Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Purpose To investigate the clinicopathologic,immunophenotypic features,genetic alterations and prognosis of melanotic Xp11 neoplasms/melanotic TFE3-rearrangement neo-plasms.Methods Five cases were selected from the Depart-ment of Pathology,Union Hospital,Huazhong University of Sci-ence and Technology from November 2018 to July 2023.The clinicopathologic,immunohistochemical,FISH assays,next-generation sequencing(NGS)and follow-up details were collect-ed.Results There were 1 male and 4 females,with their ages ranging from 16 to 59 years(mean 28.2 years).The maximum diameters of the masses were 3-6 cm(average 4.7 cm).The tumors located in right kidneys(3 cases),tubal interstitium(1 case)and pelvis(1 case).Microscopically,most tumors shared similar morphology such as nested,acinar structures sep-arated by a delicate vascular network.Epithelioid tumor cells presented with clear to granular eosinophilic cytoplasm.Lym-phocytic infiltration was seen in the background;melanin depo-sition was noted in the cases;neoplastic necrosis was detected in 4 cases.Mitotic activity was low with 5 cases showing＜3/10 HPF.Intravascular tumor thrombus was detected in 2 cases,no lymphovascular and nerve invasions were detected in other 3 ca-ses.Immunohistochemically,all 5 cases expressed TFE3 dif-fusely,and expressed HMB45,Melan A to varying degrees,CK(AE1/AE3),CK7,EMA,PAX8,TFEB,S-100,SOX10,SMA,desmin were all non-reactive in the 5 cases.The Ki67-la-beling index was＜20％.TFE3 separation signal in 4 cases were detected by FISH,1 case was interpreted as negative due to atypical signal which was confirmed by next-generation se-quencing(NGS)assay as RBM10-TFE3.Clinical follow-up was available for five patients for 2-60 months,in which four pa-tients were alive with no evidence of disease after initial resec-tion,and one patient with thoracic spine metastasis was currently in stable condition.Conclusion Melanotic Xp1 1 neoplasms/melanotic TFE3-rearrangement neoplasms has unique morpholog-ic,immunophenotypic and genetic characteristics.It might be reclassified into a distinctive malignant mesenchymal tumor enti-ty.

The modernization and development of traditional Chinese medicine has led to higher standards for the quality of traditional Chinese medicine products. The extraction process is a crucial component of traditional Chinese medicine production, and it directly impacts the final quality of the product. However, the currently relied upon methods for quality assurance of the extraction process, such as simple wet chemical analysis, have several limitations, including time consumption and labor intensity, and do not offer precise control of the extraction process. As a result, there is significant value in incorporating near-infrared spectroscopy (NIRS) in the production process of traditional Chinese medicine to improve the quality control of the final products. In this study, we focused on the extraction process of Xiao'er Xiaoji Zhike oral liquid (XXZOL), using near-infrared spectra collected by both a Fourier transform near-infrared spectrometer and a portable near-infrared spectrometer. We used the concentration of synephrine, a quality control index component specified by the pharmacopoeia, to achieve rapid and accurate detection in the extraction process. Moreover, we developed a model transfer method to facilitate the transfer of models between the two types of near-infrared spectrometers (analytical grade and portable), thus resolving the low resolution, poor performance, and insufficient prediction accuracy issues of portable instruments. Our findings enable the rapid screening and quality analysis of XXZOL onsite, which is significant for quality monitoring during the traditional Chinese medicine production process.

BACKGROUND: The prognostic benefit of complete revascularization in elderly patients (aged over 75 years) with multi-vessel disease and acute coronary syndrome (ACS) is currently unclear. This study aimed to determine the long-term prognostic impact of complete revascularization in this population. METHODS: We conducted this study using data obtained from the BleeMACS (Bleeding complications in a Multicenter registry of patients discharged after an Acute Coronary Syndrome) registry, which was carried out from 2003 to 2014. The objective was to categorize older patients diagnosed with ACS into two groups: those who underwent complete revascularization and those who did not. Propensity score matching and the Kaplan-Meier analysis were employed to examine differences in one-year clinical outcomes. The primary endpoint was major adverse cardiovascular event (MACE), which encompassed a combination of all-cause mortality and myocardial infarction. RESULTS: Out of 1263 patients evaluated, 445 patients (35.2%) received complete revascularization. Patients who underwent complete revascularization had a higher prevalence of hypertension and prior percutaneous coronary intervention compared to those who did not. During the one-year follow-up period, complete revascularization was associated with a significantly decreased risk of MACE [13.7% vs. 20.5%, hazard ratio (HR) = 0.63, 95% CI: 0.45-0.88, P = 0.007] and a lower risk of myocardial infarction (5.9% vs. 9.9%, HR = 0.55, 95% CI: 0.33-0.92, P = 0.02). However, it was not linked to a lower risk of all-cause death (9.5% vs. 13.5%, HR = 0.68, 95% CI: 0.45-1.02, P = 0.06). Similar results were observed in the subgroup analysis. CONCLUSIONS Long-term clinical improvements were observed in ACS patients aged over 75 years with multi-vessel disease who achieved complete revascularization. Therefore, adhering to guidelines for complete revascularization should be recommended for elderly patients.

