ObjectiveTo study the CT values of certain phantoms scanned by various CT scanners with dissimilar parameters.Methods The CT values of tissue equivalent inserts was measured in the TM164 and CIRS-062 phantom scanned by TOSHIBA AQUILIONTM,SIEMENS SOMATOMTMSENSATIONTM 64 and SIEMENS SOMATOMTM SENSATIONTM OPEN with different voltages,currents and slice thicknesses and then the corresponding CT-to-density curves was compared. Results There are no significant differences of CT values with various currents and slice thicknesses and also for low atom number materials scanned by different scanners with various tube voltages.The CT values of high atom number materials have obvious differences scanned with tube voltage,the maximum is about 400 HU.There are also significant differences between CT-density curves of two phantoms in the range from soft tissues to dense bone,the maximum is up to 500 HU.ConclusionsCT-density curves were highly affected by materials of phantoms,scanners and tube voltages.It is necessary to measure the curve with a comfortable phantom and certain scanner to assure the accuracy for dose calculation for treatment planning system.

Background::Ainuovirine (ANV) is a new generation of non-nucleoside reverse transcriptase inhibitor for the treatment of human immunodeficiency virus (HIV) type 1 infection. This study aimed to evaluate the population pharmacokinetic (PopPK) profile and exposure-response relationship of ANV among people living with HIV.Methods::Plasma concentration-time data from phase 1 and phase 3 clinical trials of ANV were pooled for developing the PopPK model. Exposure estimates obtained from the final model were used in exposure-response analysis for virologic responses and safety responses.Results::ANV exhibited a nonlinear pharmacokinetic profile, which was best described by a two-compartment model with first-order elimination. There were no significant covariates correlated to the pharmacokinetic parameters of ANV. The PopPK parameter estimate (relative standard error [%]) for clearance adjusted for bioavailability (CL/F) was 6.46 (15.00) L/h, and the clearance of ANV increased after multiple doses. The exposure-response model revealed no significant correlation between the virologic response (HIV-RNA <50 copies/mL) at 48 weeks and the exposure, but the incidence of adverse events increased with the increasing exposure ( P value of steady-state trough concentration and area under the steady-state curve were 0.0177 and 0.0141, respectively). Conclusions::Our PopPK model supported ANV 150 mg once daily as the recommended dose for people living with HIV, requiring no dose adjustment for the studied factors. Optimization of ANV dose may be warranted in clinical practice due to an increasing trend in adverse reactions with increasing exposure.Trial registration::Chinese Clinical Trial Registry https://www.chictr.org.cn (Nos. ChiCTR1800018022 and ChiCTR1800019041).

Objective: To study the effect of artificial intelligence in the pathological diagnosis of periapical cysts and to explore the application of artificial intelligence in the field of oral pathology. Methods: Pathological images of eighty-seven periapical cysts were selected as subjects to read, and a neural network with a U-net structure was constructed. The 87 HE images and labeled images of periapical cysts were divided into a training set (72 images) and a test set (15 images), which were used in the training model and test model, respectively. Finally, the target level index F1 score, pixel level index Dice coefficient and receiver operating characteristic (ROC) curve were used to evaluate the ability of the U-net model to recognize periapical cyst epithelium. Results : The F1 score of the U-net network model for recognizing periapical cyst epithelium was 0.75, and the Dice index and the areas under the ROC curve were 0.685 and 0.878, respectively. Conclusion The U-net network model constructed by artificial intelligence has a good segmentation result in identifying periapical cyst epithelium, which can be preliminarily applied in the pathological diagnosis of periapical cysts and is expected to be gradually popularized in clinical practice after further verification with large samples.