Space exploration has progressed from contemporary discoveries to current endeavors, such as space tourism and Mars missions. As human activity in space accelerates, understanding the physiological effects of microgravity on the human body is becoming increasingly critical. This study analyzes transcriptomic data from human cell lines exposed to microgravity, investigates its effects on gene expression, and identifies potential therapeutic interventions for health challenges posed by spaceflight. Our analysis identified five under-expressed genes (, , , , ) and six over-expressed genes (, , , , , ), all of which exhibited distinct expression patterns in response to microgravity. Enrichment analysis highlighted significant biological functions influenced by these conditions, while in silico drug repurposing identified potential modulators that could counteract these changes. This study introduces a novel approach to addressing health challenges during space missions by repurposing existing drugs and identifies specific genes and pathways as potential biomarkers for microgravity effects on human health. Our findings represent the first systematic effort to repurpose drugs for spaceflight, establishing a foundation for the development of targeted therapies for astronauts. Future research should aim to validate these findings in authentic space environments and explore broader biological impacts.
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http://dx.doi.org/10.3390/ijms26031287 | DOI Listing |
ACS Synth Biol
March 2025
Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.
Cell-free synthetic biology biosensors have potential as effective diagnostic technologies for the detection of chemical compounds, such as toxins and human health biomarkers. They have several advantages over conventional laboratory-based diagnostic approaches, including the ability to be assembled, freeze-dried, distributed, and then used at the point of need. This makes them an attractive platform for cheap and rapid chemical detection across the globe.
View Article and Find Full Text PDFIt is known that inhibition of the endoplasmic reticulum transmembrane signaling protein (ERN1) suppresses the glioblastoma cells proliferation. The present study aims to investigate the impact of inhibition of ERN1 endoribonuclease and protein kinase activities on the , , and gene expression in U87MG glioblastoma cells with an intent to reveal the role of ERN1 signaling in the regulation of expression of these genes. The U87MG glioblastoma cells with inhibited ERN1 endoribonuclease (dnrERN1) or both enzymatic activities of ERN1 (endoribonuclease and protein kinase; dnERN1) were used.
View Article and Find Full Text PDFEndocr Regul
January 2025
1Department of Molecular Biology, Palladin Institute of Biochemistry, National Academy of Sciences of Ukraine, Kyiv, Ukraine.
For the effective growth of malignant tumors, including glioblastoma, the necessary factors involve endoplasmic reticulum (ER) stress, hypoxia, and the availability of nutrients, particularly glucose. The ER degradation enhancing alpha-mannosidase like protein 1 (EDEM1) is involved in ER-associated degradation (ERAD) targeting misfolded glycoproteins for degradation in an N-glycan-independent manner. EDEM1 was also identified as a new modulator of insulin synthesis and secretion.
View Article and Find Full Text PDFAm J Drug Alcohol Abuse
March 2025
Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV, USA.
Females remain underrepresented in opioid use disorder (OUD) research, particularly regarding dorsal striatal neuroadaptations. Chaperonins seem to play a role in opioid-induced neural plasticity, yet their contribution to OUD-related changes in the dorsal striatum (DS) remains poorly understood. Given known sex differences in opioid sensitivity, it is important to determine how chaperonin expression contributes to OUD-related adaptations in females.
View Article and Find Full Text PDFBioinformatics
March 2025
Department of Computer Science, University of Turin, Torino, 10123, Italy.
Motivation: Computational models are crucial for addressing critical questions about systems evolution and deciphering system connections. The pivotal feature of making this concept recognisable from the biological and clinical community is the possibility of quickly inspecting the whole system, bearing in mind the different granularity levels of its components. This holistic view of system behaviour expands the evolution study by identifying the heterogeneous behaviours applicable, for example, to the cancer evolution study.
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