Sequence of episodic memory-related behavioral and brain-imaging abnormalities in type 2 diabetes
Bibliographic record
Abstract
BACKGROUND: Episodic memory decline is a common complication of type 2 diabetes (T2D). To comprehensively explore the neural mechanisms underlying it, we aimed to explore the sequence that episodic memory-related behavioral and brain-imaging biomarkers appear abnormal in the progression of T2D. METHODS: We enrolled 62 healthy controls and 110 patients with T2D. The California Verbal Learning Test, Montreal cognitive assessment, and Stroop color word test was used to assess the episodic memory, general cognitive function, and executive function. Principal component analysis was applied to extract behavioral biomarkers. Imaging biomarkers included structural and functional MRI features of the entorhinal cortex-hippocampus and hippocampus-anterior cingulate cortex pathways. We used a novel discriminative event-based model to determine the sequence that memory-related biomarkers appear abnormal and estimate the stage of memory decline. RESULTS: T2D patients exhibited poorer memory, general cognitive function, and executive function compared to healthy controls after controlling age, sex, and education level. In the progression of T2D, functional interaction between brain regions showed abnormalities first, followed by memory tests, the cerebral spontaneous neural activity, and finally the gray matter volume. Besides, abnormalities appeared earlier in the entorhinal cortex than in the anterior cingulate cortex. Later stage of memory decline was distributed in older patients with T2D and was associated with higher systolic blood pressure, postprandial blood glucose, and low-density lipoprotein. CONCLUSIONS: In T2D, behavioral and brain imaging biomarkers of episodic memory appear abnormal in a specific sequence, and the stage of memory decline was closely associated with old age and vascular risk factors. CLINICAL TRIAL REGISTRATION: NCT02420470, ClinicalTrials.gov ( https://www. CLINICALTRIALS: gov/ ).
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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 | 0.001 | 0.001 |
| 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".