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.

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.

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 systematically evaluate the effectiveness of different treatment regimens as first-line treatment for metastatic urothelial carcinoma （UC） using a network meta-analysis （NMA） approach. METHODS Electronic databases including PubMed， the Cochrane Library， Embase， Wanfang Data， CNKI， and VIP were searched for randomized controlled clinical trials （RCTs） on first-line treatment for metastatic UC from January 1， 2010 to January 31， 2024. After literature screening and data extraction， a risk of bias assessment of included studies was conducted. R software （version 4.3.2） was used to perform the NMA. RESULTS A total of 11 RCTs involving 14 treatment interventions were included. No significant differences were noted in objective response rate among groups， with the combination of pembrolizumab， gemcitabine and cisplatin having the highest probability of ranking first. Regarding progression-free survival （PFS） and overall survival （OS）， no significant differences were observed among groups， while enfortumab vedotin combined with pembrolizumab showed a trend towards better PFS extension compared to gemcitabine combined with cisplatin [HR＝0.45， 95%CI（0.20，1.06）， P＝0.049]， and it had the highest probability of ranking first in both PFS and OS. CONCLUSIONS The combination of enfortumab vedotin and pembrolizumab may have an advantage in prolonging survival in the first-line treatments for metastatic UC.

Objective:To explore the role of corticotrophin releasing factor receptor 2 (CRFR2) in regulating pain sensitization and anxiety and its mechanism in chronic migraine mice.Methods:Forty-eight C57BL/6J mice were randomly divided into control group, model group, NBI35965 group and K41498 group ( n=12); chronic migraine models in the later 3 groups were established by intraperitoneally administrating 10 mg/kg nitroglycerin on the 1 st, 3 rd, 5 th, 7 th and 9 th d; mice in the NBI35965 group and K41498 group were injected with 100 nL NBI35965 or K41498 solution into the bilateral trigeminal nucleus caudalis on the 2 nd, 4 th, 6 th and 8 th d, and mice in the control group were injected with same volume of normal saline. Von frey fiber was used to detect the orbitofrontal mechanical pain threshold 2 h after intraperitoneal injection on the 1 st, 3 rd, 5 th, 7 th and 9 th d, and at 11 a.m. on the 10 th d. Elevated plus maze was used to detect the anxiety-like behaviors at 11 a.m. on the 11 th d. Western blotting was performed to detect the protein expressions of corticotrophin releasing factor (CRF), corticotrophin releasing factor receptor 1 (CRFR1), CRFR2 in the trigeminal nucleus caudalis. Real-time quantitative PCR (RT-qPCR) was used to detect the CRFR1 and CRFR2 mRNA expressions in the trigeminal nucleus caudalis. Immunofluorescent staining was used to detect the protein expressions of calcitonin gene-related peptide (CGRP), immediate-early gene c-fos, glial fibrillary acidic protein (GFAP) and ionized calcium-binding adapter molecule 1 (Iba-1) in the trigeminal nucleus caudalis. Results:Compared with the control group, the model group, NBI35965 group and K41498 group had significantly decreased orbitofrontal mechanical pain thresholds 3, 5, 7, 9, and 10 d after intraperitoneal injection ( P<0.05); compared with model group, the K41498 group had significantly increased orbitofrontal mechanical pain thresholds 7, 9, and 10 d after intraperitoneal injection ( P<0.05). Compared with control group, the model group, NBI35965 group and K41498 group had significantly decreased entries and shorter time in opened arms ( P<0.05); compared with the model group, the K41498 group had significantly increased entries and shorter time in opened arms ( P<0.05). Compared with the control group, the model group, NBI35965 group and K41498 group had significantly higher CRF and CRFR2 protein expressions in the trigeminal nucleus caudalis ( P<0.05); compared with the model group, the K41498 group had statistically lower CRF protein expression in the trigeminal nucleus caudalis ( P<0.05). Compared with the control group, the model group, NBI35965 group and K41498 group had significantly higher CRFR2 mRNA expression in the trigeminal nucleus caudalis ( P<0.05). Compard with the control group, the model group, NBI35965 group and K41498 group had significantly increased CGRP, c-fos, Iba-1 and GFAP protein expressions in the trigeminal nucleus caudalis ( P<0.05); compared with the model group, the K41498 group had significantly decreased CGRP and c-fos protein expressions in the trigeminal nucleus caudalis ( P<0.05). Conclusion:CRFR2 can alter the orbitofrontal pain sensitization and anxiety-like behaviors in chronic migraine mice by regulating neuronal activation and CGRP release in the trigeminal nucleus caudalis.

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.

With the optimization of surgical technologies and postoperative management regimens, the number of lung transplantation has been significantly increased, which has become an important treatment for patients with end-stage lung disease. However, due to the impact of comprehensive factors, such as bronchial ischemia and immunosuppression, the incidence of airway stenosis after lung transplantation is relatively high, which severely affects postoperative survival and quality of life of lung transplant recipients. In recent years, with the improvement of perioperative management, organ preservation and surgical technologies, the incidence of airway stenosis after lung transplantation has been declined, but it remains at a high level. Early diagnosis and timely intervention play a significant role in enhancing clinical prognosis of patients with airway stenosis. In this article, the general conditions, diagnosis, treatment and prevention of airway stenosis after lung transplantation were reviewed, aiming to provide reference for comprehensive management of airway stenosis after lung transplantation and improving clinical prognosis of lung transplant recipients.