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1.
Artigo em Inglês | MEDLINE | ID: mdl-33656987

RESUMO

The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model label dependencies to improve recognition performance. To capture and explore such important information, we propose Graph Convolutional Networks based models for multi-label recognition, where directed graphs are constructed over classes and information is propagated between classes to learn inter-dependent class-level representations. Following this idea, we design two particular models that approach multi-label classification from different views. In our first model, the prior knowledge about the class dependencies is integrated into classifier learning. Specifically, we propose Classifier-Learning-GCN to map class-level semantic representations (\eg, word embedding) into classifiers that maintain the inter-class topology. In our second model, we decompose the visual representation of an image into a set of label-aware features and propose Prediction-Learning-GCN to encode such features into inter-dependent image-level prediction scores. Furthermore, we also present an effective correlation matrix construction approach to capture inter-class relationships and consequently guide information propagation among classes. Empirical results on generic multi-label recognition demonstrate that the effectiveness of both two proposed models. Moreover, the proposed methods also show advantages in other multi-label related applications.

2.
J Chem Inf Model ; 61(3): 1066-1082, 2021 Mar 22.
Artigo em Inglês | MEDLINE | ID: mdl-33629839

RESUMO

The development of efficient models for predicting specific properties through machine learning is of great importance for the innovation of chemistry and material science. However, predicting global electronic structure properties like Frontier molecular orbital highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels and their HOMO-LUMO gaps from the small-sized molecule data to larger molecules remains a challenge. Here, we develop a multilevel attention neural network, named DeepMoleNet, to enable chemical interpretable insights being fused into multitask learning through (1) weighting contributions from various atoms and (2) taking the atom-centered symmetry functions (ACSFs) as the teacher descriptor. The efficient prediction of 12 properties including dipole moment, HOMO, and Gibbs free energy within chemical accuracy is achieved by using multiple benchmarks, both at the equilibrium and nonequilibrium geometries, including up to 110,000 records of data in QM9, 400,000 records in MD17, and 280,000 records in ANI-1ccx for random split evaluation. The good transferability for predicting larger molecules outside the training set is demonstrated in both equilibrium QM9 and Alchemy data sets at the density functional theory (DFT) level. Additional tests on nonequilibrium molecular conformations from DFT-based MD17 data set and ANI-1ccx data set with coupled cluster accuracy as well as the public test sets of singlet fission molecules, biomolecules, long oligomers, and protein with up to 140 atoms show reasonable predictions for thermodynamics and electronic structure properties. The proposed multilevel attention neural network is applicable to high-throughput screening of numerous chemical species in both equilibrium and nonequilibrium molecular spaces to accelerate rational designs of drug-like molecules, material candidates, and chemical reactions.

3.
Artigo em Inglês | MEDLINE | ID: mdl-33621178

RESUMO

We propose a new video vectorization approach for converting videos in the raster format to vector representation with the benefits of resolution independence and compact storage. Through classifying extracted curves on each video frame as salient ones and non-salient ones, we introduce a novel bipartite diffusion curves (BDCs) representation in order to preserve both important image features such as sharp boundaries and regions with smooth color variation. This bipartite representation allows us to propagate non-salient curves across frames such that the propagation in conjunction with geometry optimization and color optimization of salient curves ensures the preservation of fine details within each frame and across different frames, and meanwhile, achieves good spatial-temporal coherence. Thorough experiments on a variety of videos show that our method is capable of converting videos to the vector representation with low reconstruction errors, low computational cost and fine details, demonstrating our superior performance over the state-of-the-arts. Our approach can also produce comparable results to video super-resolution.

