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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.

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.

This study is to identify potential multiomics biomarkers for the early detection of the prognostic recurrence of PC patients. A total of 494 prostate adenocarcinoma (PRAD) patients (60-recurrent included) from the Cancer Genome Atlas (TCGA) portal were analyzed using the autoencoder model and similarity network fusion. Then, multiomics panels were constructed according to the intersected omics biomarkers identified from the two models. Six intersected omics biomarkers, TELO2, ZMYND19, miR-143, miR-378a, cg00687383 (MED4), and cg02318866 (JMJD6, METTL23), were collected for multiomics panel construction. The difference between the Kaplan–Meier curves of high and low recurrence-risk groups generated from the multiomics panel achieved p-value = 5.33 × 10−9, which is better than the former study (p-value = 5 × 10−7). Additionally, when evaluating the selected multiomics biomarkers with clinical information (Gleason score, age, and cancer stage), a high-performance prediction model was generated with C-index = 0.713, p-value = 2.97 × 10−15, and AUC = 0.789. The risk score generated from the selected multiomics biomarkers worked as an effective indicator for the prediction of PRAD recurrence. This study helps us to understand the etiology and pathways of PRAD and further benefits both patients and physicians with potential prognostic biomarkers when making clinical decisions after surgical treatment.

ObjectivesTo investigate the effect of the Early Chronic Kidney Disease (CKD) Care Programme on CKD progression in patients with CKD stage I–IIIa.DesignObservational cohort study.SettingTaipei Medical University Research Database from three affiliated hospitals.ParticipantsAdult 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 measuresThe risks of CKD stage I–IIIa progression to IIIb between Early CKD Care Programme participants and non-participants.ResultsCompared 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.ConclusionsThe Early CKD Care Programme is an independent protective factor against progression of early CKD.

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.

The microbial colonization in the nasopharynx is a prerequisite for the onset of infectious diseases. For successful infection, pathogens should overcome host defenses as well as compete effectively with the resident microbiota. Hence, elucidating the richness and diversity of the microbiome at the site of pathogen colonization is pivotal. Here, we investigated the adenoidal tissue microbiota collected through adenoidectomy to evaluate the impact of Streptococcus pneumoniae. Prospectively, children with sleep-disordered breathing (SDB) and otitis media with effusion (OME) were enrolled. During adenoidectomy, the nasopharyngeal swab and adenoid tissues were collected to determine the pneumococcal carriage and tissue microbiota, using multiplex PCR and 16S ribosomal RNA (16S rRNA) pyrosequencing. A total of 66 pediatric patients comprising 38 children with SDB and 28 children with OME were enrolled. There was no difference between the bacterial cultures from the surface of the nasopharyngeal adenoid in the SDB and OME groups. Thirty-four samples (17 SDB and 17 OME) underwent 16S rRNA pyrosequencing and fulfilled the criteria for further analysis. The Shannon diversity index for the samples from the SDB patients was found to be higher than that observed for the samples from OME patients, although the difference was not significant (p = 0.095). The Shannon diversity index for the samples negative for the pneumococcal carriage was significantly higher than that for the samples positive for pneumococcal carriage (p = 0.038). Alloprevotella, Staphylococcus, Moraxella, and Neisseriaceae were significantly dominant in the samples positive for the pneumococcal carriage. Dialister was significantly less present in the adenoid tissue positive for the pneumococcal carriage. Streptococcus pneumoniae, one of the most common pathogens of the airway, significantly influences the composition and diversity of the microbiota in the nasopharyngeal adenoid. Thus, bacterial community analysis based on 16S rRNA pyrosequencing allows for better understanding of the relationship between the adenoidal microbial communities.

