Investigating the impact of type 2 diabetes mellitus on brain function in obstructive sleep apnea patients using regional homogeneity and seed-based functional connectivity methods
Bibliographic record
Abstract
Objective: This study aims to investigate the effects of Type 2 Diabetes Mellitus (T2DM) on brain function in patients with Obstructive Sleep Apnea (OSA) using Regional Homogeneity (ReHo) combined with seed-based Functional Connectivity (FC) methods. Materials and methods: 46 OSA patients, 38 OSA with T2DM patients, and 34 healthy controls (HC) were prospectively recruited. Clinical data were collected from all participants, and neuropsychological testing was performed using the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and Epworth Sleepiness Scale (ESS). Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected, and ReHo combined with seed-based FC analysis was used to assess brain function differences among the three groups. Finally, partial correlation analysis was conducted to investigate the relationship between clinical variables and imaging metrics ofthe differential brain regions. Results: Compared to HCs group, the OSA group showed increased ReHo in the left occipital gyrus, and decreased ReHo in the right fusiform gyrus and left cerebellum region 8. Furthermore, FC between the left occipital gyrus and left cerebellum region 8, as well as between the right fusiform gyrus and left cerebellum region 3, was significantly decreased. Partial correlation analysis revealed a significant negative correlation between ReHo in the right fusiform gyrus and the Oxygen Desaturation Index (ODI), and a significant positive correlation between FC in the left cerebellum region 8 and MMSE scores. Compared to the OSA group, the OSA with T2DM group exhibited decreased ReHo in the left occipital gyrus, with increased FC between the left occipital gyrus and left thalamus. Partial correlation analysis showed that ReHo in the left occipital gyrus was significantly negatively correlated with the Insulin Resistance Index (IRI), while FC in the left thalamus was negatively correlated with MoCA scores and positively correlated with hemoglobinA1c (HbA1c) levels. Conclusion: T2DM affects brain function in OSA patients, further exacerbating cognitive burden. These findings provide valuable insights into the neuropathological mechanisms ofT2DM in OSA and support the development of objective neuroimaging biomarkers.
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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 | 0.001 | 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".