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Record W3137817435 · doi:10.1038/s41526-021-00136-w

Evaluating the effect of spaceflight on the host–pathogen interaction between human intestinal epithelial cells and Salmonella Typhimurium

2021· article· en· W3137817435 on OpenAlexaff
Jennifer Barrila, Shameema Sarker, Nicole Hansmeier, Shanshan Yang, Kristina Buss, Natalia Briones, Jin Park, Richard R. Davis, Rebecca J. Forsyth, C. Mark Ott, Kevin Sato, Cristine Kosnik, Anthony Yang, Cheryl Shimoda, Nicole Rayl, Diana Ly, Aaron Landenberger, Stephanie D. Wilson, Naoko Yamazaki, Jason C. Steel, Camila Montano, Rolf U. Halden, Tom Cannon, Sarah L. Castro-Wallace, Cheryl A. Nickerson

Bibliographic record

Venuenpj Microgravity · 2021
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsUniversity of Regina
FundersKennedy Space CenterNuclear Safety and Security CommissionAmes Research CenterNational Aeronautics and Space Administration
KeywordsSpaceflightPathogenSalmonellaImmune systemBiologyMicrobiologyHost (biology)TranscriptomeHuman pathogenInfectious disease (medical specialty)BacteriaImmunologyGeneDiseaseGene expressionGeneticsMedicine

Abstract

fetched live from OpenAlex

Spaceflight uniquely alters the physiology of both human cells and microbial pathogens, stimulating cellular and molecular changes directly relevant to infectious disease. However, the influence of this environment on host-pathogen interactions remains poorly understood. Here we report our results from the STL-IMMUNE study flown aboard Space Shuttle mission STS-131, which investigated multi-omic responses (transcriptomic, proteomic) of human intestinal epithelial cells to infection with Salmonella Typhimurium when both host and pathogen were simultaneously exposed to spaceflight. To our knowledge, this was the first in-flight infection and dual RNA-seq analysis using human cells.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.038
GPT teacher head0.365
Teacher spread0.327 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2021
Admission routes1
Has abstractyes

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Same venuenpj MicrogravitySame topicSpaceflight effects on biologyFrench-language works237,207