Aging and Heart Failure Alter the Bone Marrow Derived Inflammatory Response and Impair Cardiac Remodeling Following Myocardial Infarction
Bibliographic record
Abstract
Title: Aging and Heart Failure Alter the Bone Marrow Derived Inflammatory Response and Impair Cardiac Remodeling Following Myocardial Infarction Name: Tina Binesh Marvasti Degree: Doctor of Philosophy Year of convocation: November 2020 Institute of Medical Sciences, University of Toronto In adult humans, sudden loss of cardiomyocytes as a result of any strain or injury to the myocardium can potentially overwhelm the innate regenerative capability of this tissue. This results in formation of a collagen based scar, which could either stabilize or expand and result in ventricular dilation and heart failure. Considering the limited therapeutic options available to treat heart failure, autologous bone marrow stem cell based regenerative therapies have gained attention due to their promising results in myocardial function recovery post infarction in pre-clinical investigations. However the results from clinical investigations have been variable and relatively inconsistent. Inconsistencies in patient outcome and inconclusive data from some clinical trials has led us to hypothesis that patient intrinsic factors could play a crucial role in the quality and function of bone marrow derived stem cells which can influence the efficacy of their function in myocardial recovery. Factors investigated in this thesis were patients’ age and early cardiac dysfunction. I profiled the post ischemia immune modulating response originating from the bone marrow derived stem and hematopoietic progenitor cells. I developed and optimised a specific humanized mouse model for investigating human immune cells’ response to ischemia by transplanting patient CD34 stem cells in the bone marrow of NOD-SCID NSG mice and assessed patient specific characteristics that modify and dampen the proper immune response. Using these techniques, I demonstrate how lack of regulatory T cell (Treg) expansion in old patients’ bone marrow derived immune modulatory cells could lead to infarct expansion and left ventricular remodelling. I also show how the quality of bone marrow stem cells isolated from patients showing early stage heart failure symptoms indicate signs of bone marrow exhaustion. Here, we demonstrate the importance of how patient specific characteristics such as aging and early stage heart failure can modify the quality of bone marrow stem cells’ response to myocardial recovery. Future clinical investigations should consider adjunct complementary immune therapy and providing appropriate personalized therapy where characterization of patients’ immune profile would take the centre stage.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".