Lymphatics - not just a chylomicron conduit
Bibliographic record
Abstract
PURPOSE OF REVIEW: Lymphatics are known to have active, regulated pumping by smooth muscle cells that enhance lymph flow, but whether active regulation of lymphatic pumping contributes significantly to the rate of appearance of chylomicrons (CMs) in the blood circulation (i.e., CM production rate) is not currently known. In this review, we highlight some of the potential mechanisms by which lymphatics may regulate CM production. RECENT FINDINGS: Recent data from our lab and others are beginning to provide clues that suggest a more active role of lymphatics in regulating CM appearance in the circulation through various mechanisms. Potential contributors include apolipoproteins, glucose, glucagon-like peptide-2, and vascular endothelial growth factor-C, but there are likely to be many more. SUMMARY: The digested products of dietary fats absorbed by the small intestine are re-esterified and packaged by enterocytes into large, triglyceride-rich CM particles or stored temporarily in intracellular cytoplasmic lipid droplets. Secreted CMs traverse the lamina propria and are transported via lymphatics and then the blood circulation to liver and extrahepatic tissues, where they are stored or metabolized as a rich energy source. Although indirect data suggest a relationship between lymphatic pumping and CM production, this concept requires more experimental evidence before we can be sure that lymphatic pumping contributes significantly to the rate of CM appearance in the blood circulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".