Objective To explore the effects of different ventilation modes of tracheobronchial foreign body in children with fiberoptic operation under general anesthesia.Methods Sixty children (1ys≤ age≤3ys) undergoing fiberoptic bronchoscopy tracheal foreign body removal according to the combinations of different ventilation modes during and after fiberoptic bronchoscopy (FOB) procedures were divided into group A [volume control ventilation (VCV) + VCV,n =20],group B [pressure control ventilation (PCV) + VCV,n =20] and group C (PCV + PCV,n =20) randomly.The P mean,Pmax,and PetCO2 during and after fiberoptic bronchoscopy procedures were monitored.The SpO2,PaO2,and PaCO2 after mechanical ventilation 1.5 hours were recorded.Results Compared to group A,groups B and C had lower P max and P mean (P ＜ 0.05) during the FOB procedures.Compared to groups A and B,group C had a lower P max and P mean (P ＜0.01) after the FOB procedures.At the 1.5 hours after the procedure,all the children showed significant increase in SpO2 and PaO2 (P ＜ 0.05) and decrease in PaCO2 (P ＜ 0.05) in groups A,B,and C.Conclusions When fiberoptic bronchoscopy in tracheobronchial foreign body operation is applied in children undergoing general anesthesia,the pressure control ventilation (VCV) mode can decrease the pressure of airway (Paw) and PaCO2 than volume control mode during procedure.

Early screening based on computed tomography (CT) pulmonary nodule detection is an important means to reduce lung cancer mortality, and in recent years three dimensional convolutional neural network (3D CNN) has achieved success and continuous development in the field of lung nodule detection. We proposed a pulmonary nodule detection algorithm by using 3D CNN based on a multi-scale attention mechanism. Aiming at the characteristics of different sizes and shapes of lung nodules, we designed a multi-scale feature extraction module to extract the corresponding features of different scales. Through the attention module, the correlation information between the features was mined from both spatial and channel perspectives to strengthen the features. The extracted features entered into a pyramid-similar fusion mechanism, so that the features would contain both deep semantic information and shallow location information, which is more conducive to target positioning and bounding box regression. On representative LUNA16 datasets, compared with other advanced methods, this method significantly improved the detection sensitivity, which can provide theoretical reference for clinical medicine.
Algorithms ; Humans ; Lung Neoplasms/diagnostic imaging* ; Neural Networks, Computer ; Radiographic Image Interpretation, Computer-Assisted/methods* ; Tomography, X-Ray Computed/methods*

Radiotherapy is widely used in the management of advanced colorectal cancer (CRC). However, the clinical efficacy is limited by the safe irradiated dose. Sensitizing tumor cells to radiotherapy via interrupting DNA repair is a promising approach to conquering the limitation. The BRCA1-BARD1 complex has been demonstrated to play a critical role in homologous recombination (HR) DSB repair, and its functions may be affected by HERC2 or BAP1. Accumulated evidence illustrates that the ubiquitination-deubiquitination balance is involved in these processes; however, the precise mechanism for the cross-talk among these proteins in HR repair following radiation hasn't been defined. Through activity-based profiling, we identified PT33 as an active entity for HR repair suppression. Subsequently, we revealed that BAP1 serves as a novel molecular target of PT33 via a CRISPR-based deubiquitinase screen. Mechanistically, pharmacological covalent inhibition of BAP1 with PT33 recruits HERC2 to compete with BARD1 for BRCA1 interaction, interrupting HR repair. Consequently, PT33 treatment can substantially enhance the sensitivity of CRC cells to radiotherapy in vitro and in vivo. Overall, these findings provide a mechanistic basis for PT33-induced HR suppression and may guide an effective strategy to improve therapeutic gain.