Background and Aims To evaluate the association of osteoporosis medications and outcomes of patients at risk of CKD. Method We included patients with stage 3-5 CKD from three Taipei Medical University-affiliated hospitals between January 1, 2011 and August 31, 2016. Patients were divided into two groups based on whether they received osteoporosis medications (bisphosphonates, raloxifene, teriparatide, or denosumab) and then matched at a 1:1 ratio by using propensity scores. The outcomes of interest were bone fractures, cardiovascular (CV) events, and all-cause mortality. Cox proportional hazard regression models were applied to identify the risk factors. Results A total of 39128 patients with CKD were included. After propensity score matching, 763 patients were in the study and control groups, respectively. The mean age of patients was 71.9 ± 12.5 years, and 34.4% of patients were men. After a median follow-up of 2.9 years, the incidence rates of bone fracture, CV events, and all-cause mortality were 10.4%, 7.5%, and 7.5%, respectively. Multivariate analysis results indicated that osteoporosis treatment was note associated with reduced risks of bone fracture (HR 0.85; 95% CI 0.43–1.68; P = 0.65), CV events (HR 0.82; 95% CI 0.56–1.20; P = 0.30), and all-cause mortality (HR 0.74; 95% CI 0.51–1.08; P = 0.12). Subgroup analysis demonstrated only patients with CKD stage 3 who received osteoporosis medications associated with better survival. Conclusion Osteoporosis medications did not reduce bone fractures, CV events or mortality in patients with CKD. Improved overall survival was observed in patients with CKD stage 3.

Enterococcus faecium is one of the leading pathogens in the world. In this study, we proposed a strategy to rapidly and accurately distinguish vancomycin-resistant Enterococcus faecium (VREfm) and vancomycin-susceptible E. faecium (VSEfm) to help doctors correctly determine the use of vancomycin by a machine learning (ML)-based algorithm. A predictive model was developed and validated to distinguish VREfm and VSEfm by analyzing MALDI-TOF MS spectra of unique E. faecium isolates from different specimen types. Firstly, 5717 mass spectra, including 2795 VREfm and 2922 VSEfm, were used to develop the algorithm. And 2280 mass spectra of isolates, namely 1222 VREfm and 1058 VSEfm, were used to externally validate the algorithm. The random forest-based algorithm demonstrated good classification performances for overall specimens, whose mean AUROC in 5-fold cross validation, time-wise validation, and external validation was all greater than 0.84. For the detection of VREfm in blood, sterile body fluid, urinary tract, and wound, the AUROC in external validation was also greater than 0.84. The predictions with algorithms were significantly more accurate than empirical antibiotic use. The accuracy of antibiotics administration could be improved by 30%. And the algorithm could provide rapid antibiotic susceptibility results at least 24 hours ahead of routine laboratory tests. The turn-around-time of antibiotic susceptibility could be reduced by 50%. In conclusion, a ML algorithm using MALDI-TOF MS spectra obtained in routine workflow accurately differentiated VREfm from VSEfm, especially in blood and sterile body fluid, which can be applied to facilitate the clinical testing process due to its accuracy, generalizability, and rapidness.

Background Oral verrucous hyperplasia is commonly observed in the oral cavity of betel quid chewers and is a potential malignant disorder. However, the prognostic factors and genetic alterations of oral verrucous hyperplasia are unclear. Methods We calculate the survival rate and prognostic factors using a Kaplan-Meier analysis and Cox proportional hazards regression model. Copy number variations were analyzed using a single-nucleotide polymorphism (SNP) array. Results The 5-year disease-free and cancer-free survival rates of patients with oral verrucous hyperplasia were approximately 40% and 70%, respectively. Heavy betel quid chewing, advanced oral submucous fibrosis, and nonbuccal and nontongue lesions were risk factors for malignant transformation, whereas dysplasia did not affect outcomes. The gene amplification of CTTN, FOLR3, ORAOV1, PPFIA1, and RNF121 were associated with the poor prognosis of oral verrucous hyperplasia. Conclusion Heavy betel quid chewing, advanced oral submucous fibrosis, and nonbuccal and nontongue lesions are high-risk factors of patients with oral verrucous hyperplasia. The 5-copy number variation-associated genes could be used for early diagnosis and predicting the prognosis.

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.

