Impaired spatial navigation and age‐dependent hippocampal synaptic dysfunction are associated with chronic inflammatory response in db/db mice
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) increases the risk of developing Alzheimer's disease (AD), which has been proposed to be driven by an abnormal neuroinflammatory response affecting cognitive function. However, the impact of T2DM on hippocampal function and synaptic integrity during aging has not been investigated. Here, we investigated the effects of aging in T2DM on AD-like pathology using the leptin receptor-deficient db/db mouse model of T2DM. Our results indicate that adult T2DM mice exhibited impaired spatial acquisition in the Morris water maze (MWM). Morphological analysis showed an age-dependent neuronal loss in the dentate gyrus. We found that astrocyte density was significantly decreased in all regions of the hippocampus in T2DM mice. Our analysis showed that microglial activation was increased in the CA3 and the dentate gyrus of the hippocampus in an age-dependent manner in T2DM mice. However, the expression of presynaptic marker protein (synaptophysin) and the postsynaptic marker protein [postsynaptic density protein 95 (PSD95)] was unchanged in the hippocampus of adult T2DM mice. Interestingly, synaptophysin and PSD95 expression significantly decreased in the hippocampus of aged T2DM mice, suggesting an impaired hippocampal synaptic integrity. Cytokine profiling analysis displayed a robust pro-inflammatory cytokine profile in the hippocampus of aged T2DM mice compared with the younger cohort, outlining the role of aging in exacerbating the neuroinflammatory profile in the diabetic state. Our results suggest that T2DM impairs cognitive function by promoting neuronal loss in the dentate gyrus and triggering an age-dependent deterioration in hippocampal synaptic integrity, associated with an aberrant neuroinflammatory response.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".