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Hierarchically porous TS-1/modified-diatomite composites with high removal efficiency for methylene blue (MB) were prepared via a facile in situ hydrothermal route. The surface charge state of the diatomite was modified to enhance the electrostatic interactions, followed by in situ hydrothermal coating with TS-1 nanoparticles. The zeolite loading amount in the composites could be adjusted by changing the hydrothermal time. The highest specific surface area and micropore volume of the obtained composites were 521.3 m 2 /g and 0.254 cm 3 /g, respectively, with an optimized zeolite loading amount of 96.8%. Based on the synergistic effect of efficient adsorption and photocatalysis resulting from the newly formed hierarchically porous structure and improved dispersion of TS-1 nanoparticles onto diatomite, the composites’ removal efficiency for MB reached 99.1% after 2 h of photocatalytic reaction, even higher than that observed using pure TS-1 nanoparticles. Moreover, the superior MB removal kinetics of the composites were well represented by a pseudo-first-order model, with a rate constant (5.28 × 10 −2 min −1 ) more than twice as high as that of pure TS-1 nanoparticles (2.43 × 10 −2 min −1 ). The significant dye removal performance of this novel TS-1/modified-diatomite composite indicates that it is a promising candidate for use in waste water treatment. [ABSTRACT FROM AUTHOR]

MicroRNA-1 (miR-1) is approved involved in cardiac hypertrophy, but the underlying molecular mechanisms of miR-1 in cardiac hypertrophy are not well elucidated. The present study aimed to investigate the potential role of miR-1 in modulating CDKs-Rb pathway during cardiomyocyte hypertrophy. A rat model of hypertrophy was established with abdominal aortic constriction, and a cell model of hypertrophy was also achieved based on PE-promoted neonatal rat ventricular cardiomyocytes (NRVCs). We demonstrated that miR-1 expression was markedly decreased in hypertrophic myocardium and hypertrophic cardiomyocytes. Dual luciferase reporter assays revealed that miR-1 interacted with the 3′UTR of CDK6, and miR-1 was verified to inhibit CDK6 expression at the posttranscriptional level. CDK6 protein expression was observed increased in hypertrophic myocardium and hypertrophic cardiomyocytes. Morover, miR-1 mimic, in parallel to CDK6 siRNA, could inhibit PE-induced hypertrophy of NRVCs, with decreases in cell size, newly transcribed RNA, expressions of ANF and β-MHC, and the phosphorylated pRb. Taken together, our results reveal that derepression of CDK6 and activation of Rb pathway contributes to the effect of attenuation of miR-1 on provoking cardiomyocyte hypertrophy. [ABSTRACT FROM AUTHOR]

Porous Co 3 O 4 nanosheets anchored on graphene nanosheets were synthesized by microwave irradiation method. The obtained Co 3 O 4 –graphene sheet-on-sheet nanocomposite as an anode material for LIBs demonstrates a high initial discharge capacity of 1359.6 mAh g −1 with a Columbic efficiency of 72.7% at a rate of 100 mA g −1 . Moreover, a significantly enhanced reversible capacity of ∼1036.9 mAh g −1 is retained after 50 cycles, and the capacity can reincrease to 1068 mAh g −1 when the current density returns back to 100 mA g −1 after cycled at various rates for 50 cycles. The improved electrochemical performance is attributed to the unique architectures of the porous Co 3 O 4 nanosheets and the incorporation of graphene nanosheets. Therefore, this nanocomposite is widely considered to be an attractive candidate as an anode material for next-generation LIBs. [ABSTRACT FROM AUTHOR]

