Search

Obstructive sleep apnea (OSA) is a common respiratory disorder. Multiple organs, especially the central nervous system (CNS), are damaged, and dysfunctional when intermittent hypoxia (IH) occurs during sleep for a long time. The quality of life of individuals with OSA is significantly impacted by cognitive decline, which also escalates the financial strain on their families. Consequently, the development of novel therapies becomes imperative. IH induces oxidative stress, endoplasmic reticulum stress, iron deposition, and neuroinflammation in neurons. Synaptic dysfunction, reactive gliosis, apoptosis, neuroinflammation, and inhibition of neurogenesis can lead to learning and long-term memory impairment. In addition to nerve injury, the role of IH in neuroprotection was also explored. While causing neuron damage, IH activates the neuronal self-repairing mechanism by regulating antioxidant capacity and preventing toxic protein deposition. By stimulating the proliferation and differentiation of neural stem cells (NSCs), IH has the potential to enhance the ratio of neonatal neurons and counteract the decline in neuron numbers. This review emphasizes the perspectives and opportunities for the neuroprotective effects of IH and informs novel insights and therapeutic strategies in OSA. [ABSTRACT FROM AUTHOR]

Microcystin LR (MC-LR) is a hazardous cyanotoxin produced by cyanobacteria during freshwater eutrophication, which can cause liver cancer. Here, a photoelectrochemical (PEC) aptasensor based on methylene blue (MB)–loaded Ni-MOF composite (Ni-MOF/MB) with spatial confinement was constructed for the sensitive detection of MC-LR. Ni-MOF with two-dimensional sheet structure was prepared via a liquid–liquid interface synthesis method with environmental-friendly solvent and milder reaction conditions. Benefiting from the uniform pore size, Ni-MOF acted as reaction platform to anchor the photosensitive molecule MB. The electron donor, ascorbic acid (AA), was produced by alkaline phosphatase (ALP) loaded on DNA strand catalyzing ascorbic acid phosphate. The generated AA was absorbed by Ni-MOF/MB, thereby effectively improving the utilization of AA and avoiding the external environment interferences to enlarge the photocurrent of MB. For analysis, ALP-labeled aptamer can specifically recognize MC-LR by forming a complex to strip from aptasensor, thus leading to a decreased photocurrent. The developed PEC aptasensor offered a linear range of 10 fM–100 pM with a detection limit of 6 fM. It was successfully employed for detecting MC-LR in farm water and fish meat, and the results were validated by ultrahigh-performance liquid chromatography-mass spectrometry. This method presents a new idea of MOF-limited domain for PEC aptasensing. [ABSTRACT FROM AUTHOR]

White blood cell detection plays an integral role in diagnosing pathologies such as leukemia and gestational diabetes. Despite this, conventional image-based white blood cell classification methodologies encounter obstacles including inaccurate cell segmentation and labor-intensive artificial feature extraction. Contrarily, Convolutional Neural Networks (CNNs) have the capacity to learn features autonomously from raw images, thereby offering a novel and effective solution for blood cell detection. Notwithstanding, the features ascertained by a solitary CNN tend to be unidirectional. Conversely, ensemble learning combines results from numerous networks, thus ensuring an adequate acquisition of feature information and subsequently enhancing the model's overall efficacy. Consequently, this study introduces a method for white blood cell classification underpinned by ensemble CNNs. Initially, three high-performing CNNs possessing disparate structures, namely VGG16, ResNet50, and Inception V3, are enlisted as base learners to augment the diversity of base learners. Subsequently, the Gompertz function is employed to strategize the ensemble learning combination strategy, taking into consideration the prediction confidence and fuzzy level of each base learner. Ultimately, the ensemble CNN model is developed, incorporating learning outcomes from several singular models and utilizing diversified information to achieve white blood cell classification. Empirical results indicate that the ensemble learning technique advanced in this study enables accurate and reliable white blood cell classification, demonstrating potential clinical value. [ABSTRACT FROM AUTHOR]

Antifungal peptides (AFPs) can be used as novel preservatives, but achieving large-scale production and application remains a long-term challenge. In this study, we developed a hybrid peptide MD (metchnikowin-drosomycin fusion) secreted into Escherichia coli supernatant, demonstrating strong inhibitory activity against Aspergillus flavus and Botrytis cinerea. The fusion tag did not impact its activity. Moreover, an endotoxin-free and oxidative leaky strain was developed by knocking out the trxB, gor, and lpp genes of endotoxin-free E. coli ClearColi-BL21(DE3). This strain facilitates the proper folding of multi-disulfide bond proteins and promotes the extracellular production of recombinant bioactive AFP MD, achieving efficient production of endotoxin-free MD. In addition, temperature control replaces chemical inducers to further reduce production costs and circumvent the toxicity of inducers. This extracellularly produced MD exhibited favorable effectiveness in inhibiting fruit mold growth, and its safety was preliminarily established by gavage testing in mice, suggesting that it can be developed into a green and sustainable fruit fungicide. In conclusion, this study provides novel approaches and systematic concepts for producing extracellularly active proteins or peptides with industrial significance. Key points: • First report of extracellular production of bioactive antifungal peptide in Escherichia coli. • The hybrid antifungal peptide MD showed strong inhibitory activity against Aspergillus flavus and Botrytis cinerea, and the activity was not affected by the fusion tag. • Endotoxin-free oxidative Escherichia coli suitable for the expression of multi-disulfide bond proteins was constructed. [ABSTRACT FROM AUTHOR]

To quickly and accurately automatically design more high-precision deep neural network models (DNNs), this paper proposes an automatic DNN architecture design ensemble model based on consensus particle swarm optimization-assisted trajectory unified and TRUST-TECH (CPSOTJUTT), called CPSOTJUTT-EM. The proposed model is a three-layer model, and its core is a three-stage method for addressing the sensitivity of the local solver to the initial point and enabling fast and robust training DNN, effectively avoiding missing high-quality DNN models in the process of automatic DNN architecture design. CPSOTJUTT has the following advantages: (1) high-quality local optimal solutions (LOSs) and (2) robust convergence against random initialization. CPSOTJUTT-EM consists of the bottom layer: stable and fast design high-quality DNN architectures, the middle layer: exploration for a diverse set of optimal DNN classification engines, and the top layer: ensemble model for higher performance. This paper tests the performance of CPSOTJUTT-EM on public datasets and three self-made power system inspection datasets. Experimental results show that the CPSOTJUTT-EM has excellent performance in automatic DNN architecture design, DNN model optimization. And the CPSOTJUTT-EM can automatically design high-quality DNN ensemble models, laying a solid foundation for the application of DNN in other fields. [ABSTRACT FROM AUTHOR]

Key message: This study provided important insights into the genetic architecture of variations in A. thalianaleaf ionome in a cell-type-specific manner. The functional interpretation of traits associated variants by expression quantitative trait loci (eQTL) analysis is usually performed in bulk tissue samples. While the regulation of gene expression is context-dependent, such as cell-type-specific manner. In this study, we estimated cell-type abundances from 728 bulk tissue samples using single-cell RNA-sequencing dataset, and performed cis-eQTL mapping to identify cell-type-interaction eQTL (cis-eQTLs(ci)) in A. thaliana. Also, we performed Genome-wide association studies (GWAS) analyses for 999 accessions to identify the genetic basis of variations in A. thaliana leaf ionome. As a result, a total of 5,664 unique eQTL genes and 15,038 unique cis-eQTLs(ci) were significant. The majority (62.83%) of cis-eQTLs(ci) were cell-type-specific eQTLs. Using colocalization, we uncovered one interested gene AT2G25590 in Phloem cell, encoding a kind of plant Tudor-like protein with possible chromatin-associated functions, which colocalized with the most significant cis-eQTL(ci) of a Mo-related locus (Chr2:10,908,806:A:C; P = 3.27 × 10–27). Furthermore, we prioritized eight target genes associated with AT2G25590, which were previously reported in regulating the concentration of Mo element in A. thaliana. This study revealed the genetic regulation of ionomic variations and provided a foundation for further studies on molecular mechanisms of genetic variants controlling the A. thaliana ionome. [ABSTRACT FROM AUTHOR]