4.
Molecules ; 25(22)2020 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-33207790

RESUMO

Titanate-based bonding agents are a class of efficient bonding agents for improving the mechanical properties of composite solid propellants, a kind of special composite material. However, high solid contents often deteriorate the rheological properties of propellant slurry, which limits the application of bonding agents. To solve this problem, a series of long-chain alkyl chelated titanate binders, N-n-octyl-N, N-dihydroxyethyl-lactic acid-titanate (DLT-8), N-n-dodecyl-N, N-dihydroxyethyl-lactic acid-titanate (DLT-12), N-n-hexadecyl-N, N-Dihydroxyethyl-lactic acid-titanate (DLT-16), were designed and synthesized in the present work. The infrared absorption spectral changes of solid propellants caused by binder coating and adhesion degrees of the bonding agents on the oxidant surface were determined by micro-infrared microscopy (MIR) and X-ray photoelectron spectroscopy (XPS), respectively, to characterize the interaction properties of the bonding agents with oxidants, ammonium perchlorate (AP) and hexogen (RDX), in solid propellants. The further application tests suggest that the bonding agents can effectively interact with the oxidants and effectively improve the mechanical and rheological properties of the four-component hydroxyl-terminated polybutadiene (HTPB) composite solid propellants containing AP and RDX. The agent with longer bond chain length can improve the rheological properties of the propellant slurry more significantly, and the propellant of the best mechanical properties was obtained with DLT-12, consistent with the conclusion obtained in the interfacial interaction study. Our work has provided a new method for simultaneously improving the processing performance and rheological properties of propellants and offered an important guidance for the bonding agent design.

5.
IEEE Trans Vis Comput Graph ; 26(4): 1702-1715, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30418912

RESUMO

We propose a new method for modeling the indoor scene from a single color image. With our system, the user only needs to drag a few semantic bounding boxes surrounding the objects of interest. Our system then automatically finds the most similar 3D models from the ShapeNet model repository and aligns them with the corresponding objects of interest. To achieve this, each 3D model is represented as a group of view-dependent representations generated from a set of synthesized views. We iteratively conduct object segmentation and 3D model retrieval, based on the observation that good segmentation of the objects of interest can significantly improve the accuracy of model retrieval and make it robust to cluttered background and occlusions, and in turn, the retrieved 3D models can be used to assist with object segmentation. Segmentation of all objects of interest is achieved simultaneously under a unified multi-labeling framework which fully utilizes the correspondences between the objects of interest and retrieved model images. Besides, we propose a new method to estimate the scene layout of the input image with the segmentation masks, which helps compose the resulting scene and further improves the modeling result remarkably. We verify the effectiveness of our approach through experimenting with a variety of indoor images and comparing against the relevant methods.

6.
IEEE Trans Vis Comput Graph ; 26(3): 1476-1489, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30281460

RESUMO

Data-driven BRDF models using real material measurements have become increasingly prevalent due to the development of novel gonioreflectometers, but efficient use of these models in many graphical applications remains challenging due to the few functionalities the raw data could provide. To ameliorate this issue, we propose to analyze BRDFs using directional statistics for better handling and exploring measured materials, especially isotropic materials, with efficient computation and compact storage. We conduct a thorough statistical analysis on both analytical BRDF models and measured materials from the MERL database. We show that different aspects of visual appearance can be characterized by different spherical moments, from which several descriptive measures can be derived to further facilitate their usage. We demonstrate how these measures are best leveraged in some graphical applications including gamut mapping using a new BRDF similarity measure, BRDF or SVBRDF reconstruction based on material clustering, and importance sampling for measured materials based on fast extracted GGX distributions. We finally show the potential of our approach in the categorization of surface reflectance types which is common for traditional photon mapping.

