Curcumin improves D-galactose and normal-aging associated memory impairment in mice: In vivo and in silico-based studies
Bibliographic record
Abstract
Aging-induced memory impairment is closely associated with oxidative stress. D-Galactose (D-gal) evokes severe oxidative stress and mimics normal aging in animals. Curcumin, a natural flavonoid, has potent antioxidant and anti-aging properties. There are several proteins like glutathione S-transferase A1 (GSTA1), glutathione S-transferase omega-1 (GSTO1), kelch-like ECH-associated protein 1 (KEAP1), beta-secretase 1 (BACE1), and amine oxidase [flavin-containing] A (MAOA) are commonly involved in oxidative stress and aging. This study aimed to investigate the interaction of curcumin to these proteins and their subsequent effect on aging-associated memory impairment in two robust animal models: D-Gal and normal aged (NA) mice. The aging mice model was developed by administering D-gal intraperitoneally (i.p). Mice (n = 64) were divided into the eight groups (8 mice in each group): Vehicle, Curcumin-Control, D-gal (100mg/kg; i.p), Curcumin + D-gal, Astaxanthin (Ast) + D-gal, Normal Aged (NA), Curcumin (30mg/kg Orally) + NA, Ast (20mg/kg Orally) + NA. Retention and freezing memories were assessed by passive avoidance (PA) and contextual fear conditioning (CFC). Molecular docking was performed to predict curcumin binding with potential molecular targets. Curcumin significantly increased retention time (p < 0.05) and freezing response (p < 0.05) in PA and CFC, respectively. Curcumin profoundly ameliorated the levels of glutathione, superoxide dismutase, catalase, advanced oxidation protein products, nitric oxide, and lipid peroxidation in mice hippocampi. In silico studies revealed favorable binding energies of curcumin with GSTA1, GSTO1, KEAP1, BACE1, and MAOA. Curcumin improves retention and freezing memory in D-gal and nature-induced aging mice. Curcumin ameliorates the levels of oxidative stress biomarkers in mice. Anti-aging effects of curcumin could be attributed to, at least partially, the upregulation of antioxidant enzymes through binding with GSTA1, GSTO1, KEAP1, and inhibition of oxidative damage through binding with BACE1 and MAOA.
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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 | 0.000 |
| 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".