Traditional white blood cell detection usually requires artificial extraction of cell features, which have higher resolution and contain more detailed information. However, due to the complex background of blood cell images and the large individual differences between cells, artificial feature extraction methods have poor generalization for different image data sets. Convolutional neural networks can extract deep features with stronger semantic information through their powerful self-learning capabilities. However, the pooling layer will cause the loss of some detailed information, while also ignoring the relationship between the whole and the part. Therefore, this paper innovatively proposes a white blood cell classification algorithm that combines deep learning features with artificial features. This algorithm not only uses artificial features, but also combines the self-learning capabilities of Inception V3 to make full use of the feature information of the image. At the same time, this paper introduces the transfer learning method to solve the problem of the dataset limitation. The final experimental results show that by fusing deep learning features with artificial features, the classification accuracy of white blood cell images reaches more than 99%. The proposed method has both low complexity and high accuracy, which makes it of great reference value for other medical image detection problems. [ABSTRACT FROM AUTHOR]

Perfluoroalkyl substances (PFASs) constitute an environmentally persistent and widespread class of anthropogenic chemicals that have been used in industrial and commercial applications in the USA and around the world. Animal studies suggested its toxic impact on lung development, but the adverse effect of PFAS exposure on childhood pulmonary function has not been clearly determined. We investigated the potential cross-sectional association of environmental PFAS exposures with pulmonary function in 765 adolescents aged 12–19 years from the US National Health and Nutrition Examination Survey (NHANES) 2007–2012. Exposure to PFASs was estimated by measuring serum concentrations, and pulmonary function was assessed by spirometry. Linear regression and weighted quantile sum (WQS) regression were performed to estimate the associations of individual chemicals and chemical mixtures with pulmonary function. Median concentrations of PFOA, PFOS, PFNA, and PFHxS (detection frequencies > 90%) were 2.70, 6.40, 0.98, and 1.51 ng/mL, respectively. No associations were found between the four individual congeners and Σ4PFASs and the pulmonary function measures in total adolescents. Sensitive analyses were further conducted stratified by age (12–15 and 16–19 years) and sex (boys and girls). In adolescents aged 12–15 years, PFNA was negatively associated with FEV1:FVC (p-trend = 0.007) and FEF25–75% (p-trend = 0.03) among girls, while PFNA was positively associated with FEV1: FVC (p-trend = 0.018) among boys. No associations were found among adolescents aged 16–19 years, either boys or girls. The aforementioned associations were confirmed when further applying WQS models, and PFNA was identified to be the most heavily weighing chemical. Our results suggested that environmental exposure to PFNA may affect pulmonary function among adolescents aged 12–15 years. Given the cross-sectional analysis and less consistent results, further replications of the association in large prospective cohort studies are warranted. [ABSTRACT FROM AUTHOR]

Background: Many diseases are clinically related to oxidative stress. Obstructive sleep apnea (OSA) is a common disease with oxidative stress in clinical practice, which is mostly associated with cardio-cerebrovascular diseases. It has been shown that the level of oxidative stress increases and the level of antioxidant copper zinc superoxide dismutase (SOD1) decreases in intermittent hypoxia (IH). SOD1 is one of the key antioxidant enzymes in organisms, and it can also be used as a signal transmission controller. Its abnormal expression further affects organ functions, but the specific mechanism is not yet fully clear. Methods: We downregulated the SOD1 gene in H9C2 cell line, using high-throughput RNA sequencing (RNA-seq) to find differentially expressed genes (DEGs) related to cardiomyocyte function by using GO and KEGG databases to annotate, enrich and analyze the metabolic pathways of DEGs. Results: Through the analysis of these functional gene changes, we can understand the regulation of SOD1 downregulation on cardiomyocyte function. The results found 213 DEGs, of which 135 genes were upregulated and 78 genes were downregulated. The upregulated DEGs were mainly enriched in biological processes such as transcriptional regulation and metabolism. The expression levels of EGR1 and NR1D1 exceeded 1 in the samples. EGR1 was reported to be involved in oxidative stress and cardiac hypertrophy, and NR1D1 played an important regulatory role in regulating inflammatory responses and reducing ROS production. The biological processes involved in downregulated DEGs mainly involve metabolism and redox processes. Among them, SCD1 and CCL2 genes were highly expressed among the genes involved in the redox process involved in SOD1. SCD1 is an important player in the regulation of cardiometabolic processes; downregulation of CCL2 reduces atherosclerosis. We found that the TNF signaling pathway, NOD-like receptor signaling pathway, and chemokine signaling pathway, which were enriched in KEGG analysis, were all associated with inflammation, and the CXCL1 and CCL7 genes are all related to inflammation. Conclusion: The gene and signaling pathways involved in oxidative stress and inflammatory response process regulated by SOD1 were demonstrated. SOD1 may affect the function of the heart by affecting myocardial contraction, inflammation, lipid metabolism, and other pathways. It is inferred that they may also play a role in the process of OSA-related myocardial injury, which is worthy of attention and further study. [ABSTRACT FROM AUTHOR]

Lead, one of the most common heavy metal toxins, seriously affects the health of humans and animals. Sinomenine hydrochloride (SH) shows antioxidative, anti-inflammatory, antiviral, and anticancer properties. Hence, this study investigated the protective effects of SH against Pb-induced liver injury and explored the underlying mechanisms. First, a mouse model of lead acetate (0.5 g/L lead acetate in water, 8 weeks) was established, and SH (100 mg/kg bw in water, 8 weeks) intervention was administered by gavage. Then, the protective effect of SH against lead-induced liver injury was evaluated through serum biochemical analysis, histopathological analysis, and determination of malondialdehyde (MDA) and total antioxidant capacity (T-AOC) levels. The messenger RNA (mRNA) expression levels of the cytokines IL-1β and TNF-α and the apoptosis factors Bax, Bcl-2, and Caspase3 in the liver were detected by quantitative real-time PCR. Then, the expression levels of IL-1β and TNF-α in the liver were detected by ELISA. Immunohistochemical determination of the expression of the apoptosis factors Bax, Bcl-2, and Caspase3 was performed. SH treatment reduced the levels of liver alanine aminotransferase, aspartate aminotransferase (AST), lactate dehydrogenase (LDH), and MDA in Pb-treated mice, indicating that SH protected the liver from injury and oxidative stress in Pb-treated mice. SH also increased the liver T-AOC of Pb-treated mice. Quantitative real-time PCR, ELISA, and immunohistochemical analysis showed that SH inhibited apoptosis, as indicated by the regulation of the mRNA expression of Bax and Bcl-2 and the reduced expression of Caspase3 and pro-inflammatory factors (IL-1β and TNF-α) in the livers of Pb-treated mice. These results suggest that SH protects the mouse liver from Pb-induced injury. The underlying mechanism involves antioxidative, anti-inflammatory, and anti-apoptotic processes. [ABSTRACT FROM AUTHOR]

