Identification of Phase-Separation-Protein-Related Function Based on Gene Ontology by Using Machine Learning Methods

Phase-separation proteins (PSPs) are a class of proteins that play a role in the process of liquid–liquid phase separation, which is a mechanism that mediates the formation of membranelle compartments in cells. Identifying phase separation proteins and their associated function could provide insights into cellular biology and the development of diseases, such as neurodegenerative diseases and cancer. Here, PSPs and non-PSPs that have been experimentally validated in earlier studies were gathered as positive and negative samples. Each protein’s corresponding Gene Ontology (GO) terms were extracted and used to create a 24,907-dimensional binary vector. The purpose was to extract essential GO terms that can describe essential functions of PSPs and build efficient classifiers to identify PSPs with these GO terms at the same time. To this end, the incremental feature selection computational framework and an integrated feature analysis scheme, containing categorical boosting, least absolute shrinkage and selection operator, light gradient-boosting machine, extreme gradient boosting, and permutation feature importance, were used to build efficient classifiers and identify GO terms with classification-related importance. A set of random forest (RF) classifiers with F1 scores over 0.960 were established to distinguish PSPs from non-PSPs. A number of GO terms that are crucial for distinguishing between PSPs and non-PSPs were found, including GO:0003723, which is related to a biological process involving RNA binding; GO:0016020, which is related to membrane formation; and GO:0045202, which is related to the function of synapses. This study offered recommendations for future research aimed at determining the functional roles of PSPs in cellular processes by developing efficient RF classifiers and identifying the representative GO terms related to PSPs

Research on the RBF-PID control method for the motor actuator used in a UHV GIS disconnector

To improve the reliability and intelligent level of the AC transmission system, the radial basis function-based proportional-integral-derivative (RBF-PID) control method for the motor actuator used in the 550 kV gas-insulated switchgear (GIS) disconnector is proposed. According to the dynamic mathematical model of the motor actuator, the main structure of the RBF neural network based on the gradient descent method for learning algorithm is constructed. An identification function is formed by taking values of the output error square, and then by gathering information on the real-time tuning parameters of PID. Based on that, the simulation of the control system is constructed. The comparative analyses of the tracking control characteristics and the servo following error of the disconnector's contact speed between double-loop PID and RBF-PID are done through the computational and experiment methods, respectively. The results show that 550 kV GIS disconnector with the motor actuator by the RFB-PID control method has better controllability, and the servo following error is controlled within 0.1 m/s

Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method

SARS-CoV-2 shows great evolutionary capacity through a high frequency of genomic variation during transmission. Evolved SARS-CoV-2 often demonstrates resistance to previous vaccines and can cause poor clinical status in patients. Mutations in the SARS-CoV-2 genome involve mutations in structural and nonstructural proteins, and some of these proteins such as spike proteins have been shown to be directly associated with the clinical status of patients with severe COVID-19 pneumonia. In this study, we collected genome-wide mutation information of virulent strains and the severity of COVID-19 pneumonia in patients varying depending on their clinical status. Important protein mutations and untranslated region mutations were extracted using machine learning methods. First, through Boruta and four ranking algorithms (least absolute shrinkage and selection operator, light gradient boosting machine, max-relevance and min-redundancy, and Monte Carlo feature selection), mutations that were highly correlated with the clinical status of the patients were screened out and sorted in four feature lists. Some mutations such as D614G and V1176F were shown to be associated with viral infectivity. Moreover, previously unreported mutations such as A320V of nsp14 and I164ILV of nsp14 were also identified, which suggests their potential roles. We then applied the incremental feature selection method to each feature list to construct efficient classifiers, which can be directly used to distinguish the clinical status of COVID-19 patients. Meanwhile, four sets of quantitative rules were set up, which can help us to more intuitively understand the role of each mutation in differentiating the clinical status of COVID-19 patients. Identified key mutations linked to virologic properties will help better understand the mechanisms of infection and will aid in the development of antiviral treatments

Electropolymerization Fabrication of Co Phosphate Nanoparticles Encapsulated in N,P-Codoped Mesoporous Carbon Networks as a 3D Integrated Electrode for Full Water Splitting

The development of high-performance nonprecious electrocatalysts toward both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is of great significance for overall water splitting but remains a grand challenge. In this study, Co phosphate (CP) nanoparticles encapsulated in three-dimensional porous N,P-codoped carbon networks (NPC) were fabricated by direct growth on carbon cloth (CC), which were further used as an integrated three-dimensional (3D) electrode for cost-effective and energy efficient HER and OER both in acid and alkaline medium. Impressively, the as-obtained flexible integrated electrode exhibited excellent activities and robust stability, due to the unique 3D architecture with improved electron transport capability, high number of active sites, and channels for reactant/product transfer. Our experimental results show significantly enhanced performance for such engineered nanostructures due to the synergistic effect from nanoparticles encapsulation and nitrogen and phosphorus doping on carbon structures. Such an versatile electrode can serve as a bifunctional catalyst for overall water splitting with excellent catalytic performance and durability in a more direct and simple way, which reduces the production cost of practical technological devices. The new design demonstrated here opened avenues for simple, low-cost, and scalable manufacture of high performance bifunctional catalysts for renewable energy technologies

Cardiac ankyrin repeat protein attenuates cardiomyocyte apoptosis by upregulation of Bcl-2 expression

Cardiac ankyrin repeat protein (CARP) is a nuclear transcriptional co-factor that has additional functions in the myoplasm as a component of the muscle sarcomere. Previous studies have demonstrated increased expression of CARP in cardiovascular diseases, however, its role in cardiomyocyte apoptosis is unclear and controversial. In the present study, we investigated possible roles of CARP in hypoxia/reoxygenation (H/R) -induced cardiomyocyte apoptosis and the underlying mechanisms. Neonatal mouse ventricular cardiomyocytes were isolated and infected with adenovirus encoding Flag-tagged CARP (Ad-CARP) and lentivirus encoding CARP targeted shRNA (sh-CARP), respectively. Cardiomyocyte apoptosis induced by exposure to H/R conditions was evaluated by TUNEL staining and western blot analysis of cleaved caspase-3. The results showed that H/R-induced apoptosis was significantly decreased in Ad-CARP cardiomyocytes and increased in sh-CARP cardiomyocytes, suggesting a protective anti-apoptosis role for CARP. Interestingly, over-expressed CARP was mainly distributed in the nucleus, consistent with its role in regulating transcriptional activity. qPCR analysis showed that Bcl-2 transcripts were significantly increased in Ad-CARP cardiomyocytes. ChIP and co-IP assays confirmed the binding of CARP to the Bcl-2 promoter through interaction with transcription factor GATA4. Collectively, our results suggest that CARP can protect against H/R induced cardiomyocyte apoptosis, possibly through increasing anti-apoptosis Bcl-2 gene expression