Heart Failure Impairs Bone Marrow Hematopoietic Stem Cell Function and Responses to Injury
Bibliographic record
Abstract
Background Heart failure (HF) is a clinical syndrome associated with a progressive decline in myocardial function and low‐grade systemic inflammation. Chronic inflammation can have lasting effects on the bone marrow (BM) stem cell pool by impacting cell renewal and lineage differentiation. However, how HF affects BM stem/progenitor cells remains largely unexplored. Methods and Results EGFP + (Enchanced green fluorescent protein) mice were subjected to coronary artery ligation, and BM was collected 8 weeks after myocardial infarction. Transplantation of EGFP + BM into wild‐type mice revealed reduced reconstitution potential of BM from mice subjected to myocardial infarction versus BM from sham mice. To study the effects HF has on human BM function, 71 patients, HF (n=20) and controls (n=51), who were scheduled for elective cardiac surgery were consented and enrolled in this study. Patients with HF exhibited more circulating blood myeloid cells, and analysis of patient BM revealed significant differences in cell composition and colony formation potential. Human CD34 + cell reconstitution potential was also assessed using the NOD‐SCID‐IL2rγ null mouse xenotransplant model. NOD‐SCID‐IL2rγ null mice reconstituted with BM from patients with HF had significantly fewer engrafted human CD34 + cells as well as reduced lymphoid cell production. Analysis of tissue repair responses using permanent left anteriordescending coronary artery ligation demonstrated reduced survival of HF‐BM reconstituted mice as well as significant differences in human (donor) and mouse (host) cellular responses after MI. Conclusions HF alters the BM composition, adversely affects cell reconstitution potential, and alters cellular responses to injury. Further studies are needed to determine whether restoring BM function can impact disease progression or improve cellular responses to injury.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".