A Brief Review of Computational Gene Prediction Methods

With the development of genome sequencing for many organisms, more and more raw sequences need to be annotated. Gene prediction by computational methods for finding the location of protein coding regions is one of the essential issues in bioinformatics. Two classes of methods are generally adopted: similarity based searches and ab initio prediction. Here, we review the development of gene prediction methods, summarize the measures for evaluating predictor quality, highlight open problems in this area, and discuss future research directions

Exploring photosynthesis evolution by comparative analysis of metabolic networks between chloroplasts and photosynthetic bacteria

BACKGROUND: Chloroplasts descended from cyanobacteria and have a drastically reduced genome following an endosymbiotic event. Many genes of the ancestral cyanobacterial genome have been transferred to the plant nuclear genome by horizontal gene transfer. However, a selective set of metabolism pathways is maintained in chloroplasts using both chloroplast genome encoded and nuclear genome encoded enzymes. As an organelle specialized for carrying out photosynthesis, does the chloroplast metabolic network have properties adapted for higher efficiency of photosynthesis? We compared metabolic network properties of chloroplasts and prokaryotic photosynthetic organisms, mostly cyanobacteria, based on metabolic maps derived from genome data to identify features of chloroplast network properties that are different from cyanobacteria and to analyze possible functional significance of those features. RESULTS: The properties of the entire metabolic network and the sub-network that consists of reactions directly connected to the Calvin Cycle have been analyzed using hypergraph representation. Results showed that the whole metabolic networks in chloroplast and cyanobacteria both possess small-world network properties. Although the number of compounds and reactions in chloroplasts is less than that in cyanobacteria, the chloroplast's metabolic network has longer average path length, a larger diameter, and is Calvin Cycle -centered, indicating an overall less-dense network structure with specific and local high density areas in chloroplasts. Moreover, chloroplast metabolic network exhibits a better modular organization than cyanobacterial ones. Enzymes involved in the same metabolic processes tend to cluster into the same module in chloroplasts. CONCLUSION: In summary, the differences in metabolic network properties may reflect the evolutionary changes during endosymbiosis that led to the improvement of the photosynthesis efficiency in higher plants. Our findings are consistent with the notion that since the light energy absorption, transfer and conversion is highly efficient even in photosynthetic bacteria, the further improvements in photosynthetic efficiency in higher plants may rely on changes in metabolic network properties

Quantitative Estimation of Urban PM2.5 Pollution Baseline and Meteorological Resource Endowment Using Machine Learning in Chinese Yangtze River Economic Belt

Considering the influence of baseline values, meteorological conditions, and human activities on PM2.5, quantifying them will facilitate the classification, control, and management of pollution. The machine learning model explained the PM2.5-meteorological nonlinear relationship between PM2.5 and meteorological factors in each city across the Yangtze River Economic Belt, China. Meteorological resource endowments (MRE) are used to quantify the variation on PM2.5 concentration caused by meteorological conditions. Contamination baseline (CB) is used to characterize the lowest limit of anthropogenic impact in PM2.5 contamination without meteorological interference. According to the values of MRE and CB, cities in the Yangtze River economic belt can be divided into four categories (Q1-4). The average value of MRE is −0.41 μg/m3. The average value of CB is 34.05 μg/m3, which is lower than the Chinese Grade II standard (GB 3095-2012). The additional emissions by humans resulted in an increase of 7 μg/m3 in concentration, while the meteorological factors led to a decrease of −0.41 μg/m3. In terms of city classification, Q1 is concentrated in the midstream, and PM2.5 is the most challenging pollutant to control. Q2 is concentrated downstream, with relatively high PM2.5 emissions but favorable meteorological conditions. Q3 is concentrated upstream, and there is surplus environmental capacity even with limited meteorological conditions. Cites in Q4 have the most suitable development potential and exhibit a discrete spatial distribution. The research distinguished various categories of pollution and provided insights into the different characteristics of pollution around the Yangtze River Economic Belt. This information has helped the government classify cities and implement specific policies based on their individual situations

High-entropy rare earth stannate ceramics: Acid corrosion resistant radiative cooling materials with high atmospheric transparency window emissivity and high near-infrared solar reflectivity

