Mediaboss Marketing

Afshinnekoo, E. et al. Fundamental biological features of spaceflight: advancing the field to enable deep-space exploration. Cell 183, 11621184 (2020).

Article Google Scholar

Loftus, D. J., Rask, J. C., McCrossin, C. G. & Tranfield, E. M. The chemical reactivity of lunar dust: from toxicity to astrobiology. Earth Moon Planets 107, 95105 (2010).

Article Google Scholar

Pohlen, M., Carroll, D., Prisk, G. K. & Sawyer, A. J. Overview of lunar dust toxicity risk. NPJ Microgravity 8, 55 (2022).

Paul, A.-L. & Ferl, R. J. The biology of low atmospheric pressureimplications for exploration mission design and advanced life support. Am. Soc. Gravit. Space Biol. 19, 317 (2005).

Council, N. R. Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era (National Academies Press, 2011).

Goswami, N. et al. Maximizing information from space data resources: a case for expanding integration across research disciplines. Eur. J. Appl. Physiol. 113, 16451654 (2013).

Article Google Scholar

Nangle, S. N. et al. The case for biotech on Mars. Nat. Biotechnol. 38, 401407 (2020).

Article Google Scholar

Costes, S. V., Sanders, L. M. & Scott, R. T. Workshop on Artificial Intelligence & Modeling for Space Biology. Zenodo https://doi.org/10.5281/zenodo.7508535 (2023).

Jordan, M. I. & Mitchell, T. M. Machine learning: trends, perspectives, and prospects. Science 349, 255260 (2015).

Article MathSciNet MATH Google Scholar

Topol, E. J. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again (Basic Books, 2019).

Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 25, 4456 (2019).

Article Google Scholar

Scott, R. T. et al. Biomonitoring and precision health in deep space supported by artificial intelligence. Nat. Mach. Intell. https://doi.org/10.1038/s42256-023-00617-5 (2023).

National Academies of Sciences, Engineering, and Medicine, Policy and Global Affairs, Board on Research Data and Information & Committee on Toward an Open Science Enterprise Open Science by Design: Realizing a Vision for 21st Century Research (National Academies Press, 2018).

Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).

Article Google Scholar

Berrios, D. C., Beheshti, A. & Costes, S. V. FAIRness and usability for open-access omics data systems. AMIA Annu. Symp. Proc. 2018, 232241 (2018).

Google Scholar

Low, L. A. & Giulianotti, M. A. Tissue chips in space: modeling human diseases in microgravity. Pharm. Res. 37, 8 (2019).

Article Google Scholar

Ronca, A. E., Souza, K. A. & Mains, R. C. (eds) Translational Cell and Animal Research in Space: 19652011 NASA Special Publication NASA/SP-2015-625 (NASA Ames Research Center, 2016).

Alwood, J. S. et al. From the bench to exploration medicine: NASA life sciences translational research for human exploration and habitation missions. NPJ Microgravity 3, 5 (2017).

Schatten, H., Lewis, M. L. & Chakrabarti, A. Spaceflight and clinorotation cause cytoskeleton and mitochondria changes and increases in apoptosis in cultured cells. Acta Astronaut. 49, 399418 (2001).

Article Google Scholar

Shi, L. et al. Spaceflight and simulated microgravity suppresses macrophage development via altered RAS/ERK/NFB and metabolic pathways. Cell. Mol. Immunol. 18, 14891502 (2021).

Article Google Scholar

Ferl, R. J., Koh, J., Denison, F. & Paul, A.-L. Spaceflight induces specific alterations in the proteomes of Arabidopsis. Astrobiology 15, 3256 (2015).

Article Google Scholar

Ou, X. et al. Spaceflight induces both transient and heritable alterations in DNA methylation and gene expression in rice (Oryza sativa L.). Mutat. Res. 662, 4453 (2009).

Article Google Scholar

Overbey, E. G. et al. Spaceflight influences gene expression, photoreceptor integrity, and oxidative stress-related damage in the murine retina. Sci. Rep. 9, 13304 (2019).

Article Google Scholar

Clment, G. & Slenzka, K. Fundamentals of Space Biology: Research on Cells, Animals, and Plants in Space (Springer Science & Business Media, 2006).

Yeung, C. K. et al. Tissue chips in space-challenges and opportunities. Clin. Transl. Sci. 13, 810 (2020).

Article Google Scholar

Low, L. A., Mummery, C., Berridge, B. R., Austin, C. P. & Tagle, D. A. Organs-on-chips: into the next decade. Nat. Rev. Drug Discov. 20, 345361 (2021).

Article Google Scholar

Globus, R. K. & Morey-Holton, E. Hindlimb unloading: rodent analog for microgravity. J. Appl. Physiol. 120, 11961206 (2016).

Article Google Scholar

Simonsen, L. C., Slaba, T. C., Guida, P. & Rusek, A. NASAs first ground-based Galactic cosmic ray simulator: enabling a new era in space radiobiology research. PLoS Biol. 18, e3000669 (2020).

Article Google Scholar

Buckey, J. C. Jr & Homick, J. L. The Neurolab Spacelab Mission: Neuroscience Research in Space: Results from the STS-90, Neurolab Spacelab Mission. NASA Technical Reports Server (NASA, 2003).

