Chronic kidney disease: targeting prostaglandin E<sub>2</sub>receptors
Bibliographic record
Abstract
Chronic kidney disease is a leading cause of morbidity and mortality in the world. A better understanding of disease mechanisms has been gained in recent years, but the current management strategies are ineffective at preventing disease progression. A widespread focus of research is placed on elucidating the specific processes implicated to find more effective therapeutic options. PGE2, acting on its four EP receptors, regulates many renal disease processes; thus EP receptors could prove to be important targets for kidney disease intervention strategies. This review summarizes the major pathogenic mechanisms contributing to initiation and progression of chronic kidney disease, emphasizing the role of hyperglycemia, hypertension, inflammation, and oxidative stress. We have long recognized the multifaceted role of PGs in both the initiation and progression of chronic kidney disease, yet studies are only now seriously contemplating specific EP receptors as targets for therapy. Given the plethora of renal complications attributed to PG involvement in the kidney, this review highlights these pathogenic events and emphasizes the PGE2 receptor targets as options available to complement current therapeutic strategies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".