Altered brain spontaneous and synchronization activity in latent autoimmune diabetes in adults: A resting‐state functional MRI study
Bibliographic record
Abstract
AIMS: This study aimed to explore the clinical features and spontaneous brain activity among patients with latent autoimmune diabetes in adults (LADA) and to investigate the relationship among these characteristics. METHODS: We conducted a cross-sectional study using cognitive assessments and resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate the cognitive function and brain activities of healthy controls (HCs) and patients with LADA. Functional connectivity (FC) analysis was performed on the brain regions that showed significantly different activation in regional homogeneity (ReHo) analysis between the two groups. Furthermore, a linear regression model was conducted for the association between metabolism and cognition. RESULTS: This study enrolled patients with LADA (and age-, sex-, and education-matched HCs). Patients with LADA had worse cognitive status at the general level and poorer memory than controls. Rs-fMRI analysis among patients with LADA showed decreased ReHo values in the right occipital lobe and temporal lobe and decreased seed-based FC in the right parietal lobe compared to those of controls. The seed-based FC values in the right parietal lobe were positively associated with word fluency and processing speed in patients with LADA. Furthermore, low-density lipoprotein cholesterol was negatively correlated with Montreal Cognitive Assessment scores in patients with LADA. CONCLUSIONS: Patients with LADA had worse cognitive function and decreased spontaneous brain activity in the temporal lobe and occipital lobe compared to controls. Moreover, glycolipid metabolism was closely related to brain structure and function in patients with LADA.
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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 | 0.001 |
| 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) | 0.001 | 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".