Background::B-cell maturation antigen (BCMA)-directed chimeric antigen receptor T (CAR-T) therapy yield remarkable responses in patients with relapsed/refractory multiple myeloma (R/RMM). Circulating tumor DNA (ctDNA) reportedly exhibits distinct advantages in addressing the challenges posed by tumor heterogeneity in the distribution and genetic variations in R/RMM.Methods::Herein, the ctDNA of 108 peripheral blood plasma samples from patients with R/RMM at the First Affiliated Hospital, School of Medicine, Zhejiang University was thoroughly investigated before administration of anti-BCMA CAR-T therapy to establish its predictive potential. Flow cytometry is used primarily to detect subgroups of T cells or CAR-T cells.Results::In this study, several tumor and T cell effector-mediated factors were considered to be related to treatment failure by an integrat analysis, including higher percentages of multiple myeloma (MM) cells in the bone marrow ( P = 0.0125), lower percentages of CAR-T cells in the peripheral blood at peak ( P = 0.0375), and higher percentages of CD8 + T cells ( P = 0.0340). Furthermore, there is a substantial correlation between high ctDNA level (>143 ng/mL) and shorter progression-free survival (PFS) ( P = 0.007). Multivariate Cox regression analysis showed that high levels of ctDNA (>143 ng/mL), MM-driven high-risk mutations (including IGLL5 [ P = 0.004], IRF4 [ P = 0.024], and CREBBP [ P = 0.041]), number of multisite mutations, and resistance-related mutation ( ERBB4, P = 0.040) were independent risk factors for PFS. Conclusion::Finally, a ctDNA-based risk model was built based on the above independent risk factors, which serves as an adjunct non-invasive measure of substantial tumor burden and a prognostic genetic feature that can assist in predicting the response to anti-BCMA CAR-T therapy.

OBJECTIVE The non-volatile and volatile chemical components in Yin-Qiao-Qing-Re Tablets were analyzed sepa-rately using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS)and Gas Chromatography Mass Spectrometry(GC-MS).METHODS The non-volatile components were analyzed using a Waters ACQUITY UPLC BEH C18 column(2.1 mm×100 mm,1.7 μm),with a mobile phase consisting of 0.1％formic acid aqueous solution(A)and acetonitrile(B)for gradient elution,a flow rate of 0.35 mL·min-1,an injection volume of 5 μL,and a column temperature of 30 ℃;the volatile components were analyzed using an Agilent SH-I-5MS column(5％Phenyl Methyl Silox,30 m×250 μm,0.25 μm);the procedure was temperature-programmed,with an injection volume of 1 μL,a split ratio of 10∶1,a flow rate of 1.0 mL·min-1,and an inlet temperature of 200 ℃.RESULTS A total of 134 non-volatile chemical components and 23 volatile components were analyzed and identified from Yin-Qiao-Qing-Re Tablets,among which 49 compounds were confirmed through comparison with reference stand-ards.The non-volatile components mainly include 27 flavonoids,21 organic acids,15 lignans,14 iridoids,12 phenylethanoid glyco-sides,11 saponins,10 alkaloids,5 terpenes,4 amino acids,3 phenylpropanoids,3 nucleosides,3 xanthones,3 phenolic glycosides,2 chromones and 1 carbohydrate.The volatile components mainly include 11 monoterpenes,5 alcohols and phenols,3 alkenes,2 ke-tones,1 ester,and 1 hydrocarbon.CONCLUSION This study rapidly identifies the chemical components of Yin-Qiao-Qing-Re Tablets,laying a preliminary foundation for research on the pharmacodynamic substances of Yin-Qiao-Qing-Re Tablets and the im-provement of quality control standards.

