OBJECTIVE: To observe the effects of electroacupuncture (EA) on improving motor function and regulating microglial activation based on Notch receptor 1 (Notch1)/Hes family bHLH transcription factor 1 (Hes1) pathway in mice with Parkinson's disease (PD). METHODS: Thirty-six male C57BL/6 mice were randomly divided into a control group, a model group and an EA group, 12 mice in each group. PD model was established by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) for 7 consecutive days in the model group and the EA group. From the 1st day of modeling, EA was applied at "Baihui" (GV20) and bilateral "Shenshu" (BL23) in the EA group, with continuous wave, in frequency of 2 Hz and current of 2 mA, 15 min a time, once a day for 14 days continuously. The behavioral performance was evaluated by gait test, pole climbing test and hanging test, the number of positive cells of tyrosine hydroxylase (TH) and the co-expression positive cells of Notch1/ionized calcium binding adaptor molecule 1 (Iba-1) in the substantia nigra of midbrain was assessed by immunofluorescence, the protein expression of TH, α-synuclein (α-syn), Notch1, Hes1, Iba-1, inducible nitric oxide synthase (iNOS), Arginase-1 (ARG1), tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, IL-6 and IL-10 was detected by Western blot, the mRNA expression of Notch1 and Hes1 was detected by real-time PCR. RESULTS: Compared with the control group, in the model group, the stride frequency was accelerated (P<0.001) and the stride length was shortened (P<0.001) for the four limbs, the pole climbing test time was prolonged (P<0.01) and the grip level was reduced (P<0.01); in the substantia nigra of midbrain, the number of positive cells of TH was decreased (P<0.001), the number of co-expression positive cells of Notch1/Iba-1 was increased (P<0.001), the protein expression of α-syn, Notch1, Hes1, Iba-1, iNOS, TNF-α, IL-1βand IL-6 was increased (P<0.01, P<0.05, P<0.001), the protein expression of TH, ARG1 and IL-10 was decreased (P<0.01, P<0.001), the mRNA expression of Notch1 and Hes1 was increased (P<0.01). Compared with the model group, in the EA group, the stride frequency was decelerated (P<0.001) and the stride length was increased (P<0.05, P<0.01, P<0.001) for the four limbs, the pole climbing test time was shortened (P<0.05) and the grip level was increased (P<0.05); in the substantia nigra of midbrain, the number of positive cells of TH was increased (P<0.01), the number of co-expression positive cells of Notch1/Iba-1 was decreased (P<0.001), the protein expression of α-syn, Notch1, Hes1, Iba-1, iNOS, TNF-α, IL-6 and IL-1β was decreased (P<0.05, P<0.01), the protein expression of TH, ARG1 and IL-10 was increased (P<0.05, P<0.001, P<0.01), the mRNA expression of Notch1 and Hes1 was decreased (P<0.05). CONCLUSION EA can improve the behavioral performance and protect the dopaminergic neurons in PD mice, its mechanism may relate to the inhibition of Notch1/Hes1-mediated neuroinflammation, thus inhibiting the microglial activation.
Animals ; Electroacupuncture ; Microglia/metabolism* ; Male ; Receptor, Notch1/metabolism* ; Parkinson Disease/physiopathology* ; Transcription Factor HES-1/metabolism* ; Mice ; Mice, Inbred C57BL ; Humans ; Signal Transduction

Objective:To construct a symptom network for type 2 diabetes mellitus (T2DM) patients, identify bridging symptoms and core symptoms, and explore influencing factors, providing references for precise and efficient symptom management.Methods:A convenience sampling method was used to select 340 T2DM patients hospitalized in the Endocrinology Department of Affiliated Hospital of North Sichuan Medical College from December 2023 to February 2024. A general information survey and the Chinese version of Diabetes Symptom Checklist-Revised were used to collect data. Multiple linear regression analysis was performed to explore the influencing factors of T2DM patients' lack of vitality. Network analysis was used to identify core symptoms and bridging symptoms among symptom clusters. A total of 340 questionnaires were distributed, and 336 valid questionnaires were returned, resulting in a valid response rate of 98.8% (336/340) .Results:The most common symptoms in T2DM patients included thirst and dry mouth, foamy urine, and overall fatigue. The most troublesome symptoms were overall fatigue, lack of vitality, and thirst and dry mouth. In the symptom network, lack of vitality had the highest intensity ( rs=7.980) and closeness centrality ( rc=0.014), followed by overall fatigue ( rs=7.940) and feeling down ( rs=7.200). Overall fatigue ( rbs=7.190, rbc=0.380) was identified as the strongest bridging symptom in the network. Univariate analysis showed that age, education level, diabetes duration, diabetes complications, and regular blood glucose monitoring were significant factors affecting lack of vitality in T2DM patients ( P<0.05). Multiple linear regression analysis indicated that education level, regular blood glucose monitoring, and diabetes complications were significant factors affecting lack of vitality ( P<0.05) . Conclusions:Lack of vitality is the core symptom in T2DM patients, and overall fatigue is the bridging symptom connecting different symptom clusters. The lack of vitality is influenced by factors such as education level, regular blood glucose monitoring, and diabetes complications. Healthcare providers should use symptom network analysis to timely identify core symptoms, bridging symptoms, and their influencing factors, and develop precise and efficient interventions to improve symptom management and reduce the symptom burden in T2DM patients.

