Fibroblasts are coupled to myocytes in heart muscle by nanotubes: a bigger and better syncytium?
Bibliographic record
Abstract
In larger mammalian species including humans, cardiac fibroblasts represent the most numerous nonmyocytes in the myocardium. These cells function to synthesize and organize collagens, fibronectins, and other interstitial components and thus maintain the integrity of the cardiac extracellular matrix (matrix). The term ‘fibroblast’ itself designates a highly heterogenous group of cells that exhibit distinct differentiated phenotypes in different organs.1 In particular, the investigation of cardiac fibroblast and myofibroblast biology in specific organs is important but remains a largely understudied area. Their prevalence alone provides significant impetus for gaining a more complete understanding of their physiology. The common assumption that fibroblasts serve to support cardiomyocyte-mediated force transduction insofar as they synthesize and organize matrix proteins such as fibrillar collagens, elastin, and others to provide a complex interstitial weave and thus tether cardiomyocytes has been in place for many years. An extension of this traditional view is that the nature of the interstitial matrix may be to provide a hammock-like weave that, by its parallelogram structure, assists in protecting the muscle fibre from overstretching as well as contributes to active relengthening of the myocytes, and thus the matrix may lend a suction-pump function to the heart.2 Nonetheless, more recent advances in the field of intercellular communication, particularly in electrically active organs including the heart, has opened up new possibilities as to the physiologic role(s) of cardiac fibroblasts.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".