MétaCan
Menu
Back to cohort
Record W2946134331 · doi:10.1111/apha.13316

Thyroid hormone regulation of neural stem cell fate: From development to ageing

2019· review· en· W2946134331 on OpenAlexaff
Jean‐David Gothié, Pieter Vancamp, Barbara Demeneix, Sylvie Remaud

Bibliographic record

VenueActa Physiologica · 2019
Typereview
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersHorizon 2020 Framework ProgrammeCentre National de la Recherche ScientifiqueAgence Nationale de la Recherche
KeywordsNeurogenesisGliogenesisBiologyNeuroscienceContext (archaeology)VertebrateNeural stem cellCell fate determinationStem cellCell biologyGenetics

Abstract

fetched live from OpenAlex

In the vertebrate brain, neural stem cells (NSCs) generate both neuronal and glial cells throughout life. However, their neuro- and gliogenic capacity changes as a function of the developmental context. Despite the growing body of evidence on the variety of intrinsic and extrinsic factors regulating NSC physiology, their precise cellular and molecular actions are not fully determined. Our review focuses on thyroid hormone (TH), a vital component for both development and adult brain function that regulates NSC biology at all stages. First, we review comparative data to analyse how TH modulates neuro- and gliogenesis during vertebrate brain development. Second, as the mammalian brain is the most studied, we highlight the molecular mechanisms underlying TH action in this context. Lastly, we explore how the interplay between TH signalling and cell metabolism governs both neurodevelopmental and adult neurogenesis. We conclude that, together, TH and cellular metabolism regulate optimal brain formation, maturation and function from early foetal life to adult in vertebrate species.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.060
GPT teacher head0.301
Teacher spread0.241 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations52
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueActa PhysiologicaSame topicThyroid Disorders and TreatmentsFrench-language works237,207