Gut microbiota manipulation in neurodevelopmental disorders: implication from animal models of infantile epilepsy
Bibliographic record
Abstract
Infantile epileptic spasms syndrome (IESS) is a devastating early-onset epileptic encephalopathy with a poor neurodevelopmental prognosis. Accumulating evidence proposes an important role of gut microbiota in neurodevelopmental disorders via microbiota-gut-brain axis. In a neonatal rat model of IESS, we show both the ketogenic diet and antibiotic administration to reduce seizure frequency and to be associated with improved developmental outcomes. Seizure reductions were accompanied by specific gut microbial alterations including increases in Streptococcus thermophilus and Lactococcus lactis. Mimicking the fecal microbial alterations in a targeted probiotic, we administered these species in a 5:1 ratio. Probiotic administration reduced seizures and improved locomotor activities in control diet-fed animals, similar to KD-fed animals while a negative control (Ligilactobacillus salivarius) had no impact. These results suggest that a targeted microbiota manipulation could improve behavior outcome in infantile epilepsy and provides new insights into microbiota manipulation as a therapeutic avenue for neurodevelopmental disorders. Link to OA paper: https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(22)00017-2/fulltext
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".