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New Insights into the Regulation of Chylomicron Production

2015· review· en· W2147086344 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Nutrition · 2015
Typereview
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsChylomicronDyslipidemiaEndocrinologyInternal medicineTriglycerideBiologyDiabetes mellitusVery low-density lipoproteinLipoproteinMedicineCholesterol

Abstract

fetched live from OpenAlex

Dietary lipids are efficiently absorbed by the small intestine, incorporated into triglyceride-rich lipoproteins (chylomicrons), and transported in the circulation to various tissues. Intestinal lipid absorption and mobilization and chylomicron synthesis and secretion are highly regulated processes. Elevated chylomicron production rate contributes to the dyslipidemia seen in common metabolic disorders such as insulin-resistant states and type 2 diabetes and likely increases the risk for atherosclerosis seen in these conditions. An in-depth understanding of the regulation of chylomicron production may provide leads for the development of drugs that could be of therapeutic utility in the prevention of dyslipidemia and atherosclerosis. Chylomicron secretion is subject to regulation by various factors, including diet, body weight, genetic variants, hormones, nutraceuticals, medications, and emerging interventions such as bariatric surgical procedures. In this review we discuss the regulation of chylomicron production, mechanisms that underlie chylomicron dysregulation, and potential avenues for future research.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.733
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.340
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it