AIM:To investigate the effect of Jianpi-Huayu decoction(JPHYD)combined with gemcitabine(GEM)on ferroptosis of pancreatic cancer PANC-1 cells and its mechanism.METHODS:PANC-1 cells were cultured in vitro,and CCK8 method was used to detect the cell viability after different concentrations of JPHYD and GEM,and ap-propriate concentrations were selected for follow-up experiments.EDU assay and clonogenesis assay were used to detect cell proliferation.The apoptosis rate was detected by flow cytometry.Intracellular reactive oxygen species(ROS)were de-tected by DCFH-DA fluorescent probe and lipid peroxidation was detected by BODIPY 581/591C11 staining.The contents of glutathione(GSH),ferrous ion(Fe2+)and malondialdehyde(MDA)in the cells were detected by the kit.The mRNA levels and protein expression levels of Nrf2,HO-1,SLC7A11,GPX4,TFR1 and ACSL4 were detected by RT-qPCR and Western blot.RESULTS:Compared with the control group,the cell viability of PANC-1 treated with JPHYD and GEM was significantly decreased in a concentration-dependent manner.And the combined use of the two can significantly im-prove the cytotoxic effect of GEM and have a synergistic effect;Compared with control group,JPHYD group,GEM group and JPHYD+GEM group can significantly reduce EDU positive efficiency,colony formation numbers and promote cell apoptosis,and the combined group has the most obvious effect.After adding JPHYD+GEM into the cells,the cells be-came rounded and the cell viability decreased.The addition of ferrostatin-1(Fer-1),an inhibitor of ferroptosis,had no significant effect on cell morphology and viability,and the co-treatment with JPHYD+GEM and Fer-1 could reverse the ef-fects of JPHYD+GEM on cell morphology and viability.Compared with control group and GEM group,JPHYD+GEM group can significantly increase the levels of intracellular reactive oxygen species(ROS)and lipid peroxidation,increase the levels of Fe2+and MDA,decrease the levels of GSH,further promote lipid peroxidation and induce ferroptosis.JPHYD+GEM also significantly down-regulated the mRNA and protein expressions of Nrf2,HO-1,SLC7A11 and GPX4,and up-regulated the mRNA and protein expressions of TFR1 and ACSL4.The addition of Fer-1 significantly reversed the activation of iron death in the combined treatment group and reversed its efficacy,and the difference was statistically signif-icant.CONCLUSION:Jianpi Huayu decoction and gemcitabine may induce ferroptosis of PANC-1 cells by inhibiting Nrf2/SLC7A11/GPX4 axis in vitro,thus playing a synergistic anticancer role.

Objective:To investigate the feasibility of deep learning based on computed tomography(CT)radiomics in improving diagnostic accuracy for pulmonary nodules.Methods:A total of 500 patients with pulmonary nodules who admitted to our hospital from January 2023 to January 2024 were selected as study subjects,and they were randomly divided into a training set(350 patients)and a test set(150 patients)as 7:3 ratio.All patients underwent CT examination,and pathological diagnosis was used as gold standard to record pulmonary nodules that were judged by clinical judgment.The radiomics features were screened from the CT images of the patients,and these features were used to construct multiple machine learning models.The predictive value of different models in diagnosing pulmonary nodules was analyzed through confusion matrices and receiver operating characteristic(ROC)curve.Results:A total of 1,594 radiomics features,including 1,195 texture features(74.97%)that was the largest ratio,334 first-order histograms(20.95%),and 65 second-order histograms(4.08%),were extracted in this study.After least absolute shrinkage and selection operator(LASSO)regression analysis and ten-fold cross-validation processing,a total of six radiomics features were screened out.The screened radiomics features were incorporated respectively into four assembled models with machine learning,including ResNet50,DenseNet121,Inception_V3 and VGG19.The constructed models were evaluated respectively using the training set and the test set.The results showed that the assembled model had the highest accuracies in both training set and the test set(96.57%and 95.33%),which area under curve(AUC)values were 0.934 and 0.923,and specificities were 81.64%and 80.52%,and sensitivities were 90.25%and 88.71%,respectively.The results of consistency test indicated that the assembled model had the best classification consistency(Kappa=0.856,P<0.001)in the constructed diagnostic model for pulmonary nodule,which was the best-performing model.Conclusion:The deep learning technique based on CT radiomics has a certain feasibility in improving the diagnostic accuracy for pulmonary nodules,and the machine learning model that is included in this study has favorable predictive value in diagnosing pulmonary nodules.In them,the assembled model that is constructed on the basis of ResNet50,DenseNet121,Inception_V3,and VGG19 has better classification ability.

