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Record W2614593555 · doi:10.1139/apnm-2016-0536

Daytime increase in caloric intake without change in total 24-h caloric intake can increase adiposity but not total bodyweight in rats with inverted feeding pattern

2017· article· en· W2614593555 on OpenAlexvenueno aff
Lanni Sarmento da Rocha, Rhowena Jane Barbosa de Matos, Julliet Araújo de Souza, Ana Carolina Oliveira Costa, Sandra Lopes de Souza, Gisélia de Santana Muniz, Elizabeth do Nascimento

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2017
Typearticle
Languageen
FieldMedicine
TopicDietary Effects on Health
Canadian institutionsnot available
Fundersnot available
KeywordsEndocrinologyCircadian rhythmInternal medicineGlycemicFood intakeMedicineAnimal scienceBiologyInsulin

Abstract

fetched live from OpenAlex

The goal of this study was to evaluate the effect of the food availability period on body weight, self-selection of macronutrients, adiposity, lipoprotein, and serum glucose profiles without changing energy intake. Young male rats were divided into 2 groups according to the availability of food during the light and dark phases of the cycle, forming 2 groups: control group (CG) and group with inverted feeding pattern (IFPG). Before inversion of food availability on the 80th day, circadian food intake was measured every 4 h over 24 h during 3 days. The glycemic curve, an oral test for glucose tolerance, and self-selection of macronutrients were evaluated. Blood samples were collected for analysis of fasting glucose, triglycerides, and total cholesterol fractions. The IFPG showed an increase in fasting glucose in the dark phase of the cycle, changes in the glycemic curve, and oral glucose tolerance test. It also showed increased abdominal and liver fat and distinct choice of macronutrients compared with the CG. A change in the availability of food according to the phase of the circadian cycle produces changes in glucose and feeding circadian rhythm culminating in increased abdominal and hepatic fat. These effects can increase the risk of metabolic disorders and installation of chronic diseases.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.267
Teacher spread0.245 · 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.

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

Citations9
Published2017
Admission routes1
Has abstractyes

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