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 More than 79.2 million confirmed COVID-19 cases and 1.7 million deaths were caused by SARS-CoV-2; the disease was named COVID-19 by the World Health Organization. Control of the COVID-19 epidemic has become a crucial issue around the globe, but there are limited studies that investigate the global trend of the COVID-19 pandemic together with each country’s policy measures. Objective We aimed to develop an online artificial intelligence (AI) system to analyze the dynamic trend of the COVID-19 pandemic, facilitate forecasting and predictive modeling, and produce a heat map visualization of policy measures in 171 countries. Methods The COVID-19 Pandemic AI System (CPAIS) integrated two data sets: the data set from the Oxford COVID-19 Government Response Tracker from the Blavatnik School of Government, which is maintained by the University of Oxford, and the data set from the COVID-19 Data Repository, which was established by the Johns Hopkins University Center for Systems Science and Engineering. This study utilized four statistical and deep learning techniques for forecasting: autoregressive integrated moving average (ARIMA), feedforward neural network (FNN), multilayer perceptron (MLP) neural network, and long short-term memory (LSTM). With regard to 1-year records (ie, whole time series data), records from the last 14 days served as the validation set to evaluate the performance of the forecast, whereas earlier records served as the training set. Results A total of 171 countries that featured in both databases were included in the online system. The CPAIS was developed to explore variations, trends, and forecasts related to the COVID-19 pandemic across several counties. For instance, the number of confirmed monthly cases in the United States reached a local peak in July 2020 and another peak of 6,368,591 in December 2020. A dynamic heat map with policy measures depicts changes in COVID-19 measures for each country. A total of 19 measures were embedded within the three sections presented on the website, and only 4 of the 19 measures were continuous measures related to financial support or investment. Deep learning models were used to enable COVID-19 forecasting; the performances of ARIMA, FNN, and the MLP neural network were not stable because their forecast accuracy was only better than LSTM for a few countries. LSTM demonstrated the best forecast accuracy for Canada, as the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were 2272.551, 1501.248, and 0.2723075, respectively. ARIMA (RMSE=317.53169; MAPE=0.4641688) and FNN (RMSE=181.29894; MAPE=0.2708482) demonstrated better performance for South Korea. Conclusions The CPAIS collects and summarizes information about the COVID-19 pandemic and offers data visualization and deep learning–based prediction. It might be a useful reference for predicting a serious outbreak or epidemic. Moreover, the system undergoes daily updates and includes the latest information on vaccination, which may change the dynamics of the pandemic.

Background MicroRNAs (miRs) regulate gene expression in heart failure. Circulating miRs as biomarkers for heart failure in mitral regurgitation patients (MR) remain unexplored. Methods This case–control study enrolled 32 MR patients with heart failure, 16 asymptomatic MR patients, and 12 control subjects without heart failure. We used next generation sequencing to study the gene expression profiles in the sera, and quantitative RT-PCR to study serum and tissue miRs in the left atria. Results Next generation sequencing analysis and enrichment analysis showed that 25 miRs were differentially expressed in the sera of MR patients with heart failure compared to control subjects. The circulating miR-148b-3p (p=0.002) and miR-409-3p (p=0.010) were significantly down-regulated in the MR patients with heart failure compared to control subjects. However, only circulation miR-148b-3p was significantly down-regulated in the MR patients without heart failure compared to control subjects (p=0.009). The tissue miR-409-3p was significantly down-regulated in the MR patients with heart failure compared to 3 purchased normal controls (p=0.041). Notably, the tissue RASGRP3 mRNA, target gene of miR-409-3p, was significantly up-regulated in the MR patients with heart failure compared to normal controls (p=0.010). The tissue FRY (p=0.010) and GADD45A (p=0.010) mRNAs, target genes of miR-148b-3p, were significantly up-regulated in the MR patients with heart failure compared to normal controls. Conclusions Circulating miR-148b-3p might serve as biomarker for future development of heart failure and miR-409-3p might serve as biomarker for incident heart failure in MR patients.

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 ( DEG s) 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 DEG s ( ABCA 1, APOD , CLU , LY 96, and SERPINF 1) in the LV septum (z‐score=−0.447) and 5 DEG s ( APOD , CLU , LY 96, MSR 1, and SERPINF 1) in the LV free wall (z‐score=−1.000) inhibited the liver X receptor/retinoid X receptor ( LXR / RXR ) pathway, and 4 DEG s ( ACTA 2, MYL 1, PPP 2R3A, and SNAI 2) 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 DEG s 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.

