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Hemicelluloses, a major component of plant cell walls, are a non-cellulosic heteropolysaccharide composed of several distinct sugars that is second in abundance to cellulose, which are one of the most abundant and cheapest renewable resources on earth. Hemicelluloses structure is complex and its chemical structure varies greatly among the different plant species. In addition to its wide use in production of feed and other chemical materials, hemicelluloses are known for its remarkable biological activities that remain largely underutilised to date. Therefore, comprehensive investigations of hemicelluloses structural and biological properties would be helpful for achieving rational utilisation and high-value conversion of this underutilised substance into agents with enhanced health benefits for incorporation in drugs and health foods. In this review, details of diverse research initiatives that have enhanced our understanding of hemicelluloses properties are summarised, including hemicelluloses sources, extraction and purification methods, structural characteristics and biological activities. Furthermore, hemicelluloses structure-activity relationships and new directions for future hemicelluloses research studies are discussed.

Drug-induced prolongation of the QT interval is common in a variety of pharmaceutical treatments and can lead to serious clinical outcomes. Although substantial efforts have been made to prevent drug-induced QT interval prolongation, the lack of a centralized data source remains the main obstacle to further study of the underlying mechanism and the development of effective prediction strategies. To fill this gap, we propose a schema for stratifying the risk of marketed QT prolonging drugs based on US Food and Drug Administration (FDA)-approved drug labeling and developed a Drug-Induced QT Prolongation Atlas (DIQTA). Potential application of DIQTA was shown by precision dosing in off-label use and therapeutic strategy optimization, as well as the facilitation of artificial intelligence (AI)-based modeling in predictive toxicity.

The disparity map produced by matching a pair of rectified stereo images provides estimated depth information and accurate distance calculations for autonomous driving. For most stereo matching networks, cost volume plays a crucial role in the accuracy of disparity maps. To increase the accuracy of disparity maps, an improved cost volume method called multi‐information cost volume (MICV) is proposed, with the fusion of concatenation volume and improved correlation volume, which is calculated both in inner product space and Euclidean space, to measure the correlation similarity between features in the left and right images. The inclusion of a squeeze and excitation (SE) module further improves MICV by adjusting the contribution of the correlation volume. To refine the disparity map and enhance the semantics of small objects, a cascade stereo network called CSNet is proposed, with a dilation feature fusion unit (DFFU) to calculate and integrate disparity maps from three different scale branches. The smaller scale branches are gradually integrated into the larger scale branches to implement the transmission of semantic information. The proposed method was evaluated using several established benchmarks including the Sceneow, KITTI2012 and KITTI2015 datasets. Experimental results demonstrate that authors' method produces more accurate disparity maps compared with existing state‐of‐the‐art methods.

Due to their known health-enhancing properties, Laminaria japonica polysaccharides (LJP) may alleviate obesity via unknown mechanisms. This study aimed to investigate beneficial LJP effects and mechanism(s) of action using an animal obesity model (ICR mice fed a high-fat diet). First, LJP were confirmed to consist of sulfated polysaccharides via infrared spectroscopy. Next, LJP administration to mice was found to induce weight loss, reduce liver fat accumulation, and support healthy obesity-related blood serum indicator levels. Notably, LJP treatment significantly reduced TC and LDL levels and significantly increased HDL, LPL, UCP-2, and PPAR-α levels. Furthermore, examinations of tissues of LJP-treated mice revealed significantly reduced intestinal tissue inflammation as compared to corresponding results obtained for untreated obese controls. Additionally, LJP treatment relieved colonic shortening and reduced colonic levels of inflammatory factors TNF-α and IL-6. Further exploration of LJP treatment effects on mouse gut microbiota conducted via fecal 16S rRNA gene sequence-based gut microbiome profiling analysis revealed that LJP treatment increased the Bacteroidetes/Firmicutes ratio and increased gut abundances of probiotics Bacteroides acidifaciens, s_Lactobacillus intestinalis, and s_Lactobacillus murinus. In conclusion, these results collectively suggest that LJP use as a food supplement may alleviate obesity and related gut microbiota dysbiosis and intestinal inflammatory disorders.

