Multiple myeloma (MM) is a hematological malignancy that poses significant treatment challenges due to its heterogeneity and propensity for relapse and progression. In the last two decades, the therapeutic landscape of MM has changed dramatically, but the disease remains largely incurable, with many patients facing treatment resistance. This review evaluates the current status of MM treatments, emphasizing the limitations of traditional therapies and the emerging role of immunotherapy in improving patient outcomes. It highlights the importance of achieving and maintaining minimal residual disease negativity and a balanced immune response as key treatment goals. Furthermore, it discusses the advancements in immunotherapies that are improving the prospects for patients, particularly those with relapsed or refractory disease. Innovative strategies, such as chimeric antigen receptor T-cell therapy, bispecific antibodies, and bispecific T cell engagers, have shown significant promise by targeting the malignant cells and the bone marrow microenvironment, which are essential for disease persistence and resistance to therapy. Future research should focus on refining MM treatment strategies, including the integration of immunotherapy into earlier treatment lines and the development of predictive biomarkers for personalized treatment approaches, ultimately enhancing patient outcomes.

Objective Based on 25 indicators including immune factors, cell count classification, and smear results of the knee joint fluid, machine learning models were established to distinguish between osteoarthritis (OA) and rheumatoid arthritis (RA). Methods 100 OA and 40 RA patients scheduled for total knee arthroplasty were enrolled respectively. Each patient's knee joint fluid was collected preoperatively. Nucleated cells were counted and classified. The expression levels of immune factors, including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), IL-6, IL-8, IL-15, matrix metalloproteinase 3 (MMP3), MMP9, MMP13, rheumatoid factor (RF), serum amyloid A (SAA), C-reactive protein (CRP), and others were measured. Smears and microscopic classification of all the immune factors were performed. Independent influencing factors for OA or RA were identified using univariate binary logistic regression, Lasso regression, and multivariate binary logistic regression. Based on the independent influencing factors, three machine learning models were constructed which are logistic regression, random forest, and support vector machine. Receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to evaluate and compare the models. Results A total of 5 indicators in the knee joint fluid were screened out to distinguish OA and RA, which were IL-1β(odds ratio(OR)=10.512, 95× confidence interval (95×CI) was 1.048-105.42, P=0.045), IL-6 (OR=1.007, 95×CI was 1.001-1.014, P=0.022), MMP9 (OR=3.202, 95×CI was 1.235-8.305, P=0.017), MMP13 (OR=1.002, 95× CI was 1-1.004, P=0.049), and RF (OR=1.091, 95×CI was 1.01-1.179, P=0.026). According to the results of ROC, calibration curve and DCA, the accuracy (0.979), sensitivity (0.98) and area under the curve (AUC, 0.996, 95×CI was 0.991-1) of the random forest model were the highest. It has good validity and feasibility, and its distinguishing ability is better than the other two models. Conclusion The machine learning model based on immune factors in the knee joint fluid holds significant value in distinguishing OA and RA. It provides an important reference for the clinical early differential diagnosis, prevention and treatment of OA and RA.
