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Record W2795814297 · doi:10.1016/j.stemcr.2018.03.008

Interleukin-6 Regulates Adult Neural Stem Cell Numbers during Normal and Abnormal Post-natal Development

2018· article· en· W2795814297 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStem Cell Reports · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health ResearchHarvard Stem Cell Institute
KeywordsForebrainBiologyNeural stem cellNeuroscienceReceptorCytokineCell biologyStem cellImmunologyCentral nervous systemGenetics

Abstract

fetched live from OpenAlex

Circulating systemic factors can regulate adult neural stem cell (NSC) biology, but the identity of these circulating cues is still being defined. Here, we have focused on the cytokine interleukin-6 (IL-6), since increased circulating levels of IL-6 are associated with neural pathologies such as autism and bipolar disorder. We show that IL-6 promotes proliferation of post-natal murine forebrain NSCs and that, when the IL-6 receptor is inducibly knocked out in post-natal or adult neural precursors, this causes a long-term decrease in forebrain NSCs. Moreover, a transient circulating surge of IL-6 in perinatal or adult mice causes an acute increase in neural precursor proliferation followed by long-term depletion of adult NSC pools. Thus, IL-6 signaling is both necessary and sufficient for adult NSC self-renewal, and acute perturbations in circulating IL-6, as observed in many pathological situations, have long-lasting effects on the size of adult NSC pools.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.002
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.011
GPT teacher head0.204
Teacher spread0.192 · 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