Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

Objective:To integrate implicit templates with deep learning techniques, a novel neural network, the tooth-deformable deep implicit network (T-DDIN), was constructed to achieve high-precision shape completion of tooth defects in a personalized manner.Methods:A total of 550 intraoral scan models were collected from patients treated at the Department of Orthodontics and Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University (500 for training and 50 for testing), between March 2022 and March 2024. T-DDIN reconstructed defective tooth morphology using an implicit template and a latent encoding prediction network. During model evaluation, Class Ⅱ cavity defects and occlusal wear defects were simulated in the test set. Morphological restoration was performed using both traditional computer aided design (CAD) methods and the T-DDIN deep learning approach. The two methods were compared based on three-dimensional deviation, occlusal adjustment volumes, cusp angle deviation, and restoration time.Results:The T-DDIN group demonstrated significantly lower three-dimensional deviation for Class Ⅱ cavity defects and occlusal wear restoration [(0.14±0.05) and (0.16±0.09) mm], occlusal adjustment volumes [(0.44±0.03) and (0.49±0.03) mm 3], and difference value of the tooth cusp angles (5.69°±1.90° and 6.04°±0.53°) compared to the traditional CAD group (both P<0.001). No significant differences were observed within the T-DDIN group between the two defect types in terms of three-dimensional deviation ( P=0.098) or occlusal adjustment volume ( P=0.154) or difference value of the tooth cusp angles ( P=0.196). However, in the traditional CAD group, three-dimensional deviation, occlusal adjustment volume and difference value of the tooth cusp angles was significantly higher in occlusal wear restorations than in Class Ⅱ cavity defects restorations ( P<0.001). The T-DDIN group, which involved Class Ⅱ cavity defects and occlusal wear, demonstrated significantly less recovery time of morphology (37.2±7.7) and (39.4±6.2) s compared to the traditional CAD group ( P<0.001). Conclusions:T-DDIN demonstrated superior stability and accuracy in morphological reconstruction for various types of dental defects while significantly reducing restoration time.

Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

Objective To investigate the impacts of long non coding RNA(LncRNA)-PH domain containing 5 antisense RNA 1(FGD5-AS1)on the proliferation,migration,and invasion of colorectal cancer(CRC)cells by regulating the miR-299-5p/recombinant lysine specific demethylase 4B(KDM4B)axis.Methods The expressions of LncRNA FGD5-AS1,miR-299-5p,and KDM4B were detected by qRT-PCR in the surgically resected CRC tissues and adjacent tissues of 34 CRC patients CRC cells HCT116 were separated into si-NC group,si-FGD5-AS1 group,si-FGD5-AS1+inhibitor NC group,and si-FGD5-AS1+miR-299-5p inhibitor group.The levels of mRNA in each group were detected.CCK8,scratch assay,and Transwell assay were ap[plied to detect the proliferation,migration,and invasion of HCT116 cells in each group.Western blot was applied to detect the expression of proteins.Dual luciferase reporter gene assay verified the interaction mechanism between LncRNA FGD5-AS1 and miR-299-5p,and between miR-299-5p and KDM4B.Results LncRNA FGD5-AS1 and KDM4B were highly expressed in CRC tissue,while miR-299-5p was low expressed in CRC tissue(P＜0.05).The expression of LncRNA FGD5-AS1 mRNA,KDM4B mRNA,OD450,scratch healing rate,invasion number,PCNA,MMP-2,MMP-9,KDM4B in the si-FGD5-AS1 group were lower than those in the si-NC group,the expression of miR-299-5p mRNA was higher than that in the si-NC group(P＜0.05).Compared with the si-FGD5-AS1 group and si-FGD5-AS1+inhibitor NC group,the expression of miR-299-5p in the si-FGD5-AS1+miR-299-5p inhibitor group decreased(P＜0.05),the KDM4B mRNA,OD450,scratch healing rate,number of invasions,and expression of PCNA,MMP-2,MMP-9,KDM4B increased(P＜0.05).LncRNA FGD5-AS1 targeted negative regulation of miR-299-5p,while miR-299-5p targeted negative regulation of KDM4B.Conclusion Knocking down LncRNA FGD5-AS1 may inhibit the proliferation,migration,and invasion of CRC cells,and its mechanism may be achieved by regulating the miR-299-5p/KDM4B signaling axis.

