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Enchytraeus bulbosus is listed in the ISO and OECD standard guidelines as a possible test species of enchytraeid. However, in contrast to other listed species, its applicability in ecotoxicological studies as well as its sensitivity is widely unknown. Therefore, copper, pentachlorophenol(PCP), carbendazim, and chloroacetamide have been investigated by performing two-generation studies with multiple endpoints. Comparable toxicity trends to the existing studies were shown for copper and PCP in the two-generation studies of E. bulbosus. Dose-related abnormal swelling of clitella were found for the first time with PCP and chloroacetamide treatments. Sensitivity comparisons of E. bulbosus to other terrestrial test species were also conducted. E. bulbosus showed high sensitivity, it has comparable sensitivity as other sensitive species of genus Enchytraeus ( E. albidus or E. luxuriosus)to different chemicals, and was more sensitive than E. crypticus and earthworm species ( Eisenia fetida or Eisenia andrei). Combined with the phylogenetic and biological characterization, the results lead to the conclusion that E.bulbosus is a suitable model species in ecotoxicology and the chemical risk assessment (especially in multi-generation) because it has a short generation time, comparatively moderate fecundity, ideal and reasonable sensitivity.
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State-of-the-art no-reference image quality assessment methods usually learn to evaluate image quality by regression from the human subjective scores of a training set. Their dependence on the regression algorithm and human subjective scores may limit the practical application of such methods. In this paper, we propose a completely blind image quality assessment method that is highly unsupervised and training free. We first use a specific image primitive to analyze the image gray-scale fluctuation and use this result as one of the image quality assessment features. The box-counting method is then used to evaluate the image fractal dimension, and the result is used as the other feature. Finally, the two features are combined together, and a formula is introduced to calculate a comprehensive image quality feature, which is used to measure the image quality. Experimental results on four open databases show that the newly proposed method correlates well with the human subjective judgments of diversely distorted images.
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Electronic skin (e-skin), a skin-like wearable electronic device, holds great promise in the fields of telemedicine and personalized healthcare because of its good flexibility, biocompatibility, skin conformability, and sensing performance. E-skin can monitor various health indicators of the human body in real time and over the long term, including physical indicators (exercise, respiration, blood pressure, etc.) and chemical indicators (saliva, sweat, urine, etc.). In recent years, the development of various materials, analysis, and manufacturing technologies has promoted significant development of e-skin, laying the foundation for the application of next-generation wearable medical technologies and devices. Herein, the properties required for e-skin health monitoring devices to achieve long-term and precise monitoring and summarize several detectable indicators in the health monitoring field are discussed. Subsequently, the applications of integrated e-skin health monitoring systems are reviewed. Finally, current challenges and future development directions in this field are discussed. This review is expected to generate great interest and inspiration for the development and improvement of e-skin and health monitoring systems.
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Dispositivos Electrónicos Vestibles , Humanos , Monitoreo Fisiológico/instrumentación , Monitoreo Fisiológico/métodos , Piel , Telemedicina/instrumentaciónRESUMEN
The complexity and challenging underwater environment leading to degradation in underwater image. Measuring the quality of underwater image is a significant step for the subsequent image processing step. Existing Image Quality Assessment (IQA) methods do not fully consider the characteristics of degradation in underwater images, which limits their performance in underwater image assessment. To address this problem, an Underwater IQA (UIQA) method based on color space multi-feature fusion is proposed to focus on underwater image. The proposed method converts underwater images from RGB color space to CIELab color space, which has a higher correlation to human subjective perception of underwater visual quality. The proposed method extract histogram features, morphological features, and moment statistics from luminance and color components and concatenate the features to obtain fusion features to better quantify the degradation in underwater image quality. After features extraction, support vector regression(SVR) is employed to learn the relationship between fusion features and image quality scores, and gain the quality prediction model. Experimental results on the SAUD dataset and UIED dataset show that our proposed method can perform well in underwater image quality assessment. The performance comparisons on LIVE dataset, TID2013 dataset,LIVEMD dataset,LIVEC dataset and SIQAD dataset demonstrate the applicability of the proposed method.
