Lactobacilli and bifidobacteria ameliorate memory and learning deficits and oxidative stress in β-amyloid (1–42) injected rats
Bibliographic record
Abstract
The gastrointestinal microbiota affects brain function, including memory and learning. In this study we investigated the effects of probiotics on memory and oxidative stress biomarkers in an experimental model of Alzheimer’s disease. Sixty rats were randomly divided into 5 groups: control; control-probiotics, which received probiotics for 8 weeks; sham operation, which received an intrahippocampal injection of phosphate-buffered saline; Alzheimer, which received an intrahippocampal injection of β-amyloid (Aβ1–42); and Alzheimer-probiotics, which in addition to being injected with Aβ1–42, received 2 g (1 × 1010 CFU/g) of probiotics (Lactobacillus acidophilus, L. fermentum, Bifidobacterium lactis, and B. longum) for 8 weeks. Memory and learning were measured using the Morris water maze, and oxidative stress biomarkers in the hippocampus were measured using ELISA kits. Morris water maze results indicated that compared with the Alzheimer group, the Alzheimer-probiotics group had significantly improved spatial memory, including shorter escape latency and travelled distance and greater time spent in the target quadrant. There was also improvement in oxidative stress biomarkers such as increased malondialdehyde levels and superoxide dismutase activity following the β-amyloid injection. Overall, it seems that probiotics play a role in improving memory deficit and inhibiting the pathological mechanisms of Alzheimer’s disease by modifying microbiota.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".