Objective Evidence shows that both macrophage migration inhibitory factor (MIF) and GLUT4 glucose transporter are involved in diabetic cardiomyopathy (DCM), but it remains largely unknown whether and how MIF regulates GLUT4 expression in cardiomyocytes. The present study aims to investigate the mechanism underlying the modulation of GLUT4 by MIF in cardiomyocytes. Material and methods Activations of AKT and AMPK signaling, and expressions of MIF, GLUT4 and the candidate GLUT4 regulation associated transcription factors in the diabetic mouse myocardium were determined. The screened transcription factors mediating MIF-promoted GLUT4 expression were verified by RNA interference (RNAi) and electrophoretic mobility shift assay (EMSA), respectively. Results MIF was increased, but GLUT4 was decreased in the diabetic mouse myocardium. MIF could enhance glucose uptake and up-regulate GLUT4 expression in NMVCs. Expressions of transcription factor MEF2A, -2C, -2D and Zac1 were significantly up-regulated in MIF-treated neonatal mouse ventricular cardiomyocytes (NMVCs), and markedly reduced in the diabetic myocardium. Knockdown of MEF2A, -2C, -2D and Zac1 could significantly inhibit glucose uptake and GLUT4 expression in cardiomyocytes. Moreover, EMSA results revealed that transcriptional activities of MEF2 and Zac1 were significantly increased in MIF-treated NMVCs. AMPK signaling was activated in MIF-stimulated NMVCs, and AMPK activator AICAR could enhance MEF2A, -2C, -2D, Zac1 and GLUT4 expression. Additionally, MIF effects were inhibited by an AMPK inhibitor compound C and siRNA targeting MIF receptor CD74, suggesting the involvement of CD74-dependent AMPK activation. Conclusions Transcription factor MEF2 and Zac1 mediate MIF-induced GLUT4 expression through CD74-dependent AMPK activation in cardiomyocytes. [ABSTRACT FROM AUTHOR]

Novel hierarchically porous nanocomposites of diatomite-based ceramic supports coated with silicalite-1 (Sil-1) nanoparticles for benzene adsorption were prepared via a facile preparation route. In this route, porous ceramic supports with three-dimensional reticulated structures were first prepared using the polymeric sponge method in which diatomite was used as the ceramic framework and polyurethane foam was used as the sacrificial template. This process was followed by facile in situ homogeneous coating of Sil-1 on the surface of the ceramic under mild conditions. The hierarchical porosity of the nanocomposites was due to the inherent micropores of Sil-1, the mesopores resulting from the stacking of Sil-1, and the hierarchical macropores of ceramic supports. The specific area and micropore volume of the nanocomposites were 122.9 m 2 /g and 0.07 cm 3 /g, respectively, with a high zeolite loading of 32.4%. The nanocomposites exhibited a much higher benzene adsorption capacity (133.3 mg/g(Sil-1)) compared with that of a commercial micron-sized ZSM-5 product (66.5 mg/g) and a synthesized Sil-1 (Sil SYN , 94.7 mg/g). Moreover, adsorption–desorption rate constants of the nanocomposites were three and five times higher than those of the ZSM-5 and Sil SYN , respectively, as evaluated via a gravimetric method using an intelligent gravimetric analyzer. The excellent benzene adsorption performance is ascribed not only to the in situ silicalite-1 coating process that facilitates the stability and dispersity of Sil-1 on the modified surface of the ceramic supports but also to the hierarchically porous monolithic structure of the nanocomposites, which is beneficial to the mass transfer efficiency for benzene adsorption. [ABSTRACT FROM AUTHOR]

Porous CoO microrods have been prepared by an ultrasound-assisted route with subsequent calcination. The as-prepared CoO microrods are composed of interconnected nanoparticles with porous characteristics. The ultrasonic irradiation is critical to determine the morphology and the electrochemical performance of the products. When tested as anode material for lithium-ion battery, the porous CoO microrods show improved capacity and rate cycling performance. The reversible capacity of the materials retains 678 (±5) mAh g after 50 cycles at 100 mA g. Even when cycled at various rate for more than 50 cycles, the reversible capacity recovers to 600 (±5) mAh g for the current of 100 mA g. The improved lithium-storage performance can be attributed to the reduced electrochemical reaction resistance due to the unique porous architecture of CoO microrods. [ABSTRACT FROM AUTHOR]

