Probiotics counteract hepatic steatosis caused by ketogenic diet and upregulate AMPK signaling in a model of infantile epilepsy
Bibliographic record
Abstract
BACKGROUND: Infantile spasms syndrome (IS) is a type of epilepsy affecting 1.6 to 4.5 per 10,000 children in the first year of life, often with severe lifelong neurodevelopmental consequences. Only two first-line pharmacological treatments currently exist for IS and many children are refractory to these therapies. In such cases, children are treated with the ketogenic diet (KD). While effective in reducing seizures, the diet can result in dyslipidemia over time. METHODS: Employing a neonatal Sprague-Dawley rat model of IS, we investigated how the KD affects hepatic steatosis and its modulation by a defined probiotic blend. A combination of multiple readouts, including malondialdehyde, fatty acid profiles, lipid metabolism-related enzyme mRNA expression, mitochondrial function, histone deacetylase activity, cytokines and chemokines were evaluated using liver homogenates. FINDINGS: The KD reduced seizures, but resulted in severe hepatic steatosis, characterized by a white liver, triglyceride accumulation, elevated malondialdehyde, polyunsaturated fatty acids and lower acyl-carnitines compared to animals fed a control diet. The KD-induced metabolic phenotype was prevented by the co-administration of a blend of Streptococcus thermophilus HA-110 and Lactococcus lactis subsp. lactis HA-136. This probiotic blend protected the liver by elevating pAMPK-mediated signaling and promoting lipid oxidation. The strains further upregulated the expression of caspase 1 and interleukin 18, which may contribute to their hepatoprotective effect in this model. INTERPRETATION: Our results suggest that early intervention with probiotics could be considered as an approach to reduce the risk of hepatic side effects of the KD in children who are on the diet for medically indicated reasons. FUNDING: This study was funded by the Alberta Children's Hospital Research Institute and Mitacs Accelerate Program (IT16942).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".