A perspective on Notch signalling in progression and arrhythmogenesis in familial hypertrophic and dilated cardiomyopathies
Bibliographic record
Abstract
In this perspective, we discussed emerging data indicating a role for Notch signalling in inherited disorders of the heart failure with focus on hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) linked to variants of genes encoding mutant proteins of the sarcomere. We recently reported an upregulation of elements in the Notch signalling cascade in cardiomyocytes derived from human inducible pluripotent stem cells expressing a TNNT2 variant encoding cardiac troponin T (cTnT-I79N +/− ), which induces hypertrophy, remodelling, abnormalities in excitation–contraction coupling and electrical instabilities (Shafaattalab S et al. 2021 Front . Cell Dev. Biol . 9 , 787581. ( doi:10.3389/fcell.2021.787581 )). Our search of the literature revealed the novelty of this finding and stimulated us to discuss potential connections between the Notch signalling pathway and familial cardiomyopathies. Our considerations focused on the potential role of these interactions in arrhythmias, microvascular ischaemia, and fibrosis. This finding underscored a need to consider the role of Notch signalling in familial cardiomyopathies which are trigged by sarcomere mutations engaging mechano-signalling pathways for which there is evidence of a role for Notch signalling with crosstalk with Hippo signalling. Our discussion included a role for both cardiac myocytes and non-cardiac myocytes in progression of HCM and DCM. This article is part of the theme issue ‘The heartbeat: its molecular basis and physiological mechanisms’.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".