Whey Protein Phospholipid Concentrate Supplementation Prevents High-Fat Diet Induced Cognitive Impairment in Wistar Rats by Promoting Brain Neuronal Connectivity and Sphingolipid Clearance
Bibliographic record
Abstract
Abstract Whey protein phospholipid concentrate (WPPC), a byproduct of whey protein processing, is high in phospholipids and glycoconjugates which serve as substrates for fatty acids and sugar monomers (e.g. sialic acid) critical to neuronal myelin synthesis in the brain. This led us to hypothesize that WPPC will improve cognitive impairment induced by a high fat (HF) diet by promoting myelin turnover and improving myelin-dependent processes associated with encoding and storing memory. Male Wistar rats were randomized to one of four diets starting at weaning to ∼6.5 months on age: a low-fat (LF) diet containing 10% fat by weight, a HF diet containing 45% fat by weight to induce cognitive impairment, and a HF diet containing either 1.6% or 10% WPPC by weight (n=12 per diet). Rats were subjected to cognitive testing after 2 and 4 months of dietary intervention and then implanted with chronic bipolar electrodes to measure axonal evoked responses within the entorhinal cortex-hippocampal circuitry. Phospholipid and sphingolipid components of myelin were quantified in the hippocampus. There were no significant differences in cognition measured by novel object recognition after 2 months of supplementation. At 4 months, rats on the HF diet performed significantly worse than rats on the LF, HF1.6 and HF10 diets. The beneficial effects of WPPC on cognition were due to a partial reversal in evoked response impairments in hippocampal memory storage. Additionally, hippocampus sphingolipids were higher in rats on the HF diet compared to the LF, HF1.6 and HF10 groups. These findings demonstrate that WPPC prevented cognitive impairment induced by a HF diet by regulating entorhinal cortex-hippocampal circuitries associated with memory storage, though modulating myelin turnover.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".