Intestinal Lipid Handling
Bibliographic record
Abstract
OBJECTIVE: Animal models have evidenced the role of intestinal triglyceride-rich lipoprotein overproduction in dyslipidemia. However, few studies have confronted this issue in humans and disclosed the intrinsic mechanisms. This work aimed to establish whether intestinal insulin resistance modifies lipid and lipoprotein homeostasis in the intestine of obese subjects. APPROACH AND RESULTS: Duodenal specimens obtained from 20 obese subjects undergoing bariatric surgery were paired for age, sex, and body mass index with or without insulin resistance, as defined by the homeostasis model assessment of insulin resistance. Insulin signaling, biomarkers of inflammation and oxidative stress, and lipoprotein assembly were assessed. The intestine of insulin-resistant subjects showed defects in insulin signaling as demonstrated by reduced protein kinase B phosphorylation and increased p38 mitogen-activated protein kinase phosphorylation, likely as the result of high oxidative stress (evidenced by malondialdehyde and conjugated dienes) and inflammation (highlighted by nuclear factor-κB, tumor necrosis factor-α, interleukin-6, intercellular adhesion molecule-1, and cyclooxygenase-2). Enhanced de novo lipogenesis rate and apolipoprotein B-48 biogenesis along with exaggerated triglyceride-rich lipoprotein production were observed, concomitantly with the high expression levels of liver and intestinal fatty acid-binding proteins and microsomal transfer protein. The presence of an aberrant intracellular cholesterol transport/metabolism was also suggested by the reduced expression of ATP-binding cassette A1 transporter and proprotein convertase subtilisin/kexin type 9. CONCLUSIONS: According to the present data, the small intestine may be classified as an insulin-sensitive tissue. Dysregulation of intestinal insulin signaling, possibly triggered by oxidative stress and inflammation, was associated with exaggerated lipogenesis and lipoprotein synthesis, which may represent a key mechanism for atherogenic dyslipidemia in patients with metabolic syndrome.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".