The whole‐brain voxel‐based morphometry study in early stage of T2DM patients
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Bibliographic record
Abstract
AIM: This study aimed to investigate the alterations in whole-brain gray matter density in early stage type 2 diabetes mellitus (T2DM) patients with cognitive impairment using magnetic resonance imaging. METHODS: Thirty-six cases of early stage T2DM patients with cognitive impairment (T2DM-CI), 34 cases of early stage T2DM patients without cognitive impairment (T2DM) and 30 cases of healthy controls (HC) were enrolled. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores were used to identify the cognitive impairment. The whole-brain gray matter density was analyzed using 3D-T1 BRAVO imaging, using the voxel-based morphometry method on T1 structure imaging of two groups. RESULTS: The correlation analysis of total gray matter density with MMSE and MoCA scores in the T2DM-CI group was performed. There were no significant differences in MMSE and MoCA scores between the HC and T2DM groups. However, the MMSE and MoCA scores in the T2DM-CI group were significantly reduced compared with the T2DM group. There were no significant differences in age, gender, education, body mass index (BMI) or blood pressure among the three groups. Voxel-based morphometry (VBM) results showed that the density of left triangle part of inferior frontal gyrus, orbital part of inferior frontal gyrus and opercular part of inferior frontal gyrus and left insula in the T2DM-CI group decreased compared with the T2DM group. Correlation analysis results showed that there was a significant positive correlation between total gray matter density and scores of MMSE and MoCA scores in the T2DM-CI group. CONCLUSION: In conclusion, total gray matter density is positively correlated with the scores of MMSE and MoCA in T2DM patients, which may be an early sign of cognitive impairment in patients with T2DM.
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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 | 0.001 | 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 it