BACKGROUND:There is still no consensus on the optimal internal fixation for the treatment of Pauwels Ⅲ femoral neck fracture,and most of the related finite element analyses have been performed using a single simplified loading condition,and the biomechanical properties of commonly used internal fixation devices need to be further investigated. OBJECTIVE:To analyze the biomechanical characteristics of Pauwels Ⅲ femoral neck fractures treated with cannulated compression screw,dynamic hip screw,and femoral neck system by finite element method under different loading conditions of single-leg standing loads and sideways fall loads. METHODS:The DICOM data of healthy adult femur were obtained by CT scanning,imported into Mimics 15.0 software to obtain the rough model of bone tissue.The data exported from Mimics were optimized by Geomagics software,and then three internal fixation models were built and assembled with the femur model according to the parameters of the clinical application of the cannulated compression screw,dynamic hip screw,and femoral neck system by using Pro/E software.Finally,the three internal fixation models were imported into Ansys software for loading and calculation to analyze the stress distribution and displacement of the femur and the internal fixation under different working conditions of single-leg standing loads and sideways fall loads,as well as the stress characteristics of the calcar femorale and Ward's triangle. RESULTS AND CONCLUSION:(1)Under the single-leg standing load and the sideways fall load,the proximal femoral stress of the three internal fixation models was mainly distributed above the fracture end of the femoral neck.The peak stress of the proximal femoral end,fracture end,Ward triangle,and calcar femorale of the three internal fixation models were the smallest in the femoral neck system model and the largest in the cannulated compression screw model.(2)Under the single-leg standing load and the sideways fall load,the peak displacement of the proximal femur of the three internal fixation models was all located at the top of the femoral head,and the peak displacement was the smallest in the femoral neck system model and the largest in the cannulated compression screw model.(3)The peak displacement of the three internal fixation models was all located at the top of the internal fixation device under the single-leg standing and sideways fall loading conditions,and the peak displacement values were the smallest in the femoral neck system internal fixation model and the largest in the cannulated compression screw internal fixation model.(4)The internal fixation stress of the three internal fixation models was mainly distributed in the area near the fracture end of the internal fixation device under the single-leg standing and sideways fall loads,and the peak value of internal fixation stress was the smallest in the femoral neck system model and the largest in the cannulated compression screw model.(5)These results suggest that the mechanical stability of the femoral neck system is the best,but there may be a risk of stress shielding of the fracture end and calcar femorale.The stress of the internal fixation device of the femoral neck system is more dispersed,and the risk of internal fixation break is lower.

BACKGROUND: P16 inactivation is frequently accompanied by telomerase reverse transcriptase ( TERT ) amplification in human cancer genomes. P16 inactivation by DNA methylation often occurs automatically during immortalization of normal cells by TERT . However, direct evidence remains to be obtained to support the causal effect of epigenetic changes, such as P16 methylation, on cancer development. This study aimed to provide experimental evidence that P16 methylation directly drives cancer development. METHODS: A zinc finger protein-based P16 -specific DNA methyltransferase (P16-Dnmt) vector containing a "Tet-On" switch was used to induce extensive methylation of P16 CpG islands in normal human fibroblast CCD-18Co cells. Battery assays were used to evaluate cell immortalization and transformation throughout their lifespan. Cell subcloning and DNA barcoding were used to track the diversity of cell evolution. RESULTS: Leaking P16-Dnmt expression (without doxycycline-induction) could specifically inactivate P16 expression by DNA methylation. P16 methylation only promoted proliferation and prolonged lifespan but did not induce immortalization of CCD-18Co cells. Notably, cell immortalization, loss of contact inhibition, and anchorage-independent growth were always prevalent in P16-Dnmt&TERT cells, indicating cell transformation. In contrast, almost all TERT cells died in the replicative crisis. Only a few TERT cells recovered from the crisis, in which spontaneous P16 inactivation by DNA methylation occurred. Furthermore, the subclone formation capacity of P16-Dnmt&TERT cells was two-fold that of TERT cells. DNA barcoding analysis showed that the diversity of the P16-Dnmt&TERT cell population was much greater than that of the TERT cell population. CONCLUSION P16 methylation drives TERT -mediated immortalization and transformation of normal human cells that may contribute to cancer development.
Humans ; Telomerase/genetics* ; DNA Methylation/physiology* ; Fibroblasts/cytology* ; Cyclin-Dependent Kinase Inhibitor p16/metabolism* ; Cell Line ; Cell Transformation, Neoplastic/genetics*

