagnosis is based on changes to the “normal” vaginal microbiome; however, the normal microbiome appears to differ according to reproductive status and ethnicity, and even among individuals within these groups. The Amsel criteria and Nugent score test are widely used for diagnosing BV; however, these tests are based on different criteria, and so may indicate distinct changes in the vaginal microbial community. Nevertheless, few studies have compared the results of these test against metagenomics analysis. Methods Vaginal flora samples from 77 participants were classified according to the Amsel criteria and Nugent score test. The microbiota composition was analyzed using 16S ribosome RNA gene amplicon sequencing. Bioinformatics analysis and multivariate statistical analysis were used to evaluate the microbial diversity and function. Results Only 3 % of the participants diagnosed BV negative using the Amsel criteria (A−) were BV-positive according to the Nugent score test (N+), while over half of the BV-positive patients using the Amsel criteria (A+) were BV-negative according to the Nugent score test (N−). Thirteen genera showed significant differences in distribution among BV status defined by BV tests (e.g., A − N−, A + N− and A + N+). Variations in the four most abundant taxa, Lactobacillus, Gardnerella, Prevotella, and Escherichia, were responsible for most of this dissimilarity. Furthermore, vaginal microbial diversity differed significantly among the three groups classified by the Nugent score test (N−, N+, and intermediate flora), but not between the Amsel criteria groups. Numerous predictive microbial functions, such as bacterial chemotaxis and bacterial invasion of epithelial cells, differed significantly among multiple BV test, but not between the A− and A+ groups. Conclusions Metagenomics analysis can greatly expand our current understanding of vaginal microbial diversity in health and disease. Metagenomics profiling may also provide more reliable diagnostic criteria for BV testing.

Recurrence and poorly differentiated (grade 3 and above) and atypical cell type endometrial cancer (EC) have poor prognosis outcome. The mechanisms and characteristics of recurrence and distal metastasis of EC remain unclear. The extracellular matrix (ECM) of the reproductive tract in women undergoes extensive structural remodelling changes every month. Altered ECMs surrounding cells were believed to play crucial roles in a cancer progression. To decipher the associations between ECM and EC development, we generated a PAN-ECM Data list of 1516 genes including ECM molecules (ECMs), synthetic and degradation enzymes for ECMs, ECM receptors, and soluble molecules that regulate ECM and used RNA-Seq data from The Cancer Genome Atlas (TCGA) for the studies. The alterations of PAN-ECM genes by comparing the RNA-Seq expressions profiles of EC samples which have been grouped as tumorigenesis and metastasis group based on their pathological grading were identified. Differential analyses including functional enrichment, co-expression network, and molecular network analysis were carried out to identify the specific PAN-ECM genes that may involve in the progression of EC. Eight hundred and thirty-one and 241 PAN-ECM genes were significantly involved in tumorigenesis (p-value

Introduction: In the United States and Europe, endometrial endometrioid carcinoma (EEC) is the most prevalent gynecologic malignancy. Lymph node metastasis (LNM) is the key determinant of the prognosis and treatment of EEC. A biomarker that predicts LNM in patients with EEC would be beneficial, enabling individualized treatment. Current preoperative assessment of LNM in EEC is not sufficiently accurate to predict LNM and prevent overtreatment. This pilot study established a biomarker signature for the prediction of LNM in early stage EEC.Methods: We performed RNA sequencing in 24 clinically early stage (T1) EEC tumors (lymph nodes positive and negative in 6 and 18, respectively) from Cathay General Hospital and analyzed the RNA sequencing data of 289 patients with EEC from The Cancer Genome Atlas (lymph node positive and negative in 33 and 256, respectively). We analyzed clinical data including tumor grade, depth of tumor invasion, and age to construct a sequencing-based prediction model using machine learning. For validation, we used another independent cohort of early stage EEC samples (n = 72) and performed quantitative real-time polymerase chain reaction (qRT-PCR). Finally, a PCR-based prediction model and risk score formula were established.Results: Eight genes (ASRGL1, ESR1, EYA2, MSX1, RHEX, SCGB2A1, SOX17, and STX18) plus one clinical parameter (depth of myometrial invasion) were identified for use in a sequencing-based prediction model. After qRT-PCR validation, five genes (ASRGL1, RHEX, SCGB2A1, SOX17, and STX18) were identified as predictive biomarkers. Receiver operating characteristic curve analysis revealed that these five genes can predict LNM. Combined use of these five genes resulted in higher diagnostic accuracy than use of any single gene, with an area under the curve of 0.898, sensitivity of 88.9%, and specificity of 84.1%. The accuracy, negative, and positive predictive values were 84.7, 98.1, and 44.4%, respectively.Conclusion: We developed a five-gene biomarker panel associated with LNM in early stage EEC. These five genes may represent novel targets for further mechanistic study. Our results, after corroboration by a prospective study, may have useful clinical implications and prevent unnecessary elective lymph node dissection while not adversely affecting the outcome of treatment for early stage EEC.

