AKT2 Blocks Nucleus Translocation of Apoptosis-Inducing Factor (AIF) and Endonuclease G (EndoG) While Promoting Caspase Activation during Cardiac Ischemia

The AKT (protein kinase B, PKB) family has been shown to participate in diverse cellular processes, including apoptosis. Previous studies demonstrated that protein kinase B2 (AKT2 − / − ) mice heart was sensitized to apoptosis in response to ischemic injury. However, little is known about the mechanism and apoptotic signaling pathway. Here, we show that AKT2 inhibition does not affect the development of cardiomyocytes but increases cell death during cardiomyocyte ischemia. Caspase-dependent apoptosis of both the extrinsic and intrinsic pathway was inactivated in cardiomyocytes with AKT2 inhibition during ischemia, while significant mitochondrial disruption was observed as well as intracytosolic translocation of cytochrome C (Cyto C) together with apoptosis-inducing factor (AIF) and endonuclease G (EndoG), both of which are proven to conduct DNA degradation in a range of cell death stimuli. Therefore, mitochondria-dependent cell death was investigated and the results suggested that AIF and EndoG nucleus translocation causes cardiomyocyte DNA degradation during ischemia when AKT2 is blocked. These data are the first to show a previous unrecognized function and mechanism of AKT2 in regulating cardiomyocyte survival during ischemia by inducing a unique mitochondrial-dependent DNA degradation pathway when it is inhibited.This work was supported by the National Natural Science Foundation of China, (Grant No. 81500179); the Natural Science Foundation of Jiangsu Province (Grant No. BK20150696); the Fundamental Research Funds for the Central Universities (Grant No. 2015PY005); the National Found for Fostering Talents of Basic Science (NFFTBS) (Grant No. J1310032); the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD); the National High Technology Research and Development Program of China (863 Program, No.2015AA020314); and the National Natural Science Foundation of China (Grant No. 81570696 and No. 31270985); this work is also sponsored by Qing Lan Project

Profiling of mismatch discrimination in RNAi enabled rational design of allele-specific siRNAs

Silencing specificity is a critical issue in the therapeutic applications of siRNA, particularly in the treatment of single nucleotide polymorphism (SNP) diseases where discrimination against single nucleotide variation is demanded. However, no generally applicable guidelines are available for the design of such allele-specific siRNAs. In this paper, the issue was approached by using a reporter-based assay. With a panel of 20 siRNAs and 240 variously mismatched target reporters, we first demonstrated that the mismatches were discriminated in a position-dependent order, which was however independent of their sequence contexts using position 4th, 12th and 17th as examples. A general model was further built for mismatch discrimination at all positions using 230 additional reporter constructs specifically designed to contain mismatches distributed evenly along the target regions of different siRNAs. This model was successfully employed to design allele-specific siRNAs targeting disease-causing mutations of PIK3CA gene at two SNP sites. Furthermore, conformational distortion of siRNA-target duplex was observed to correlate with the compromise of gene silencing. In summary, these findings could dramatically simplify the design of allele-specific siRNAs and might also provide guide to increase the specificity of therapeutic siRNAs

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Crystalline microporous metal phosphonates

Bibliography: p. 115-125Some pages are in colour

Smart Evaluation Index of Roof SHS Suitability

The instability of solar energy and its resource distribution characteristics make it difficult to judge its suitability in practical engineering applications, which hinders its promotion and application. In order to better promote the effective use of solar energy and promote the solar heating system, it is necessary to put forward a simple method of judging the suitability of the solar heating system for engineering application. This study puts forward “F, Q” as the basis for judging the suitability of solar heating systems built on the roof. Two types of public buildings, office buildings and three-star hotels, are taken as the research objects. DeST software is used to change the heating area of the building by superimposing floors to simulate the heat load of the building when the heating area changes. A dynamic simulation coupling model of solar heating system is established in the TRNSYS software to analyze the operating status of the system under all working conditions. The functional relationship between “F, Q” and solar energy guarantee rate is established, and the solar energy contribution rate is divided into three regions of F 50%. The evaluation standard of the building suitability of the solar energy heating system is established according to the scope of “F, Q” in different regions (An office building for, e.g., if the contribution rate of solar heating system is required to be greater than 50%, the “F” of these four areas should be greater than 0.11388, 0.15543, 0.10572, and 0.04511.), and the effectiveness of “F” is verified through actual cases verified by other scholars in the research. The method proposed in this paper is helpful to judge the suitability of solar heating systems in different regions and different types of conventional buildings, so as to better promote solar heating systems

Study on Supersonic Dehydration Efficiency of High Pressure Natural Gas

Supersonic cyclone separator is a novel type of natural gas dewatering device that overcomes the shortcomings of traditional dewatering methods. In order to investigate the factors affecting the separation efficiency and improve the separation performance of the supersonic cyclone separator, the discrete particle model was employed in numerical calculation. On the basis of an accurate numerical model, the flow field of supersonic cyclone separator was analyzed, the trajectories of droplets were predicted, and the factors affecting the separation efficiency of droplets were investigated. The numerical results indicated that Laval nozzle could provide the necessary conditions for the condensation of water vapor. The swirler can throw droplets onto the wall or into the separator, both of which are foundations for realizing the separation of droplets. Droplets had three typical trajectories affected by centrifugal effect and inertia effect. The existence of a shock wave increases the swirl intensity of droplets, which is conducive to the separation of droplets. The diameter of droplets should be increased as much as possible in order to improve separation efficiency, and the gas–liquid area ratio should be about 45.25%, and the number of vanes should be 10

