A view of the genetic and proteomic profile of extracellular matrix molecules in aging and stroke

IntroductionModification of the extracellular matrix (ECM) is one of the major processes in the pathology of brain damage following an ischemic stroke. However, our understanding of how age-related ECM alterations may affect stroke pathophysiology and its outcome is still very limited.MethodsWe conducted an ECM-targeted re-analysis of our previously obtained RNA-Seq dataset of aging, ischemic stroke and their interactions in young adult (3-month-old) and aged (18-month-old) mice. The permanent middle cerebral artery occlusion (pMCAo) in rodents was used as a model of ischemic stroke. Altogether 56 genes of interest were chosen for this study.ResultsWe identified an increased activation of the genes encoding proteins related to ECM degradation, such as matrix metalloproteinases (MMPs), proteases of a disintegrin and metalloproteinase with the thrombospondin motifs (ADAMTS) family and molecules that regulate their activity, tissue inhibitors of metalloproteinases (TIMPs). Moreover, significant upregulation was also detected in the mRNA of other ECM molecules, such as proteoglycans, syndecans and link proteins. Notably, we identified 8 genes where this upregulation was enhanced in aged mice in comparison with the young ones. Ischemia evoked a significant downregulation in only 6 of our genes of interest, including those encoding proteins associated with the protective function of ECM molecules (e.g., brevican, Hapln4, Sparcl1); downregulation in brevican was more prominent in aged mice. The study was expanded by proteome analysis, where we observed an ischemia-induced overexpression in three proteins, which are associated with neuroinflammation (fibronectin and vitronectin) and neurodegeneration (link protein Hapln2). In fibronectin and Hapln2, this overexpression was more pronounced in aged post-ischemic animals.ConclusionBased on these results, we can conclude that the ratio between the protecting and degrading mechanisms in the aged brain is shifted toward degradation and contributes to the aged tissues’ increased sensitivity to ischemic insults. Altogether, our data provide fresh perspectives on the processes underlying ischemic injury in the aging brain and serve as a freely accessible resource for upcoming research

Platforms for Single-Cell Collection and Analysis

Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS). In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments

Application of cardio-forecasting for evaluation of human-operator performance

The paper presents the results of the development of the cardio-forecasting technology, which introduces a new method to monitor the state of human-operator, which is characteristic for the given production conditions and for individual operators, to predict the moment of exhaustion of his/her working capacity. The work aims to demonstrate the unique, distinctive features of the cardio-forecasting technology for predicting an individual limit of his/her working capacity for each person. A unique methodology for predicting individually for each person the moment when he/she reaches the limit of his/her working capacity is based on a spectral analysis of a human phonocardiogram in order to isolate the frequency component located at the heart contraction frequency. The trend of the amplitude of this component is approximated by its model; consequently, the coefficients of the trend model are determined. They include the operator’s operating time until his/her working capacity is exhausted. A methodology for predicting the moment when he/she reaches the limit of his/her working capacity for each person individually and assessment based on this degree of criticality of their condition will be realized as a software application for smartphones using the Android operating system.project KEG