Construction waste (CW) source reduction is a crucial strategy to address the sustainability issue of the construction industry. The economic benefit is a key factor affecting project decision-makers on whether to implement this strategy. However, limited studies analysed the cost–benefit of CW source reduction from a system dynamic perspective. Therefore, by considering the design and construction phase as a whole, this study constructed a system dynamics (SD) model based on the identification of the factors affecting the cost–benefit of CW source reduction to analyse the cost–benefit of CW source reduction. A residential building project in China's Chengdu was used for the study case. The results show that the net benefit of CW source reduction is positive, and BIM implementation, design for standard material size, and building material storage are the three strategies to effectively improve the economic benefits of CW source reduction. Furthermore, the best investment level of CW source reduction was also determined. This study provides a model which can be used to simulate the cost–benefit under different implementation levels of reduction strategies and different investment levels in advance, thereby providing a reference for project decision-makers to plan CW source reduction. [ABSTRACT FROM AUTHOR]

The correlation characteristics between anomalous changes in summer precipitation on the Qinghai–Tibet Plateau (QTP) and the high-impact areas of global sea-surface temperature (SST) are mainly studied in this paper. The results show that the interdecadal change of the regional "warming-wetting" in China is especially prominent in the northern part of the main body of the QTP, which is therefore identified as the high-value area of precipitation variability. Investigations have revealed that the high-value areas of summer precipitation variability in the northern QTP are significantly correlated with four high-value areas of SST variability, namely the western North Pacific, the western Central Pacific, the Southwest Pacific, and the central Indian Ocean. In these four high-impact areas, a synchronous tendency is found in the SST increase and sea-surface specific humidity. Through the tracking analysis of the correlated vectors of the water vapor source for the warming-wetting of the QTP, it further confirms that the four high-value areas of SST variability in the Indo-Pacific Ocean are the major impact sources of water vapor transport for the warming-wetting of the QTP. Moreover, the comparison of the characteristics of various interdecadal global water vapor transport circulations show that from 1991 to 2020, the trans-equatorial water vapor transport from the Southern Hemisphere witnessed a notable increase, which furthermore suggests that the interdecadal change of SST increase in the Southwest Pacific and central Indian Ocean is the key reason for the warming-wetting of the QTP. In addition, a comprehensive image of high-impact marine water vapor sources for modulating the warming-wetting tendency in the QTP is proposed. [ABSTRACT FROM AUTHOR]

Small ubiquitin-like modifier (SUMO) tag is widely used to promote soluble expression of exogenous proteins, which can then be cleaved by ubiquitin-like protease 1 (Ulp1) to obtain interested protein. But the application of Ulp1 in large-scale recombinant protein production is limited by complicated purification procedures and high cost. In this study, we describe an efficient and simple method of extracellular production of Ulp1403-621 using a leaky Escherichia coli BL21(DE3), engineered by deleting the peptidoglycan-associated outer membrane lipoprotein (pal) gene. Ulp1403-621 was successfully leaked into extracellular supernatant by the BL21(DE3)-Δpal strain after IPTG induction. The addition of 1% glycine increased the extracellular production of Ulp1403-621 approximately four fold. Moreover, extracellular Ulp1403-621 without purification had high activities for cleaving SUMO fusion proteins, and antimicrobial peptide pBD2 obtained after cleavage can inhibit the growth of Staphylococcus aureus. The specific activity of extracellular Ulp1403-621 containing 1 mM EDTA and 8 mM DTT reached 2.0 × 106 U/L. Another commonly used protease, human rhinovirus 3C protease, was also successfully secreted by leaky E. coli strains. In conclusion, extracellular production of tool enzymes is an attractive way for producing large-scale active recombinant proteins at a lower cost for pharmaceutical, industrial, and biotechnological applications. Key points: • First report of extracellular production of Ulp1403-621 in leaky Escherichia coli BL21(DE3) strain. • One percent glycine addition into cultivation medium increased the extracellular production of Ulp1403-621 approximately four fold. • The specific activity of extracellular Ulp1403-621 produced in this study reached 2.0 × 106 U/L. [ABSTRACT FROM AUTHOR]

Heatwaves detrimentally affect human health and ecosystems. While previous studies focused on either temporal changes or spatial extents of heatwaves, their spatiotemporal contiguity and propagation patterns are unclear. Here, we investigate the climatology, long-term trends, and interannual variations of spatiotemporally contiguous heatwaves across China during 1961 to 2018. Two distinct propagation patterns are identified by introducing a spatiotemporally contiguous events tracking (SCET) method and the k-means clustering. Type 1 contiguous heatwaves mostly generate over eastern China and move southwestward at shorter distances, while Type 2 heatwaves generally initiate over western China and move southeastward at longer distances, with stronger intensity, longer lifetime, and larger coverage. Since the 1960s, both types exhibit significant increases in frequency, intensity, coverage, lifetime, and traveling distances, with relatively larger magnitudes for Type 2, but significant decreases in moving speed only appear for Type 1. On interannual timescale, preceding winter El Niño prolongs the duration and slows down the moving speed of Type 1 through the western North Pacific subtropical high. Type 2 contiguous heatwaves are intensified by the negative spring North Atlantic Oscillation via the upper-atmospheric Rossby wave train. [ABSTRACT FROM AUTHOR]

Deep networks have shown remarkable results in the task of object detection. However, their performance suffers critical drops when they are subsequently trained on novel classes without any sample from the base classes originally used to train the model. This phenomenon is known as catastrophic forgetting. Recently, several incremental learning methods are proposed to mitigate catastrophic forgetting for object detection. Despite the effectiveness, these methods require co-occurrence of the unlabeled base classes in the training data of the novel classes. This requirement is impractical in many real-world settings since the base classes do not necessarily co-occur with the novel classes. In view of this limitation, we consider a more practical setting of complete absence of co-occurrence of the base and novel classes for the object detection task. We propose the use of unlabeled in-the-wild data to bridge the non co-occurrence caused by the missing base classes during the training of additional novel classes. To this end, we introduce a blind sampling strategy based on the responses of the base-class model and pre-trained novel-class model to select a smaller relevant dataset from the large in-the-wild dataset for incremental learning. We then design a dual-teacher distillation framework to transfer the knowledge distilled from the base- and novel-class teacher models to the student model using the sampled in-the-wild data. Additionally, the novel class data is in the training to facilitate the learning of discriminative representations between base and novel classes. Furthermore, on the consideration that the training samples are all false positives when there is no class overlap in the in-the-wild data, we propose a single-teacher distillation framework to relieve the mutual suppression of the dual-teacher distillation framework and balance a trade-off between the performances of base and novel classes. Experimental results on the PASCAL VOC and MS-COCO datasets show that our proposed method significantly outperforms other state-of-the-art class-incremental object detection methods when there is no co-occurrence between the base and novel classes during training. [ABSTRACT FROM AUTHOR]

