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Record W2604554793 · doi:10.1017/jns.2017.4

Utilisation of supplemented<scp>l</scp>-carnitine for fuel efficiency, as an antioxidant, and for muscle recovery in Labrador retrievers

2017· article· en· W2604554793 on OpenAlexaboutno aff
Jessica L Varney, Jason W Fowler, William Gilbert, C.N. Coon

Bibliographic record

VenueJournal of Nutritional Science · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCarnitineTBARSSprintAnimal scienceLevocarnitineThiobarbituric acidAntioxidantMedicineCreatineLean body massCreatine kinaseChemistryBody weightInternal medicineBiologyBiochemistryPhysical therapyLipid peroxidation

Abstract

fetched live from OpenAlex

Abstract The primary goal was to investigate the effects ofl-carnitine on fuel efficiency, as an antioxidant, and for muscle recovery in Labrador retrievers. Dogs were split into two groups, with one group being supplemented with 250 mg/d of Carniking™l-carnitine powder. Two experiments (Expt 1 and Expt 2) were performed over a 2-year period which included running programmes, activity monitoring, body composition scans and evaluation of recovery using biomarkers. Each experiment differed slightly in dog number and design: fifty-sixv. forty dogs; one endurance and two sprint runs per weekv. two endurance runs; and differing blood collection time points. All dogs were fed a low-carnitine diet in which a fixed amount was offered based on maintaining the minimum starting weight. Results from Expt 1 found that the carnitine dogs produced approximately 4000 more activity points per km compared with the control group during sprint (P = 0·052) and endurance runs (P = 0·0001). Male carnitine dogs produced half the creatine phosphokinase (CPK) following exercise compared with male control dogs (P = 0·05). Carnitine dogs had lower myoglobin at 6·69 ng/ml following intensive exercise compared with controls at 24·02 ng/ml (P = 0·0295). Total antioxidant capacity (TAC) and thiobarbituric acid reactive substance (TBARS) results were not considered significant. In Expt 2, body composition scans indicated that the carnitine group gained more total tissue mass while controls lost tissue mass (P = 0·0006) and also gained lean mass while the control group lost lean mass (P < 0·0001). Carnitine dogs had lower CPK secretion at 23·06v. control at 28·37 mU/ml 24 h after post-run (P = 0·003). Myoglobin levels were lower in carnitinev. control dogs both 1 h post-run (P = 0·0157; 23·83v. 37·91 ng/ml) and 24 h post-run (P = 0·0189; 6·25v.13·5 ng/ml). TAC indicated more antioxidant activity in carnitine dogs at 0·16 mmv. control at 0·13 mm(P = 0·0496). TBARS were also significantly lower in carnitine dogs both pre-run (P = 0·0013; 15·36v. 23·42 µm) and 1 h post-run (P = 0·056; 16·45v. 20·65 µm). Supplementingl-carnitine in the form of Carniking™ had positive benefits in Labrador retrievers for activity intensity, body composition, muscle recovery and oxidative capacity.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.305
Teacher spread0.287 · 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

Citations21
Published2017
Admission routes1
Has abstractyes

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