Plumbagin protects H9c2 cardiomyocytes against TBHP-induced cytotoxicity by alleviating ROS-induced apoptosis and modulating autophagy.

Plumbagin (PLB) has been previously reported to alleviate myocardial ischemia/reperfusion injury in vivo. In the present study, the potential of plumbagin to protect against hydrogen peroxide-induced injury in cardiomyocytes was analyzed. Specifically, the cytoprotective effects of PLB were evaluated in H9c2 cardiomyocytes, in which oxidative stress was induced by tertiary butyl hydrogen peroxide (TBHP; 75 µM) treatment. After the cardiomyocytes were treated with different concentrations of PLB, cell viability, creatine kinase (CK) activity and lactate dehydrogenase (LDH) release were determined. The apoptosis rate and reactive oxygen species (ROS) levels were evaluated by flow cytometry. Western blot analyses of cleaved caspase-3, nicotinamide adenine dinucleotide phosphate (NADPH) oxidase enzyme 4 (NOX4), and phosphorylated (p)-p38 mitogen-activated protein kinase (MAPK) were performed. PLB pretreatment (5, 10 or 20 µM) restored TBHP-treated H9c2 cell viability (P<0.01). Additionally, PLB significantly decreased CK (P<0.01) and LDH activity (P<0.01). TBHP induced apoptosis and oxidative stress in cardiomyocytes, whereas PLB pretreatment significantly reduced the TBHP-induced apoptosis rate (P<0.01) and ROS levels (P<0.01). Furthermore, PLB resulted in a decrease in the expression of cleaved caspase-3, NOX4, and p-p38 MAPK in TBHP-treated H9c2 cells. The active marker of autophagosomes, LC3-II/LC3-I, was increased following treatment with PLB, indicating the induction of autophagy. The present study revealed the protective role of PLB against TBHP-induced cardiomyocyte injury via the alleviation of ROS-mediated apoptosis and induction of autophagy.

Bacterial communities in home-made Doushen with and without chili pepper.

Doushen is a traditional Chinese fermented soybean product prepared with sterilizated soybeans under open conditions. However, little is known on the bacterial community and their influence on the flavor of Doushen. In the present study, Doushen samples with and without chili pepper were collected to reveal the bacterial community and assess a correlation between bacterial community and VFCs in the two kinds of Doushen samples. We identified four phyla and 97 bacterial genera in the two kinds of Doushen samples. In addition, a total of 17 significantly different OTUs were detected by LEfSe (Line Discriminant Analysis (LDA) Effect Size). Results of Principal coordinates analysis (PCoA), unweighted pair-group method (UPGMA) and functional and phenotypes prediction showed that bacterial communities in the two kinds of Doushen were significantly different. Spearman correlation analysis showed that all the dominant genera, except Clostridium Sensu stricto 1, were significantly correlated with the characteristic VFCs. This study provides a theoretical basis for improving the flavour quality of traditional homemade Doushen.

An inner-filter-effect based ratiometric fluorescent sensor for the detection of uranyl ions in real samples.

In this work, a ratiometric fluorescence system was designed for the detection of trace UO22+ in water based on the inner filter effect (IFE) between gold nanoparticles (AuNPs) and gold nanoclusters (AuNCs). IFE-induced fluorescence quenching was achieved due to the enhanced complementary overlap between the absorption spectra of AuNPs and the emission spectrum of AuNCs after the addition of UO22+. Blue carbon dots (B-CDs) were added to serve as reference fluorophores to expand the color tonality and make human eye recognition easier. The ratiometric fluorescent sensor demonstrated a unique fluorescence color change from red to blue when different doses of UO22+ were added, with a detection limit of 8.4 nM. Furthermore, the ratiometric fluorescent sensor was effectively used for UO22+ determination in real-world water samples, with acceptable recoveries.

Influence of Tissue Type on the Bacterial Diversity and Community in Pork Bacon.

In current study, bacterial diversity and community in different tissues of pork bacon were determined using high-throughput sequencing. In total, six phyla and 111 bacterial genera were identified. Among them, three dominant genera (Staphylococcus, Acinetobacter, and Macrococcus) were shared by all bacon samples. The linear discriminant analysis showed that 24 bacterial taxa significantly differentiated between the tissues. Results of non-metric Multidimensional Scaling and redundancy analysis showed that physicochemical characteristics of the tissue prominently structured the bacterial communities. Network analysis also illustrated that tissue type was an important factor impacting the bacterial interactions in different types of tissue. The results of current study can add valuable insights to the traditional homemade pork bacon.

A Real-Time Fire Detection Method from Video with Multifeature Fusion.

The threat to people's lives and property posed by fires has become increasingly serious. To address the problem of a high false alarm rate in traditional fire detection, an innovative detection method based on multifeature fusion of flame is proposed. First, we combined the motion detection and color detection of the flame as the fire preprocessing stage. This method saves a lot of computation time in screening the fire candidate pixels. Second, although the flame is irregular, it has a certain similarity in the sequence of the image. According to this feature, a novel algorithm of flame centroid stabilization based on spatiotemporal relation is proposed, and we calculated the centroid of the flame region of each frame of the image and added the temporal information to obtain the spatiotemporal information of the flame centroid. Then, we extracted features including spatial variability, shape variability, and area variability of the flame to improve the accuracy of recognition. Finally, we used support vector machine for training, completed the analysis of candidate fire images, and achieved automatic fire monitoring. Experimental results showed that the proposed method could improve the accuracy and reduce the false alarm rate compared with a state-of-the-art technique. The method can be applied to real-time camera monitoring systems, such as home security, forest fire alarms, and commercial monitoring.

A Literature Review: Geometric Methods and Their Applications in Human-Related Analysis.

Geometric features, such as the topological and manifold properties, are utilized to extract geometric properties. Geometric methods that exploit the applications of geometrics, e.g., geometric features, are widely used in computer graphics and computer vision problems. This review presents a literature review on geometric concepts, geometric methods, and their applications in human-related analysis, e.g., human shape analysis, human pose analysis, and human action analysis. This review proposes to categorize geometric methods based on the scope of the geometric properties that are extracted: object-oriented geometric methods, feature-oriented geometric methods, and routine-based geometric methods. Considering the broad applications of deep learning methods, this review also studies geometric deep learning, which has recently become a popular topic of research. Validation datasets are collected, and method performances are collected and compared. Finally, research trends and possible research topics are discussed.

Neo4j graph database realizes efficient storage performance of oilfield ontology.

The integration of oilfield multidisciplinary ontology is increasingly important for the growth of the Semantic Web. However, current methods encounter performance bottlenecks either in storing data and searching for information when processing large amounts of data. To overcome these challenges, we propose a domain-ontology process based on the Neo4j graph database. In this paper, we focus on data storage and information retrieval of oilfield ontology. We have designed mapping rules from ontology files to regulate the Neo4j database, which can greatly reduce the required storage space. A two-tier index architecture, including object and triad indexing, is used to keep loading times low and match with different patterns for accurate retrieval. Therefore, we propose a retrieval method based on this architecture. Based on our evaluation, the retrieval method can save 13.04% of the storage space and improve retrieval efficiency by more than 30 times compared with the methods of relational databases.

Human Pose Estimation from Monocular Images: A Comprehensive Survey.

Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used.