Osteoporosis (OP) is a frequent orthopedic disease characterized by pain, fractures and deformities. Glucocorticoids are the most common cause of secondary osteoporosis. Here, we aim to explore the function and mechanism of STK11 in glucocorticoid (GC)-induced OP. Human mesenchymal stromal cells (hMSCs) were differentiated under osteogenic or adipogenic culture medium. An in-vitro OP model was induced by dexamethasone (DEX). The viability, differentiation, apoptosis, and ROS level were evaluated for investigating the functions of SKT11 on hMSCs. The SIRT1 inhibitor EX-527, PGC1α inhibitor SR-18292, and AMPK activator metformin were administered into hMSCs for confirming the mechanism of SKT11. Our results showed that STK11 was down-regulated in OP tissues, as well as DEX-treated hMSCs. Overexpressing STK11 attenuated DEX-mediated inhibition of osteogenic differentiation and heightened the activation of the AMPK/SIRT1/PGC1α pathway, whereas STK11 knockdown exerted opposite effects. Inhibiting SIRT1 or PGC1α repressed the promotive effect of STK11 on osteogenic differentiation of hMSCs, while activation of AMPK abated the inhibitory effect of STK11 knockdown on osteogenic differentiation of hMSCs. In conclusion, this study revealed that overexpressing STK11 dampened GC-induced OP by activating the AMPK/SIRT1/PGC1α axis. [ABSTRACT FROM AUTHOR]

The biophysical effects of vegetation changes are important in determining future climate changes using climate model. However, compared to observations, model has biases in energy exchange between vegetation and the lower atmosphere modulated by leaf area index and albedo. In this study, land-use induced anthropogenic influences, estimated as the differences between present land-use and idealized natural vegetation, on near-surface temperature were investigated using a regional climate model. Results show that present land-use transitions over China brings a cooler summer and winter accompanied by reduced diurnal temperature ranges by 0.11 °C and 0.25 °C respectively, which are mainly determined by the overwhelming increased evaporation and latent heat flux in summer and reduced net radiation in winter. Three vegetation pairs (i.e., forest and cropland, grassland and cropland, grassland and forest) were selected using observational datasets to evaluate vegetation induced climatic impact without atmospheric feedbacks across various climatic regimes. Albedo led absorbed radiation plays a dominate role in middle to north region while both LAI and albedo are significant below 30° N for latitudinal temperature changes between cropland and forest transitions. Model results have inconsistencies with observations on temperature trends caused by vegetation pairs, indicating summer cropland and forest over southern China is the most sensitive to the atmosphere conditions and forest and grassland pair is the least. These findings demonstrate the heterogeneous biophysical effect of vegetation in different climate zones and imply that a region-oriented parameterization of vegetation types should be applied in the land surface model to reduce uncertainties in future climate prediction. [ABSTRACT FROM AUTHOR]

Impressive methods for object detection tasks have been proposed based on convolutional neural networks (CNNs), however, they usually use very computation expensive deep networks to obtain such significant performance. Knowledge distillation has attracted much attention in the task of image classification lately since it can use compact models that reduce computations while preserving performance. Moreover, the best performing deep neural networks often assemble the outputs of multiple networks in an average way. However, the memory required to store these networks, and the time required to execute them in inference, which prohibits these methods used in real-time applications. In this paper, we present a knowledge distillation method for one-stage object detection, which can assemble a variety of large, complex trained networks into a lightweight network. In order to transfer diverse knowledge from various trained one-stage object detection networks, an adversarial-based learning strategy is employed as supervision to guide and optimize the lightweight student network to recover the knowledge of teacher networks, and to enable the discriminator module to distinguish the feature of teacher and student simultaneously. The proposed method exhibits two predominant advantages: (1) The lightweight student model can learn the knowledge of the teacher, which contains richer discriminative information than the model trained from scratch. (2) Faster inference speed than traditional ensemble methods from multiple networks is realized. A large number of experiments are carried out on PASCAL VOC and MS COCO datasets to verify the effectiveness of the proposed method for one-stage object detection, which obtains 3.43%, 2.48%, and 5.78% mAP promotions for vgg11-ssd, mobilenetv1-ssd-lite and mobilenetv2-ssd-lite student network on the PASCAL VOC 2007 dataset, respectively. Furthermore, with multi-teacher ensemble method, vgg11-ssd gains 7.10% improvement, which is remarkable. [ABSTRACT FROM AUTHOR]

Background and aims: Kandelia obovata, a dominant mangrove species in China, produces complex buttress roots and prop roots in intertidal wetlands where high quantities of nitric oxide (NO) are produced by reducing sediments. NO, a key signaling molecule, participates in an array of plant physiological and developmental processes. However, it is unclear whether NO functions in K. obovata root system establishment. Methods: Here, we used a transcriptomic approach to investigate the potential role of NO in the regulation of K. obovata lateral root development and growth. Transcript profiles and bioinformatics analyses were used to characterize potential regulatory mechanisms. Results: Application of exogenous sodium nitroprusside (SNP, an NO donor) enhanced K. obovata lateral root development and growth in a dose-dependent manner. Furthermore, the effects of SNP were abolished by the addition of cPTIO (NO scavenger). RNA-seq analysis identified 1,593 differentially expressed genes (DEGs), of which 646 and 947 were up- and down-regulated in roots treated with NO donor. Functional annotation analysis demonstrated that the starch and sucrose pathway was significantly induced in response to NO. A suite of DEGs involved in hormone signal transduction and cell wall metabolism was also differentially regulated by NO. Taken together, our results suggest that a complex interaction between energy metabolism, multiple hormone signaling pathways, and cell wall biosynthesis is required for the NO regulation on lateral root development and growth in mangrove plant K. obovata. Conclusion: NO appears to contribute to the formation of the unique root system of mangrove plants. [ABSTRACT FROM AUTHOR]

Based on the model-free adaptive control (MFAC) theory, the temperature tracking control problem of single-effect LiBr/H2O absorption chiller is explored. Due to the complex nonlinearity and strong coupling characteristics of the absorption refrigeration system, model-free adaptive control strategy is designed for its temperature tracking control. Nevertheless, the traditional model-free adaptive control has a slow tracking speed and poor denoising ability. In order to improve its control effect, output error rate is added to the objective function and new control laws of model-free adaptive control with output error rate (MFAC-OER) have been derived through an exhaustive convergence and stability analysis. The input information and output information of the absorption refrigeration system, namely the hot water pump frequency and chilled water outlet water temperature, are combined. The data model of the absorption refrigeration system is subsequently deduced using a compact format dynamic linearization method. Next, based on the single-effect absorption chiller experimental platform in our laboratory, its sixth-order dynamic model is built. Finally, the effectiveness and practicability of the improved control strategy are illustrated by numerical simulations and experimental operating data from our laboratory as well as by the dynamical model of the absorption chiller. [ABSTRACT FROM AUTHOR]

Lead is one of the most common heavy metal elements and has high biological toxicity. Long-term lead exposure will induce the contamination of animal feed, water, and food, which can cause chronic lead poisoning including nephrotoxicity, hepatotoxicity, neurotoxicity, and reproductive toxicity in humans and animals. In the past few decades, lead has caused widespread concern because of its significant threat to health. A large number of in vitro and animal experiments have shown that oxidative stress plays a key role in lead toxicity, and endoplasmic reticulum (ER) stress and the mitochondrial apoptosis pathway can also be induced by lead toxicity. Therefore, plant polyphenols have attracted attention, with their advantages of being natural antioxidants and having low toxicity. Plant polyphenols can resist lead toxicity by chelating lead with their special chemical molecular structure. In addition, scavenging active oxygen and improving the level of antioxidant enzymes, anti-inflammatory, and anti-apoptosis are also the key to relieving lead poisoning by plant polyphenols. Various plant polyphenols have been suggested to be useful in alleviating lead toxicity in animals and humans and are believed to have good application prospects. [ABSTRACT FROM AUTHOR]

