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Yao-Dan Liang,1,2 Yao-Nan Zhang,3 Yan-Ming Li,4 Yu-Hui Chen,5 Jing-Yong Xu,6 Ming Liu,7 Jing Li,8 Zhao Ma,9 Lin-Lin Qiao,10 Zi Wang,11 Jie-Fu Yang,1 Hua Wang1 1Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, People’s Republic of China; 2Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, People’s Republic of China; 3Department of Orthopedics; 4Department of Pulmonary and Critical Care Medicine; 5Department of Neurology; 6Department of General Surgery; 7Department of Urology; 8Department of Geriatrics; 9Department of Rehabilitation; 10Department of Traditional Chinese Medicine; 11Department of Cardiac Surgery, Beijing Hospital, National Center of Gerontology, Beijing, People’s Republic of ChinaCorrespondence: Hua Wang; Jie-Fu YangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, No. 1, Dahua Road, Dongcheng District, Beijing 100730, People’s Republic of ChinaTel +86 13911680467; +86 13601292259Fax +86-010-58115035Email wh74220@aliyun.com; yangjiefu2011@126.comObjectives: To survey the difference of frailty prevalence in elderly inpatients amongdifferent wards; to compare the diagnostic performance of five frailty measurements (Clinical Frailty Scale [CFS], FRAIL, Fried, Edmonton, Frailty Index [FI]) in identifying frailty; and to explore the risk factors of frailty in elderly inpatients.Participants and methods: This was a cross-sectional study including 1000 inpatients (mean age 75.2±6.7 years, 51.5% male; 542, 229, and 229 patients from cardiology, non-surgical, and surgical wards, respectively) in a tertiary hospital from September 2018 to February 2019. We applied the combined index to integrate the five frailty measurements mentioned above as the gold standard of frailty diagnosis. Multivariate logistic regression models were used to determine the independent risk factors of frailty.Results: Frailty prevalence was 32.3% (Fried), 36.2% (CFS), 19.2% (FRAIL), 25.2% (Edmonton), 35.1% (FI) in all patients. The frailty was more common in non-surgical wards, regardless of the frailty assessment tools used (non-surgical wards: 27.5% to 51.5%; cardiology ward: 14.9% to 29.3%; surgical wards: 18.8% to 41.9%). CFS≥5 showed a sensitivity of 94.1% and a specificity of 85.2% for all patients. FI≥0.25 showed a sensitivity of 94.8% and a specificity of 87.0% for all patients. Age [odds ratio (OR) = 1.089, P

With increase of the yield of vegetable, the vegetable wastes production is also increasing year by year, which has become an important pollution source in China. At present due to lack of some basic parameters, such as straw coefficient, physical and chemical properties, vegetable wastes utilization can not get effective data support. So the paper studied the straw coefficient, nutrient content, C/N, pH and EC of vegetable wastes through the literatures, investigations and laboratory analysis. The results showed that leafy vegetables, rhizomes vegetables and amphisarca vegetables straw coefficient was 9.7%, 4.7% and 3.8% respectively. Comparing with other solid wastes, vegetable wastes had the characteristics of high moisture, high organic matter content, high nutrient content, high EC and weak acid. But there were great distinctions in different types of vegetable wastes properties, especially in the total nitrogen content and C/N. The total nitrogen of rhizomes vegetables wastes was significantly lower than the others. On the contrary, the higest C/N was rhizome vegetables of 34.6, followed by amphisarca vegetables with 13.8, and leafy vegetables with 11.5.

Background Sleep-disordered breathing (SDB) is known to occur frequently in and may predict worsening progression of patients with congestive heart failure (CHF). SDB is also known to play an important role in the development of idiopathic pulmonary arterial hypertension (PAH) via inducing endothelial dysfunction and vascular remodeling, a pathological process that can be significantly influenced by factors such as osteoprotegerin (OPG) and endothelial progenitor cells (EPCs). The objective of this study is to determine if CHF with SDB is associated with changes in OPG, EPCs, and PAH. Methods EPCs were isolated, cultured, and quantified from CHF patients with SDB (n = 52), or without SDB (n = 68). OPG and N-terminal pro-brain natriuretic peptide (NT-proBNP) from each group was analyzed and correlated with EPCs and the mean pulmonary artery pressure (mPAP) measured by right heart catheterization. Results A significant decrease in circulating EPCs (29.30 ± 9.01 vs. 45.17 ± 10.51 EPCs/× 200 field; P < 0.05) was found in CHF patients with SDB compared to those without SDB. Both OPG (789.83 ± 89.38 vs. 551.29 ± 42.12 pg/mL; P < 0.05) and NT-proBNP (5946.50 ± 1434.50 vs. 3028.60 ± 811.90 ng/mL; P < 0.05) were also significantly elevated in SDB CHF patients who also had significantly elevated mPAP (50.2 ± 9.5 vs. 36.4 ± 4.1 mm Hg; P < 0.05). EPC numbers correlated inversely with the episodes of apnea and hypopnea per hour (RDI, r = –0.45, P = 0.037) and blood level of OPG (r = –0.53, P = 0.011). Although NT-proBNP was also increased significantly in patients with SDB, it had no correlation with either EPCs or RDI. Conclusions SDB due to hypoxemia from decompensated CHF is associated with (1) OPG elevation, (2) EPC depletion, and (3) mPAP elevation. The inverse relationship of circulating OPG with EPCs suggests a likely mechanism for hypoxemia and OPG in the development of pulmonary vascular dysfunction via depleting EPCs, thus worsening prognosis of CHF.

According to the analysis of the grain size, content of heavy metals (Cu, Cr, Zn, As and Pb) and 137Cs dating in Shilianghe Reservoir, the sedimentary rate and pollution characteristic of heavy metals were investigated. The geo-accumulation index was used to assess the pollution degree of heavy metals. It showed that the averaged sedimentary rate was 3.85cm/a, and Cu, Cr and Zn were in the light polluted level with the geo-accumulation index less than 1 during the past 40 years. The geo-accumulation index of As fluctuated strongly, but now it was in the light polluted level. The geo-accumulation index of Pb was more than 1, and the pollution level increased gradually from the bottom of the core and trends to aggravate.

Background: MicroRNAs (miRNAs) play key roles in cardiac development, and the expression of miRNAs is altered in the diseased heart. The aim of this study was to explore the value of circulating microRNA-122-5p (miR-122-5p) as a potential biomarker for acute myocardial infarction (AMI). Methods: Plasma samples from 50 patients with AMI and 39 healthy adults (non-AMI controls) were collected. The abundance of circulating miR-122-5p was measured using quantitative real-time PCR (qRT-PCR). The cTnI concentrations of these samples were analyzed by ELISA. Results: Our findings revealed that circulating miR-122-5p expression were increased in AMI patients at 4 h, 8 h, 12 h, and 24 h by contrast to those non-AMI controls and displayed similar trends to that of cTnI concentrations in AMI patients. Further study showed that there is a high correlation between circulating miR-122-5p and cTnI concentrations. At last, the receiver operating characteristic (ROC) curve was performed and showed that circulating miR-122-5p had considerable diagnostic accuracy for AMI with an area under curve (AUC) of 0.855. Conclusions: Our results implied that circulating miR-122-5p could be a potential biomarker for AMI.