Objective: To understand the allocation and use of safety seats for preschool children and explore its related factors, so as to provide a scientific reference for promoting the usage of safety seats. Methods: A stratified random cluster sampling method was used to select 3 143 parents of preschool children aged 3 to 6 from six kindergartens in Shunyi District, Beijing from January 3 to 10, 2022. An online questionnaire survey was conducted to collect and evaluate the equipment and use of child safety seats in different characteristics of preschool children, as well as their scores of health beliefs. Multiple factor Logistic regression analysis was used to investigated the related factors of safety seat configuration and use. Results: The equipping rate and usage rate of safety seats for preschool children were 66.56% and 58.45%, respectively. The proportion of equipped and used safety seats for preschool children in core families (69.52%, 62.23%) were higher than that in large families (64.35%, 55.62%), only child families ( 72.39 %, 64.87%) were higher than non only child families (61.49%, 52.86%), and urban families (71.63%, 63.04%) were higher than rural families (52.31%, 45.51%) ( χ 2=9.23, 13.86; 41.72, 46.44; 101.96 ,76.97,all P <0.05) . As the educational level of parents ( χ 2 trend =154.23,98.76) and annual income of the family ( χ 2 trend =155.78,127.69) rised, the reporting rates of the equipped and used child safety seats in the family also increased(all P <0.05 ). There were statistically significant differences in the scores of different dimensions of health beliefs for the provision ( t =-20.22-18.16) and use ( t =24.32-24.17) of safety seats for preschool children(all P <0.05). After adjusting for child sex, child age, family annual income, parental education level, family type, whether the child was an only child, and place of residence，multivariate Logistic regression analysis showed that preschool children with higher perceived susceptibility score( OR =1.11, 1.08), higher self efficacy score( OR =1.23, 1.33), and higher suggestive factors score( OR =1.08, 1.12) were more likely to have and use safety seats in their families, while preschool children with higher perceived impairments score( OR =0.82, 0.80) were less likely to have and use safety seats in their families (all P <0.05). Conclusions The installation rate of child safety seats needs to be improved, and there is also a certain gap in their use after installation. Parents of preschool children should improve susceptibility and self efficacy to safety seat equipment and use, and perceptual barriers should be reduced.

Objective: To understand the current status and related factors of oral health behavior in preschool children, so as to provide scientific basis for improving parents oral health care abilities. Methods: From March 5 to 12, 2024, using a stratified cluster sampling method, an online questionnaire survey was conducted among parents of 1 381 preschool children aged 3-6 from 6 selected kindergartens of a district in Beijing. A structural equation model (SEM) was constructed based on the Theory of Planned Behavior framework to analyze the factors associated with preschool children s oral health behaviors. Results: The rates of parental assistance in brushing teeth, regular oral examination, and postprandial rinsing were 44.4%, 18.6% and 23.6%, respectively. Attitude, subjective norms were positively correlated with oral health behavior intention ( r =0.61, 0.55); attitude, perceived behavioral control, and behavioral intention were positively correlated with oral health behavior ( r =0.14, 0.13, 0.16) (all P < 0.01 ). The results of the SEM showed that attitude and subjective norms had a significant direct effect on oral health behavior intention ( β = 0.42 , 0.40), and the direct effect of perceived behavioral control on oral health behavior was statistically significant ( β =0.42) (all P <0.01). Conclusions The overall level of oral health behavior among preschool children needs to be improved. Perceived behavioral control is the most direct positive related factor of oral health behavior. In the future, intervention measures should focus on perceived behavioral control as the entry point and provide systematic intervention guidance in combination with planned behavior theory.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

