Abstract P189: Disruption of <i>Cyp2c44</i> Increases Sodium Chloride Cotransporter Expression and Activity in the Distal Convoluted Tubule
Bibliographic record
Abstract
Cytochrome-P450 (CYP) epoxygenase plays an important role in the regulation of renal sodium transport. Previous studies have demonstrated that global disruption of Cyp2c44 , a major epoxygenase in the renal tubules, increased ENaC activity in the collecting duct. In addition, we have demonstrated that an increase in dietary Na intake significantly increased the mRNA expression of CYP2c44 in the DCT. DCT is responsible for the reabsorption of 5-9% of filter Na load and is the target for thiazide diuretic. Na absorption in the DCT is mediated by NaCl cotransporter (NCC) and also by ENaC in the late part of DCT. However, the role of epoxyeicosatrienoic acid (EET) in the regulation Na transport in the DCT is not clear. We now examine the role of CYP2c44 and EET in the regulation of NCC expression. The disruption of Cyp2c44 increases the expression of NCC and ENaC activity in the DCT. The disruption of CYP2c44 also suppressed the renal expression of GPR75, a receptor which is activated by 20-hydroxyeicosatetraenoic acid (20-HETE). Renal Na clearance study also demonstrates that the effect of hydrochlorothiazide on Na excretion in Cyp2c44 knockout (KO) mice was significantly higher than those of WT mice. In addition, the disruption of Cyp2c44 significantly increased the expression of ste20-proline and alanine-rich kinase (SPAK) which is known to stimulate NCC activity by phosphorylation. Increased dietary Na intake decreases NCC expression and this effect is blunted in Cyp2c44 KO mice. The role of EET in the regulation of NCC expression is further suggested by the finding that high fat-diet induced increase in NCC expression is inhibited by application of EET. We conclude that CYP2c44-derived EET plays an important role in inhibiting NCC and ENaC in the DCT.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".