Background The molecular mechanisms through which high‐demand pacing induce myocardial dysfunction remain unclear. Methods and Results We created atrioventricular block in pigs using dependent right ventricular septal pacing for 6 months. Echocardiography was performed to evaluate dyssynchrony between pacing (n=6) and sham control (n=6) groups. Microarray and enrichment analyses were used to identify differentially expressed genes (DEGs) in the left ventricular (LV) myocardium between pacing and sham control groups. Histopathological and protein changes were also analyzed and an A cell pacing model was also performed. Pacing significantly increased mechanical dyssynchrony. Enrichment analysis using Ingenuity Pathway Analysis and the activation z‐score analysis method demonstrated that there were 5 DEGs (ABCA1, APOD, CLU, LY96, and SERPINF1) in the LV septum (z‐score=−0.447) and 5 DEGs (APOD, CLU, LY96, MSR1, and SERPINF1) in the LV free wall (z‐score=−1.000) inhibited the liver X receptor/retinoid X receptor (LXR/RXR) pathway, and 4 DEGs (ACTA2, MYL1, PPP2R3A, and SNAI2) activated the integrin‐linked kinase (ILK) pathway in the LV septum (z‐score=1.000). The pacing group had a larger cell size, higher degree of myolysis and fibrosis, and increased expression of intracellular lipid, inflammatory cytokines, and apoptotic markers than the sham control group. The causal relationships between pacing and DEGs related to LXR/RXR and ILK pathways, apoptosis, fibrosis, and lipid expression after pacing were confirmed in the cell pacing model. Luciferase reporter assay in the cell pacing model also supported inhibition of the LXR pathway by pacing. Conclusions Right ventricular septal‐dependent pacing was associated with persistent LV dyssynchrony–induced cardiomyopathy through inhibition of the LXR/RXR pathway.

BackgroundLeft atrial enlargement in mitral regurgitation (MR) predicts a poor prognosis. The regulatory mechanisms of atrial myocyte hypertrophy of MR patients remain unknown.Methods and resultsThis study comprised 14 patients with MR, 7 patients with aortic valve disease (AVD), and 6 purchased samples from normal subjects (NC). We used microarrays, enrichment analysis and quantitative RT-PCR to study the gene expression profiles in the left atria. Microarray results showed that 112 genes were differentially up-regulated and 132 genes were differentially down-regulated in the left atria between MR patients and NC. Enrichment analysis of differentially expressed genes demonstrated that "NFAT in cardiac hypertrophy" pathway was not only one of the significant associated canonical pathways, but also the only one predicted with a non-zero score of 1.34 (i.e. activated) through Ingenuity Pathway Analysis molecule activity predictor. Ingenuity Pathway Analysis Global Molecular Network analysis exhibited that the highest score network also showed high association with cardiac related pathways and functions. Therefore, 5 NFAT associated genes (PPP3R1, PPP3CB, CAMK1, MEF2C, PLCE1) were studies for validation. The mRNA expressions of PPP3CB and MEF2C were significantly up-regulated, and CAMK1 and PPP3R1 were significantly down-regulated in MR patients compared to NC. Moreover, MR patients had significantly increased mRNA levels of PPP3CB, MEF2C and PLCE1 compared to AVD patients. The atrial myocyte size of MR patients significantly exceeded that of the AVD patients and NC.ConclusionsDifferentially expressed genes in the "NFAT in cardiac hypertrophy" pathway may play a critical role in the atrial myocyte hypertrophy of MR patients.

