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Record W2945584238 · doi:10.1097/mco.0000000000000569

Intestinal lipogenesis

2019· review· en· W2945584238 on OpenAlexafffund
Simon Hoffman, Danielle Alvares, Khosrow Adeli

Bibliographic record

VenueCurrent Opinion in Clinical Nutrition & Metabolic Care · 2019
Typereview
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsLipogenesisChylomicronPostprandialInternal medicineEndocrinologyLipoproteinFructoseBiologyLipid metabolismChemistryBiochemistryVery low-density lipoproteinInsulinMedicineCholesterol

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To review recent evidence for the role of carbohydrates in the promotion of de novo lipogenesis and lipoprotein secretion from the intestine. RECENT FINDINGS: The consumption of diets rich in carbohydrates have been shown to promote elevations in circulating lipids. In particular, the consumption of monosaccharides, such as glucose and fructose, have been shown to induce increases in intestinal de novo lipogenesis, as well as be used as a substrate for the synthesis of triglycerides and lipoprotein export in the form of chylomicrons. Recently, various systematic reviews have analyzed the relative contribution of dietary fructose to intestinal lipogenesis. Although, there remains controversy within the literature, the body of evidence supports lipogenic effects of high fructose diets. In addition, alterations in markers of de novo lipogenesis within the jejunum of patients with insulin resistance may explain the alterations in their postprandial lipid profile. SUMMARY: Recent evidence supports the contribution of dietary carbohydrates to intestinal lipogenesis and lipoprotein secretion; however, further research is required to fully understand the mechanisms underlying this complex process.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.004

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 head0.316
GPT teacher head0.532
Teacher spread0.215 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations17
Published2019
Admission routes2
Has abstractyes

Explore more

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