MétaCan
Menu
Back to cohort
Record W4299514145

Alterations in the hypothalamic-pituitary-thyroidaxis in animals submitted to early-life trauma

2017· article· en· W4299514145 on OpenAlexaff
Tania Diniz Machado, Roberta Dalle Molle, Patrícia Pelufo Silveira

Bibliographic record

VenueAmericanae (AECID Library) · 2017
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsHypothalamic–pituitary–thyroid axisThyroidMedicinePituitary glandEndocrinologyInternal medicineNeurosciencePsychologyThyroid hormonesHormone
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Changes in maternal care can affect offspring’s thyroid hormone T3 levels. Pups from highly caring mothers have higher levels of thyroid hormone T3. In humans, physical abuse in childhood is related to lower levels of T3 in adolescence. This study aimed at verifying if early-life trauma in rodents is correlated with T3 levels in adulthood.Methods: From the second day of life, litters of Wistar rats were subjected to reduced nesting material (Early–Life Stress-ELS) or standard care (Controls). In adult life, the animals were chronically exposed to standard diet or standard diet + palatable diet and plasma T3 levels were measured before and after the exposition to diet.Results: Thyroid hormone T3 levels in adult life correlated negatively with the licking and grooming (LG) scores in the ELS group. This correlation disappeared when the animals had the opportunity to choose between two diets chronically.Conclusion: The adverse environment affected maternal behavior and caused marks on the metabolism of the intervention group (T3), which were reverted by chronic palatable food consumption.Keywords: Trauma; T3; stress

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 score0.002
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.290
Teacher spread0.260 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmericanae (AECID Library)Same topicBirth, Development, and HealthFrench-language works237,207