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The pituitary in reeler mice

2007· article· en· W1146576 on OpenAlexaff
Matilde Lombardero, Ignacio Salazar, Kálmán Kovács, Éva Horváth

Bibliographic record

VenueThe FASEB Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsReelerImmunohistochemistryHormonePituitary glandInternal medicineEndocrinologyHistologyReelinBiologyMedicine

Abstract

fetched live from OpenAlex

Reeler mutant mice lack Reelin, a neuronal glycoprotein, that plays a crucial role in brain development. They have low body weight and most of them are sterile. Since the brain plays a key role in the regulation of pituitary function and structure, we decided to study the pituitary in the reeler mutant mice. All mice were handled in accordance with the procedures of the Guiding Principles for the Care and Use of Animal Research (86/609/EU). Mice were divided into 3 groups of 5 mice each: Reeler Homozygotes (RHM), Reeler Heterozygotes (RHT) and Controls (CO). Animals were weighted and sacrificed with pentothal anesthesia. Blood hormones levels were measured by RIA. Pituitaries were removed, weighted and paraffin embedded for histology and immunohistochemistry or Epon embedded for electron microscopy. Body and pituitary weights were decreased in RHM and RHT mice. Blood Growth Hormone (GH) levels were not reduced and no major changes were detected in the blood levels of other pituitary hormones. Histological, immunohistochemical and ultrastructural studies revealed no differences in pituitary cells between RHM, RHT and CO except that somatotrophs seemed to be slightly smaller in RHM and RHT. In conclusion, no major alteration indicating pituitary hypofunction was demonstrated in reeler mice. More studies are needed to reveal the cause of their low body weight and infertility.

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)0.001
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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
Published2007
Admission routes1
Has abstractyes

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