The Effect of Trehalose on Autophagy Gene Transcription and Ultrastructure in Neurons and Glia of 5-Month-Old db/db Mice, a Model of Type 2 Diabetes-Associated Neurodegeneration
Bibliographic record
Abstract
Type 2 diabetes is associated with the formation of features of Alzheimer’s disease (AD). A common mechanism appears to be the impairment of autophagy, making its stimulation a potential target for AD treatment. A good opportunity to study the correction of diabetes and neurodegeneration is provided by db/db mice, a model of diabetes and obesity that develop signs of AD with age. In our previous work, we found that db/db mice are amenable to treatment with the disaccharide trehalose, which activates autophagy via an mTOR-independent pathway. In 3-month-old mice, trehalose reduced obesity, attenuated hyperglycaemia, significantly activated autophagy in the brain, weakened neuroinflammation and oxidative stress, and restored cognitive impairment. It remains unclear to what extent the therapeutic effect of trehalose depends on the age of mice and on the activation of autophagy gene transcription and ultrastructural changes in neurons and glia cells. The therapeutic effect of treatment with 3% trehalose in drinking was investigated on 5-month-old db/db mice. Trehalose did not induce a significant decrease in the body mass or blood glucose and cholesterol levels but it decreased the expression of the insulin receptor gene Insr. There was a visual increase in the lipofuscin levels in cortical neurons and glial cells, while trehalose did not attenuate the accumulation of the marker. Thus, a differential effect of trehalose was obtained for 5-month-old db/db mice, consisting in the absence of activation of autophagy gene transcription or attenuation of lipofuscin accumulation. Apparently, the therapeutic effect of trehalose on the disturbances in db/db line mice decreases with age and becomes ineffective at 5 months of age.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".