GCOD - GeneChip Oncology Database

<p>Abstract</p> <p>Background</p> <p>DNA microarrays have become a nearly ubiquitous tool for the study of human disease, and nowhere is this more true than in cancer. With hundreds of studies and thousands of expression profiles representing the majority of human cancers completed and in public databases, the challenge has been effectively accessing and using this wealth of data.</p> <p>Description</p> <p>To address this issue we have collected published human cancer gene expression datasets generated on the Affymetrix GeneChip platform, and carefully annotated those studies with a focus on providing accurate sample annotation. To facilitate comparison between datasets, we implemented a consistent data normalization and transformation protocol and then applied stringent quality control procedures to flag low-quality assays.</p> <p>Conclusion</p> <p>The resulting resource, the GeneChip Oncology Database, is available through a publicly accessible website that provides several query options and analytical tools through an intuitive interface.</p

A cricket Gene Index: a genomic resource for studying neurobiology, speciation, and molecular evolution

<p>Abstract</p> <p>Background</p> <p>As the developmental costs of genomic tools decline, genomic approaches to non-model systems are becoming more feasible. Many of these systems may lack advanced genetic tools but are extremely valuable models in other biological fields. Here we report the development of expressed sequence tags (EST's) in an orthopteroid insect, a model for the study of neurobiology, speciation, and evolution.</p> <p>Results</p> <p>We report the sequencing of 14,502 EST's from clones derived from a nerve cord cDNA library, and the subsequent construction of a Gene Index from these sequences, from the Hawaiian trigonidiine cricket <it>Laupala kohalensis</it>. The Gene Index contains 8607 unique sequences comprised of 2575 tentative consensus (TC) sequences and 6032 singletons. For each of the unique sequences, an attempt was made to assign a provisional annotation and to categorize its function using a Gene Ontology-based classification through a sequence-based comparison to known proteins. In addition, a set of unique 70 base pair oligomers that can be used for DNA microarrays was developed. All Gene Index information is posted at the DFCI Gene Indices web page</p> <p>Conclusion</p> <p>Orthopterans are models used to understand the neurophysiological basis of complex motor patterns such as flight and stridulation. The sequences presented in the cricket Gene Index will provide neurophysiologists with many genetic tools that have been largely absent in this field. The cricket Gene Index is one of only two gene indices to be developed in an evolutionary model system. Species within the genus <it>Laupala </it>have speciated recently, rapidly, and extensively. Therefore, the genes identified in the cricket Gene Index can be used to study the genomics of speciation. Furthermore, this gene index represents a significant EST resources for basal insects. As such, this resource is a valuable comparative tool for the understanding of invertebrate molecular evolution. The sequences presented here will provide much needed genomic resources for three distinct but overlapping fields of inquiry: neurobiology, speciation, and molecular evolution.</p

The Roles of Platelet GPIIb/IIIa and αvβ3 Integrins during HeLa Cells Adhesion, Migration, and Invasion to Monolayer Endothelium under Static and Dynamic Shear Flow

During their passage through the circulatory system, tumor cells undergo extensive interactions with various host cells including endothelial cells and platelets. Mechanisms mediating tumor cell adhesion, migration, and metastasis to vessel wall under flow condition are largely unknown. The aim of this study was to investigate the potential roles of GPIIb/IIIa and αvβ3 integrins underlying the HeLa-endothelium interaction in static and dynamic flow conditions. HeLa cell migration and invasion were studied by using Millicell cell culture insert system. The numbers of transmigrated or invaded HeLa cells significantly increased by thrombin-activated platelets and reduced by eptifibatide, a platelet inhibitor. Meanwhile, RGDWE peptides, a specific inhibitor of αvβ3 integrin, also inhibited HeLa cell transmigration. Interestingly, the presence of endothelial cells had significant effect on HeLa cell migration regardless of static or cocultured flow condition. The adhesion capability of HeLa cells to endothelial monolayer was also significantly affected by GPIIb/IIIa and αvβ3 integrins. The arrested HeLa cells increased nearly 5-fold in the presence of thrombin-activated platelets at shear stress condition (1.84 dyn/cm2 exposure for 1 hour) than the control (static). Our findings showed that GPIIb/IIIa and αvβ3 integrins are important mediators in the pathology of cervical cancer and provide a molecular basis for the future therapy, and the efficient antitumor benefit should target multiple receptors on tumor cells and platelets

Measuring cell deformation by microfluidics

Microfluidics is an increasingly popular method for studying cell deformation, with various applications in fields such as cell biology, biophysics, and medical research. Characterizing cell deformation offers insights into fundamental cell processes, such as migration, division, and signaling. This review summarizes recent advances in microfluidic techniques for measuring cellular deformation, including the different types of microfluidic devices and methods used to induce cell deformation. Recent applications of microfluidics-based approaches for studying cell deformation are highlighted. Compared to traditional methods, microfluidic chips can control the direction and velocity of cell flow by establishing microfluidic channels and microcolumn arrays, enabling the measurement of cell shape changes. Overall, microfluidics-based approaches provide a powerful platform for studying cell deformation. It is expected that future developments will lead to more intelligent and diverse microfluidic chips, further promoting the application of microfluidics-based methods in biomedical research, providing more effective tools for disease diagnosis, drug screening, and treatment

Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors

Decision-based methods have shown to be effective in black-box adversarial attacks, as they can obtain satisfactory performance and only require to access the final model prediction. Gradient estimation is a critical step in black-box adversarial attacks, as it will directly affect the query efficiency. Recent works have attempted to utilize gradient priors to facilitate score-based methods to obtain better results. However, these gradient priors still suffer from the edge gradient discrepancy issue and the successive iteration gradient direction issue, thus are difficult to simply extend to decision-based methods. In this paper, we propose a novel Decision-based Black-box Attack framework with Gradient Priors (DBA-GP), which seamlessly integrates the data-dependent gradient prior and time-dependent prior into the gradient estimation procedure. First, by leveraging the joint bilateral filter to deal with each random perturbation, DBA-GP can guarantee that the generated perturbations in edge locations are hardly smoothed, i.e., alleviating the edge gradient discrepancy, thus remaining the characteristics of the original image as much as possible. Second, by utilizing a new gradient updating strategy to automatically adjust the successive iteration gradient direction, DBA-GP can accelerate the convergence speed, thus improving the query efficiency. Extensive experiments have demonstrated that the proposed method outperforms other strong baselines significantly.Comment: Accepted by IJCAI 202

Boosting Few-Shot Text Classification via Distribution Estimation

Distribution estimation has been demonstrated as one of the most effective approaches in dealing with few-shot image classification, as the low-level patterns and underlying representations can be easily transferred across different tasks in computer vision domain. However, directly applying this approach to few-shot text classification is challenging, since leveraging the statistics of known classes with sufficient samples to calibrate the distributions of novel classes may cause negative effects due to serious category difference in text domain. To alleviate this issue, we propose two simple yet effective strategies to estimate the distributions of the novel classes by utilizing unlabeled query samples, thus avoiding the potential negative transfer issue. Specifically, we first assume a class or sample follows the Gaussian distribution, and use the original support set and the nearest few query samples to estimate the corresponding mean and covariance. Then, we augment the labeled samples by sampling from the estimated distribution, which can provide sufficient supervision for training the classification model. Extensive experiments on eight few-shot text classification datasets show that the proposed method outperforms state-of-the-art baselines significantly.Comment: Accepted to AAAI 202

Sources of variation in baseline gene expression levels from toxicogenomics study control animals across multiple laboratories

<p>Abstract</p> <p>Background</p> <p>The use of gene expression profiling in both clinical and laboratory settings would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies could yield useful information on baseline fluctuations in gene expression, although control animal data has not been available on a scale and in a form best served for data-mining.</p> <p>Results</p> <p>A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques.</p> <p>Conclusion</p> <p>The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selective, or altered by fasting were also identified and functionally categorized. Better characterization of gene expression variability in control animals will aid in the design of toxicogenomics studies and in the interpretation of their results.</p

SYNTHÈSES D'OBSERVATEURS A ENTREES INCONNUES POUR LES SYSTÈMES NON LINEAIRES

The presented work in this thesis concerns the synthesis of high gain observer for the classes of non-linear MIMO systems. The major part of this work refers to solve the problem of observer's synthesis for the non-linear MIMO systems with unknown inputs. In addition, we present a large class of uniformly observable system (without unknown inputs) such that the high gain observer's synthesis is proposed. We considered a canonical observable form in which the unknown inputs intervene not only in the dynamic of states but also in the expression of outputs for the synthesis of unknown input observer. The synthesis was made under certain sufficient conditions which have been formulated so that the proposed observers allow: - to estimate the whole states of the system as well as the unknown inputs when such hypothesis which stipulates that the dynamics of these inputs are uniformly bounded by the unknown function is adopted. - to estimate only the unmeasurable states of the system, in the absence of any hypothesis concerning the unknown inputs. Our contribution in term of synthesis of standard observers consists in proposing a high gain observer for a class of systems which includes, to the best of our knowledge, all the classes of uniformly observable non- linear MIMO systems considered in the literature for observer's synthesis. The different theoretical results are illustrated by several examples in simulation. The last chapter is dedicated in particular to the use of the unknown inputs observer to estimate the substrate's concentrations and the reaction rates in the biochemical reactors. Keywords: high gain observer, unknown inputs observer, non linear observer, non linear MIMO system, uniformly observable system, biochemical reactor.Le travail présenté dans ce mémoire de thèse porte sur la synthèse d'observateurs de type grand gain pour des classes de systèmes non linéaires multi-sorties. La majeure partie de ce travail porte sur la synthèse d'observateurs à entrées inconnues mais nous présentons aussi la synthèse d'un observateur pour une large classe de systèmes uniformément observables (sans entrées inconnues). Pour la synthèse des observateurs à entrées inconnues, nous avons considéré une forme canonique observable qui fait intervenir les entrées inconnues aussi bien au niveau de la dynamique de l'état que dans l"'expression de la sortie. La synthèse s'est effectuée sous certaines conditions suffisantes qui ont été formulées de sorte que les observateurs proposés permettent : - d'estimer conjointement tous les états du système et les entrées inconnues lorsqu'on adopte l'hypothèse qui stipule la bornitude de la dynamique de ces entrées. - d'estimer tous les états non mesurés du système, en l'absence de toute hypothèse portant sur les entrées inconnues Notre contribution en terme de synthèse d'observateurs standards consiste à proposer un observateur de type grand gain pour une classe de systèmes qui inclut, à notre connaissance, toutes les classes de systèmes non linéaires multi-sorties uniformément observables considérées dans la littérature pour la synthèse d'observateurs. Les différents résultats théoriques sont illustrés à travers des exemples en simulation. Le dernier chapitre est en particulier dédié à l'utilisation des observateurs à entrées inconnues pour l'estimation des concentrations en composés et des vitesses de réactions dans les réacteurs biochimiques

Synthèse d'observateurs à entrées inconnues pour les systèmes non linéaires

CAEN-BU Sciences et STAPS (141182103) / SudocSudocFranceF