The development of Driverless Car, Unmanned Aerial Vehicle, Human–Computer Interaction and Artificial Intelligence has promoted the Internet of Things (IoT) industry, in which, Visual Simultaneous Localization and Mapping (VSLAM) is an important Localization and Mapping technique. Closed loop detection can alleviate the error accumulation during the operation of VSLAM. The traditional closed loop detection methods mostly rely on manually defined features, subjective and unstable, which are difficult to cope with complex and repetitive scenarios. Thus, triplet loss-based metric learning has been considered as a better solution for closed loop detection. In this paper, first, constructed Generator is applied to generate feature vector of hard negative sample. Second, triplet loss and generative loss have been applied to construct loss function. The keyframes are converted into feature vectors with well-trained model, evaluating the similarity of keyframes by calculating their distance of feature vectors, which is used to determine whether a closed loop is formed. Finally, TUM dataset is introduced to evaluate the Precision and Recall of the proposed metric learning. The well-trained model is applied to establish loop closing thread for VSLAM system. The experimental results illustrate the feasibility and effectiveness of the metric learning-based closed loop detection, which can be further applied to practical VSLAM systems. [ABSTRACT FROM AUTHOR]

The permeability of thermally cracked granites is crucial information for understanding and modeling a number of processes in the earth's crust, such as folding, geothermal activity, magmatic intrusions, and nuclear waste disposal. Factors, including the coefficient of thermal expansion, elastic modulus, grain size, and bonding stress, have a significant impact on thermal cracking and induced permeability. We performed thermal cracking experiments on granite with different grain sizes to determine the effect of grain size on permeability. The results indicated that permeability increased with temperature up to 700 °C for all samples. The ratio of permeability at the target temperature to that at room temperature is an exponential function of temperature. Coarse-grained granite has a higher increase in permeability than fine-grained granite. A mathematical model was presented to explain the effect of grain size on thermal cracking and induced permeability. In addition, the model can also quantitatively describe the influence of the linear thermal expansion coefficient and elastic modulus of minerals on thermal cracking. [ABSTRACT FROM AUTHOR]

Background Beers criteria have been into the mainstay to characterize the potentially inappropriate medication since its first publication, but the recent version, Beers 2019, is yet to be validated by clinical studies nationally. Objective To identify the prevalence and the predictors of potentially inappropriate medications in hospitalized geriatric patients based on the Beers 2019 and 2015 criteria. Setting Nanjing Drum Tower Hospital, a 3000-bed tertiary care teaching hospital in China. Method We conducted a cross-sectional study from July 1, 2018 to December 31, 2018. Data from all hospitalized patients aged ≥ 65 years were collected from the hospital database. Inappropriate prescriptions were identified using the Beers 2019 criteria and the Beers 2015 criteria. Main outcome measure Prevalence Ratio (PR) and predictors of potentially inappropriate medications. Results The prevalence of inappropriate prescriptions based on the Beers 2019 criteria was 64.80%. This result was slightly higher than that of the Beers 2015 criteria (64.31%). The most commonly encountered inappropriate prescriptions identified using the two criteria were proton-pump inhibitors. The kappa coefficient was 0.826 (p < 0.001) indicating a strong coherence between the two criteria. The most important factor associated with inappropriate medications use was the number of prescribed drugs (PR 5.17, 95% CI 2.89–8.43; PR 4.58, 95% CI 1.93–7.25). Conclusion This study showed a high prevalence of potentially inappropriate medication in the Chinese geriatric population, which was associated with the number of prescribed drugs. The predictors identified in this research might help pharmacists to detect high-risk drugs and intervene in time [ABSTRACT FROM AUTHOR]

In recent years, conventional artificial method leads to low efficiency in the classification of cervical cell, which requires professional completion. Therefore, the classification process is increasingly dependent on artificial intelligence. The traditional image classification method needs to extract a large number of features. Redundant features cause the recognition speed to be slow, and influence the recognition effect. To address these problems and obtain the highest recognition accuracy with the least number of features, this paper proposes a machine learning method based on feature selection algorithm for cervical cell classification. Firstly, we introduced classification and regression trees (CART) for cell feature selection, which reduces the dimension of input feature attributes. Subsequently, particle swarm optimization (PSO) was used to optimize the hyperparameters of support vector machine (SVM) in this paper, making the SVM model better for classification. Finally, the Herlev dataset was introduced to verify the classification performance. The experimental results show that the proposed algorithm can extract accurate and effective features and obtain high classification accuracy, thus verifying the effectiveness of the proposed algorithm. Moreover, the network structure of the proposed algorithm is relatively simple with a low computation cost, which makes it feasible of further extension to the classification application of other cancer cells. [ABSTRACT FROM AUTHOR]

Antibiotic residues in animal-derived food products such as milk pose a potential health risk to consumers. A portable antimicrobial screening test plate was fabricated particularly for on-farm testing of milk. A cold-water soluble compound gelling agent composed of guar gum (GG) and konjac glucomannan (KG) was prepared and its properties were optimized for enhancing performance of the test plate. A ratio of 4:6 (GG:KG) showed improved gel strength, cohesiveness, transmittance, and water diffusion of the compound gel. Microbial colony number and size were also increased. The test plate displayed a minimum inhibition concentration of 4 µg/L penicillin G and clearer zone of inhibition. Detection time was also significantly reduced to approximately 9–15 h compared to the conventional agar plate method. The plastic film test plate with optimized compound gel demonstrated tremendous potential for detection of antibiotics in milk. [ABSTRACT FROM AUTHOR]

Purpose: In recent years, with the increasing incidence of cervical cancer, it is a tedious and time-consuming task with unsatisfying accuracy to manually recognize the cells. Machine recognition can be a good solution, but it suffers from the difficulty of obtaining precise edges of cells, which directly influence the final recognition accuracy. To improve the recognition accuracy and shorten the time used for cell recognition, an AGVF-Snake (Adaptive Gradient Vector Flow-Snake) model for the extraction of cell edges has been proposed in this paper. Methods: Firstly, the cell is initially located by the improved Canny algorithm. Then, the adaptive initial contour model and gradient vector model are used to obtain accurate cell edges. Finally, the PSO–SVM (Particle Swarm Optimization-Support Vector Machine) classifier is selected to recognize the cervical cells. Results: Herlev dataset is used to verify the AGVF-Snake algorithm; the accuracy of two and seven classifications are recorded. Six other classification methods are introduced for comparison. According to the experimental results, the accuracy of two and seven classifications can achieve up to 99%, which are better than other six methods. Conclusion: The experiment results show that the proposed algorithm has obvious recognition advantages, and thus provides an effective methodological framework for the diagnosis of cervical cancer diseases. [ABSTRACT FROM AUTHOR]

This paper mainly investigated the controllable preparation of well-dispersed ZnO nanoparticles by a surfactant-assisted method which selected laminated 6-polyglycerol monostearate (6-PGME) supermicelle as template. Typically, nano-ZnO particles confined in 6-PGME (6-PGME-ZnO) exhibited promising ultraviolet (UV) absorption with a blue-shift in comparison with the conventional bulk ZnO. Notably, the as-prepared 6-PGME-ZnO particles could be easily dispersed in sweet almond, jojoba oil and/or evening primrose oil as sunscreen agent. The physicochemical properties of 6-PGME-ZnO sample were further characterized to elucidate its relationship with adsorption capacity. This work might provide an alternative and green route for the development of ZnO-based nanomaterials, which have remarkable potential application in anti-UV fields. [ABSTRACT FROM AUTHOR]