OBJECTIVE: To explore the immunophenotypic characteristics of bone marrow granulocytes (G) and their clinical significance in patients with multiple myeloma (MM). METHODS: The granulocyte immunophenotypes of bone marrow in 70 MM patients (MM group) and 40 anemia patients (control group) were detected by flow cytometry, and its correlation with clinical characteristics was further analyzed. Univariate and multivariate regression analysis were used to screen factors that affected prognosis. RESULTS: The CD56⁺G%, CD13⁺G%, CD22⁺G% and CD117⁺G% in MM group were higher than those in the control group (all P <0.05). CD56⁺G% and CD117⁺G% in CR⁺VGPR group were significantly lower than those in PR+MR+PD group (both P <0.05). The CD10⁺G% in RISS Ⅲ stage and Ca²⁺ ≥2.65 mmol/L groups were increased (both P <0.05). The CD56⁺G% in elevated lactate dehydrogenase, β₂-microglobulin≥5.5 mg/L and hemoglobin <85 g/L groups were increased (all P <0.05), while the CD117⁺G% in high-risk cytogenetic positive group was decreased (P <0.05). The expression rate of CD molecules on granulocytes was divided into low (L) and high (H) groups according to the median value. The overall survival (OS) of the LCD56⁺G%, LCD13⁺G% and LCD22⁺G% groups was significantly prolonged (all P <0.05). CD13⁺G% and CD22⁺G% were independent risk factors for OS in MM patients (HR=0.443, 0.410, both P <0.05). CONCLUSION The CD56⁺G%, CD10⁺G% and CD117⁺G% are closely correlated with clinical features in MM patients, while CD13⁺G% and CD22⁺G% are closely correlated with prognosis. Detection of CD molecules expression on granulocytes may be used to evaluate prognosis and guide treatment.
Humans ; Multiple Myeloma/immunology* ; Granulocytes/immunology* ; Prognosis ; Immunophenotyping ; Male ; Bone Marrow ; Female ; Flow Cytometry ; Middle Aged ; Aged ; Clinical Relevance

AIM:To investigate the effect of Jianpi-Huayu decoction(JPHYD)combined with gemcitabine(GEM)on ferroptosis of pancreatic cancer PANC-1 cells and its mechanism.METHODS:PANC-1 cells were cultured in vitro,and CCK8 method was used to detect the cell viability after different concentrations of JPHYD and GEM,and ap-propriate concentrations were selected for follow-up experiments.EDU assay and clonogenesis assay were used to detect cell proliferation.The apoptosis rate was detected by flow cytometry.Intracellular reactive oxygen species(ROS)were de-tected by DCFH-DA fluorescent probe and lipid peroxidation was detected by BODIPY 581/591C11 staining.The contents of glutathione(GSH),ferrous ion(Fe2+)and malondialdehyde(MDA)in the cells were detected by the kit.The mRNA levels and protein expression levels of Nrf2,HO-1,SLC7A11,GPX4,TFR1 and ACSL4 were detected by RT-qPCR and Western blot.RESULTS:Compared with the control group,the cell viability of PANC-1 treated with JPHYD and GEM was significantly decreased in a concentration-dependent manner.And the combined use of the two can significantly im-prove the cytotoxic effect of GEM and have a synergistic effect;Compared with control group,JPHYD group,GEM group and JPHYD+GEM group can significantly reduce EDU positive efficiency,colony formation numbers and promote cell apoptosis,and the combined group has the most obvious effect.After adding JPHYD+GEM into the cells,the cells be-came rounded and the cell viability decreased.The addition of ferrostatin-1(Fer-1),an inhibitor of ferroptosis,had no significant effect on cell morphology and viability,and the co-treatment with JPHYD+GEM and Fer-1 could reverse the ef-fects of JPHYD+GEM on cell morphology and viability.Compared with control group and GEM group,JPHYD+GEM group can significantly increase the levels of intracellular reactive oxygen species(ROS)and lipid peroxidation,increase the levels of Fe2+and MDA,decrease the levels of GSH,further promote lipid peroxidation and induce ferroptosis.JPHYD+GEM also significantly down-regulated the mRNA and protein expressions of Nrf2,HO-1,SLC7A11 and GPX4,and up-regulated the mRNA and protein expressions of TFR1 and ACSL4.The addition of Fer-1 significantly reversed the activation of iron death in the combined treatment group and reversed its efficacy,and the difference was statistically signif-icant.CONCLUSION:Jianpi Huayu decoction and gemcitabine may induce ferroptosis of PANC-1 cells by inhibiting Nrf2/SLC7A11/GPX4 axis in vitro,thus playing a synergistic anticancer role.