BACKGROUND:Ilizarov bone transport is very effective in the treatment of open large tibial bone defects,but there are still complications,among which the difficulty of junction healing is one of the difficult points in treatment. OBJECTIVE:To investigate the effect of Ilizarov bone transport combined with antibiotic bone cement on junction healing after operation of open large tibial bone defect. METHODS:Totally 51 patients with open large tibial bone defect(bone defect>4 cm)admitted to Binzhou Medical University Hospital from August 2010 to January 2022 were selected,of which 28 received Ilizarov bone transport alone(control group)and 23 received Ilizarov bone transport combined with antibiotic bone cement treatment(trial group).External fixation time,bone healing time,bone healing index,visual analog scale score during bone removal,bone defect limb function,junction healing and complications at the final follow-up were statistically compared between the two groups. RESULTS AND CONCLUSION:(1)All the 51 patients were followed up for a mean of(22.53±5.77)months.External fixation time,bone healing time,bone healing index,postoperative infection rate,and non-healing rate of junction were less in the trial group than those in the control group(P<0.05).There was no significant difference between the two groups in visual analog scale scores at 6 months after the second surgery and in the functional excellence and good rate of limb with bone defect at the final follow-up(P>0.05).(2)These findings indicate that compared with the Ilizarov bone transport alone,Ilizarov bone transport combined with antibiotic bone cement treatment can promote the healing of open tibial fracture junction and increase the rate of bone healing.

OBJECTIVES: Renal cell carcinoma (RCC) is a malignant renal tumor that poses a significant threat to patient health. Accurate preoperative pathological grading plays a crucial role in determining the appropriate treatment for this disease. Currently, deep learning technology has become an important method for pathological grading of RCC. However, existing methods primarily rely on single-phase computed tomography (CT) imaging for analysis and prediction, which has limitations such as missing small lesions, one-sided evaluation, and local focusing issues. Therefore, this study proposes a multi-modal deep learning algorithm that integrates multi-phase enhanced CT images with clinical variable data, aiming to provide a basis for predicting the pathological grading of RCC. METHODS: First, the algorithm took four-phase enhanced CT images from the plain scan, arterial phase, venous phase, and delayed phase, along with clinical variables, as inputs. Then, an embedding encoding module was used to extract heterogeneous information from the clinical variables, and a 3-dimensional (3D) ResNet50 model was employed to capture spatial information from the multi-phase enhanced CT image data. Finally, a Fusion module deeply integrated the feature information from clinical variables and each phase's CT image features, further utilizing a cross-self-attention mechanism to achieve multi-phase feature fusion. This approach comprehensively captures the deep semantic information from the patient data, fully leveraging the complementary advantages of multi-modal and multi-phase data. To validate the effectiveness of the proposed method, a total of 1 229 RCC patients were approved by ethics review were included to train the model. RESULTS: Experimental results demonstrated superior performance compared to traditional radiomics and state-of-the-art deep learning methods, achieving an accuracy of 83.87%, a recall rate of 95.04%, and an F1-score of 82.23%. CONCLUSIONS The proposed algorithm exhibits strong stability and sensitivity, significantly enhancing the predictive performance of RCC pathological grading. It offers a novel approach for accurate RCC diagnosis and personalized treatment planning.
Humans ; Carcinoma, Renal Cell/pathology* ; Deep Learning ; Kidney Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed/methods* ; Algorithms ; Neoplasm Grading ; Male ; Female ; Middle Aged

Osteosarcoma is a highly aggressive malignant bone tumor whose immuno evasion mechanisms play a pivotal role in tumor progression and therapeutic resistance. Recent studies have identified mitochondrial transfer as a novel mode of intercellular communication that significantly influences metabolic reprogramming and immune evasion in osteosarcoma cells. This mechanism operates through three principal pathways: (1) enhancing energy metabolic efficiency in tumor cells; (2) mitigating intracellular oxidative stress; and (3) modulating immune checkpoint molecule expression. Collectively, these alterations impair host immune surveillance while promoting tumor proliferation, invasion, and distant metastasis through metabolic remodeling, immune tolerance induction, and tumor microenvironment reconstruction. This review systematically elucidates the molecular mechanisms by which mitochondrial transfer regulates immune evasion in osteosarcoma and its dynamic impact on the tumor microenvironment. Furthermore, we discuss the translational potential of targeting this pathway for precision therapy and outline future research directions in this emerging field.