7.
IEEE Trans Vis Comput Graph ; 25(8): 2636-2649, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-29994616

RESUMO

This paper studies the problem of how to assess the quality of photographing viewpoints and how to choose good viewpoints for taking photographs of architectures. We achieve this by learning from photographs of world famous landmarks that are available on the Internet and their viewpoint quality ranked by online user annotation. Unlike previous efforts devoted to photo quality assessment which mainly rely on 2D image features, we show in this paper combining 2D image features extracted from images with 3D geometric features computed on the 3D models can result in more reliable evaluation of viewpoint quality. Specifically, we collect a set of photographs for each of 15 world famous architectures as well as their 3D models from the Internet. Viewpoint recovery for images is carried out through an image-model registration process, after which a newly proposed viewpoint clustering strategy is exploited to validate users' viewpoint preferences when photographing landmarks. Finally, we extract a number of 2D and 3D features for each image based on multiple visual and geometric cues and perform viewpoint recommendation by learning from both 2D and 3D features using a specifically designed SVM-2K multi-view learner, achieving superior performance over using solely 2D or 3D features. We show the effectiveness of the proposed approach through extensive experiments. The experiments also demonstrate that our system can be used to recommend viewpoints for rendering textured 3D models of buildings for the use of architectural design, in addition to viewpoint evaluation of photographs and recommendation of viewpoints for photographing architectures in practice.

8.
IEEE Trans Vis Comput Graph ; 24(6): 1956-1968, 2018 06.
Artigo em Inglês | MEDLINE | ID: mdl-28504939

RESUMO

A new method is presented for producing photo collages that preserve content correlation of photos. We use deep learning techniques to find correlation among given photos to facilitate their embedding on the canvas, and develop an efficient combinatorial optimization technique to make correlated photos stay close to each other. To make efficient use of canvas space, our method first extracts salient regions of photos and packs only these salient regions. We allow the salient regions to have arbitrary shapes, therefore yielding informative, yet more compact collages than by other similar collage methods based on salient regions. We present extensive experimental results, user study results, and comparisons against the state-of-the-art methods to show the superiority of our method.

9.
IEEE Trans Vis Comput Graph ; 24(9): 2473-2486, 2018 09.
Artigo em Inglês | MEDLINE | ID: mdl-28922123

RESUMO

We present a data-driven approach that colorizes 3D furniture models and indoor scenes by leveraging indoor images on the internet. Our approach is able to colorize the furniture automatically according to an example image. The core is to learn image-guided mesh segmentation to segment the model into different parts according to the image object. Given an indoor scene, the system supports colorization-by-example, and has the ability to recommend the colorization scheme that is consistent with a user-desired color theme. The latter is realized by formulating the problem as a Markov random field model that imposes user input as an additional constraint. Our system is able to imitate the colorization results for those scenes containing the same type of objects, but with spatially varied patterns. We contribute to the community a hierarchically organized image-model database with correspondences between each image and the corresponding model at the part-level. Our experiments and a user study show that our system produces perceptually convincing results comparable to those generated by interior designers.

10.
IEEE Trans Image Process ; 26(4): 1833-1844, 2017 04.
Artigo em Inglês | MEDLINE | ID: mdl-28207395

RESUMO

We present a video vectorization method that generates a video in vector representation from an input video in raster representation. A vector-based video representation offers the benefits of vector graphics, such as compactness and scalability. The vector video we generate is represented by a simplified tetrahedral control mesh over the spatial-temporal video volume, with color attributes defined at the mesh vertices. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. From an input raster video, our method is capable of generating a compact video in vector representation that allows a faithful reconstruction with low reconstruction errors.

11.
IEEE Trans Vis Comput Graph ; 23(9): 2108-2119, 2017 09.
Artigo em Inglês | MEDLINE | ID: mdl-28113400

RESUMO

Realistic Rendering of thin transparent layers bounded by rough surfaces involves substantial expense of computation time to account for multiple internal reflections. Resorting to Monte Carlo rendering for such material is usually impractical since recursive importance sampling is inevitable. To reduce the burden of sampling for simulating subsurface scattering and hence improve rendering performance, we adapt the microfacet model to the material with a single thin layer by introducing the extended normal distribution function (ENDF), a new representation of this model, to express visually perceived roughness due to multiple bounces of reflections and refractions. With such a representation, both surface reflection and subsurface scattering can be treated in the same microfacet framework, and the sampling process can be reduced to only once for each bounce of scattering. We derive analytical expressions of the ENDF for several cases using joint spherical warping. We also show how to choose proper shadowing-masking and Fresnel terms to make the proposed bidirectional scattering distribution function (BSDF) model energy-conserving. Experiments demonstrate that our model can be easily incorporated into a Monte Carlo path tracer with little extra computational and storage overhead, enabling some real-time applications.

