Objective To study the correlation between traditional Chinese medicine(TCM)constitution and pathogenic factors in patients with ankylosing spondylitis(AS).Methods One hundred patients of AS and their family members who had medical consultation in the Fifth Hospital of Xi'an(i.e.,Shaanxi Hospital of Integrated Traditional Chinese and Western Medicine)in August 2019 and September 2020 were selected as the study subjects.The guidelines of Classification and Determination of Traditional Chinese Medicine Constitution issued by the China Association of Chinese Medicine were adopted to determine the traditional Chinese medicine(TCM)constitution types of the study subjects.The sociodemographic information,living habits,clinical symptoms,and TCM constitution types of the AS patients and their family members were collected by means of questionnaires and clinical investigations,and then the pathogenic factors of the patients with AS were investigated.The binomial Logistic regression model was used to analyze the correlation between TCM constitution types and pathogenic factors in patients with AS.Results(1)Among the 100 AS patients,the majority of them had the biased constitutions,and the biased constitutions with the occurrence frequency in descending order were yang deficiency constitution,qi deficiency constitution,and damp-heat constitution,which accounted for 33.00%,14.00%,and 18.00%,respectively.(2)The prevalence rates of AS in the first-,second-,and third-degree relatives of AS patients were 56.25%,40.00%and 25.00%,respectively.For the positive rates of human leukocyte antigen B27(HLA-B27)in AS patients and their family members,HLA-B27 in AS patients was all positive,while the positive rates of HLA-B27 in the first-,second-,and third-degree relatives of AS patients were 44.31%,30.67%and 15.63%,respectively.(3)The results of regression analysis showed that the disease duration of AS patients was significantly correlated with qi deficiency constitution,the grading of sacroiliac arthritis was correlated with qi stagnation constitution,and age was correlated with blood stasis constitution(P＜0.05 or P＜0.01).The results indicated that disease duration and age were the important factors affecting the constitution types of AS patients,and disease duration was closely related to qi deficiency while age was closely related to blood stasis.Conclusion AS is a highly hereditary autoimmune disease,and its onset is associated with HLA-B27.Yang deficiency is the basic constitution type of AS,and damp-heat constitution is the main constitution type in the progression of AS(especially in the active stage of the disease).The prolongation of the disease will exacerbate the illness condition of AS and then the manifestations of qi deficiency will be more obvious.

Objective To investigate the risk factors for re-fracture after percutaneous kyphoplasty (PKP) in elderly patients with osteoporotic thoracolumbar compression fractures and to construct a line graph prediction model. Methods One hundred and eighty-two elderly patients with osteoporotic thoracolumbar compression fractures treated with PKP from January 2016 to November 2019 were selected for the study‚ and the patients were continuously followed up for 3 years after surgery. Clinical data were collected from both groups; Receiver operating characteristic (ROC) curve analysis was performed on the measures; Logistic regression analysis was performed to determine the independent risk factors affecting postoperative re-fracture in PKP; the R language software 4. 0 “rms” package was used to construct a predictive model for the line graph‚ and the calibration and decision curves were used to internally validate the predictive model for the line graph and for clinical evaluation of predictive performance. Results The differences between the two groups were statistically significant (P<0. 05) in terms of bone mineral density (BMD)‚ number of injured vertebrae‚ single-segment cement injection‚ type of cement distribution‚ cement leakage‚ difference in vertebral body height before and after PKP‚ and change in posterior convexity angle. The area under the curve (AUC) for BMD‚ number of injured vertebrae‚ single-segment cement injection volume‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity change were 0. 772‚ 0. 732‚ 0. 722‚ 0. 801‚ and 0. 813‚ respectively‚ and the best cutoff values were -3. 1‚ 2‚ 3. 9 ml‚ 0. 4 mm‚ and 8. 7°‚ respectively. BMD‚ number of injured vertebrae‚ single-segment cement injection volume‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity change were independent risk factors for re-fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fractures. The calibration curve of the column line graph prediction model was close to the original curve and the ideal curve with a C-index of 0. 818 (95% CI: 0. 762-0. 883)‚ and the model fit was good; the threshold value of the column line graph prediction model was >0. 22‚ which could provide a net clinical benefit‚ and the net clinical benefit was higher than the independent predictors. Conclusion BMD‚ number of injured vertebrae‚ single-segment cement injection‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity angle change are independent risk factors affecting the recurrent fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fracture‚ and this study constructs a column line graph model to predict the recurrent fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fracture as a predictor for clinical. This study provides an important reference for clinical prevention and treatment‚ and has clinical application value.

