ELABELA Improves Cardio-Renal Outcome in Fatal Experimental Septic Shock
Bibliographic record
Abstract
OBJECTIVES: Apelin-13 was recently proposed as an alternative to the recommended β-adrenergic drugs for supporting endotoxin-induced myocardial dysfunction. Since Apelin-13 signals through its receptor (Apelin peptide jejunum) to exert singular inotropic/vasotropic actions and to optimize body fluid balance, this candidate pathway might benefit septic shock management. Whether the newly discovered ELABELA (ELA), a second endogenous ligand of the Apelin peptide jejunum receptor highly expressed in the kidney, further improves cardio-renal impairment remains unknown. DESIGN, SETTING, AND SUBJECTS: Interventional study in a rat model of septic shock (128 adult males) to assess the effects of ELA and Apelin-13 on vascular and cardio-renal function. Experiments were performed in a tertiary care University-based research institute. INTERVENTIONS: Polymicrobial sepsis-induced cardiac dysfunction was produced by cecal ligation puncture to assess hemodynamic efficacy, cardioprotection, and biomechanics under acute or continuous infusions of the apelinergic agonists ELA or Apelin-13 (39 and 15 µg/kg/hr, respectively) versus normal saline. MEASUREMENTS AND MAIN RESULTS: Apelinergic agonists improved 72-hour survival after sepsis induction, with ELA providing the best clinical outcome after 24 hours. Apelinergic agonist infusion counteracted cecal ligation puncture-induced myocardial dysfunction by improving left ventricular pressure-volume relationship. ELA-treated cecal ligation puncture rats were the only group to 1) display a significant improvement in left ventricular filling as shown by increased E-wave velocity and left ventricular end-diastolic volume, 2) exhibit a higher plasma volume, and 3) limit kidney injury and free-water clearance. These beneficial renal effects were superior to Apelin-13, likely because full-length ELA enabled a distinctive regulation of pituitary vasopressin release. CONCLUSIONS: Activation of the apelinergic system by exogenous ELA or Apelin-13 infusion improves cardiovascular function and survival after cecal ligation puncture-induced sepsis. However, ELA proved better than Apelin-13 by improving fluid homeostasis, cardiovascular hemodynamics recovery, and limiting kidney dysfunction in a vasopressinergic-dependent manner.
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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) | 0.001 | 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 | 0.001 |
| 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".