Formaldehyde induces diabetes‐associated cognitive impairments
Bibliographic record
Abstract
Patients with type 2 diabetes mellitus (T2DM) often develop cognitive impairments and have an increased risk of developing Alzheimer's disease. Hyperglycemia is a major characteristic of T2DM, but how elevated glucose levels lead to cognitive decline remains elusive. Here, we report that patients with T2DM and mutations in the formaldehyde (FA)-degrading enzyme aldehyde dehydrogenase 2 ( ALDH2) gene had higher levels of FA and more severe dementia. Injection of FA induced hyperglycemia and cognitive deficits in rats. Ablation of gene expression of ALDH2, the main enzyme to oxidize FA, resulted in abnormally high levels of hippocampal FA, leading to hyperglycemia and cognitive impairments as well as potentiating streptozotocin-induced diabetes development in ALDH2 knockout mice. We found that FA interacts with insulin to form FA-insulin adducts, and these FA-insulin adducts caused insulin deficiency, contributing to memory decline in diabetic rodent models. Reduction of FA by transgenic overexpression of human ALDH2 attenuates hyperglycemia and alleviates cognitive deficits in diabetic mouse models. These findings suggest that excess FA plays a critical role in mediating diabetes-related dementia. Targeting FA and its metabolizing enzyme ALDH2 may be a valid approach for preventing and treating dementia in diabetes mellitus.-Tan, T., Zhang, Y., Luo, W., Lv, J., Han, C., Hamlin, J. N. R., Luo, H., Li, H., Wan, Y., Yang, X., Song, W., Tong, Z. Formaldehyde induces diabetes-associated cognitive impairments.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".