Anterior diastema is a common esthetic defect in China.The general treatment for a patient with diastema-ta,including orthodontics and direct and indirect restorations,is a multidisciplinary clinical procedure covering the ortho-dontics,operative dentistry,general dentistry,and prosthodontics department.Given the diversity of departments and the complex etiology of this defect,decision-making regarding the closing methods and time selection is undefined and unin-tegrated,which makes the long-term stability of closure unpredictable.This article proposed an etiology-based decision tree with actual measurement of diastemata width for diastemata closure.The decisional steps include classifying the eti-ological factors based on patients'medical history and clinical manifestation to evaluate the stability of diastemata.After maintaining the stability of diastemata,contemporary and multidisciplinary treatment plans were selected in accordance with the measured width of diastemata and patients'cosmetic psychology,economics,and available time.These decision trees focus on the challenges of collaboration among dental departments,propose an objective and efficient ways for con-nections,and promote efficient and effective diastemata closure.

Background and purpose:Primary adrenal intravascular large B-cell lymphoma(IVLBCL)is rare and highly aggressive.Unfortunately,comprehensive and sufficient understanding of the disease is lacking.This study investigated the clinicopathological and molecular genetic characteristics of adrenal IVLBCL.Methods:Adrenal IVLBCL cases diagnosed from 2012 to 2023 were collected from Department of Pathology,Fudan University Shanghai Cancer Center.The clinical and histopathological features,immunophenotype,treatment and prognosis were analyzed.The molecular genetic characteristics were detected using next-generation sequencing(NGS).This study was approved by the Ethics Committee of Fudan University Shanghai Cancer Center(Ethics number:050432-4-2307E).Results:All of the 5 patients were male,with median age 52 years(ranged 50-82 years).Two cases had low-grade fever,1 case had abdominal pain,1 case was found by physical examination,and the information of the remaining one was unknown.Peripheral blood test showed elevated serum lactate dehydrogenase in 2 cases and adrenal dysfunction in 2 cases.On initial diagnosis,imaging tests displayed adrenal enlargement or masses with increased fluorodeoxyglucose(FDG)uptake.Bilateral adrenal glands were involved in 4 cases and only the right adrenal gland was involved in the other case.Morphologically,large atypical lymphocytes were confined to blood vessels,and fibrinous necrosis was observed in some cases.Immunohistochemical study revealed that CD20 was positive in all cases.Ki-67 proliferation index was high,all above 80%.80%(4/5)of the cases were of non-germinal-center B-cell-like(non-GCB)phenotype,100%(4/4)of the cases had MYC/BCL2 double expression.Endothelial cell markers staining indicated that most of the tumor cells were confined within the blood vessels in all cases.Follow-up data were available in 3 patients.One patient who underwent only surgical resection died 5 months after diagnosis,one achieved complete remission after surgery plus R-CHOP,and the other diagnosed by biopsy achieved a partial remission after R-CHOP.The 1-year overall survival rate was 66.7%,and overall survival was 5-87 months.NGS testing in 1 case showed missense mutations in MYD88 V217F,TP53,CDH1,ARID1B,MSH3,MLH3,PTPRK,CD22 and FLCN.Conclusion:Adrenal IVLBCL is rare and tends to occur in the middle-aged and elderly male.The majority of our patients were non-GCB phenotype,often accompanied by MYC/BCL2 double expression,and MYD88 non-L265P mutation was detected.Early diagnosis of adrenal IVLBCL is difficult due to its diverse clinical symptoms and lack of specificity.It is of great importance to accumulate more cases and further understand the clinicopathological and molecular genetic characteristics of this rare disease,which might not only help with early diagnosis,timely treatment and improvement of prognosis,but also provide a theoretical basis for further understanding the pathogenesis and development of the disease and exploring therapeutic targets.

Pharmaceutical cocrystals is an advanced technology to improve the physicochemical and biological properties of drugs. However, there are few studies on the in vivo metabolism of pharmaceutical cocrystals. In this study, the pharmacokinetics of wogonin cocrystal in normal rats was further studied on the basis of the previous preparation of wogonin-aloperine cocrystal. Firstly, an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was established for simultaneous determination of wogonin and its metabolite wogonoside in rat plasma, and to investigate the methodology. The method was applied to the pharmacokinetic study of wogonin-aloperine cocrystal (Wog-Alop) in rats. The results showed that wogonin and its metabolite wogonoside had a good linear relationship in the range of 1-800 ng·mL^-1, and the precision, accuracy, matrix effect and stability in this range met the requirements of biological analysis. Compared with direct administration of wogonin, the C_max of wogonin and its metabolite in rats increased to 7.44-fold and 9.15-fold, AUC_0-t increased to 1.67-fold and 3.72-fold, and oral bioavailability of wogonin increased to 187.66% after cocrystal administration. Wog-Alop cocrystal can significantly improve the C_max, AUC, and oral bioavailability of wogonin and its metabolite, which provides a new perspective for the clinical application of wogonin. This study was approved by the Experimental Animal Ethics Review Committee of Beijing University of Chinese Medicine (approval number: BUCM-2023032307-1148).

