Sex differences alter primitive progenitors in the C57BL/6 Tet2 knockout mouse model
Bibliographic record
Abstract
The precancerous expansion of hematopoietic cells, termed clonal hematopoiesis (CH), has been correlated to disease development and all-cause mortality.Despite multiple observations that hematopoietic stem cell and progenitors (HSPCs) are significantly affected by both sex and age, there remain few studies quantifying male and female HSPC populations in wild-type and transgenic Tet2 models over time.Here, we determine that male mice (with a hematopoietic deficiency of Tet2 and control) have more Lin À Sca-1 + c-kit + (LSK) cells, that include multipotent progenitor cells (MPPs; LSK CD48 À CD150 À ) and long-term hematopoietic stem cells (LT-HSC; LSK CD48 À CD150 + ) compared with females.LT-HSC, MPP, and progenitor populations were observed to possess equal male/female ratios in mice at 6 weeks of age; however, the LSK compartment was found most susceptible to sex-based effects in transgenic mice between 6 weeks and 4 months.In contrast, all differentiated progenitor populations analyzed in mice were observed to be unaffected by sex between 6 weeks to 4 months.This study provides a comprehensive analysis of bone-sourced HSPCs in Tet2-deficient mouse models and reveals important sex and age considerations that must be taken into account when using C57BL/6 mice for transgenic studies.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".