12.
Carbohydr Polym ; 152: 327-336, 2016 Nov 05.
Artigo em Inglês | MEDLINE | ID: mdl-27516279

RESUMO

Chitosan and its derivatives can be used to modify magnetic materials to promote the adsorption properties of the magnetic materials and avoid the weakness of chitosan and its derivatives. In the present study, chitosan grafted poly(trimethyl allyl ammonium chloride) (CTS-g-PTMAAC) was prepared by graft copolymerization; then it was coated on the surfaces of the sodium citrate coated Fe3O4 nanoparticles (SC-Fe3O4) to prepare a novel composite CTS-g-PTMAAC/SC-Fe3O4 magnetic nanoparticles, with which possesses abundant surface positive charges. The structure and properties of the CTS-g-PTMAAC/SC-Fe3O4 composite magnetic nanoparticles were characterized by FTIR, TEM, VSM, and zeta potential. The dye adsorption characteristics of the CTS-g-PTMAAC/SC-Fe3O4 nanoparticles were determined using the food yellow 3 aqueous solutions as a model food effluent. Effect of pH of the dye solution on the adsorption of food yellow 3 was determined and compared with N-2-hydroxylpropyl trimethyl ammonium chloride chitosan coated sodium citrate-Fe3O4 (CTS-g-HTCC/SC-Fe3O4) composite magnetic nanoparticles. The adsorption kinetics, adsorption isotherms, adsorption thermodynamics, and desorption and reusability of the magnetic nanoparticles were investigated.


Assuntos
Compostos de Amônio/química , Compostos Azo/farmacocinética , Quitosana/química , Óxido Ferroso-Férrico/química , Corantes de Alimentos/farmacocinética , Nanopartículas de Magnetita/química , Polímeros/síntese química , Adsorção , Compostos de Amônio/farmacocinética , Recuperação e Remediação Ambiental/métodos , Óxido Ferroso-Férrico/farmacocinética , Humanos , Polímeros/química , Polímeros/farmacocinética , Poluentes Químicos da Água/farmacocinética
13.
IEEE Trans Image Process ; 24(12): 5442-54, 2015 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-26415176

RESUMO

Discovering common visual patterns (CVPs) from two images is a challenging task due to the geometric and photometric deformations as well as noises and clutters. The problem is generally boiled down to recovering correspondences of local invariant features, and the conventionally addressed by graph-based quadratic optimization approaches, which often suffer from high computational cost. In this paper, we propose an efficient approach by viewing the problem from a novel perspective. In particular, we consider each CVP as a common object in two images with a group of coherently deformed local regions. A geometric space with matrix Lie group structure is constructed by stacking up transformations estimated from initially appearance-matched local interest region pairs. This is followed by a mean shift clustering stage to group together those close transformations in the space. Joining regions associated with transformations of the same group together within each input image forms two large regions sharing similar geometric configuration, which naturally leads to a CVP. To account for the non-Euclidean nature of the matrix Lie group, mean shift vectors are derived in the corresponding Lie algebra vector space with a newly provided effective distance measure. Extensive experiments on single and multiple common object discovery tasks as well as near-duplicate image retrieval verify the robustness and efficiency of the proposed approach.