Humans ; Arthritis, Rheumatoid/metabolism* ; Machine Learning ; Male ; Female ; Middle Aged ; Aged ; Synovial Fluid/immunology* ; Osteoarthritis, Knee/metabolism* ; Knee Joint/metabolism* ; ROC Curve ; Diagnosis, Differential

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Objective:To investigate the feasibility of the bortezomib, lenalidomide, and dexamethasone (VRD) regimen combined with autologous hematopoietic stem cell transplantation (auto-HSCT) in patients with multiple myeloma (MM) and renal impairment, analyze treatment efficacy and renal responses stratified based on renal dysfunction severity, and explore the prognostic significance of early renal response and its affecting factors.Methods:This retrospective study, conducted at the First Affiliated Hospital of Soochow University, categorized 316 patients with newly diagnosed MM (NDMM) from August 2018 to October 2022 based on renal function for analysis of clinical characteristics, treatment response, and prognosis. Continuous variables were compared using t-tests or Mann-Whitney U tests, categorical variables utilizing Chi-square tests, survival outcomes employing Kaplan-Meier and Log-rank tests, and renal response predictors with logistic regression.Results:Patients were stratified based on baseline estimated glomerular filtration rate (eGFR) : normal [≥90 ml·min -1· (1.73 m 2) -1, n=160], mild [≥60 ml·min -1· (1.73 m 2) -1 to <90 ml·min -1· (1.73 m 2) -1, n=55], moderate [≥30 ml·min -1· (1.73 m 2) -1 to <60 ml·min -1· (1.73 m 2) -1, n=39], and severe impairment [<30 ml·min -1· (1.73 m 2) -1, n=62]. Moderate and severe renal impairment correlated with advanced International Staging System/Revised International Staging System classification, lower hemoglobin levels, frailty, and higher light-chain/IgD subtype prevalence ( P<0.05). Despite younger age ( P=0.001) and higher transplant rates ( P=0.041) in severe cases, overall response rates ( ORR: 93.7% ; ≥VGPR: 82.9% ) were comparable across groups ( P>0.05). Among 24 dialysis-dependent patients at diagnosis, 11 (45.8% ) achieved dialysis independence after induction [median: 3.0 (0.5–4.0) months], including 10 undergoing auto-HSCT. In 89 evaluable patients [baseline eGFR <50 ml·min -1· (1.73 m 2) -1], renal ORR (RORR) was 70.8% [rapid complete response: 31.5% ; rapid partial response: 11.2% ; rapid minimal response (RMR) : 28.1% ]. Renal response predicted better survival (overall survival: HR=0.36, 95% CI: 0.13–0.99, P=0.049). Moderate-to-severe renal impairment was associated with increased transplant-related adverse events and delayed engraftment ( P<0.05) ; however, auto-HSCT significantly improved outcomes after 33.5-month median follow-up (range: 2–65 months). Multivariate analysis identified 1q21+ ( OR=3.58, 95% CI: 1.17–11.02, P=0.026) and light-chain subtype ( OR=2.86, 95% CI: 1.08–7.69, P=0.036) as independent predictors of poor renal response. Conclusion:VRD regimen plus auto-HSCT demonstrates robust efficacy in NDMM, including patients with renal impairment, with a 70.8% RORR and manageable toxicity. Achieving ≥RMR correlates with superior prognosis, whereas 1q21+ and light-chain subtype independently predict inferior renal response.

Objective·To detect immunoglobulin(Ig)expression levels in newly diagnosed multiple myeloma(MM)patients before and after induction therapy,and to explore the clinical significance of Ig expression levels and their dynamic changes in relation to treatment efficacy,infection occurrence,and prognosis.Methods·Clinical data from 142 MM patients treated at the Department of Hematology,The First Affiliated Hospital of Soochow University between August 2018 and September 2020 were analyzed.Baseline Ig expression levels and post-induction changes following bortezomib-lenalidomide-dexamethasone(VRD)regimen were assessed.Immunoparesis was defined as uninvolved Igs below the laboratory lower limit of normal.Patients were stratified by immunoparesis severity(mild,moderate,severe,extremely severe).ANOVA,rank-sum tests,and x2 tests were used to analyze correlations with baseline characteristics.The relationship between the improvement in immunoparesis and the induction efficacy,infection occurrence,and prognosis was analyzed based on the dynamic changes in immunoparesis.Results·Normal Igs were severely reduced in newly diagnosed MM patients.Immunoparesis was present in 128 patients(90.1%),with severe or extremely severe immunoparesis accounting for 76.1%.Patients with extensive immunoparesis(all uninvolved Ig levels below the lower normal limit)were more likely to have severe immunoparesis(P<0.05).There were no statistically significant differences in age,gender,presence of severe renal insufficiency,and high-risk cytogenetics among MM patients with different degrees of immunoparesis(P>0.05),but there were statistically significant differences in MM staging(P=0.008)and typing(P=0.010).Most patients with severe immunoparesis were at stage Ⅱ/Ⅲ based on the Revised International Staging System(R-ISS)and were of the IgG type.At diagnosis,the levels of the involved Ig or light chain were negatively correlated with normal Ig levels(P<0.05).Improvement in immunoparesis after induction therapy was positively correlated with treatment response(P=0.006).The infection rate was high(26.8%),but no significant correlation was found between immunoparesis and infection occurrence(P>0.05).After induction therapy,patients showing improvement in immunoparesis had significantly longer progression-free survival(PFS)(median PFS:not reached vs 38 months,P=0.025),but no significant impact on overall survival(OS)was observed(P=0.450).Conclusion·Immunoparesis is common and severe in newly diagnosed MM patients,with severity correlating with disease stage and subtype.VRD therapy can partially reverse immunoparesis,and improvement is positively associated with treatment response and PFS benefit.Infection risk appears unrelated to immunoparesis severity and warrants comprehensive prevention strategies.Humoral immune deficiency may serve as a prognostic indicator in MM,but its impact on OS requires further investigation.