Background: The treatment of modified Mason Type III or IV fractures is controversial. Many authors report open reduction and internal fixation (ORIF) with reconstruction of the radial head, but others advocate radial head arthroplasty (RHA). This study compares the clinical and radiological outcomes of ORIF and RHA in modified Mason Type III or IV radial head fracture and evaluates correlations between prognostic factors and postoperative clinical outcomes. Materials and Methods: 42 patients with modified Mason Type III or IV radial head fractures who were surgically treated between January 2010 and January 2014 were retrospectively analyzed (20 patients with RHA and 22 patients with ORIF group were selected). Clinically, the patient rated elbow evaluation (PREE), the disabilities of the arm, shoulder and hand (DASH), and the range of motion (ROM) were measured. Radiologically, plain radiographs and computed tomography scans were taken. Results: The mean PREE scores were 13.9 for the RHA group and 13.0 for the ORIF group, and mean DASH scores were 9.5 and 10.7, respectively. The differences were not statistically significant. When comparing ROM, the patients in the RHA group showed greater movement at all measured angles. In multiple regression analysis, age was the only variable significantly associated with both PREE and DASH. Conclusion: Overall, there were no significant differences in clinical outcomes of modified Mason Type III or IV radial head fractures treated with ORIF or RHA. However, a subgroup of younger patients had better clinical outcomes with ORIF treatment. Therefore, ORIF should be the first line of treatment, particularly if the reduction is possible. [ABSTRACT FROM AUTHOR]

Immune recognition of pathogen-associated molecular patterns (PAMPs) by pattern recognition receptors often activates proinflammatory NF-κB signalling1. Recent studies indicate that the bacterial metabolite D-glycero-β-D-manno-heptose 1,7-bisphosphate (HBP) can activate NF-κB signalling in host cytosol2-4, but it is unclear whether HBP is a genuine PAMP and the cognate pattern recognition receptor has not been identified. Here we combined a transposon screen in Yersinia pseudotuberculosis with biochemical analyses and identified ADP-β-D-manno-heptose (ADP-Hep), which mediates type III secretion system-dependent NF-κB activation and cytokine expression. ADP-Hep, but not other heptose metabolites, could enter host cytosol to activate NF-κB. A CRISPR-Cas9 screen showed that activation of NF-κB by ADP-Hep involves an ALPK1 (alpha-kinase 1)-TIFA (TRAF-interacting protein with forkhead-associated domain) axis. ADP-Hep directly binds the N-terminal domain of ALPK1, stimulating its kinase domain to phosphorylate and activate TIFA. The crystal structure of the N-terminal domain of ALPK1 and ADP-Hep in complex revealed the atomic mechanism of this ligand-receptor recognition process. HBP was transformed by host adenylyltransferases into ADP-heptose 7-P, which could activate ALPK1 to a lesser extent than ADP-Hep. ADP-Hep (but not HBP) alone or during bacterial infection induced Alpk1-dependent inflammation in mice. Our findings identify ALPK1 and ADP-Hep as a pattern recognition receptor and an effective immunomodulator, respectively. The bacterial metabolite ADP-heptose activates NF-κB in host cells via alpha-kinase 1 and the TIFA-TRAF signalling pathway. [ABSTRACT FROM AUTHOR]

To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion. [ABSTRACT FROM AUTHOR]

Objective: To investigate the role of aqueous extracts of Tribulus terrestris (TT) against oxidized low-density lipoprotein (ox-LDL)-induced human umbilical vein endothelial cells (HUVECs) dysfunction in vitro. Methods: HUVECs were pre-incubated for 60 min with TT (30 and 3 μg/mL respectively) or 10 mol/L valsartan (as positive controls) and then the injured endothelium model was established by applying 100 μg/mL ox-LDL for 24 h. Cell viability of HUVECs was observed by real-time cell electronic sensing assay and apoptosis rate by Annexin V/PI staining. The cell migration assay was performed with a transwell insert system. Cytoskeleton remodeling was observed by immunofluorescence assay. The content of endothelial nitric oxide synthase (eNOS) was measured by enzyme-linked immunosorbent assay. Intracellular reactive oxygen species (ROS) generation was assessed by immunofluorescence and flow cytometer. Key genes associated with the metabolism of ox-LDL were chosen for quantitative real-time polymerase chain reaction to explore the possible mechanism of TT against oxidized LDL-induced endothelial dysfunction. Results: TT suppressed ox-LDL-induced HUVEC proliferation and apoptosis rates significantly (41.1% and 43.5% after treatment for 3 and 38 h, respectively; P<0.05). It also prolonged the HUVEC survival time and postponed the cell's decaying stage (from the 69th h to over 100 h). According to the immunofluorescence and transwell insert system assay, TT improved the endothelial cytoskeletal network, and vinculin expression and increased cell migration. Additionally, TT regulated of the synthesis of endothelial nitric oxide synthase and generation of intracellular reactive oxygen species ( P<0.05). Both 30 and 3 μg/mL TT demonstrated similar efficacy to valsartan. TT normalized the increased mRNA expression of PI3Kα and Socs3. It also decreased mRNA expression of Akt1, AMPKα1, JAK2, LepR and STAT3 induced by ox-LDL. The most notable changes were JAK2, LepR, PI3Kα, Socs3 and STAT3. Conclusions: TT demonstrated potential lowering lipid benefits, anti-hypertension and endothelial protective effects. It also suggested that the JAK2/STAT3 and/or PI3K/AKT pathway might be a very important pathway which was involved in the pharmacological mechanism of TT as the vascular protective agent. [ABSTRACT FROM AUTHOR]

To generate effective antimicrobial peptides (AMPs) with good antimicrobial activities and cell selectivity, many synthetic strategies have been implemented to facilitate the development of AMPs. However, these synthetic strategies represent only a small proportion of the methods used for the development of AMPs and are not optimal with the requirements needed for the design of AMPs. In this investigation, we designed a mirror-like structure with a lower charge and a higher number of hydrophobic amino acids. The amino acid sequence of the designed mirror-like peptides was XXYXXXY XXXYXX [X represents L (Leu) and/or A (Ala); Y represents K (Lys)]. These mirror-like peptides displayed antimicrobial activity against both Gram-positive and Gram-negative bacteria. Hemolysis activity and cytotoxicity, detected by using human red blood cells (hRBCs) and human embryonic kidney cells (HEK293), respectively, demonstrated that the frequency of Ala residues in this structure had a regulatory effect on the high hydrophobic region. In particular, KLA showed a greater antimicrobial potency than the other three mirror-like peptides, folded into an α-helical structure, and displayed the highest therapeutic index, suggesting its good cell selectivity. Observations from fluorescence spectroscopy, flow cytometry, and electron microscopy experiments indicated that KLA exhibited good membrane penetration potential by inducing membrane blebbing, disruption and lysis. Therefore, generating mirror-like peptides is a promising strategy for designing effective AMPs with regions of high hydrophobicity. [ABSTRACT FROM AUTHOR]

This paper presents a novel sliding mode control (SMC) strategy based on approximate feedback linearization and enhanced nonlinear disturbance observer for small-scale unmanned helicopters with high-order time-varying matched and mismatched disturbance. The novel SMC method is developed by designing a new sliding surface with the estimation of mismatched disturbance and its derivative. The proposed novel SMC method possesses following two appealing traits. First, it is robust with both matched disturbance and mismatched disturbance. Second, the chattering problem can be attenuated significantly. Moreover, the uniformly ultimately bounded stability of the closed-loop helicopter system is proved by theoretical analysis. Finally, the excellent tracking performance and robustness of the proposed flight control scheme are demonstrated by simulation results. [ABSTRACT FROM AUTHOR]

