Microplastics are ubiquitous in marine environments. Sediments and marine organisms are recognized as the carriers and final destinations of microplastics. However, research on the concentration and ...abundance of microplastics in deep-sea sediments and organisms is limited. In this study, samples of sediments and organisms were collected from deep-sea locations of the western Pacific Ocean, with the depth ranging from 4601 m to 5732 m. Microplastics were extracted from the samples and analyzed by micro-Fourier-transform infrared spectroscopy. The average abundance of microplastics in the sediments was 240 items per kg dry weight of sediment. The microplastics were predominantly fibrous in shape (52.5%), blue in color (45.0%), and less than 1 mm in size (90.0%). The most commonly detected polymers were poly(propylene-ethylene) copolymer (40.0%) and polyethylene terephthalate (27.5%). The concentrations of polychlorinated biphenyls (PCBs), which are representatives of persistent organic pollutants, in the pore water of sediment samples were also investigated. A significant correlation between the distribution of microplastics and the PCB concentrations in sediments was found (P = 0.016). Microplastics were also detected in deep-sea organisms (i.e., Crinoidea, Pheronematidae, Ophiuroidea, and Gammaridea) in the sampling region, with an abundance of 0–3 items per individual biological sample. This assessment of microplastics in deep-sea sediments and benthic organisms of the western Pacific Ocean confirms that microplastic pollution exists in the deep-sea ecosystems of this region.
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•Microplastics in western Pacific deep-sea sediments and organisms were quantified.•Microplastics found were classified by shape, color, and size.•PP-PE and PET were the predominant types of polymers.•PCB concentration in sediment pore water was correlated to microplastic abundance.
The microplastic pollution in deep-sea sediments and organisms of the western Pacific Ocean were investigated.
At the present stage, the evaluation of human motor function is mainly semi-quantitative, which only evaluates the overall motor function from the degree of joint mobility and muscle status, but the ...size of muscle strength cannot be obtained by direct measurement. In this paper, we take the muscle activation degree and joint angle of college students in traditional archery programs based on “functional training” as the experimental objects and establish a muscle strength prediction model based on a generalized dynamic fuzzy neural network (GD-FNN). By analyzing the relationship between the surface electromyographic signals and muscle strength under elbow flexion and extension, we selected suitable parameters as the sample data of the fuzzy neural network and proposed a learning algorithm based on the variable sliding window of the GD-FNN. The predicted muscle force was compared with the desired muscle force of the main flexion and extension muscles through the subjects’ elbow flexion exercise and extension exercise. The normalized root-mean-square error between the predicted and actual muscle strength of the algorithm in this paper is less than 0.2. Compared with the maximal strength test, the peak extensor moments (right) and peak extensor moments (left) of the college athletes before and after the functional training, the mean values increased by 30.6 N.m and 42.39 N.m, respectively. Compared with the metabolism of the students during the ordinary training of 2.74 met based on the “functional training” of traditional archery increased, students’ metabolism to 5.03 met. It shows that functional training is favorable to the muscle strength of traditional archery college students and has a positive effect on the metabolic capacity of the body.
Efficient signal amplification strategies are crucial for ultrasensitive detection of tumor markers. Herein, a new signal amplification strategy by coupling cascade catalysis-initiated radical ...polymerization with impedimetric immunoassay was proposed for ultrasensitive detection of carbohydrate antigen 15–3 (CA15-3). Copper-based metal-organic framework nanoparticles (Cu-MOF), as peroxidase mimics, combined with CA15-3 antibody (Ab2) and glucose oxidase (GOx) were employed as immunoprobes to initiate radical polymerization by cascade catalysis. In this work, the oxidation of glucose was catalyzed by GOx to generate hydrogen peroxide (H2O2), which reacted with acetylacetone (ACAC) via Cu-MOF catalysis to yield ACAC radicals for the polymerization of N-isopropylacrylamide (NIPAM). The polymer, poly (N-isopropylacrylamide) (PNIPAM), was generated in situ from the radical polymerization. As resistance enhancer, PNIPAM was covered on electrode surface to amplify resistance value by its poor conductivity. With the help of polymerization-based amplification, the resistance differences caused by target were improved significantly. Under optimum conditions, the designed biosensor showed wide detection ranges from 10 μU/mL to 10 mU/mL and 10 mU/mL to 100 U/mL, with ultralow detection limit of 5.06 μU/mL for CA15-3. Such an approach opened a new avenue for signal amplification, thus offering an ultrasensitive detection platform for a broad range of tumor markers.
•Ultrasensitive impedimetric immunosensor was designed for CA15-3 detection.•A new immunoprobe composed of Cu-MOF, GOx and antibody was fabricated.•The immunoprobe triggered radical polymerization to amplify resistance.
Highlights • Warburg effect is known as a hallmark of cancer and targeting this process is a promising therapeutic method. • 2-Deoxy-D-glucose is an effective glycolytic inhibitor and also exhibits ...other metabolic functions. • 2-Deoxy-D-glucose mono-therapy is inefficient in inducing death to some cell types leading to the come-up of combined therapies. • 2-Deoxy-D-glucose is generally considered to be a safe agent for clinical use.
