The network map of Elabela signaling pathway in physiological and pathological conditions
Bibliographic record
Abstract
Elabela (ELA; also called Apela and Toddler) is one of the recently discovered ligand among the two endogenous peptide ligands (Apelin and Elabela) of the apelin receptor (APLNR, also known as APJ). Elabela-induced signaling plays a crucial role in diverse biological processes, including formation of the embryonic cardiovascular system and early placental development by reducing the chances of occurrence of preeclampsia during pregnancy. It also plays the major role in the renoprotection by reducing kidney injury and the inflammatory response and regulation of gene expression associated with heart failure and fibrosis. Elabela may be processed into different active peptides, each of which binds to APLNR and predominantly activates the signals through PI3K/AKT pathway. Owing to its biomedical importance, we developed a consolidated signaling map of Elabela, in accordance with the NetPath criteria. The presented Elabela signaling map comprises 12 activation/inhibition events, 15 catalysis events, 1 molecular association, 34 gene regulation events and 32 protein expression events. The Elabela signaling pathway map is freely made available through the WikiPathways Database ( https://www.wikipathways.org/index.php/Pathway:WP5100 ).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".