MétaCan
Menu
Back to cohort
Record W2032456325 · doi:10.1056/nejmoa1400284

Targeting APOC3 in the Familial Chylomicronemia Syndrome

2014· article· en· W2032456325 on OpenAlexaff
Daniel Gaudet, Diane Brisson, Karine Tremblay, Veronica Alexander, W. S. Singleton, Steven G. Hughes, Richard S. Geary, Brenda F. Baker, Mark J. Graham, Rosanne M. Crooke, Joseph L. Witztum

Bibliographic record

VenueNew England Journal of Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversité de MontréalUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsHypertriglyceridemiaMedicineLipoprotein lipaseTriglycerideInternal medicineEndocrinologyApolipoprotein BCholesterolAdipose tissue

Abstract

fetched live from OpenAlex

The familial chylomicronemia syndrome is a genetic disorder characterized by severe hypertriglyceridemia and recurrent pancreatitis due to a deficiency in lipoprotein lipase (LPL). Currently, there are no effective therapies except for extreme restriction in the consumption of dietary fat. Apolipoprotein C-III (APOC3) is known to inhibit LPL, although there is also evidence that APOC3 increases the level of plasma triglycerides through an LPL-independent mechanism. We administered an inhibitor of APOC3 messenger RNA (mRNA), called ISIS 304801, to treat three patients with the familial chylomicronemia syndrome and triglyceride levels ranging from 1406 to 2083 mg per deciliter (15.9 to 23.5 mmol per liter). After 13 weeks of study-drug administration, plasma APOC3 levels were reduced by 71 to 90% and triglyceride levels by 56 to 86%. During the study, all patients had a triglyceride level of less than 500 mg per deciliter (5.7 mmol per liter) with treatment. These data support the role of APOC3 as a key regulator of LPL-independent pathways of triglyceride metabolism.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.251
Teacher spread0.240 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations493
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueNew England Journal of MedicineSame topicLipid metabolism and disordersFrench-language works237,207