OBJECTIVES: This study investigates independent risk factors for postoperative internal fixation device infection in patients with maxillofacial fractures and proposes an early warning model based on the synthetic minority over-sampling technique (SMOTE) algorithm. METHODS: A total of 1 104 patients who underwent surgical treatment for maxillofacial fractures at Oral and Maxillofacial Surgery Department, Affiliated Hospital of Nantong University from January 2021 to December 2024 were retrospectively analyzed. The patients were divided into two groups based on the presence of postoperative internal fixation device infection: the infection group (27 cases) and non-infection group (1 077 cases). Clinical data from both groups were collected and subjected to statistical analysis. Univariate and binary Logistic regression analysis were used to identify risk factors for postoperative internal fixation device infection in maxillofacial fractures. Subsequently, a Logistic regression model was established, and the dataset was improved based on the SMOTE algorithm to construct an early warning model with the improved dataset. The prediction performance of the models was compared and validated. RESULTS: Among the 1 104 patients who underwent surgical treatment for maxillofacial fractures, 27 cases of postoperative internal fixation device infections were identified, corresponding to an infection rate of 2.45% (27/1 104). Age, diabetes history, fracture severity, and oral hygiene status were all identified as risk factors for postoperative internal fixation device infections in maxillofacial fractures (all P<0.05). The prediction model based on the original data (P1). The prediction model based on the SMOTE algorithm (P2). Receiver operating characteristic (ROC) curve analysis shows that the area under curve (AUC) for the P2 model was 0.882, the P1 model was 0.861, indicating the superior predictive performance of the P2 model. The DeLong test results show that the difference in AUC between the two models was statistically significant (P<0.05). CONCLUSIONS Age, diabetes history, postoperative fracture severity, and oral hygiene status are all risk factors for infections associated with internal fixation devices after maxillofacial fracture surgery. The proposed early warning model demonstrated good predictive performance. Medical professionals can utilize this model to effectively intervene and anticipate infections related to internal fixation devices after maxillofacial fracture surgery.
Humans ; Algorithms ; Retrospective Studies ; Male ; Female ; Fracture Fixation, Internal/instrumentation* ; Risk Factors ; Middle Aged ; Adult ; Logistic Models ; Surgical Wound Infection/epidemiology* ; Aged ; Internal Fixators/adverse effects* ; Maxillofacial Injuries/surgery* ; Adolescent

Psoriasis is an incurable chronic inflammatory disease that requires new interventions. Here, we found that fibroblasts exacerbate psoriasis progression by promoting macrophage recruitment via CCL2 secretion by single-cell multi-omics analysis. The natural small molecule celastrol was screened to interfere with the secretion of CCL2 by fibroblasts and improve the psoriasis-like symptoms in both murine and cynomolgus monkey models. Mechanistically, celastrol directly bound to the low-density lipoprotein receptor-related protein 1 (LRP1) β-chain and abolished its binding to the transcription factor c-Jun in the nucleus, which in turn inhibited CCL2 production by skin fibroblasts, blocked fibroblast-macrophage crosstalk, and ameliorated psoriasis progression. Notably, fibroblast-specific LRP1 knockout mice exhibited a significant reduction in psoriasis like inflammation. Taken together, from clinical samples and combined with various mouse models, we revealed the pathogenesis of psoriasis from the perspective of fibroblast-macrophage crosstalk, and provided a foundation for LRP1 as a novel potential target for psoriasis treatment.

Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

Objective:To investigate the prevalence and risk factors of overweight and obesity among Chinese children aged 3-18 years from 11 provinces, antonomous regions, or municipalities.Methods:This national cross-sectional community health survey utilized a multistage stratified cluster-random sampling method to recruit 193 997 nationally representative participants from 11 provinces, autonomous regions, or municipalities between January 2017 and December 2019. All participants underwent physical examinations, and their caregivers completed questionnaires assessing participants′ dietary, lifestyle, familial, and perinatal information. Multilevel multinomial logistic regression models were employed to identify the potential risk factors.Results:The cohort comprised 193 997 children (102 178 boys, 91 819 girls),aged (10±4) years. Overall prevalence rates were 30 574(15.8%)overweight children and 17 217(8.9%) obesity children. Boys exhibited higher overweight and obesity rates than girls (17.0% (17 368/102 178) vs. 14.4% (13 206/102 178), 11.3% (11 553/91 819) vs. 6.2% (5 664/91 819), χ2=249.12,1 578.69,both P<0.001). The detection rates of obesity in Tanner stage 2 and 3 were the highest in boys and girls, with 13.4%(2 231/16 665) and 8.6%(880/10 221) respectively. Risk factors for obesity included parental overweight (paternal OR=2.34 and maternal OR=2.29), annual household income of 100 000-200 000 yuan (compared with<100 000 yuan, OR=1.04), higher paternal education (compared with below high school,high school and a college education OR=1.09,1.14), birth weight >4.0 kg (≤5 and>5 years old OR=1.74, 1.44,respectively), and western food consumption≥1 time/month (compared with<1, 1-2, 3-4,>4 times/month OR=1.36, 1.30, 1.67(≤5 years), 1.19, 1.16, 1.15 (>5 years), respectively) (all P<0.05). Conversely, coarse grain intake≥1 times/week (compared with<1 times/week, every day, 3-4, 1-2 times/week OR=0.74, 0.80, 0.71 (≤5 years), 0.75, 0.87, 0.90(>5 years), respectively, all P<0.05) was associated with reduced obesity risk. Conclusions:Obesity epidemiology in children demonstrates significant heterogeneity across age, gender, geographic regions, and pubertal stages. It is necessary to establish a personalized prevention and control strategy.

Objective:To investigate the changes of the epidemiology and clinical characteristics of human metapneumovirus (hMPV) among children with acute lower respiratory tract infection (ALRTI) before and after the discontinuation of non-pharmaceutical interventions (NPI) during coronavirus disease 2019 epidemic.Methods:This was a retrospective cohort study. Children hospitalized at The Second Affiliated Hospital and Yuying Children′s Hospital of Wenzhou Medical University between January 2021 and December 2023, who were diagnosed with ALRTI by nasopharyngeal secretion testing for respiratory pathogens nucleic acid were enrolled. Clinical and laboratory data were collected. Children admitted between January 1, 2021 and January 7, 2023 were classified as the pre-NPI withdrawal group (abbreviated as pre-withdrawal group), while those admitted from January 8, 2023 afterward were classified as the post-NPI withdrawal group (abbreviated as post-withdrawal group). Nasopharyngeal secretions from the enrolled children were tested for 13 respiratory pathogens using polymerase chain reaction-capillary electrophoresis fragment analysis, and bacterial cultures were also performed. Statistical analyses were performed using the Mann-Whitney U test or chi-square test. Results:A total of 30 855 ALRTI cases were enrolled, with 1 679 of hMPV-positive. In the pre-withdrawal group, there were 861 cases with an age of onset of 2.0(1.0, 3.0) years, and the highest proportion was in the 1 to <3 years age group, accounting for 35.3%(304/861). In the post-withdrawal group, there were 818 cases with an age of onset of 3.0(2.0, 4.0) years, and the highest proportion was in the 3 to <5 years age group, accounting for 39.2%(321/818).The age of onset in the post-withdrawal group was significantly older than that in the pre-withdrawal group ( Z=7.69, P<0.001) .The hMPV detection rate was higher in the pre-withdrawal group than that in post-withdrawal group (5.75%(861/14 984) vs 5.15%(818/15 871); χ2=5.25, P=0.022). In the pre-withdrawal group, the epidemic peaks occurred in winter and spring, with the highest rates in January 2022(25.2%(224/890)) and March 2022 (21.6%(186/860)). In the post-withdrawal group, the epidemic peak shifted to spring and summer, and the detection rate became increased since April 2023(10.8%(136/1 258)). The post-withdrawal group showed lower rates of wheezing, shortness of breath, cyanosis, respiratory support, severe pneumonia, intensive care unit admission, and shorter hospital stays compared to the pre-withdrawal group ( χ2=69.09, 31.63, 12.97, 57.96, 55.73, 5.48 and Z=7.11, respectively, all P< 0.05).In the pre-withdrawal group, 412 cases (47.9%(412/861)) had other pathogens detected, compared to 445 cases (54.4%(445/181)) in the post-withdrawal group, indicating a significantly higher rate of co-infections in the post-withdrawal group ( χ2=7.20, P<0.05). The most commonly detected pathogens in both groups were Mycoplasma pneumoniae (MP), rhinovirus, and Streptococcus pneumoniae. However, the post-withdrawal group showed significantly higher detection rates of MP and influenza virus, but lower bacterial detection rates compared to the pre-withdrawal group ( χ2=39.41, 9.70, 5.63, respectively, all P<0.05). The detection rate of Haemophilus influenzae was 2.1%(17/818) in the post-withdrawal group which lower than that (6.7%(58/861)) in the pre-withdrawal group, and the difference was statistically significant ( χ2=21.32, P<0.001). Conclusions:In 2023, following the withdrawal of NPI, the epidemic peak of hMPV in Wenzhou area is delayed to spring and summer. The age of children with hMPV-associated ALRTI increases, with the majority being 3 to <5 years old. The overall severity of the disease decreases. However, the detection of mixed pathogens increases, with MP being the most common, while bacterial detection decreases.

