Objective To compare the accuracy of18F-fluorodeoxyglucose(18F-FDG)PET in locating the epileptogenic focus in patients with temporal lobe epilepsy using the single-patient research method based on statistical parametric mapping(SPM)at dif-ferent confidence levels,and to compare it with the asymmetry index(AI)analysis method.Methods A retrospective analysis was conducted on the clinical and imaging data of 86 patients with drug-resistant temporal lobe epilepsy and 37 healthy controls.The pri-mary epileptogenic focus were located by 18F-FDG PET,and two-sample t-test and intracranial asymmetry analysis were performed on individual patients based on SPM.The accuracy of 18F-FDG PET in locating the epileptogenic focus was compared at different confidence levels P＜0.05,P＜0.05[familywise error rate(FWE)corrected],P＜0.01,P＜0.001,respectively.The diagnostic accuracy of the SPM method at the optimal confidence level P value was compared with the AI analysis method,and the data were analyzed using the x2 test.Results The diagnostic accuracy of the two-sample t-test method were 69.77％,79.07％,67.44％ and 63.95％ at confidence levels of P＜0.05,P＜0.05(FWE corrected),P＜0.01 and P＜0.001,respectively;the diagnostic accuracy of the intracranial asymmetry analysis method were 94.19％,81.39％,79.07％,and 75.58％,respectively.There was a statistically significant differ-ence in diagnostic accuracy between the intracranial asymmetry analysis method(P＜0.05)and the two-sample t-test method P＜0.05(FWE corrected)(x2=8.482,P＜0.05);there was also a statistically significant difference in AI analysis method between the two methods(x2=4.793,P＜0.05).Conclusion The intracranial asymmetry analysis method(P＜0.05)based on SPM has a higher accuracy in locating the primary epileptogenic focus in unilateral drug-resistant temporal lobe epilepsy than those in the two-sample t-test method P＜0.05(FWE corrected)and AI analysis method.

Objective To observe hierarchical differences in brain functional networks in unilateral mesial temporal lobe epilepsy(mTLE)patients with different outcomes after surgery.Methods A total of 69 unilateral mTLE patients who underwent resection of epileptogenic lesion on the affected side were retrospectively enrolled.Based on Engel classification 1 year after surgery,the patients were divided into seizure free(SF)group and non-seizure free(NSF)group.Functional connectivity gradient analysis was employed to extract principal gradient explaining the highest variance on preoperative resting-state functional MRI(rs-fMRI),then the whole-brain gradient characteristics and principal gradient values within specific functional networks were compared between groups.Results Principal gradient connected default mode network(DMN)with sensorimotor network(SMN)along a continuous axis.Compared to SF group,NSF group showed a contracted gradient range at both ends(DMN and SMN)of the functional network and weakened hierarchical differentiation,and principal gradient value of DMN was higher,while that of SMN was lower than those in SF group(both P＜0.05).Conclusion Hierarchical differences in brain functional networks in unilateral mTLE patients with different outcomes after surgery mainly present as enhanced DMN and weakened SMN in NSF ones,and the latter two might serve as important neuroimaging markers for evaluating postoperative seizure recurrence.

Objective To observe the value of machine learning(ML)models based on brain functional network features combining clinical indicators for predicting postoperative outcomes of patients with drug-resistant mesial temporal lobe epilepsy(DR-mTLE).Methods Totally 84 patients with unilateral DR-mTLE who underwent surgery were retrospectively enrolled and classified into seizure free(SF)group(n=55)and non-seizure free(NSF)group(n=29)according to one-year postoperative follow-up.Clinical data were analyzed to screen independent predictors of postoperative outcomes.Based on brain preoperative resting-state functional MRI,brain functional networks were constructed using graph theory analysis,and 587 features were extracted.Five-fold cross validation was used to divide the data into training set and test set,then the optimal brain functional network features related to postoperative outcomes of DR-mTLE patients were selected.Combining with clinically relevant independent predictors,ML models were constructed using classifiers including Gaussian process(GP),logistic regression(LR),support vector machine(SVM)and quadratic discriminant analysis(QDA),respectively,and the prediction efficacy,calibration and clinical value of each ML model were evaluated.Results Both course of disease and lesion location were clinically relevant independent predictors of postoperative outcome of DR-mTLE patients(OR=0.928,5.710,P=0.010,0.016).Four optimal brain function network features were selected,including betweenness centrality of the third zone of cerebellar vermis,degree centrality of right globus pallidus,nodal efficiency of temporal left inferior temporal gyrus and nodal clustering coefficient of left inferior parietal lobule.The average area under the curve(AUC)of GP,LR,SVM and QDA models in test set was 0.868,0.864,0.875 and 0.870,respectively.Calibration curves and decision curve analysis indicated that each ML model had good calibration and high clinical net benefit.Conclusion ML models based on brain functional network features combining with clinical indicators could be used to effectively predict postoperative outcomes in DR-mTLE patients.

