Altered static and dynamic intrinsic brain activity patterns in type 2 diabetic patients
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia resulting from insulin secretion and/or resistance. This study investigated intrinsic brain activity alterations using static and dynamic resting-state fMRI metrics in 65 T2DM patients versus 60 healthy controls. We analyzed fractional amplitude of low-frequency fluctuations (fALFF), dynamic fALFF (dfALFF) and dynamic functional stability(DFS). The T2DM group exhibited increased fALFF in the left inferior temporal gyrus and left fusiform gyrus and decreased fALFF in the bilateral precuneus, medial superior frontal gyrus, left inferior parietal lobule, and right supramarginal gyrus when compared with health controls. The T2DM group also showed increased dfALFF in the bilateral precuneus, left inferior parietal lobule, and right middle frontal gyrus. Moreover, the T2DM group exhibited decreased DFS in the bilateral precuneus, supramarginal gyrus, and left middle frontal gyrus, while the left cuneus showed increased dynamic stability. In the T2DM group, montreal cognitive assessment (MoCA) scores correlated negatively with glycated hemoglobin A 1c (HbA 1c ) and fasting blood glucose (FBG), and positively with right supramarginal gyrus acticity in both fALFF and DFS difference regions, Multiple brain regions exhibiting fALFF and DFS alterations showed negative correlations with fasting blood glucose and total cholesterol. These findings indicate that T2DM brain activity demonstrates a distinctive “low-intensity, highly-fluctuating, and destabilized” pattern, suggesting complex neural network dysfunction beyond simple functional suppression.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".