Humans ; RNA-Binding Protein EWS/genetics* ; Histiocytoma, Malignant Fibrous/pathology* ; Oncogene Proteins, Fusion/genetics* ; Biomarkers, Tumor ; Cyclic AMP Response Element-Binding Protein/genetics*

Fingerprints of 18 batches of substance benchmark of Shentong Zhuyu Decoction(SZD) were established by UPLC under the following conditions: Waters Sun Fire C_(18) column(3.0 mm×150 mm, 3.5 μm), column temperature of 35 ℃, gradient elution with mobile phase of acetonitrile(A)-0.1% phosphoric acid aqueous solution(B) at the flow rate of 0.4 mL·min~(-1), and detection by wavelength switching. A total of 16 common peaks were identified. The similarities among the fingerprints were calculated by Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(2012 Edition) and the result showed they were in the range of 0.911-0.988. Based on the 16 common peaks, cluster analysis(CA), principal component analysis(PCA), and partial least square discriminant analysis(PLS-DA) all categorized the 18 batches of samples into two groups(S1, S2, S5-S8, S14, and S17 in one group, and S1, S2, S5-S8, S14, and S17 in another), and 11 most influential components were screened. Five known components with great difference among samples(hydroxysafflor yellow A, ferulic acid, benzoic acid, ecdysone, and ammonium glycyrrhizinate) were determined. The combination of multi-component content determination and fingerprints can reflect the overall cha-racteristics of the primary standards of SZD, which is simple, feasible, reproducible, and stable. This study can serve as a reference for the quality control of the primary standards of SZD.
Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal/standards* ; Quality Control

Objective To explore the correlation between 4 tag single nucleotide polymorphisms （Tag SNP） sites （rs7721799, rs32897, rs7718461, rs10062367） of corticotropin releasing hormone binding protein （CRHBP） and schizophrenia and aggressive behavior in the Yunnan Han population. Methods Case-control correlation analysis was used to establish a complex amplification system. Improved multiplex ligase detection reaction （iMLDR） technology was used to detect the genotypes of 4 SNP sites of CRHBP gene of 163 Han schizophrenic patients （including 81 patients with aggressive behavior, 82 patients without aggressive behavior） and 345 healthy Han individuals, which were analyzed statistically by SPSS 19.0, Haploview 4.2 and PHASE 2.1 software. Results There was no correlation between the 3 SNP sites of CRHBP gene and the onset of schizophrenia except for the rs7718461 site （P>0.05）. The relative risk of aggressive behavior of patients carrying GG or GA genotype at rs7718461 site were 4.903 times higher than those carrying AA genotype （P<0.05）. Conclusion The CRHBP gene may not be associated with the occurrence of schizophrenia in Yunnan Han population, but AA genotype of rs7718461 may reduce the risk of aggressive behavior in schizophrenia patients.
Asian People/genetics* ; Carrier Proteins/genetics* ; China ; Gene Frequency ; Genetic Predisposition to Disease ; Genotype ; Humans ; Polymorphism, Single Nucleotide ; Schizophrenia/genetics*

Objective: To study on the physical and chemical properties of dichroa alkali hydrochloride and to establish a method for the determination of entrapment efficiency of dichroa alkali hydrochloride liposomes. Method: HPLC was used to determine the content of dichroa alkali hydrochloride with mobile phase of acetonitrile-water-triethylamine-glacial acetic acid(9:91:0.35:0.75) and detection wavelength at 265 nm.The oil-water partition coefficient of this compound in different pH range was measured by shake flask method.The stability of the dichroa alkali hydrochloride in phosphate buffer solution with different pH after sterilization at 125℃ for 30 min was investigated.Ammonium sulfate gradient method was used to prepare dichroa alkali hydrochloride liposomes.The microcolumn was prepared by dextran gel and cation exchange resin,respectively.Then the free drug and liposome were separated by centrifugation,the drug content was measured,and the encapsulation efficiency was calculated.The t-test was performed using SPSS 20.0 software,the differences between these two methods were compared. Result: In the pH 6-9,the oil-water partition coefficient of dichroa alkali hydrochloride increased with increasing of pH,which was between 0.016 and 1.44;the recovery rate of dichroa alkali hydrochloride after sterilization was 37.16%-57.91%.Between the dextran gel microcolumn centrifugation and the cation exchange resin microcolumn centrifugation,there was no significant difference in the entrapment efficiency of the liposomes. Conclusion: Dichroa alkali hydrochloride is suitable for preparation of liposomes.However,its stability is not ideal,so the experimental temperature should be strictly controlled in the preparation process.Dextran gel microcolumn centrifugation and cation exchange resin microcolumn centrifugation can be used to determine the entrapment efficiency of dichroa alkali hydrochloride liposomes,and the cation exchange resin microcolumn centrifugation is suggested after comparison.

OBJECTIVETo explore the therapeutic effect of Yishen Qufeng Shengshi Recipe (, YQSR) in patients with glomerular proteinuria METHODS: A total of 145 patients with glomerular proteinuria were selected and randomly assigned to the treatment group (108 cases) and the control group (37 cases) according to a random number table in a ratio of 3:1. All patients received conventional and symptomatic treatment. In addition, patients in the treatment and control groups were given YQSR (200 mL, twice per day, orally) and losartan (50 mg/d orally), respectively for 6 months. The 24-h urine protein quantity, blood urea nitrogen, and serum creatinine in the two groups were measured at multiple time points before and after treatment.

RESULTSAt the end of the study, 5 cases were lost to follow-up in the treatment group and 1 in the control group. Finally, the statistical data included 103 cases in the treatment group and 36 cases in the control group. The total effectiveness after 2, 4, and 6 months was 81.6% (84/103), 87.4% (90/103), and 92.2% (95/103), respectively, in the treatment group and 47.2% (17/36), 55.6% (20/36), and 61.1% (22/36), respectively, in the control group, with significant difference between the two groups (P<0.01 at all observation points). In the treatment group, the curative effect after 6 months was better than that after 2 months (P<0.05). The 24-h urine protein quantity was significantly lower in the treatment group at 3, 4, 5, and 6 months than that in the control group (P<0.05 or P<0.01, respectively) CONCLUSION: YQSR could significantly reduce the amount of glomerular proteinuria in the early stage.