Objective To explore the pathological features of bronchiolar adenoma(BA)and its specific high-resolution computed tomography(HRCT)signs,and to differentiate BA from minimally invasive adenocarcinoma(MIA)using a non-invasive preoperative method.Methods A total of 80 patients with BA and 130 patients with MIA were retrospectively selected,and the clinical information and HRCT features were compared.All cases were divided into development set and test set at a 7︰3 ratio.Logistic regression analysis was used to screen the independent predictors of MIA and construct a model.Results There were significant differences in age,lobe distribution,density,vacuole sign,tumor-related vessels number(TVN),and distance to pleura(DTP)between BA and MIA patients(P<0.05).Age,density,TVN,DTP and long diameter were identified as independent predictors of MIA.A model was constructed,with area under the curve(AUC)of 0.887 and 0.884 in the development and test sets,respectively.Conclusion The model based on HRCT morphological features of BA and MIA demonstrates superior diagnostic performance compared to individual CT morphological features.

Objective To explore the pathological features of bronchiolar adenoma(BA)and its specific high-resolution computed tomography(HRCT)signs,and to differentiate BA from minimally invasive adenocarcinoma(MIA)using a non-invasive preoperative method.Methods A total of 80 patients with BA and 130 patients with MIA were retrospectively selected,and the clinical information and HRCT features were compared.All cases were divided into development set and test set at a 7︰3 ratio.Logistic regression analysis was used to screen the independent predictors of MIA and construct a model.Results There were significant differences in age,lobe distribution,density,vacuole sign,tumor-related vessels number(TVN),and distance to pleura(DTP)between BA and MIA patients(P<0.05).Age,density,TVN,DTP and long diameter were identified as independent predictors of MIA.A model was constructed,with area under the curve(AUC)of 0.887 and 0.884 in the development and test sets,respectively.Conclusion The model based on HRCT morphological features of BA and MIA demonstrates superior diagnostic performance compared to individual CT morphological features.

Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

Objective:To investigate the prevalence and risk factors of overweight and obesity among Chinese children aged 3-18 years from 11 provinces, antonomous regions, or municipalities.Methods:This national cross-sectional community health survey utilized a multistage stratified cluster-random sampling method to recruit 193 997 nationally representative participants from 11 provinces, autonomous regions, or municipalities between January 2017 and December 2019. All participants underwent physical examinations, and their caregivers completed questionnaires assessing participants′ dietary, lifestyle, familial, and perinatal information. Multilevel multinomial logistic regression models were employed to identify the potential risk factors.Results:The cohort comprised 193 997 children (102 178 boys, 91 819 girls),aged (10±4) years. Overall prevalence rates were 30 574(15.8%)overweight children and 17 217(8.9%) obesity children. Boys exhibited higher overweight and obesity rates than girls (17.0% (17 368/102 178) vs. 14.4% (13 206/102 178), 11.3% (11 553/91 819) vs. 6.2% (5 664/91 819), χ2=249.12,1 578.69,both P<0.001). The detection rates of obesity in Tanner stage 2 and 3 were the highest in boys and girls, with 13.4%(2 231/16 665) and 8.6%(880/10 221) respectively. Risk factors for obesity included parental overweight (paternal OR=2.34 and maternal OR=2.29), annual household income of 100 000-200 000 yuan (compared with<100 000 yuan, OR=1.04), higher paternal education (compared with below high school,high school and a college education OR=1.09,1.14), birth weight >4.0 kg (≤5 and>5 years old OR=1.74, 1.44,respectively), and western food consumption≥1 time/month (compared with<1, 1-2, 3-4,>4 times/month OR=1.36, 1.30, 1.67(≤5 years), 1.19, 1.16, 1.15 (>5 years), respectively) (all P<0.05). Conversely, coarse grain intake≥1 times/week (compared with<1 times/week, every day, 3-4, 1-2 times/week OR=0.74, 0.80, 0.71 (≤5 years), 0.75, 0.87, 0.90(>5 years), respectively, all P<0.05) was associated with reduced obesity risk. Conclusions:Obesity epidemiology in children demonstrates significant heterogeneity across age, gender, geographic regions, and pubertal stages. It is necessary to establish a personalized prevention and control strategy.