Objective:To construct a symptom network for type 2 diabetes mellitus (T2DM) patients, identify bridging symptoms and core symptoms, and explore influencing factors, providing references for precise and efficient symptom management.Methods:A convenience sampling method was used to select 340 T2DM patients hospitalized in the Endocrinology Department of Affiliated Hospital of North Sichuan Medical College from December 2023 to February 2024. A general information survey and the Chinese version of Diabetes Symptom Checklist-Revised were used to collect data. Multiple linear regression analysis was performed to explore the influencing factors of T2DM patients' lack of vitality. Network analysis was used to identify core symptoms and bridging symptoms among symptom clusters. A total of 340 questionnaires were distributed, and 336 valid questionnaires were returned, resulting in a valid response rate of 98.8% (336/340) .Results:The most common symptoms in T2DM patients included thirst and dry mouth, foamy urine, and overall fatigue. The most troublesome symptoms were overall fatigue, lack of vitality, and thirst and dry mouth. In the symptom network, lack of vitality had the highest intensity ( rs=7.980) and closeness centrality ( rc=0.014), followed by overall fatigue ( rs=7.940) and feeling down ( rs=7.200). Overall fatigue ( rbs=7.190, rbc=0.380) was identified as the strongest bridging symptom in the network. Univariate analysis showed that age, education level, diabetes duration, diabetes complications, and regular blood glucose monitoring were significant factors affecting lack of vitality in T2DM patients ( P<0.05). Multiple linear regression analysis indicated that education level, regular blood glucose monitoring, and diabetes complications were significant factors affecting lack of vitality ( P<0.05) . Conclusions:Lack of vitality is the core symptom in T2DM patients, and overall fatigue is the bridging symptom connecting different symptom clusters. The lack of vitality is influenced by factors such as education level, regular blood glucose monitoring, and diabetes complications. Healthcare providers should use symptom network analysis to timely identify core symptoms, bridging symptoms, and their influencing factors, and develop precise and efficient interventions to improve symptom management and reduce the symptom burden in T2DM patients.

Objective:To explore the current situation of hypoglycemia fear of elderly patients with type 2 diabetes mellitus (T2DM) in the community, identify different types of hypoglycemia fear among elderly T2DM patients in the community by latent profile analysis, and analyze its influencing factors, so as to provide reference for formulating intervention measures.Methods:From February to April 2023, convenience sampling was used to select 300 elderly T2DM patients from three community health service centers in Shunqing District, Nanchong City, Sichuan Province as the research subject. The self-designed General Information Questionnaire, the Chinese Version Hypoglycemia Fear Survey-Ⅱ (CHFS-Ⅱ), and the Summary Diabetes Self Care Activities (SDSCA) were used to investigate the patients, and the latent profile of hypoglycemia fear was analyzed. Binary Logistic regression was used to analyze the influencing factors of different latent categories of hypoglycemic fear in elderly T2DM patients in the community.Results:A total of 300 questionnaires were distributed, and 290 valid questionnaires were collected, with an effective response rate of 96.7% (290/300). Among 290 elderly T2DM patients in the community, the hypoglycemia fear could be divided into two latent categories, including the "moderate worry-normal coping" group ( n=134) and the "high fear-cautious behavior" group ( n=156). The binary Logistic regression showed that marital status, whether there were complications of diabetes, treatment plan and self-management were the factors influencing the latent categories of elderly T2DM patients in the community, and the difference was statistically significant ( P<0.05) . Conclusions:There are classification characteristics of hypoglycemic fear levels in elderly T2DM patients in the community. Community medical and nursing staff should early identify patients in the "high fear-cautious behavior" group, regularly carry out targeted hypoglycemic health education and psychological intervention, reduce their hypoglycemic fear, and improve their quality of life.