The impact of diabetes on perioperative outcomes remains incompletely understood. Our purpose is to evaluate post-operative complications and mortality in patients with diabetes. Using the institutional and clinical databases of three university hospitals from 2009&ndash, 2015, we conducted a matched study of 16,539 diabetes patients, aged &gt, 20 years, who underwent major surgery. Using a propensity score matching procedure, 16,539 surgical patients without diabetes who underwent surgery were also selected. Logistic regressions were used to calculate the odds ratios (ORs) with 95% confidence intervals (CIs) for post-operative complications and in-hospital mortality associated with diabetes. Patients with diabetes had a higher risk of postoperative septicemia (OR 1.33, 95% CI 1.01&ndash, 1.74), necrotizing fasciitis (OR 3.98, 95% CI 1.12&ndash, 14.2), cellulitis (OR 2.10, 95% CI 1.46&ndash, 3.03), acute pyelonephritis (OR 1.86, 95% CI 1.01&ndash, 3.41), infectious arthritis (OR 3.89, 95% CI 1.19&ndash, 12.7), and in-hospital mortality (OR 1.51, 95% CI 1.07&ndash, 2.13) compared to people without diabetes. Previous admission for diabetes (OR 2.33, 95% CI 1.85&ndash, 2.93), HbA1c &gt, 8% (OR 1.96, 95% CI 1.64&ndash, 2.33) and fasting glucose &gt, 180 mg/dL (OR 1.90, 95% CI 1.68&ndash, 2.16) were predictors for post-operative adverse events. Diabetes patients who underwent surgery had higher risks of infectious complications and in-hospital mortality compared with patients without diabetes who underwent similar major surgeries.

Oral squamous cell carcinoma (OSCC) is often diagnosed at a late stage and may be malignantly transformed from oral leukoplakia (OL). This study aimed to identify potential plasma microRNAs (miRNAs) for the early detection of oral cancer. Plasma from normal, OL, and OSCC patients were evaluated. Small RNA sequencing was used to screen the differently expressed miRNAs among the groups. Next, these miRNAs were validated with individual samples by quantitative real-time polymerase chain reaction (qRT-PCR) assays in the training phase (n = 72) and validation phase (n = 178). The possible physiological roles of the identified miRNAs were further investigated using bioinformatics analysis. Three miRNAs (miR-222-3p, miR-150-5p, and miR-423-5p) were identified as differentially expressed among groups; miR-222-3p and miR-423-5p negatively correlated with T stage, lymph node metastasis status, and clinical stage. A high diagnostic accuracy (Area under curve = 0.88) was demonstrated for discriminating OL from OSCC. Bioinformatics analysis reveals that miR-423-5p and miR-222-3p are significantly over-expressed in oral cancer tissues and involved in various cancer pathways. The three-plasma miRNA panel may be useful to monitor malignant progression from OL to OSCC and as potential biomarkers for early detection of oral cancer.

// Yi-Hui Wu 1 , Tzu-Hao Chang 2 , Yu-Fang Huang 1 , Chien-Chin Chen 3, 4 , Cheng-Yang Chou 1 1 Department of Obstetrics and Gynaecology, College of Medicine, National Cheng Kung University and Hospital, Tainan, Taiwan 2 Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan 3 Department of Pathology, Chia-Yi Christian Hospital, Chia-Yi, Taiwan 4 Department of Cosmetic Science, Chia Nan University of Pharmacy and Science, Tainan, Taiwan Correspondence to: Cheng-Yang Chou, e-mail: chougyn@mail.ncku.edu.tw Keywords: epithelial ovarian carcinoma, chemoresistance, collagen type XI alpha 1, Akt, PDK1 Received: March 27, 2015 Accepted: May 28, 2015 Published: June 10, 2015 ABSTRACT Chemoresistance to anticancer drugs substantially reduces survival in epithelial ovarian carcinoma (EOC). Here, microarray analysis showed that collagen type XI alpha 1 ( COL11A1 ) is a chemotherapy response-associated gene. Chemoresistant cells expressed higher COL11A1 and c/EBPβ than chemosensitive cells. COL11A1 or c/EBPβ downregulation suppressed chemoresistance, whereas COL11A1 overexpression attenuated sensitivity to cisplatin and paclitaxel.The c/EBPβ binding site in the COL11A1 promoter was identified as the major determinant of cisplatin- and paclitaxel-induced COL11A1 expression. Immunoprecipitation and immunofluorescence showed that in resistant cells, Akt and PDK1 were highly expressed and that anticancer drugs enhanced binding activity between COL11A1 and PDK1 binding and attenuated PDK1 ubiquitination and degradation. Conversely, chemosensitive cells showed decreased activity of COL11A1 binding to PDK1 and increased PDK1 ubiquitination, which were reversed by COL11A1 overexpression. Analysis of 104 EOC patients showed that high COL11A1 mRNA levels are significantly associated with poor chemoresponse and clinical outcome.

