ArticleAstrobiology2023
BioSentinel: A Biological CubeSat for Deep Space Exploration.
Article in Astrobiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Autonomous, miniature research station (lab-payload) for the nanosatellite biological mission: LabSat.Scientific reports · 2025Article
- Inertial microfluidic mixer for biological CubeSat missions.Mikrochimica acta · 2024Article
- Microbiology of human spaceflight: microbial responses to mechanical forces that impact health and habitat sustainability.Microbiology and molecular biology reviews : MMBR · 2024Review
- Multi-Modal Multi-Array Electrochemical and Optical Sensor Suite for a Biological CubeSat Payload.Sensors (Basel, Switzerland) · 2024Article
- Lab-on-chip technologies for space research - current trends and prospects.Mikrochimica acta · 2023Review
- Spaceflight Induces Strength Decline inCells · 2023Article
- Future space experiment platforms for astrobiology and astrochemistry research.NPJ microgravity · 2023Review
- BioSentinel: Validating Sensitivity of Yeast Biosensors to Deep Space Relevant Radiation.Astrobiology · 2023Article
- Review
- Nanosatellite Payload for Research on Seed Germination in a 3D Printed Micropot.Sensors (Basel, Switzerland) · 2023Article
- Enabling deep-space experimentations on cyanobacteria by monitoring cell division resumption in driedFrontiers in microbiology · 2023Article
- Lab-on-a-Chip Technologies for Microgravity Simulation and Space Applications.Micromachines · 2022Review
- Microfluidic-Assisted Human Cancer Cells Culturing Platform for Space Biology Applications.Sensors (Basel, Switzerland) · 2022Article
- Microfluidic chip-based long-term preservation and culture of engineering bacteria for DNA damage evaluation.Applied microbiology and biotechnology · 2022Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BioSentinel is the first biological CubeSat designed and developed for deep space. The main objectives of this NASA mission are to assess the effects of deep space radiation on biological systems and to engineer a CubeSat platform that can autonomously support and gather data from model organisms hundreds of thousands of kilometers from Earth. The articles in this special collection describe the extensive optimization of the biological payload system performed in preparation for this long-duration deep space mission. In this study, we briefly introduce BioSentinel and provide a glimpse into its technical and conceptual heritage by detailing the evolution of the science, subsystems, and capabilities of NASA's previous biological CubeSats. This introduction is not intended as an exhaustive review of CubeSat missions, but rather provides insight into the unique optimization parameters, science, and technology of those few that employ biological model systems.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.