The beneficial effects of mesenchymal stem cells (MSCs) in cardiac cell therapy are greatly limited due to poor survival after transplantation into ischemic hearts. Here, we investigated whether caspase 8 small hairpin RNA (shRNA) modification enhance human MSCs (hMSCs) survival and improve infarcted heart function. Recombinant adenovirus encoding pre-miRNA-155-designed caspase 8 shRNA was prepared to inhibit caspase 8 expression in hMSCs. The effect of caspase 8 shRNA modification on protecting hMSCs from apoptosis under the conditions of serum deprivation and hypoxia was tested by Annexin V/PI staining and caspase 8 activity assay. The caspase 8 shRNA-modified and superparamagnetic iron oxide (SPIO)-labeled hMSCs were injected into the border zone of the infarcted region of rat heart. Echocardiography and Masson trichrome staining were performed to assess heart function and cardiac fibrosis. Our results showed that adenovirus-mediated caspase 8 shRNA could efficiently inhibit caspase 8 expression in hMSCs. Knock-down of caspase 8 expression lead to inhibition of hMSCs apoptosis, reduction of caspase 8 activity and up-regulations of HGF, IGF-1 and Bcl-2. Transplantation of caspase 8 shRNA-modified hMSCs could significantly improve infracted heart function, attenuate cardiac fibrosis. Consistently, the rate of cardiomyocyte apoptosis and caspase 8 activity were significantly decreased, and the survival rate of transplanted hMSCs was markedly elevated in the myocardium receiving caspase 8 shRNA-modified hMSCs transplantation. Together, our findings implicated the therapeutic potential of caspase 8 shRNA-modified hMSCs in improving the infarcted heart function. [ABSTRACT FROM AUTHOR]

Abstract: Classification techniques are important in bioinformatics analysis as they can separate various bioinformatical data into distinct groups. To obtain good classifiers, accurate labeling of the training data is required. However labeling in practical bioinformatics applications might be erroneous due to various reasons. To identify those mislabeled data, an ensemble learning based scheme, single-voting has been widely used. It generates multiple classifiers and makes use of their voting to detect mislabeled data. Single-voting scheme mainly consists of two components: data partitioning component to generate multiple classifiers, and mislabeled detection component to identify mislabeled data. Existing works in this field mainly focus on mislabeled detection part and neglect data partitioning. However, our analysis shows that data partitioning plays an important role in single-voting scheme. This analysis helps us proposing a novel multiple-voting scheme. It is superior to traditional single-voting by reducing the unreliable influence from data partitioning. Empirical and theoretical evaluations on a set of bioinformatics datasets illustrate the utility of our proposed scheme. [Copyright &y& Elsevier]

Highlights: [•] Porosity of diatomite-templated carbons was greatly enhanced by KOH activation. [•] KOH-activated carbons had much larger adsorption capacity than original carbons. [•] A mesopore-predominant zeolite, zeolite K-H, was prepared as a byproduct. [Copyright &y& Elsevier]

Highlights: [•] Porous CoO/C polyhedra were synthesized by reducing Co3O4 polyhedra with sugar. [•] The CoO/C polyhedra exhibited an initial discharge capacity of 1025mAhg−1. [•] Coulombic efficiency over 99% and improved rate capability were achieved for the CoO/C polyhedra. [•] Porous and hierarchical structure was responsible for the improved electrochemical performance. [ABSTRACT FROM AUTHOR]

Highlights: [•] Porosity of diatomite-templated carbon was greatly improved by physical activation. [•] Two-step CO2 activation was more efficient than H2O activation. [•] Derived carbons had 2–3 times larger pore parameters than original carbons. [•] CO2-activated carbon had a high methylene blue adsorption capacity (505.1mg/g). [ABSTRACT FROM AUTHOR]

