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Record W2139834662 · doi:10.1096/fj.01-1002fje

Alterations in TNF‐ and IL‐related gene expression in space‐flown WI38 human fibroblasts

2002· article· en· W2139834662 on OpenAlexaff
Alexandre Semov, Nathalia Semova, Chantale Lacelle, Richard Marcotte, Emmanuel Petroulakis, Gregory Proestou, Eugenia Wang

Bibliographic record

VenueThe FASEB Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicBone and Dental Protein Studies
Canadian institutionsMcGill UniversityJewish General Hospital
FundersAmes LaboratoryAmes Research Center
KeywordsTumor necrosis factor alphaProinflammatory cytokineBiologyOsteopeniaGene expressionGeneReceptorMicroarrayCell biologyInflammationEndocrinologyImmunologyGeneticsOsteoporosisBone mineral

Abstract

fetched live from OpenAlex

Spaceflight, just like aging, causes profound changes in musculoskeletal parameters, which result in decreased bone density and muscular weakness. As these conditions decrease our ability to conduct long-term manned space missions, and increase bone frailty in the elderly, the identification of genes responsible for the apparition of these physiological changes will be of great benefit. Thus, we developed and implemented a new microarray approach to investigate the changes in normal WI38 human fibroblast gene expression that arise as a consequence of space flight. Using our microarray, we identified changes in the level of expression of 10 genes, belonging to either the tumor necrosis factor- (TNF) or interleukin- (IL) related gene families in fibroblasts when WI38 cells exposed to microgravity during the STS-93 Space Shuttle mission were compared with ground controls. The genes included two ligands from the TNF superfamily, TWEAK and TNFSF15; two TNF receptor-associated proteins, NSMAF and PTPN13; three TNF-inducible genes, ABC50, PTX3, and SCYA13; TNF-alpha converting enzyme, IL-1 receptor antagonist, and IL-15 receptor alpha chain. Most of these are involved in either the regulation of bone density, and as such the development of spaceflight osteopenia, or in the development of proinflammatory status.

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 score0.376
Threshold uncertainty score0.342

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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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

Citations57
Published2002
Admission routes1
Has abstractyes

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