Sodium hydrogen exchanger (NHE) antagonist methyl isobutyl amiloride inhibits cerebral edema associated with diabetic ketoacidosis (DKA‐CE)
Bibliographic record
Abstract
Cerebral edema associated with diabetic ketoacidosis (DKA‐CE) is a serious complication that occurs in 1–3% of children during DKA treatment. There is currently no consensus on the etiology of DKA‐CE. Sodium hydrogen exchanger 1 (NHE1) is a plasma membrane protein that is crucial for the maintenance of intracellular pH and cell volume. Increases in NHE1 activity are associated with cell swelling, and NHE1 is activated by changes in external pH and osmolality, and by insulin. The objectives of this study were to determine if NHE1 mRNA expression increases in DKA brain and to determine if inhibition of NHE activity reduces DKA‐CE. DKA was confirmed in our juvenile mice as elevated serum glucose and β‐hydroxybutyrate levels (n=120–138, P<0.001). Real‐time RT‐PCR showed significantly increased NHE1 mRNA expression in DKA mice (n=6–7/group, P<0.001). In situ hybridization also showed increased NHE1 mRNA expression in DKA mouse brain. Finally, DKA mice that were pretreated before DKA therapy with a blood brain barrier permeable NHE inhibitor methylisobutylamiloride (MIA; 50 mg/kg IP) had significantly decreased brain water content compared to DKA mice pre‐treated with vehicle (P<0.05). Thus, DKA increases brain NHE1 mRNA expression, and pretreatment with NHE inhibitor reduced the formation of DKA‐CE, suggesting that increased expression and/or activity of NHE contributes to DKA‐CE.
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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) | 0.000 | 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".