Objective:To investigate the feasibility of deep learning based on computed tomography(CT)radiomics in improving diagnostic accuracy for pulmonary nodules.Methods:A total of 500 patients with pulmonary nodules who admitted to our hospital from January 2023 to January 2024 were selected as study subjects,and they were randomly divided into a training set(350 patients)and a test set(150 patients)as 7:3 ratio.All patients underwent CT examination,and pathological diagnosis was used as gold standard to record pulmonary nodules that were judged by clinical judgment.The radiomics features were screened from the CT images of the patients,and these features were used to construct multiple machine learning models.The predictive value of different models in diagnosing pulmonary nodules was analyzed through confusion matrices and receiver operating characteristic(ROC)curve.Results:A total of 1,594 radiomics features,including 1,195 texture features(74.97%)that was the largest ratio,334 first-order histograms(20.95%),and 65 second-order histograms(4.08%),were extracted in this study.After least absolute shrinkage and selection operator(LASSO)regression analysis and ten-fold cross-validation processing,a total of six radiomics features were screened out.The screened radiomics features were incorporated respectively into four assembled models with machine learning,including ResNet50,DenseNet121,Inception_V3 and VGG19.The constructed models were evaluated respectively using the training set and the test set.The results showed that the assembled model had the highest accuracies in both training set and the test set(96.57%and 95.33%),which area under curve(AUC)values were 0.934 and 0.923,and specificities were 81.64%and 80.52%,and sensitivities were 90.25%and 88.71%,respectively.The results of consistency test indicated that the assembled model had the best classification consistency(Kappa=0.856,P<0.001)in the constructed diagnostic model for pulmonary nodule,which was the best-performing model.Conclusion:The deep learning technique based on CT radiomics has a certain feasibility in improving the diagnostic accuracy for pulmonary nodules,and the machine learning model that is included in this study has favorable predictive value in diagnosing pulmonary nodules.In them,the assembled model that is constructed on the basis of ResNet50,DenseNet121,Inception_V3,and VGG19 has better classification ability.

The study focused on individuals with influenza-like symptoms (fever, cough, sore throat, runny nose, and other respiratory symptoms) in three kindergartens in Tongzhou District, Beijing City, in April 2023. Nasopharyngeal swab specimens were collected, and real-time fluorescent quantitative PCR was used to detect common respiratory pathogens in the collected specimens. Positive specimens were subjected to sequencing analysis of the highly variable region of human respiratory syncytial virus (HRSV) G protein, homology analysis and phylogenetic tree analysis. A total of 25 fever cases were collected from 3 kindergartens, aged 3-8 years old, with an age M ( Q1, Q3) of 4 (3.5, 5) years old. Ten confirmed cases of HRSV positive were screened and detected using the fluorescent quantitative PCR method, with a total detection rate of 40% (10/25). Typing identification and sequencing analysis confirmed that the main epidemic type was HRSV subtype B, which was highly homologous and closely related to previous epidemic strains in the region. Through pathogen investigation and analysis, it was preliminarily determined that this epidemic was dominated by HRSV subtype B.