Previous studies have shown an association between gout and/or hyperuricemia and a subsequent increase in cardiovascular disease (CVD) outcomes. Allopurinol reduces vascular oxidative stress, ameliorates inflammatory state, improves endothelial function, and prevents atherosclerosis progression. Accordingly, we tested the hypothesis that a positive association between allopurinol therapy in gout patients and future cardiovascular outcomes is present using a population-based matched-cohort study design.Patients aged ≥40 years with newly diagnosed gout having no pre-existing severe form of CVD were separated into allopurinol (n = 2483) and non-allopurinol (n = 2483) groups after matching for age, gender, index date, diabetes mellitus, hypertension, hyperlipidemia, and atrial fibrillation. The two groups were also balanced in terms of uric acid nephrolithiasis, acute kidney injury, hepatitis, and Charlson comorbidity index.With a median follow-up time of 5.25 years, the allopurinol group had a modest increase in cardiovascular risk [relative risk, 1.20; 95% confidence interval (CI), 1.08-1.34]. A Cox proportional hazard model adjusted for chronic kidney disease, uremia, and gastric ulcer gave a hazard ratio (HR) for cardiovascular outcomes of 1.25 (95% CI, 1.10-1.41) in gout patients receiving allopurinol compared with the non-allopurinol group. In further analysis of patients receiving urate-lowering therapy, the uricosuric agent group (n = 1713) had an adjusted HR of 0.83 (0.73-0.95) for cardiovascular events compared with the allopurinol group.The current population-based matched-cohort study did not support the association between allopurinol therapy in gout patients with normal risk for cardiovascular sequels and beneficial future cardiovascular outcomes. Several important risk factors for cardiovascular disease, such as smoking, alcohol consumption, body mass index, blood pressure were not obtainable in the current retrospective cohort study, thus could potentially bias the effect estimate.

Some previous studies have identified bacteria in semen as being a potential factor in male infertility. However, only few types of bacteria were taken into consideration while using PCR-based or culturing methods. Here we present an analysis approach using next-generation sequencing technology and bioinformatics analysis to investigate the associations between bacterial communities and semen quality. Ninety-six semen samples collected were examined for bacterial communities, measuring seven clinical criteria for semen quality (semen volume, sperm concentration, motility, Kruger's strict morphology, antisperm antibody (IgA), Atypical, and leukocytes). Computer-assisted semen analysis (CASA) was also performed. Results showed that the most abundant genera among all samples were Lactobacillus (19.9%), Pseudomonas (9.85%), Prevotella (8.51%) and Gardnerella (4.21%). The proportion of Lactobacillus and Gardnerella was significantly higher in the normal samples, while that of Prevotella was significantly higher in the low quality samples. Unsupervised clustering analysis demonstrated that the seminal bacterial communities were clustered into three main groups: Lactobacillus, Pseudomonas, and Prevotella predominant group. Remarkably, most normal samples (80.6%) were clustered in Lactobacillus predominant group. The analysis results showed seminal bacteria community types were highly associated with semen health. Lactobacillus might not only be a potential probiotic for semen quality maintenance, but also might be helpful in countering the negative influence of Prevotella and Pseudomonas. In this study, we investigated whole seminal bacterial communities and provided the most comprehensive analysis of the association between bacterial community and semen quality. The study significantly contributes to the current understanding of the etiology of male fertility.

BACKGROUND: Patients with Type 2 diabetes (T2DM) are prone to develop dementia. Results from a recent study indicated that statin users had lower chance of developing incident dementia. However there is little information on the potential benefits of statin use on dementia in patients with T2DM cohort. METHOD: A population-based retrospective study using a nationwide cohort of National Health Insurance Research Database in Taiwan was performed. T2DM cohort with regular use of statins was followed up to 8 years. Multivariate cox-proportional hazards regression model was used to estimate the association between statin use and incidence of dementia including Alzheimer's disease and non-Alzheimer dementia after adjusting for several potential confounders. RESULTS: Among 28,321 patients diagnosed with T2DM age above 50 and without history of dementia before 2000/1/1, 15,770 patients who had never used statin and 2,400 patients who regularly used statin drugs were enrolled. After adjusting for age group, gender, CCI (Charlson-Deyo comorbidity index) group, stroke types and anti-diabetic drugs, regular statin use was associated with a decreased risk of developing incident Alzheimer's disease dementia (adjusted HR: 0.48, 95% CI 0.30 - 0.76, p