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Record W2296805285 · doi:10.1038/ncomms10573

Diapause is associated with a change in the polarity of secretion of insulin-like peptides

2016· article· en· W2296805285 on OpenAlexfundno aff
Yohei Matsunaga, Yoko Honda, Shuji Honda, Takashi Iwasaki, Hiroshi Qadota, Guy M. Benian, Tsuyoshi Kawano

Bibliographic record

VenueNature Communications · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceNational Institutes of HealthInstitute of GeneticsNational Center for Research ResourcesNorthwestern University
KeywordsDiapauseBiologyCell biologySecretionCaenorhabditis elegansPolarity (international relations)InsulinNematodeLarvaEndocrinologyBiochemistryGeneEcology

Abstract

fetched live from OpenAlex

The insulin/IGF-1 signalling (IIS) pathway plays an important role in the regulation of larval diapause, the long-lived growth arrest state called dauer arrest, in Caenorhabditis elegans. In this nematode, 40 insulin-like peptides (ILPs) have been identified as putative ligands of the IIS pathway; however, it remains unknown how ILPs modulate larval diapause. Here we show that the secretory polarity of INS-35 and INS-7, which suppress larval diapause, is changed in the intestinal epithelial cells at larval diapause. These ILPs are secreted from the intestine into the body cavity during larval stages. In contrast, they are secreted into the intestinal lumen and degraded during dauer arrest, only to be secreted into the body cavity again when the worms return to developmental growth. The process that determines the secretory polarity of INS-35 and INS-7, thus, has an important role in the modulation of larval diapause.

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicGenetics, Aging, and Longevity in Model OrganismsFrench-language works237,207