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Video hashing learns compact representation by mapping video into low-dimensional Hamming space and has achieved promising performance in large-scale video retrieval. It is challenging to effectively exploit temporal and spatial structure in an unsupervised setting. To fulfill this gap, this paper proposes Contrastive Transformer Hashing (CTH) for effective video retrieval. Specifically, CTH develops a bidirectional transformer autoencoder, based on which visual reconstruction loss is proposed. CTH is more powerful to capture bidirectional correlations among frames than conventional unidirectional models. In addition, CTH devises multi-modality contrastive loss to reveal intrinsic structure among videos. CTH constructs inter-modality and intra-modality triplet sets and proposes multi-modality contrastive loss to exploit inter-modality and intra-modality similarities simultaneously. We perform video retrieval tasks on four benchmark datasets, i.e., UCF101, HMDB51, SVW30, FCVID using the learned compact hash representation, and extensive empirical results demonstrate the proposed CTH outperforms several state-of-the-art video hashing methods.
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Geographic origins play a vital role in traditional Chinese medicinal materials. Using the geo-authentic crude drug can improve the curative effect. The main producing areas of Chinese wolfberry are Ningxia, Gansu, Qinghai, and so on. The geographic origin of Chinese wolfberry can affect its texture, shape, color, smell, nutrients, etc. However, the traditional method for identifying the geographic origin of Chinese wolfberries is still based on human eyes. To efficiently identify Chinese wolfberries from different origins, this paper presents an intelligent identification method for Chinese wolfberries based on color space transformation and texture morphological features. The first step is to prepare the Chinese wolfberry samples and collect the image data. Then the images are preprocessed, and the texture and morphology features of single wolfberry images are extracted. Finally, the random forest algorithm is employed to establish a model of the geographic origin of Chinese wolfberries. The proposed method can accurately predict the origin information of a single wolfberry image and has the advantages of low cost, fast recognition speed, high recognition accuracy, and no damage to the sample.
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BACKGROUND: Colorectal cancer (CRC) is one of the most common gastrointestinal malignancies. LncRNA CASC15 has also been found to play a vital role in malignant tumors. OBJECTIVE: Our objective is to explore the role of CASC15 in colorectal cancer and its regulation of EMT and to clarify the reasons for its up-regulated expression in CRC. METHODS: Quantitative real-time PCR was performed to evaluate the expression of CASC15 in CRC. The biology function of CASC15 on CRC was assessed by in vitro experiments, including CCK8, colony formation, transwell assays and flow cytometry. Luciferase reporter assays were used to confirm the regulation between TCF12 and CASC15. Quantitative real-time PCR and western blot analysis were used to evaluate the biomarkers associated with epithelial-mesenchymal transition (EMT). RESULTS: We found that CASC15 was remarkably upregulated in CRC and positively correlated with poorer relapse-free survival. CASC15 knockdown significantly suppressed the proliferation and migration of CRC. Furthermore, CASC15 downregulation mediated apoptosis of CRC. Mechanistically, TCF12 activates CASC15 transcription to mediate its up-regulation, which activates EMT and promotes CRC progression. CONCLUSION: Our study identified TCF12/CASC15/EMT as a new regulatory signal axis of CRC. CASC15 may be a new molecular marker and target for CRC.
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Transcranial magnetic stimulation (TMS) is a non-invasive brain neurostimulation technique that can be used as one of the adjunctive treatment techniques for neurological recovery after stroke. Animal studies have shown that TMS treatment of rats with middle cerebral artery occlusion (MCAO) model reduced cerebral infarct volume and improved neurological dysfunction in model rats. In addition, clinical case reports have also shown that TMS treatment has positive neuroprotective effects in stroke patients, improving a variety of post-stroke neurological deficits such as motor function, swallowing, cognitive function, speech function, central post-stroke pain, spasticity, and other post-stroke sequelae. However, even though numerous studies have shown a neuroprotective effect of TMS in stroke patients, its possible neuroprotective mechanism is not clear. Therefore, in this review, we describe the potential mechanisms of TMS to improve neurological function in terms of neurogenesis, angiogenesis, anti-inflammation, antioxidant, and anti-apoptosis, and provide insight into the current clinical application of TMS in multiple neurological dysfunctions in stroke. Finally, some of the current challenges faced by TMS are summarized and some suggestions for its future research directions are made.
