Programmed Cell Death (PCD) is considered to be a pathological form of cell death when mediated by an intracellular program and it balances cell death with survival of normal cells. Pyroptosis, a ...type of PCD, is induced by the inflammatory caspase cleavage of gasdermin D (GSDMD) and apoptotic caspase cleavage of gasdermin E (GSDME). This review aims to summarize the latest molecular mechanisms about pyroptosis mediated by pore-forming GSDMD and GSDME proteins that permeabilize plasma and mitochondrial membrane activating pyroptosis and apoptosis. We also discuss the potentiality of pyroptosis as a therapeutic target in human diseases. Blockade of pyroptosis by compounds can treat inflammatory disease and pyroptosis activation contributes to cancer therapy.
Binary Relevance is a well-known framework for multi-label classification, which considers each class label as a binary classification problem. Many existing multi-label algorithms are constructed ...within this framework, and utilize identical data representation in the discrimination of all the class labels. In multi-label classification, however, each class label might be determined by some specific characteristics of its own. In this paper, we seek to learn label-specific data representation for each class label, which is composed of label-specific features. Our proposed method LLSF can not only be utilized for multi-label classification directly, but also be applied as a feature selection method for multi-label learning and a general strategy to improve multi-label classification algorithms comprising a number of binary classifiers. Inspired by the research works on modeling high-order label correlations, we further extend LLSF to learn class-Dependent Labels in a sparse stackingway, denoted as LLSF-DL. It incorporates both second-order- and high-order label correlations. A comparative study with the state-of-the-art approaches manifests the effectiveness and efficiency of our proposed methods.
Motivated by the fact that unlabeled data can be easily collected and help to exploit the correlations among different modalities, this paper proposes a novel method named generalized semi-supervised ...structured subspace learning (GSS-SL) for the task of cross-modal retrieval. First, to predict more relevant class labels for unlabeled data, we propose a label graph constraint that ensures the intrinsic geometric structures of different feature spaces consistent with that of label space. Second, considering that class labels directly reveal the semantic information of multimedia data, GSS-SL takes the label space as a linkage to model the correlations among different modalities. Concretely, the label graph constraint, label-linked loss function, and regularization are integrated into a joint minimization formulation to learn a discriminative common subspace. Finally, an efficient optimization algorithm is designed to alternately optimize multiple linear transformations for different modalities and update the class indicator matrices for unlabeled data. Furthermore, an arbitrary number of modalities can be solved in the proposed framework. Extensive experiments on three standard benchmark datasets demonstrate that GSS-SL outperforms previous methods on exploiting the correlations among different modalities.
Cancer is one of the most serious diseases endangering human health. In view of the side effects caused by chemotherapy and radiotherapy, it is necessary to develop low-toxic anti-cancer compounds. ...Polyphenols are natural compounds with anti-cancer properties and their application is a considerable choice. Pro-senescence therapy is a recently proposed anti-cancer strategy and has been shown to effectively inhibit cancer. It is of great significance to clarify the mechanisms of polyphenols on tumor suppression by inducing senescence. In this review, we delineated the characteristics of senescent cells, and summarized the mechanisms of polyphenols targeting tumor microenvironment and inducing cancer cell senescence for cancer prevention and therapy. Although many studies have shown that polyphenols effectively inhibit cancer by targeting senescence, it warrants further investigation in preclinical and clinical studies.
Material with high dielectric constant plays an important role in energy storage elements. (Gd + Nb) co-doped TiO2 (GNTO) ceramics with giant dielectric permittivity (>104), low dielectric loss, good ...temperature and frequency stability in broad range of 30–150 °C and 102–106 Hz have been systematically characterized. Especially, a low dielectric loss of 0.027 and a giant dielectric permittivity of 5.63 × 104 at 1 kHz are attained for the composition with x = 0.01. Results of complex impedance spectroscopy, I–V curve and frequency dependent dielectric constant under DC bias indicate that internal barrier layer capacitance (IBLC) effect, electrode effect and electron-pinned defect-dipole (EPDD) effect contribute to the colossal permittivity (CP) property simultaneously.
Using the AIS data in 2017, this study aims to investigate the effectiveness of five ECA policies on pollutant emissions from merchant ships in Shanghai Port waters. Results show that the estimated ...annual emissions from merchant ships including cargo ships, container ships and tankers are 3.4029 × 104 tons for NOx, 2.1037 × 104 tons for SO2, 2.291 × 103 tons for PM2.5, and 2.921 × 103 tons for PM10 in 2017, respectively. Impact analysis results highlight the fact that effects of each ECA policy vary significantly among different merchant ship types and different water areas. The amount of pollutant emissions from cargo ships (e.g., SO2 and PM2.5) is most affected by the ECA policy. However, the NOx emissions are not significantly changed under different ECA policies. Results also show that future ECA policies could cause a much greater decrease of pollutant emissions in water areas of Yangshan and Wusong.
•Examine effects of five ECA policies on merchant ship emissions•The ECA policy effects vary with different merchant ship types and water areas.•The emissions from cargo ships are more sensitive with the ECA policy.•The NOx emissions are not significantly changed under different ECA policies.