The excitatory neurons of the medial prefrontal cortex (mPFC) respond to social stimuli. However, little is known about how the neural activity is altered during social avoidance, and whether it could act as a target of low-intensity focused ultrasound stimulation (LIFUS) to rescue social deficits. The present study aimed to investigate the mechanisms of neuronal activities and inflammatory responses underlying the effect of LIFUS on social avoidance. We found that chronic LIFUS stimulation can effectively improve social avoidance in the defeated mice. Calcium imaging recordings by fiber photometry in the defeated mice showed inhibited ensemble activity during social behaviors. LIFUS instantaneously triggered the mPFC neuronal activities, and chronic LIFUS significantly enhanced their neuronal excitation related to social interactions. We further found that the excessive activation of microglial cells and the overexpression of the inflammation signaling, i.e. Toll-like receptors(TLR4)/nuclear factor-kappaB(NF-КB), in mPFC were significantly inhibited by LIFUS. These results suggest that the LIFUS may inhibit social avoidance behavior by reducing activation of the inflammatory response, increasing neuronal excitation, and protecting the integrity of the neuronal structure in the mPFC. Our findings raised the possibility of LIFUS being applied as novel neuromodulation for social avoidance treatment in neuropsychiatric diseases.

Drug-induced rhabdomyolysis (DIR) is a rare and potentially life-threatening muscle injury that is characterized by low incidence and high risk. To our best knowledge, the performance of the current predictive models for the early detection of DIR is suboptimal because of the scarcity and dispersion of DIR cases. Therefore, on the basis of the curated drug information from the Drug-Induced Rhabdomyolysis Atlas (DIRA) database, we proposed a random forest (RF) model to predict the DIR severity of the marketed drugs. Compared with the state-of-art methods, our proposed model outperformed extreme gradient boosting, support vector machine, and logistic regression in distinguishing the Most-DIR concern drugs from the No-DIR concern drugs (Matthews correlation coefficient (MCC) and recall rate of our model were 0.46 and 0.81, respectively). Our model was subsequently applied to predicting the potentially serious DIR for 1402 drugs, which were reported to cause DIR by the postmarketing DIR surveillance data in the FDA Spontaneous Adverse Events Reporting System (FAERS). As a result, 62.7% (94) of drugs ranked in the top 150 drugs with the Most-DIR concerns in FAERS can be identified by our model. The top four drugs (odds ratio >30) including acepromazine, rapacuronium, oxyphenbutazone, and naringenin were correctly predicted by our model. In conclusion, the RF model can well predict the Most-DIR concern drug only based on the chemical structure information and can be a facilitated tool for early DIR detection.

Panax ginseng C. A. Meyer (P. ginseng) has a long history of medicinal use and can treat a variety of diseases. P. ginseng contains a variety of active ingredients, such as saponins, polypeptides, volatile oils, and polysaccharides. Among them, saponins have always been considered as the main components responsible for its pharmacological activities. However, more and more studies have shown that polysaccharides play an indispensable role in the medicinal value of ginseng. Modern biological and medical studies have found that ginseng polysaccharides have complex structural characteristics and diverse biological activities, such as immune regulation, anti-tumor, antioxidant, hypoglycemic, and anti-radiation functions, among others. Additionally, the structural characteristics of ginseng polysaccharides are closely related to their activity. In this review, the research background, extraction, purification, structural characteristics, and biological activities of ginseng polysaccharides from different parts of P. ginseng (roots, flowers stems and leaves, and berries) under different growth conditions (artificially cultivated ginseng, mountain ginseng, and wild ginseng) are summarized. The structural characteristics of purified polysaccharides were reviewed. Meanwhile, their biological activities were introduced, and some possible mechanisms were listed. Furthermore, the structure–activity relationship of polysaccharides was discussed. Some research perspectives for the study of ginseng polysaccharides were also provided.

Two sets of BAF - ozonation systems, with (System-A) and without (System-B) Fe

The time synchronization system which uses the BeiDou and GPS as double clock source can receive GPS and the BeiDou satellite signal. The system built-in constant temperature crystal clock or rubidium clock utilizes the "BeiDou bidirectional synchronization method" technology and advanced control algorithm. The core control processor using STM32 chip with high performance, which can achieve multi-sources timing intelligent switching. The multi-sources timing not only enhanced the reliability of the system, but also enhance the security of the whole system. It can ensure the power system synchronization and also synchronize the whole network time in large area.

The spectrum characteristic of the chaotic signal was very important for the communication system, which could provide necessary protection for the information. A chaotic system design method was introduced to generate a chaotic signal which has and wide bandwidth in which the spectral components have large power. This new system is constructed by adding a high-order feedback to the classical chaotic system, so that new trapping region is introduced to the new chaotic system. Because of the high-order feedback, the dynamic behavior is more complex than the original chaotic system, and the large power spectrum components of the chaotic signal are extended to high frequency. The efficiency of the method was shown by analysis and simulation. The new signal was suitable for secure communication systems.