Optimal path selection of innovation resource allocation in China’s regions with shared inputs

As an effective form of interaction between innovation subjects and resources, the regional innovation network’s optimal allocation of resources is the key to improving national innovation capacity. According to the innovation value chain, the process of resource allocation in innovation can be divided into two correlative sub-systems: the knowledge innovation stage (KIS) and the achievements commercialisation stage (ACS). To evaluate regional innovation efficiency, a two-stage network data envelopment analysis model with shared inputs is used, with fuzzy set qualitative comparative analysis to analyse the improvement path of resource allocation efficiency from the dimensions of regional environment and network structure. The results show that efficiency in the KIS is higher than in the ACS, and the efficiency scores for most regions in China are better under the model with shared inputs. The efficiency of innovative resource allocation is affected by the cross-action of seven factors: regional economic development, infrastructure, policy system, social culture, network scale, network openness, and network centrality. To achieve highefficiency resource allocation, regions should build an innovation network that matches their environmental characteristics. These findings provide theoretical guidance for formulating innovative resource allocation policies suitable for different regions

Cathepsin S Deficiency Results in Abnormal Accumulation of Autophagosomes in Macrophages and Enhances Ang II–Induced Cardiac Inflammation

BACKGROUND: Cathepsin S (Cat S) is overexpressed in human atherosclerotic and aneurysmal tissues and may contributes to degradation of extracellular matrix, especially elastin, in inflammatory diseases. We aimed to define the role of Cat S in cardiac inflammation and fibrosis induced by angiotensin II (Ang II) in mice. METHODS AND RESULTS: Cat S-knockout (Cat S(-/-)) and littermate wild-type (WT) C57BL/6J mice were infused continuously with Ang II (750 ng/kg/min) or saline for 7 days. Cat S(-/-) mice showed severe cardiac fibrosis, including elevated expression of collagen I and α-smooth muscle actin (α-SMA), as compared with WT mice. Moreover, macrophage infiltration and expression of inflammatory cytokines (tumor necrosis factor α, transforming growth factor β and interleukin 1β) were significantly greater in Cat S(-/-) than WT hearts. These Ang II-induced effects in Cat S(-/-) mouse hearts was associated with abnormal accumulation of autophagosomes and reduced clearance of damaged mitochondria, which led to increased levels of reactive oxygen species (ROS) and activation of nuclear factor-kappa B (NF-κB) in macrophages. CONCLUSION: Cat S in lysosomes is essential for mitophagy processing in macrophages, deficiency in Cat S can increase damaged mitochondria and elevate ROS levels and NF-κB activity in hypertensive mice, so it regulates cardiac inflammation and fibrosis

The Effect of Hepatosteatosis on Response to Antiviral Treatment in Patients with Chronic Hepatitis B: A Meta-Analysis

Background. This study is to systematically analyze the effects of hepatosteatosis on the response to antiviral treatment in patients with chronic hepatitis B (CHB) and hepatosteatosis. Methods. Systematic search was performed in PubMed, Embase, Web of Science, Elsevier, and the Chinese BioMedical literature databases for relevant studies published until February 2016. Treatment outcomes were compared between patients with CHB plus concomitant hepatosteatosis and those without hepatosteatosis. Results. A total of 8 prospective cohort studies (399 patients with CHB plus hepatosteatosis and 688 patients with only CHB) were included. Biochemical and virological response at both 48 and 96 weeks were significantly lower in patients with CHB plus hepatosteatosis as compared to that in patients with only CHB. Subgroup analysis based on methods used for diagnosis of hepatosteatosis and treatment regimens showed that when hepatosteatosis was diagnosed on Doppler ultrasound and treated with nucleotide analogues, patients with CHB plus hepatosteatosis showed lower biochemical (62.7% versus 75.8%, P=0.002) and virological response (66.2% versus 72.3%, P=0.006) as compared to that in patients with CHB. Conclusion. Hepatosteatosis lowers the efficacy of antiviral treatment in patients with CHB, especially when hepatosteatosis was diagnosed on ultrasound findings and treated with nucleotide analogues

Determination of geotechnical parameters based on the unsupervised learning method

With the development of urban engineering construction, the issue of construction engineering accidents has become more and more prominent. The geotechnical parameter interval obtained by using the traditional methods cannot meet the needs of actual engineering. Based on the idea of unsupervised learning, the peaty soil with the worst engineering properties is considered, and 8 physical indexes are selected as the input set. The principal component analysis (PCA) algorithm is used to realize the dimensionality reduction of multi-sample and multi-parameter decoupling, and the correlation and sensitivity of each physical index is obtained. Combined with its correlation and sensitivity, the comprehensive evaluation value of physical indexes of peat soil with different buried depths is given. The k-means clustering is used to analyze the relationship among physical index, and comprehensive evaluation value and engineering characteristics of peaty soil provide a theoretical basis for the selection of geotechnical parameters. The supervised learning method-BP neural network algorithm is used to analyze the unsupervised results and verify the accuracy of the (PCA—k-means) algorithm model. The normal samples obtained by clustering analysis are optimized by a variety of truncation methods to obtain a reliable value range, and the value results are compared with the actual engineering values to verify the rationality of the model engineering parameters. The algorithm model is of good engineering application value. The research results can provide references for engineering investigation, design and construction parameter values, and also provide a new analysis method for geotechnical parameter value analyses

Cartilage Oligomeric Matrix Protein Inhibits Vascular Smooth Muscle Calcification by Interacting With Bone Morphogenetic Protein-2

Rationale: Vascular calcification is a significant contributor to cardiovascular morbidity and mortality. We recently reported that cartilage oligomeric matrix protein (COMP) is pivotal for maintaining the homeostasis of vascular smooth muscle cells (VSMCs). Whether COMP affects the process of vascular calcification is unknown. Objective: We aimed to test whether COMP modulates vascular calcification. Methods and Results: VSMC calcification in vitro was induced by calcifying media containing high inorganic phosphate or calcium. In vivo medial vessel calcification was induced in rats by 5/6 nephrectomy with a high-phosphate diet or by periadventitial application of CaCl2 to the abdominal aorta. COMP protein level was markedly reduced in both calcified VSMCs and arteries. COMP deficiency remarkably exacerbated VSMC calcification, whereas ectopic expression of COMP greatly reduced calcification. Furthermore, COMP knockdown facilitated osteogenic markers expression by VSMCs even in the absence of calcifying media. By contrast, COMP overexpression significantly inhibited high phosphate-or high calcium-induced VSMC osteochondrogenic transition. Induction of osteogenic marker expression by COMP silencing was reversed by a soluble form of bone morphogenetic protein (BMP)-2 receptor IA, which suggests a BMP-2-dependent mechanism. Our data revealed that COMP bound directly to BMP-2 through the C terminus, inhibited BMP-2 receptor binding, and blocked BMP-2 osteogenic signaling, indicating COMP inhibits osteochondrogenic transition of VSMCs at least partially through inhibiting BMP-2. Conclusions: Our data strongly suggest that COMP is a novel inhibitor of vascular calcification. The imbalance between the effects of COMP and BMP-2 may provide new insights into the pathophysiology of vascular calcification. (Circ Res. 2011;108:917-928.)Cardiac & Cardiovascular SystemsHematologyPeripheral Vascular DiseaseSCI(E)PubMed19ARTICLE8917-U7910

Are medical record front page data suitable for risk adjustment in hospital performance measurement? Development and validation of a risk model of in-hospital mortality after acute myocardial infarction

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement