Duffyborg2483

Finally, the network model is quantitatively analyzed by evaluation indexes from the perspective of bionics. The experimental results show that the DBN network, LeNet5 network, and BP network have synchronous characteristics. And the DBN network and LeNet5 network have certain chaotic characteristics, but there is still a certain distance between the three classical neural networks and actual biological neural networks. The KIII model has certain small-world characteristics in structure, and its network also exhibits synchronization characteristics and chaotic characteristics. Compared with the DBN network, LeNet5 network, and the BP network, the KIII model is closer to the real biological neural network.Visceral leishmaniasis (VL) infection is mostly caused by Leishmania donovani and affects countries worldwide. Despite the need for a safe and effective vaccine against leishmaniasis due to the increased drug resistance, however, no vaccine has yet been licensed for clinical use. This study revolves around the immunoinformatics approach to design a multi-epitope vaccine against VL infection. In this case, the proteome of L. donovani has been investigated, and three host non-homologous and antigenic extracellular secretory proteins have been identified as potential vaccine candidates with low transmembrane helices (≤ 1). The multi-epitope subunit vaccine construct consists of T-cell (cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL)) epitopes accompanied by appropriate adjuvant and linkers. A 372-amino acid vaccine construct has been established with specific characteristics, such as soluble, stable, antigenic, non-allergenic, non-toxic, and non-host homologous. Besides, the tertiary structure of the designed vaccine was modeled and validated. Also, the stability and affinity of the vaccine- TLR4 complex were confirmed by using molecular docking and molecular dynamics (MD) simulation. In addition, in silico immunization assay showed the efficiency of this candidate vaccine to stimulate an effective immune response. Furthermore, the refined vaccine was optimized and cloned in the pET28a (+) vector, and its successful expression was confirmed virtually. However, the experimental validation is required to verify the multi-epitope vaccine efficacy against VL infection.The structural consequences of ongoing mutations on the SARS-CoV-2 spike-protein remains to be fully elucidated. These mutations could change the binding affinity between the virus and its target cell. Moreover, obtaining new mutations would also change the therapeutic efficacy of the designed drug candidates. To evaluate these consequences, 3D structure of a mutant spike protein was predicted and checked for stability, cavity sites, and residue depth. The docking analyses were performed between the 3D model of the mutated spike protein and the ACE2 protein and an engineered therapeutic ACE2 against COVID-19. The obtained results revealed that the N501Y substitution has altered the interaction orientation, augmented the number of interface bonds, and increased the affinity against the ACE2. On the other hand, the P681H mutation contributed to the increased cavity size and relatively higher residue depth. The binding affinity between the engineered therapeutic ACE2 and the mutant spike was significantly higher with a distinguished binding orientation. It could be concluded that the mutant spike protein increased the affinity, preserved the location, changed the orientation, and altered the interface amino acids of its interaction with both the ACE2 and its therapeutic engineered version. The obtained results corroborate the more aggressive nature of mutated SARS-CoV-2 due to their higher binding affinity. Moreover, designed ACe2-baased therapeutics would be still highly effective against covid-19, which could be the result of conserved nature of cellular ACE2.

The online version contains supplementary material available at 10.1007/s10989-021-10346-1.