Objective:To analyze the epidemic characteristics of reported tuberculosis incidence in Kashgar from 2015 to 2022, and use the seasonal autoregressive integrated moving average (SARIMA) model to predict the incidence, providing references for the local control of pulmonary tuberculosis.Methods:The reported incidence data of tuberculosis in the Kashgar area of Xinjiang from January 2015 to August 2023 were collected through the"Infectious Disease Monitoring System", a subsystem of the "Chinese Disease Prevention and Control Information System". The epidemic characteristics of reported incidence in this area from 2015 to 2022 were analyzed. Two SARIMA models of monthly reported incidence number and rate were established. The prediction performance of the two models was evaluated using the reported incidence data of tuberculosis from January 2023 to August 2023. The χ2 test was used to analyze population characteristics, and the Cochran-Armitage trend test was used to analyze annual incidence. Results:From 2015 to 2022, 133 972 cases of pulmonary tuberculosis were reported in Kashgar, with a yearly reported incidence rate of 383.64/100 000, showing a rising trend ( TCA=77.03, P<0.001) and then a declining trend ( TCA=176.16, P<0.001). The proportion of pathogenic positive pulmonary tuberculosis had increased yearly ( TCA=132.66, P<0.001). The reported onset time was concentrated from January to June each year, with a peak in April. Yengisar County, Zepu County and Yopurga County had the highest reported incidence rate in Kashgar. The sex ratio of men to women was 1.03∶1, and the reported incidence rate of men was higher than that of women ( χ2=27.04, P<0.001). The reported incidence rate of the group aged 60 years and older was the highest. The patient′s occupation was mainly farmers (84.99%). The average relative errors of the SARIMA ( 1, 1, 2) ( 0, 1, 1) 12 model and SARIMA ( 0, 1, 1)( 0, 1, 1) 12 model in predicting the reported monthly incidence number and rate were 11.67% and -9.81%, respectively. Both models had good prediction accuracy (MAPE=33.55%, MAPE=38.22%). Conclusion:The average reported incidence rate of pulmonary tuberculosis in the Kashgar area shows a rising trend first and then a declining trend. The patients are mainly men and farmers, and attention should be paid to the prevention and control of tuberculosis among the elderly in winter and spring. The SARIMA ( 1, 1, 2) ( 0, 1, 1) 12 model and SARIMA ( 0, 1, 1)( 0, 1, 1) 12 model can fit the trend of reported tuberculosis incidence in the Kashgar area well and have good predictive performance.

A review was undertaken of the operation process and development of transcutaneous electrical acupoint stimulation (TEAS) and related devices for TEAS, with the aim to offer a reference for developing an international standard for the basic safety and essential performance of the devices. The articles related to TEAS and instruction of devices for TEAS were searched using the EMBASE, MEDLINE, and Web of Science databases with the time period from inception to July 18, 2023. In the absence of a parameter description of the stimulators, a multimeter was used to measure the output voltage, resistance, and current. Thirty-two related devices for TEAS were obtained. The safety parameters of most devices were neither clearly defined, nor stand ardized, and in some cases were missing. There was a noticeable disparity in the upper safety limits of the output current among the devices. The sizes of the skin electrode pads as well as the lengths of the electrode connecting wires of most devices were not clearly indicated. Acupoints on different parts of the human body, including the upper limbs, head, auricle, chest, abdomen, trunk, and lower limbs, required different maximum tolerable current intensities and current densities. It is important to indicate comprehensive output/safety parameters and essential performance for devices for TEAS to meet the need of global distribution, achieve precise stimulation parameters at different acupoints across the human body, and allay any safety concern of national therapeutic device authorities, the regulators, manufacturers, and end users.