Objective·To detect immunoglobulin(Ig)expression levels in newly diagnosed multiple myeloma(MM)patients before and after induction therapy,and to explore the clinical significance of Ig expression levels and their dynamic changes in relation to treatment efficacy,infection occurrence,and prognosis.Methods·Clinical data from 142 MM patients treated at the Department of Hematology,The First Affiliated Hospital of Soochow University between August 2018 and September 2020 were analyzed.Baseline Ig expression levels and post-induction changes following bortezomib-lenalidomide-dexamethasone(VRD)regimen were assessed.Immunoparesis was defined as uninvolved Igs below the laboratory lower limit of normal.Patients were stratified by immunoparesis severity(mild,moderate,severe,extremely severe).ANOVA,rank-sum tests,and x2 tests were used to analyze correlations with baseline characteristics.The relationship between the improvement in immunoparesis and the induction efficacy,infection occurrence,and prognosis was analyzed based on the dynamic changes in immunoparesis.Results·Normal Igs were severely reduced in newly diagnosed MM patients.Immunoparesis was present in 128 patients(90.1%),with severe or extremely severe immunoparesis accounting for 76.1%.Patients with extensive immunoparesis(all uninvolved Ig levels below the lower normal limit)were more likely to have severe immunoparesis(P<0.05).There were no statistically significant differences in age,gender,presence of severe renal insufficiency,and high-risk cytogenetics among MM patients with different degrees of immunoparesis(P>0.05),but there were statistically significant differences in MM staging(P=0.008)and typing(P=0.010).Most patients with severe immunoparesis were at stage Ⅱ/Ⅲ based on the Revised International Staging System(R-ISS)and were of the IgG type.At diagnosis,the levels of the involved Ig or light chain were negatively correlated with normal Ig levels(P<0.05).Improvement in immunoparesis after induction therapy was positively correlated with treatment response(P=0.006).The infection rate was high(26.8%),but no significant correlation was found between immunoparesis and infection occurrence(P>0.05).After induction therapy,patients showing improvement in immunoparesis had significantly longer progression-free survival(PFS)(median PFS:not reached vs 38 months,P=0.025),but no significant impact on overall survival(OS)was observed(P=0.450).Conclusion·Immunoparesis is common and severe in newly diagnosed MM patients,with severity correlating with disease stage and subtype.VRD therapy can partially reverse immunoparesis,and improvement is positively associated with treatment response and PFS benefit.Infection risk appears unrelated to immunoparesis severity and warrants comprehensive prevention strategies.Humoral immune deficiency may serve as a prognostic indicator in MM,but its impact on OS requires further investigation.

Objective:To investigate the feasibility of the bortezomib, lenalidomide, and dexamethasone (VRD) regimen combined with autologous hematopoietic stem cell transplantation (auto-HSCT) in patients with multiple myeloma (MM) and renal impairment, analyze treatment efficacy and renal responses stratified based on renal dysfunction severity, and explore the prognostic significance of early renal response and its affecting factors.Methods:This retrospective study, conducted at the First Affiliated Hospital of Soochow University, categorized 316 patients with newly diagnosed MM (NDMM) from August 2018 to October 2022 based on renal function for analysis of clinical characteristics, treatment response, and prognosis. Continuous variables were compared using t-tests or Mann-Whitney U tests, categorical variables utilizing Chi-square tests, survival outcomes employing Kaplan-Meier and Log-rank tests, and renal response predictors with logistic regression.Results:Patients were stratified based on baseline estimated glomerular filtration rate (eGFR) : normal [≥90 ml·min -1· (1.73 m 2) -1, n=160], mild [≥60 ml·min -1· (1.73 m 2) -1 to <90 ml·min -1· (1.73 m 2) -1, n=55], moderate [≥30 ml·min -1· (1.73 m 2) -1 to <60 ml·min -1· (1.73 m 2) -1, n=39], and severe impairment [<30 ml·min -1· (1.73 m 2) -1, n=62]. Moderate and severe renal impairment correlated with advanced International Staging System/Revised International Staging System classification, lower hemoglobin