Mental state is an important part of the normal life activities of the human body, and it is also the most external expression and the most easily obtained information of the physical condition. The normal activities of the mind depend on the normal operation of the viscera, qi, and blood, and are a unified whole that prospers together and suffers together. The theory of the five-spirit-viscera in the Yellow Emperor’s Inner Classic revealed that the normal mental activities of the human body were dominated by the five internal organs, that is, the five internal organs were the body and the five spirits were the function. And it highlighted the viewpoint that the five internal organs store the spirits and are actually one. The heart governs the spirit and belongs to the four internal organs. On this basis, Synopsis of Golden Chamber used the internal organs to diagnose and treat mental diseases, integrating the theory of the five spirits into it, forming a unique method of diagnosis and treatment with the heart as the leading factor and regulating the qi and blood of the four internal organs. It identified the pathogenesis of diseases such as pathogenic crying, lily disease, and hysteria from five levels: heart deficiency and weak qi, heart-lung disharmony, heart-liver disharmony, the heart of the loss of the spleen nourishment, and disharmony between heart and kidney. The treatment was mainly to replenish the deficiency of the viscera and eliminate the pathogens, reflecting the characteristics of regulating the mind and calming the four internal organs. This unique view on diagnosis and treatment has profoundly influenced the diagnosis and treatment theories of mental illnesses by later doctors, and is of great significance to the current clinical treatment of such illnesses.

Objective To analyze the effect of Hsa-circ-0101216 on gemcitabine(GEM)chemotherapy resistance in pancreatic cancer and its mechanism.Methods Differentially expressed circRNAs between GEM-resistant pancreatic cancer cells and parent cells were screened using the GEO database.Pancreatic cancer GEM resistant cell lines(BxPC-3-GEM and Capan-1-GEM)were constructed by intermittent concentration gradient method.qRT-PCR was used to detect the expression of Hsa-circ-0101216 in cells.GEM resistant pancreatic cancer cell lines were taken and divided into sh-circ-0101216 group(knockdown of circ-0101216),sh-NC group(transfected with sh-NC),and blank control group(untreated).CCK-8 assay and EdU proliferation assay were used to detect the half inhibitory concentration(IC50)of GEM and proliferation ability of cells in each group.Western blotting was performed to detect the expression of multidrug resistance-related protein 1(MRP1),breast cancer resistance protein(BCRP),and human equilibrative nucleoside transporter-1(hENT-1).A subcutaneous xenograft tumor model of human pancreatic cancer in nude mice was constructed,and sh-NC+GEM group and sh-circ-0101216+GEM group(n=6)were set up.The volume and weight of xenograft tumor in nude mice were compared between the two groups.Western blotting and immunohistochemistry were used to detect the expression of MRP1,BCRP,and hENT-1 proteins in xenograft tumor tissues,and EDU proliferation assay was used to detect the proliferation ability of tumor cells.Results The GEO database screening showed that Hsa-circ-0101216 was up-regulated in GEM-resistant pancreatic cancer cell lines.Pancreatic cancer GEM-resistant cell lines were successfully constructed,and the expression levels of Hsa-circ-0101216 and the IC50 value in GEM-resistant pancreatic cancer cells BxPC-3-GEM and Capan-1-GEM were significantly higher than those in parental cells(P<0.05).In sh-circ-0101216 group,the IC50 values of GEM,cell viability,EdU positivity rate,and the expression levels of MRP1 and BCRP proteins in GEM-resistant pancreatic cancer cells BxPC-3-GEM and Capan-1-GEM were significantly lower than those in blank control group and sh-NC group,while the expression level of hENT-1 protein was significantly higher(P<0.05 or P<0.001).In sh-circ-0101216+GEM group,the weight and volume of subcutaneous xenograft tumors in nude mice,the expression levels and positive expression rates of MRP1 and BCRP proteins in tumor tissues,and the EdU positive rate were significantly lower than those in sh-NC+GEM group,while the expression level and positive expression rate of hENT-1 protein were significantly higher(P<0.05).Conclusions Hsa-circ-0101216 is highly expressed in GEM-resistant pancreatic cancer cell lines.Its knockdown can inhibit the proliferation of pancreatic cancer cells and enhance the chemosensitivity of pancreatic cancer cells to GEM.The mechanism may be related to the regulation of transmembrane transporter protein expression.

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.