14.
Nucleic Acids Res ; 43(4): 2326-41, 2015 Feb 27.
Artigo em Inglês | MEDLINE | ID: mdl-25653157

RESUMO

Steady state cellular microRNA (miRNA) levels represent the balance between miRNA biogenesis and turnover. The kinetics and sequence determinants of mammalian miRNA turnover during and after miRNA maturation are not fully understood. Through a large-scale study on mammalian miRNA turnover, we report the co-existence of multiple cellular miRNA pools with distinct turnover kinetics and biogenesis properties and reveal previously unrecognized sequence features for fast turnover miRNAs. We measured miRNA turnover rates in eight mammalian cell types with a combination of expression profiling and deep sequencing. While most miRNAs are stable, a subset of miRNAs, mostly miRNA*s, turnovers quickly, many of which display a two-step turnover kinetics. Moreover, different sequence isoforms of the same miRNA can possess vastly different turnover rates. Fast turnover miRNA isoforms are enriched for 5' nucleotide bias against Argonaute-(AGO)-loading, but also additional 3' and central sequence features. Modeling based on two fast turnover miRNA*s miR-222-5p and miR-125b-1-3p, we unexpectedly found that while both miRNA*s are associated with AGO, they strongly differ in HSP90 association and sensitivity to HSP90 inhibition. Our data characterize the landscape of genome-wide miRNA turnover in cultured mammalian cells and reveal differential HSP90 requirements for different miRNA*s. Our findings also implicate rules for designing stable small RNAs, such as siRNAs.


Assuntos
MicroRNAs/metabolismo , Estabilidade de RNA , Animais , Proteínas Argonauta/metabolismo , Linhagem Celular , Células Cultivadas , Proteínas de Choque Térmico HSP90/metabolismo , Humanos , Cinética , Camundongos , MicroRNAs/química , Inibidores da Síntese de Ácido Nucleico/farmacologia , Isoformas de RNA/metabolismo , Análise de Sequência de RNA , Transcrição Genética/efeitos dos fármacos
15.
Methods Mol Biol ; 1176: 33-44, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25030917

RESUMO

As small noncoding RNAs, microRNAs (miRNAs) regulate diverse biological functions, including physiological and pathological processes. The expression and deregulation of miRNA levels contain rich information with diagnostic and prognostic relevance and can reflect pharmacological responses. The increasing interest in miRNA-related research demands global miRNA expression profiling on large numbers of samples. We describe here a robust protocol that supports high-throughput sample labeling and detection on hundreds of samples simultaneously. This method employs 96-well-based miRNA capturing from total RNA samples and on-site biochemical reactions, coupled with bead-based detection in 96-well format for hundreds of miRNAs per sample. With low-cost, high-throughput, high detection specificity, and flexibility to profile both small and large numbers of samples, this protocol can be adapted in a wide range of laboratory settings.


Assuntos
Perfilação da Expressão Gênica/métodos , MicroRNAs/genética , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Pequeno RNA não Traduzido/genética
16.
IEEE Trans Vis Comput Graph ; 20(2): 182-95, 2014 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-24356362

RESUMO

In this paper, we present a novel approach for automatically creating the photo collage that assembles the interest regions of a given group of images naturally. Previous methods on photo collage are generally built upon a well-defined optimization framework, which computes all the geometric parameters and layer indices for input photos on the given canvas by optimizing a unified objective function. The complex nonlinear form of optimization function limits their scalability and efficiency. From the geometric point of view, we recast the generation of collage as a region partition problem such that each image is displayed in its corresponding region partitioned from the canvas. The core of this is an efficient power-diagram-based circle packing algorithm that arranges a series of circles assigned to input photos compactly in the given canvas. To favor important photos, the circles are associated with image importances determined by an image ranking process. A heuristic search process is developed to ensure that salient information of each photo is displayed in the polygonal area resulting from circle packing. With our new formulation, each factor influencing the state of a photo is optimized in an independent stage, and computation of the optimal states for neighboring photos are completely decoupled. This improves the scalability of collage results and ensures their diversity. We also devise a saliency-based image fusion scheme to generate seamless compositive collage. Our approach can generate the collages on nonrectangular canvases and supports interactive collage that allows the user to refine collage results according to his/her personal preferences. We conduct extensive experiments and show the superiority of our algorithm by comparing against previous methods.

