Isolation and Identification of Extravascular Immune Cells of the Heart
Bibliographic record
Abstract
The immune system is an essential component of a healthy heart. The myocardium is home to a rich population of different immune cell subsets with functional compartmentalization both during steady state and during different forms of inflammation. Until recently, the study of immune cells in the heart required the use of microscopy or poorly developed digestion protocols, which provided enough sensitivity during severe inflammation but were unable to confidently identify small - but key - populations of cells during steady state. Here, we discuss a simple method combining enzymatic (collagenase, hyaluronidase and DNAse) and mechanical digestion of murine hearts preceded by intravascular administration of fluorescently-labelled antibodies to differentiate small but unavoidable intravascular cell contaminants. This method generates a suspension of isolated viable cells that can be analyzed by flow cytometry for identification, phenotyping and quantification, or further purified with fluorescence-activated cell sorting or magnetic bead separation for transcriptional analysis or in vitro studies. We include an example of a step-by-step flow cytometric analysis to differentiate the key macrophage and dendritic cell populations of the heart. For a medium sized experiment (10 hearts) the completion of the procedure requires 2-3 h.
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 | 0.000 | 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 | 0.000 | 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".