Chinese PLA General Hospital

About: Chinese PLA General Hospital is a healthcare organization based out in Beijing, China. It is known for research contribution in the topics: Medicine & Population. The organization has 18037 authors who have published 12349 publications receiving 184803 citations. The organization is also known as: 301 Military Hospital.

Flexible piezoelectric nanogenerator in wearable self-powered active sensor for respiration and healthcare monitoring

Abstract: A wearable self-powered active sensor for respiration and healthcare monitoring was fabricated based on a flexible piezoelectric nanogenerator. An electrospinning poly(vinylidene fluoride) thin film on silicone substrate was polarized to fabricate the flexible nanogenerator and its electrical property was measured. When periodically stretched by a linear motor, the flexible piezoelectric nanogenerator generated an output open-circuit voltage and short-circuit current of up to 1.5 V and 400 nA, respectively. Through integration with an elastic bandage, a wearable self-powered sensor was fabricated and used to monitor human respiration, subtle muscle movement, and voice recognition. As respiration proceeded, the electrical output signals of the sensor corresponded to the signals measured by a physiological signal recording system with good reliability and feasibility. This self-powered, wearable active sensor has significant potential for applications in pulmonary function evaluation, respiratory monitoring, and detection of gesture and vocal cord vibration for the personal healthcare monitoring of disabled or paralyzed patients.

A differential diagnostic model of diabetic nephropathy and non-diabetic renal diseases

Abstract: Background. Renal diseases in diabetes include diabetic nephropathies (DN) and non-diabetic renal diseases (NDRD).Theclinicaldifferentiationbetweenthesetwocategories is usually not so clear and effective. This study aims to develop a quantified differential diagnostic model. Methods. We consecutively screened the diabetic patients with overt proteinuria but no severe renal failure for kidney biopsy from 1993 to 2003. The finally enrolled 110 patients were divided into two groups according to pathological features (60 in DN group and 50 in NDRD group). Clinical and laboratory data were compared between two groups. Then a diagnostic model was developed based on the logistic regression analysis. Results. Forty-six percent of patients were NDRD including a variety of pathological types. Many differences between DN and NDRD were found by comparison of the clinical indices. In the final logistic regression analysis, only diabetes duration (Dm), systolic blood pressure (Bp), HbA1c(Gh),haematuria(Hu)anddiabeticretinopathy(Dr) showedstatisticalsignificance.Basedonthelogisticregression model: π = e z /(1 + e z ), a diagnostic model was constructed as follows: PDN = exp(−13.5922 + 0.0371Dm + 0.0395Bp + 0.3224Gh − 4.4552Hu + 2.9613Dr)/ [1 +exp(−13.5922 +0.0371Dm +0.0395Bp +0.3224Gh − 4.4552Hu + 2.9613Dr)]. PDN was the probability of DN diagnosis (PDN ≥ 0.5 as DN, PDN < 0.5 as NDRD). Validation tests showed that this model had good sensitivity (90%) and specificity (92%). Conclusions.This diagnostic model may be helpful to clinical differentiation of DN and NDRD in type 2 diabetic patients with overt proteinuria.

Aberrant intra- and inter-network connectivity architectures in Alzheimer’s disease and mild cognitive impairment

Abstract: Alzheimer’s disease (AD) patients and those with high-risk mild cognitive impairment are increasingly considered to have dysfunction syndromes. Large-scale network studies based on neuroimaging techniques may provide additional insight into AD pathophysiology. The aim of the present study is to evaluate the impaired network functional connectivity with the disease progression. For this purpose, we explored altered functional connectivities based on previously well-defined brain areas that comprise the five key functional systems [the default mode network (DMN), dorsal attention network (DAN), control network (CON), salience network (SAL), sensorimotor network (SMN)] in 35 with AD and 27 with mild cognitive impairment (MCI) subjects, compared with 27 normal cognitive subjects. Based on three levels of analysis, we found that intra- and inter-network connectivity were impaired in AD. Importantly, the interaction between the sensorimotor and attention functions was first attacked at the MCI stage and then extended to the key functional systems in the AD individuals. Lower cognitive ability (lower MMSE scores) was significantly associated with greater reductions in intra- and inter-network connectivity across all patient groups. These profiles indicate that aberrant intra- and inter-network dysfunctions might be potential biomarkers or predictors of AD progression and provide new insight into AD pathophysiology.

Serum miR-125a-5p, miR-145 and miR-146a as diagnostic biomarkers in non-small cell lung cancer.

Abstract: Background: Lung cancer is becoming the leading cause of cancer-related deaths with high mortality worldwide and in China as well. Non-small-cell lung cancer (NSCLC) is the most common type of lung cancer accounting for approximately 85% of all cases. Over 70% of cases are at loco-regionally advanced stages or have distant metastasis at the time of presentation with subsequently poor prognosis. MiRNAs are stable molecules in blood and used as biomarkers for the early diagnosis of various malignancy. The purpose of this study was to evaluate whether circulating miR-125a-5p, miR-145 and miR-146a could be used as biomarkers for the diagnosis of NSCLC through measuring their expression and assess their relationship with clinical pathological factors. Methods: Expression levels of serum miR-125a-5p, miR-145 and miR-146a were detected in 70 pairs of NSCLC patients and healthy controls using quantitative real-time PCR analysis. Results: Serum miR-125a-5p, miR-145 and miR-146a were overexpressed in NSCLC patients compared with healthy controls. Their values of the area under the receiver –operating characteristic curve (AUC-ROC) were 0.71, 0.84 and 0.78. Optimal sensitivity and specificity were 73.53% and 55.71%, 92.75% and 61.43%, 84.06% and 58.57%, respectively in differentiating NSCLC patients from healthy controls. Conclusions: These preliminary data suggest that serum miR-125a-5p, miR-145 and miR-146a may be useful noninvasive biomarkers for the clinical diagnosis of NSCLC.