Diallo, O. N. et al. Impact of the International Space Station Research Results. NASA Technical Reports Server (NASA, 2019).

Vandenbrink, J. P. & Kiss, J. Z. Space, the final frontier: a critical review of recent experiments performed in microgravity. Plant Sci. 243, 115119 (2016).

Article Google Scholar

Massaro Tieze, S., Liddell, L. C., Santa Maria, S. R. & Bhattacharya, S. BioSentinel: a biological CubeSat for deep space exploration. Astrobiology https://doi.org/10.1089/ast.2019.2068 (2020).

Ricco, A. J., Maria, S. R. S., Hanel, R. P. & Bhattacharya, S. BioSentinel: a 6U nanosatellite for deep-space biological science. IEEE Aerospace Electron. Syst. Mag. 35, 618 (2020).

Article Google Scholar

Chen, Y. et al. Automated cells-to-peptides sample preparation workflow for high-throughput, quantitative proteomic assays of microbes. J. Proteome Res. 18, 37523761 (2019).

Article Google Scholar

Zampieri, M., Sekar, K., Zamboni, N. & Sauer, U. Frontiers of high-throughput metabolomics. Curr. Opin. Chem. Biol. 36, 1523 (2017).

Article Google Scholar

Stephens, Z. D. et al. Big data: astronomical or genomical? PLoS Biol. 13, e1002195 (2015).

Article Google Scholar

Tomczak, K., Czerwiska, P. & Wiznerowicz, M. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemp. Oncol. 19, A68A77 (2015).

Google Scholar

Lonsdale, J. et al. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580585 (2013).

Article Google Scholar

Atta, L. & Fan, J. Computational challenges and opportunities in spatially resolved transcriptomic data analysis. Nat. Commun. 12, 5283 (2021).

Article Google Scholar

Marx, V. Method of the year: spatially resolved transcriptomics. Nat. Methods 18, 914 (2021).

Article Google Scholar

Deamer, D., Akeson, M. & Branton, D. Three decades of nanopore sequencing. Nat. Biotechnol. 34, 518524 (2016).

Article Google Scholar

Mardis, E. R. DNA sequencing technologies: 20062016. Nat. Protoc. 12, 213218 (2017).

Article Google Scholar

Stuart, T. & Satija, R. Integrative single-cell analysis. Nat. Rev. Genet. 20, 257272 (2019).

Article Google Scholar

Asp, M. et al. A spatiotemporal organ-wide gene expression and cell atlas of the developing human heart. Cell 179, 16471660.e19 (2019).

Article Google Scholar

Giacomello, S. et al. Spatially resolved transcriptome profiling in model plant species. Nat Plants 3, 17061 (2017).

Article Google Scholar

Mao, X. W. et al. Characterization of mouse ocular response to a 35-day spaceflight mission: evidence of blood-retinal barrier disruption and ocular adaptations. Sci. Rep. 9, 8215 (2019).

Article Google Scholar

Jonscher, K. R. et al. Spaceflight activates lipotoxic pathways in mouse liver. PLoS ONE 11, e0152877 (2016).

Article Google Scholar

Beheshti, A. et al. Multi-omics analysis of multiple missions to space reveal a theme of lipid dysregulation in mouse liver. Sci. Rep. 9, 19195 (2019).

Article Google Scholar

Malkani, S. et al. Circulating miRNA spaceflight signature reveals targets for countermeasure development. Cell Rep. 33, 108448 (2020).

Article Google Scholar

da Silveira, W. A. et al. Comprehensive multi-omics analysis reveals mitochondrial stress as a central biological hub for spaceflight impact. Cell 183, 11851201.e20 (2020).

Article Google Scholar

Jiang, P., Green, S. J., Chlipala, G. E., Turek, F. W. & Vitaterna, M. H. Reproducible changes in the gut microbiome suggest a shift in microbial and host metabolism during spaceflight. Microbiome 7, 113 (2019).

Article Google Scholar

Beisel, N. S., Noble, J., Barbazuk, W. B., Paul, A.-L. & Ferl, R. J. Spaceflight-induced alternative splicing during seedling development in Arabidopsis thaliana. NPJ Microgravity 5, 9 (2019).

Polo, S.-H. L. et al. RNAseq analysis of rodent spaceflight experiments is confounded by sample collection techniques. iScience 23, 101733 (2020).

Article Google Scholar

Choi, S., Ray, H. E., Lai, S.-H., Alwood, J. S. & Globus, R. K. Preservation of multiple mammalian tissues to maximize science return from ground based and spaceflight experiments. PLoS ONE 11, e0167391 (2016).

Article Google Scholar

Krishnamurthy, A., Ferl, R. J. & Paul, A.-L. Comparing RNA-seq and microarray gene expression data in two zones of the Arabidopsis root apex relevant to spaceflight. Appl. Plant Sci. 6, e01197 (2018).

Article Google Scholar

Vrana, J. et al. Aquarium: open-source laboratory software for design, execution and data management. Synth. Biol. 6, ysab006 (2021).

Article Google Scholar

Miles, B. & Lee, P. L. Achieving reproducibility and closed-loop automation in biological experimentation with an IoT-enabled lab of the future. SLAS Technol. 23, 432439 (2018).

Article Google Scholar

Read the original:
Biological research and self-driving labs in deep space supported by artificial intelligence - Nature.com