Abstract: Novel porous NiO hollow microspheres are fabricated by a facile two-step method involving the ultrasound-assisted synthesis of nickel oxalate precursors and subsequent thermal annealing in air. The as-prepared NiO microspheres are composed of loosely packed nanoparticles with diameters around 30–80nm, and have a main pore distribution from 3 to 20nm with a mean pore size of 5.7nm. When evaluated as anode material for lithium ion battery, the porous NiO hollow microspheres showed enhanced electrochemical performance with high lithium storage capacity, satisfactory cyclability and rate capacity. The reversible capacity of the NiO microspheres retained 380mAhg−1 after 30 cycles at 200mAg−1. Even when cycled at various rate for more than 60 cycles, the capacity could recover to 520mAhg−1 for the current of 100mAg−1. The good lithium-storage performance can be attributed to the unique porous architecture, which provides the structural flexibility for volume change and the routes for fast Li+ diffusion. [Copyright &y& Elsevier]

This paper presents a new approach for identifying and eliminating mislabeled training instances for supervised learning algorithms. The novelty of this approach lies in the using of unlabeled instances to aid the detection of mislabeled training instances. This is in contrast with existing methods which rely upon only the labeled training instances. Our approach is straightforward and can be applied to many existing noise detection methods with only marginal modifications on them as required. To assess the benefit of our approach, we choose two popular noise detection methods: majority filtering (MF) and consensus filtering (CF). MFAUD/CFAUD is the new proposed variant of MF/CF which relies on our approach and denotes majority/ consensus filtering with the aid of unlabeled data. Empirical study validates the superiority of our approach and shows that MFAUD and CFAUD can significantly improve the performances of MF and CF under different noise ratios and labeled ratios. In addition, the improvement is more remarkable when the noise ratio is greater. [ABSTRACT FROM AUTHOR]

The topology of the trust network is important to optimize its usage in the trust-aware applications. However, since the users can join trust network ubiquitously, the structure of the highly dynamic trust network is still unknown. This paper contributes to verify that the trust network is the small-world network, and its small-world topology is independent of its dynamics. This is achieved by verifying the scale-freeness of five trust networks extracted from real online sites. Using the small-world nature of the trust network, we optimize the rating prediction mechanism of the conventional trust-aware recommender system. Experimental results clearly show that our proposed mechanism can achieve the maximum accuracy and coverage with the minimum computation complexity for the rating predictions. [ABSTRACT FROM AUTHOR]

Abstract: The trust network is a social network where nodes are inter-linked by their trust relations. It has been widely used in various applications, however, little is known about its structure due to its highly dynamic nature. Based on five trust networks obtained from the real online sites, we contribute to verify that the trust network is the small-world network: the nodes are highly clustered, while the distance between two randomly selected nodes is short. This has considerable implications on using the trust network in the trust-aware applications. We choose the trust-aware recommender system as an example of such applications and demonstrate its advantages by making use of our verified small-world nature of the trust network. [Copyright &y& Elsevier]

A number of studies have confirmed the relationship between constipation and gut microbiota. Additionally, many human and animal experiments have identified probiotics as effectors for the relief of constipation symptoms. In this study, probiotic compounds, including Lactobacillus acidophilus LA11-Onlly, Lacticaseibacillus rhamnosus LR22, Limosilactobacillus reuteri LE16, Lactiplantibacillus plantarum LP-Onlly, and Bifidobacterium animalis subsp. lactis BI516, were administered to mice with loperamide-induced constipation, and the impacts of these strains on constipation-related indicators and gut microbiota were evaluated. The effects of probiotic compounds on constipation relief were associated with various aspects, including gastrointestinal transit rate, number and weight of stools, serum and intestinal gastrointestinal regulatory hormones, and serum cytokines. Some of the probiotic compounds, including Limosilactobacillus reuteri, Lactiplantibacillus plantarum, and Lacticaseibacillus rhamnosus, were found to colonize the intestinal tract. Furthermore, higher dosages promoted the colonization of specific strains. This study yields a new perspective for the clinical use of probiotics to improve constipation symptoms by combining strains with different mechanisms for the alleviation of constipation. [ABSTRACT FROM AUTHOR]

