a-conflict-model-of-reward-seeking-behavior-in-male-rats

A Conflict Model of Reward-seeking Behavior in Male Rats

The present protocol describes a novel conflict task as a model of inhibitory control in rats. In this model, a natural rewarding stimulus (sexual ...

Chinese Academy of Sciences

University of Chinese Academy of Sciences

As a result of their advantages for superparamagnetic properties, good biocompatibility and high binding capacity, functionalized magnetic materials became widely popular over the past couple of decades, being applied on large scale in various processes of sample preparation for biomedicine. In this work we perform an in-depth review on the current progress in the field of magnetic bead separation, discussing in detail the physical basis of this process, various synthesis methods and surface modification strategies. We place a special focus of attention as well on the latest applications of magnetic polymer microspheres in cell separation, protein purification, immobilized enzyme, nucleic acid separation and extraction of bioactive compounds with low molecular weight. Existing problems are highlighted and possible trends of magnetic separation techniques for biomedicine in the future are proposed. This article is protected by copyright. All rights reserved.

Applications of magnetic materials separation in biological nanomedicine.

Bromodomain PHD finger transcription factor (BPTF), a bromodomain-containing protein, plays a crucial role in the regulation of downstream gene expression through the specific recognition of lysine acetylation on bulk histones. The dysfunction of BPTF is closely involved with the development and progression of many human diseases, especially cancer. Therefore, BPTF bromodomain has become a promising drug target for epigenetic cancer therapy. However, unlike BET family inhibitors, few BPTF bromodomain inhibitors have been reported. In this study, by integrating docking-based virtual screening with biochemical analysis, we identified a novel selective BPTF bromodomain inhibitor DCB29 with the IC value of 13.2 ± 1.6 μM by homogenous time-resolved fluorescence resonance energy transfer (HTRF) assays. The binding between DCB29 and BPTF was confirmed by NMR and SPR. Molecular docking disclosed that DCB29 occupied the pocket of acetylated H4 peptide substrate and provided detailed SAR explanations for its derivatives. Collectively, DCB29 presented great potential as a powerful tool for BPTF-related biological research and further medicinal chemistry optimization.

Discovery of alkoxy benzamide derivatives as novel BPTF bromodomain inhibitors via structure-based virtual screening.

Accurate stride-length estimation is a fundamental component in numerous applications, such as pedestrian dead reckoning, gait analysis, and human activity recognition. The existing stride-length estimation algorithms work relatively well in cases of walking a straight line at normal speed, but their error overgrows in complex scenes. Inaccurate walking-distance estimation leads to huge accumulative positioning errors of pedestrian dead reckoning. This paper proposes TapeLine, an adaptive stride-length estimation algorithm that automatically estimates a pedestrian's stride-length and walking-distance using the low-cost inertial-sensor embedded in a smartphone. TapeLine consists of a Long Short-Term Memory module and Denoising Autoencoders that aim to sanitize the noise in raw inertial-sensor data. In addition to accelerometer and gyroscope readings during stride interval, extracted higher-level features based on excellent early studies were also fed to proposed network model for stride-length estimation. To train the model and evaluate its performance, we designed a platform to collect inertial-sensor measurements from a smartphone as training data, pedestrian step events, actual stride-length, and cumulative walking-distance from a foot-mounted inertial navigation system module as training labels at the same time. We conducted elaborate experiments to verify the performance of the proposed algorithm and compared it with the state-of-the-art SLE algorithms. The experimental results demonstrated that the proposed algorithm outperformed the existing methods and achieves good estimation accuracy, with a stride-length error rate of 4.63% and a walking-distance error rate of 1.43% using inertial-sensor embedded in smartphone without depending on any additional infrastructure or pre-collected database when a pedestrian is walking in both indoor and outdoor complex environments (stairs, spiral stairs, escalators and elevators) with natural motion patterns (fast walking, normal walking, slow walking, running, jumping).

Article	Year
Applications of magnetic materials separation in biological nanomedicine. Electrophoresis\| PubMed ID: 30779364	2019
Discovery of alkoxy benzamide derivatives as novel BPTF bromodomain inhibitors via structure-based virtual screening. Bioorganic chemistry\| PubMed ID: 30780018	2019
Pedestrian Stride-Length Estimation Based on LSTM and Denoising Autoencoders. Sensors (Basel, Switzerland)\| PubMed ID: 30781668	2019

Haoshuang Luo

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