Selective Probiotic Treatment Positively Modulates the Microbiota–Gut–Brain Axis in the BTBR Mouse Model of Autism
Bibliographic record
Abstract
Recent studies have shown promise for the use of probiotics in modulating behaviour through the microbiota–gut–brain axis. In the present study, we assessed the impact of two probiotic strains in mitigating autism-related symptomology in the BTBR T+ Itpr3tf/J mouse model of autism spectrum disorder (ASD). Male juvenile BTBR mice were randomized into: (1) control, (2) Lr probiotic (1 × 109 CFU/mL Lacticaseibacillus rhamnosus HA-114), and (3) Ls probiotic groups (1 × 109 CFU/mL Ligilactobacillus salivarius HA-118) (n = 18–21/group), receiving treatments in drinking water for 4 weeks. Gut microbiota profiling by 16S rRNA showed Lr, but not Ls supplementation, to increase microbial richness and phylogenetic diversity, with a rise in potential anti-inflammatory and butyrate-producing taxa. Assessing serum and brain metabolites, Lr and Ls supplementation produced distinct metabolic profiles, with Lr treatment elevating concentrations of potentially beneficial neuroactive compounds, such as 5-aminovaleric acid and choline. As mitochondrial dysfunction is often observed in ASD, we assessed mitochondrial oxygen consumption rates in the prefrontal cortex and hippocampus. No differences were observed for either treatment. Both Lr and Ls treatment reduced behavioural deficits in social novelty preference. However, no changes in hyperactivity, repetitive behaviour, and sociability were observed. Results show Lr to impart positive changes along the microbiota–gut–brain axis, exhibiting beneficial effects on selected behaviour, gut microbial diversity, and metabolism in BTBR mice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".