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Record W2577296060 · doi:10.1186/s12986-016-0158-y

Efficacy of a novel formulation of L-Carnitine, creatine, and leucine on lean body mass and functional muscle strength in healthy older adults: a randomized, double-blind placebo-controlled study

2017· article· en· W2577296060 on OpenAlexaff
Malkanthi Evans, Najla Guthrie, John C. Pezzullo, Toran Sanli, Roger A. Fielding, Aouatef Bellamine

Bibliographic record

VenueNutrition & Metabolism · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsKGK Synergize (Canada)
FundersU.S. Department of Agriculture
KeywordsCarnitinePlaceboCreatineLean body massMedicineCreatine MonohydrateInternal medicinePopulationSarcopeniaClinical nutritionRandomized controlled trialPhysical therapyLeg pressEndocrinologyMuscle strengthPathologyBody weight

Abstract

fetched live from OpenAlex

Progressive decline in skeletal muscle mass and function are growing concerns in an aging population. Diet and physical activity are important for muscle maintenance but these requirements are not always met. This highlights the potential for nutritional supplementation. As a primary objective, we sought to assess the effect of a novel combination of L-Carnitine, creatine and leucine on muscle mass and performance in older subjects. Forty-two healthy older adults aged 55–70 years were randomized to receive either a novel L-Carnitine (1500 mg), L-leucine (2000 mg), creatine (3000 mg), Vitamin D3 (10 μg) (L-Carnitine-combination) product ( n = 14), L-Carnitine (1500 mg) ( n = 14), or a placebo ( n = 14) for eight weeks. We evaluated body mass by DXA, upper and lower strength by dynamometry, and walking distance by a 6-min walk test at baseline and after eight weeks of intervention. These measures, reflecting muscle mass, functional strength and mobility have been combined to generate a primary composite score. Quality of life, blood safety markers, and muscle biopsies for protein biomarker analysis were also conducted at baseline and the end of the study. The primary composite outcome improved by 63.5 percentage points in the L-Carnitine-combination group vs. placebo ( P = 0.013). However, this composite score did not change significantly in the L-Carnitine group ( P = 0.232), and decreased slightly in the placebo group ( P = 0.534). Participants supplemented with the L-Carnitine-combination showed a 1.0 kg increase in total lean muscle mass ( P = 0.013), leg lean muscle mass (0.35 kg, P = 0.005), and a 1.0 kg increase in lower leg strength ( P = 0.029) at week 8. In addition, these increases were significant when compared to the placebo group (P = 0.034, P = 0.026, and P = 0.002, respectively). Total mTOR protein expression was increased in participants in the L-Carnitine-combination group at the end of the study compared to the baseline ( P = 0.017). This increase was also significant when compared to the placebo ( P = 0.039), suggesting that the increase in muscle mass and strength was due to new protein synthesis and mTOR pathway activation. The trial did reach its primary objective. L-Carnitine combined with creatine and L-leucine significantly improved the composite score which reflects muscle mass and strength, at the end of the study compared to placebo. The combination showed an increase in mTOR protein level, a driver for increased muscle mass which translated to an improvement in muscle strength. This new combination may provide a potential nutritional intervention to promote muscle growth and improved physical functioning in older adults.

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)0.002
metaresearch head score (Gemma)0.001
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: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.290
Teacher spread0.269 · 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

Citations59
Published2017
Admission routes1
Has abstractyes

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