In response to the development of the concepts of “carbon neutrality” and “carbon peak”, it is critical to developing materials with high near-infrared (NIR) solar reflectivity and high emissivity in the atmospheric transparency window (ATW; 8–13 μm) to advance zero energy consumption radiative cooling technology. To regulate emission and reflection properties, a series of high-entropy rare earth stannate ceramics (HE-RE2Sn2O7: (Y0.2La0.2Nd0.2Eu0.2Gd0.2)2Sn2O7, (Y0.2La0.2Sm0.2Eu0.2Lu0.2)2Sn2O7, and (Y0.2La0.2Gd0.2Yb0.2Lu0.2)2Sn2O7) with severe lattice distortion were prepared using a solid phase reaction followed by a pressureless sintering method for the first time. Lattice distortion is accomplished by introducing rare earth elements with different cation radii and mass. The as-synthesized HE-RE2Sn2O7 ceramics possess high ATW emissivity (91.38%–95.41%), high NIR solar reflectivity (92.74%–97.62%), low thermal conductivity (1.080–1.619 W·m−1·K−1), and excellent chemical stability. On the one hand, the lattice distortion intensifies the asymmetry of the structural unit to cause a notable alteration in the electric dipole moment, ultimately enlarging the ATW emissivity. On the other hand, by selecting difficult excitation elements, HE-RE2Sn2O7, which has a wide band gap (Eg), exhibits high NIR solar reflectivity. Hence, the multi-component design can effectively enhance radiative cooling ability of HE-RE2Sn2O7 and provide a novel strategy for developing radiative cooling materials

Coronary angiography enhancement for visualization

High quality visualization on X-ray angiograms is of great significance both for the diagnosis of vessel abnormalities and for coronary interventions. Algorithms for improving the visualization of detailed vascular structures without significantly increasing image noise are currently demanded in the market. A new algorithm called stick-guided lateral inhibition (SGLI) is presented for increasing the visibility of coronary vascular structures. A validation study was set up to compare the SGLI algorithm with the conventional unsharp masking (UM) algorithm on 20 still frames of coronary angiographic images. Ten experienced QCA analysts and nine cardiologists from various centers participated in the validation. Sample scoring value (SSV) and observer agreement value (OAV) were defined to evaluate the validation result, in terms of enhancing performance and observer agreement, respectively. The mean of SSV was concluded to be 77.1 ± 11.9%, indicating that the SGLI algorithm performed significantly better than the UM algorithm (P-value < 0.001). The mean of the OAV was concluded to be 70.3%, indicating that the average agreement with respect to a senior cardiologist was 70.3%. In conclusion, this validation study clearly demonstrates the superiority of the SGLI algorithm in the visualization of coronary arteries from X-ray angiograms

Qishen Yiqi dripping pills for chronic ischaemic heart failure:results of the CACT-IHF randomized clinical trial

10.1002/ehf2.12980ESC Heart Failure763881-389

Study on the evaluation of the clinical effects of traditional chinese medicine in heart failure by complex intervention: protocol of SECETCM-HF

<p>Abstract</p> <p>Background</p> <p>Experts in Traditional Chinese Medicine (TCM) have studied the TCM subject of the pathogenesis of heart failure (HF) for several decades. As a result, the general idea is <it>ben </it>deficiency and <it>biao </it>excess. However, the clinical evaluation system which combined the TCM and western medicine in HF has not been developed yet. The objective is to establish the evaluation index system for the integration of TCM and western medicine. The evaluation indexes which include TCM items will specify the research design and methods.</p> <p>Methods</p> <p>Nine medical centers in different cities in China will participate in the trial. A population of 340 patients with HF will be enrolled through a central randomized system for different test groups. Group A will be treated with only western medicine, while group B with western and Chinese medicine together. The study will last for 12 months from the date of enrollment. The cardiovascular death will be the primary outcome.</p> <p>Discussion</p> <p>By putting the protocol into practice, the clinical effects of TCM for HF will be identified scientifically, objectively as well as rationally. The proper index system which built in the study will be helpful for the clinical effect expression of HF by integrated medicine in future.</p> <p>Trial Registration</p> <p>ChiCTR-TRC-00000059</p

Measuring shape complexity of breast lesions on ultrasound images

ABSTRACT The shapes of malignant breast tumors are more complex than the benign lesions due to their nature of infiltration into surrounding tissues. We investigated the efficacy of shape features and presented a method using polygon shape complexity to improve the discrimination of benign and malignant breast lesions on ultrasound. First, 63 lesions (32 benign and 31 malignant) were segmented by K-way normalized cut with the priori rules on the ultrasound images. Then, the shape measures were computed from the automatically extracted lesion contours. A polygon shape complexity measure (SCM) was introduced to characterize the complexity of breast lesion contour, which was calculated from the polygonal model of lesion contour. Three new statistical parameters were derived from the local integral invariant signatures to quantify the local property of the lesion contour. Receiver operating characteristic (ROC) analysis was carried on to evaluate the performance of each individual shape feature. SCM outperformed the other shape measures, the area under ROC curve (AUC) of SCM was 0.91, and the sensitivity of SCM could reach 0.97 with the specificity 0.66. The measures of shape feature and margin feature were combined in a linear discriminant classifier. The resubstitution and leave-one-out AUC of the linear discriminant classifier were 0.94 and 0.92, respectively. The distinguishing ability of SCM showed that it could be a useful index for the clinical diagnosis and computer-aided diagnosis to reduce the number of unnecessary biopsies