Objective To observe hierarchical differences in brain functional networks in unilateral mesial temporal lobe epilepsy(mTLE)patients with different outcomes after surgery.Methods A total of 69 unilateral mTLE patients who underwent resection of epileptogenic lesion on the affected side were retrospectively enrolled.Based on Engel classification 1 year after surgery,the patients were divided into seizure free(SF)group and non-seizure free(NSF)group.Functional connectivity gradient analysis was employed to extract principal gradient explaining the highest variance on preoperative resting-state functional MRI(rs-fMRI),then the whole-brain gradient characteristics and principal gradient values within specific functional networks were compared between groups.Results Principal gradient connected default mode network(DMN)with sensorimotor network(SMN)along a continuous axis.Compared to SF group,NSF group showed a contracted gradient range at both ends(DMN and SMN)of the functional network and weakened hierarchical differentiation,and principal gradient value of DMN was higher,while that of SMN was lower than those in SF group(both P＜0.05).Conclusion Hierarchical differences in brain functional networks in unilateral mTLE patients with different outcomes after surgery mainly present as enhanced DMN and weakened SMN in NSF ones,and the latter two might serve as important neuroimaging markers for evaluating postoperative seizure recurrence.

Objective To observe the value of machine learning(ML)models based on brain functional network features combining clinical indicators for predicting postoperative outcomes of patients with drug-resistant mesial temporal lobe epilepsy(DR-mTLE).Methods Totally 84 patients with unilateral DR-mTLE who underwent surgery were retrospectively enrolled and classified into seizure free(SF)group(n=55)and non-seizure free(NSF)group(n=29)according to one-year postoperative follow-up.Clinical data were analyzed to screen independent predictors of postoperative outcomes.Based on brain preoperative resting-state functional MRI,brain functional networks were constructed using graph theory analysis,and 587 features were extracted.Five-fold cross validation was used to divide the data into training set and test set,then the optimal brain functional network features related to postoperative outcomes of DR-mTLE patients were selected.Combining with clinically relevant independent predictors,ML models were constructed using classifiers including Gaussian process(GP),logistic regression(LR),support vector machine(SVM)and quadratic discriminant analysis(QDA),respectively,and the prediction efficacy,calibration and clinical value of each ML model were evaluated.Results Both course of disease and lesion location were clinically relevant independent predictors of postoperative outcome of DR-mTLE patients(OR=0.928,5.710,P=0.010,0.016).Four optimal brain function network features were selected,including betweenness centrality of the third zone of cerebellar vermis,degree centrality of right globus pallidus,nodal efficiency of temporal left inferior temporal gyrus and nodal clustering coefficient of left inferior parietal lobule.The average area under the curve(AUC)of GP,LR,SVM and QDA models in test set was 0.868,0.864,0.875 and 0.870,respectively.Calibration curves and decision curve analysis indicated that each ML model had good calibration and high clinical net benefit.Conclusion ML models based on brain functional network features combining with clinical indicators could be used to effectively predict postoperative outcomes in DR-mTLE patients.

