Oral Trehalose Intake Modulates the Microbiota–Gut–Brain Axis and Is Neuroprotective in a Synucleinopathy Mouse Model
Bibliographic record
Abstract
Parkinson’s disease (PD) is a neurodegenerative disease affecting dopaminergic neurons in the nigrostriatal and gastrointestinal tracts, causing both motor and non-motor symptoms. This study examined the neuroprotective effects of trehalose. This sugar is confined in the gut due to the absence of transporters, so we hypothesized that trehalose might exert neuroprotective effects on PD through its action on the gut microbiota. We used a transgenic mouse model of PD (PrP-A53T G2-3) overexpressing human α-synuclein and developing GI dysfunctions. Mice were given water with trehalose, maltose, or sucrose (2% w/v) for 6.5 m. Trehalose administration prevented a reduction in tyrosine hydroxylase immunoreactivity in the substantia nigra (−25%), striatum (−38%), and gut (−18%) in PrP-A53T mice. It also modulated the gut microbiota, reducing the loss of diversity seen in PrP-A53T mice and promoting bacteria negatively correlated with PD in patients. Additionally, trehalose treatment increased the intestinal secretion of glucagon-like peptide 1 (GLP-1) by 29%. Maltose and sucrose, which break down into glucose, did not show neuroprotective effects, suggesting glucose is not involved in trehalose-mediated neuroprotection. Since trehalose is unlikely to cross the intestinal barrier at the given dose, the results suggest its effects are mediated indirectly through the gut microbiota and GLP-1.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".