104 research outputs found
Leveraging colour-based pseudo-labels to supervise saliency detection in hyperspectral image datasets
Saliency detection mimics the natural visual attention mechanism that identifies an imagery region to be salient when it attracts visual attention more than the background. This image analysis task covers many important applications in several fields such as military science, ocean research, resources exploration, disaster and land-use monitoring tasks. Despite hundreds of models have been proposed for saliency detection in colour images, there is still a large room for improving saliency detection performances in hyperspectral imaging analysis. In the present study, an ensemble learning methodology for saliency detection in hyperspectral imagery datasets is presented. It enhances saliency assignments yielded through a robust colour-based technique with new saliency information extracted by taking advantage of the abundance of spectral information on multiple hyperspectral images. The experiments performed with the proposed methodology provide encouraging results, also compared to several competitors
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Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume I—conceptual challenges
The sharing of clinical trial data and biomarker data sets among the scientific community, whether the data originates from pharmaceutical companies or academic institutions, is of critical importance to enable the development of new and improved cancer immunotherapy modalities. Through data sharing, a better understanding of current therapies in terms of their efficacy, safety and biomarker data profiles can be achieved. However, the sharing of these data sets involves a number of stakeholder groups including patients, researchers, private industry, scientific journals and professional societies. Each of these stakeholder groups has differing interests in the use and sharing of clinical trial and biomarker data, and the conflicts caused by these differing interests represent significant obstacles to effective, widespread sharing of data. Thus, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to identify the current barriers to biomarker data sharing in immuno-oncology (IO) and to help in establishing professional standards for the responsible sharing of clinical trial data. The conclusions of the committee are described in two position papers: Volume I-conceptual challenges and Volume II-practical challenges, the first of which is presented in this manuscript. Additionally, the committee suggests actions by key stakeholders in the field (including organizations and professional societies) as the best path forward, encouraging the cultural shift needed to ensure responsible data sharing in the IO research setting
Antigen-specific clonal expansion and cytolytic effector function of CD8+ T lymphocytes depend on the transcription factor Bcl11b
CD8+ T lymphocytes mediate the immune response to viruses, intracellular bacteria, protozoan parasites, and tumors. We provide evidence that the transcription factor Bcl11b/Ctip2 controls hallmark features of CD8+ T cell immunity, specifically antigen (Ag)-dependent clonal expansion and cytolytic activity. The reduced clonal expansion in the absence of Bcl11b was caused by altered proliferation during the expansion phase, with survival remaining unaffected. Two genes with critical roles in TCR signaling were deregulated in Bcl11b-deficient CD8+ T cells, CD8 coreceptor and Plcγ1, both of which may contribute to the impaired responsiveness. Bcl11b was found to bind the E8I, E8IV, and E8V, but not E8II or E8III, enhancers. Thus, Bcl11b is one of the transcription factors implicated in the maintenance of optimal CD8 coreceptor expression in peripheral CD8+ T cells through association with specific enhancers. Short-lived Klrg1hiCD127lo effector CD8+ T cells were formed during the course of infection in the absence of Bcl11b, albeit in smaller numbers, and their Ag-specific cytolytic activity on a per-cell basis was altered, which was associated with reduced granzyme B and perforin
Conserved Molecular Underpinnings and Characterization of a Role for Caveolin-1 in the Tumor Microenvironment of Mature T-Cell Lymphomas
Neoplasms of extra-thymic T-cell origin represent a rare and difficult population characterized by poor clinical outcome, aggressive presentation, and poorly defined molecular characteristics. Much work has been done to gain greater insights into distinguishing features among malignant subtypes, but there also exists a need to identify unifying characteristics to assist in rapid diagnosis and subsequent potential treatment. Herein, we investigated gene expression data of five different mature T-cell lymphoma subtypes (n = 187) and found 21 genes to be up- and down-regulated across all malignancies in comparison to healthy CD4+ and CD8+ T-cell controls (n = 52). From these results, we sought to characterize a role for caveolin-1 (CAV1), a gene with previous description in the progression of both solid and hematological tumors. Caveolin-1 was upregulated, albeit with a heterogeneous nature, across all mature T-cell lymphoma subtypes, a finding confirmed using immunohistochemical staining on an independent sampling of mature T-cell lymphoma biopsies (n = 65 cases). Further, stratifying malignant samples in accordance with high and low CAV1 expression revealed that higher expression of CAV1 in mature T-cell lymphomas is analogous with an enhanced inflammatory and invasive gene expression profile. Taken together, these results demonstrate a role for CAV1 in the tumor microenvironment of mature T-cell malignancies and point toward potential prognostic implications
Genome-wide association of multiple complex traits in outbred mice by ultra low-coverage sequencing
The authors wish to acknowledge excellent technical assistance from A. Kurioka, L. Swadling, C. de Lara, J. Ussher, R. Townsend, S. Lionikaite, A.S. Lionikiene, R. Wolswinkel and I. van der Made. We would like to thank T.M. Keane and A.G. Doran for their help in annotating variants and adding the FVB/NJ strain to the MGP. We thank the High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics and the Wellcome Trust Sanger Institute for the generation of the sequencing data. This work was funded by Wellcome Trust grant 090532/Z/09/Z (J.F.). Primary phenotyping of the mice was supported by the Mary Lyon Centre and Mammalian Genetics Unit (Medical Research Council, UK Hub grant G0900747 91070 and Medical Research Council, UK grant MC U142684172). D.A.B. acknowledges support from NIH R01AR056280. The sleep work was supported by the state of Vaud (Switzerland) and the Swiss National Science Foundation (SNF 14694 and 136201 to P.F.). The ECG work was supported by the Netherlands CardioVascular Research Initiative (Dutch Heart Foundation, Dutch Federation of University Medical Centres, Netherlands Organization for Health Research and Development and the Royal Netherlands Academy of Sciences) PREDICT project, InterUniversity Cardiology Institute of the Netherlands (ICIN; 061.02; C.A.R. and C.R.B.). N.C. is supported by the Agency of Science, Technology and Research (A*STAR) Graduate Academy. R.W.D. is supported by a grant from the Wellcome Trust (097308/Z/11/Z).Peer reviewedPostprin
Perivascular macrophages in health and disease
Macrophages are a heterogeneous group of cells that are capable of carrying out distinct functions in different tissues, as well as in different locations within a given tissue. Some of these tissue macrophages lie on, or close to, the outer (abluminal) surface of blood vessels and perform several crucial activities at this interface between the tissue and the blood. In steady-state tissues, these perivascular macrophages maintain tight junctions between endothelial cells and limit vessel permeability, phagocytose potential pathogens before they enter tissues from the blood and restrict inappropriate inflammation. They also have a multifaceted role in diseases such as cancer, Alzheimer disease, multiple sclerosis and type 1 diabetes. Here, we examine the important functions of perivascular macrophages in various adult tissues and describe how these functions are perturbed in a broad array of pathological conditions
A study on malware detection and classification using the analysis of API calls sequences through shallow learning and recurrent neural networks
Malware detection and classification is a critical issue in cybersecurity. Systems acting through signatures suffer the problem of not being able to detect attacks via zero-day malware. Among the approaches that can detect unknown attacks are the possibilities offered by analyzing the sequence of API calls performed by the executable. Such information can be extracted through static and dynamic analysis methods in a sandbox environment. This work proposes an analysis of different techniques to detect malware and subsequently classify them by identifying the family of belonging. Machine Learning algorithms based on trees are compared with Deep Learning algorithms based on Recurrent Neural Networks. The results obtained lead to choosing an algorithm based on RNNs for malware detection and an algorithm based on trees for malware classification
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