Objective To detect the content of rheumatoid factor(RF)after RF-CIC dissociation using serum circulating immune complexes(CIC)dissociation technology and evaluate its diagnostic and clinical value in rheumatic arthritis(RA).Methods 55 RA patients diagnosed and treated in the 903rd Hospital of the People's Liberation Army from January 2024 to December 2024 were selected as the RA disease group,and 20 healthy individuals were selected as the control group.In addition,57 non RA pa-tients with symptoms resembling RA[patients with systemic lupus erythematosus(SLE),gout,ankylosing spondylitis(AS),osteo-arthritis,etc)]as the non RA disease group.Using CIC dissociation technology,RF content after RF-CIC dissociation was detect-ed in the serum of all three groups of study subjects,and C-reactive protein(CRP)and RF levels in all subjects were detected using a biochemical analyzer.Analyzed and compared the differences in the positive rate and levels of RF-CIC among three groups object of study.In addition,analyze and compare the correlation between RF-CIC and inflammatory index CRP.Results The positive rates of RF-CIC in the serum of RA disease group,non RA disease group,and control group were 87.27%(48/55),10.53%(6/57)and 0.0%(0/20),respectively,and the differences between the three groups was statistically significant(χ2=84.520,P<0.05).Further subgroup analysis showed that the RF-CIC positivity rate in the RF negative subgroup of RA disease patients[61.11%(11/18)]higher than that in the non RA disease group[1.92%(1/52)]and the control group[0%(0/20)],and the differ-ences were statistically significant(χ2=44.493,21.671,all P<0.05).The RF-CIC positivity rate was higher in RF positive pa-tients than in RF negative patients in the RA disease group(100%vs 61.11%),and the difference was statistically significant(χ2=16.487,P<0.05).The RF-CIC content in the serum of RF positive patients in the RA disease group was higher than that of RF negative patients[16.35(10.53,26.49)vs 3.57(2.53,3.89)],and the difference was statistically significant(Z=-4.243,P<0.05).Correlation analysis showed that the levels of CRP and RF in the serum of RA patients were positively correlated with the levels of RF-CIC(r=0.490,0.970,all P<0.05).Conclusion RF-CIC demonstrates high positivity even in RF-negative RA patients,and their levels correlate with CRP.RF-CIC shows potential as a serological indicator for early diagnosis and disease activity assess-ment in RA.

OBJECTIVE To establish a extraction process of Changyan Heji Ⅱ(CYHJ-Ⅱ)based on UPLC-Q-TOF-MS/MS technology combined with response surface analysis,and to optimize the extraction process.METHODS The chemical components in CYHJ-Ⅱ were qualitatively analyzed by UPLC-Q-TOF-MS/MS technology,and the chemical components with good linear relation-ship in mass spectrometry response were selected as process investigation indicators;the extraction process parameters(water addition amount,extraction time and soaking time)were investigated by Box-Behnken design;the comprehensive score was obtained by princi-pal component analysis(PCA),and the optimal process was determined by the comprehensive score combined with response surface a-nalysis.RESULTS Through qualitative analysis,110 components were inferred and identified from CYHJ-Ⅱ,including 2 organic acids,82 flavonoids,13 terpenoids,and 13 alkaloids.Based on the results of qualitative analysis,48 index components with good lin-ear relationships were derived by UPLC-Q-TOF-MS/MS combined with Masshunter mass spectrometry data analysis software.PCA was performed and the comprehensive score was calculated.Response surface analysis was performed with the comprehensive score as an indicator.The optimal extraction process obtained by combining the response surface prediction results and actual production was:soaking for 45 min,8 times the amount of solvent,2 extractions,each time for 120 min.CONCLUSION This study provides a new idea for the investigation of the extraction process of traditional Chinese medicine compound prescriptions and expands a new method for the development of traditional Chinese medicine compound prescriptions.

Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

Objective To detect the content of rheumatoid factor(RF)after RF-CIC dissociation using serum circulating immune complexes(CIC)dissociation technology and evaluate its diagnostic and clinical value in rheumatic arthritis(RA).Methods 55 RA patients diagnosed and treated in the 903rd Hospital of the People's Liberation Army from January 2024 to December 2024 were selected as the RA disease group,and 20 healthy individuals were selected as the control group.In addition,57 non RA pa-tients with symptoms resembling RA[patients with systemic lupus erythematosus(SLE),gout,ankylosing spondylitis(AS),osteo-arthritis,etc)]as the non RA disease group.Using CIC dissociation technology,RF content after RF-CIC dissociation was detect-ed in the serum of all three groups of study subjects,and C-reactive protein(CRP)and RF levels in all subjects were detected using a biochemical analyzer.Analyzed and compared the differences in the positive rate and levels of RF-CIC among three groups object of study.In addition,analyze and compare the correlation between RF-CIC and inflammatory index CRP.Results The positive rates of RF-CIC in the serum of RA disease group,non RA disease group,and control group were 87.27%(48/55),10.53%(6/57)and 0.0%(0/20),respectively,and the differences between the three groups was statistically significant(χ2=84.520,P<0.05).Further subgroup analysis showed that the RF-CIC positivity rate in the RF negative subgroup of RA disease patients[61.11%(11/18)]higher than that in the non RA disease group[1.92%(1/52)]and the control group[0%(0/20)],and the differ-ences were statistically significant(χ2=44.493,21.671,all P<0.05).The RF-CIC positivity rate was higher in RF positive pa-tients than in RF negative patients in the RA disease group(100%vs 61.11%),and the difference was statistically significant(χ2=16.487,P<0.05).The RF-CIC content in the serum of RF positive patients in the RA disease group was higher than that of RF negative patients[16.35(10.53,26.49)vs 3.57(2.53,3.89)],and the difference was statistically significant(Z=-4.243,P<0.05).Correlation analysis showed that the levels of CRP and RF in the serum of RA patients were positively correlated with the levels of RF-CIC(r=0.490,0.970,all P<0.05).Conclusion RF-CIC demonstrates high positivity even in RF-negative RA patients,and their levels correlate with CRP.RF-CIC shows potential as a serological indicator for early diagnosis and disease activity assess-ment in RA.

OBJECTIVE To establish a extraction process of Changyan Heji Ⅱ(CYHJ-Ⅱ)based on UPLC-Q-TOF-MS/MS technology combined with response surface analysis,and to optimize the extraction process.METHODS The chemical components in CYHJ-Ⅱ were qualitatively analyzed by UPLC-Q-TOF-MS/MS technology,and the chemical components with good linear relation-ship in mass spectrometry response were selected as process investigation indicators;the extraction process parameters(water addition amount,extraction time and soaking time)were investigated by Box-Behnken design;the comprehensive score was obtained by princi-pal component analysis(PCA),and the optimal process was determined by the comprehensive score combined with response surface a-nalysis.RESULTS Through qualitative analysis,110 components were inferred and identified from CYHJ-Ⅱ,including 2 organic acids,82 flavonoids,13 terpenoids,and 13 alkaloids.Based on the results of qualitative analysis,48 index components with good lin-ear relationships were derived by UPLC-Q-TOF-MS/MS combined with Masshunter mass spectrometry data analysis software.PCA was performed and the comprehensive score was calculated.Response surface analysis was performed with the comprehensive score as an indicator.The optimal extraction process obtained by combining the response surface prediction results and actual production was:soaking for 45 min,8 times the amount of solvent,2 extractions,each time for 120 min.CONCLUSION This study provides a new idea for the investigation of the extraction process of traditional Chinese medicine compound prescriptions and expands a new method for the development of traditional Chinese medicine compound prescriptions.

Objective:To investigate the prospective association between lifestyle and the risk for all-cause mortality in middle-aged and elderly residents in China.Methods:The data from China Health and Retirement Longitudinal Study were used. Baseline information about the lifestyle were collected through questionnaire survey and physical measurements, and the mortality data were obtained through surveys conducted at 2-3 year intervals. A total of 5 436 study participants were included. A comprehensive lifestyle including smoking, alcohol consumption, sleep, BMI and physical activity was constructed, and a multivariate-adjusted Cox proportional hazards regression model was used to estimate the association between lifestyle and the risk for all-cause mortality.Results:During the follow-up of average 8.2 years, 695 deaths were recorded. The comprehensive lifestyle score was linearly associated with the risk for all-cause mortality. Compared with the study participants with comprehensive lifestyle score of 0-1, those with score of 2-5 all had lower risk for all-cause mortality, with HRs of 0.78 (95% CI: 0.62-0.98), 0.56 (95% CI: 0.44-0.72), 0.36 (95% CI:0.27-0.48), and 0.33 (95% CI: 0.21-0.52), respectively. The results of Cox proportional hazards regression model analysis of single lifestyle showed that compared with those with unhealthy lifestyles, the HRs of all-cause mortality for study participants who never smoked, had moderate alcohol consumption, had appropriate night sleep, maintained healthy body weight and kept active physical activity were 0.70 (95% CI: 0.57-0.84), 0.76 (95% CI: 0.64-0.90), 0.79 (95% CI: 0.67-0.94), 0.73 (95% CI: 0.62-0.87), and 0.68 (95% CI: 0.58-0.80), respectively. Conclusions:Keeping healthy lifestyles can significantly reduce the risk for all-cause mortality in middle-aged and elderly residents China. The higher the healthy lifestyle level, the lower the risk for all-cause mortality.

