ObjectiveTo develop a community-family management model for older adults with mild cognitive impairment (MCI) and to formulate detailed application specifications, and to fully leverage the initiative of communities and families under limited resource conditions, for achieving community-based early detection and early intervention for older adults with MCI. MethodsA systematic literature review was conducted to identify pertinent publications. Corpus-based research methodologies were employed to extract, refine, integrate and synthesize management elements, thereby establishing the specific content and service processes for each stage of the management model. Utilizing the 5W2H analytical framework, essential elements such as management stakeholders, target populations, content and methods for each stage were delineated. The model and its application guidelines were finalized through expert consultation and demonstration. ResultsAn expert evaluation of the management model yielded mean scores of 4.84, 4.32 and 4.84 for acceptability, feasibility and systematicity, respectively. By integrating the identified core elements with expert ratings and feedback, the final iteration of the community-family management model for older adults with MCI was formulated. This model comprised of five stages: screening and identification, comprehensive assessment, intervention planning, monitoring and referral pathways to ensure implementation, and enhanced support for communities, family members and caregivers. Additionally, it included 18 specific application guidelines. ConclusionThe proposed management model may theoretically help delay cognitive decline, improve cognitive function and potentially promote reversal from MCI to normal cognition. It may also enhance the awareness and coping capacity of older adults and their families, strengthen community healthcare professionals' ability to early identify and manage MCI.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

Objective:To analyze postictal electroencephalographic(EEG) characteristics of patients with status epilepticus (SE) based on the score of grand total electroencephalography (GTE), and explore the relationship between electroencephalographic characteristics of SE and clinical prognosis.Methods:A total of 110 SE patients were enrolled in the Department of Neurology, the Affiliated Hospital of Yangzhou University from September 1, 2021 to September 1, 2023. EEG and GTE scores were performed in all patients after seizures (0-2 days after the cessation of SE). After one year of discharge, the medication and seizure status of patients were followed up by phone or outpatient visits. The seizure outcomes were recorded according to the international league against epilepsy (ILAE) seizure outcome classification, with favorable outcomes defined as good prognosis group ( n=54) and unfavorable outcomes defined as poor prognosis group ( n=56). SPSS 27.0 software was used for statistical analysis. Binary Logistic regression analysis was employed to screen impact variables of prognosis. The receiver operating characteristic(ROC) curve was plotted to determine the optimal cut-off point for predicting prognosis in epilepsy. Results:There were statistically significant differences in the total GTE score(2(1, 4), 8(5, 10); Z=-6.837, P<0.001), diffuse slow activity(0(0, 1), 2(0, 2); Z=-6.495, P<0.001), reactivity of the rhythmic background activity(0(0, 0), 0(0, 1); Z=-2.705, P=0.007), paroxysmal activity(0(0, 0), 1.5(0, 3.0); Z=-4.420, P<0.001), focal disturbances(0(0, 0), 0(0, 0); Z=-2.130, P=0.033), and sharp wave activity(0(0, 2), 2(2, 3); Z=-5.714, P<0.001)between the good prognosis group and poor prognosis group. The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity and total GTE score (all P<0.05). The differences in EEG results between SE patients with clear and unknown causes were statistically significant in terms of paroxysmal activity and focal disturbances(both P<0.05). The results of binary Logistic regression analysis showed that independent factors associated with the prognosis of SE included medication adherence ( B=-0.496, OR=0.609, 95% CI=0.395-0.940, P=0.025), diffuse slow activity( B=1.580, OR=4.854, 95% CI=1.586-14.855, P=0.006), sharp wave activity( B=0.824, OR=2.280, 95% CI=1.210-4.297, P=0.011), and total GTE score ( B=0.561, OR=1.753, 95% CI=1.360-2.259, P<0.001). In evaluating the prognosis of SE, the GTE score had a certain sensitivity (74.6%) and specificity (85.1%), with a optimal cut-off point of 6. Conclusions:The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity. The appearance of diffuse slow activity and sharp wave activity in the electroencephalogram of SE patients indicates poor prognosis, and the total GTE score≥6 may be a strong predictor of poor prognosis. However, good medication adherence is a protective factor for epilepsy recurrence.

