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Daily Consumption of a Chocolate Rich in Flavonoids Decreases Cellular Genotoxicity and Improves Biochemical Parameters of Lipid and Glucose Metabolism

2018· preprint· en· W3123191947 on OpenAlexaff
Aldo Leyva‐Soto, Linda Lara-Jacobo, Lina Natalia Gonzalez-Cobian, Rocío Alejandra Chávez-Santoscoy

Bibliographic record

VenuePreprints.org · 2018
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsInstitut National de la Recherche Scientifique
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsDark chocolatePlaceboFood scienceGenotoxicityDiabetes mellitusWaistCholesterolMedicineChemistryObesityTraditional medicineInternal medicineEndocrinologyToxicity

Abstract

fetched live from OpenAlex

In recent years, Atherosclerotic Cardiovascular Disease (ACVD), Obesity and Diabetes, have increase exponentially worldwide. In the present work, we evaluate the genoprotective effect of consuming a flavonoids-rich chocolate and the improvement in the biochemical parameters related to the prevention and treatment of cardiovascular risk and metabolic syndrome in young Mexican adults. A randomized, placebo-controlled, double-blind study was undertaken in the Autonomous University of Baja California. The treatments were a daily intake of 2 grams of dark chocolate containing 70% cooca or milk chocolate. Total phenolic compounds and flavonoids were evaluated in both chocolates. Anthropometrical and Biochemical parameters were measured in the 84 participants before and after the study. Buccal epithelial genotoxicity was also evaluated from the beginning to the end of the experiment in the participants. Result suggested that flavonoids of cocoa intake have protective effects against DNA damage, and Biochemical parameters (total cholesterol, triglycerides, and LDL-cholesterol level in blood) and anthropometrical parameters (waist circumference) were also improved after six months of daily intake of 2 grams of dark chocolate with a 70% of cocoa.

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 score0.180
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.001
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 head0.060
GPT teacher head0.269
Teacher spread0.209 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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