Lactobacilli and bifidobacteria ameliorate memory and learning deficits and oxidative stress in β-amyloid (1–42) injected rats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 × 10 10 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.
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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 | 0.000 | 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 | 0.000 |
| 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 it