Code-Free Machine Learning Solutions for Microscopy Image Processing: Deep Learning.

In recent years, there has been a significant expansion in the realm of processing microscopy images, thanks to the advent of machine learning techniques. These techniques offer diverse applications for image processing. Currently, numerous methods are used for processing microscopy images in the field of biology, ranging from conventional machine learning algorithms to sophisticated deep learning artificial neural networks with millions of parameters. However, a comprehensive grasp of the intricacies of these methods usually necessitates proficiency in programming and advanced mathematics. In our comprehensive review, we explore various widely used deep learning approaches tailored for the processing of microscopy images. Our emphasis is on algorithms that have gained popularity in the field of biology and have been adapted to cater to users lacking programming expertise. In essence, our target audience comprises biologists interested in exploring the potential of deep learning algorithms, even without programming skills. Throughout the review, we elucidate each algorithm's fundamental concepts and capabilities without delving into mathematical and programming complexities. Crucially, all the highlighted algorithms are accessible on open platforms without requiring code, and we provide detailed descriptions and links within our review. It's essential to recognize that addressing each specific problem demands an individualized approach. Consequently, our focus is not on comparing algorithms but on delineating the problems they are adept at solving. In practical scenarios, researchers typically select multiple algorithms suited to their tasks and experimentally determine the most effective one. It is worth noting that microscopy extends beyond the realm of biology; its applications span diverse fields such as geology and material science. Although our review predominantly centers on biomedical applications, the algorithms and principles outlined here are equally applicable to other scientific domains. Furthermore, a number of the proposed solutions can be modified for use in entirely distinct computer vision cases.

Novel Immortalized Human Multipotent Mesenchymal Stromal Cell Line for Studying Hormonal Signaling.

Multipotent mesenchymal stromal cells (MSCs) integrate hormone and neuromediator signaling to coordinate tissue homeostasis, tissue renewal and regeneration. To facilitate the investigation of MSC biology, stable immortalized cell lines are created (e.g., commercially available ASC52telo). However, the ASC52telo cell line has an impaired adipogenic ability and a depressed response to hormones, including 5-HT, GABA, glutamate, noradrenaline, PTH and insulin compared to primary cells. This markedly reduces the potential of the ASC52telo cell line in studying the mechanisms of hormonal control of MSC's physiology. Here, we have established a novel immortalized culture of adipose tissue-derived MSCs via forced telomerase expression after lentiviral transduction. These immortalized cell cultures demonstrate high proliferative potential (up to 40 passages), delayed senescence, as well as preserved primary culture-like functional activity (sensitivity to hormones, ability to hormonal sensitization and differentiation) and immunophenotype up to 17-26 passages. Meanwhile, primary adipose tissue-derived MSCs usually irreversibly lose their properties by 8-10 passages. Observed characteristics of reported immortalized human MSC cultures make them a feasible model for studying molecular mechanisms, which regulate the functional activities of these cells, especially when primary cultures or commercially available cell lines are not appropriate.

Peripheral 5-HT/HTR6 axis is responsible for obesity-associated hypertension.

Hypertension is one of the major life-threatening complications of obesity. Recently adipose multipotent mesenchymal stromal cells (MSCs) were implicated to the pathogenesis of obesity-associated hypertension. These cells amplify noradrenaline-induced vascular cell contraction via cAMP-mediated signaling pathway. In this study we tested the ability of several cAMP-mediated hormones to affect the adrenergic sensitivity of MSCs and their associated contractility. Despite that adipose MSCs express a plethora of receptors capable of cAMP signaling activation, only 5-HT was able to elevate α1A-adrenoceptor-induced Ca2+ signaling in MSCs. Furthermore, 5-HT markedly enhanced noradrenaline-induced MSCs contractility. Using HTR isoform-specific antagonists followed by CRISPRi-mediated knockdown, we identified that the observed 5-HT effect on MSCs was mediated by the HTR6 isoform. This receptor was previously associated exclusively with 5-HT central nervous system activity. Discovered effect of HTR6 on MSCs contractility points to it as a potential therapeutic target for the prevention and treatment of obesity-associated hypertension.

Advances and Obstacles in Using CRISPR/Cas9 Technology for Non-Coding RNA Gene Knockout in Human Mesenchymal Stromal Cells.

Non-coding RNA (ncRNAs) genes have attracted increasing attention in recent years due to their widespread involvement in physiological and pathological processes and regulatory networks. The study of the function and molecular partners of ncRNAs opens up opportunities for the early diagnosis and treatment of previously incurable diseases. However, the classical "loss-of-function" approach in ncRNA function analysis is challenged due to some specific issues. Here, we have studied the potency of two CRISPR/Cas9 variants, wild-type (SpCas9wt) and nickase (SpCas9D10A) programmable nucleases, for the editing of extended DNA sequences in human mesenchymal stromal cells (MSCs). Editing the genes of fibrosis-related hsa-miR-21-5p and hsa-miR-29c-3p, we have shown that a pair of SpCas9D10A molecules can effectively disrupt miRNA genes within the genomes of MSCs. This leads not only to a decrease in the level of knockout miRNA in MSCs and MSC-produced extracellular vesicles, but also to a change in cell physiology and the antifibrotic properties of the cell secretome. These changes correlate well with previously published data for the knockdown of certain miRNAs. The proposed approach can be used to knock out ncRNA genes within the genomes of MSCs or similar cell types in order to study their function in biological processes.