Development and validation of a deep-learning model for the detection of non-displaced femoral neck fractures with anteroposterior and lateral hip radiographs.

Background: Hip fractures, including femoral neck fractures, are a significant cause of morbidity and mortality in the elderly population and are typically diagnosed using plain radiography. However, diagnosing non-displaced femoral neck fractures can be challenging due to their subtle appearance on hip radiographs. Previous deep-learning models have shown low accuracy in identifying these fractures on anteroposterior (AP) radiographs; however, no studies have used lateral radiographs. This study aimed to evaluate the potential of using deep-learning with both AP and lateral hip radiographs to automatically identify non-displaced femoral neck fractures. Methods: We conducted a retrospective analysis of patients with femoral neck fractures at The First Affiliated Hospital of Xiamen University. All the hip radiographs were reviewed, and cases of non-displaced femoral neck fractures were included in the study. Additionally, 439 participants with normal hip radiographs were also included in the study. A vision transformer (Vit) model was developed using 1,536 AP and lateral hip radiograph. The model's performance was compared to the performance of two groups of human observers: an expert group comprising orthopedic surgeons and radiologists, and a non-expert group, including emergency physicians and general practice doctors. We also carried out the external validation using two additional data sets to assess the generalizability of the model. Results: The Vit model showed exceptional performance in detecting non-displaced femoral neck fractures on paired AP and lateral hip radiographs, achieving a binary accuracy of 95.8% [95% confidence interval (CI): 94.9%, 96.8%] and an area under the curve (AUC) of 0.988. Compared to the human observers, the model had a higher accuracy of 96.7% (95% CI: 93.9%, 99.5%) on the paired AP and lateral hip radiographs, while the accuracy of the expert group was 90.5% (95% CI: 85.7%, 95.2%). Further, the model maintained good performance during the external validation, with an AUC of 0.959 on the paired AP and lateral views. Conclusions: Our Vit model showed expert-level performance in identifying non-displaced femoral neck fractures on paired AP and lateral hip radiographs. This model has the potential to enhance diagnosis accuracy and improve patient outcomes by reducing the need for additional examinations and preoperative time.

Robot-assisted versus navigation-assisted screw placement in spinal vertebrae.

PURPOSE: Both robots and navigation are effective strategies for optimizing screw placement, as compared to freehand placement. However, few studies have compared the accuracy and efficiency of these two techniques. Thus, the purpose of this study is to compare the accuracy and efficiency of robotic and navigation-assisted screw placement in the spinal vertebrae. METHODS: The 24 spine models were divided into a robot- and navigation-assisted groups according to the left and right sides of the pedicle. The C-arm transmits image data simultaneously to the robot and navigates using only one scan. After screw placement, the accuracy of the two techniques were compared using "angular deviation" and "Gertzbein and Robbins scale" in different segments (C1-7, T1-4, T5-8, T9-12, and L1-S1). In addition, operation times were compared between robot- and navigation-assisted groups. RESULTS: Robots and navigation systems can simultaneously assist in screw placement. The robot-assisted group had significantly less angular deviation than the navigation-assisted group from C1 to S1 (p < 0.001). At the C1-7 and T1-4 segments, the robot-assisted group had a higher rate of acceptable screws than the robot-assisted group. However, at the T5-8, T9-12, and L1-S1 segments, no significant difference was found in the incidence of acceptable screws between the two groups. Moreover, robot-assisted screw placement required less operative time than navigation (p < 0.05). CONCLUSION: The robot is more accurate and efficient than navigation in aiding screw placement. In addition, robots and navigation can be combined without increasing the number of fluoroscopic views.

[The impact of socioeconomic status on the prevalence of hypertension among adults in 9 provinces of China, 1991-2009].

OBJECTIVE: To investigate the trends of hypertension prevalence among Chinese adults from 1991 to 2009. To analysis the effects of socioeconomic status (SES) on hypertension rate. METHODS: This study was based on the data of China Health and Nutrition Survey which was conducted in 1991, 1993, 1997, 2000, 2004, 2006 and 2009. Adult subjects aged 18 to 74 years old in each round were included. Statistical method of single factor and multi-factor analysis was used. RESULTS: During the eighteen-year follow up, from 1991 to 2009, the crude rate increased from 14.6% to 28.7%, and the adjusted rate by age increased from 14.6% to 32.2% among males. The crude rate increased from 12.0% to 24.6% , and age adjusted rate from 12.0% to 24.9% among females. Hypertension prevalence was highest among the male group with highest SES score at 1991, 1993, 1997, 2000 and 2004. However, the lowest SES score with highest hypertension prevalence was found among the male group at 2006 and 2009. From 1997, the hypertension prevalence of female with highest SES score was lowest, and the group with lowest SES score was highest hypertension prevalence in female group from 1993. Negative association was found between SES score and female hypertension prevalence by the logistic regression analysis. No association was found between SES score and male hypertension prevalence. CONCLUSION: The prevalence of hypertension among Chinese adults had a continual increase with age during the period from 1991 to 2009. Negative association was existed between SES and hypertension prevalence for female. However, further study should be conducted between SES and male hypertension prevalence.

Enhancement of virus-induced gene silencing in tomato by low temperature and low humidity.

Virus-induced gene silencing (VIGS) is an attractive reverse-genetics tool for studying gene function in plants. We showed that silencing of a phytoene desaturase (PDS) gene is maintained throughout TRV-PDS-inoculated tomato plants as well as in their flowers and fruit and is enhanced by low temperature (15 degrees C) and low humidity (30%). RT-PCR analysis of the PDS gene revealed a dramatic reduction in the level of PDS mRNA in leaves, flowers and fruits. Silencing of PDS results in the accumulation of phytoene, the desaturase substrate. In addition, the content of chlorophyll a, chlorophyll b and total chlorophyll in the leaves of PDS-silenced plants was reduced by more than 90%. We also silenced the LeEIN2 gene by infecting seedlings, and this suppressed fruit ripenning. We conclude that this VIGS approach should facilitate large-scale functional analysis of genes involved in the development and ripening of tomato.

Virus-induced gene silencing in tomato fruit.

Virus-induced gene silencing (VIGS) is a powerful tool for the study of gene function in plants. Here we report that either by syringe-infiltrating the tobacco rattle virus (TRV)-vector into the surface, stem or carpopodium of a tomato fruit attached to the plant or by vacuum-infiltrating into a tomato fruit detached from the plant, TRV can efficiently spread and replicate in the tomato fruit. Although VIGS can be performed in tomato fruit by all of the means mentioned above, the most effective method is to inject the TRV-vector into the carpopodium of young fruit attached to the plant about 10 days after pollination. Several reporter genes related to ethylene responses and fruit ripening, including LeCTR1 and LeEILs genes, were also successfully silenced by this method during fruit development. In addition, we found that the silencing of the LeEIN2 gene results in the suppression of tomato fruit ripening. The results of our study indicate that the application of VIGS techniques by the described methods can be successfully applied to tomato fruit and is a valuable tool for studying functions of the relevant genes during fruit developing.