Objective:To investigate the association between cognitive impairment and manifestation of interictal electroencephalogram (EEG) in epilepsy patients, and the early assessment significance of the Grand Total Electroencephalography (GTE) score.Methods:A totall of 100 patients with primary epilepsy admitted to the Department of Neurology of the Affiliated Hospital of Yangzhou University were continuously collected from January 2019 to January 2024, and they were classified according to the latest version of the epilepsy classification by the International League Against Epilepsy in 2017. General information of all research subjects was recorded, including age, gender, educational level, etc. The disease details of epilepsy patients were recorded, including seizure duration, severity, seizure precursors, post seizure status, and use of anti-seizure medications (ASM). The survey scales and questionnaires used included the interictal GTE, Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale, Hamilton Depression Scale, National Hospital Seizure Severity Scale (NHS3), Status Epilepticus Severity Score (STESS). All research subjects were classified into normal cognitive (NC) group, mild cognitive impairment (MCI) group, and dementia group according to MoCA score. Comparisons among multiple groups and pairwise comparisons were conducted. The correlation between 2 variables was analyzed using Spearman rank correlation analysis, and multiple linear regression analysis was employed to screen variables that have an impact on cognitive impairment. The receiver operating characteristic curve was plotted to determine the optimal cut-off point for predicting cognitive impairment in epilepsy.Results:According to the MoCA score, there were 32 (32%) patients in the NC group, 49 (49%) patients in the MCI group, and 19 (19%) patients in the dementia group. There were statistically significant differences in age [(26.31±10.01) years, (43.96±16.19) years, (57.68±16.83) years,respectively; F=29.440, P<0.001], education ( χ2=28.894, P<0.001), ASM ( χ2=11.258, P<0.017), STESS score [2.00(1.75, 2.25), 2.00(2.00, 3.00), 3.50(2.75, 4.25),respectively; H=12.646, P=0.002], STESS score>2 ( χ2=10.075, P=0.006), frequency of rhythmic background activity ( H=17.429, P<0.001), diffuse slow activity ( H=42.033, P<0.001), reactivity of the rhythmic background activity ( H=15.206, P<0.001), paroxysmal activity ( H=25.279, P<0.001), sharp wave activity ( H=15.492, P<0.001) and total GTE score [1 (1, 3), 6 (2, 8), 8 (7, 11),respectively; H=47.871, P<0.001] among the 3 groups. A significant negative correlation was observed between cognitive level (MoCA scores) and total GTE score ( ρ=-0.766, P<0.001), frequency of rhythmic background activity ( ρ=-0.520, P<0.001), diffuse slow activity ( ρ=-0.734, P<0.001), reactivity of the rhythmic background activity ( ρ=-0.438, P<0.001), paroxysmal activity ( ρ=-0.566, P<0.001), and sharp wave activity ( ρ=-0.407, P<0.001). The results of multiple linear regression analysis indicated that total GTE score ( t=-5.566, P<0.001), diffuse slow activity ( t=-2.548, P=0.014), reactivity of the rhythmic background activity ( t=-3.891, P<0.001), paroxysmal activity ( t=-3.139, P=0.003), age ( t=-5.493, P<0.001), education ( t=3.379, P=0.001), and STESS ( t=-2.183, P=0.033) were independent risk factors for cognitive impairment. In evaluating the cognitive impairment of epilepsy patients, the GTE score had a certain sensitivity (75.0%) and specificity (93.8%), with an optimal critical point value of 5. Conclusions:The interictal EEG of patients with poorer cognitive function is mainly characterized by an increase in slow waves and a decrease in overall background. The increase in slow waves, poor background responsiveness, paroxysmal activity and a high total GTE score may be important factors in predicting the outcome of cognitive impairment in epilepsy.

