Reproducibility of quantitative flow ratio: An inter-core laboratory variability study

Background: Quantitative flow ratio (QFR) is a novel approach to derive fractional flow reserve (FFR) from coronary angiography. This study sought to evaluate the reproducibility of QFR when analyzed in independent core laboratories. Methods: All interrogated vessels in the FAVOR II China Study were separately analyzed using the AngioPlus system (Pulse medical imaging technology, Shanghai) by two independent core laboratories, following the same standard operation procedures. The analysts were blinded to the FFR values and online QFR values. For each interrogated vessel, two identical angiographic image runs were used by two core laboratories for QFR computation. In both core laboratories QFR was successfully obtained in 330 of 332 vessels, in which FFR was available in 328 vessels. Thus, 328 vessels ended in the present statistical analysis. Results: The mean difference in contrast-flow QFR between the two core laboratories was 0.004 ± 0.03 (p = 0.040), which was slightly smaller than that between the online analysis and the two core laboratories (0.01 ± 0.05, p < 0.001 and 0.01 ± 0.05, p = 0.038). The mean difference of QFR with re­spect to FFR were comparable between the two core laboratories (0.002 ± 0.06, p = 0.609, and 0.002 ± 0.06, p = 0.531). Receiver operating characteristic curve analysis showed that diagnostic accuracies of QFR analyzed by the two core laboratories were both excellent (area under the curve: 0.970 vs. 0.963, p = 0.142), when using FFR as the reference standard. Conclusions: The present study showed good inter-core laboratory reproducibility of QFR in assessing functionally-significant stenosis. It suggests that QFR analyses can be carried out in different core labo­ratories if, and only if, highly standardized conditions are maintained

Empagliflozin inhibits coronary microvascular dysfunction and reduces cardiac pericyte loss in db/db mice

BackgroundCoronary microvascular dysfunction (CMD) is a pathophysiological feature of diabetic heart disease. However, whether sodium-glucose cotransporter 2 (SGLT2) inhibitors protect the cardiovascular system by alleviating CMD is not known.ObjectiveWe observed the protective effects of empagliflozin (EMPA) on diabetic CMD.Materials and methodsThe mice were randomly divided into a db/db group and a db/db + EMPA group, and db/m mice served as controls. At 8 weeks of age, the db/db + EMPA group was given empagliflozin 10 mg/(kg⋅d) by gavage for 8 weeks. Body weight, fasting blood glucose and blood pressure were dynamically observed. Cardiac systolic and diastolic function and coronary flow reserve (CFR) were detected using echocardiography. The coronary microvascular structure and distribution of cardiac pericytes were observed using immunofluorescence staining. Picrosirius red staining was performed to evaluate cardiac fibrosis.ResultsEmpagliflozin lowered the increased fasting blood glucose levels of the db/db group. The left ventricular ejection fraction, left ventricular fractional shortening, E/A ratio and E/e′ ratio were not significantly different between the three groups. CFR was decreased in the db/db group, but EMPA significantly improved CFR. In contrast to the sparse and abnormal expansion of coronary microvessels observed in the db/db group, the number of coronary microvessels was increased, and the capillary diameter was decreased in the db/db + EMPA group. The number and microvascular coverage of cardiac pericytes were reduced in the db/db mice but were improved by EMPA. The cardiac fibrosis was increased in db/db group and may alleviate by EMPA.ConclusionEmpagliflozin inhibited CMD and reduced cardiac pericyte loss in diabetic mice

Integrated Photonics for NASA Applications

No abstract availabl

Enabling the ability of Li storage at high rate as anodes by utilizing natural rice husks-based hierarchically porous SiO2/N-doped carbon composites

One of the greatest challenges in developing SiO 2/C composites as anode materials in lithium ion batteries (LIBs) is to improve the ability of Li storage at high rate over long-term cycles. Herein, biomass rice husks-based hierarchically porous SiO 2/N-doped carbon composites (BM-RH-SiO 2/NC) were prepared by ball mill and thermal treatment. BM-RH-SiO 2/NC can still retain a reversible capacity of 556 mAh g −1 over 1000 cycles at a high current of 1.0 A g −1. At 5.0 A g −1 the capacity is kept as high as 402 mAh g −1. This impressively long-term cyclic performance and high-rate capability of BM-RH-SiO 2/NC can be ascribed to the synergetic effect between the natural SiO 2 nanoparticles (< 50 nm) and the NC layer. The coating NC layer can not only effectively mitigate the volume strain during charge-discharge process to offer stably cyclic performance but also improve the electrical conductivity. Furthermore, the hierarchical porosity and better electrolyte wettability offer the rapid Li + diffusion and electron transfer, which enhance the pseudocapacitive behavior of whole electrode material and then guarantee fast electrochemical kinetics. Importantly, the unique Li-storage mechanism of active SiO 2 in BM-RH-SiO 2/NC composite was formed and found, which further validates the improved electrochemical capability