Objective:To integrate implicit templates with deep learning techniques, a novel neural network, the tooth-deformable deep implicit network (T-DDIN), was constructed to achieve high-precision shape completion of tooth defects in a personalized manner.Methods:A total of 550 intraoral scan models were collected from patients treated at the Department of Orthodontics and Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University (500 for training and 50 for testing), between March 2022 and March 2024. T-DDIN reconstructed defective tooth morphology using an implicit template and a latent encoding prediction network. During model evaluation, Class Ⅱ cavity defects and occlusal wear defects were simulated in the test set. Morphological restoration was performed using both traditional computer aided design (CAD) methods and the T-DDIN deep learning approach. The two methods were compared based on three-dimensional deviation, occlusal adjustment volumes, cusp angle deviation, and restoration time.Results:The T-DDIN group demonstrated significantly lower three-dimensional deviation for Class Ⅱ cavity defects and occlusal wear restoration [(0.14±0.05) and (0.16±0.09) mm], occlusal adjustment volumes [(0.44±0.03) and (0.49±0.03) mm 3], and difference value of the tooth cusp angles (5.69°±1.90° and 6.04°±0.53°) compared to the traditional CAD group (both P<0.001). No significant differences were observed within the T-DDIN group between the two defect types in terms of three-dimensional deviation ( P=0.098) or occlusal adjustment volume ( P=0.154) or difference value of the tooth cusp angles ( P=0.196). However, in the traditional CAD group, three-dimensional deviation, occlusal adjustment volume and difference value of the tooth cusp angles was significantly higher in occlusal wear restorations than in Class Ⅱ cavity defects restorations ( P<0.001). The T-DDIN group, which involved Class Ⅱ cavity defects and occlusal wear, demonstrated significantly less recovery time of morphology (37.2±7.7) and (39.4±6.2) s compared to the traditional CAD group ( P<0.001). Conclusions:T-DDIN demonstrated superior stability and accuracy in morphological reconstruction for various types of dental defects while significantly reducing restoration time.

Objective:To explore the influence of initial high-risk cytogenetic abnormalities on the outcomes of children with acute myeloid leukemia (AML) after post-transplant Cyclophosphamide (PTCy)-based allogeneic hematopoietic stem cell transplantation (allo-HSCT).Methods:A retrospective cohort study.AML children who underwent PTCy-based allo-HSCT after the first complete remission at Wuhan Children′s Hospital, Tongji Medical College, Huazhong University of Science and Technology between April 2017 and April 2024 were enrolled.Patients were divided into intermediate-risk and high-risk groups based on their initial cytogenetic features.These patients were further divided into complex karyotype, 11q23 rearrangement, and other karyotype groups.Clinical characteristics and survival outcomes were compared among these groups.Measurement and count data were analyzed using Wilcoxon rank-sum/Kruskal-Wallis and χ2 tests, respectively.Survival and risk factor analyses were performed using Kaplan-Meier and Cox proportional hazards methods, respectively. Results:A total of 51 AML children who underwent allo-HSCT were included in this study.The median age at transplantation was 3.2 years and the median follow-up time was 4.6 years.There were 26 cases in the intermediate-risk group and 25 cases in the high-risk group; 8 cases in the complex karyotype group, 14 cases in the 11q23 rearrangement group, and 29 cases in the other karyotype groups.By the end of the follow-up on November 30, 2024, 11 patients relapsed, 8 patients died, and 13 patients developed grades Ⅱ-Ⅳ acute graft-versus-host disease (GVHD).The 3-year overall survival (OS), relapse-free survival (RFS), and grades Ⅱ-Ⅳ acute GVHD-free and relapse-free survival (GRFS) were 84.0% (95% CI: 74.4%-94.8%), 74.5% (95% CI: 63.4%-87.5%), and 58.8% (95% CI: 46.7%-74.0%), respectively.The 3-year OS of the high-risk group was significantly lower than that of the intermediate-risk group (71.8% vs.96.2%, P=0.022), while differences in 3-year RFS and GRFS between the 2 groups were not statistically significant (68.0% vs.80.8%, P=0.400; 52.0% vs.65.4%, P=0.420).The 3-year OS, RFS and GRFS of the complex karyotype group were significantly lower than those of 11q23 rearrangement and other karyotype groups (50.0% vs.85.7%, 93.1%, P=0.009; 37.5% vs.85.7%, 79.3%, P=0.022; 25.0% vs.64.3%, 65.5%, P=0.049).Multivariate analysis showed that a complex karyotype was an independent prognostic factor affecting 3-year OS and GRFS [OS: HR=6.79 (95% CI: 1.13-43.80), P=0.044; GRFS: HR=3.72(95% CI: 1.13-12.20), P=0.030]. Conclusions:High-risk cytogenetic features are significant predictors of survival outcomes in pediatric AML patients undergoing PTCy-based allo-HSCT.

