Macao Polytechnic University

Weng J., Tong H.H., Chow S.F.

The in vitro release study is a critical test to assess the safety, efficacy, and quality of nanoparticle-based drug delivery systems, but there is no compendial or regulatory standard. The variety of testing methods makes direct comparison among different systems difficult. We herein proposed a novel sample and separate (SS) method by combining the United States Pharmacopeia (USP) apparatus II (paddle) with well-validated centrifugal ultrafiltration (CU) technique that efficiently separated the free drug from nanoparticles. Polymeric drug nanoparticles were prepared by using a four-stream multi-inlet vortex mixer with d-α-tocopheryl polyethylene glycol 1000 succinate as a stabilizer. Itraconazole, cholecalciferol, and flurbiprofen were selected to produce three different nanoparticles with particle size <100 nm. By comparing with the dialysis membrane (DM) method and the SS methods using syringe filters, this novel SS + CU technique was considered the most appropriate in terms of the accuracy and repeatability to provide the in vitro release kinetics of nanoparticles. Interestingly, the DM method appeared to misestimate the release kinetics of nanoparticles through separate mechanisms. This work offers a superior analytical technique for studying in vitro drug release from polymeric nanoparticles, which could benefit the future development of in vitro-in vivo correlation of polymeric nanoparticles.

Huang X., Feng C., Qin J., Wang X., Zhang T.

Improving agricultural green total factor productivity (AGTFP) is essential to China's agricultural sustainable development. Although several studies have focused on China's AGTFP, its measurement and drivers are not fully investigated yet. More specifically, the published research examining the drivers of China's AGTFP at both the production and factor levels is still scarce. To fill this gap, this study constructs two different data envelopment analysis models combined with green Luenberger productivity indicator (GLPI), the biennial weight modified Russell model and the biennial bounded adjusted model, to measure China's AGTFP as well as check the robustness. We further decompose the AGTFP growth at both production and factor levels to investigate its drivers. The main findings are as follows. First, during 1998-2019, the central region with its GLPI at 0.0377 had the largest AGTFP growth, followed by the western (0.0281) and eastern regions (0.0254). Second, in terms of production-decomposition, technical progress was crucial driver to AGTFP growth, energy conservation and emission reduction (ECER) and market performance. Third, in terms of factors-decomposition, the contributions of these factors to the AGTFP growth were positive and the contribution rates ranged from 1.01% (pesticide) to 38.51% (agricultural carbon emissions). Additionally, ECER performance was the primary driver of AGTFP, accounting for about 51.35% of the growth. Finally, according to the decompositions, Porter effect was discovered in China's agricultural sector. ECER drove China's agriculture to achieve win-win development between the environment and economic production.

Zhang Y., Sheng H., Wu Y., Wang S., Lyu W., Ke W., Xiong Z.

Recently, most multiple object tracking (MOT) algorithms adopt the idea of tracking-by-detection. Relevant research shows that the performance of the detector obviously affects the tracker, while the improvement of detector is gradually slowing down in recent years. Therefore, trackers using tracklet (short trajectory) are proposed to generate more complete trajectories. Although there are various tracklet generation algorithms, the fragmentation problem still often occurs in crowded scenes. In this paper, we introduce an iterative clustering method that generates more tracklets while maintaining high confidence. Our method shows robust performance on avoiding internal identity switch. Then we propose a deep association method for tracklet association. In terms of motion and appearance, we construct motion evaluation network (MEN) and appearance evaluation network (AEN) to learn long-term features of tracklets for association. In order to explore more robust features of tracklets, a tracklet-based training mechanism is also introduced. Tracklet groups are used as the input of the networks instead of discrete detections. Experimental results show that our training method enhances the performance of the networks. In addition, our tracking framework generates more complete trajectories while maintaining the unique identity of each target as the same time. On the latest MOT 2017 benchmark, we achieve state-of-the-art results.

Chen J., Wan Z., Zhang J., Li W., Chen Y., Li Y., Duan Y.