Synthetic seeds were obtained in vitro through the encapsulation of axillary buds of Gossypium hirsutum in calcium alginate beads. The optimal combination for the production of uniform, easy to handle, firm and clear beads was found to be 3 % sodium alginate in liquid Murashige and Skoog (MS) medium supplemented with 100 mM CaCl. The optimal combination for the synthetic endosperm contained 0.5 mg L indole-3-butyric acid and 0.5 mg L α-naphthalene acetic acid, which was used in alginate beads in the MS basal medium. On this synthetic endosperm medium, a 95 % synthetic seed germination rate was observed and 35.8 % of synthetic seeds rooted, with an average length of 2.2 cm after 30 days of culturing. The optimal synthetic seed coat was obtained using a solution containing 3 % sodium alginate and 1 % chitosan dissolved in 85 mM acetic acid, and solidified liquid containing 200 mM CaCl and 0.02 % NaOH. Here, 96.1 % of synthetic seeds germinated on MS medium, and the synthetic seeds were stored in the open for 24 h at 25 °C with only an 8 % water loss rate. The percentage of seedling emergence from the synthetic seeds was 35.2 % in the aseptic mixture. This is the first report on synthetic G. hirsutum seeds. [ABSTRACT FROM AUTHOR]

Squamous cell carcinoma (SCC) is one of the most common skin cancers. In the present study, we explored the effects of depletion of murine double minute gene 2 (MDM2) together with overexpression of N-myc downstream-regulated gene 2 (NDRG2) on cutaneous SCC. In order to achieve high efficiency of gene knockdown and overexpression in SCC-13 cells, recombinant adenovirus carrying siMDM2 and NDRG2 expression construct was produced. We found Ad-siMDM2, Ad-NDRG2, and Ad-siMDM2-NDRG2 infections inhibit the growth of SCC-13 cells in vitro, and Ad-siMDM2-NDRG2 infection has the highest inhibitory effect. Subcutaneous injections of Ad-siMDM2, Ad-NDRG2, and Ad-siMDM2-NDRG2 into SCC-13 xenograft nude mice resulted in the reduction of tumor volume. Moreover, we found that apoptosis protein caspase 3 was up-regulated in the Ad-siMDM2-, Ad-NDRG2-, and Ad-siMDM2-NDRG2-treated groups. Our data indicate that the adenovirus-mediated MDM2 silencing and NDRG2 overexpression can synergistically inhibit local cancer cell proliferation, induce apoptosis, and further prevent metastases of SCC. Our study provides a promising method that can be further developed as a new therapeutic approach against SCC. [ABSTRACT FROM AUTHOR]

Many studies have evaluated the association between serum levels of mannose-binding lectin (MBL) and sepsis; however, the findings are inconclusive and conflicting. For a better understanding of MBL in sepsis, we conducted a comprehensive meta-analysis. Potential relevant studies were identified covering Science Citation Index, the Cochrane Library, PubMed, Embase, CINAHL, and Current Contents Index databases. Two reviewers extracted data and assessed studies independently. Statistical analyses were conducted with the version 12.0 STATA statistical software. Ten papers were collected for meta-analysis. Results identified that sepsis patients had considerably lower MBL level than those in the controls (standardized mean difference (SMD) = 1.59, 95 % confidence interval (95%CI) = 0.86∼2.31, P < 0.001). Ethnicity-subgroup analysis showed that sepsis patients were associated with decreased serum MBL level in contrast to the healthy controls in Asians (SMD = 3.07, 95%CI = 1.27∼4.88, P = 0.001) and Caucasians (SMD = 1.00, 95%CI = 0.35∼1.65, P = 0.003). In the group-stratified subgroup analysis, subjects with lower serum MBL level did underpin susceptibility to sepsis in the infants subgroup (SMD = 2.57, 95%CI = 1.59∼3.55, P < 0.001); however, this was not the case in the adults subgroup (SMD = 0.13, 95%CI = −1.30∼1.55, P = 0.862). Our study suggests an important involvement of serum MBL level in sepsis patients considering their lower level compared to controls, especially among infants. [ABSTRACT FROM AUTHOR]

User authentication scheme allows user and server to authenticate each other, and generates a session key for the subsequent communication. How to resist the password guessing attacks and smart card stolen attacks are two key problems for designing smart cart and password based user authentication scheme. In 2011, Li and Lee proposed a new smart cart and password based user authentication scheme with smart card revocation, and claimed that their scheme could be immunity to these attacks. In this paper, we show that Li and Lee's scheme is vulnerable to off-line password guessing attack once the information stored in smart card is extracted, and it does not provide perfect forward secrecy. A robust user authentication scheme with smart card revocation is then proposed. We use a most popular and widely used formal verification tool ProVerif, which is based on applied pi calculus, to prove that the proposed scheme achieves security and authentication. [ABSTRACT FROM AUTHOR]

The tumour necrosis factor (TNF) family is crucial for immune homeostasis, cell death and inflammation. These cytokines are recognized by members of the TNF receptor (TNFR) family of death receptors, including TNFR1 and TNFR2, and FAS and TNF-related apoptosis-inducing ligand (TRAIL) receptors. Death receptor signalling requires death-domain-mediated homotypic/heterotypic interactions between the receptor and its downstream adaptors, including TNFR1-associated death domain protein (TRADD) and FAS-associated death domain protein (FADD). Here we discover that death domains in several proteins, including TRADD, FADD, RIPK1 and TNFR1, were directly inactivated by NleB, an enteropathogenic Escherichia coli (EPEC) type III secretion system effector known to inhibit host nuclear factor-κB (NF-κB) signalling. NleB contained an unprecedented N-acetylglucosamine (GlcNAc) transferase activity that specifically modified a conserved arginine in these death domains (Arg 235 in the TRADD death domain). NleB GlcNAcylation (the addition of GlcNAc onto a protein side chain) of death domains blocked homotypic/heterotypic death domain interactions and assembly of the oligomeric TNFR1 complex, thereby disrupting TNF signalling in EPEC-infected cells, including NF-κB signalling, apoptosis and necroptosis. Type-III-delivered NleB also blocked FAS ligand and TRAIL-induced cell death by preventing formation of a FADD-mediated death-inducing signalling complex (DISC). The arginine GlcNAc transferase activity of NleB was required for bacterial colonization in the mouse model of EPEC infection. The mechanism of action of NleB represents a new model by which bacteria counteract host defences, and also a previously unappreciated post-translational modification. [ABSTRACT FROM AUTHOR]

Wooden activated carbon fibers (WACFs) were prepared from phenolated Chinese fir ( Cunninghamia lanceolata) using CO activation; microstructure characterization, the adsorption capacity, BET-specific surface area, and pore distribution of WACFs were investigated by SEM and X-ray analysis. Results showed that WACFs have a smooth surface and round or elliptical cross-section. The (002) crystal plane diffraction peak of the WACFs was obviously heightened, also showing an apparent (100) diffraction peak. With increased activation temperature, the value of d gradually decreased, whereas the values of the crystallite sizes L and L initially decreased and then increased. The L/ d and g values corresponding to the degree of change in the graphitization structure increased. WACFs mainly have micropores as well as a few macro- and mesopores. The micropore diameter of WACFs has a narrow range (0.3-0.5 nm). With increased activation temperature, the single-point surface area, Brunauer-Emmett-Teller surface area, micropore area, single-point total pore volume, and micropore volume of WACFs increased, while the pore diameter decreased. At 900 °C, the iodine adsorption and yield rate of WACFs were 779.22 mg/g and 51.48 %, respectively. [ABSTRACT FROM AUTHOR]