(1) Background: Constipation is a common condition that affects the health and the quality of life of patients. Recent studies have suggested that the gut microbiome is associated with constipation, but these studies were mainly focused on a single research cohort. Thus, we aimed to construct a classification model based on fecal bacterial and identify the potential gut microbes' biomarkers. (2) Methods: We collected 3056 fecal amplicon sequence data from five research cohorts. The data were subjected to a series of analyses, including alpha- and beta-diversity analyses, phylogenetic profiling analyses, and systematic machine learning to obtain a comprehensive understanding of the association between constipation and the gut microbiome. (3) Results: The alpha diversity of the bacterial community composition was higher in patients with constipation. Beta diversity analysis evidenced significant partitions between the two groups on the base of gut microbiota composition. Further, machine learning based on feature selection was performed to evaluate the utility of the gut microbiome as the potential biomarker for constipation. The Gradient Boosted Regression Trees after chi2 feature selection was the best model, exhibiting a validation performance of 70.7%. (4) Conclusions: We constructed an accurate constipation discriminant model and identified 15 key genera, including Serratia, Dorea, and Aeromonas, as possible biomarkers for constipation. [ABSTRACT FROM AUTHOR]

Plant growth-promoting rhizobacteria (PGPR) have been reported to suppress various diseases as potential bioagents. It can inhibit disease occurrence through various means such as directly killing pathogens and inducing systemic plant resistance. In this study, a bacterium isolated from soil showed significant inhibition of Valsa mali. Morphological observations and phylogenetic analysis identified the strain as Pseudomonas thivervalensis , named K321. Plate confrontation assays demonstrated that K321 treatment severely damaged V. mali growth, with scanning electron microscopy (SEM) observations showing severe distortion of hyphae due to K321 treatment. In vitro twigs inoculation experiments indicated that K321 had good preventive and therapeutic effects against apple Valsa canker (AVC). Applying K321 on apples significantly enhanced the apple inducing systemic resistance (ISR), including induced expression of apple ISR-related genes and increased ISR-related enzyme activity. Additionally, applying K321 on apples can activate apple MAPK by enhancing the phosphorylation of MPK3 and MPK6. In addition, K321 can promote plant growth by solubilizing phosphate, producing siderophores, and producing 3-indole-acetic acid (IAA). Application of 0.2% K321 increased tomato plant height by 53.71%, while 0.1% K321 increased tomato fresh weight by 59.55%. Transcriptome analysis revealed that K321 can inhibit the growth of V. mali by disrupting the integrity of its cell membrane through inhibiting the metabolism of essential membrane components (fatty acids) and disrupting carbohydrate metabolism. In addition, transcriptome analysis also showed that K321 can enhance plant resistance to AVC by inducing ISR-related hormones and MAPK signaling, and application of K321 significantly induced the transcription of plant growth-related genes. In summary, an excellent biocontrol strain has been discovered that can prevent AVC by inducing apple ISR and directly killing V. mali. This study indicated the great potential of P. thivervalensis K321 for use as a biological agent for the control of AVC. [Display omitted] • K321 induces V. mali membrane disruption by altering V. mali fatty acid metabolism. • K321 exhibits both excellent protective and therapeutic effects against AVC. • K321 enhances apple resistance to AVC by inducing ISR. • K321 can significantly promote plant growth through multiple mechanisms. [ABSTRACT FROM AUTHOR]

