Skeletal and hematological anomalies in HYAL2‐deficient mice: a second type of mucopolysaccharidosis IX?
Bibliographic record
Abstract
The metabolism of hyaluronan (HA) relies on HA synthases and hyaluronidases, among which hyaluronidase-1 (HYAL1) and -2 (HYAL2) have been proposed as key actors. Congenital HYAL1 deficiency leads to mucopolysaccharidosis IX (MPS IX), a rare lysosomal storage disorder characterized by joint abnormalities. Knowledge of HYAL2 is limited. This protein displays weak in vitro hyaluronidase activity and acts as a receptor for oncogenic ovine retroviruses. We have generated HYAL2-deficient mice through a conditional Cre-lox system. Hyal2(-/-) mice are viable and fertile. They exhibit localized congenital defects in frontonasal and vertebral bone formation and suffer from mild thrombocytopenia and chronic, possibly intravascular, hemolysis. In addition, Hyal2(-/-) mice display 10-fold increases in plasma levels of HA and 2-fold increases in plasma hyaluronidase activity. Globally, there is no HA accumulation in tissues, including bones, but liver sinusoidal cells seem overloaded with undigested HA. Taken together, these elements demonstrate for the first time that murine HYAL2 has a physiological activity in vivo that is relevant for craniovertebral bone formation, maintenance of plasma HA concentrations, and erythrocyte and platelet homeostasis. In addition, the viability of HYAL2-deficient mice raises the possibility that a similar defect, defining a new MPS disorder, exists in humans.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".