The world has witnessed tremendous advancements in nano-base applications. Zinc oxide nanoparticles (ZON) are widely used in food industry and medicine. Although their application is of important value, they may cause toxicity to body tissues. Peripheral blood mononuclear cells (PBMCs) proved its efficacy in tissue regeneration especially when it is preconditioned by activated platelet supernatant (APS). The aim of this study is to evaluate the effect of ZON on the gastric mucosa and the therapeutic role of the PBMCs preconditioned by APS in rats. Ten rats were donors and fifty rats were recipients. The recipients were divided into; control group, ZON group (10 mg/kg/day orally for five days) and preconditioned PBMCs group (1×107 once intravenously 24 hours after ZON). Gastric specimens were processed for histological, immunohistochemical, biochemical and quantitative real-time polymerase chain reaction studies. ZON group showed marked structural changes in the gastric mucosa. There was desquamation or deep ulceration of the epithelium. Cytoplasmic vacuoles and pyknotic nuclei were in glandular cells. Reduced proliferating cell nuclear antigen and increased tumor necrosis factor-α were in epithelial cells. There were significant elevation in malondialdahyde and reduction in glutathione, superoxide dismutase, and catalase. Enhancement in mRNA expression of nuclear factor kappa-B and cyclooxygenase-2 was detected.The preconditioned PBMCs group showed significant improvement of all parameters. So, ZON had cytotoxic effects on the gastric mucosa and the preconditioned PBMCs had a therapeutic effect on gastric mucosal damage after ZON.

Purpose: To create a computer-aided prediction (CAP) system to predict Wilms tumor (WT) responsiveness to preoperative chemotherapy (PC) using pre-therapy contrast-enhanced computed tomography (CECT). Materials and Methods: A single-center database was reviewed for children <18 years diagnosed with WT and received PC between 2001 and 2021. Patients were excluded if pre- and post-PC CECT were not retrievable. According to the Response Evaluation Criteria in Solid Tumors criteria, volumetric response was considered favorable if PC resulted in ≥30% tumor volume reduction.Histological response was considered favorable if post-nephrectomy specimens had ≥66% necrosis. Four steps were used to create the prediction model: tumor delineation; extraction of shape, texture and functionality-based features; integration of the extracted features and selection of the prediction model with the highest diagnostic performance. K-fold cross-validation allowed the presentation of all data in the training and testing phases. Results: A total of 63 tumors in 54 patients were used to train and test the prediction model. Patients were treated with 4–8 weeks of vincristine/actinomycin-D combination. Favorable volumetric and histologic responses were achieved in 46 tumors (73.0%) and 38 tumors (60.3%), respectively. Among machine learning classifiers, support vector machine had the best diagnostic performance with an accuracy, sensitivity, and specificity of 95.24%, 95.65%, and 94.12% for volumetric and 84.13%, 89.47%, 88% for histologic response prediction. Conclusions Based on pre-therapy CECT, CAP systems can help identify WT that are less likely to respond to PC with excellent accuracy. These tumors can be offered upfront surgery, avoiding the cons of PC.