The Anti-brain Ageing Effects of Krill Phosphatidylserine in SAMP10 Mice
Bibliographic record
Abstract
We examined the biological effect of krill phosphatidylserine (K-PS) on brain ageing and investigated the mechanisms that how K-PS works on the brain using senescence-accelerated mouse (SAM) model with age-associated neurodegeneration. SAMP10 mice with 5 months of age were treated orally once a day for 75 days with 10 or 100 mg kg?1 d?1 K-PS (low and high dose). The effect of K-PS treatment on the cross-sectional area and Nissl body number of the neocortex at point C, an area prone to atrophy in SAMP10 mice, behavior and oxidative stress were evaluated by Image-Pro Plus software, step-down testing, and malondialdehyde (MDA) and glutathione peroxidase (GSH-Px) assays. Ionized calcium binding adaptor molecule 1 (Iba-1) and insulin-like growth factor 1 (IGF-1) expression was evaluated using immunohistochemistry. Low or high doses of K-PS significantly increased the cross-sectional area and Nissl body number at point C, partly reversed memory impairment, increased the activity of GSH-Px and reduced MDA levels. Moreover, immunohistochemistry indicated that K-PS suppressed Iba-1 expression and upregulate the expression of IGF-1. These findings suggest that K-PS could prevent or slow the progression of brain atrophy and neuronal damage associated with aging by the inhibition of Iba-1 and the upregulation of IGF-1 expression.
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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) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".