Objective To analyze the risk factors of unplanned reoperation and construct a nomogram-based risk prediction model to identify high-risk patients,so as to provide a basis for perioperative manage-ment to reduce the rate of reoperation.Methods A total of 880 patients with underwent unplanned reopera-tion between 2018 and 2021 were included as the unplanned reoperation group.Using propensity score matc-hing,2640 patients were matched in a 1∶3 ratio to form the control group.Potential risk factor indicators were collected and subjected to univariate analysis.Significant indicators were then selected for multivariable logistic regression analysis to construct the risk prediction model.The predictive value of the model was evalu-ated.Results For unplanned reoperation,The number of complications 3-5 (OR=1.84),the number of complications 6-10 (OR=2.94),combined with maligant tumor (OR=1.75),combined with end-stage renal disease (OR=1.92),major surgery grade 3 (OR=4.27),major surgery grade 4 (OR=7.26),and incision grade Ⅰ,Ⅱ,Ⅲ (OR=2.18,1.97,6.85) were independent factors (P<0.05).The model passed the calibra-tion degree test,and the area under ROC curve (AUC) was 0.715,indicating good model differentiation.Con-clusion A risk prediction model based on risk factors can help identify high-risk populations for unplanned reoperation and suggest corresponding measures for prevention.

In recent years,3D bioprinting technology has developed rapidly,becoming an essential tool in the fields of cancer research,tissue engineering,disease modeling and mechanistic studies.This paper reviewed the fundamental principles of bioprinting technology and its current applications in cancer research and tissue engineering.Bioprinting is an additive manufacturing technology that constructs complex three-dimensional tissue structures by digitally controlling the layer-by-layer deposition of biomaterials and living cells.The core steps of bioprinting include designing a 3D model,selecting appropriate bioprinting techniques and materials,printing layer by layer,followed by post-processing involving cell culture and functionalization.In cancer research,3D bioprinting can create complex tumor models that simulate the tumor microenvironment,revealing new mechanisms of tumor initiation and progression.Traditional in vitro models,such as 2D cell cultures or animal models,often fail to accurately replicate the complexity of human tumors.However,3D bioprinted tumor models,which mimic the dynamic interactions between tumor cells and their environment such as immune cells,stroma and blood vessels,offer a more biomimetic platform for studying tumor growth,invasion and metastasis.These models provide a research platform that closely mirrors actual tumor behavior.Additionally,Bioprinted models and scaffolds can be leveraged in personalized precision therapies by efficiently constructing patient-specific 3D models from their own cells.These models enable the prediction of patient's sensitivity to drugs and radiotherapy.Additionally,localized scaffolds can be developed to meet individual patient needs,allowing for the formulation of appropriate drug types and dosages.Furthermore,3D-printed scaffolds can support drug delivery by targeting specific areas,reducing drug-related side effects.They can also be used to facilitate local immunotherapy,cytokine therapy,cancer vaccines,and chimeric antigen receptor cell therapy,enhancing therapeutic outcomes.In tissue engineering,traditional tissue repair methods often struggle to address the complex requirements of constructing intricate tissue structures.3D bioprinting offers a novel solution by enabling the creation of complex tissue architectures and promoting tissue regeneration.Basic tissues,such as bone,cartilage and skin,which have higher regenerative capacities,are gradually being incorporated into clinical practice.Significant progress has also been made in the repair and reconstruction of more complex organs like the liver and heart,though considerable challenges remain before these advancements can be fully translated into clinical applications.Finally,this paper discussed the current challenges and future directions of 3D bioprinting in these fields,aiming to provide reference for researchers.

The paper summarizes the clinical and follow-up data of percutaneous endoscopic gastrostomy (PEG) in three infants with chronic kidney disease to explore the safety and reliability of using PEG to improve the growth and development, and nutritional status. During follow-up, the weight and height of case 1 and 3 were obviously improved. Case 2 was followed up for 3 months, due to dying of cardiac arrest, and the infant's height and weight were not significantly improved. Serum albumin and prealbumin improved in 3 cases after PEG. No PEG-related infection occurred in 3 infants.