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Ketogenic Diet Acts on Body Remodeling and MicroRNAs Expression Profile

2018· article· en· W2902015555 on OpenAlexaboutno aff
Roberto Cannataro, Mariarita Perri, Luca Gallelli, Maria Cristina Caroleo, Giovambattista De Sarro, Erika Cione

Bibliographic record

VenueMicroRNA · 2018
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
FundersRegione CalabriaUniversità della Calabria
KeywordsmicroRNAAnthropometryKetogenic dietMedicineObesityInternal medicineEndocrinologyBiologyBioinformaticsBiochemistryGene

Abstract

fetched live from OpenAlex

BACKGROUND: The Ketogenic Diet (KD) promotes metabolic changes and optimizes energy metabolism. It is unknown if microRNAs (miRs) are influenced by KD in obese subjects. The screening of circulating miRs was performed with the FDA approved platform n-counter flex and blood biochemical parameters were dosed by ADVIA 1800. OBJECTIVES: The aim of this study was to evaluate mir profile under 6 weeks of biphasic KD in obese subjects. We enrolled 36 obese subjects (18 females and 18 males) in stage 1 of Edmonton Obesity Staging System (EOSS) parameter. RESULT: Any correlation was found between biochemical parameter and three miRs, hsa-let-7b-5p, hsa-miR-143-3p and hsa-miR-504-5p influenced in an equal manner in both sexes. The KD resulted safe and ameliorate both biochemical and anthropometric factors in obese subjects re-collocating them into stage 0 of EOSS parameters. CONCLUSION: The miRs herein identified under KD might be a useful tool to monitor low carbohydrate nutritional regimens which reflect indirectly the regulatory biochemical mechanisms and cell signaling that orchestrate metabolic and signaling pathways.

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 score0.316
Threshold uncertainty score0.542

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 head0.022
GPT teacher head0.284
Teacher spread0.262 · 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

Citations63
Published2018
Admission routes1
Has abstractyes

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