Single-cell transcriptome analysis reveals CD34 as a novel marker of human sinoatrial node pacemaker cardiomyocytes
Bibliographic record
Abstract
Abstract The sinoatrial node (SAN) regulates the heart rate throughout life. Failure of this primary pacemaker results in life-threatening, slow heart rhythm. Despite its important function, the cellular and molecular composition of the human SAN is not completely resolved. Particularly, no cell surface marker to identify and isolate SAN pacemaker cells has been reported to date. Here we used single-nuclei/cell RNA sequencing of fetal and human pluripotent stem cell (hPSC)- derived SAN cells and show that the SAN consists of three subtypes of pacemaker cells, including Core SAN, SAN, and Transitional Cells. Our study identified a host of novel Core SAN markers including MYH11, BMP4, and the cell surface antigen CD34. We demonstrate that sorting for CD34 + cells from cardiac hPSC differentiations enriches for SAN cells with a functional pacemaker phenotype. This novel SAN pacemaker cell surface marker is highly valuable for future hPSC- based disease modelling, drug discovery, cell replacement therapies, as well as the delivery of therapeutics to SAN cells in vivo using antibody-drug conjugates.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".