Arrhythmia classification detection based on multiple electrocardiograms databases.

According to the World Health Organization, cardiovascular diseases are the leading cause of deaths globally. Electrocardiogram (ECG) is a non-invasive approach for detecting heart diseases and reducing the risk of heart disease-related death. However, there are limited numbers of ECG samples and imbalance distribution for existing ECG databases. It is difficult to train practical and efficient neural networks. Based on the analysis and research of many existing ECG databases, this paper conduct an in-depth study on three fine-labeled ECG databases, to extract heartbeats, unify the sampling frequency, and propose a self-processing method of heartbeats, and finally form a unified ECG arrhythmia classification database, noted as Hercules-3. It is separated into training sets (80%) and testing sets (the remaining 20%). In order to verify its capabilities, we have trained a 16-classification fully connected neural network based on Hercules-3 and it achieves an accuracy rate of up to 98.67%. Compared with other data processing, our proposed method improves classification recall by at least 6%, classification accuracy by at least 4%, and F1-score by at least 7%.

MicroRNA-381 suppresses proliferation and invasion of prostate cancer cells through downregulation of the androgen receptor.

Prostate cancer (PCa) is the most frequently diagnosed malignancy in men and its incidence has increased rapidly worldwide. Notably, the molecular mechanisms underlying prostate tumorigenesis have not been fully identified. The levels of microRNA (miR)-381 have been explored in numerous types of malignancy; however, the expression levels and biological function of miR-381 in PCa remain largely unknown. In the present study, reverse-transcription polymerase chain reaction was used to detect the expression levels of miR-381 in PCa cells and normal prostate epithelial cells. Subsequently, miR-381 antisense oligonucleotides and mimics were transfected into LNCaP PCa cells. Bioinformatics analysis was performed to identify the potential target genes of miR-381. Protein expression analysis, dual-luciferase reporter assay and a rescue assay were used to confirm the target of miR-381. The data suggested that the expression levels of miR-381 were significantly decreased in PCa cells compared with in normal prostatic epithelial cells. Furthermore, transfection of LNCaP cells with miR-381 mimics suppressed their proliferation, migration and invasion. In addition, bioinformatics analysis suggested that the androgen receptor (AR) was a target gene of miR-381. miR-381 suppressed the expression levels of AR by directly binding to its 3'-untranslated region. Furthermore, transfection with an AR plasmid partially attenuated miR-381-induced inhibition of cell proliferation, migration and invasion. The results of the present study suggested that miR-381 may act as a tumor suppressor in PCa by directly targeting the AR.

MiR-1, a Potential Predictive Biomarker for Recurrence in Prostate Cancer After Radical Prostatectomy.

BACKGROUND: Increasing evidence suggests that aberrant microRNAs expressions are significantly associated with cancer progression. Previous studies have reported that the relative expression of miR-1 is significantly downregulated in recurrent prostate cancer (PCa) samples when compared with nonrecurrent PCa tissues. However, whether miR-1 can serve as a novel predictive biomarker for PCa recurrence still remains unclear. MATERIALS AND METHODS: The patients with clinically localized PCa who underwent radical prostatectomy by the same medical team at the Department of Urology, Ningbo No.2 Hospital were enrolled in this study. We examined the miR-1 expression levels in recurrent and nonrecurrent tumor samples by quantitative reverse transcription polymerase chain reaction. Univariate and multivariate Cox proportional hazards analyses were used for the evaluation of potential predictors of PCa recurrence. RESULTS: During the study period, 78 patients (including 27 in the recurrent group and 51 in the nonrecurrent group) who were diagnosed with PCa and who underwent radical prostatectomy were included in the final analysis. MiR-1 was significantly downregulated in recurrent PCa tissues when compared with nonrecurrent tumor samples (P < 0.001). The univariate and multivariate Cox proportional hazards analyses indicated that miR-1 was the only independent prognostic factor for PCa recurrence (hazard ratio = 1.86; 95% CI: 1.21-2.94; P = 0.011). The area under the curve value of miR-1 for PCa recurrence was 0.885 (P < 0.001) with the sensitivity of 0.863 and specificity of 0.889 based on receiver operating characteristic curve analysis. CONCLUSIONS: This study identifies that miR-1 in PCa tissues can function as an important independent predictive factor for PCa recurrence.

High PCA3 scores in urine correlate with poor-prognosis factors in prostate cancer patients.

BACKGROUND: To improve the prediction of prostate cancer (PCA) risk and pathological type of PCA by non-invasive approaches before performing prostatic biopsy are the current challenges for the management of PCA. The aim of this present study was evaluate the clinical validity of prostate cancer associated 3 (PCA3) gene in the prediction of PCA and the correlations between the PCA3 level and prognostic factors. METHODS: A total of 207 patients with suspected prostate cancer in Ningbo No. 2 hospital between June 2012 and July 2014 were enrolled in this study. All patients included underwent prostate biopsy under the direction of digital rectal examination (DRE) and were divided into PCA group and no evidence of malignancy (NEM) group according to the pathological diagnosis. We analyzed the association between PCA3 score and indicators of prognosis (Gleason score, percentage of positive cores and clinical stage) by multivariate analysis. RESULTS: The levels of total prostate-specific antigen (t-PSA), prostate health index (PHI) and PCA3 score in patients with PCA were significantly higher than those in NEM group (P<0.05). In PCA group, PHI value and t-PSA were both factors significantly correlated with high Gleason score and clinical stage (P<0.05). A high PCA3 score in urine was significantly correlated with a high Gleason score, % positive cores and an advanced clinical stage (P<0.05). CONCLUSION: PCA3 score might be one of useful diagnostic tools for determining suitable therapeutic programs for PCa and predicting the prognosis.

Diabetes, a risk factor for both infectious and major complications after percutaneous nephrolithotomy.

BACKGROUND: It is reported that up to one-third of patients might have some postoperative complications after percutaneous nephrolithotomy (PCNL). The predictive factors for infectious and major complications remains conflicted, which was the main objective of this study. METHODS: This was a retrospective analysis using data from enrolled 411 patients diagnosed with renal stones underwent PCNL from 2008 to 2013. The correlation between postoperative complications with demographic characteristics, comorbidities and perioperative features was analyzed by Fisher's exact test or Mann-Whitney test. Logistic regression analysis was used for assessment of risk factors associatedwith infectious and major complications. RESULTS: The mean age of 411 patients included was 53.6 years and male patients occupied 57.9%. Of all the 411 patients enrolled, 145 patients were diagnosed with systemic inflammatory response syndrome (SIRS). The comorbidity of diabetes and complete staghorn calculi were suggested to be independent risk factors for postoperative infectious complications by Logistic regression analysis. The overall complication rate was 31.1% (128/411) and 33 cases (8.0%) was categorized as major complications according to the modified Clavien score. The comorbidity of diabetes and an upper pole tract were risk factors for the occurrence of major complications after PCNL. CONCLUSIONS: The comorbidity of diabetes was significantly associated with an increasing incidence of both infectious and major postoperative complications after PCNL.