ArticleeLife2026
Cardiac neurons expressing a glucagon-like receptor mediate cardiac arrhythmia induced by high-fat diet in
Article in eLife, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Decoding Neuropeptide Complexity: Advancing Neurobiological Insights from Invertebrates to Vertebrates through Evolutionary Perspectives.ACS chemical neuroscience · 2025Review
Corrections and comments
- Update of
Authors and funding
4 authors.
Funding
Abstract
Cardiac arrhythmia leads to increased risks for stroke, heart failure, and cardiac arrest. Arrhythmic pathology is often rooted in the cardiac conduction system, but the mechanism is complex and not fully understood. For example, how metabolic diseases, like obesity and diabetes, increase the risk for cardiac arrhythmia. Glucagon regulates glucose production, mobilizes lipids from the fat body, and affects cardiac rate and rhythm, attributes of a likely key player.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.