Objective:To investigate the changes of the epidemiology and clinical characteristics of human metapneumovirus (hMPV) among children with acute lower respiratory tract infection (ALRTI) before and after the discontinuation of non-pharmaceutical interventions (NPI) during coronavirus disease 2019 epidemic.Methods:This was a retrospective cohort study. Children hospitalized at The Second Affiliated Hospital and Yuying Children′s Hospital of Wenzhou Medical University between January 2021 and December 2023, who were diagnosed with ALRTI by nasopharyngeal secretion testing for respiratory pathogens nucleic acid were enrolled. Clinical and laboratory data were collected. Children admitted between January 1, 2021 and January 7, 2023 were classified as the pre-NPI withdrawal group (abbreviated as pre-withdrawal group), while those admitted from January 8, 2023 afterward were classified as the post-NPI withdrawal group (abbreviated as post-withdrawal group). Nasopharyngeal secretions from the enrolled children were tested for 13 respiratory pathogens using polymerase chain reaction-capillary electrophoresis fragment analysis, and bacterial cultures were also performed. Statistical analyses were performed using the Mann-Whitney U test or chi-square test. Results:A total of 30 855 ALRTI cases were enrolled, with 1 679 of hMPV-positive. In the pre-withdrawal group, there were 861 cases with an age of onset of 2.0(1.0, 3.0) years, and the highest proportion was in the 1 to <3 years age group, accounting for 35.3%(304/861). In the post-withdrawal group, there were 818 cases with an age of onset of 3.0(2.0, 4.0) years, and the highest proportion was in the 3 to <5 years age group, accounting for 39.2%(321/818).The age of onset in the post-withdrawal group was significantly older than that in the pre-withdrawal group ( Z=7.69, P<0.001) .The hMPV detection rate was higher in the pre-withdrawal group than that in post-withdrawal group (5.75%(861/14 984) vs 5.15%(818/15 871); χ2=5.25, P=0.022). In the pre-withdrawal group, the epidemic peaks occurred in winter and spring, with the highest rates in January 2022(25.2%(224/890)) and March 2022 (21.6%(186/860)). In the post-withdrawal group, the epidemic peak shifted to spring and summer, and the detection rate became increased since April 2023(10.8%(136/1 258)). The post-withdrawal group showed lower rates of wheezing, shortness of breath, cyanosis, respiratory support, severe pneumonia, intensive care unit admission, and shorter hospital stays compared to the pre-withdrawal group ( χ2=69.09, 31.63, 12.97, 57.96, 55.73, 5.48 and Z=7.11, respectively, all P< 0.05).In the pre-withdrawal group, 412 cases (47.9%(412/861)) had other pathogens detected, compared to 445 cases (54.4%(445/181)) in the post-withdrawal group, indicating a significantly higher rate of co-infections in the post-withdrawal group ( χ2=7.20, P<0.05). The most commonly detected pathogens in both groups were Mycoplasma pneumoniae (MP), rhinovirus, and Streptococcus pneumoniae. However, the post-withdrawal group showed significantly higher detection rates of MP and influenza virus, but lower bacterial detection rates compared to the pre-withdrawal group ( χ2=39.41, 9.70, 5.63, respectively, all P<0.05). The detection rate of Haemophilus influenzae was 2.1%(17/818) in the post-withdrawal group which lower than that (6.7%(58/861)) in the pre-withdrawal group, and the difference was statistically significant ( χ2=21.32, P<0.001). Conclusions:In 2023, following the withdrawal of NPI, the epidemic peak of hMPV in Wenzhou area is delayed to spring and summer. The age of children with hMPV-associated ALRTI increases, with the majority being 3 to <5 years old. The overall severity of the disease decreases. However, the detection of mixed pathogens increases, with MP being the most common, while bacterial detection decreases.