Topological Analysis of Brain Glucose Metabolic Connectivity Networks of Patients with Type 2 Diabetes Mellitus Combined with Mild Cognitive Impairment
Bibliographic record
Abstract
ObjectiveTo analyze the changes in the topology of the brain glucose metabolic connectivity networks of patients with type 2 diabetes mellitus (T2DM) combined with mild cognitive impairment (MCI).MethodsA total of 35 T2DM&MCI subjects (observation group) and 35 healthy subjects (control group) were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Mini-mental state examination (MMSE) score, everyday cognition: the patient-reported memory (EcogPtMem) score, everyday cognition: the study partner-reported memory (EcogSPMem) score, and fluoro-2-deoxyglucose (FDG)-positron emission tomography (PET) images of both groups were included from the ANDI database. FDG-PET images were normalised to the Montreal neurological institute (MNI) spatial brain template by SPM 12 software. Using the cerebellum as reference area, standardized uptake value ratio (SUVR) of the anatomical automatic labeling (AAL) module brain regions of each subject was extracted to construct the glucose metabolism connectivity brain network. GRETNA software was used to analyze the topological properties of the brain network, including global efficiency, degree centrality, and node local efficiency. Spearman's correlation analysis was used to analyze the correlation of differential brain area degree centrality with EcogPtMem score as well as EcogSPMem score, and the correlation of node local efficiency with EcogPtMem score as well as EcogSPMem score.ResultsCompared with the control group, MMSE score of the observation group was significantly lower, EcogPtMem and EcogSPMem scores were significantly higher, and the differences were statistically significant (<italic>P</italic><0.05). There was no statistically significant difference of the global efficiency between the control group and the observation group (<italic>P</italic>>0.05). Compared with the control group, the degree centralities of the left parahippocampal gyrus (<italic>P</italic>=0.005), left hippocampus (<italic>P</italic>=0.013), left subparietal marginal angular gyrus (<italic>P</italic>=0.031), left angular gyrus (<italic>P</italic>=0.034), right angular gyrus (<italic>P</italic>=0.013), right subparietal marginal angular gyrus (<italic>P</italic>=0.044), and right parahippocampal gyrus (<italic>P</italic>=0.024) of the observation group were significantly lower. The nodal local efficiencies of the left straight gyrus (<italic>P</italic>=0.028), left parahippocampal gyrus (<italic>P</italic>=0.044), left hippocampus (<italic>P</italic>=0.026), left subparietal angular gyrus (<italic>P</italic>=0.031), left angular gyrus (<italic>P</italic>=0.024), right angular gyrus (<italic>P</italic>=0.004), right subparietal angular gyrus (<italic>P</italic>=0.039) decreased significantly. Correlation analyses showed that, degree centrality of left hippocampal (<italic>r</italic>=-0.273, <italic>P</italic>=0.022) and left hippocampal parahippocampal gyrus (<italic>r</italic>=-0.341, <italic>P</italic>=0.004) were negatively correlated with EcogPtMem score. The degree centrality of left hippocampal (<italic>r</italic>=-0.391, <italic>P</italic>=0.001), left hippocampal parahippocampal gyrus (<italic>r</italic>=-0.410, <italic>P</italic><0.001), and right hippocampal parahippocampal gyrus (<italic>r</italic>=-0.240, <italic>P</italic>=0.045) were negatively correlated with EcogSPMem score. The nodal local efficiencies of the left hippocampal (<italic>r</italic>=-0.257, <italic>P</italic>=0.032), left parahippocampal gyrus(<italic>r</italic>=-0.251, <italic>P</italic>=0.036), and right angular gyrus (<italic>r</italic>=-0.265, <italic>P</italic>=0.027) were negatively correlated with the EcogPtMem score. The nodal local efficiencies of left hippocampal (<italic>r</italic>=-0.363, <italic>P</italic>=0.002) and left parahippocampal gyrus (<italic>r</italic>=-0.362, <italic>P</italic>=0.002) were negatively correlated with EcogSPMem score.ConclusionThe abnormal topological structure of brain glucose metabolic connectivity network in patients with T2DM&MCI might be one of the reasons for the decline in memory, which could provide a reference for the exploring of the neural mechanism of patients with T2DM&MCI.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".