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Record W2548364394

Biosentinel: Developing a Space Radiation Biosensor

2014· article· en· W2548364394 on OpenAlexaff
T. Straume, Ming X. Tan, Sergio R. Santa Maria, Terry C. Lusby, Antonio J. Ricco, Troy A. A. Harkness, Debra Reiss-Bubenheim, Roger Brent, Macarena Parra, Diana Marina, Travis D. Boone, Sharmila Bhattacharya

Bibliographic record

VenueNASA STI Repository (National Aeronautics and Space Administration) · 2014
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsHomologous recombinationRadiationIonizing radiationDosimeterInternational Space StationPhysicsIrradiationBiologyDNAOpticsGeneticsAstronomy
DOInot available

Abstract

fetched live from OpenAlex

Ionizing radiation presents a major challenge to human exploration and long-term residence in space. The deep-space radiation spectrum includes highly energetic particles that generate double strand breaks (DSBs), deleterious DNA lesions that are usually repaired without errors via homologous recombination (HR), a conserved pathway in all eukaryotes. While progress identifying and characterizing biological radiation effects using Earth-based facilities has been significant, no terrestrial source duplicates the unique space radiation environment.We are developing a biosensor-based nanosatellite to fly aboard NASAs Space Launch System Exploration Mission 1, expected to launch in 2017 and reach a 1AU (astronomic unit) heliocentric orbit. Our biosensor (called BioSentinel) uses the yeast S. cerevisiae to measure DSBs in response to ambient space radiation. The BioSentinel strain contains engineered genetic defects that prevent growth until and unless a radiation-induced DSB near a reporter gene activates the yeasts HR repair mechanisms. Thus, culture growth and metabolic activity directly indicate a successful DSB-and-repair event. In parallel, HR-defective and wild type strains will provide survival data. Desiccated cells will be carried within independent culture microwells, built into 96-well microfluidic cards. Each microwell set will be activated by media addition at different time points over 18 months, and cell growth will be tracked continuously via optical density. One reserve set will be activated only in the occurrence of a solar particle event. Biological measurements will be compared to data provided by onboard physical dosimeters and to Earth-based experiments.BioSentinel will conduct the first study of biological response to space radiation outside Low Earth Orbit in over 40 years. BioSentinel will thus address strategic knowledge gaps related to the biological effects of space radiation and will provide an adaptable platform to perform human-relevant measurements in multiple space environments. We hope that it can therefore be used on the ISS, on and around other planetary bodies as well as other exploration platforms as a self-contained system that will allow us to compare and calibrate different radiation environments.BioSentinels results will be critical for improving interpretation of the effects of space radiation exposure, and for reducing the risk associated with long-term human exploration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.275
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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