Background Prostate cancer is a disease with a high incidence of tumors in men. Due to the long incubation time and insidious condition, early diagnosis is difficult; especially imaging diagnosis is more difficult. In actual clinical practice, the method of manual segmentation by medical experts is mainly used, which is time-consuming and labor-intensive and relies heavily on the experience and ability of medical experts. The rapid, accurate and repeatable segmentation of the prostate area is still a challenging problem. It is important to explore the automated segmentation of prostate images based on the 3D AlexNet network. Method Taking the medical image of prostate cancer as the entry point, the three-dimensional data is introduced into the deep learning convolutional neural network. This paper proposes a 3D AlexNet method for the automatic segmentation of prostate cancer magnetic resonance images, and the general network ResNet 50, Inception -V4 compares network performance. Results Based on the training samples of magnetic resonance images of 500 prostate cancer patients, a set of 3D AlexNet with simple structure and excellent performance was established through adaptive improvement on the basis of classic AlexNet. The accuracy rate was as high as 0.921, the specificity was 0.896, and the sensitivity It is 0.902 and the area under the receiver operating characteristic curve (AUC) is 0.964. The Mean Absolute Distance (MAD) between the segmentation result and the medical expert's gold standard is 0.356 mm, and the Hausdorff distance (HD) is 1.024 mm, the Dice similarity coefficient is 0.9768. Conclusion The improved 3D AlexNet can automatically complete the structured segmentation of prostate magnetic resonance images. Compared with traditional segmentation methods and depth segmentation methods, the performance of the 3D AlexNet network is superior in terms of training time and parameter amount, or network performance evaluation. Compared with the algorithm, it proves the effectiveness of this method.

Lim W.M., To W.

Availability of full-year economic data is indicative of an opportune time to compare and contrast predicted and actual economic impact. In this regard, this study delineates the impact of the COVI...

Zhang Y., Sheng H., Wu Y., Wang S., Ke W., Xiong Z.

In recent years, the demand for intelligent devices related to the Internet of Things (IoT) is rapidly increasing. In the field of computer vision, many algorithms have been preinstalled in IoT devices to achieve higher efficiency, such as face recognition, area detection, target tracking, etc. Tracking is an important but complex task that needs high efficiency solutions in real applications. There is a common assumption that detection can only represent one pedestrian to describe nonoverlapping in physical space. In fact, the pixels of the image do not exactly correspond to the positions in the real world. In order to overcome the limitation of this assumption, we remove this unreasonable assumption and present a novel idea that each detector response can have multiple labels to describe different targets at the same time. Therefore, we propose a graph-based method for near-online tracking in this article. We introduce a detection multiplexing method for tracking in the monocular image and propose a multiplex labeling graph (MLG) model. Each node in MLG has the ability to represent multiple targets. In addition, we improve the shortage of graph-based trackers in using temporal features. We construct long short-term memory networks to model motion and appearance features for MLG optimization. On the public multiobject tracking challenge benchmark, our near-online method gains satisfactory efficiency and achieves state-of-the-art results without additional private detection as well.

Zhou J., Yi T., Zhang Z., Yu D., Liu P., Wang L., Zhu Y.

Structural polymeric nanohybrids is presently a popular topic and can be conceived for numerous functional applications, including the pH-sensitive oral colon-targeted drug-delivery system. In this paper, a brand-new Janus core@shell (JCS) nanostructure was fabricated using a trifluid electrospinning, in which three polymers and a model drug 5-fluorouracil (5-FU) were elaborately and intentionally positioned. In the structural hybrids, the pH-sensitive polymer hydroxypropyl methyl cellulose acetate succinate was located in the common shell layer, and the 5-FU-loaded ethyl cellulose (EC) and polyethylene oxide (PEO) were organized in a side-by-side manner in the core sections. The JCS fiber had a fine linear morphology with a multiple-chamber structure and a shell thickness of about 24 nm. The drug presented in the fibers in an amorphous state, owing to the secondary intermolecular interactions between EC and 5-FU. The ex vivo adhesion experiments suggested that the JCS fibers could stick firmly to the intestine membranes. In vitro dissolution tests showed the JCS fibers released only 7.8% ± 3.5% of the loaded 5-FU in an acid condition. In vivo gavage administration verified that the JCS fibers effectively promoted the absorbance of 5-FU in a synergistic manner, better than the double-layer core–shell and Janus nanofibers, and near fourfold than the drug solutions as a control. The present protocol opens a new way for developing novel multifunctional nanomaterials with the JCS nanostructure as a powerful supporting platform.