Aging research was hindered because of the long lifespan of available vertebrates. Annual fishes of Nothobranchius have become a new model organism for aging studies. Resveratrol, a natural ...plant-derived chemical, prolongs lifespan in many animals. Here we used the wild strain of N. guentheri, which has the mean lifespan of 12months, to detect the effects of resveratrol on the longevity, cognitive ability and aging-related histological markers. Our results showed that the pharmaceutical treatment of resveratrol prolonged the lifespan of N. guentheri but did not affect their body size. Three behavioral assays for cognitive ability and locomotor activity demonstrated that the resveratrol-treated fish exhibited the higher rate of performances than the fish in the control group. Further data indicated that resveratrol not only had the property of protecting N. guentheri from neurodegeneration, but retarded the aging-related histological markers in lipofuscin formation and in the expression of senescence-associated beta-galactosidase activity.
► We use annual fish Nothobranchius guentheri. ► We examine the effects of resveratrol on age-related markers. ► Resveratrol prolongs lifespan of Nothobranchius guentheri. ► Resveratrol retards locomotor and cognitive decay by neuroprotection. ► Resveratrol retards lipofuscin accumulation and reduces SA-β-Gal activity.
Material with colossal permittivity (CP) is important for the miniaturization of electronic devices and fabrication of high-density energy storage devices. However, the unbalanced developments of ...dielectric constant, dielectric loss and stability preclude its practical applications. In this work, we report that Sb + Ga co-doped TiO2 (SGTO) ceramics exhibit colossal permittivity and low dielectric loss. Especially, a high dielectric permittivity of 3.5 × 104 and a low dielectric loss of 0.06 at 1 kHz are obtained in the optimum composition with x = 0.02. The dielectric property shows high stability in wide temperature (25–130 °C) and frequency (20–106 Hz) range. XPS, complex impedance spectroscopy, I-V curve and frequency dependent dielectric constant under DC bias results indicate that electron-pinned defect-dipoles (EPDD) model, internal barrier layer capacitance (IBLC) effect and electrode effect all contribute to the observed colossal permittivity behavior in (Sb0.5Ga0.5)xTi1-xO2 ceramics.
In multi-label learning, each example is represented by a single instance and associated with multiple class labels. Existing multi-label learning algorithms mainly exploit label correlations ...globally, by assuming that the label correlations are shared by all the examples. Moreover, these multi-label learning algorithms exploit the positive label correlations among different class labels. In practical applications, however, different examples may share different label correlations, and the labels are not only positive correlated, but also mutually exclusive with each other. In this paper, we propose a simple and effective Bayesian model for multi-label classification by exploiting Local positive and negative Pairwise Label Correlations, named LPLC. In the training stage, the positive and negative label correlations of each ground truth label for all the training examples are discovered. In the test stage, the k nearest neighbors and their corresponding positive and negative pairwise label correlations for each test example are first identified, then we make prediction through maximizing the posterior probability, which is estimated on the label distribution, the local positive and negative pairwise label correlations embodied in the k nearest neighbors. A comparative study with the state-of-the-art approaches manifests a competitive performance of our proposed method.
Soil nutrients play vital roles in vegetation growth and are a key indicator of land degradation. Accurate, rapid, and non-destructive measurement of the soil nutrient content is important for ...ecological conservation, degradation monitoring, and precision farming. Currently, visible and near-infrared (Vis-NIR) spectroscopy allows for rapid and non-destructive monitoring of soil nutrients. However, the performance of Vis-NIR inversion models is extremely dependent on the number of samples. Limited samples may lead to low prediction accuracy of the models. Therefore, modeling and prediction based on a small sample size remain a challenge. This study proposes a method for the simultaneous augmentation of soil spectral and nutrient data (total nitrogen (TN), soil organic matter (SOM), total potassium oxide (TK
O), and total phosphorus pentoxide (TP
O
)) using a generative adversarial network (GAN). The sample augmentation range and the level of accuracy improvement were also analyzed. First, 42 soil samples were collected from the pika disturbance area on the QTP. The collected soils were measured in the laboratory for Vis-NIR and TN, SOM, TK
O, and TP
O
data. A GAN was then used to augment the soil spectral and nutrient data simultaneously. Finally, the effect of adding different numbers of generative samples to the training set on the predictive performance of a convolutional neural network (CNN) was analyzed and compared with another data augmentation method (extended multiplicative signal augmentation, EMSA). The results showed that a GAN can generate data very similar to real data and with better diversity. A total of 15, 30, 60, 120, and 240 generative samples (GAN and EMSA) were randomly selected from 300 generative samples to be included in the real data to train the CNN model. The model performance first improved and then deteriorated, and the GAN was more effective than EMSA. Further shortening the interval for adding GAN data revealed that the optimal ranges were 30-40, 50-60, 30-35, and 25-35 for TK
O, TN, TP
O
, and SOM, respectively, and the validation set accuracy was maximized in these ranges. Therefore, the above method can compensate to some extent for insufficient samples in the hyperspectral prediction of soil nutrients, and can quickly and accurately estimate the content of soil TK
O, TN, TP
O
, and SOM.
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