Heterogeneous information network (HIN) embedding represents heterogeneous nodes as vectors in the low-dimensional space. Meta-path is used to measure the nodes similarity to guide HIN embedding. Existing works assume that different meta-paths share the same semantic space and directly fuse the different mate-paths for node similarity calculation. This ignores the incompatibility of different meta-paths, which cannot reflect the real relationship between nodes. To solve the problems of existing works, a novel S emantic-A ware H IN E mbedding (SAHE) is proposed to fuse incompatible meta-paths for node similarity measurement. The key idea of the proposed method is to measure the relative similarity relationship on each meta-path in its own semantic space, and aggregate these similarity relationships to obtain the node similarity to calculate HIN embedding. The kendall tau distance is used to aggregate the different similarity relationship in multiple semantic spaces. The semantic preference is extracted as a constraint to optimize the aggregated similarity matrix. The Kullback-Leibler Divergence (KL Divergence) is used to learn nodes embedding by measuring the node similarity distribution in the embedded space. Experiments on three real HIN datasets verify that the superiority of the proposed model is superior to other state-of-the-art methods on the node classification and the node clustering tasks. [ABSTRACT FROM AUTHOR]

Potato diseases and pests have a serious impact on the quality and yield of potatoes, and timely prevention and control of potato diseases and pests is essential. A rich knowledge reserve of potato diseases and pests is one of the most important prevention and control measures; however, valuable knowledge is buried in the massive data of potato diseases and pests, making it difficult for potato growers and managers to obtain and use it in a timely manner and to develop the potential of knowledge. Therefore, this paper explores the construction method of a knowledge graph for automatic knowledge extraction, which extracts the knowledge of potato diseases and pests scattered in heterogeneous data from multiple sources, organises it into a semantically related knowledge base, and provides potato growers with professional knowledge and timely guidance to effectively prevent and control potato diseases and pests. In this paper, a data corpus on potato diseases and pests, called PotatoRE, is first constructed. Then, a model of ALBert-BiLSTM-Self_Att-CRF is designed to extract knowledge from the corpus to form a triplet structure, which is imported into the Neo4j graph database for storage and visualisation. Furthermore, the performance of the model constructed in this paper is compared and verified using the datasets PotatoRE and People's Daily. The results show that compared to the SOTA models of ALBert BiLSTM-CRF and ALBert BiGRU-CRF, the accuracy of our model has been improved by 2.92% and 3.12%, respectively, using PotatoRE. Compared to the Bert BiLSTM-CRF model on two datasets, our model not only improves the accuracy, recall, and F1 values, but also has a higher efficiency. The model in this paper solves the problem of the difficult recognition of nested entities. On this basis, through comparative experiments, the TransH model is used to effectively represent the constructed knowledge graph, which lays the foundation for achieving inference, extension, and automatic updating of the knowledge base. The achievements of the thesis have made certain contributions to the automatic construction of large-scale knowledge bases. [ABSTRACT FROM AUTHOR]

The high cost for microalgae harvesting still is the bottleneck of microalgae commercial production. In the present study, the effect of adjusting pH to alkaline conditions with sodium hydroxide/calcium hydroxide and the addition of chitosan together with pH adjustments on the flocculation of Chlorella vulgaris (C. vulgaris) was studied, respectively. A single-factor experiment showed a maximum flocculation efficiency of 96.7% when adjusting the pH to 12 with calcium hydroxide. There was synergistic action between chitosan and calcium hydroxide. Flocculation conditions of C. vulgaris for the combined use of calcium hydroxide and chitosan was optimized by response surface methodology (RSM) with a Box-Behnken design (BBD). Flocculation efficiency reached 97.08% under optimal flocculation conditions when adjustion of pH to 8.97 with 2 g/L calcium hydroxide, a chitosan dosage of 20 mg/L, and a flocculation time of 60 min. The current study presents one method for efficient flocculation harvesting of C. vulgaris at weak alkaline conditions and low chitosan dosage. [ABSTRACT FROM AUTHOR]