Study on the design, synthesis, and activity of anti-tumor staple peptides targeting MDM2/MDMX.

Staple peptides, which have a significantly enhanced pharmacological profile, are promising therapeutic molecules due to their remarkable resistance to proteolysis and cell-penetrating properties. In this study, we designed and synthesized a series of PMI-M3-based dual-targeting MDM2/MDMX staple peptides and compared them with straight-chain peptides. The staple peptide SM3-4 screened in the study induced apoptosis of tumor cells at low μM concentrations, and the helix was significantly increased.

3D reconstruction for maxillary anterior tooth crown based on shape and pose estimation networks.

Purpose: The design of a maxillary anterior tooth crown is crucial to post-treatment aesthetic appearance. Currently, the design is performed manually or by semi-automatic methods, both of which are time-consuming. As such, automatic methods could improve efficiency, but existing automatic methods ignore the relationships among crowns and are primarily used for occlusal surface reconstruction.

Texture-less surface reconstruction using shape-based image augmentation.

The development of intelligent Robot-Assisted Minimally Invasive Surgery demands geometric reconstruction from endoscopic images. However, images of human tissue surfaces are commonly texture-less. Obtaining the dense depth map of a texture-less scene is very difficult because traditional feature-based 3D reconstruction methods cannot detect enough features to build dense correspondences for depth computation.

An image-guided hybrid robot system for dental implant surgery.

Purpose: Dental implant surgery is an effective method for remediating the loss of teeth. Robot is expected to increase the accuracy of dental implant surgery. However, most of them are industrial serial robot, with low stiffness and non-unique inverse kinematic solution, which may reduce the success rate and safety of robotic surgery.

Multi-Dimension and Multi-Feature Hybrid Learning Network for Classifying the Sub Pathological Type of Lung Nodules through LDCT.

In order to develop appropriate treatment and rehabilitation plans with regard to different subpathological types (PILs and IAs) of lung nodules, it is important to diagnose them through low-dose spiral computed tomography (LDCT) during routine screening before surgery. Based on the characteristics of different subpathological lung nodules expressed from LDCT images, we propose a multi-dimension and multi-feature hybrid learning neural network in this paper. Our network consists of a 2D network part and a 3D network part.

Embryo location in the uterus during embryo transfer: An in vitro simulation.

Objective: To evaluate the location of transferred embryos under various parameters during embryo transfer in in vitro fertilization (IVF) by applying an in vitro experimental model for embryo transfer (ET).

Methods: Mock ET simulations were conducted with a laboratory model of the uterine cavity. The transfer catheter was loaded with a sequence of air and liquid volumes, including development-arrested embryos donated by patients.