OBJECTIVE To analyze pathogens of multiple drug-resistant organism(MDRO)infection and its risk factors during the recovery period of patients with traumatic brain injury,and to construct and validate the predic-tion model for MDRO lung infection.METHODS Patients who were admitted to the Shanxi Second People's Hos-pital for traumatic brain injury(TBI)and developed hospital-acquired pneumonia(HAP)during their hospitaliza-tion between Aug.2019 and Aug.2023 were selected as the study subjects,their clinical data were retrospectively collected,and the patients were randomly divided into a modeling group(n=270)and a verification group(n=90)at a ratio of 3∶1,and they were further categorized into the MDRO infection group(148 cases)and the non-infection group(122 cases)based on whether they developed pneumonia caused by MDRO infections.Clinical data of the patients were collected for analysis,with pathogen identification performed for all patients.The risk factors for MDRO infection in TBI patients with HAP were analyzed by multivariate Logistic regression analysis,a pre-diction model for MDRO infections during the hospitalization and recovery period of TBI patients with HAP was constructed using a formula-based method,the goodness-of-fit of the model was assessed using Hosmer-Leme-show test,and its predictive ability was evaluated using receiver operating characteristic(ROC)curves.RESULTS There was no significant differences in the baseline characteristics of TBI patients with HAP between the modeling group and the verification group.The incidence of MDRO infections among TBI patients with HAP in modeling group was 54.81％(148/270),with Klebsiella pneumoniae(25.27％)being the predominant pathogen.Mechan-ical ventilation duration(OR=5.789,95％CI:2.164-15.486,P=0.001),ICU length of stay(OR=5.441,95％CI:2.153-13.751,P＜0.001),combined kidney diseases(OR=2.770,95％CI:1.321-5.812,P=0.007),duration of antibiotics use(OR=7.486,95％CI:1.928-29.059,P=0.004),occurrence of impaired consciousness(OR=5.720,95％CI:2.586-12.652,P＜0.001)and use of aminoglycoside antibiotics(OR=3.861,95％CI:1.608-9.273,P=0.003)were risk factors for MDRO infections.The Hosmer-Lemeshow for the risk prediction model showed that x2=5.013 and P=0.496.ROC curves analysis showed The area under the curve(AUC)for the modeling group by ROC curve analysis was 0.80(95％CI:0.773-0.877),with a sensitivi-ty of 83.33％and a specificity of 73.60％respectively,and the AUC for the verification group were 0.800(95％CI:0.670-0.895),with a sensitivity of 81.82％and a specificity of 77.27％respectively.CONCLUSION The prediction model constructed in this study,based on the risk factors for MDRO infection pneumonia during the re-covery period in hospitalized patients with traumatic brain injury,demonstrated high goodness-of-fit,as well as satisfactory sensitivity and specificity,and its application in clinical practice may help identify patients at high risk of MDRO infections.