17.
Cell Rep ; 5(2): 471-81, 2013 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-24120864

RESUMO

The Ten-Eleven-Translocation 2 (TET2) gene, which oxidates 5-methylcytosine in DNA to 5-hydroxylmethylcytosine (5hmC), is a key tumor suppressor frequently mutated in hematopoietic malignancies. However, the molecular regulation of TET2 expression is poorly understood. We show that TET2 is under extensive microRNA (miRNA) regulation, and such TET2 targeting is an important pathogenic mechanism in hematopoietic malignancies. Using a high-throughput 3' UTR activity screen, we identify >30 miRNAs that inhibit TET2 expression and cellular 5hmC. Forced expression of TET2-targeting miRNAs in vivo disrupts normal hematopoiesis, leading to hematopoietic expansion and/or myeloid differentiation bias, whereas coexpression of TET2 corrects these phenotypes. Importantly, several TET2-targeting miRNAs, including miR-125b, miR-29b, miR-29c, miR-101, and miR-7, are preferentially overexpressed in TET2-wild-type acute myeloid leukemia. Our results demonstrate the extensive roles of miRNAs in functionally regulating TET2 and cellular 5hmC and reveal miRNAs with previously unrecognized oncogenic potential. Our work suggests that TET2-targeting miRNAs might be exploited in cancer diagnosis.


Assuntos
Proteínas de Ligação a DNA/metabolismo , MicroRNAs/metabolismo , Proteínas Proto-Oncogênicas/metabolismo , Regiões 3' não Traduzidas , 5-Metilcitosina/análogos & derivados , Animais , Citosina/análogos & derivados , Citosina/metabolismo , Proteínas de Ligação a DNA/genética , Regulação para Baixo , Neoplasias Hematológicas/genética , Neoplasias Hematológicas/metabolismo , Neoplasias Hematológicas/patologia , Hematopoese , Humanos , Camundongos , Fenótipo , Proteínas Proto-Oncogênicas/genética
18.
Cell Rep ; 2(4): 1048-60, 2012 Oct 25.
Artigo em Inglês | MEDLINE | ID: mdl-23084747

RESUMO

Hematopoietic stem and progenitor cells are often undesired targets of chemotherapies, leading to hematopoietic suppression requiring careful clinical management. Whether microRNAs control hematopoietic injury response is largely unknown. We report an in vivo gain-of-function screen and the identification of miR-150 as an inhibitor of hematopoietic recovery upon 5-fluorouracil-induced injury. Utilizing a bone marrow transplant model with a barcoded microRNA library, we screened for barcode abundance in peripheral blood of recipient mice before and after 5-fluorouracil treatment. Overexpression of screen-candidate miR-150 resulted in significantly slowed recovery rates across major blood lineages, with associated impairment of bone marrow clonogenic potential. Conversely, platelets and myeloid cells from miR-150 null marrow recovered faster after 5-fluorouracil treatment. Heterozygous knockout of c-myb, a conserved target of miR-150, partially phenocopied miR-150-forced expression. Our data highlight the role of microRNAs in controlling hematopoietic injury response and demonstrate the power of in vivo functional screens for studying microRNAs in normal tissue physiology.


Assuntos
Células da Medula Óssea/citologia , MicroRNAs/metabolismo , Animais , Células Sanguíneas/metabolismo , Células da Medula Óssea/efeitos dos fármacos , Células da Medula Óssea/metabolismo , Transplante de Medula Óssea , Linhagem da Célula , Células Cultivadas , Fluoruracila/toxicidade , Perfilação da Expressão Gênica , Biblioteca Gênica , Hematopoese , Heterozigoto , Camundongos , MicroRNAs/genética , Proteínas Proto-Oncogênicas c-myb/antagonistas & inibidores , Proteínas Proto-Oncogênicas c-myb/genética , Proteínas Proto-Oncogênicas c-myb/metabolismo , Radiação Ionizante
19.
Blood ; 120(11): 2317-29, 2012 Sep 13.
Artigo em Inglês | MEDLINE | ID: mdl-22806889

