Cyp1 Inhibition Prevents Doxorubicin-Induced Cardiomyopathy in a Zebrafish Heart-Failure Model

Doxorubicin is a highly effective chemotherapy agent used to treat many common malignancies. However, its use is limited by cardiotoxicity, and cumulative doses exponentially increase the risk of heart failure. To identify novel heart failure treatment targets, a zebrafish model of doxorubicin-induced cardiomyopathy was previously established for small-molecule screening. Using this model, several small molecules that prevent doxorubicin-induced cardiotoxicity both in zebrafish and in mouse models have previously been identified. In this study, exploration of doxorubicin cardiotoxicity is expanded by screening 2271 small molecules from a proprietary, target-annotated tool compound collection. It is found that 120 small molecules can prevent doxorubicin-induced cardiotoxicity, including 7 highly effective compounds. Of these, all seven exhibited inhibitory activity towards cytochrome P450 family 1 (CYP1). These results are consistent with previous findings, in which visnagin, a CYP1 inhibitor, also prevents doxorubicin-induced cardiotoxicity. Importantly, genetic mutation of cyp1a protected zebrafish against doxorubicin-induced cardiotoxicity phenotypes. Together, these results provide strong evidence that CYP1 is an important contributor to doxorubicin-induced cardiotoxicity and highlight the CYP1 pathway as a candidate therapeutic target for clinical cardioprotection.     

Improvement of 19F MR image uniformity in a mouse model of cellular therapy using inductive coupling

Magnetic Resonance Materials in Physics, Biology and Medicine - Improve 19F magnetic resonance imaging uniformity of perfluorocarbon (PFC)-labeled cells by using a secondary inductive resonator...     

Photopolymerization kinetics of bis-aromatic based urethane acrylate macromonomers in the presence of reactive diluent

The present work deals with the photopolymerization of bis-aromatic based urethane acrylate macromonomers in the presence of excess end capping agent as reactive diluent and estimation of their kinetic parameters. Formulations were made by independently homogenizing the macromonomers with photoinitiators of three different classes. Three different compositions of photoinitiators were used to study the effect of concentration of photoinitiator on cure kinetics. These compositions obtained were tested for photo curing performance using photo DSC under polychromatic radiation. The heat flows against time were recorded for all formulations under isothermal condition and the rates of polymerization, peak maximum times as well as the percentage conversions were estimated. It was observed that due to a longer timescale for reaction diffusion, formulations with macromonomer containing propoxylated backbone showed higher conversions than the corresponding ethoxylated analogue. The photopolymerization and kinetic estimations of the formulations including evaluation of kinetic model are discussed.     

Concrete crack detection using context‐aware deep semantic segmentation network

Computer‐vision and deep‐learning techniques are being increasingly applied to inspect, monitor, and assess infrastructure conditions including detection of cracks. Traditional vision‐based methods to detect cracks lack accuracy and generalization to work on complicated infrastructural conditions. This paper presents a novel context‐aware deep convolutional semantic segmentation network to effectively detect cracks in structural infrastructure under various conditions. The proposed method applies a pixel‐wise deep semantic segmentation network to segment the cracks on images with arbitrary sizes without retraining the prediction network. Meanwhile, a context‐aware fusion algorithm that leverages local cross‐state and cross‐space constraints is proposed to fuse the predictions of image patches. This method is evaluated on three datasets: CrackForest Dataset (CFD) and Tomorrows Road Infrastructure Monitoring, Management Dataset (TRIMMD) and a Customized Field Test Dataset (CFTD) and achieves Boundary F1 (BF) score of 0.8234, 0.8252, and 0.7937 under 2‐pixel error tolerance margin in CFD, TRIMMD, and CFTD, respectively. The proposed method advances the state‐of‐the‐art performance of BF score by approximately 2.71% in CFD, 1.47% in TRIMMD, and 4.14% in CFTD. Moreover, the averaged processing time of the proposed system is 0.7 s on a typical desktop with Intel^® Quad‐Core? i7‐7700 CPU@3.6 GHz Processor, 16GB RAM and NVIDIA GeForce GTX 1060 6GB GPU for an image of size 256 × 256 pixels.     

Partial replacement of carbon black with graphene in natural rubber/butadiene rubber based tire compound: Investigation of critical properties

Journal of Polymer Research - In this study, we prepared graphene oxide-based styrene/acrylic elastomeric disks (GSAE) from sugarcane bagasse/ferrocene (GO) and styrene/acrylic emulsion (SAE) to...