Objective:To explore the characteristics of the immunophenotypic expression of bone marrow monocytes (M ) and its clinical significance in patients with multiple myeloma (MM ). Methods:The monocyte immunophenotypes expression of 67 MM and 30 anemic patients (control group)were detected by flow cytometry.The immunophenotypes that exhibited statistical differences from the control group were screened out.Further univariate and multivariate regression was used analyze the risk factors affecting the prognosis. The effect of monocyte immunophenotype on the prognosis of MM was analyzed.The correlation of CD38+monocytes with clinical features was explored.Results:The percentages of CD138+monocytes (CD138+M％),CD27+monocytes (CD27+M％),and CD56+monocytes (CD56+M％)in the MM group were significantly higher than that in the control group(P<0.05),but the percentages of CD38+monocytes (CD38+M％)and HLA-DR+monocytes (HLA-DR+M％)were significantly lower than that in the control group (P<0.01 ).The median progression-free survival (PFS)was shorter in the low CD38+monocyte proportion (LCD38+M％)group compared to the high CD38+monocyte proportion (HCD38+M％) group.Additionally,the median overall survival (OS)was significantly shorter in the low CD138+monocyte proportion (LCD138+M％),low CD27+monocyte proportion (LCD27+M％),low CD38+monocyte proportion (LCD38+M％),and low HLA-DR+monocyte proportion (LHLA-DR+M％)groups.Cox regression analysis showed that the low CD38+M％ was an independent risk factor for OS.The LCD38+M％group had significantly higher proportions of involved/uninvolved free light chain ratios ≥100 and 1q21+compared to the HCD38+M％ group (P<0.05 ). Moreover,the proportion of CD38-myeloma cells was significantly higher in the LCD38+M％ group than that in the HCD38+M％ group (P<0.05).Conclusion:The expression of CD38+monocytes in bone marrow of MM patients is closely related to the prognosis and clinical characteristics.CD38+monocytes maybe used to predict prognosis and guide treatment decisions.

Objective:To investigate the pathogen spectrum and the epidemiological characteristics of hospitalized severe acute respiratory tract infection (SARI) cases in a sentinel hospital in Tongzhou District of Beijing from 2019 to 2022, and provide reference for scientific prevention and control of SARI.Methods:This study enrolled SARI patients in the Beijing Luhe Hospital from January 2019 to December 2022. Nasopharyngeal swabs or respiratory secretions of the patients were collected and analyzed by quantitative real-time PCR to detect the pathogens and their types. The epidemiological and clinical characteristics of the cases were analyzed.Results:In this study, 1 124 SARI cases were enrolled, of which 379 were positive for respiratory pathogens with a detection rate of 33.72%. Most of the SARI cases were positive for bacteria pathogens, and the detection rates of Mycoplasma pneumoniae, Streptococcus pneumoniae, and Stenotrophomonas maltophilia were high. Influenza A virus, parainfluenza virus, and respiratory syncytial virus were the main viral pathogens detected in the cases. There were significant differences in the number of cases and the detection rate of respiratory pathogens among different age groups (χ 2=555, P=0.000 1). The predominant pathogens in different years were different. Mycoplasma pneumoniae [27.27% (51/187)] and influenza A virus [17.65% (33/187), ] were the predominant pathogens in 2019; parainfluenza virus [16.67% (10/60)], Mycoplasma pneumoniae [11.67% (7/60)], and Haemophilus influenzae [11.67% (7/60)] were the predominant pathogens in 2020; Stenotrophomonas maltophilia [24.39% (20/82)] and respiratory syncytial virus [19.51% (16/82)] were the predominant pathogens in 2021; Stenotrophomonas maltophilia [20% (10/50)] and parainfluenza virus [12% (6/50)] were the predominant pathogens in 2022. Conclusions:Most of the SARI cases in Tongzhou district of Beijing from 2019 to 2022 are caused by bacteria. More attention should be paid to the prevalence of Stenotrophomonas maltophilia and Mycoplasma pneumoniae, as well as the prevalence of respiratory syncytial virus, parainfluenza virus, and influenza A virus. The predominant pathogens change every year from 2019 to 2022. Therefore, the prevention and control strategies should be made accordingly. This study provides basis data for the national respiratory multipathogen surveillance program.