The online version contains supplementary material available at 10.1007/s10989-021-10346-1.Secondary pulmonary tuberculosis (SPT) is one of the top ten causes of death from a single infectious agent. To recognize SPT more accurately, this paper proposes a novel artificial intelligence model, which uses Pseudo Zernike moment (PZM) as the feature extractor and deep stacked sparse autoencoder (DSSAE) as the classifier. In addition, 18-way data augmentation is employed to avoid overfitting. This model is abbreviated as PZM-DSSAE. The ten runs of 10-fold cross-validation show this model achieves a sensitivity of 93.33% ± 1.47%, a specificity of 93.13% ± 0.95%, a precision of 93.15% ± 0.89%, an accuracy of 93.23% ± 0.81%, and an F1 score of 93.23% ± 0.83%. The area-under-curve reaches 0.9739. This PZM-DSSAE is superior to 5 state-of-the-art approaches.B-cell epitope prediction research has received growing interest since the development of the first method. B-cell epitope identification with the aid of an accurate prediction method is one of the most important steps in epitope-based vaccine development, immunodiagnostic testing, antibody production, disease diagnosis, and treatment. Nevertheless, using experimental methods in epitope mapping is very time-consuming, costly, and labor-intensive. Therefore, although successful predictions with in silico methods are very important in epitope prediction, there are limited studies in this area. The aim of this study is to propose a new approach for successfully predicting B-cell epitopes for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, the SARS-CoV B-cell epitope prediction performances of different fuzzy learning classification models genetic cooperative competitive learning (GCCL), fuzzy genetics-based machine learning (GBML), Chi's method (CHI), Ishibuchi's method with weight fe outbreaks of the coronavirus family, especially SARS-CoV-2 and its possible mutations.The most prevalent cause of mortality and morbidity worldwide is acute coronary syndrome (ACS) and its consequences. Exposure to particulate matter (PM) from air pollution has been shown to impair both. Various plausible pathogenic mechanisms have been identified, including microRNAs (miRNAs), an epigenetic regulator for gene expression. Endogenous miRNAs, average 22-nucleotide RNAs (ribonucleic acid), regulate gene expression through mRNA cleavage or translation repression and can influence proinflammatory gene expression posttranscriptionally. However, little is known about miRNA responses to fine PM (PM2.5, PM10, ultrafine particles, black carbon, and polycyclic aromatic hydrocarbon) from air pollution and their potential contribution to cardiovascular consequences, including systemic inflammation regulation. For the past decades, microRNAs (miRNAs) have emerged as novel, prospective diagnostic and prognostic biomarkers in various illnesses, including ACS. We wanted to outline some of the most important studies in the field and address the possible utility of miRNAs in regulating particulate matter-induced ACS (PMIA) on inflammatory factors in this review.Wearing surgical masks remains the most effective protective measure against COVID-19 before mass vaccination, but insufficient comfortability and low antibacterial/antiviral activities accelerate the replacement frequency of surgical masks, resulting in large amounts of medical waste. To solve this problem, we report new nanofiber membrane masks with outstanding comfortability and anti-pathogen functionality prepared using fluorinated carbon nanofibers/carbon fiber (F-CNFs/CF). This was used to replace commercial polypropylene (PP) nonwovens as the core layer of face masks. The through-plane and in-plane thermal conductivity of commercial PP nonwovens were only 0.12 and 0.20 W/m K, but the F-CNFs/CF nanofiber membranes reached 0.62 and 5.23 W/m K, which represent enhancements of 380% and 2523%, respectively. The surface temperature of the PP surgical masks was 23.9 ℃ when the wearing time was 15 min, while the F-CNFs/CF nanocomposite fibrous masks reached 27.3 ℃, displaying stronger heat dissipation. Moreover, the F-CNFs/CF nanofiber membranes displayed excellent electrical conductivity and produced a high-temperature layer that killed viruses and bacteria in the masks. The surface temperature of the F-CNFs/CF nanocomposite fibrous masks reached 69.2 ℃ after being connected to a portable power source for 60 s. Their antibacterial rates were 97.9% and 98.6% against E. coli and S. aureus, respectively, after being connected to a portable power source for 30 min.Imperial County, California, is a high-need, medically underserved area that has some of the worst overall health outcomes of all California counties. Given this and the high depression and anxiety rates in agricultural occupations, Imperial County farmers and ranchers may be at an increased risk of stress and poor mental health outcomes. An exploratory mixed methods assessment was used to collect information from 24 farmers and ranchers in Imperial County. Survey topics included questions about farm or ranch operations, farm-related stress, mental health, community support, and health behaviors. The results indicate that most respondents perceive unpredictable factors, such as government regulations, as the most impactful stressors related to their farm or ranch operations. Additionally, depression symptomatology scores were positively correlated with respondents' ability to obtain credit. DLin-KC2-DMA solubility dmso Efforts to understand farm-related stress and how community support can help Imperial County farmers and ranchers mediate adverse physical and mental health effects through formal and informal networks are considered.Detection and quantification of biotargets are important analytical tasks, which are solved using a wide range of various methods. In recent years, methods based on the isothermal amplification of nucleic acids (NAs) have been extensively developed. Among them, a special place is occupied by rolling circle amplification (RCA), which is used not only for the detection of a specific NA but also for the analysis of other biomolecules, and is also a versatile platform for the development of highly sensitive methods and convenient diagnostic devices. The present review reveals a number of methodical aspects of RCA-mediated analysis; in particular, the data on its key molecular participants are presented, the methods for increasing the efficiency and productivity of RCA are described, and different variants of reporter systems are briefly characterized. Differences in the techniques of RCA-mediated analysis of biotargets of various types are shown. Some examples of using different RCA variants for the solution of specific diagnostic problems are given.Azaadamantanes are nitrogen-containing analogs of adamantane, which contain one or more nitrogen atoms instead of carbon atoms. This substitution leads to several specific chemical and physical properties. The azaadamantane derivatives have less lipophilicity compared to their adamantane analogs, which affects both their interaction with biological targets and bioavailability. The significant increase in the number of publications during the last decade (2009-2020) concerning the study of reactivity and biological activity of azaadamantanes and their derivatives indicates a great theoretical and practical interest in these compounds. Compounds with pronounced biological activity have been already discovered among azaadamantane derivatives. The review is devoted to the biological activity of azaadamantanes and their derivatives. It presents the main methods for the synthesis of di- and triazaadamantanes and summarizes the accumulated data on studying the biological activity of these compounds. The prospects for the use of azaadamantanes in medical chemistry and pharmacology are discussed.