Background. Left atrial enlargement is a mortality and heart failure risk factor in primary mitral regurgitation (MR) patients. Pig models of MR have shown differential expression of genes linked to the renin-angiotensin system. Therefore, the aim of this study was to investigate the key genes of the renin-angiotensin that are expressed differentially in the left atrial myocardium in MR patients. Methods. Quantitative RT-PCR was used to compare gene expression in the renin-angiotensin system in the left atrium in MR patients, aortic valve disease patients, and normal subjects. Results. Plasma angiotensin II concentrations did not significantly differ between MR patients and aortic valve disease patients (P=0.582). Compared to normal controls, however, MR patients had significantly downregulated expressions of angiotensin-converting enzyme, angiotensin I converting enzyme 2, type 1 angiotensin II receptor, glutamyl aminopeptidase, angiotensinogen, cathepsin A (CTSA), thimet oligopeptidase 1, neurolysin, alanyl aminopeptidase, cathepsin G, leucyl/cystinyl aminopeptidase (LNPEP), neprilysin, and carboxypeptidase A3 in the left atrium. The MR patients also had significantly upregulated expressions of MAS1 oncogene (MAS1) and mineralocorticoid receptor compared to normal controls. Additionally, in comparison with aortic valve disease patients, MR patients had significantly downregulated CTSA and LNPEP expression and significantly upregulated MAS1 expression in the left atrium. Conclusions. Expressions of genes in the renin-angiotensin system, especially CTSA, LNPEP, and MAS1, in the left atrium in MR patients significantly differed from expressions of these genes in aortic valve disease patients and normal controls. Notably, differences in expression were independent of circulating angiotensin II levels. The results of this study provide a rationale for pharmacological therapies or posttranslational regulation therapies targeting genes expressed differentially in the renin-angiotensin system to remedy structural remodeling associated with atrial enlargement and heart failure progression in patients with MR.

Fungal rhinosinusitis is a unique phenotype of chronic rhinosinusitis with unique clinical and histological characteristics. The role of bacterial microbiota in various phenotypes chronic rhinosinusitis is not thoroughly understood. Therefore, we conducted 16s rRNA amplification sequencing to determine differences in bacterial communities between phenotypes (fungal vs. non- fungal) and anatomical sites (middle meatus vs. nasopharynx). Endoscope-guided swabs were used to collect samples from the middle meatus and nasopharynx of seven consecutive patients with fungal and 18 consecutive patients with non-fungal rhinosinusitis. DNA was extracted and investigated through 16S rRNA amplification. Among samples from the middle meatus, Shannon diversity was significantly lower in those from the fungal rhinosinusitis group (p = 0.029). However, no significant differences in diversity were noted between nasopharynx samples (p = 0.85). Fungal rhinosinusitis samples exhibited a distinct distribution of taxon relative abundance, which involved not only the absence of rhinosinusitis-associated commensal Corynebacterium and Fusobacterium in the middle meatus but also a significant increase in Haemophilus prevalence and abundance. This is the first study to compare bacterial communities in fungal and non-fungal rhinosinusitis samples. Our findings demonstrated that bacterial community dysbiosis was more apparent in fungal rhinosinusitis samples and was limited to the middle meatus.

