Proteins, under conditions of cellular stress, typically tend to unfold and form lethal aggregates leading to neurological diseases like Parkinson's and Alzheimer's. A clear understanding of the conditions that favor dis-aggregation and restore the cell to its healthy state after they have been stressed is therefore important in dealing with these diseases. The heat shock response (HSR) mechanism is a signaling network that deals with these undue protein aggregates and aids in the maintenance of homeostasis within a cell. This framework, on its own, is a mathematically well studied mechanism. However, not much is known about how the various intermediate mis-folded protein states of the aggregation process interact with some of the key components of the HSR pathway such as the Heat Shock Protein (HSP), the Heat Shock Transcription Factor (HSF) and the HSP-HSF complex. In this article, using kinetic parameters from the literature, we propose and analyze two mathematical models for HSR that also include explicit reactions for the formation of protein aggregates. Deterministic analysis and stochastic simulations of these models show that the folded proteins and the misfolded aggregates exhibit bistability in a certain region of the parameter space. Further, the models also highlight the role of HSF and the HSF-HSP complex in reducing the time lag of response to stress and in re-folding all the mis-folded proteins back to their native state. These models, therefore, call attention to the significance of studying related pathways such as the HSR and the protein aggregation and re-folding process in conjunction with each other. Discover possible Drug Target Interactions (DTIs) is a decisive step in the detection of the effects of drugs as well as drug repositioning. There is a strong incentive to develop effective computational methods that can effectively predict potential DTIs, as traditional DTI laboratory experiments are expensive, time-consuming, and labor-intensive. Some technologies have been developed for this purpose, however large numbers of interactions have not yet been detected, the accuracy of their prediction still low, and protein sequences and structured data are rarely used together in the prediction process. This paper presents DTIs prediction model that takes advantage of the special capacity of the structured form of proteins and drugs. Our model obtains features from protein amino-acid sequences using physical and chemical properties, and from drugs smiles (Simplified Molecular Input Line Entry System) strings using encoding techniques. https://www.selleckchem.com/products/BEZ235.html Comparing the proposed model with different existing methods under K-foB05203 are predicted with 100 % accuracy to interact with ACE2 protein. This protein is a self-membrane protein that enables Covid-19 infection. Hence, our model can be used as an effective tool in drug reposition to predict possible drug treatments for Covid-19. Small for gestational age (SGA) and large for gestational age (LGA) newborns are at increased risk for developmental, metabolic and cardiovascular morbidities. To compare the metabolic biomarkers of SGA and LGA infants with those of appropriate for gestational age (AGA) newborns in order to shed more light on a possible pathogenesis of those morbidities. An observational retrospective study. 70,809 term newborns divided into AGA, SGA, LGA, and severe subcategories (<3rd percentile or ≥97th percentile). 18 metabolites were measured by dried blood tandem mass spectrometry and compared in between groups in univariate and multivariate logistic regression. SGA newborns had a significant likelihood for elevated methionine, proline, free carnitine, and reduced valine levels compared to AGA newborns (P<.0001). Severe SGA showed more apparent trends including elevated leucine. LGA newborns had a significant likelihood for low citrulline, glutamine, proline, tyrosine, and elevated leucine levels (P≤.0033). Severe LGA newborns showed the same trends, with the exception of citrulline and glutamine. SGA and LGA newborns demonstrate distinct metabolic biomarkers in newborn screening. Most of the altered metabolites in the SGA group were elevated while those in the LGA group were decreased in comparison to AGA newborns. These trends were more apparent in the severe SGA subgroup while they mostly remained the same in the severe LGA subgroup. Whether these metabolic changes are involved with or can predict long-term outcome awaits further trials. SGA and LGA newborns demonstrate distinct metabolic biomarkers in newborn screening. Most of the altered metabolites in the SGA group were elevated while those in the LGA group were decreased in comparison to AGA newborns. These trends were more apparent in the severe SGA subgroup while they mostly remained the same in the severe LGA subgroup. Whether these metabolic changes are involved with or can predict long-term outcome awaits further trials.Circulating inflammatory factor inorganic polyphosphate (polyP) released from activated platelets could enhance factor XII and bradykinin resulted in increased capillary leakage and vascular permeability. PolyP induce inflammatory responses through mTOR pathway in endothelial cells, which is being reported in several diseases including atherosclerosis, thrombosis, sepsis, and cancer. Systems and molecular biology approaches were used to explore the regulatory role of the AMPK activator, metformin, on polyP-induced hyper-permeability in different organs in three different models of polyP-induced hyper-permeability including local, systemic short- and systemic long-term approaches in murine models. Our results showed that polyP disrupts endothelial barrier integrity in skin, liver, kidney, brain, heart, and lung in all three study models and metformin abrogates the disruptive effect of polyP. We also showed that activation of AMPK signaling pathway, regulation of oxidant/anti-oxidant balance, as well as decrease in inflammatory cell infiltration constitute a set of molecular mechanisms through which metformin elicits it's protective responses against polyP-induced hyper-permeability. These results support the clinical values of AMPK activators including the FDA-approved metformin in attenuating vascular damage in polyP-associated inflammatory diseases.