characteristics of papez loop neural network in t2dm （type 2 diabetes mellitus）

Conditions: Type 2 Diabetes; Insulin Resistance; Cognitive Impairment

Summary: this is a cross-sectional and longitudinal study to investigate the characteristic changes in papez's circuit neural network activity and connectivity based on multimodal mri, and through follow-up study of the interaction between the internal brain regions of papez circuit and the function of the external neural network, a prediction model of the characteristic changes of papez circuit neural network was constructed based on machine learning technology.

t2dm patients may have multidimensional cognitive impairment, which is related to the damage of key brain regions in papez's circuit. the purpose of this study is to establish a prediction model for the occurrence, development, and severity of cognitive impairment by using machine learning of papez circuit neural network in t2dm patients. this will allow for early intelligent assessment with high accuracy and efficiency, and assist in clinical personalized treatment and early intervention. the research center has 1 principal investigator, 4 sub-investigators, and 1 nurse. participants will include 200 patients with type 2 diabetes recruited from outpatient and inpatient departments. additionally, 200 healthy controls will be recruited from the community. each subject will undergo clinical information collection, biochemical measurements including fasting blood glucose, c-peptide, hba1c, blood lipid, postprandial blood glucose, and postprandial c-peptide, multimodal mri scans, and cognitive assessments at baseline and each follow-up visit. the study duration is 6 years, with a follow-up every 36 months. at the end of the study, all assessments will be performed again for all recruited subjects.

Eligibility criteria:
inclusion criteria: 1. t2dm patients met the diagnostic criteria for diabetes (who, 1999) with a duration of 3-20 years; the control group met the criteria of fasting blood glucose \< 6.1mmol/l and glycosylated hemoglobin \< 5.7%; 2. right-handed, aged 45-70 years, with ≥8 years of education; 3. no contraindications to mri scanning such as electronic and metal device implantation; 4. the visual acuity or corrected visual acuity and binaural hearing can meet the needs of the evaluation, and can cooperate to complete the examination. 5. without a history of substance abuse or dependence, evaluation is not used during the period of calm sleeping pills and antidepressants, not long-term use of drugs to improve cognitive. exclusion criteria: 1. patients with acute metabolic complications or a history of severe hypoglycemia; 2. severe heart, liver, lung, kidney and hematopoietic system diseases; hyperthyroidism or hypothyroidism; stroke, alzheimer's disease, epilepsy, parkinson's disease and other neurological history; a history of mental illness such as depression, mania, or alcohol dependence; history of loss of consciousness due to neurological diseases or traumatic brain injury; 3. one month before the laboratory examination, with a record and surgical trauma infection;

Keywords: type 2 diabetes insulin resistance papez circuit multimodal magnetic resonance imaging machine learning