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Structural colors from photonic crystals (PCs) have attracted emerging attention in the research area of wearable sensors. Conventional self-assembly of PC takes days to weeks. Here, a fast self-assembly method of PC with horizontal precipitation of silica nanoparticles (NPs) in a polydimethylsiloxane fence, which can be completed within 1-4 h depending on the fence parameters, is introduced. The resultant PC exhibits tunable structural colors in the entire visible spectrum. With infiltration of composite hydrogels containing acrylic acid, acrylamide, chitosan, and carbon nanotubes (CNTs) into the gaps of NPs to form an inverse opal PC, a structural color hydrogel that can quickly respond to different stimuli, including strain and temperature, is obtained. Moreover, with the addition of CNTs, the composite PC hydrogel can also output an electronic signal together with optical color changes. Based on these extraordinary responsive behaviors, the PC hydrogel sensor for quantitative feedback to external stimuli of stretching, bending, pressing, and thermal stimuli, with brilliant color change and electronic signal outputs simultaneously, is demonstrated. This fast-assembled PC hydrogel with excellent responsive properties has great potential for applications in wearable devices, mechanical sensors, temperature sensors, and colorimetric displays.
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Nanotubos de Carbono , Dispositivos Electrónicos Vestibles , Hidrogeles/química , Fotones , TemperaturaRESUMEN
BACKGROUND: The manual identification of Fructus Crataegi processed products is inefficient and unreliable. Therefore, efficient identification of the Fructus Crataegis' processed products is important. OBJECTIVE: In order to efficiently identify Fructus Crataegis processed products with different odor characteristics, a new method based on an electronic nose and convolutional neural network is proposed. METHODS: First, the original smell of Fructus Crataegis processed products is obtained by using the electronic nose and then preprocessed. Next, feature extraction is carried out on the preprocessed data through convolution pooling layer LCP1, convolution pooling layer LCP2 and a full connection layer LFC. Thus, the feature vector of the processed products can be obtained. Then, the recognition model for Fructus Grataegis processed products is constructed, and the model is trained to obtain the optimized parameters: filters F1 and F2, bias vectors B1, B2, B3, and B4, matrices M1 and M2. Finally, the features of the target processed products are extracted through the trained parameters to achieve accurate prediction. RESULTS: The experimental results show that the proposed method has higher accuracy for the identification of Fructus Crataegis processed products, and is competitive with other machine learning based methods. CONCLUSION: The method proposed in this paper is effective for the identification of Fructus Crataegi processed products.
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Medicamentos Herbarios Chinos/análisis , Nariz Electrónica , Redes Neurales de la Computación , Extractos Vegetales/análisis , CrataegusRESUMEN
Pore geometry plays a crucial role in determining the properties and functions of porous materials. Various methods have been developed to prepare porous materials that have randomly distributed or well-aligned pores. However, a technique capable of fine regulation of local pore orientation is still highly desired but difficult to attain. A technique, termed mold-assisted ice templating (MIT), is reported to control and program the local orientation of micropores. MIT employs a copper mold of a particular shape (for instance a circle, square, hexagon, or star) and a cold finger to regulate the 3D orientation of a local temperature gradient, which directs the growth of ice crystals; this approach results in the formation of finely regulated patterns of lamellar pore structures. Moreover, the lamellar thickness and spacing can be tuned by controlling the solution concentration.
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Small RNAs (sRNAs) are widespread and play major roles in regulation circuits in bacteria. Previously, we have demonstrated that transcription of esrE is under the control of its own promoter. However, the regulatory elements involved in EsrE sRNA expression are still unknown. In this study, we found that different cis-regulatory elements exist in the promoter region of esrE. We then screened and analyzed seven potential corresponding trans-regulatory elements by using pull-down assays based on DNA affinity chromatography. Among these candidate regulators, we investigated the relationship between the ferric uptake regulator (Fur) and the EsrE sRNA. Electrophoresis mobility shift assays (EMSAs) and ß-galactosidase activity assays demonstrated that Fur can bind to the promoter region of esrE, and positively regulate EsrE sRNA expression in the presence of Fe2+.
