Labeled Subgraph Entropy Kernel

In recent years, kernel methods are widespread in tasks of similarity measuring. Specifically, graph kernels are widely used in fields of bioinformatics, chemistry and financial data analysis. However, existing methods, especially entropy based graph kernels are subject to large computational complexity and the negligence of node-level information. In this paper, we propose a novel labeled subgraph entropy graph kernel, which performs well in structural similarity assessment. We design a dynamic programming subgraph enumeration algorithm, which effectively reduces the time complexity. Specially, we propose labeled subgraph, which enriches substructure topology with semantic information. Analogizing the cluster expansion process of gas cluster in statistical mechanics, we re-derive the partition function and calculate the global graph entropy to characterize the network. In order to test our method, we apply several real-world datasets and assess the effects in different tasks. To capture more experiment details, we quantitatively and qualitatively analyze the contribution of different topology structures. Experimental results successfully demonstrate the effectiveness of our method which outperforms several state-of-the-art methods.Comment: 9 pages,5 figure

Time delay estimation in the ultrasonic flowmeter in the oil well

AbstractA new prototype of ultrasonic flowmeter used in the oil well is presented. The flowmeter depends on the time delay between the propagating times of the downstream and upstream ultrasonic pulses. The ultrasonic passageway is slanted to prevent the disadvantage introduced by the high viscosity of the oil. Two method of time delay estimation: threshold and cross-correlation are both studied and realized

Adenovirus-mediated siRNA targeting Bcl-xL inhibits proliferation, reduces invasion and enhances radiosensitivity of human colorectal cancer cells

<p>Abstract</p> <p>Introduction</p> <p>Bcl-xL, an important member of anti-apoptotic Bcl-2 family, plays critical roles in tumor progression and development. Previously, we have reported that overexpression of Bcl-xL was correlated with prognosis of colorectal cancer (CRC) patients. The aim of this study was to investigate the association of Bcl-xL expression with invasion and radiosensitivity of human CRC cells.</p> <p>Methods</p> <p>RT-PCR and Western blot assays were performed to determine the expression of Bcl-xL mRNA and protein in CRC cells and normal human intestinal epithelial cell line. Then, adenovirus-mediated RNA interference technique was employed to inhibit the expression of Bcl-xL gene in CRC cells. The proliferation of CRC cells was analyzed by MTT and colony formation assay. The migration and invasion of CRC cells was determined by wound-healing and tranwell invasion assays. Additionally, the in vitro and in vivo radiosensitivity of CRC cells was determined by clonogenic cell survival assay and murine xnograft model, respectively.</p> <p>Results</p> <p>The levels of Bcl-xL mRNA and protein expression were significantly higher in human CRC cells than in normal human intestinal epithelial cell line. Ad/shBcl-xL could significantly reduce the expression of Bcl-xL protein in CRC cells. Also, we showed that adenovirus-mediated siRNA targeting Bcl-xL could significantly inhibit proliferation and colony formation of CRC cells. Ad/shBcl-xL could significantly suppress migration and invasion of CRC cells. Moreover, Ad/shBcl-xL could enhance in vitro and in vivo radiosensitivity of CRC cells by increasing caspase-dependent apoptosis.</p> <p>Conclusions</p> <p>Targeting Bcl-xL will be a promising strategy to inhibit the metastatic potential and reverse the radioresistance of human CRC.</p

Two-level Graph Neural Network

Graph Neural Networks (GNNs) are recently proposed neural network structures for the processing of graph-structured data. Due to their employed neighbor aggregation strategy, existing GNNs focus on capturing node-level information and neglect high-level information. Existing GNNs therefore suffer from representational limitations caused by the Local Permutation Invariance (LPI) problem. To overcome these limitations and enrich the features captured by GNNs, we propose a novel GNN framework, referred to as the Two-level GNN (TL-GNN). This merges subgraph-level information with node-level information. Moreover, we provide a mathematical analysis of the LPI problem which demonstrates that subgraph-level information is beneficial to overcoming the problems associated with LPI. A subgraph counting method based on the dynamic programming algorithm is also proposed, and this has time complexity is O(n^3), n is the number of nodes of a graph. Experiments show that TL-GNN outperforms existing GNNs and achieves state-of-the-art performance.Comment: 14 pages, 10 figure

Structural and Biochemical Bases for the Inhibition of Autophagy and Apoptosis by Viral BCL-2 of Murine γ-Herpesvirus 68

All gammaherpesviruses express homologues of antiapoptotic B-cell lymphoma-2 (BCL-2) to counter the clearance of infected cells by host antiviral defense machineries. To gain insights into the action mechanisms of these viral BCL-2 proteins, we carried out structural and biochemical analyses on the interactions of M11, a viral BCL-2 of murine γ-herpesvirus 68, with a fragment of proautophagic Beclin1 and BCL-2 homology 3 (BH3) domain-containing peptides derived from an array of proapoptotic BCL-2 family proteins. Mainly through hydrophobic interactions, M11 bound the BH3-like domain of Beclin1 with a dissociation constant of 40 nanomole, a markedly tighter affinity compared to the 1.7 micromolar binding affinity between cellular BCL-2 and Beclin1. Consistently, M11 inhibited autophagy more efficiently than BCL-2 in NIH3T3 cells. M11 also interacted tightly with a BH3 domain peptide of BAK and those of the upstream BH3-only proteins BIM, BID, BMF, PUMA, and Noxa, but weakly with that of BAX. These results collectively suggest that M11 potently inhibits Beclin1 in addition to broadly neutralizing the proapoptotic BCL-2 family in a similar but distinctive way from cellular BCL-2, and that the Beclin1-mediated autophagy may be a main target of the virus

