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The tetrapeptide tuftsin effectively impairs the binding of SARS-CoV-2 S1 to ACE2

In their recent study posted to the preprint server bioRxiv , the researchers from China have shown that tuftsin, a natural phagocytosis-stimulating peptide, can effectively impair the binding of SARS-CoV-2 spike S1 subunit to ACE2 receptor in a dose-dependent manner and therefore can be considered a potential drug against SARS-CoV-2 infection. ....

Image Credit , Coronavirus Disease Covid 19 , Ars Cov 2 , Binding Affinity , Covid 19 , Evere Acute Respiratory , Evere Acute Respiratory Syndrome ,

Frontiers | GPX7 Is Targeted by miR-29b and GPX7 Knockdown Enhances Ferroptosis Induced by Erastin in Glioma

Background Glioma is a lethal primary tumor of central nervous system. Ferroptosis is a newly identified form of necrotic cell death. Triggering ferroptosis has shown potential to eliminate aggressive tumors. GPX7, a member of glutathione peroxidase family (GPXs), has been described to participate in oxidative stress and tumorigenesis. However, the biological functions of GPX7 in glioma are still unknown. Methods Bioinformatics method was used to assess the prognostic role of GPX7 in glioma. CCK8, wound healing, transwell and cell apoptosis assays were performed to explore the functions of GPX7 in glioma cells. In vivo experiment was also conducted to confirm in vitro findings. Ferroptosis-related assays were carried out to investigate the association between GPX7 and ferroptosis in glioma. Results GPX7 was aberrantly expressed in glioma and higher expression of GPX7 was correlated with adverse outcomes. GPX7 silencing enhanced ferroptosis-related oxidative stress in glioma cells and t ....

United States , United Kingdom , Dunfa Peng , Biochim Biophys Acta , Silva Mcda , Chin Neurosurg , Duttaa Micrornas , Liuy Erastin , Zheng Chen , Extensive Network , Huanhu Hospital Department Of Neurosurgery , Beina Chuanglian Biotechnology Institute , Dojindo Molecular Technology , Sunz Global Research Trends Of Ferroptosis , Cell Bioscience Inc , Committee Of Tianjin Huanhu Hospital , National Natural Science Foundation Of China , Sibeifu Beijing Biotechnology Co , Jackson Immunoresearch Inc , Pathology Department Of Huanhu Hospital , Detection Kit Solarbio Co , Technology Commission , Implications For Cancer Development , Chinese Glioma Genome Atlas , Cancer Genome Atlas , Gene Expression Ominibus ,

Exploring biological characteristics of SARS-CoV-2-induced myocardial damage

In a new study, researchers used bioinformatics tools to explore the biological characteristics of SARS-CoV-2-infected myocardium. ....

Aimee Molineux , Neha Mathur , Neha Mathurjan , Kateryna Kon Shutterstock , Image Credit , Connectivity Map , Coronavirus Disease Covid 19 , Ars Cov 2 , Covid 19 , N Vitro , N Vivo , Evere Acute Respiratory , Evere Acute Respiratory Syndrome , Ignaling Pathway ,

Dolomite Bio announce new affordable Bioinformatics service

The Bioinformatics service hopes to allow for easy forecasting and hassle-free RNA-Sequencing ....

Bio Rnadia , Xuan Nguyen , Bioinformatics Service , Product News , Dolomite Bio , Bioinformatics Leader , Dolomite Bio Announce Launch Of Cost Effective Bioinformatics Service With Brand New Rnadia Kit For Single Cell Research ,

"Trustworthy Deep Neural Network for Inferring Anticancer Synergistic C" by Muhammad Alsherbiny, Ibrahim Radwan et al.

The lack of a gold standard synergy quantification method for chemotherapeutic drug combinations warrants the consideration of different synergy metrics to develop efficient predictive models. Furthermore, neglecting combination sensitivity may lead to biased synergistic combinations, which are ineffective in cancer treatment. In this paper, we propose a deep learning-based model, SynPredict, which effectively predicts synergy in five synergy metrics together with the combination sensitivity score. SynPredict assesses the impact of multimodal fusion architectures of the input data, including the gene expression data of cancer cells, along with the representative chemical features of drugs in pairwise combinations. Both ONEIL and ALMANAC anticancer combination datasets are employed comparatively. The impact of the training datasets was more significant and consistent across most synergy models than input data fusion architectures. Synpredict outperforms the state-of-the-art predictive m ....

Anticancer Cocktails , Ombination Sensitivity Score , Deep Learning , Arly Fusion , Ntermediate Fusion , Predictive Models , Ynergistic Combinations , Ynergy Metrics ,