Severity of Megakaryocyte-Driven Osteosclerosis in Mpig6b-Deficient Mice Is Sex-Linked
Bibliographic record
Abstract
ABSTRACT Patients with chronic myelofibrosis often suffer from osteosclerosis, which is associated with bone pain and may lead to bone marrow failure. The pathogenesis of myelofibrosis is linked to aberrant megakaryocyte development and function. Null and loss-of-function mutations in MPIG6B, which codes for the inhibitory heparan sulfate receptor G6b-B, result in severe macrothrombocytopenia, large megakaryocyte clusters, and focal primary myelofibrosis in mice and humans. We investigated the development of osteosclerosis in Mpig6b null (Mpig6b−/−) mice. Although male and female Mpig6b−/− mice presented with elevated bone marrow megakaryocyte number and macrothrombocytopenia, female Mpig6b−/− mice developed progressive splenomegaly starting at 8 weeks of age. Micro–computed tomography (μCT) of femurs showed that female Mpig6b−/− mice had increased cortical thickness and reduced bone marrow area starting at 8 weeks of age and developed occlusion of the medullary cavity by trabeculae by 16 weeks of age. In contrast, male Mpig6b−/− mice developed only a small number of trabeculae in the medullary cavity at the proximal diaphysis and demonstrated a temporary decrease in bone volume fraction and trabecular thickness at 16 weeks. Ovariectomy of 10-week-old female Mpig6b−/− mice prevented the development of medullary cavity osteosclerosis, whereas orchiectomy of male Mpig6b−/− mice did not exacerbate their disease. Importantly, ovariectomized female Mpig6b−/− mice also demonstrated improvement in spleen weight compared to sham-operated Mpig6b−/− mice, establishing estrogen as a contributing factor to the severity of the megakaryocyte-driven osteosclerosis. © 2021 American Society for Bone and Mineral Research (ASBMR).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".