Objective:To analyze postictal electroencephalographic(EEG) characteristics of patients with status epilepticus (SE) based on the score of grand total electroencephalography (GTE), and explore the relationship between electroencephalographic characteristics of SE and clinical prognosis.Methods:A total of 110 SE patients were enrolled in the Department of Neurology, the Affiliated Hospital of Yangzhou University from September 1, 2021 to September 1, 2023. EEG and GTE scores were performed in all patients after seizures (0-2 days after the cessation of SE). After one year of discharge, the medication and seizure status of patients were followed up by phone or outpatient visits. The seizure outcomes were recorded according to the international league against epilepsy (ILAE) seizure outcome classification, with favorable outcomes defined as good prognosis group ( n=54) and unfavorable outcomes defined as poor prognosis group ( n=56). SPSS 27.0 software was used for statistical analysis. Binary Logistic regression analysis was employed to screen impact variables of prognosis. The receiver operating characteristic(ROC) curve was plotted to determine the optimal cut-off point for predicting prognosis in epilepsy. Results:There were statistically significant differences in the total GTE score(2(1, 4), 8(5, 10); Z=-6.837, P<0.001), diffuse slow activity(0(0, 1), 2(0, 2); Z=-6.495, P<0.001), reactivity of the rhythmic background activity(0(0, 0), 0(0, 1); Z=-2.705, P=0.007), paroxysmal activity(0(0, 0), 1.5(0, 3.0); Z=-4.420, P<0.001), focal disturbances(0(0, 0), 0(0, 0); Z=-2.130, P=0.033), and sharp wave activity(0(0, 2), 2(2, 3); Z=-5.714, P<0.001)between the good prognosis group and poor prognosis group. The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity and total GTE score (all P<0.05). The differences in EEG results between SE patients with clear and unknown causes were statistically significant in terms of paroxysmal activity and focal disturbances(both P<0.05). The results of binary Logistic regression analysis showed that independent factors associated with the prognosis of SE included medication adherence ( B=-0.496, OR=0.609, 95% CI=0.395-0.940, P=0.025), diffuse slow activity( B=1.580, OR=4.854, 95% CI=1.586-14.855, P=0.006), sharp wave activity( B=0.824, OR=2.280, 95% CI=1.210-4.297, P=0.011), and total GTE score ( B=0.561, OR=1.753, 95% CI=1.360-2.259, P<0.001). In evaluating the prognosis of SE, the GTE score had a certain sensitivity (74.6%) and specificity (85.1%), with a optimal cut-off point of 6. Conclusions:The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity. The appearance of diffuse slow activity and sharp wave activity in the electroencephalogram of SE patients indicates poor prognosis, and the total GTE score≥6 may be a strong predictor of poor prognosis. However, good medication adherence is a protective factor for epilepsy recurrence.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

Objective:To investigate the association between cognitive impairment and manifestation of interictal electroencephalogram (EEG) in epilepsy patients, and the early assessment significance of the Grand Total Electroencephalography (GTE) score.Methods:A totall of 100 patients with primary epilepsy admitted to the Department of Neurology of the Affiliated Hospital of Yangzhou University were continuously collected from January 2019 to January 2024, and they were classified according to the latest version of the epilepsy classification by the International League Against Epilepsy in 2017. General information of all research subjects was recorded, including age, gender, educational level, etc. The disease details of epilepsy patients were recorded, including seizure duration, severity, seizure precursors, post seizure status, and use of anti-seizure medications (ASM). The survey scales and questionnaires used included the interictal GTE, Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale, Hamilton Depression Scale, National Hospital Seizure Severity Scale (NHS3), Status Epilepticus Severity Score (STESS). All research subjects were classified into normal cognitive (NC) group, mild cognitive impairment (MCI) group, and dementia group according to MoCA score. Comparisons among multiple groups and pairwise comparisons were conducted. The correlation between 2 variables was analyzed using Spearman rank correlation analysis, and multiple linear regression analysis was employed to screen variables that have an impact on cognitive impairment. The receiver operating characteristic curve was plotted to determine the optimal cut-off point for predicting cognitive impairment in epilepsy.Results:According to the MoCA score, there were 32 (32%) patients in the NC group, 49 (49%) patients in the MCI group, and 19 (19%) patients in the dementia group. There were statistically significant differences in age [(26.31±10.01) years, (43.96±16.19) years, (57.68±16.83) years,respectively; F=29.440, P<0.001], education ( χ2=28.894, P<0.001), ASM ( χ2=11.258, P<0.017), STESS score [2.00(1.75, 2.25), 2.00(2.00, 3.00), 3.50(2.75, 4.25),respectively; H=12.646, P=0.002], STESS score>2 ( χ2=10.075, P=0.006), frequency of rhythmic background activity ( H=17.429, P<0.001), diffuse slow activity ( H=42.033, P<0.001), reactivity of the rhythmic background activity ( H=15.206, P<0.001), paroxysmal activity ( H=25.279, P<0.001), sharp wave activity ( H=15.492, P<0.001) and total GTE score [1 (1, 3), 6 (2, 8), 8 (7, 11),respectively; H=47.871, P<0.001] among the 3 groups. A significant negative correlation was observed between cognitive level (MoCA scores) and total GTE score ( ρ=-0.766, P<0.001), frequency of rhythmic background activity ( ρ=-0.520, P<0.001), diffuse slow activity ( ρ=-0.734, P<0.001), reactivity of the rhythmic background activity ( ρ=-0.438, P<0.001), paroxysmal activity ( ρ=-0.566, P<0.001), and sharp wave activity ( ρ=-0.407, P<0.001). The results of multiple linear regression analysis indicated that total GTE score ( t=-5.566, P<0.001), diffuse slow activity ( t=-2.548, P=0.014), reactivity of the rhythmic background activity ( t=-3.891, P<0.001), paroxysmal activity ( t=-3.139, P=0.003), age ( t=-5.493, P<0.001), education ( t=3.379, P=0.001), and STESS ( t=-2.183, P=0.033) were independent risk factors for cognitive impairment. In evaluating the cognitive impairment of epilepsy patients, the GTE score had a certain sensitivity (75.0%) and specificity (93.8%), with an optimal critical point value of 5. Conclusions:The interictal EEG of patients with poorer cognitive function is mainly characterized by an increase in slow waves and a decrease in overall background. The increase in slow waves, poor background responsiveness, paroxysmal activity and a high total GTE score may be important factors in predicting the outcome of cognitive impairment in epilepsy.