The function of a protein is generally related to its subcellular localization. Therefore, knowing its subcellular localization is helpful in understanding its potential functions and roles in biological processes. This work develops a hybrid method for computationally predicting the subcellular localization of eukaryotic protein. The method is called EuLoc and incorporates the Hidden Markov Model (HMM) method, homology search approach and the support vector machines (SVM) method by fusing several new features into Chou's pseudo-amino acid composition. The proposed SVM module overcomes the shortcoming of the homology search approach in predicting the subcellular localization of a protein which only finds low-homologous or non-homologous sequences in a protein subcellular localization annotated database. The proposed HMM modules overcome the shortcoming of SVM in predicting subcellular localizations using few data on protein sequences. Several features of a protein sequence are considered, including the sequence-based features, the biological features derived from PROSITE, NLSdb and Pfam, the post-transcriptional modification features and others. The overall accuracy and location accuracy of EuLoc are 90.5 and 91.2 %, respectively, revealing a better predictive performance than obtained elsewhere. Although the amounts of data of the various subcellular location groups in benchmark dataset differ markedly, the accuracies of 12 subcellular localizations of EuLoc range from 82.5 to 100 %, indicating that this tool is much more balanced than other tools. EuLoc offers a high, balanced predictive power for each subcellular localization. EuLoc is now available on the web at http://euloc.mbc.nctu.edu.tw/.

The aim of this study was to investigate whether long-term use of Benzodiazepines (BZDs) is associated with breast cancer risk through the combination of population-based observational and gene expression profiling evidence. We conducted a population-based case-control study by using 1998 to 2009year Taiwan National Health Insurance Research Database and investigated the association between BZDs use and breast cancer risk. We selected subjects age of >20years old and six eligible controls matched for age, sex and the index date (i.e., free of any cancer at the case diagnosis date) by using propensity scores. A bioinformatics analysis approach was also performed for the identification of oncogenesis effects of BZDs on breast cancer. We used breast cancer gene expression data from the Cancer Genome Atlas and perturbagen signatures of BZDs from the Library of Integrated Cellular Signatures database in order to identify the oncogenesis effects of BZDs on breast cancer. We found evidence of increased breast cancer risk for diazepam (OR, 1.16; 95%CI, 0.95-1.42; connectivity score [CS], 0.3016), zolpidem (OR, 1.11; 95%CI, 0.95-1.30; CS, 0.2738), but not for lorazepam (OR, 1.04; 95%CI, 0.89-1.23; CS, -0.2952) consistently in both methods. The finding for alparazolam was contradictory from the two methods. Diazepam and zolpidem trends showed association, although not statistically significant, with breast cancer risk in both epidemiological and bioinformatics analyses outcomes. The methodological value of our study is in introducing the way of combining epidemiological and bioinformatics approaches in order to answer a common scientific question. Combining the two approaches would be a substantial step towards uncovering, validation and further application of previously unknown scientific knowledge to the emerging field of precision medicine informatics.

Cancer is a multifactorial disease, and imbalances of the immune response and sex-associated features are considered risk factors for certain types of cancer. The present study aimed to assess whether ankylosing spondylitis (AS), an immune disorder that predominantly affects young adult men, is associated with an increased risk of cancer. Using the Taiwan National Health Insurance Research Database, a cohort of patients diagnosed with AS between 2000 and 2008 who had no history of cancer prior to enrollment was established (n=5,452). Age- and sex-matched patients without AS served as controls (n=21,808). The results revealed that the overall incidence of cancer was elevated in patients with AS [standardized incidence ratio (SIR), 1.15; 95% confidence interval (CI), 1.03-1.27]. AS carried an increased risk of hematological malignancy in both sexes, colon cancer in females and bone and prostate cancer in males. Young patients with AS (≤35 years) and patients with a Charlson comorbidity index (CCI) ≥2 experienced a higher incidence of cancer (males, SIR 1.92, and 95% CI 1.04-3.26; females, SIR 2.00 and 95% CI 1.46-5.50). The cancer risk was increased during the first 3 years following the diagnosis of AS (SIR 1.49, 95% CI 1.29-1.71), and overall cancer-free survival was significantly decreased in patients with AS patients of both sexes (P

Introduction 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. Methods 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. Results 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. Conclusions 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.