Rab GTPases are emerging targets of diverse bacterial pathogens. Here, we perform biochemical and structural analyses of LepB, a Rab GTPase-activating protein (GAP) effector from Legionella pneumophila. We map LepB GAP domain to residues 313-618 and show that the GAP domain is Rab1 specific with a catalytic activity higher than the canonical eukaryotic TBC GAP and the newly identified VirA/EspG family of bacterial RabGAP effectors. Exhaustive mutation analyses identify Arg444 as the arginine finger, but no catalytically essential glutamine residues. Crystal structures of LepB313-618 alone and the GAP domain of Legionella drancourtii LepB in complex with Rab1-GDP-AlF3 support the catalytic role of Arg444, and also further reveal a 3D architecture and a GTPase-binding mode distinct from all known GAPs. Glu449, structurally equivalent to TBC RabGAP glutamine finger in apo-LepB, undergoes a drastic movement upon Rab1 binding, which induces Rab1 Gln70 side-chain flipping towards GDP-AlF3 through a strong ionic interaction. This conformationally rearranged Gln70 acts as the catalytic cis-glutamine, therefore uncovering an unexpected RasGAP-like catalytic mechanism for LepB. Our studies highlight an extraordinary structural and catalytic diversity of RabGAPs, particularly those from bacterial pathogens. [ABSTRACT FROM AUTHOR]

A novel adaptive data driven control strategy is proposed for general discrete non-linear systems. The controller is designed based upon the Simultaneous Perturbation Stochastic Approximation (SPSA) method, and is constructed through use of a Function Approximator (FA), which is fixed as a neural network here. In this novel control strategy, the parametric estimation is designed to be adaptive with convergence analysis, and the control ability has been greatly improved. The proposed control method is finally applied into the non-linear tracking problems, as well as near-optimal control problems for discrete-time non-linear systems. Simulation comparison tests were conducted on typical non-linear plants, through which, the convergence and feasibility of the proposed adaptive data driven control strategy are well demonstrated. [ABSTRACT FROM AUTHOR]

Background: To determine whether the inferior outcome noted with triple-negative breast cancer (TNBC) reflects a higher risk population among patients with breast cancer liver metastases. Methods: A total of 123 patients with breast cancer liver metastases diagnosed at Tianjin Medical University Cancer Hospital were included in this study. Breast cancer subtype was assigned using immunohistochemistry or fluorescence in situ hybridization: hormone receptor (HR) positive (+)/human epidermal growth factor receptor 2 (HER2) negative (−), HR+/HER2+, HR−/HER2+ and triple-negative subtype. Clinical features and survival were evaluated in different subtypes. Results: The median age at breast cancer diagnosis was 47 years (range, 23-67 years). Breast cancer subtype was confirmed in all patients (39.8% with HR+/HER2−, 24.4% with HR+/HER2+, 15.3% with HR−/HER2+ and 20.3% with TNBC). The median overall survival after liver metastases was 29 months (range, 4-89 months), and the overall 1-, 2- and 3-year survival rate was 68.3, 48.0 and 34.1%, respectively. Survival was found to be impacted by breast cancer subtype ( P = 0.001), and was shortest for patients with TNBC. Time to liver metastases (TTLM) less than 24 months and liver metastasis lesions ≥3 were found to be important predictors of poor survival after liver metastases ( P = 0.009 and 0.001, respectively). Conclusions: The results indicate that clinical breast cancer subtype remains an independent prognostic predictor among patients with breast cancer liver metastases. Liver metastases arising from TNBC confers the worst prognosis, and novel agents capable of controlling intrahepatic and extrahepatic TNBC are needed. [ABSTRACT FROM AUTHOR]

Typical peptides composed of Phe, Ile, and Arg residues have not been reported, and the effect of the helix-forming unit (HFU) composed of the tripeptide core on biological activity remains unclear. In this study, multimers of the 3-residue HFU were designed to investigate the structure-function relationships. The in vitro biological activities of the peptides were determined. We used synthetic lipid vesicles and intact bacteria to assess the interactions of the peptides with cell membranes. The well-studied peptide melittin was chosen as a control peptide. The results showed that the antimicrobial and hemolytic activities of the peptides increased with the number of HFUs. HFU3 had optimal cell selectivity as determined by the therapeutic index. HFU3 and HFU4 exhibited strong resistance to salts, pH, and heat. CD spectra revealed that the peptides except HFU2 displayed α-helix-rich secondary structures in the presence of SDS or trifluoroethanol (TFE). The peptides interacted weakly with zwitterionic phospholipids (mimicking mammalian membranes) but strongly with negatively charged phospholipids (mimicking bacterial membranes), which corresponds well with the data for the biological activities. There was a correlation between the cell selectivity of the peptides and their high binding affinity with negatively charged phospholipids. Cell membrane permeability experiments suggest that the peptides targeted the cell membrane, and HFU3 showed higher permeabilization of the inner membrane but lower permeabilization of the outer membrane than melittin. These findings provide the new insights to design antimicrobial peptides with antimicrobial potency by trimers. [ABSTRACT FROM AUTHOR]

The selection and popularization of early-maturing cotton is paramount in resolving the conflict between occupying farmlands utilizing grain and cotton while optimizing agricultural structure. Node of first fruiting branch (NFFB) and its height (HNFFB) can be used as the important indicators to measure cotton earliness. In this study, Baimian2, an early-maturing upland cotton ( Gossypium hirsutum L.) variety, was used as the female parent crossed with a late-maturing material (TM-1) and intermediate-maturing variety (CIR12), respectively. Quantitative trait locus (QTL) detection for NFFB and HNFFB was performed within the two F populations, Baimian2 × TM-1 and Baimian2 × CIR12 by composite interval mapping (CIM) and mixed model CIM (MCIM). Eight QTL (three suggestive and five significant) for NFFB and six QTL (three suggestive and three significant) for HNFFB were detected in both populations, located on C1(A1), C5(A5), C6(A6), C9(A9), C11(A11), C13(A13), C17(D3), C25(D6), C12(A12)/C26(D12) and LG1. Results of QTL are consistent with separation analysis to some extent. The two significant major QTL, qNFFB- 17- I for NFFB and qHNFFB- 17- I for HNFFB, were detected simultaneously by CIM and MCIM. They had high reliability and could be used for the marker-assisted breeding to improve cotton earliness. Single marker-analysis showed that 11 molecular markers, such as CGR5222, are linked with NFFB and/or HNFFB. [ABSTRACT FROM AUTHOR]

Dynamic programming is a very useful tool in solving optimization and optimal control problems. Here, the Approximate Dynamic Programming (ADP) and the notion of neural networks based predictive control are combined with a model-free control method based on SPSA (Simultaneous perturbation stochastic approximation), and a novel ADP based model-free predictive control strategy for nonlinear systems is proposed. Dynamic programming is used to adjust the control parameters in the novel model-free control method and the notion of predictive control is introduced to modify the whole control structure. Finally, the proposed ADP based model-free predictive control strategy is applied to solve nonlinear tracking problems and the effectiveness of this novel control method is fully illustrated though simulation tests on two typical nonlinear systems. [ABSTRACT FROM AUTHOR]