Understanding lymphatic drug delivery through chylomicron blockade: A retrospective and prospective analysis
Bibliographic record
Abstract
Scientists have developed and employed various models to investigate intestinal lymphatic uptake. One approach involves using specific blocking agents to influence the chylomicron-mediated lymphatic absorption of drugs. Currently utilized models include pluronic L-81, puromycin, vinca alkaloids, colchicine, and cycloheximide. This review offers a thorough analysis of the diverse models utilized, evaluating existing reports while delineating the gaps in current research. It also explores pharmacokinetic related aspects of intestinal lymphatic uptake pathway and its blockage through the discussed models. Pluronic L-81 has a reversible effect, minimal toxicity, and unique mode of action. Yet, it lacks clinical reports on chylomicron pathway blockage, likely due to low concentrations used. Puromycin and vinca alkaloids, though documented for toxicity, lack information on their application in drug intestinal lymphatic uptake. Other vinca alkaloids show promise in affecting triglyceride profiles and represent possible agents to test as blockers. Colchicine and cycloheximide, widely used in pharmaceutical development, have demonstrated efficacy, with cycloheximide preferred for lower toxicity. However, further investigation into effective and toxic doses of colchicine in humans is needed to understand its clinical impact. The review additionally followed the complete journey of oral lymphatic targeting drugs from intake to excretion, provided a pharmacokinetic equation considering the intestinal lymphatic pathway for assessing bioavailability. Moreover, the possible application of urinary data as a non-invasive way to measure the uptake of drugs through intestinal lymphatics was illustrated, and the likelihood of drug interactions when specific blockers are employed in human subjects was underscored.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".