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Record W1980025504 · doi:10.1038/srep00487

Genes down-regulated in spaceflight are involved in the control of longevity in Caenorhabditis elegans

2012· article· en· W1980025504 on OpenAlexfundno aff
Yoko Honda, Akira Higashibata, Yohei Matsunaga, Yukiko Yonezawa, Tsuyoshi Kawano, Atsushi Higashitani, Kana Kuriyama, Toru Shimazu, Masashi Tanaka, Nathaniel J. Szewczyk, Noriaki Ishioka, Shuji Honda

Bibliographic record

VenueScientific Reports · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesJapan Aerospace Exploration AgencyNational Center for Research ResourcesMedical Research CouncilCanadian Space AgencyNational Institutes of HealthNational Aeronautics and Space AdministrationEuropean Space AgencyAmes Research Center
KeywordsCaenorhabditis elegansBiologyCell biologyGenemCherryDrosophila melanogasterLongevityGeneticsGreen fluorescent protein

Abstract

fetched live from OpenAlex

How microgravitational space environments affect aging is not well understood. We observed that, in Caenorhabditis elegans, spaceflight suppressed the formation of transgenically expressed polyglutamine aggregates, which normally accumulate with increasing age. Moreover, the inactivation of each of seven genes that were down-regulated in space extended lifespan on the ground. These genes encode proteins that are likely related to neuronal or endocrine signaling: acetylcholine receptor, acetylcholine transporter, choline acetyltransferase, rhodopsin-like receptor, glutamate-gated chloride channel, shaker family of potassium channel, and insulin-like peptide. Most of them mediated lifespan control through the key longevity-regulating transcription factors DAF-16 or SKN-1 or through dietary-restriction signaling, singly or in combination. These results suggest that aging in C. elegans is slowed through neuronal and endocrine response to space environmental cues.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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

Citations88
Published2012
Admission routes1
Has abstractyes

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