BACKGROUND: Neuroticism has been associated with numerous health outcomes. However, most research has focused on a single specific disorder and has produced controversial results, particularly regarding mortality risk. Here, we aimed to examine the association of neuroticism with morbidity and mortality and to elucidate how neuroticism affects trajectories from a healthy state, to one or more neuroticism-related disorders, and subsequent mortality risk. METHODS: We included 483,916 participants from the UK Biobank at baseline (2006-2010). Neuroticism was measured using the Eysenck Personality Questionnaire. Three clusters were constructed, including worry, depressed affect, and sensitivity to environmental stress and adversity (SESA). Cox proportional hazards regression and multistate models were used. Linear regression was used to examine the association between neuroticism and immune parameters and neuroimaging measures. RESULTS: High neuroticism was associated with 37 non-overlapping diseases, including increased risk of infectious, cardiometabolic, neuropsychiatric, digestive, and respiratory diseases, and decreased risk of cancer. After adjustment for sociodemographic variables, physical measures, healthy behaviors, and baseline diagnoses, moderate-to-high neuroticism was associated with a decreased risk of all-cause mortality. In multistate models, high neuroticism was associated with an increased risk of transitions from a healthy state to a first neuroticism-related disease (hazard ratio [HR] [95% confidence interval (CI)] = 1.09 [1.05-1.13], P  <0.001) and subsequent transitions to multimorbidity (1.08 [1.02-1.14], P  = 0.005), but was associated with a decreased risk of transitions from multimorbidity to death (0.90 [0.84-0.97], P for trend = 0.006). The leading neuroticism cluster showing a detrimental role in the health-illness transition was depressed affect, which correlated with higher amygdala volume and lower insula volume. The protective effect of neuroticism against mortality was mainly contributed by the SESA cluster, which, unlike the other two clusters, did not affect the balance between innate and adaptive immunity. CONCLUSION This study provides new insights into the differential role of neuroticism in health outcomes and into new perspectives for establishing mortality prevention programs for patients with multimorbidity.
Humans ; Neuroticism/physiology* ; Male ; Female ; Middle Aged ; Aged ; Proportional Hazards Models ; Surveys and Questionnaires ; Adult ; Risk Factors

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 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 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 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.

Ulcerative colitis (UC) is a chronic and non-specific inflammatory bowel disease (IBD). Huanglian Ganjiang decoction (HGD), derived from ancient book Beiji Qianjin Yao Fang, has demonstrated efficacy in treating UC patients traditionally. Previous research established that the compatibility of cold herb Coptidis Rhizoma + Phellodendri Chinensis Cortex (CP) and hot herb Angelicae Sinensis Radix + Zingiberis Rhizoma (AZ) in HGD synergistically improved colitis mice. This study investigated the compatibility mechanisms through which CP and AZ regulated inflammatory balance in colitis mice. The experimental colitis model was established by administering 3% dextran sulphate sodium (DSS) to mice for 7 days, followed by CP, AZ and CPAZ treatment for an additional 7 days. M1/M2 macrophage polarization levels, glucose metabolites levels and pyruvate dehydrogenase kinase 4 (PDK4) expression were analyzed using flow cytometry, Western blot, immunofluorescence and targeted glucose metabolomics. The findings indicated that CP inhibited M1 macrophage polarization, decreased inflammatory metabolites associated with tricarboxylic acid (TCA) cycle, and suppressed PDK4 expression and pyruvate dehydrogenase (PDH) (Ser-293) phosphorylation level. AZ enhanced M2 macrophage polarization, increased lactate axis metabolite lactate levels, and upregulated PDK4 expression and PDH (Ser-293) phosphorylation level. TCA cycle blocker AG-221 and adeno-associated virus (AAV)-PDK4 partially negated CP's inhibition of M1 macrophage polarization. Lactate axis antagonist oxamate and PDK4 inhibitor dichloroacetate (DCA) partially reduced AZ's activation of M2 macrophage polarization. In conclusion, the compatibility of CP and AZ synergistically alleviated colitis in mice through M1/M2 macrophage polarization balance via PDK4-mediated glucose metabolism reprogramming. Specifically, CP reduced M1 macrophage polarization by restoration of TCA cycle via PDK4 inhibition, while AZ increased M2 macrophage polarization through activation of PDK4/lactate axis.
Animals ; Drugs, Chinese Herbal/chemistry* ; Mice ; Macrophages/immunology* ; Glucose/metabolism* ; Pyruvate Dehydrogenase Acetyl-Transferring Kinase/genetics* ; Male ; Mice, Inbred C57BL ; Humans ; Colitis/drug therapy* ; Disease Models, Animal ; Colitis, Ulcerative/drug therapy* ; Metabolic Reprogramming

