Enzyme Replacement Therapy for Murine Hypophosphatasia
Bibliographic record
Abstract
INTRODUCTION: Hypophosphatasia (HPP) is the inborn error of metabolism that features rickets or osteomalacia caused by loss-of-function mutation(s) within the gene that encodes the tissue-nonspecific isozyme of alkaline phosphatase (TNALP). Consequently, natural substrates for this ectoenzyme accumulate extracellulary including inorganic pyrophosphate (PPi), an inhibitor of mineralization, and pyridoxal 5'-phosphate (PLP), a co-factor form of vitamin B6. Babies with the infantile form of HPP often die with severe rickets and sometimes hypercalcemia and vitamin B6-dependent seizures. There is no established medical treatment. MATERIALS AND METHODS: Human TNALP was bioengineered with the C terminus extended by the Fc region of human IgG for one-step purification and a deca-aspartate sequence (D10) for targeting to mineralizing tissue (sALP-FcD10). TNALP-null mice (Akp2-/-), an excellent model for infantile HPP, were treated from birth using sALP-FcD10. Short-term and long-term efficacy studies consisted of once daily subcutaneous injections of 1, 2, or 8.2 mg/kg sALP-FcD10 for 15, 19, and 15 or 52 days, respectively. We assessed survival and growth rates, circulating levels of sALP-FcD10 activity, calcium, PPi, and pyridoxal, as well as skeletal and dental manifestations using radiography, microCT, and histomorphometry. RESULTS: Akp2-/- mice receiving high-dose sALP-FcD10 grew normally and appeared well without skeletal or dental disease or epilepsy. Plasma calcium, PPi, and pyridoxal concentrations remained in their normal ranges. We found no evidence of significant skeletal or dental disease. CONCLUSIONS: Enzyme replacement using a bone-targeted, recombinant form of human TNALP prevents infantile HPP in Akp2-/- mice.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".