OBJECTIVE: We aimed to investigate the patterns of fasting blood glucose (FBG) trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers. METHODS: The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort (TGOC) between 2017 and 2022. A group-based trajectory model was used to identify the FBG trajectories. Environmental risk scores (ERS) were constructed using regression coefficients from the occupational hazard model as weights. Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories. RESULTS: FBG trajectories were categorized into three groups. An association was observed between high temperature, noise exposure, and FBG trajectory ( P < 0.05). Using the first quartile group of ERS1 as a reference, the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90 and 2.21 times, respectively (odds ratio [ OR] = 1.90, 95% confidence interval [ CI]: 1.17-3.10; OR = 2.21, 95% CI: 1.09-4.45). CONCLUSION An association was observed between occupational hazards based on ERS and FBG trajectories. The risk of FBG trajectory levels increase with an increase in ERS.
Humans ; Male ; Adult ; Blood Glucose/analysis* ; China ; Prospective Studies ; Occupational Exposure/adverse effects* ; Risk Factors ; Middle Aged ; Steel ; Fasting/blood* ; Metal Workers ; East Asian People

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To investigate the impacts of long non coding RNA(LncRNA)-PH domain containing 5 antisense RNA 1(FGD5-AS1)on the proliferation,migration,and invasion of colorectal cancer(CRC)cells by regulating the miR-299-5p/recombinant lysine specific demethylase 4B(KDM4B)axis.Methods The expressions of LncRNA FGD5-AS1,miR-299-5p,and KDM4B were detected by qRT-PCR in the surgically resected CRC tissues and adjacent tissues of 34 CRC patients CRC cells HCT116 were separated into si-NC group,si-FGD5-AS1 group,si-FGD5-AS1+inhibitor NC group,and si-FGD5-AS1+miR-299-5p inhibitor group.The levels of mRNA in each group were detected.CCK8,scratch assay,and Transwell assay were ap[plied to detect the proliferation,migration,and invasion of HCT116 cells in each group.Western blot was applied to detect the expression of proteins.Dual luciferase reporter gene assay verified the interaction mechanism between LncRNA FGD5-AS1 and miR-299-5p,and between miR-299-5p and KDM4B.Results LncRNA FGD5-AS1 and KDM4B were highly expressed in CRC tissue,while miR-299-5p was low expressed in CRC tissue(P＜0.05).The expression of LncRNA FGD5-AS1 mRNA,KDM4B mRNA,OD450,scratch healing rate,invasion number,PCNA,MMP-2,MMP-9,KDM4B in the si-FGD5-AS1 group were lower than those in the si-NC group,the expression of miR-299-5p mRNA was higher than that in the si-NC group(P＜0.05).Compared with the si-FGD5-AS1 group and si-FGD5-AS1+inhibitor NC group,the expression of miR-299-5p in the si-FGD5-AS1+miR-299-5p inhibitor group decreased(P＜0.05),the KDM4B mRNA,OD450,scratch healing rate,number of invasions,and expression of PCNA,MMP-2,MMP-9,KDM4B increased(P＜0.05).LncRNA FGD5-AS1 targeted negative regulation of miR-299-5p,while miR-299-5p targeted negative regulation of KDM4B.Conclusion Knocking down LncRNA FGD5-AS1 may inhibit the proliferation,migration,and invasion of CRC cells,and its mechanism may be achieved by regulating the miR-299-5p/KDM4B signaling axis.