Objective To compare the accuracy of18F-fluorodeoxyglucose(18F-FDG)PET in locating the epileptogenic focus in patients with temporal lobe epilepsy using the single-patient research method based on statistical parametric mapping(SPM)at dif-ferent confidence levels,and to compare it with the asymmetry index(AI)analysis method.Methods A retrospective analysis was conducted on the clinical and imaging data of 86 patients with drug-resistant temporal lobe epilepsy and 37 healthy controls.The pri-mary epileptogenic focus were located by 18F-FDG PET,and two-sample t-test and intracranial asymmetry analysis were performed on individual patients based on SPM.The accuracy of 18F-FDG PET in locating the epileptogenic focus was compared at different confidence levels P＜0.05,P＜0.05[familywise error rate(FWE)corrected],P＜0.01,P＜0.001,respectively.The diagnostic accuracy of the SPM method at the optimal confidence level P value was compared with the AI analysis method,and the data were analyzed using the x2 test.Results The diagnostic accuracy of the two-sample t-test method were 69.77％,79.07％,67.44％ and 63.95％ at confidence levels of P＜0.05,P＜0.05(FWE corrected),P＜0.01 and P＜0.001,respectively;the diagnostic accuracy of the intracranial asymmetry analysis method were 94.19％,81.39％,79.07％,and 75.58％,respectively.There was a statistically significant differ-ence in diagnostic accuracy between the intracranial asymmetry analysis method(P＜0.05)and the two-sample t-test method P＜0.05(FWE corrected)(x2=8.482,P＜0.05);there was also a statistically significant difference in AI analysis method between the two methods(x2=4.793,P＜0.05).Conclusion The intracranial asymmetry analysis method(P＜0.05)based on SPM has a higher accuracy in locating the primary epileptogenic focus in unilateral drug-resistant temporal lobe epilepsy than those in the two-sample t-test method P＜0.05(FWE corrected)and AI analysis method.

There is a bidirectional relationship between intestinal flora and bile acids,and the imbalance of intestinal flora-bile acid axis metabolism is closely related to hypertension.Based on classical TCM literature and clinical practice,this article found that"earth deficiency"is the important pathological basis of hypertension,"wood depression"is the initiating factor of hypertension,and"earth deficiency and wood depression"is the key pathogenesis of hypertension.Combined with the research results of modern medicine and molecular biology,it is considered that the imbalance of intestinal flora and abnormal bile acid metabolism are closely related to the"earth deficiency"and"wood depression"of TCM respectively,and the imbalance of intestinal flora-bile acid axis coincides with the"earth deficiency and wood depression"of TCM in the process of hypertension.It is of great theoretical and practical significance to explore the biological connotation of hypertension"earth deficiency and wood depression"from the perspective of intestinal flora-bile acid axis for guiding TCM to prevent and treat hypertension.

ObjectiveTo observe the effect of Zhengan Xifengtang on blood pressure and fecal microflora of spontaneously hypertensive rats （SHRs）. MethodA total of 75 male SHRs aged nine weeks were randomly divided into SHR group， Benazepril group （1.00 mg·kg^-1·d^-1）， high-dose Zhengan Xifengtang group （34.5 g·kg^-1·d^-1）， medium-dose Zhengan Xifengtang group （17.25 g·kg^-1·d^-1）， and low-dose Zhengan Xifengtang group （8.625 g·kg^-1·d^-1）. A total of 15 male Wistar-Kyoto （WKY） rats aged nine weeks were selected as the normal group. The normal group and SHR group were administrated with an equal volume of distilled water for eight weeks. During the administration， the blood pressure of the rats was measured regularly. After the intervention， fresh feces were collected with a sterile frozen storage tube， and 16S amplicon information was collected and analyzed. Plasma， hippocampus， and ileum of rats were collected for ultra-high performance liquid chromatography-tandem mass spectrometry（UPLC-MS/MS） detection. ResultZhengan Xifengtang decreased the systolic blood pressure and diastolic blood pressure of SHRs. Compared with the SHR group， Zhengan Xifengtang decreased the diversity of fecal microflora of SHRs. At the phylum level， Zhengan Xifengtang increased the relative abundance of SHR Verrucomicrobia and Actinobacteria and decreased the relative abundance of Synergistetes， Tenericutes， and Candidatus Saccharibacteria. Compared with the SHR group， Zhengan Xifengtang increased the relative abundance of Blautia wexlerae， Fusicatenibacter saccharivorans， and Akkermansia muciniphila and decreased the relative abundance of Clostridium lavalense， Intestinimonas butyriciproducens， Acetatifactor muris， Alloprevotella rava， and Oscillibacter valericigenes. Spearman correlation analysis showed that the systolic blood pressure of rats was negatively correlated with the relative abundance of Ethanoligenens， Aerococcus， Butyrivibrio， Olsenella， Bifidobacterium， Clostridium XIVb， Allobaculum， and Fusicatenibacter and positively correlated with the relative abundance of Alloprevotella. Zhengan Xifengtang increased the contents of plasma， hippocampal 5-hydroxy tryptamine（5-HT）， and 5-hydroxyindole acetic acid（5-HIAA） in SHRs and decreased the contents of 5-HT and 5-HIAA in the ileum， and the content of 5-HT in the hippocampus was negatively correlated with that in the ileum. ConclusionZhengan Xifengtang can reduce the blood pressure of SHRs， which may be related to reducing the diversity of SHR microflora， regulating the structure of the microflora， increasing the relative abundance of 5-HT and short-chain fatty acids bacteria， and lowering the relative abundance of pathogenic bacteria related to intestinal inflammation.