OBJECTIVES: This study aimed to use machine learning algorithms to build a prediction model of the first permanent molar caries of 9-year-old children in Suzhou and screen out risk factors. METHODS: Random stratified whole group sampling was applied to randomly select 9-year-old students from 38 primary schools in 14 townships and streets in Wuzhong District for oral examination and questionnaire survey. Multifactor Logistics regression was used to analyze the risk factors of tooth decay. The data set was randomly divided into training sets and verification sets according to 8∶2, and R 4.3.1 was used to build five machine learning algorithms: random forest, decision tree, extreme gradient boosting (XGBoost), Logistics regression, and lightweight gradient enhancement (LightGBM). The predictive effect of these five models was evaluated using the area under the characteristic curve (AUC). The marginal contribution of quantitative characteristics to the caries prediction model was determined through Shapley additive explanations (SHAP). RESULTS: This study included 7 225 samples that met the standard. The caries rate of the first permanent molar was 54.96%. Multifactor Logistic regression analysis showed that sweet drinks, dessert and candy, snack frequency, and snacks before going to bed after brushing teeth were correlated with the occurrence of first permanent molar caries (P<0.05). The AUC values of decision tree, Logistic regression, LightGBM, random forest, and XGBoost were 75.5%, 83.9%, 88.6%, 88.9%, and 90.1%, respectively. Compared with the variables after single heat coding, the SHAP value of high-frequency sweets (such as dessert candy ≥2 times a day, mother's sugary diet ≥2 times a day) and bad oral hygiene habits (such as frequent snacks before going to bed after brushing teeth and irregular brushing teeth) exhibited the highest positive. CONCLUSIONS XGBoost algorithm has a good prediction effect for first permanent molar caries in 9-year-old children. High-frequency sweet factors and bad oral hygiene habits have a strong positive impact on the risk of first permanent molar caries and are key drivers that can be used in the formulation of targeted interventions.
Humans ; Dental Caries/epidemiology* ; Child ; Machine Learning ; China/epidemiology* ; Molar ; Risk Factors ; Female ; Logistic Models ; Male ; Decision Trees ; Algorithms

Proteins are fundamental carriers as the structural elements and biochemically active entities responsible for catalysis, transport, and regulation. These functions are depending on the protein folding into precise three-dimensional structures, interacting with ligands, and conformational changes. This article reviews the recent progress of nanopores in single-molecule protein sensing, involving the identification of polypeptides and proteins, the conformation changes of protein folding, the molecular structure responsible to the pH of solutions, the molecular interactions, and protein sequencing. These studies provide clues to understand life activities and facilitate the early diagnosis of diseases and design of drugs for precise treatment.
Nanopores ; Proteins/chemistry* ; Biosensing Techniques/methods* ; Protein Folding ; Humans

OBJECTIVE To explore the effect of fluconazole on proteomics of Trichosporon asahii so as to reveal the responding process of T.asahii to fluconazole stress and the resistance mechanisms to azoles on the protein level.METHODS T.asahii AS 2.2174 was chosen as the research subject,the minimum inhibitory concentration(MIC)of fluconazole was determined by broth microdilution assay.The protein abundance of T.asahii was detec-ted by means of tandem mass tag(TMT)technique combined with liquid chromatography-tandem mass spectrom-etry(LC-MS/MS)before and after the treatment with fluconazole(1× MIC).The differentially expressed pro-teins(DEPs)were identified based on the screening standards of fold change ≥1.20 or ≤0.83 and P＜0.05.Gene ontlogy(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis were performed for the DEPs so as to understand the biological property of the DEPs and the major biological pathways that the DEPs in-volved in.Finally,the targeted validation was carried out for the targeted differentially expressed proteins by using multiple reaction monitoring(MRM).RESULTS The MIC of fluconazole to T.asahii AS 2.2174 was 8 μg/ml.Totally 196 DEPs were identified,including 93 upregulated DEPs and 103 downregulated DEPs.The function en-richment analysis showed that the DEPs mainly participated in synthesis and metabolism of sterols,drug metabo-lism,stress response,energy metabolism and intertranslation.The targeted DEPs showed the consistent expres-sion trends in MRM target validation and TMT-LC-MS/MS.CONCLUSIONS The protein abundance of T.asahii has remarkable change under the fluconazole stress.The bioinformatics analysis reveals the complicated molecular mechanisms of T.asahii in response to the fluconazole stress,which may offer valuable ideas for understanding the drug resistance to azoles and developing new drug targets.