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Proteínas Bacterianas/genética , Escherichia coli/genética , Regulación Bacteriana de la Expresión Génica , Regiones Promotoras Genéticas , ARN Bacteriano/genética , Proteínas Represoras/genética , Transcripción GenéticaRESUMEN
OBJECTIVE: To investigate the risk factors for fulminant myocarditis by analyzing clinical symptoms/signs or laboratory findings in children with viral myocarditis. METHODS: The medical data of 71 children with acute viral myocarditis from March 2005 to September 2008 were retrospectively studied. They were classified into fulminant (n=16) and non-fulminant myocarditis groups (n=55). Chi-square and Student's t-test were used to analyze the clinical presentations, laboratory data, EEG and cardiac ultrasound findings on admission. The multiple regression analysis was used to identify the independent risk factors for fulminant myocarditis. RESULTS: Eight children (50%) died in the fulminant myocarditis group, but none in the non-fulminant group. The following factors were closely related to the fulminant course of myocarditis: lower blood pressure, higher serum CK-MB level, positive cTnI, complete atrioventricular block and left bundle branch block, ST segment alterations, prolonged QRS complex, and decreased left ventricular ejection fraction and short axis fractional shortening. Multiple regression analysis revealed that prolonged QRS complex (OR=1.139; CI=1.014-1.279, P<0.05) and decreased left ventricular ejection fraction (OR=0.711; CI=0.533-0.949, P<0.05) were independent risk factors for fulminant myocarditis. CONCLUSIONS: The mortality of fulminant myocarditis is high in children. Prolonged QRS complex and decreased left ventricular ejection fraction on admission are independent risk factors for fulminant myocarditis in children.
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Miocarditis/etiología , Enfermedad Aguda , Niño , Preescolar , Electrocardiografía , Femenino , Humanos , Lactante , Modelos Logísticos , Masculino , Factores de Riesgo , Función Ventricular IzquierdaRESUMEN
The yigP locus is widely conserved among γ-proteobacteria. Mutation of the yigP locus impacts aerobic growth of Gram-negative bacteria. However, the underlying mechanism of how the yigP locus influences aerobic growth remains largely unknown. Here, we demonstrated that the yigP locus in Escherichia coli encodes two transcripts; the mRNA of ubiquinone biosynthesis protein, UbiJ, and the 3' untranslated region small regulatory RNA (sRNA), EsrE. EsrE is an independent transcript that is transcribed using an internal promoter of the yigP locus. Surprisingly, we found that both the EsrE sRNA and UbiJ protein were required for Q8 biosynthesis, and were sufficient to rescue the growth defect ascribed to deletion of the yigP locus. Moreover, our data showed that EsrE targeted multiple mRNAs involved in several cellular processes including murein biosynthesis and the tricarboxylic acid cycle. Among these targets, sdhD mRNA that encodes one subunit of succinate dehydrogenase (SDH), was significantly activated. Our findings provided an insight into the important function of EsrE in bacterial adaptation to various environments, as well as coordinating different aspects of bacterial physiology.
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We propose a blind image quality assessment that is highly unsupervised and training free. The new method is based on the hypothesis that the effect caused by distortion can be expressed by certain latent characteristics. Combined with probabilistic latent semantic analysis, the latent characteristics can be discovered by applying a topic model over a visual word dictionary. Four distortion-affected features are extracted to form the visual words in the dictionary: (1) the block-based local histogram; (2) the block-based local mean value; (3) the mean value of contrast within a block; (4) the variance of contrast within a block. Based on the dictionary, the latent topics in the images can be discovered. The discrepancy between the frequency of the topics in an unfamiliar image and a large number of pristine images is applied to measure the image quality. Experimental results for four open databases show that the newly proposed method correlates well with human subjective judgments of diversely distorted images.