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Record W4381185894 · doi:10.1111/epi.17688

Intermittent vs continuous ketogenic diet: Impact on seizures, gut microbiota, and mitochondrial metabolism

2023· article· en· W4381185894 on OpenAlexafffund
Jane Shearer, Morris H. Scantlebury, Jong M. Rho, Thomas A. Tompkins, Chunlong Mu

Bibliographic record

VenueEpilepsia · 2023
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsHotchkiss Brain InstituteLallemand (Canada)Alberta Children's HospitalUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta Children's Hospital Research InstituteMitacs
KeywordsKetogenic dietBioenergeticsEpilepsyEndocrinologyBiologyInternal medicineGut floraStreptococcusFecesMetabolismMitochondrionMedicineImmunologyBiochemistryNeuroscienceMicrobiologyBacteria

Abstract

fetched live from OpenAlex

We have shown previously that the ketogenic diet (KD) is effective in reducing seizures associated with infantile spasms syndrome (ISS) and that this benefit is related to alterations in the gut microbiota. However, it remains unclear whether the efficacy of the KD persists after switching to a normal diet. Employing a neonatal rat model of ISS, we tested the hypothesis that the impact of the KD would diminish when switched to a normal diet. Following epilepsy induction, neonatal rats were divided into two groups: continuous KD for 6 days; and a group fed with KD for 3 days and then a normal diet for 3 days. Spasms frequency, mitochondrial bioenergetics in the hippocampus, and fecal microbiota were evaluated as major readouts. We found that the anti-epileptic effect of the KD was reversible, as evidenced by the increased spasms frequency in rats that were switched from the KD to a normal diet. The spasms frequency was correlated inversely with mitochondrial bioenergetic function and a set of gut microbes, including Streptococcus thermophilus and Streptococcus azizii. These findings suggest that the anti-epileptic and metabolic benefits of the KD decline rapidly in concert with gut microbial alterations in the ISS model.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.014
GPT teacher head0.288
Teacher spread0.273 · 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 designNot applicable
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

Citations21
Published2023
Admission routes2
Has abstractyes

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