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Record W3109889211 · doi:10.1093/ajcn/nqaa283

A high-protein total diet replacement increases energy expenditure and leads to negative fat balance in healthy, normal-weight adults

2020· article· en· W3109889211 on OpenAlexafffund
Camila L. P. Oliveira, Normand G. Boulé, Arya M. Sharma, Sarah A Elliott, Mario Siervo, Sunita Ghosh, Aloys Berg, Carla M. Prado

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta Innovates
KeywordsEnergy expenditureBalance (ability)Energy balanceAnimal scienceMedicineInternal medicineBody weightEndocrinologyBiologyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

BACKGROUND: High-protein diets and total diet replacements are becoming increasingly popular for weight loss; however, further research is needed to elucidate their impact on the mechanisms involved in weight regulation. OBJECTIVE: The aim of this inpatient metabolic balance study was to compare the impact of a high-protein total diet replacement (HP-TDR) versus a control diet (CON) on select components of energy metabolism in healthy adults of both sexes. METHODS: The acute intervention was a randomized, controlled, crossover design with participants allocated to 2 isocaloric arms: 1) HP-TDR: 35% carbohydrate, 40% protein, and 25% fat achieved through a nutritional supplement; 2) CON: 55% carbohydrate, 15% protein, and 30% fat. Participants received the prescribed diets for 32 h while inside a whole-body calorimetry unit (WBCU). The first dietary intervention randomly offered in the WBCU was designed to maintain energy balance and the second matched what was offered during the first stay. Energy expenditure, macronutrient oxidation rates and balances, and metabolic blood markers were assessed. Body composition was measured at baseline using DXA. RESULTS: Forty-three healthy, normal-weight adults (19 females and 24 males) were included. Compared with the CON diet, the HP-TDR produced higher total energy expenditure [(EE) 81 ± 82 kcal/d, P <0.001], protein and fat oxidation rates (38 ± 34 g/d, P <0.001; 8 ± 20 g/d, P = 0.013, respectively), and a lower carbohydrate oxidation rate (-38 ± 43 g/d, P <0.001). Moreover, a HP-TDR led to decreased energy (-112 ± 85 kcal/d; P <0.001), fat (-22 ± 20 g/d; P <0.001), and carbohydrate balances (-69 ± 44 g/d; P <0.001), and increased protein balance (90 ± 32 g/d; P <0.001). CONCLUSIONS: Our primary findings were that a HP-TDR led to higher total EE, increased fat oxidation, and negative fat balance. These results suggest that a HP-TDR may promote fat loss compared with a conventional isocaloric diet. These trials were registered at clinicaltrials.gov as NCT02811276 and NCT03565510.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.011
GPT teacher head0.293
Teacher spread0.281 · 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 designObservational
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

Citations23
Published2020
Admission routes2
Has abstractyes

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