levels, frailty, and higher light-chain/IgD subtype prevalence ( P<0.05). Despite younger age ( P=0.001) and higher transplant rates ( P=0.041) in severe cases, overall response rates ( ORR: 93.7% ; ≥VGPR: 82.9% ) were comparable across groups ( P>0.05). Among 24 dialysis-dependent patients at diagnosis, 11 (45.8% ) achieved dialysis independence after induction [median: 3.0 (0.5–4.0) months], including 10 undergoing auto-HSCT. In 89 evaluable patients [baseline eGFR <50 ml·min -1· (1.73 m 2) -1], renal ORR (RORR) was 70.8% [rapid complete response: 31.5% ; rapid partial response: 11.2% ; rapid minimal response (RMR) : 28.1% ]. Renal response predicted better survival (overall survival: HR=0.36, 95% CI: 0.13–0.99, P=0.049). Moderate-to-severe renal impairment was associated with increased transplant-related adverse events and delayed engraftment ( P<0.05) ; however, auto-HSCT significantly improved outcomes after 33.5-month median follow-up (range: 2–65 months). Multivariate analysis identified 1q21+ ( OR=3.58, 95% CI: 1.17–11.02, P=0.026) and light-chain subtype ( OR=2.86, 95% CI: 1.08–7.69, P=0.036) as independent predictors of poor renal response. Conclusion:VRD regimen plus auto-HSCT demonstrates robust efficacy in NDMM, including patients with renal impairment, with a 70.8% RORR and manageable toxicity. Achieving ≥RMR correlates with superior prognosis, whereas 1q21+ and light-chain subtype independently predict inferior renal response.

Objective To investigate the effect of Galangin on pyroptosis of bone marrow derived macrophages(BMDMs).Methods BMDMs were cultured in vitro and divided into blank control group,model group and Galangin group with different concentrations.Lipopolysaccharide(LPS)and adenosine triphosphate(ATP)were used to construct the pyroptosis model.The effect of different concentrations of Galangin on the proliferation of BMDMs was detected by cell counting Kit-8(CCK-8).The level of cysteinyl aspartate specific proteinase-1 p10 subunit(caspase-1 p10),interleukin-1β(IL-1β)in supernatant and intracellular nucleotide NOD-like receptor protein 3(NLRP3)were detected by Western blotting.IL-1β in supernatant was detected by enzyme-linked immunosorbent assay(ELISA).The cell death was observed by propidium iodide(PI)staining.High-throughput sequencing was used to compare the gene expression in the model group and Galangin groups at 20 μmol/L.Results There was no statistically significant difference between the 5,10,20,40,60,80 μmol/L Galangin groups on the proliferation level of BMDMs(all P>0.05),indicating that no significant effect of Galangin at 5,10,20,40,60,80 μmol/L was observed on the proliferation of BMDMs.So we selected Galangin at 5,10,20 μmol/L and treatment for 1,2 and 4 hours as the effects of different concentrations and time on the pyroptosis of BMDMs.Compared with blank control group,the expression of caspase-1 p10 and mature IL-1β protein and IL-1β in supernatant in model group were significantly increased(all P<0.05).Compared with model group,the expression of caspase-1 p10 and mature IL-1β protein and IL-1β in supernatant of Galangin at 5,10 and 20 μmol/L were significantly decreased[IL-1β protein expression(gray value):0.155±0.006,0.113±0.006,0.111±0.007 vs.1.000±0.000,caspase-1 p10 protein expression(gray value):0.207±0.044,0.160±0.008,0.082±0.008 vs.1.000±0.000,IL-1β(μg/L):99.80±10.36,85.21±8.78,26.53±4.56 vs.494.10±35.47,all P<0.05].There was no significant difference between the different concentration groups(all P>0.05),but with the extension of treatment time of Galangin,the inhibitory effect was enhanced.The inhibitory effect of Galangin at 20 μmol/L for 4 hours was the most obvious[IL-1β protein expression(gray value):0.186±0.004 vs.1.000±0.000,caspase-1 p10 protein expression(gray value):0.247±0.009 vs.1.000±0.000,IL-1β(μg/L):173.80±10.56 vs.653.80±76.02,all P<0.05].Treatment with 20 μmol/L Galangin for 4 hours could reduce the number of pyroptotic cell deaths(number of view:23.00±3.61 vs.67.67±15.63,P<0.05)and inhibited the expression of NLRP3 protein(gray value:0.178±0.025 vs.0.406±0.066,P<0.05).High-throughput sequencing showed that,compared with the model group,Galangin down-regulated the genes of Nlrp3,Nod2,IL-1β and up-regulated genes of Skp2(also known as Fbxl1),Fbxl20,Fbxl4,Fbxo32 and Fbxw7.Conclusion Galangin inhibited pyroptosis mediated by NLRP3 inflammasome in macrophages.