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

Background MicroRNAs (miRNAs) play a critical role in down-regulating gene expression. By coupling with Argonaute family proteins, miRNAs bind to target sites on mRNAs and employ translational repression. A large amount of miRNA-target interactions (MTIs) have been identified by the crosslinking and immunoprecipitation (CLIP) and the photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) along with the next-generation sequencing (NGS). PAR-CLIP shows high efficiency of RNA co-immunoprecipitation, but it also lead to T to C conversion in miRNA-RNA-protein crosslinking regions. This artificial error obviously reduces the mappability of reads. However, a specific tool to analyze CLIP and PAR-CLIP data that takes T to C conversion into account is still in need. Results We herein propose the first CLIP and PAR-CLIP sequencing analysis platform specifically for miRNA target analysis, namely miRTarCLIP. From scratch, it automatically removes adaptor sequences from raw reads, filters low quality reads, reverts C to T, aligns reads to 3'UTRs, scans for read clusters, identifies high confidence miRNA target sites, and provides annotations from external databases. With multi-threading techniques and our novel C to T reversion procedure, miRTarCLIP greatly reduces the running time comparing to conventional approaches. In addition, miRTarCLIP serves with a web-based interface to provide better user experiences in browsing and searching targets of interested miRNAs. To demonstrate the superior functionality of miRTarCLIP, we applied miRTarCLIP to two public available CLIP and PAR-CLIP sequencing datasets. miRTarCLIP not only shows comparable results to that of other existing tools in a much faster speed, but also reveals interesting features among these putative target sites. Specifically, we used miRTarCLIP to disclose that T to C conversion within position 1-7 and that within position 8-14 of miRNA target sites are significantly different (p value = 0.02), and even more significant when focusing on sites targeted by top 102 highly expressed miRNAs only (p value = 0.01). These results comply with previous findings and further suggest that combining miRNA expression and PAR-CLIP data can improve accuracy of the miRNA target prediction. Conclusion To sum up, we devised a systematic approach for mining miRNA-target sites from CLIP-seq and PAR-CLIP sequencing data, and integrated the workflow with a graphical web-based browser, which provides a user friendly interface and detailed annotations of MTIs. We also showed through real-life examples that miRTarCLIP is a powerful tool for understanding miRNAs. Our integrated tool can be accessed online freely at http://miRTarCLIP.mbc.nctu.edu.tw.

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.

Background Severe mitral regurgitation (MR) may cause myolysis in the left atrial myocytes. Myolysis may contribute to atrial enlargement. However, the relationship between Rho-associated kinase (ROCK) and myolysis in the left atrial myocytes of MR patients remain unclear. Methods This study comprised 22 patients with severe MR [12 with atrial fibrillation (AF) and ten in sinus rhythm]. Left atrial appendage tissues were obtained during surgery. Normal left atrial tissues were purchased. Immunofluorescence histochemical and immunoblotting studies were performed. Results The expression of ROCK2 in the myolytic left atrial myocytes of MR AF patients (p = 0.009) and MR sinus patients (p = 0.011) were significantly higher than that of the normal subjects. Similarly, the expression of ROCK1 in the myolytic left atrial myocytes of MR AF patients was significantly higher than that of the normal subjects (p = 0.010), and the expression of ROCK1 in the myolytic left atrial myocytes of MR sinus patients was higher than that of the normal subjects (p = 0.091). Immunofluorescence study revealed significant co-localization and juxtaposition of ROCK2 and cleaved caspase-3 in the left atrial myocytes both in the MR AF group (Pearson’s coefficient = 0.74 ± 0.03) and the MR sinus group (Pearson’s coefficient = 0.73 ± 0.02). Similarly, immunofluorescence study revealed significant co-localization and juxtaposition of ROCK1 and cleaved caspase-3 in the left atrial myocytes both in the MR AF group (Pearson’s coefficient = 0.65 ± 0.03) and the MR sinus group (Pearson’s coefficient = 0.65 ± 0.03). Correlation analysis demonstrated that there was a significant direct relationship between the expression of ROCK2 in the myolytic left atrial myocytes and left atrial diameter in the MR patients (p = 0.041; r = 0.440). Moreover, the ratio of phosphorylated myosin-binding subunit of myosin light chain phosphatase (pMBS)/total MBS of left atrial tissues was significantly higher in the MR AF group (p

Background The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable to specific and cultivable bacteria and are also tedious. Based on high throughput sequencing technology, this work derives 16S rRNA sequences of bacteria and analyzes probiotics and pathogens species. Results We constructed a database that recorded the species of probiotics and pathogens from literature, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. We also constructed a bacteria disease risk model for seven diseases based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. Conclusions The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species (including uncultivable pathogens) for clinical microbiology applications. That is, detecting how probiotics and pathogens inhabit humans and how affect their health can significantly contribute to develop a diagnosis and treatment method.