Objective To propose an algorithm to extract fetal ECG signals from mixed signals of maternal abdominal wall with high signal-to-noise ratio and clear waveforms by combining kernel principal component analysis(KPCA),fast independent component analysis(FastICA)and singular value decomposition(SVD).Methods Firstly,KPCA was used to downscale the maternal ECG signals,and then the improved negative entropy-based FastICA was applied to processing the downscaled data to obtain the independent components.Subsequently,sample entropy was introduced for signal channel selection,and the signal channel containing the most maternal information was selected.SVD was performed on the selected maternal channel to get an approximate estimate of the maternal ECG signals,which was then subtracted from the abdominal wall source signals to obtain a preliminary estimate of the fetal ECGs.Finally,the pure fetal ECG signals were successfully separated using a modified negentropy-based FastICA.The proposed algorithm was validated in the Abdominal and Direct Fetal Electrocardiogram Database(ADFECGDB)and the PhysioNet 2013 Challenge database.Results The proposed algorithm gained advantages in both subjective visualization and objective evaluation metrics,which had the sensitivity,positive predictive value and F1 value of fetal QRS compound wave respectively being 99.74％,98.85％and 99.30％for the ADFECGDB database,and 99.10％,97.87％and 98.48％for the PhysioNet 2013 Challenge database.Conclusion The fetal ECG signal extraction algorithm incorporating KPCA,FastICA and SVD effectively handles the additional noise while extracting fetal ECG signals,which provides strong support for the early diagnosis of fetal diseases.[Chinese Medical Equipment Journal,2024,45(7):1-7]

Objective To plan microwave antenna puncture direction effectively and realize personalized preoperative simulation by exploring microwave ablation(MWV)outcomes of lung cancer based on real anatomical model.Methods Firstly,a personalized MWA simulation model consisting of the lung tissue,tumor and vascular system was constructed based on the lung CT data of real patients.Secondly,the MWA effect was simulated by coupling 2 physical fields including an electromagnetic field and a biological heat transfer field,so as to determine the volume of the ablation thermocoagulation zone and the temperature distribution of the lung tissue.Finally,the effects of the vascularized network on the ablation results were quantitatively evaluated in terms of conductivity and blood perfusion,and the ablation results were analyzed with different distances between the large vessels and the antennae(5 and 10 mm from the antennae tips)and puncture angles(large vessels parallelling or intersecting with the antennae tips).Results The vascularized network reduced the volume of the thermocoagulation zone by 0.5％to 3.7％,and blood perfusion made the ablation temperature and the volume of the thermocoagulation zone decreased significantly.The cooling effect gradually diminished with the increase of the distance between the large vessels and the antenna.With the same treatment parameters,the thermocoagulation zone formed when the large vessels paralleled with the antenna was obviously larger than that when the vessles intersected with the antenna.Conclusion Personalized MWA simulation analysis based on real CT data contributes to clarifying the temperature distribution and damage estimation close to the actual situation,which provides guidance and reference for precise treatment of the lung tumor and determination of microwave antenna puncture direction.[Chinese Medical Equipment Journal,2024,45(9):27-34]

