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Record W3088718065 · doi:10.1111/vcp.12895

Lipoprotein characterization in Quaker parrots (<i>Myiopsitta monachus</i>) using gel‐permeation high‐performance liquid chromatography

2020· article· en· W3088718065 on OpenAlexafffund
Hugues Beaufrère, Sara Gardhouse, Mélanie Ammersbach

Bibliographic record

VenueVeterinary Clinical Pathology · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBird parasitology and diseases
Canadian institutionsUniversity of Guelph
FundersUniversity of GuelphQuaker
KeywordsVery low-density lipoproteinLipoproteinChromatographyHigh-performance liquid chromatographyTriglycerideChemistryCholesterolIntermediate-density lipoproteinHigh-density lipoproteinGel permeation chromatographyBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Lipid accumulation disorders, such as atherosclerosis and hepatic lipidosis, are common in psittacine birds and associated with various dyslipidemias. Gel-permeation high-performance liquid chromatography (GP-HPLC) is a reference method for advanced lipoprotein profiling based on particle size separation, followed by an analysis of lipid contents. OBJECTIVES: The objectives were to (a) characterize Quaker parrot lipoproteins using a commercial GP-HPLC method (Liposearch panel), and (b) obtain preliminary information on the reliability of the Friedewald formula for low-density lipoprotein-cholesterol (LDL-C) measurements. METHODS: Plasma samples were collected from 12 fasted healthy Quaker parrots. Cholesterol concentrations, triglyceride concentrations, particle sizes, and particle numbers were determined by GP-HPLC for four classes and 20 sub-fractions of lipoproteins. The LDL-C concentrations obtained using the Friedewald formula and direct measurements were compared with Bland-Altman plots. Alternate formulas were determined using multiple linear regression. RESULTS: High-density lipoprotein (HDL) was the predominant lipoprotein in Quaker parrots, and most particles were of medium-to-small sizes belonging to two sub-fractions (average size, 10.6 nm). LDL was the second most common lipoprotein and included large-to-small particles belonging to three sub-fractions (average size, 24.9 nm). Very-low-density lipoproteins (VLDL) and portomicrons were present in low concentrations. The Friedewald formula underestimated LDL-C concentrations with a significant bias of 0.44 mmol/L. An alternate formula was proposed: LDL-C = 0.75*Non-HDL-C. CONCLUSIONS: GP-HPLC allowed unprecedented characterization of plasma lipoproteins in Quaker parrots. Characterizing psittacine lipoprotein is useful for validation and interpretation of routine clinical tests as well as for use in epidemiologic and experimental research on psittacine lipid accumulation disorders.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.069
GPT teacher head0.325
Teacher spread0.255 · 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 designBench or experimental
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

Citations15
Published2020
Admission routes2
Has abstractyes

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