The mirn23a microRNA cluster antagonizes B cell development
Bibliographic record
Abstract
Abstract Ablation of microRNA synthesis by deletion of the microRNA-processing enzyme Dicer has demonstrated that microRNAs are necessary for normal hematopoietic differentiation and function. However, it is still unclear which specific microRNAs are required for hematopoiesis and at what developmental stages they are necessary. This is especially true for immune cell development. We previously observed that overexpression of the products of the mirn23a gene (microRNA-23a, -24-2, and 27a) in hematopoietic progenitors increased myelopoiesis with a reciprocal decrease in B lymphopoiesis, both in vivo and in vitro. In this study, we generated a microRNA-23a, -24-2, and 27a germline knockout mouse to determine whether microRNA-23a, -24-2, and 27a expression was essential for immune cell development. Characterization of hematopoiesis in microRNA-23a, -24-2, and 27a−/− mice revealed a significant increase in B lymphocytes in both the bone marrow and the spleen, with a concomitant decrease in myeloid cells (monocytes/granulocytes). Analysis of the bone marrow progenitor populations revealed a significant increase in common lymphoid progenitors and a significant decrease in both bone marrow common myeloid progenitors and granulocyte monocyte progenitors. Gene-expression analysis of primary hematopoietic progenitors and multipotent erythroid myeloid lymphoid cells showed that microRNA-23a, -24-2, and 27a regulates essential B cell gene-expression networks. Overexpression of microRNA-24-2 target Tribbles homolog 3 can recapitulate the microRNA-23a, -24-2, and 27a−/− phenotype in vitro, suggesting that increased B cell development in microRNA-23a, -24-2, and 27a null mice can be partially explained by a Tribbles homolog 3-dependent mechanism. Data from microRNA-23a, -24-2, and 27a−/− mice support a critical role for this microRNA cluster in regulating immune cell populations through repression of B lymphopoiesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".