Abnormal Thyroid Hormone Status Differentially Affects Bone Mass Accrual and Bone Strength in C3H/HeJ Mice: A Mouse Model of Type I Deiodinase Deficiency
Bibliographic record
Abstract
C3H/HeJ (C3H) mice are deficient of type I deiodinase (D1), an enzyme that activates thyroid hormone (TH), converting thyroxine (T4) to triiodothyronine (T3). Nevertheless, C3H mice present normal serum T3 and a gross euthyroid phenotype. To investigate if a global D1 deficiency interferes in the TH effects on bone, we compared bone growth, bone mass accrual and bone strength of C3H and C57BL/6J (B6) mice under abnormal TH status. Four-week-old female mice of both strains were grouped as Euthyroid, Hypothyroid (pharmacologically-induced), 1xT4 and 10xT4 (hypothyroid animals receiving 1- or 10-fold the physiological dose of T4 /day/16 weeks). Hypothyroidism and TH excess similarly impaired body weight (BW) gain and body growth in both mice strains. In contrast, whereas hypothyroidism only slightly impaired bone mineral density (BMD) accrual in B6 mice, it severely impaired BMD accrual in C3H mice. No differences were observed in serum and bone concentrations of T3 between hypothyroid animals of both strains. Interestingly, treatment with 10xT4 was less deleterious to BMD accrual in C3H than in B6 mice and resulted in less elevated T3 serum levels in B6 than in C3H mice, which is probably explained by the lower D1 activity in C3H mice. In addition, hypothyroidism decreased bone strength only in C3H but not in B6 mice, while TH excess decreased this parameter in both strains. These findings indicate that D1 deficiency contributes to the TH excess-induced differences in bone mass accrual in C3H vs. B6 mice and suggest that deiodinase-unrelated genetic factors might account for the different skeleton responses to hypothyroidism between strains.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".