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A Simulation Study of Defects in a Rolling Element Bearing using FEA

An internal impact usually happens when there is a small defect in one part of rolling bearings. The Fault signal from this impact is always masked by different noises such as strong vibrations from other parts and the random noise of instrumentation, which makes it difficult to extract an accurate feature signal for early fault diagnosis. In this paper, a simulation study is conducted using the method of finite element analysis (FEA) to understand the vibration characteristics from the small impact. The vibration responses have been modelled based on a typical bearing assembly. Common faults including outer ring defect, inner ring defect and rolling ball defect are simulated and their vibration responses are compared between different faults and at different locations in the bearing housing. The results obtained have shown that under the same defect size, the vibration from the outer ring is the highest whereas that from the rolling ball is the smallest. In addition the vibration close to the mounting hole attenuates considerably compared to that close to outer ring. These findings provide fundamental information to place vibration sensors and to analyse vibration signals

Hyperspectral Inversion of Chromium Content in Soil Using Support Vector Machine Combined with Lab and Field Spectra

Chromium is not only an essential trace element for the growth and development of living organisms; it is also a heavy metal pollutant. Excessive chromium in farmland soil will not only cause harm to crops, but could also constitute a serious threat to human health through the cumulative effect of the food chain. The determination of heavy metals in tailings of farmland soil is an essential means of soil environmental protection and sustainable development. Hyperspectral remote sensing technology has good characteristics, e.g., high speed, macro, and high resolution, etc., and has gradually become a focus of research to determine heavy metal content in soil. However, due to the spectral variation caused by different environmental conditions, the direct application of the indoor spectrum to conduct field surveys is not effective. Soil components are complex, and the effect of linear regression of heavy metal content is not satisfactory. This study builds indoor and outdoor spectral conversion models to eliminate soil spectral differences caused by environmental conditions. Considering the complex effects of soil composition, we introduce a support vector machine model to retrieve chromium content that has advantages in solving problems such as small samples, non-linearity, and a large number of dimensions. Taking a mining area in Hunan, China as a test area, this study retrieved the chromium content in the soil using 12 combination models of three types of spectra (field spectrum, lab spectrum, and direct standardization (DS) spectrum), two regression methods (stepwise regression and support vector machine regression), and two factors (strong correlation factor and principal component factor). The results show that: (1) As far as the spectral types are concerned, the inversion accuracy of each combination of the field spectrum is generally lower than the accuracy of the corresponding combination of other spectral types, indicating that field environmental interference affects the modeling accuracy. Each combination of DS spectra has higher inversion accuracy than the corresponding combination of field spectra, indicating that DS spectra have a certain effect in eliminating soil spectral differences caused by environmental conditions. (2) The inversion accuracy of each spectrum type of SVR_SC (Support Vector Regression_Strong Correlation) is the highest for the combination of regression method and inversion factor. This indicates the feasibility and superiority of inversion of heavy metals in soil by a support vector machine. However, the inversion accuracy of each spectrum type of SVR_PC (Support Vector Regression_Principal Component) is generally lower than that of other combinations, which indicates that, to obtain superior inversion performance of SVR, the selection of characteristic factors is very important. (3) Through principal component regression analysis, it is found that the pre-processed spectrum is more stable for the inversion of Cr concentration. The regression coefficients of the three types of differential spectra are roughly the same. The five statistically significant characteristic bands are mostly around 384&ndash;458 nm, 959&ndash;993 nm, 1373&ndash;1448 nm, 1970&ndash;2014 nm, and 2325&ndash;2400 nm. The research results provide a useful reference for the large-scale normalization monitoring of chromium-contaminated soil. They also provide theoretical and technical support for soil environmental protection and sustainable development