Wang Z., Pan H., Sun H., Kang Y., Liu H., Cao D., Hou T.

Abstract Predicting the native or near-native binding pose of a small molecule within a protein binding pocket is an extremely important task in structure-based drug design, especially in the hit-to-lead and lead optimization phases. In this study, fastDRH, a free and open accessed web server, was developed to predict and analyze protein–ligand complex structures. In fastDRH server, AutoDock Vina and AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA free energy calculation procedures and multiple poses based per-residue energy decomposition analysis were well integrated into a user-friendly and multifunctional online platform. Benefit from the modular architecture, users can flexibly use one or more of three features, including molecular docking, docking pose rescoring and hotspot residue prediction, to obtain the key information clearly based on a result analysis panel supported by 3Dmol.js and Apache ECharts. In terms of protein–ligand binding mode prediction, the integrated structure-truncated MM/PB(GB)SA rescoring procedures exhibit a success rate of &gt;80% in benchmark, which is much better than the AutoDock Vina (~70%). For hotspot residue identification, our multiple poses based per-residue energy decomposition analysis strategy is a more reliable solution than the one using only a single pose, and the performance of our solution has been experimentally validated in several drug discovery projects. To summarize, the fastDRH server is a useful tool for predicting the ligand binding mode and the hotspot residue of protein for ligand binding. The fastDRH server is accessible free of charge at http://cadd.zju.edu.cn/fastdrh/.

Sheng H., Chen J., Zhang Y., Ke W., Xiong Z., Yu J.

This paper proposes a novel iterative maximum weighted independent set (MWIS) algorithm for multiple hypothesis tracking (MHT) in a tracking-by-detection framework. MHT converts the tracking problem into a series of MWIS problems across the tracking time. Previous works solve these NP-hard MWIS problems independently without the use of any prior information from each frame, and they ignore the relevance between adjacent frames. In this paper, we iteratively solve the MWIS problems by using the MWIS solution from the previous frame rather than solving the problem from scratch each time. First, we define five hypothesis categories and a hypothesis transfer model, which explicitly describes the hypothesis relationship between adjacent frames. We also propose a polynomial-time approximation algorithm for the MWIS problem in MHT. In addition to that, we present a confident short tracklet generation method and incorporate tracklet-level association into MHT, which further improves the computational efficiency. Our experiments on both MOT16 and MOT17 benchmarks show that our tracker outperforms all the previously published tracking algorithms on both MOT16 and MOT17 benchmarks. Finally, we demonstrate that the polynomial-time approximate tracker reaches nearly the same tracking performance.

Tai Z., Huang Y., Zhu Q., Wu W., Yi T., Chen Z., Lu Y.

• Properties of particle stabilizers are crucial to construct Pickering emulsions. • Pickering emulsions enhance bioavailability or bioaccessibility of drugs. • Controllable release and high stability relate to the interfacial particles. • Digestion can be tailored by tuning the properties of the particle stabilizers. Pickering emulsions are surfactant-free emulsions stabilized by solid particles. Their unique structure endows them with good stability, excellent biocompatibility, and environmental friendliness. Pickering emulsions have displayed great potential in oral drug delivery. Several-fold increases in the oral bioavailability or bioaccessibility of poorly soluble drugs, such as curcumin, silybin, puerarin, and rutin, were achieved by using Pickering emulsions, whereas controlled release was found for indomethacin and caffeine. The shell of the interfacial particle stabilizers provides enhanced gastrointestinal stability to the cargos in the oil core. Here, we also discuss general considerations concerning particle stabilizers and design strategies to control lipid digestion.