Trilogy of drug repurposing for developing cancer and chemotherapy-induced heart failure co-therapy agent.

Chemotherapy-induced complications, particularly lethal cardiovascular diseases, pose significant challenges for cancer survivors. The intertwined adverse effects, brought by cancer and its complication, further complicate anticancer therapy and lead to diminished clinical outcomes. Simple supplementation of cardioprotective agents falls short in addressing these challenges. Developing bi-functional co-therapy agents provided another potential solution to consolidate the chemotherapy and reduce cardiac events simultaneously. Drug repurposing was naturally endowed with co-therapeutic potential of two indications, implying a unique chance in the development of bi-functional agents. Herein, we further proposed a novel "trilogy of drug repurposing" strategy that comprises function-based, target-focused, and scaffold-driven repurposing approaches, aiming to systematically elucidate the advantages of repurposed drugs in rationally developing bi-functional agent. Through function-based repurposing, a cardioprotective agent, carvedilol (CAR), was identified as a potential neddylation inhibitor to suppress lung cancer growth. Employing target-focused SAR studies and scaffold-driven drug design, we synthesized 44 CAR derivatives to achieve a balance between anticancer and cardioprotection. Remarkably, optimal derivative 43 displayed promising bi-functional effects, especially in various self-established heart failure mice models with and without tumor-bearing. Collectively, the present study validated the practicability of the "trilogy of drug repurposing" strategy in the development of bi-functional co-therapy agents.

Augmented reality navigation with real-time tracking for facial repair surgery.

PURPOSE: Facial repair surgeries (FRS) require accuracy for navigating the critical anatomy safely and quickly. The purpose of this paper is to develop a method to directly track the position of the patient using video data acquired from the single camera, which can achieve noninvasive, real time, and high positioning accuracy in FRS. METHODS: Our method first performs camera calibration and registers the surface segmented from computed tomography to the patient. Then, a two-step constraint algorithm, which includes the feature local constraint and the distance standard deviation constraint, is used to find the optimal feature matching pair quickly. Finally, the movements of the camera and the patient decomposed from the image motion matrix are used to track the camera and the patient, respectively. RESULTS: The proposed method achieved fusion error RMS of 1.44 ± 0.35, 1.50 ± 0.15, 1.63 ± 0.03 mm in skull phantom, cadaver mandible, and human experiments, respectively. The above errors of the proposed method were lower than those of the optical tracking system-based method. Additionally, the proposed method could process video streams up to 24 frames per second, which can meet the real-time requirements of FRS. CONCLUSIONS: The proposed method does not rely on tracking markers attached to the patient; it could be executed automatically to maintain the correct augmented reality scene and overcome the decrease in positioning accuracy caused by patient movement during surgery.

Deep learning approach for guiding three-dimensional computed tomography reconstruction of lower limbs for robotically-assisted total knee arthroplasty.

BACKGROUND: Robotic-assisted total knee arthroplasty (TKA) was performed to promote the accuracy of bone resection and mechanical alignment. Among these TKA system procedures, 3D reconstruction of CT data of lower limbs consumes significant manpower. Artificial intelligence (AI) algorithms applying deep learning has been proved efficient in automated identification and visual processing. METHODS: CT data of a total of 200 lower limbs scanning were used for AI-based 3D model construction and CT data of 20 lower limbs scanning were utilised for verification. RESULTS: We showed that the performance of an AI-guided 3D reconstruction of CT data of lower limbs for robotic-assisted TKA was similar to that of the operator-based approach. The time of 3D lower limb model construction using AI was 4.7 min. AI-based 3D models can be used for surgical planning. CONCLUSION: AI was used for the first time to guide the 3D reconstruction of CT data of lower limbs for facilitating robotic-assisted TKA. Incorporation of AI in 3D model reconstruction before TKA might reduce the workload of radiologists.

A new robotically assisted system for total knee arthroplasty: A sheep model study.

BACKGROUND: We investigated the accuracy and safety of a new HURWA robotic-assisted total knee arthroplasty (TKA) system in a sheep model. METHODS: Ten male small-tailed Han sheep were used in this study. Sheep were imaged by computed tomography scan before and after bone resection and the cutting errors between actual bone preparation and preoperative planning of the femur and tibia in three dimensions were measured. RESULTS: The overall accuracies after surgery compared with that from preoperative surgical planning of the left and right femurs were 1.93 ± 1.02° and 1.93 ± 1.23°, respectively. Additionally, similarly high overall accuracies for the left and right tibia of 1.26 ± 1.04 and 1.68 ± 0.92°, respectively, were obtained. The gap distances of the distal cut, anterior chamfer, anterior cut, posterior chamfer and posterior cut on the medial side were 0.47 ± 0.35 mm, 0.41 ± 0.37 mm, 0.12 ± 0.26 mm, 0.41 ± 0.44 mm and 0.12 ± 0.23 mm, respectively. No intraoperative complications, such as intraoperative fracture, massive bleeding or death, occurred. CONCLUSION: This new HURWA robotic-assisted TKA system is an accurate and safe tool for TKA surgery based on the sheep model.

Inhibition of human carboxylesterases by magnolol: Kinetic analyses and mechanism.

Magnolol, the most abundant bioactive constituent of the Chinese herb Magnolia officinalis, has been found with multiple biological activities, including anti-oxidative, anti-inflammatory and enzyme-regulatory activities. In this study, the inhibitory effects and inhibition mechanism of magnolol on human carboxylesterases (hCEs), the key enzymes responsible for the hydrolytic metabolism of a variety of endogenous esters as well as ester-bearing drugs, have been well-investigated. The results demonstrate that magnolol strongly inhibits hCE1-mediated hydrolysis of various substrates, whereas the inhibition of hCE2 by magnolol is substrate-dependent, ranging from strong to moderate. Inhibition of intracellular hCE1 and hCE2 by magnolol was also investigated in living HepG2 cells, and the results showed that magnolol could strongly inhibit intracellular hCE1, while the inhibition of intracellular hCE2 was weak. Inhibition kinetic analyses and docking simulations revealed that magnolol inhibited both hCE1 and hCE2 in a mixed manner, which could be partially attributed to its binding at two distinct ligand-binding sites in each carboxylesterase, including the catalytic cavity and the regulatory domain. In addition, the potential risk of the metabolic interactions of magnolol via hCE1 inhibition was predicted on the basis of a series of available pharmacokinetic data and the inhibition constants. All these findings are very helpful in deciphering the metabolic interactions between magnolol and hCEs, and also very useful for avoiding deleterious interactions via inhibition of hCEs.