Near infrared spectroscopy(NIRS)has emerged as an indispensable analytical technology for quality monitoring in industrial and agricultural production.It is widely used in quantitative analysis in areas such as food,agriculture and medicine.To meet the requirements of industrial and agricultural production,it is particularly important to develop a NIRS quantitative analysis model that can predict the multicomponent of different samples.In this study,the multicomponent quantitative analysis model of NIRS based on convolution neural network(MulCoSpecNet)was proposed.MulCoSpecNet was composed of an encoding and decoding module,an expert module,a gate module,a multicomponent quantitative prediction module,and a hyperparameter optimizer.The spectral noise and random errors were mitigated,and the signal-to-noise ratio was enhanced through up-sampling and down-sampling in the encoding and decoding module.Diverse weightings were employed by the expert module and gate module to construct distinct sub-spectra.The model prediction accuracy and generalization ability were enhanced by the multicomponent quantitative prediction module,which employed convolutional and pooling operations.The hyperparameters in the hyperparameter space were synchronously optimized by the hyperparameter optimizer.By taking public NIRS datasets of grain and corn as examples,the prediction results of MulCoSpecNet were compared with partial least squares(PLS),extreme learning machine(ELM),support vector regression(SVM)and back propagation neural network(BP).The results showed that compared to PLS,the prediction accuracy of MulCoSpecNet to grain and corn were increased by 25.5%?45.2%and 10.0%?35.7%,respectively.Compared to ELM,the prediction accuracy of MulCoSpecNet were increased by 17.8%?38.6%and 18.2%?37.2%,respectively.Compared to SVM,the prediction accuracy of MulCoSpecNet were increased by 33.6%?47.0%and 31.3%?50.7%,respectively.Compared to BP,the prediction accuracy of MulCoSpecNet were increased by 2.0%?58.5%and 29.6%?48.6%,respectively.The issues of low prediction accuracy and poor generalization ability were effectively solved by the MulCoSpecNet,which was a NIRS multicomponent prediction model based on convolutional neural network.It provided a theoretical foundation for establishing non-destructive and high-precision NIRS multicomponent quantitative analysis model.

Objective To investigate the mechanism of Bushen Yixin Tablets in the treatment of diabetic nephropathy(DN).Methods The key targets of Bushen Yixin Tablets for the treatment of DN were predicted by network pharmacology.A high-glucose-processed MPC-5 cell model was constructed,enzyme-linked immunosorbent assay(ELISA),real-time quantitative polymerase chain reaction(RT-qPCR)and Western Blot were applied to verify the potential action targets and pathways of Bushen Yixin Tablets for the treatment of DN.Results Twenty-four active ingredients were obtained from Bushen Yixin Tablets.There were 131 targets involved in the treatment of DN by Bushen Yixin Tablets,and the results of pathway enrichment analysis showed that the key targets might mainly focus on inflammatory pathways,lipids and atherosclerosis.The further experimental validation showed that,compared with the high glucose group,the secretion level of matrix metalloproteinase 1(MMP-1)in the supernatant of MPC-5 cells in the medium-and high-dose groups of Bushen Yixin Tablets medicated serum were increased(P＜0.001),and the secretion levels of tissue inhibitor of metalloproteinase 1(TIMP-1)and transforming growth factor β1(TGF-β1)were decreased(P＜0.001).Compared with the high glucose group,the protein and mRNA expression levels of MMP1 and BCL-2 in the high-dose group of Bushen Yixin Tablets medicated serum were increased(P＜0.001),and the protein and mRNA expression levels of phosphatidylinositol 3-kinase(PI3K)and protein kinase B(AKT)were decreased(P＜0.001).Conclusion Bushen Yixin Tablets may play a protective role against DN by inhibiting the proliferation of glomerular mesangial cells and promoting the degradation of extracellular matrix through PI3K/AKT/BCL-2 pathway.

Objective To explore the prediction of hospital indoor microbial concentration in air based on real-time indoor air environment monitoring data and machine learning algorithms.Methods Four locations in a hospital were selected as monitoring sampling points from May 23 to June 5,2022.The"internet of things"sensor was used to monitor a variety of real-time air environment data.Air microbial concentration data collected at each point were matched,and the gradient boosting decision tree(GBDT)was used to predict real-time indoor microbial concentra-tion in air.Five other common machine learning models were selected for comparison,including random forest(RF),decision tree(DT),k-nearest neighbor(KNN),linear regression(LR)and artificial neural network(ANN).The validity of the model was verified by the mean absolute error(MAE),root mean square error(RMSE)and mean absolute percentage error(MAPE).Results The MAPE value of GBDT model in the outpa-tient elevator room(point A),bronchoscopy room(point B),CT waiting area(point C),and nurses'station in the supply room(point D)were 22.49％,36.28％,29.34％,and 26.43％,respectively.The mean performance of the GBDT model was higher than that of other machine learning models at three sampling points and slightly lower than that of the ANN model at only one sampling point.The mean MAPE value of GBDT model at four sampling points was 28.64％,that is,the predicted value deviated from the actual value by 28.64％,indicating that GBDT model has good prediction results and the predicted value was within the available range.Conclusion The GBDT machine learning model based on real-time indoor air environment monitoring data can improve the prediction accuracy of in-door air microbial concentration in hospitals.