<i>Lacticaseibacillus rhamnosus</i> HA-114 and <i>Bacillus subtilis</i> R0179 Prolong Lifespan and Mitigate Amyloid-β Toxicity in <i>C. elegans</i> via Distinct Mechanisms
Bibliographic record
Abstract
Background: Recent advances linking gut dysbiosis with neurocognitive disorders such as Alzheimer's disease (AD) suggest that the microbiota-gut-brain axis could be targeted for AD prevention, management, or treatment. Objective: We sought to identify probiotics that can delay Aβ-induced paralysis. Methods: Using C. elegans expressing human amyloid-β (Aβ)1-42 in body wall muscles (GMC101), we assessed the effects of several probiotic strains on paralysis. Results: We found that Lacticaseibacillus rhamnosus HA-114 and Bacillus subtilis R0179, but not their supernatants or heat-treated forms, delayed paralysis and prolonged lifespan without affecting the levels of amyloid-β aggregates. To uncover the mechanism involved, we explored the role of two known pathways involved in neurogenerative diseases, namely mitophagy, via deletion of the mitophagy factor PINK-1, and fatty acid desaturation, via deletion of the Δ9 desaturase FAT-5. Pink-1 deletion in GMC101 worms did not modify the life-prolonging and anti-paralysis effects of HA-114 but reduced the protective effect of R0179 against paralysis without affecting its life-prolonging effect. Upon fat5 deletion in GMC101 worms, the monounsaturated C14:1 and C16:1 FAs conserved their beneficial effect while the saturated C14:0 and C16:0 FAs did not. The beneficial effects of R0179 on both lifespan and paralysis remained unaffected by fat-5 deletion, while the beneficial effect of HA-114 on paralysis and lifespan was significantly reduced. Conclusions: Collectively with clinical and preclinical evidence in other models, our results suggest that HA-114 or R0179 could be studied as potential therapeutical adjuncts in neurodegenerative diseases such as AD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".