OBJECTIVE The non-volatile and volatile chemical components in Yin-Qiao-Qing-Re Tablets were analyzed sepa-rately using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS)and Gas Chromatography Mass Spectrometry(GC-MS).METHODS The non-volatile components were analyzed using a Waters ACQUITY UPLC BEH C18 column(2.1 mm×100 mm,1.7 μm),with a mobile phase consisting of 0.1％formic acid aqueous solution(A)and acetonitrile(B)for gradient elution,a flow rate of 0.35 mL·min-1,an injection volume of 5 μL,and a column temperature of 30 ℃;the volatile components were analyzed using an Agilent SH-I-5MS column(5％Phenyl Methyl Silox,30 m×250 μm,0.25 μm);the procedure was temperature-programmed,with an injection volume of 1 μL,a split ratio of 10∶1,a flow rate of 1.0 mL·min-1,and an inlet temperature of 200 ℃.RESULTS A total of 134 non-volatile chemical components and 23 volatile components were analyzed and identified from Yin-Qiao-Qing-Re Tablets,among which 49 compounds were confirmed through comparison with reference stand-ards.The non-volatile components mainly include 27 flavonoids,21 organic acids,15 lignans,14 iridoids,12 phenylethanoid glyco-sides,11 saponins,10 alkaloids,5 terpenes,4 amino acids,3 phenylpropanoids,3 nucleosides,3 xanthones,3 phenolic glycosides,2 chromones and 1 carbohydrate.The volatile components mainly include 11 monoterpenes,5 alcohols and phenols,3 alkenes,2 ke-tones,1 ester,and 1 hydrocarbon.CONCLUSION This study rapidly identifies the chemical components of Yin-Qiao-Qing-Re Tablets,laying a preliminary foundation for research on the pharmacodynamic substances of Yin-Qiao-Qing-Re Tablets and the im-provement of quality control standards.

Background/Aims: Reflux symptoms frequently present in patients diagnosed with functional dyspepsia (FD). This investigation sought to elucidate the contribution of gastroesophageal reflux in the overlap relationship. Methods: Consecutive patients presenting with reflux symptoms and/or FD symptoms were prospectively included. Comprehensive assessments, including symptoms evaluation, endoscopy, esophageal functional examinations (high-resolution manometry and reflux monitoring), and proton pump inhibitor (PPI) treatment efficacy evaluation, were conducted in these patients. Results: The study enrolled 315 patients, 43.2% of which had concurrent FD symptoms and overlapping reflux symptoms. Notably, a mere 28.7% of patients in the overlap symptoms group had objective gastroesophageal reflux disease evidences (the grade of esophagitis≥ B or the acid exposure time ≥ 4.2%). Functional heartburn was demonstrated to be the main cause of overlapping reflux symptoms(55.1%). Reflux parameters analysis revealed that the reflux burden in the overlap symptoms group paralleled that of the FD symptoms group, with both registering lower levels than the reflux symptoms group (P < 0.05). Furthermore, PPI response rates were notably diminished in the overlap symptoms group (P < 0.001), even for those with objective gastroesophageal reflux disease evidences. Conclusions The study illuminated that overlapping reflux symptoms in FD was common. Strikingly, these symptoms primarily diverged from reflux etiology and exhibited suboptimal responses to PPI intervention. These findings challenge prevailing paradigms and accentuate the imperative for nuanced therapeutic approaches tailored to the distinctive characteristics of overlapping reflux symptoms in the context of FD.