Iridescent Daytime Radiative Cooling with No Absorption Peaks in the Visible Range

Coatings for passive radiative cooling applications must be highly reflected in the solar spectrum, and thus can hardly support any coloration without losing their functionality. In this work, a colorful daytime radiative cooling surface based on structural coloration is reported. A designed radiative cooler with a bioinspired array of truncated SiO2 microcones is manufactured via a self-assembly method and reactive ion etching. Complemented with a silver reflector, the radiative cooler exhibits broadband iridescent coloration due to the scattering induced by the truncated microcone array while maintaining an average reflectance of 95% in the solar spectrum and a high thermal emissivity (ε) of 0.95, owing to the reduced impedance mismatch provided by the patterned surface at infrared wavelengths, reaching an estimated cooling power of ≈143&nbsp;W&nbsp;m-2 at an ambient temperature of 25&nbsp;°C and a measured average temperature drop of 7.1&nbsp;°C under direct sunlight. This strong cooling performance is attributed to its bioinspired surface pattern, which promotes both the aesthetics and cooling capacity of the daytime radiative cooler

A Novel Inhibitory Mechanism of Mitochondrion-Dependent Apoptosis by a Herpesviral Protein

Upon viral infection, cells undergo apoptosis as a defense against viral replication. Viruses, in turn, have evolved elaborate mechanisms to subvert apoptotic processes. Here, we report that a novel viral mitochondrial anti-apoptotic protein (vMAP) of murine γ-herpesvirus 68 (γHV-68) interacts with Bcl-2 and voltage-dependent anion channel 1 (VDAC1) in a genetically separable manner. The N-terminal region of vMAP interacted with Bcl-2, and this interaction markedly increased not only Bcl-2 recruitment to mitochondria but also its avidity for BH3-only pro-apoptotic proteins, thereby suppressing Bax mitochondrial translocation and activation. In addition, the central and C-terminal hydrophobic regions of vMAP interacted with VDAC1. Consequently, these interactions resulted in the effective inhibition of cytochrome c release, leading to the comprehensive inhibition of mitochondrion-mediated apoptosis. Finally, vMAP gene was required for efficient γHV-68 lytic replication in normal cells, but not in mitochondrial apoptosis-deficient cells. These results demonstrate that γHV-68 vMAP independently targets two important regulators of mitochondrial apoptosis-mediated intracellular innate immunity, allowing efficient viral lytic replication

OpenFermion: The Electronic Structure Package for Quantum Computers

Quantum simulation of chemistry and materials is predicted to be an important application for both near-term and fault-tolerant quantum devices. However, at present, developing and studying algorithms for these problems can be difficult due to the prohibitive amount of domain knowledge required in both the area of chemistry and quantum algorithms. To help bridge this gap and open the field to more researchers, we have developed the OpenFermion software package (www.openfermion.org). OpenFermion is an open-source software library written largely in Python under an Apache 2.0 license, aimed at enabling the simulation of fermionic models and quantum chemistry problems on quantum hardware. Beginning with an interface to common electronic structure packages, it simplifies the translation between a molecular specification and a quantum circuit for solving or studying the electronic structure problem on a quantum computer, minimizing the amount of domain expertise required to enter the field. The package is designed to be extensible and robust, maintaining high software standards in documentation and testing. This release paper outlines the key motivations behind design choices in OpenFermion and discusses some basic OpenFermion functionality which we believe will aid the community in the development of better quantum algorithms and tools for this exciting area of research.Comment: 22 page

OCLN as a novel biomarker for prognosis and immune infiltrates in kidney renal clear cell carcinoma: an integrative computational and experimental characterization

BackgroundOccludin (OCLN) is an important tight junction protein and has been reported to be abnormally expressed in the development of malignant tumors. However, its biomarker and carcinogenic roles in kidney renal clear cell carcinoma (KIRC) are less investigated.MethodsThe Cancer Genome Atlas database and Human Protein Atlas database were used to analyze the expression of OCLN in KIRC. UALCAN database and methylation-specific PCR assay were used to evaluate the methylation level of OCLN in KIRC. Univariate and multivariate Cox regression analyses were performed to model the prognostic significance of OCLN in KIRC patient cohorts. The correlation between OCLN expression and the immune cell infiltration, immune-related function and immune checkpoints were explored. Finally, EdU, scratch assay and transwell experiments were conducted to validate the role of OCLN in KIRC development.ResultsThe expression of OCLN was significantly downregulated in KIRC, compared with normal renal tissues (p&lt;0.001). Patients with low OCLN expression showed a worse prognosis and poorer clinicopathological characteristics. Functional enrichment analysis revealed that OCLN was mainly involved in biological processes such as immune response, immunoglobulin complex circulating and cytokine and chemokine receptor to mediate KIRC development. Immune-related analysis indicated that OCLN could potentially serve as a candidate target for KIRC immunotherapy. OCLN overexpression inhibited proliferation, migration and invasion of KIRC cells in vitro.ConclusionOCLN was validated as a candidate prognostic biomarker and therapeutic target of KIRC based both on computational and experimental approaches. More in vivo experiments will be conducted to decode its molecular mechanism in KIRC carcinogenesis in the future work