OBJECTIVE To analyze pathogens of multiple drug-resistant organism(MDRO)infection and its risk factors during the recovery period of patients with traumatic brain injury,and to construct and validate the predic-tion model for MDRO lung infection.METHODS Patients who were admitted to the Shanxi Second People's Hos-pital for traumatic brain injury(TBI)and developed hospital-acquired pneumonia(HAP)during their hospitaliza-tion between Aug.2019 and Aug.2023 were selected as the study subjects,their clinical data were retrospectively collected,and the patients were randomly divided into a modeling group(n=270)and a verification group(n=90)at a ratio of 3∶1,and they were further categorized into the MDRO infection group(148 cases)and the non-infection group(122 cases)based on whether they developed pneumonia caused by MDRO infections.Clinical data of the patients were collected for analysis,with pathogen identification performed for all patients.The risk factors for MDRO infection in TBI patients with HAP were analyzed by multivariate Logistic regression analysis,a pre-diction model for MDRO infections during the hospitalization and recovery period of TBI patients with HAP was constructed using a formula-based method,the goodness-of-fit of the model was assessed using Hosmer-Leme-show test,and its predictive ability was evaluated using receiver operating characteristic(ROC)curves.RESULTS There was no significant differences in the baseline characteristics of TBI patients with HAP between the modeling group and the verification group.The incidence of MDRO infections among TBI patients with HAP in modeling group was 54.81％(148/270),with Klebsiella pneumoniae(25.27％)being the predominant pathogen.Mechan-ical ventilation duration(OR=5.789,95％CI:2.164-15.486,P=0.001),ICU length of stay(OR=5.441,95％CI:2.153-13.751,P＜0.001),combined kidney diseases(OR=2.770,95％CI:1.321-5.812,P=0.007),duration of antibiotics use(OR=7.486,95％CI:1.928-29.059,P=0.004),occurrence of impaired consciousness(OR=5.720,95％CI:2.586-12.652,P＜0.001)and use of aminoglycoside antibiotics(OR=3.861,95％CI:1.608-9.273,P=0.003)were risk factors for MDRO infections.The Hosmer-Lemeshow for the risk prediction model showed that x2=5.013 and P=0.496.ROC curves analysis showed The area under the curve(AUC)for the modeling group by ROC curve analysis was 0.80(95％CI:0.773-0.877),with a sensitivi-ty of 83.33％and a specificity of 73.60％respectively,and the AUC for the verification group were 0.800(95％CI:0.670-0.895),with a sensitivity of 81.82％and a specificity of 77.27％respectively.CONCLUSION The prediction model constructed in this study,based on the risk factors for MDRO infection pneumonia during the re-covery period in hospitalized patients with traumatic brain injury,demonstrated high goodness-of-fit,as well as satisfactory sensitivity and specificity,and its application in clinical practice may help identify patients at high risk of MDRO infections.

Objective:To describe the distribution of fat-free mass (FFM) and fat-free mass index (FFMI) in children aged 3-17 years in China.Methods:Data were collected from National Nutrition and Health Systematic Survey in 0-18 years old children in China. By using multi-stage stratified randomized cluster sampling method, the project was conducted in 28 survey points in urban and rural areas in 14 provinces (autonomous regions and municipalities) in 7 regions in China from 2019 to 2021. FFM was measured using bioelectrical impedance meter. Finally, the body composition data of 70 853 children were included in the analysis. M ( Q1, Q3) was used to describe the gender and age specific FFM and FFMI of the children in different regions. Kruskal-Wallis H rank sum test was used to compare FFM and FFMI of boys and girls in same age group, boys in different age groups, girls in different age groups, as well as boys in same age group and girls in same age group in different regions. DSCF method was used for pairwise comparisons. Results:After the age of 11 years, the difference of FFMI between boys and girls increased year by year. The FFMI was 14.2 kg/m 2 in boys and 13.8 kg/m 2 in girls at 11 years old, the difference was significant ( χ2=135.86, P<0.001). The difference of FFMI between boys and girls exceed 1.0 kg/m 2 from 12 years old, and FFMI was 15.3 kg/m 2 in boys and 14.2 kg/m 2 in girls at 12 year old, the difference was significant ( χ2=597.27, P<0.001). The FFMI was 17.5 kg/m 2 in boys and 14.7 kg/m 2 in girls at 16 years old, the difference was significant ( χ2=2 543.60, P<0.001). The FFMI was higher in boys in northeast China, while the FFMI was lower in both boys and girls in northwest China. Conclusions:Gender specific difference was observed in the increase of FFMI with age. The FFMI was significantly higher in boys than in girls after 11 years old. It is necessary to pay attention to the problem of FFM in children in northeastern and northwestern China.

Objective:To investigate the distribution characteristics of body height, body weight and body mass index (BMI) in children aged 3-17 years in China.Methods:Data were obtained from the National Nutrition and Health Systematic Survey in 0-18 years old children in China. The study selected 70 853 children aged 3-17 years from 28 urban and rural survey sites in 14 provinces (autonomous regions and municipalities) in 7 regions of China with multi-stage stratified cluster random sampling. M ( Q1, Q3) was used to describe the region, age and gender specific body height, body weight and BMI in the children aged 3-17 years. Wilcoxon rank sum test was used to compare the body height, body weight, and BMI between boys and girls in same age group. Kruskal-Wallis H rank sum test was used to compare the body height, body weight and BMI among boys in different age groups and among girls in different age groups, as well as among boys in same age group and among girls in same age group from different regions, and DSCF method was used for further pairwise comparisons. Results:In this study, the median body height and body weight were 172.0 cm and 62.9 kg in 17-year-old boys and 160.0 cm and 53.7 kg in 17-year-old girls. The median for children's body height, body weight, and BMI in most age groups were higher in northeastern and northern China than in southern China, and the differences could be observed until age 17 years. The differences in body weight and BMI in children in northeastern and northern China were greater in Q3 than in Q1 compared with southern China. Conclusions:The body height of children aged 3-17 years continues to increase in China. Northeastern and northern China have more children with higher bodyweight, showing an obvious body weight increase trend, to which close attention needs to be paid.