High rock stress and ground temperature pose great threats to the routine production of longwall top coal caving (LTCC) panels. In this risky condition, the width of the chain pillar is considered a ...factor adjustable for controlling coal burst and goaf ignition hazards. However, a contradiction, as suggested by longwall experience, is that narrowing the pillar helps coal burst prevention but negatively leads to higher self-ignition potentials, while widening the pillar restrains goaf ignition but increases the likelihood of coal burst. This paper conducted a case study on a longwall panel from Tangkou Mine, China. The paper first analysed stress, elastic strain energy, and goaf temperature variation with varying pillar widths, by which the coal burst risk index δr and goaf ignition risk index Qs were defined and correlated to pillar width D. Further, a pillar width determination method considering coal burst and goaf ignition dual-hazard management was developed by means of the operating point principle. By this method, a reasonable width range was defined by plotting both correlation curves δr=f(D) and Qs=g(D) on a chart, followed by optimal width determination according to the intersection of both curves and further verification via a field trial.
Metabolic reprogramming is reported to be one of the hallmarks of cancer, which is an adaptive mechanism by which fast-growing cancer cells adapt to their increasing energy demands. Recently, ...extracellular vesicles (EVs) known as exosomes have been recognized as crucial signaling mediators in regulating the tumor microenvironment (TME). Meanwhile, the TME is a highly heterogeneous ecosystem incorporating cancer cells, fibroblasts, adipocytes, endothelial cells, mesenchymal stem cells, and extracellular matrix. Accumulated evidence indicates that exosomes may transfer biologically functional molecules to the recipient cells, which facilitate cancer progression, angiogenesis, metastasis, drug resistance, and immunosuppression by reprogramming the metabolism of cancer cells and their surrounding stromal cells. In this review, we present the role of exosomes in the TME and the underlying mechanism of how exosomes exacerbate tumor development through metabolic reprogramming. In addition, we will also discuss the potential role of exosomes targeting metabolic process as biomarkers for tumor diagnosis and prognosis, and exosomes-mediated metabolic reprogramming as potential targets for cancer therapy. Furthermore, a better understanding of the link between exosomes and metabolic reprogramming, and their impact on cancer progression, would provide novel insights for cancer prevention and treatment in the future.
An optical system for measuring the coefficient of thermal expansion (CTE) of materials has been developed based on electronic speckle interferometry. In this system, the temperature can be varied ...from -60°C to 180°C with a Peltier device. A specific specimen geometry and an optical arrangement based on the Michelson interferometer are proposed to measure the deformation along two orthogonal axes due to temperature changes. The advantages of the system include its high sensitivity and stability over the whole range of measurement. The experimental setup and approach for estimating the CTE was validated using an Aluminum alloy. Following this validation, the system was applied for characterizing the CTE of carbon fiber reinforced composite (CFRP) laminates. For the unidirectional fiber reinforced composites, the CTE varied with fiber orientation and exhibits anisotropic behavior. By stacking the plies with specific angles and order, the CTE of a specific CFRP was constrained to a low level with minimum variation temperature. The optical system developed in this study can be applied to CTE measurement for engineering and natural materials with high accuracy.
Cloud detection is a key step in the preprocessing of optical satellite remote sensing images. In the existing literature, cloud detection methods are roughly divided into threshold methods and ...deep-learning methods. Most of the traditional threshold methods are based on the spectral characteristics of clouds, so it is easy to lose the spatial location information in the high-reflection area, resulting in misclassification. Besides, due to the lack of generalization, the traditional deep-learning network also easily loses the details and spatial information if it is directly applied to cloud detection. In order to solve these problems, we propose a deep-learning model, Cloud Detection UNet (CDUNet), for cloud detection. The characteristics of the network are that it can refine the division boundary of the cloud layer and capture its spatial position information. In the proposed model, we introduced a High-frequency Feature Extractor (HFE) and a Multiscale Convolution (MSC) to refine the cloud boundary and predict fragmented clouds. Moreover, in order to improve the accuracy of thin cloud detection, the Spatial Prior Self-Attention (SPSA) mechanism was introduced to establish the cloud spatial position information. Additionally, a dual-attention mechanism is proposed to reduce the proportion of redundant information in the model and improve the overall performance of the model. The experimental results showed that our model can cope with complex cloud cover scenes and has excellent performance on cloud datasets and SPARCS datasets. Its segmentation accuracy is better than the existing methods, which is of great significance for cloud-detection-related work.
Large-scale underground mining of shallow coal seams can have significant impacts on ground surface and potentially leads to incidental damage to the overlying aquifer with subsequent environmental ...hazards. In order to deal with the apparent conflict between water protection and high production in underground mining, an aquifer protection mining technique was trialed in panel #51201 in the Shangwan colliery, the Shendong Coalfield, China. Overburden failure, water level of the unconsolidated aquifer, surface cracks, and ground subsidence were monitored in a series of boreholes using borescope, and also by observations in a nearby water well and by surface surveys. Monitoring results indicate that the aquifer protection mining technique can be successfully applied by modifying a few mining parameters such as mining height or advance rate under some suitable geological conditions. The critical zone in the stratigraphy appears to be the weathered bedrock located immediately below the aquifer. The weathered bedrock will remain impermeable after mining as long as its thickness is greater than the mining height. The development of the mining-induced overburden failure is affected by the key strata but ultimately controlled by the soft aquiclude such as the weathered zone. It was observed respectively that the height of the caved zone was observed to be 5 to 6 times the mining height, whilst the height of the fractured zone is about 10 to 11 times the mining height.
► Aquifer protection mining can be successfully applied by some adjustments. ► The crack development is finally controlled by the soft aquiclude. ► The weathered bedrock zone will remain impermeable after mining. ► Key strata and weathered zone affect the aquifer protection mining in geology.
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