Identification of methotrexate as a heterochromatin-promoting drug.

Heterochromatin is a tightly packed form of DNA involved in gene silencing, chromosome segregation, and protection of genome stability. Heterochromatin is becoming more recognized in tumor suppression and may thus serve as a potential target for cancer therapy. However, to date there are no drugs that are well established to specifically promote heterochromatin formation. Here, we describe a screening method using Drosophila to identify small molecule compounds that promote heterochromatin formation, with the purpose of developing epigenetic cancer therapeutics. We took advantage of a Drosophila strain with a variegated eye color phenotype that is sensitive to heterochromatin levels, and screened a library of 97 FDA approved oncology drugs. This screen identified methotrexate as the most potent small molecule drug, among the 97 oncology drugs screened, in promoting heterochromatin formation. Interestingly, methotrexate has been identified as a JAK/STAT inhibitor in a functional screen, causing reduced phosphorylation of STAT proteins. These findings are in line with our previous observation that unphosphorylated STAT (uSTAT) promotes heterochromatin formation in both Drosophila and human cells and suppresses tumor growth in mouse xenografts. Thus, Drosophila with variegated eye color phenotypes could be an effective tool for screening heterochromatin-promoting compounds that could be candidates as cancer therapeutics

Endogenous IL-33 and Its Autoamplification of IL-33/ST2 Pathway Play an Important Role in Asthma.

IL-33 and its receptor ST2 are contributing factors to airway inflammation and asthma exacerbation. The IL-33/ST2 signaling pathway is involved in both the onset and the acute exacerbations of asthma. In this study, we address the role of endogenous IL-33 and its autoamplification of the IL-33/ST2 pathway in Ag-dependent and Ag-independent asthma-like models. Wild-type, IL-33 knockout, ST2 knockout mice were either intratracheally administrated with 500 ng of rIL-33 per day for four consecutive days or were sensitized and challenged with OVA over 21 d. In wild-type mice, IL-33 or OVA induced similar airway hyperresponsiveness and eosinophilic airway inflammation. IL-33 induced its own mRNA and ST2L mRNA expression in the lung. IL-33 autoamplified itself and ST2 protein expression in airway epithelial cells. OVA also induced IL-33 and ST2 protein expression. In IL-33 knockout mice, the IL-33- and OVA-induced airway hyperresponsiveness and eosinophilic airway inflammation were both significantly attenuated, whereas IL-33-induced ST2L mRNA expression was preserved, although no autoamplification of IL-33/ST2 pathway was observed. In ST2 knockout mice, IL-33 and OVA induced airway hyperresponsiveness and eosinophilic airway inflammation were both completely diminished, and no IL-33/ST2 autoamplification was observed. These results suggest that endogenous IL-33 and its autoamplification of IL-33/ST2 pathway play an important role in the induction of asthma-like phenotype. Thus an intact IL-33/ST2 pathway is necessary for both Ag-dependent and Ag-independent asthma-like mouse models

Theoretical and Experimental Research on CO2 Electrical Heating Pool Boiling Heat Transfer Outside a Horizontal Tube

Numerical simulation on electrical heating pool boiling heat transfer with CO2 as refrigerant outside a horizontal tube is carried. A voltage-controlled heating method has been used in the experiment, with the advantages of good stability and adjustability of the experimental heat flux density. After a series of preliminary calculation and pre-work, numerical simulation is carried based on a software FLUENT. Bubble behaviors are observed, the distribution regularity of volume fraction of vapor is obtained and compared with the experimental results. The results show that numerical simulation and experimental results are in good agreement. Furthermore, by changing the heat flux density, the comparison of velocity on center location of experimental tube is analyzed. Varying pattern is satisfying. Evidently, for velocity, the simulation values are relatively higher and the data locate in the range of 1.40~1.52 times higher than the experimental data. This paper makes useful exploration of CO2 pool boiling heat transfer and the design of evaporator

Joint Motion Deblurring and Superresolution from Single Blurry Image

Currently superresolution from a motion blurred image still remains a challenging task. The conventional approach, which preprocesses the blurry low resolution (LR) image with a deblurring algorithm and employs a superresolution algorithm, has the following limitation. The high frequency texture of the image is unavoidably lost in the deblurring process and this loss restricts the performance of the subsequent superresolution process. This paper presents a novel technique that performs motion deblurring and superresolution jointly from one single blurry image. The basic idea is to regularize the ill-posed reconstruction problem using an edge-preserving gradient prior and a sparse kernel prior. This method derives from an inverse problem approach under an efficient optimization scheme that alternates between blur kernel estimation and superresolving until convergence. Furthermore, this paper proposes a simple and efficient refinement formulation to remove artifacts and render better deblurred high resolution (HR) images. The improvements brought by the proposed combined framework are demonstrated by the processing results of both simulated and real-life images. Quantitative and qualitative results on challenging examples show that the proposed method outperforms the existing state-of-the-art methods and effectively eliminates motion blur and artifacts in the superresolved image

Di-μ-oxido-bis­[(4-formyl-2-methoxy­phenolato-κO 1)oxido(1,10-phenan­throline-κ2 N,N′)vanadium(V)]

The title complex, [V2(C8H7O3)2O4(C12H8N2)2], is a centrosymmetric dimer formed by two VV complex units bridged by two μ2-oxido groups. The VV atom is six-coordinated by three oxide O atoms, one O atom from a vanillinate ligand and two N atoms from a 1,10-phenanthroline ligand in a significantly distorted octa­hedral geometry. In the crystal structure, weak inter­molecular C—H⋯O hydrogen bonds connect the mol­ecules into a three-dimensional network

(Methoxo-κO)oxidobis(quinolin-8-olato-κ2 N,O)vanadium(V)

In the title complex, [V(C9H6NO)2(CH3O)O], the central VV atom is coordinated by the O atoms from the oxido and methoxo ligands and the N and O atoms of two bis-chelating quinolin-8-olate ligands, forming a distorted octa­hedral environment. In the crystal structure, weak inter­molecular C—H⋯O hydrogen bonds connect mol­ecules into centrosymmetric dimers which are, in turn, linked by weak C—H⋯π inter­actions into chains along the b axis

A Framework For Refining Text Classification and Object Recognition from Academic Articles

With the widespread use of the internet, it has become increasingly crucial to extract specific information from vast amounts of academic articles efficiently. Data mining techniques are generally employed to solve this issue. However, data mining for academic articles is challenging since it requires automatically extracting specific patterns in complex and unstructured layout documents. Current data mining methods for academic articles employ rule-based(RB) or machine learning(ML) approaches. However, using rule-based methods incurs a high coding cost for complex typesetting articles. On the other hand, simply using machine learning methods requires annotation work for complex content types within the paper, which can be costly. Furthermore, only using machine learning can lead to cases where patterns easily recognized by rule-based methods are mistakenly extracted. To overcome these issues, from the perspective of analyzing the standard layout and typesetting used in the specified publication, we emphasize implementing specific methods for specific characteristics in academic articles. We have developed a novel Text Block Refinement Framework (TBRF), a machine learning and rule-based scheme hybrid. We used the well-known ACL proceeding articles as experimental data for the validation experiment. The experiment shows that our approach achieved over 95% classification accuracy and 90% detection accuracy for tables and figures.Comment: This paper has been accepted at 'The International Symposium on Innovations in Intelligent Systems and Applications 2023 (INISTA 2023)