Objective: To analyze the strengths, weaknesses, opportunities and threats of the construction on intelligent vaccination clinics in Zhejiang Province, so as to provide countermeasures for promoting the construction of intelligent vaccination clinics in Zhejiang Province. Methods: By reviewing the annual reports of Zhejiang immunization planning, survey data from Zhejiang Centers for Disease Control and Prevention and Immunization Intelligent Service System, data of human resources of immunization planning, vaccine procurement, construction progress of intelligent vaccination clinics and vaccination were collected. The relevant literature was searched to gather information on the construction standards and norms of intelligent vaccination clinics. The analysis of the strengths, weaknesses, opportunities and threats (SWOT) of the construction of intelligent vaccination clinics was conducted, and corresponding countermeasures and suggestions were proposed. Results: The National Immunization Program reported vaccine rate in Zhejiang Province is more than 99%, and standardized vaccination clinics have been popularized throughout the province. The vaccination staff are professional, and a province-wide intelligent immunization service information system has been established, providing the resources and conditions for the construction of intelligent vaccination clinics. However, there are problems such as low data quality and matching efficiency in vaccination, insufficient data interoperability and sharing, unbalanced regional capabilities in intelligent transformation, and uneven distribution of talent and resources. It is crucial to seize the opportunities presented by the development of big data and artificial intelligence, rely on the regional development of the Internet and health industry, seize the opportunity of rapid growth in demand for intelligent vaccination services and high public acceptance, accelerate the construction of intelligent vaccination clinics, and establish intelligent vaccination service standards as soon as possible. Conclusion We should seize the opportunities presented by the digital reform and development, fully utilize the existing vaccination resources and strengths, address the shortcomings, and accelerate the construction of intelligent vaccination clinics in Zhejiang Province.

Objective To analyze the influencing factors of survival of patients with airway stenosis requiring clinical interventions after lung transplantation. Methods Clinical data of 66 patients with airway stenosis requiring clinical interventions after lung transplantation were retrospectively analyzed. Univariate and multivariate Cox’s regression models were adopted to analyze the influencing factors of survival of all patients with airway stenosis and those with early airway stenosis. Kaplan-Meier method was used to calculate the overall survival and delineate the survival curve. Results For 66 patients with airway stenosis, the median airway stenosis-free time was 72 (52,102) d, 27% (18/66) for central airway stenosis and 73% (48/66) for distal airway stenosis. Postoperative mechanical ventilation time [hazard ratio (HR) 1.037, 95% confidence interval (CI) 1.005-1.070, P=0.024] and type of surgery (HR 0.400, 95%CI 0.177-0.903, P=0.027) were correlated with the survival of patients with airway stenosis after lung transplantation. The longer the postoperative mechanical ventilation time, the higher the risk of mortality of the recipients. The overall survival of airway stenosis recipients undergoing bilateral lung transplantation was better than that of their counterparts after single lung transplantation. Subgroup analysis showed that grade 3 primary graft dysfunction (PGD) (HR 4.577, 95%CI 1.439-14.555, P=0.010) and immunosuppressive drugs (HR 0.079, 95%CI 0.022-0.287, P<0.001) were associated with the survival of patients with early airway stenosis after lung transplantation. The overall survival of patients with early airway stenosis after lung transplantation without grade 3 PGD was better compared with that of those with grade 3 PGD. The overall survival of patients with early airway stenosis after lung transplantation treated with tacrolimus was superior to that of their counterparts treated with cyclosporine. Conclusions Long postoperative mechanical ventilation time, single lung transplantation, grade 3 PGD and use of cyclosporine may affect the survival of patients with airway stenosis after lung transplantation.