Validity of a Soft and Flexible 3D-Printed Nissen Fundoplication Model in Surgical Training.

Rapid development of three-dimensional (3D) printing technique has enabled the production of many new materials for medical applications but the dry laboratory surgical training model made of soft and flexible materials is still insufficient. We established a new 3D-printed Nissen fundoplication training model of which materials simulate the real mechanical properties. In this study, 16 participants were divided into two groups: Experimental group and control group. The validity of model was tested using Likert scale by the experts and the experimental group. To evaluate the efficacy, performances of the experimental group were scored at the first, fourth, and eighth training by OSATS system and the duration of procedure was compared through the use of recorded video. Meanwhile, an ex vivo model was used to compare the performance of the experiment group and control group after the training in the same way. Our results showed that the 3D-printed model can support the future surgical applications, help improve surgical skills, and shorten procedure time after training.

Validation of a three-dimensional printed dry lab pancreaticojejunostomy model in surgical assessment: a cross-sectional study.

OBJECTIVES: Until now, there have been few tools to evaluate whether a surgeon was technically ready to perform a safe pancreaticojejunostomy (PJ). In the current study, we aimed to evaluate whether a three-dimensional model could mimic a real surgical situation and distinguish between surgeons of different levels of experiences. DESIGN: A three-dimensional PJ dry laboratory model was printed. Eight experienced pancreatic surgeons were tasked to evaluate the appearance and tactile sensation of the model. Proficiency was scored based on 15 surgeons with various levels of pancreatic experience performing a PJ on the three-dimensional model. Additionally, the time of manipulation and NASA Task Load Index (NASA-TLX) scores were recorded for each operation. SETTING: Our study was conducted in multimedical centre in China. RESULTS: Compared with real surgical situations, this model had similar appearance (3.96±0.55 out of five points) and tactile sensation (3.85±0.46 out of five points) according to the expert evaluation. Additionally, the chief surgeon group scored the best in proficiency (based on NASA-TLX scores and operative time), and there were statistical differences for performances among surgeons of various levels (p<0.05). CONCLUSION: The three-dimensional PJ model could mimic a real surgical situation and can distinguish between surgeons of different levels of experiences.

Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new water quality prediction CSWLSTM-GPR model, which fused the spatial feature of convolutional neural network (CNN), the temporal feature of sharing-weight long short-term memory (SWLSTM) and the probabilistic reliability of Gaussian process regression (GPR), was applied for monitoring papermaking wastewater treatment system with high-precision point prediction and interval prediction. Compared with SWLSTM-GPR and CLSTM-GPR, RMSE of CSWLSTM-GPR reduced by more than 48.9% on effluent chemical oxygen demand (CODeff), MAE reduced by more than 49.3%, R2 increased by more than 25.14%, R increased by more than 7.07%. And for the effluent suspended solids (SSeff), CSWLSTM-GPR had better predictive results than SWLSTM-GPR and CSWLSTM-GPR. Compared with SWLSTM-GPR, RMSE, MAE, R, R2 of CSWLSTM-GPR on effluent suspended solids (SSeff) were improved by 4.8%, 6.1%, 29.01% and 31.15%, respectively. Simulation results showed convincing comprehensive forecasting ability were obtained and the true values frequently stayed within the water quality range obtained by CSWLSTM-GPR model, which provided important insights for online monitoring, wastewater recycling and carbon neutrality of papermaking industry.

Enhanced plasma miR-142-5p promotes the progression of intrahepatic cholangiocarcinoma via targeting PTEN.

The aim of the present study was to evaluate the expression and specific role of microRNA (miR)-142-5p in the progression of intrahepatic cholangiocarcinoma (ICC). Reverse transcription-quantitative polymerase chain reaction was performed to evaluate miR-142-5p expression in patients with ICC and healthy control subjects. The results revealed that plasma miR-142-5p was significantly increased in patients with ICC compared with the control group. Furthermore, miR-142-5p was also increased in ICC tissues compared with adjacent non-neoplastic tissues. Compared with patients with Ta-T1 stage ICC, miR-142-5p was significantly elevated in patients with ICC ≥T2 stage. Patients with ICC at G3 stage had much higher plasma miR-142-5p levels compared with those at G1/2 stage. Receiver operating characteristic analysis indicated that miR-142-5p could be used as a biomarker to differentiate patients with ICC from healthy controls. Kaplan-Meier analysis demonstrated that plasma miR-142-5p was negatively correlated with survival in patients with ICC. A dual luciferase reporter assay indicated that miR-142-5p significantly suppressed the relative luciferase activity of pmirGLO-PTEN-3' untranslated region compared with the control group. In summary, the results of the present study provide novel data indicating that plasma miR-142-5p is significantly upregulated in patients with ICC. miR-142-5p may therefore have potential as a biomarker for screening patients with ICC from healthy controls.