Objective:To investigate the clinical and pathological characteristics of primary mucinous gland lesions of the fallopian tubes.Methods:The clinical data, pathomorphological characteristics and immunophenotype of 14 cases of primary mucinous gland lesions of the fallopian tube diagnosed at Obstetrics and Gynecology Hospital of Fudan University from 2015 to 2023 were analyzed retrospectively. In addition, a comprehensive review of relevant literature was conducted.Results:The age of 14 patients ranged from 53 to 83 years, with an average of 65 years. Among them, 13 cases exhibited unilateral involvement while one case showed bilateral presentation. Nine cases were mucinous metaplasia of the fallopian tube, four cases were invasive mucinous adenocarcinoma and one case was mucinous carcinoma in situ. Morphologically, mucinous metaplasia of the fallopian tube was focal, with or without inflammation. The cells of mucinous adenocarcinoma or mucinous carcinoma in situ exhibited characteristics indicative of gastrointestinal differentiation. Immunohistochemical analysis revealed diffuse positive expression of CK7, and negative expression of SATB2. CDX2 demonstrated positive staining in two cases. One case exhibited diffuse and strongly positive mutant expression of p53, whereas the remaining cases displayed wild-type expression. MUC6 showed diffuse or focally positive staining in mucinous gland lesions characterized by gastric differentiation. Some cases of mucinous adenocarcinoma of fallopian tube were subject to AB-PAS staining, resulting in red to purple cytoplasmic staining.Conclusions:Primary mucinous lesions of the fallopian tube are exceedingly uncommon. All cases of mucinous adenocarcinoma of fallopian tubes in this study exhibit the morphology and immunohistochemical characteristics of gastrointestinal differentiation. Mucinous metaplasia of the fallopian tube is a benign lesion of incidental finding, which is closely related to inflammation or gastric differentiation. Mucinous lesions of cervix, ovary and digestive tract are excluded in all patients, confirming the independent existence of mucinous lesions within fallopian tubes.

Chinese materia medica and its compound formulas have the characteristics of multi-component,multi-target,and multi pathway effects,and have unique advantages in preventing and treating complex diseases.Network pharmacology explains disease patterns and drug mechanisms from the perspective of complex biological networks,and explores the pharmacological substance basis and target of Chinese medicine.This article summarized the application of network pharmacology from the aspects of biological basis of TCM syndrome,the substance basis and pharmacological mechanism of TCM,compatibility theory of TCM compound formulas,etc.,with the purpose to provide a reference for the research and application of network pharmacology in TCM.

We analysed the similarities between theory of The Inner Canon of Yellow Emperor （《黄帝内经》） and modern sleep medicine on sleep and wakefulness， and initially constructed the "eye-brain" sleep regulation system. The similarities between the sleep theories in The Inner Canon of Yellow Emperor and modern sleep medicine research are described from three perspectives： the anatomical basis of sleep physiology， the pathogenesis of sleep disorder pathology， and the mechanism of sleep disorder treatment. It is found that the regulation of sleep and wakefulness in both medicine theories is based on the "eye" and "brain" as the main control centres， and there exists a "eye-brain" pathway to regulate sleep and wakefulness in the human body. Based on this， the "eye-brain" sleep regulation theory is constructed， in order to find an effective way to solve the pathogenesis and treatment strategy of sleep disorders.