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Record W4206077807 · doi:10.1089/ast.2021.0072

Microfluidics Microbial Activity MicroAssay: An Automated <i>In Situ</i> Microbial Metabolic Detection System

2022· article· en· W4206077807 on OpenAlexaff
David Touchette, Ianina Altshuler, Isabelle Raymond‐Bouchard, Miguel Ángel Fernández-Martínez, Louis‐Jacques Bourdages, Brady O'Connor, Antonio J. Ricco, Lyle G. Whyte

Bibliographic record

VenueAstrobiology · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsMcGill University
Fundersnot available
KeywordsExtant taxonMetabolic activityMicrofluidicsRedoxBiologyEnvironmental chemistryChemistryNanotechnologyBiological systemMaterials science

Abstract

fetched live from OpenAlex

With no direct extant-life detection instrumentation included in a space mission since the 1970s, the advancement of new technologies to be included in future space missions is imperative. We developed, optimized, and tested a semi-automated prototype, the microfluidics Microbial Activity MicroAssay (μMAMA). This system metabolically characterizes and detects extant microbial life by way of metabolism-indicator redox dyes. We first evaluated the robustness and sensitivity of six redox dye/buffer combinations, and we then tested their responses to metabolic activity in astrobiological analog high-Arctic samples. We determined that the Biolog Inoculating Fluid (IF)-C and AlamarBlue buffered in IF-0a (aB-IF0a) dye/buffer combinations were optimal, as they detected metabolic activity from the fewest microbial cells (10 2 cells/mL) while maintaining efficacy over a broad physiochemical range of pH (0–13), temperature (−10°C to 37°C), salinity and perchlorate (tested up to 30%), and in the presence of a Mars regolith simulant (MMS-2). The μMAMA, which incorporated these redox dyes, detected extant active cold-adapted microbial life from high Arctic analog sites, including samples amended with substrates targeting chemolithoautotrophic metabolisms. Given μMAMA's small size (we estimate a complete planetary instrument could occupy as little as 3 L) and potential for automation, it could easily be incorporated into almost any landed platform for life detection missions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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 designBench or experimental
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

Citations8
Published2022
Admission routes1
Has abstractyes

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