Aging impairs human bone marrow function and cardiac repair following myocardial infarction in a humanized chimeric mouse
Bibliographic record
Abstract
Abstract Ventricular remodeling following myocardial infarction (MI) is a major cause of heart failure, a condition prevalent in older individuals. Following MI, immune cells are mobilized to the myocardium from peripheral lymphoid organs and play an active role in orchestrating repair. While the effect of aging on mouse bone marrow (BM) has been studied, less is known about how aging affects human BM cells and their ability to regulate repair processes. In this study, we investigate the effect aging has on human BM cell responses post‐MI using a humanized chimeric mouse model. BM samples were collected from middle aged (mean age 56.4 ± 0.97) and old (mean age 72.7 ± 0.59) patients undergoing cardiac surgery, CD34 +/− cells were isolated, and NOD‐scid‐IL2rγ null (NSG) mice were reconstituted. Three months following reconstitution, the animals were examined at baseline or subjected to coronary artery ligation (MI). Younger patient cells exhibited greater repopulation capacity in the BM, blood, and spleen as well as greater lymphoid cell production. Following MI, CD34 + cell age impacted donor and host cellular responses. Mice reconstituted with younger CD34 + cells exhibited greater human CD45 + recruitment to the heart compared to mice reconstituted with old cells. Increased cellular responses were primarily driven by T‐cell recruitment, and these changes corresponded with greater human IFNy levels and reduced mouse IL‐1β in the heart. Age‐dependent changes in BM function led to significantly lower survival, increased infarct expansion, impaired host cell responses, and reduced function by 4w post‐MI. In contrast, younger CD34 + cells helped to limit remodeling and preserve function post‐MI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".