RESUMO

Serum response factor and its transcriptional cofactor MKL1 are critical for megakaryocyte maturation and platelet formation. We show that MKL2, a homologue of MKL1, is expressed in megakaryocytes and plays a role in megakaryocyte maturation. Using a megakaryocyte-specific Mkl2 knockout (KO) mouse on the conventional Mkl1 KO background to produce double KO (DKO) megakaryocytes and platelets, a critical role for MKL2 is revealed. The decrease in megakaryocyte ploidy and platelet counts of DKO mice is more severe than in Mkl1 KO mice. Platelet dysfunction in DKO mice is revealed by prolonged bleeding times and ineffective platelet activation in vitro in response to adenosine 5'-diphosphate. Electron microscopy and immunofluorescence of DKO megakaryocytes and platelets indicate abnormal cytoskeletal and membrane organization with decreased granule complexity. Surprisingly, the DKO mice have a more extreme thrombocytopenia than mice lacking serum response factor (SRF) expression in the megakaryocyte compartment. Comparison of gene expression reveals approximately 4400 genes whose expression is differentially affected in DKO compared with megakaryocytes deficient in SRF, strongly suggesting that MKL1 and MKL2 have both SRF-dependent and SRF-independent activity in megakaryocytopoiesis.


Assuntos
Plaquetas/citologia , Plaquetas/metabolismo , Hematopoese , Megacariócitos/citologia , Megacariócitos/metabolismo , Transativadores/metabolismo , Fatores de Transcrição/metabolismo , Difosfato de Adenosina/metabolismo , Animais , Tempo de Sangramento , Plaquetas/ultraestrutura , Células da Medula Óssea/citologia , Células da Medula Óssea/metabolismo , Células Cultivadas , Cruzamentos Genéticos , Citoplasma/metabolismo , Citoplasma/ultraestrutura , Citoesqueleto/metabolismo , Citoesqueleto/ultraestrutura , Perfilação da Expressão Gênica , Megacariócitos/ultraestrutura , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Análise de Sequência com Séries de Oligonucleotídeos , Ativação Plaquetária , Trombocitopenia/etiologia , Transativadores/genética , Fatores de Transcrição/genética
20.
Med Chem ; 8(2): 163-73, 2012 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-22385175

RESUMO

We have previously found that the dithiocarbamate derivatives of quinazolin-4(3H)-one could act as cytotoxic agents against a panel of human tumor cell lines. To investigate the contribution of dithiocarbamate moiety to the cytotoxic activity, three series of novel quinazolin-4(3H)-one derivatives bearing thiocarbamate, thiourea or Nmethyldithiocarbamate side chains were synthesized and tested for their cytotoxic activity against human cancer cell lines A549, MCF-7, HeLa, HT29 and HCT-116 by MTT assay. The results showed that transformation of the dithiocarbamate moiety in lead compound I to thiocarbamate or thiourea led to a decrease or loss of cytotoxic activity. Some N-alkylated analogs of lead compound II preferentially inhibited the proliferation of A549 cells, although their potencies were not improved in comparison with the unalkylated counterparts. The structure-activity relationship obtained in this research will be beneficial for further synthesis and discovery of effective cytotoxic agents.


Assuntos
Antineoplásicos/toxicidade , Quinazolinonas/toxicidade , Tiocarbamatos/química , Tioureia/química , Antineoplásicos/síntese química , Antineoplásicos/química , Antineoplásicos/farmacologia , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Relação Dose-Resposta a Droga , Ensaios de Seleção de Medicamentos Antitumorais , Células HT29 , Células HeLa , Humanos , Estrutura Molecular , Quinazolinonas/síntese química , Quinazolinonas/química , Quinazolinonas/farmacologia , Relação Estrutura-Atividade , Tiocarbamatos/farmacologia , Tioureia/farmacologia
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