The effect of oral sodium acetate administration on plasma acetate concentration and acid-base state in horses
Bibliographic record
Abstract
AIM: Sodium acetate (NaAcetate) has received some attention as an alkalinizing agent and possible alternative energy source for the horse, however the effects of oral administration remain largely unknown. The present study used the physicochemical approach to characterize the changes in acid-base status occurring after oral NaAcetate/acetic acid (NAA) administration in horses. METHODS: Jugular venous blood was sampled from 9 exercise-conditioned horses on 2 separate occasions, at rest and for 24 h following a competition exercise test (CET) designed to simulate the speed and endurance test of 3-day event. Immediately after the CETs horses were allowed water ad libitum and either: 1) 8 L of a hypertonic NaAcetate/acetic acid solution via nasogastric tube followed by a typical hay/grain meal (NAA trial); or 2) a hay/grain meal alone (Control trial). RESULTS: Oral NAA resulted in a profound plasma alkalosis marked by decreased plasma [H+] and increased plasma [TCO2] and [HCO3-] compared to Control. The primary contributor to the plasma alkalosis was an increased [SID], as a result of increased plasma [Na+] and decreased plasma [Cl-]. An increased [Atot], due to increased [PP] and a sustained increase in plasma [acetate], contributed a minor acidifying effect. CONCLUSION: It is concluded that oral NaAcetate could be used as both an alkalinizing agent and an alternative energy source in the horse.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".