Objective:To describe the distribution of fat mass (FM), fat mass percentage (FMP), and fat mass index (FMI) in children aged 3-17 years in China.Methods:Data of this study were from the National Nutrition and Health Systematic Survey in 0-18 years old children in China. A total of 70 853 children aged 3-17 years old selected from seven regions of China were included in this analysis. Body composition were measured by using bioelectrical impedance meter. The region, gender and age specific FM, FMP and FMI of the subjects were described by using M ( Q1, Q3). Kruskal-Wallis H rank sum test was used for the comparison of intergroup differences. DSCF method was used for pairwise comparisons. Results:The medians of FM, FMP and FMI were 3.0 kg, 18.3% and 2.9 kg/m 2 in boys aged 3 years and 2.9 kg, 19.0% and 2.9 kg/m 2 in girls aged 3 years, respectively. The FM increased with age and the FMP and FMI decreased with age in both boys and girls aged 3-5 years. After 11 years old, the FM, FMP and FMI decreased first and then increased in boys. From 6-17 years old, the FM, FMP and FMI increased gradually in girls. The FM, FMP and FMI were higher in girls than in boys after 12 years old (all P<0.05). The FM, FMP and FMI were relatively higher in children at the age of 6-14 in northeastern and northern China than in other regions. Conclusions:The age specific FM, FMP and FMI had different changing characteristics in boys and girls aged 3-17 years in seven regions of China. The FM, FMP and FMI also differed with region.

Objective:To analyze the relationship between body mass index (BMI) and fat mass percentage (FMP) in children aged 3-17 years in China.Methods:The BMI and FMP data of children aged 3-17 years from the National Nutrition and Health Systematic Survey in 0-18 years old children in China was analyzed. BMI- Z score/BMI and FMP were used to classify the subjects, respectively. Spearman correlation was used to analyze the correlation between BMI and FMP. The consistency between BMI- Z score/BMI and FMP in classifying the subjects was measured using Kappa coefficient. Results:The FMP of malnutrition, normal and overweight/obesity in boys was higher in age group 10-13-year than in other age groups (all P<0.001). The FMP of all nutritional status in girls increased with age (all P<0.05). The BMI of boys in all the FMP levels increased with age (all P<0.05). When the FMP of girls was 25%- or ≥30%, BMI increased with age (all P<0.001). The relationship between BMI and FMP was strong ( r=0.705, P<0.001), with r of 0.618 in boys and 0.884 in girls. The consistency between BMI- Z score/BMI and FMP in classifying the subjects was found to be moderate (Kappa=0.574, P<0.001). Conclusions:There was a strong relationship between BMI and FMP. The consistency between BMI- Z score/BMI and FMP in classifying the subjects was moderate.

Objective:To evaluate the consistency between bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) in the measurement of body composition in children aged 6-17 years in China.Methods:Fat-free mass, fat mass and fat mass percentage were measured by both BIA and DXA in 1 161 children. t-test or Wilcoxon paired test was used to evaluate the different outcome of the two methods. The correlation and consistency between the methods were evaluated by Spearman correlation coefficients ( r) and Bland-Altman analysis. Results:Body compositions measured by BIA was positively correlated with those measured by DXA (fat mass r=0.95, fat-free mass r=0.98, fat mass percentage r=0.86, all P<0.05). Comparing with DXA, BIA underestimate children's fat mass [the mean difference is -3.15 kg, and the SD is 2.35 kg, 95% limits of agreement (LoA): -7.74-1.45 kg] and fat mass percentage (the mean difference is -8.45%, and the SD is 4.63%, 95% LoA: -17.53%-0.64%). Conclusions:Body compositions measured by BIA was highly positively correlated with those measured by DXA. BIA has certain application value in the measurement of body fat mass and fat-free mass of children aged 6-17 years.