Objective To investigate the clinical efficacy of endoscopic assisted minimally invasive trans foraminal lumbar interbody fusion(MIS-TLIF)and traditional open TLIF in the treatment of senile degenerative spondylolisthesis.Methods From January 2020 to March 2021,100 elderly patients with degenerative spondylolisthesis were selected and divided into MIS-TLIF group and TLIF group according to the surgical method,with 50 cases in each group.The preoperative and postoperative VAS,Japanese Orthopedic Association score(JO A)and Oswestry disability index(ODI),and the rate of interbody fusion and the incidence of complications were compared and analyzed between the two groups.Results In MIS-TLIF group,the operative time,intraoperative blood loss,incision length,postoperative drainage volume and hospital stay were(167.5±54.2)minutes,(173.8±47.1)ml,(3.5±0.7)cm,(69.6±16.3)ml,and(8.3±2.7)days,respectively.In the TLIF group,it was(136.3±38.9)minutes,(281.0±50.3)ml,(10.0±2.1)cm,(148.4±28.2)ml,and(11.2±3.1)days,respectively.The difference between the two groups was statistically significant(P＜0.05).The VAS,JO A and ODI scores of MIS-TLIF group were(2.17±0.62)points,(21.72±3.14)points and(13.22 ±2.43)points,respectively.The results in TLIF group were(3.24±1.06)points,(17.06±2.85)points and(16.83±2.87)points,respectively,and there was statistical significance between the two groups(P＜0.05).There was no significant difference in the rate of interbody fusion between the two groups at 12 months after operation(P＞0.05).The incidence of postoperative complications in MIS-TLIF group(8.00％)was significantly lower than that in TLIF group(24.00％,P＜0.05).Conclusion MIS-TLIF assisted by endoscope has the advantages of less trauma,faster recovery and less postoperative complications,and the short-term curative effect is more satisfactory than TLIF.

Objective:To evaluate the clinical application of three dimensional artificial intelligence(3D-AI) localization technology in chest CT scan.Methods:A total of 100 patients who underwent chest CT for COVID-19 screening in Nanjing University Medical School Affiliated Drum Tower Hospital were collected from September 2020 to October 2020 were analyzed retrospectively. The patients were divided into manual positioning group ( n=50) and 3D-AI automatic positioning group ( n=50) with block randomization method. All patients were scanned with the same CT scanning protocol. The off-center distance, CT dose index (CTDI), dose length product (DLP) and CT examination time were measured and recorded. Quantitative image evaluation of mediastinal window images and qualitative image evaluation of chest window images were assessed by two radiologists. The off-center distance, CTDI, DLP, CT examination time and objective indexes of image quality of two groups were compared by independent sample t test. The quantitative image quality scores were compared with χ 2 test. Results:Compared with manual positioning group, the overall off-center distance of 3D-AI automatic positioning group was reduced by 42.86% [(15.4±9.7) vs. (8.8±7.2)mm, t=3.65, P<0.01], CTDI was reduced by 10.67%[(7.5±2.5) vs. (6.7±2.6)mGy, t=0.59, P=0.04], DLP was reduced by 13.33%[(270±95) vs. (234±86)mGy·cm, t=1.98, P=0.02], the average examination time was reduced by 29.91% [(214±26) vs. (150±14)s, t=15.79, P<0.01]. There were no significant differences in the background noise, signal to noise ratio of descending aorta and erecting spinal muscle, and subjective score between two groups ( P>0.05). Conclusion:The 3D-AI automatic positioning technology can greatly improve the accuracy of patient positioning and reduce the radiation dose for chest CT imaging, and improve work efficiency with qualified chest CT image quality.