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Record W2753038767 · doi:10.18433/j30d2v

Lipid Emulsion, More Than Reversing Bupivacaine Cardiotoxicity: Potential Organ Protection

2017· review· en· W2753038767 on OpenAlexvenueno aff
Negar Motayagheni, Sheshanna Phan, Ala Nozari, Anthony Atala

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2017
Typereview
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsnot available
Fundersnot available
KeywordsCardiotoxicityLipid emulsionEmulsionPharmacologyReversingFat emulsionMechanism (biology)Mechanism of actionMedicineChemistryIntensive care medicineBiochemistryToxicityParenteral nutritionInternal medicine

Abstract

fetched live from OpenAlex

Efforts to develop a treatment for bupivacaine cardiotoxicity led to the discovery that Intralipid, a popular brand of intravenous lipid emulsion, could be used not only as an effective treatment for anesthetic-induced cardiac arrest, but also as a means of reversing many other toxicities. Contradictory data exist regarding the mechanism of action of lipid emulsion, a combination of fatty acids traditionally used in parenteral nutrition. Some researchers attribute the effects to lipophilicity and the individual characteristics of the lipids, while other data demonstrate a direct empowering mechanism through cellular upstream and downstream pathways. Understanding the underlying mechanism of action of this safe source of calories may assist in the development of novel organ protective agents. In this review, some of the direct cardiac effects of lipid emulsion are briefly discussed. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

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 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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.003
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 head0.390
GPT teacher head0.508
Teacher spread0.118 · 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 teacher head, not a consensus.

Study designOther design
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

Citations13
Published2017
Admission routes1
Has abstractyes

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