Topological Analysis of Brain Glucose Metabolic Connectivity Networks of Patients with Type 2 Diabetes Mellitus Combined with Mild Cognitive Impairment
Notice bibliographique
Résumé
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 (P<0.05). There was no statistically significant difference of the global efficiency between the control group and the observation group (P>0.05). Compared with the control group, the degree centralities of the left parahippocampal gyrus (P=0.005), left hippocampus (P=0.013), left subparietal marginal angular gyrus (P=0.031), left angular gyrus (P=0.034), right angular gyrus (P=0.013), right subparietal marginal angular gyrus (P=0.044), and right parahippocampal gyrus (P=0.024) of the observation group were significantly lower. The nodal local efficiencies of the left straight gyrus (P=0.028), left parahippocampal gyrus (P=0.044), left hippocampus (P=0.026), left subparietal angular gyrus (P=0.031), left angular gyrus (P=0.024), right angular gyrus (P=0.004), right subparietal angular gyrus (P=0.039) decreased significantly. Correlation analyses showed that, degree centrality of left hippocampal (r=-0.273, P=0.022) and left hippocampal parahippocampal gyrus (r=-0.341, P=0.004) were negatively correlated with EcogPtMem score. The degree centrality of left hippocampal (r=-0.391, P=0.001), left hippocampal parahippocampal gyrus (r=-0.410, P<0.001), and right hippocampal parahippocampal gyrus (r=-0.240, P=0.045) were negatively correlated with EcogSPMem score. The nodal local efficiencies of the left hippocampal (r=-0.257, P=0.032), left parahippocampal gyrus(r=-0.251, P=0.036), and right angular gyrus (r=-0.265, P=0.027) were negatively correlated with the EcogPtMem score. The nodal local efficiencies of left hippocampal (r=-0.363, P=0.002) and left parahippocampal gyrus (r=-0.362, P=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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».