Effects of intestinal constituents and lipids on intestinal formation and pharmacokinetics of desethylamiodarone formed from amiodarone
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To model the impact of intestinal components associated with a high fat meal on metabolism of amiodarone, rat everted intestinal sacs were evaluated for their ability to metabolize the drug to its active metabolite (desethylamiodarone) under a variety of conditions. The preparations were obtained from fasted rats or rats pretreated with 1% cholesterol in peanut oil. After isolation of the tissues, the intestinal segments were immersed in oxygenated Krebs Henseleit buffer containing varying concentrations of bile salts, cholesterol, lecithin and lipase with or without soybean oil emulsion as a source of triglycerides. Amiodarone uptake was similar between the five 10-cm segments isolated distally from the stomach. Desethylamiodarone was measurable in all segments. Based on the metabolite-to-drug concentration ratio within the tissues, there was little difference in metabolic efficiency between segments for any of the treatments. Between treatments, however, it appeared that the lowest level of metabolism was noted in rats pretreated with 1% cholesterol in peanut oil. This reduction in metabolic efficiency was not observed in gut sacs from the fasted rats to which soybean oil emulsion was directly added to the incubation media. Despite the apparent reduction in intestinal metabolism, there was no apparent change in the ratio of metabolite-to-drug area under the plasma concentration versus time ratios of fasted rats and those given 1% cholesterol in peanut oil, suggesting that the intestinal presystemic formation of desethylamiodarone is not substantial.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it