ADA-deficient SCID is associated with a specific microenvironment and bone phenotype characterized by RANKL/OPG imbalance and osteoblast insufficiency
Bibliographic record
Abstract
Adenosine deaminase (ADA) deficiency is a disorder of the purine metabolism leading to combined immunodeficiency and systemic alterations, including skeletal abnormalities. We report that ADA deficiency in mice causes a specific bone phenotype characterized by alterations of structural properties and impaired mechanical competence. These alterations are the combined result of an imbalanced receptor activator of nuclear factor-kappaB ligand (RANKL)/osteoprotegerin axis, causing decreased osteoclastogenesis and an intrinsic defect of osteoblast function with subsequent low bone formation. In vitro, osteoblasts lacking ADA displayed an altered transcriptional profile and growth reduction. Furthermore, the bone marrow microenvironment of ADA-deficient mice showed a reduced capacity to support in vitro and in vivo hematopoiesis. Treatment of ADA-deficient neonatal mice with enzyme replacement therapy, bone marrow transplantation, or gene therapy resulted in full recovery of the altered bone parameters. Remarkably, untreated ADA-severe combined immunodeficiency patients showed a similar imbalance in RANKL/osteoprotegerin levels alongside severe growth retardation. Gene therapy with ADA-transduced hematopoietic stem cells increased serum RANKL levels and children's growth. Our results indicate that the ADA metabolism represents a crucial modulatory factor of bone cell activities and remodeling.
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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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".