The Role of Immune Cell Types in Ischemic Heart Disease Progression: A Systematic Review
Bibliographic record
Abstract
Introduction: Globally, Myocardial Ischemia or Ischemic Heart Disease (IHD) inflicts 126 million individuals, totaling an estimated nine million deaths annually. IHD injury and healing are characterized by recruitment of several immune cell types to the cardiac tissue. In addition, atherosclerosis, a common causative factor of IHD, is initiated by mediators of innate and adaptive immunity, thus providing the rationale for studying the role of immune cell types in myocardial ischemia. Clarifying the functions and interactions among these cell types will inform drug targeting studies and ultimately facilitate development of IHD treatment and prevention approaches. Methods: This systematic review highlights and summarizes pertinent studies evidencing the function and interaction of macrophages, monocytes, lymphocytes, platelets, and endothelial cells in IHD pathology. Electronic databases searched consist of Ovid, PubMed, Google Scholar, Web of Science, and ScienceDirect. Keywords include: “immune cells”, “innate immunity”, “inflammation”, “cardiac macrophages”, “adaptive immunity”, “lymphocytes”, “B cells”, “T cells”, “T-regulatory cells”, “myocardial infarction”, “reperfusion”, and additional related keywords. Results: Macrophages, monocytes, lymphocytes, platelets, and endothelial cells interact under innate and adaptive immune responses to initiate and sustain inflammation in cardiac tissue. Sustained inflammation signals for the recruitment of associated molecules to the site of ischemic heart damage which instigate injury and healing processes. Discussion: Building a comprehensive picture of interacting cell types enables the identification of druggable targets and potential treatment and prevention options. Here, we propose several steps of IHD pathology during which further studies with agonist and inhibitor molecules may yield fruitful treatment directions. Lastly, we discuss study limitations and future research avenues. Conclusions: Overall, explicating the immune cell type function and interactions will build a connective understanding of IHD pathology. In turn, elucidating the molecular and cell-specific mechanisms of the inflammatory immune response in cardiomyopathies will aid in the modelling of IHD disease progression as well as facilitate the identification of potential biomarkers and druggable targets to alleviate heart failure disease burden.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".