Osteo-Chondroprogenitor–Specific Deletion of the Selenocysteine tRNA Gene, Trsp, Leads to Chondronecrosis and Abnormal Skeletal Development: A Putative Model for Kashin-Beck Disease
Bibliographic record
Abstract
Kashin-Beck disease, a syndrome characterized by short stature, skeletal deformities, and arthropathy of multiple joints, is highly prevalent in specific regions of Asia. The disease has been postulated to result from a combination of different environmental factors, including contamination of barley by mold mycotoxins, iodine deficiency, presence of humic substances in drinking water, and, importantly, deficiency of selenium. This multifunctional trace element, in the form of selenocysteine, is essential for normal selenoprotein function, including attenuation of excessive oxidative stress, and for the control of redox-sensitive molecules involved in cell growth and differentiation. To investigate the effects of skeletal selenoprotein deficiency, a Cre recombinase transgenic mouse line was used to trigger Trsp gene deletions in osteo-chondroprogenitors. Trsp encodes selenocysteine tRNA([Ser]Sec), required for the incorporation of selenocysteine residues into selenoproteins. The mutant mice exhibited growth retardation, epiphyseal growth plate abnormalities, and delayed skeletal ossification, as well as marked chondronecrosis of articular, auricular, and tracheal cartilages. Phenotypically, the mice thus replicated a number of the pathological features of Kashin-Beck disease, supporting the notion that selenium deficiency is important to the development of this syndrome.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".