Acute inflammatory events attenuate high-sucrose diet-induced neurodegenerative processes in reproductively normal female wild-type mice
Bibliographic record
Abstract
Abstract It is known that diabetic and chronic inflammatory conditions can increase the risk of Alzheimer’s disease (AD)-like neurodegeneration in isolation. As certain elements of the diabetic/pre-diabetic state may sensitize the brain to inflammatory insult ( i.e . excess glucocorticoid activity), there is reason to believe that obesogenic and inflammatory factors may accelerate neurodegeneration in a synergistic manner. Also, given that most AD research utilizes male animal models despite increased prevalence of AD among women, we sought to characterize elements of the established (in males) high-sucrose model of neurodegeneration, for the first time, in reproductively normal (pre-menopausal) female mice. A high-sucrose diet (20% of the drinking water) was combined with systemic intraperitoneal lipopolysaccharide (LPS) injections (0.1 mg/kg; 1x/month over 3 months) over seven months in reproductively normal female wild-type mice (C57Bl/6; n=10/group). Although a deleterious effect was hypothesized, low-dose LPS proved to protect against high sucrose diet-induced pathologies in female wild-type mice. Results from our high-sucrose group confirmed that a high-sucrose diet is a mild model of neurodegeneration in wild-type females, as evidenced by exaggerated glucocorticoid expression, spatial learning deficits, irregularities within the insulin pathway, and increased β-amyloid production and Tau phosphorylation. While LPS had little to no effect in isolation, it exerted a protective influence when added to animals sustained on a high-sucrose diet. Corticosterone homeostasis, and levels of amyloid-β (Aβ) and pTau were rescued following addition of LPS. The work presented supports a high-sucrose diet as a model of mild neurodegeneration in female mice and highlights a protective role for transient inflammation against dietary-insult that may be sex dependent.
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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 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".