Toward Identification of Black Lemma and Pericarp Gene Blp1 in Barley Combining Bulked Segregant Analysis and Specific-Locus Amplified Fragment Sequencing

Black barley is caused by phytomelanin synthesized in lemma and/or pericarp and the trait is controlled by one dominant gene Blp1. The gene is mapped on chromosome 1H by molecular markers, but it is yet to be isolated. Specific-locus amplified fragment sequencing (SLAF-seq) is an effective method for large-scale de novo single nucleotide polymorphism (SNP) discovery and genotyping. In the present study, SLAF-seq with bulked segregant analysis (BSA) was employed to obtain sufficient markers to fine mapping Blp1 gene in an F2 population derived from Hatiexi No.1 × Zhe5819. Based on SNP screening criteria, a total of 77,542 polymorphic SNPs met the requirements for association analysis. Combining two association analysis methods, the overlapped region with a size of 32.41 Mb on chromosome 1H was obtained as the candidate region of Blp1 gene. According to SLAF-seq data, markers were developed in the target region and were used for mapping the Blp1 gene. Linkage analysis showed that Blp1 co-segregated with HZSNP34 and HZSNP36, and was delimited by two markers (HZSNP35 and HZSNP39) spanning 8.1 cM in 172 homozygous yellow grain F2 plants of Hatiexi No.1 × Zhe5819. More polymorphic markers were screened in the reduced target region and were used to genotype the population. As a result, Blp1 was delimited within a 1.66 Mb on chromosome 1H by the upstream marker HZSNP63 and the downstream marker HZSNP59. Our results demonstrated the utility of SLAF-seq-BSA approach to identify the candidate region and discover polymorphic markers at the specific targeted genomic region

Extraction Optimization, Purification, Antioxidant Activity, and Preliminary Structural Characterization of Crude Polysaccharide from an Arctic Chlorella sp.

The arctic strain of Chlorella sp. (Chlorella-Arc) exists in the coldest and driest arctic ecosystems, and it is a new resource of active polysaccharides. The extraction of crude polysaccharide from Chlorella-Arc was optimized using the response surface methodology. A crude polysaccharide yield of approximately 9.62 ± 0.11% dry weight was obtained under these optimized conditions. Three fractions (P-I, P-II, and P-III) were present after purification by 2-diethylaminoethanol Sepharose Fast Flow and Sephadex G-100 chromatography. The P-IIa fraction demonstrated significant antioxidant activities. Moreover, P-IIa was an α- and β-type heteropolysaccharide with a pyran group and contained variable amounts of rhamnose, arabinose, glucose, and galactose based on fourier-transform infrared spectroscopy, high-performance liquid chromatography, and 1H and 13C nuclear magnetic resonance imaging. Production of high amounts of polysaccharide may allow further exploration of the microalgae Chlorella-Arc as a natural antioxidant

Performance Analysis and Optimization of SHS Based on Solar Resources Distribution in Typical Cities in Cold Regions of China

The variability and inhomogeneity of solar energy limits the development of solar heating systems (SHS) in many fields. In order to improve the utilization efficiency of SHS, this paper takes three typical cities (Xi’an, Dunhuang, Lhasa) as the research object, studies the operation state of SHS in student dormitory buildings, and puts forward a corresponding optimization strategy. The research shows that the reduction of water supply temperature will improve the operation efficiency and energy saving effect of a spontaneous combustion heat pump and that there is an optimal volume of heat storage water tank (HSWT), which can make the energy saving effect of SHS run better. The optimization of the SHS shows the water supply temperature is 35 °C, and the optimal volume of HSWT is 15 m3 in the “Resource-general area (Ⅲ)” represented by Xi’an, 25 m3 in the “Resource-rich area (Ⅱ)” represented by Dunhuang, and 40 m3 in the “Resource-richer area (Ⅰ)” represented by Lhasa. With the increase in the abundance of solar energy resources in the region, the optimal volume of HSWT also increases. Meanwhile, the solar energy contribution rate of the three regions in descending order is 61.3% (Lhasa), 32.8% (Dunhuang), and 25.9% (Xi’an). After optimization, the contribution of SHS increased by about 5%. The research results will help improve the efficiency of SHS in cold areas of China and make the system more efficient and energy efficient during operation

Improved conversion of stearic acid to diesel-like hydrocarbons by carbon nanotubes-supported CuCo catalysts

In this study, a novel carbon nanotube (CNT)-supported CuCo catalyst was successfully synthesized by wet impregnation. Experimental and theoretical results on catalytic deoxygenation of stearic acid, a model compound of microalgal bio-oil, revealed that the CuCo catalyst can effectively inhibit cracking reactions and promote production of diesel-like hydrocarbons. CuCo particles in the pores of CNTs were conducive to conversion of stearic acid to long-chain alkanes, featuring a high selectivity of 94.82% at 100% conversion. CuCo catalyst in oxidation state underwent fast in-situ reduction at the beginning of deoxygenation reaction, and its catalytic performance was comparable to that of reduced CuCo catalyst. The improved catalytic conversion of stearic acid to diesel-like hydrocarbons can be achieved at a high ratio of Cu-0/(Cu+ + Cu-0) and lattice Co atoms. In addition, the reduced H-2 pressure and amounts of catalysts show potential for large-scale industrial applications