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Record W3178651283 · doi:10.1016/j.celrep.2021.109336

Distribution of dietary protein intake in daily meals influences skeletal muscle hypertrophy via the muscle clock

2021· article· en· W3178651283 on OpenAlexfundno aff
Shinya Aoyama, Hyeon-Ki Kim, Rina Hirooka, Mizuho Tanaka, Takeru Shimoda, Hanako Chijiki, Shuichi Kojima, Keisuke Sasaki, Kengo Takahashi, Saneyuki Makino, Miku Takizawa, Masaki Takahashi, Yu Tahara, Shigeki Shimba, Kazuyuki Shinohara, Shigenobu Shibata

Bibliographic record

VenueCell Reports · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
FundersBio-oriented Technology Research Advancement InstitutionJapan Society for the Promotion of ScienceJapan Society of Nutrition and Food ScienceCouncil for Science, Technology and InnovationNational Agriculture and Food Research OrganizationSwine Innovation Porc
KeywordsSkeletal muscleMuscle hypertrophyMuscle proteinInternal medicineDietary proteinEndocrinologyDistribution (mathematics)SarcopeniaBiologyChemistryCell biologyMedicine

Abstract

fetched live from OpenAlex

or muscle-specific Bmal1 knockout mice. Additionally, we examined the relationship between the distribution of proteins in meals and muscle functions, such as skeletal muscle index and grip strength in humans. Higher muscle functions were observed in subjects who ingested dietary proteins mainly at breakfast than at dinner. These data suggest that protein intake at breakfast may be better for the maintenance of skeletal muscle mass.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.291
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

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 head0.009
GPT teacher head0.221
Teacher spread0.213 · 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.

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

Citations68
Published2021
Admission routes1
Has abstractyes

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