Distinct Excitability Properties of Cardiac Calbindin Neurons: Identifying a Unique Neuronal Population
Bibliographic record
Abstract
Abstract The intrinsic cardiac nervous system is a complex system that plays a critical role in the regulation of cardiac physiological parameters and has been shown to contribute to cardiac arrhythmias. To date, several types of neurons with distinct neurochemical and electrophysiological phenotypes have been identified. However, no study has correlated the neurochemical phenotype to a specific electrophysiological behavior. Calbindin-D28k, a calcium binding protein, is expressed in numerous cardiac neurons. Given that changes in neuronal excitability have been associated with arrhythmia susceptibility and that calbindin expression has been associated with modulations of neuronal excitability, our objective is to assess whether the cardiac calbindin neuronal population has specific properties that could be involved in cardiac modulation and arrhythmias. By using a Cre-Lox mouse model to specifically target calbindin neurons with a fluorescent reporter, we characterized the neurochemical and the electrophysiological phenotype of this cardiac neuronal population. Calbindin neurons exhibit a specific neurochemical profile and a larger soma with shorter neurite length compared to other neurons. This was combined with a distinct electrophysiological signature characterized by a lower excitability with a predominantly phasic profile associated to a lower N-type calcium current density. These properties resemble to the cardiac neuronal remodeling observed in pathologies such as type II diabetes and heart failure. Therefore, we believe that this specific neuronal population deserves investigations in the context of these pathologies.
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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".