144 resultados para Signature


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We have developed a model to predict the post-collision brightness increase of sub-catastrophic collisions between asteroids and to evaluate the likelihood of a survey detecting these events. It is based on the cratering scaling laws of Holsapple and Housen (2007) and models the ejecta expansion following an impact as occurring in discrete shells each with their own velocity. We estimate the magnitude change between a series of target/impactor pairs, as- suming it is given by the increase in reflecting surface area within a photometric aperture due to the resulting ejecta. As expected the photometric signal increases with impactor size, but we find also that the photometric signature decreases rapidly as the target aster- oid diameter increases, due to gravitational fallback. We have used the model results to make an estimate of the impactor diameter for the (596) Scheila collision of D = 49 − 65m depending on the impactor taxonomy, which is broadly consistent with previous estimates. We varied both the strength regime (highly porous and sand/cohesive soil) and the tax- onomic type (S-, C- and D-type) to examine the effect on the magnitude change, finding that it is significant at early stages but has only a small effect on the overall lifetime of the photometric signal. Combining the results of this model with the collision frequency estimates of Bottke et al. (2005), we find that low-cadence surveys of ∼one visit per luna- tion will be insensitive to impacts on asteroids with D < 20km if relying on photometric detections.

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Digital signatures are an important primitive for building secure systems and are used in most real-world security protocols. However, almost all popular signature schemes are either based on the factoring assumption (RSA) or the hardness of the discrete logarithm problem (DSA/ECDSA). In the case of classical cryptanalytic advances or progress on the development of quantum computers, the hardness of these closely related problems might be seriously weakened. A potential alternative approach is the construction of signature schemes based on the hardness of certain lattice problems that are assumed to be intractable by quantum computers. Due to significant research advancements in recent years, lattice-based schemes have now become practical and appear to be a very viable alternative to number-theoretic cryptography. In this article, we focus on recent developments and the current state of the art in lattice-based digital signatures and provide a comprehensive survey discussing signature schemes with respect to practicality. Additionally, we discuss future research areas that are essential for the continued development of lattice-based cryptography.

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Understanding the extent, scale and genetic basis of local adaptation is important for conservation and management. Its relevance in salmonids at microgeographic scales, where dispersal (and hence potential gene flow) can be substantial, has however been questioned. Here we compare the fitness of communally-reared offspring of local and foreign Atlantic salmon Salmo salar from adjacent Irish rivers and reciprocal F1 hybrid crosses between them, in the wild ‘home’ environment of the local population. Experimental groups did not differ in wild smolt output but a catastrophic flood event may have limited our ability to detect freshwater performance differences, which were evident in a previous study. Foreign parr exhibited higher, and hybrids intermediate, emigration rates from the natal stream relative to local parr, consistent with genetically-based behavioural differences. Adult return rates were lower for the foreign compared to the local group. Overall lifetime success of foreigners and hybrids relative to locals was estimated at 31% and 40% (mean of both hybrid groups), respectively. The results imply a genetic basis to fitness differences among populations separated by only 50km, driven largely by variation in smolt to adult return rates. Hence even if supplementary stocking programs obtain broodstock from neighbouring rivers, the risk of extrinsic outbreeding depression may be high.

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BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

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BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers.

METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets.

RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a prostate cancer RNA-seq dataset generated as part of the The Cancer Genomics Atlas (TCGA) initiative. Biologically, glycosylation was the single enriched process associated with this 33 gene signature, encompassing four glycosylating enzymes. We went on to evaluate the performance of this signature against three individual markers of prostate cancer, v-ets avian erythroblastosis virus E26 oncogene homolog (ERG) expression, prostate specific antigen (PSA) expression and androgen receptor (AR) expression in an additional independent dataset. Our signature had greater discriminatory power than these markers both for localised cancer and metastatic disease relative to benign tissue, or in the case of metastasis, also localised prostate cancer.

CONCLUSION: In conclusion, robust transcript biomarkers are present within datasets assembled over many years and cohorts and our study provides both examples and a strategy for refining and comparing datasets to obtain additional markers as more data are generated.

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The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.

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Background: Around 10-15% of patients with locally advanced rectal cancer (LARC) undergo a pathologically complete response (TRG4) to neoadjuvant chemoradiotherapy; the rest of patients exhibit a spectrum of tumour regression (TRG1-3). Understanding therapy-related genomic alterations may help us to identify underlying biology or novel targets associated with response that could increase the efficacy of therapy in patients that do not benefit from the current standard of care.
Methods: 48 FFPE rectal cancer biopsies and matched resections were analysed using the WG-DASL HumanHT-12_v4 Beadchip array on the illumina iScan. Bioinformatic analysis was conducted in Partek genomics suite and R studio. Limma and glmnet packages were used to identify genes differentially expressed between tumour regression grades. Validation of microarray results will be carried out using IHC, RNAscope and RT-PCR.
Results: Immune response genes were observed from supervised analysis of the biopsies which may have predictive value. Differential gene expression from the resections as well as pre and post therapy analysis revealed induction of genes in a tumour regression dependent manner. Pathway mapping and Gene Ontology analysis of these genes suggested antigen processing and natural killer mediated cytotoxicity respectively. The natural killer-like gene signature was switched off in non-responders and on in the responders. IHC has confirmed the presence of Natural killer cells through CD56+ staining.
Conclusion: Identification of NK cell genes and CD56+ cells in patients responding to neoadjuvant chemoradiotherapy warrants further investigation into their association with tumour regression grade in LARC. NK cells are known to lyse malignant cells and determining whether their presence is a cause or consequence of response is crucial. Interrogation of the cytokines upregulated in our NK-like signature will help guide future in vitro models.

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We have carried out a 129 close-coupling level Dirac-Coulomb R-matrix calculation for the electron-impact excitation of Ni-like Xe. We have utilized this data to generate the spectral signature of Xe26+ in terms of feature photon-emissivity coefficients (F-PεCs). We have compared these F-PεCs with those generated using semi-relativistic plane-wave Born excitation data, which forms the heavy species baseline for the Atomic Data and Analysis Structure (ADAS), We find that the Born-based F-PεCs give a reasonable qualitative description of the spectral signature but that, quantitatively, the R-matrix-based F-PεCs differ by up to a factor of 2. The spectral signature of heavy species is key to diagnosing hot plasmas such as will be found in the International Thermonuclear Experimental Reactor.

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Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user’s perspective.

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Increasing levels of tissue hypoxia have been reported as a natural feature of the aging prostate gland and may be a risk factor for the development of prostate cancer. In this study, we have used PwR-1E benign prostate epithelial cells and an equivalently aged hypoxia-adapted PwR-1E sub-line to identify phenotypic and epigenetic consequences of chronic hypoxia in prostate cells. We have identified a significantly altered cellular phenotype in response to chronic hypoxia as characterized by increased receptor-mediated apoptotic resistance, the induction of cellular senescence, increased invasion and the increased secretion of IL-1 beta, IL6, IL8 and TNFalpha cytokines. In association with these phenotypic changes and the absence of HIF-1 alpha protein expression, we have demonstrated significant increases in global levels of DNA methylation and H3K9 histone acetylation in these cells, concomitant with the increased expression of DNA methyltransferase DMNT3b and gene-specific changes in DNA methylation at key imprinting loci. In conclusion, we have demonstrated a genome-wide adjustment of DNA methylation and histone acetylation under chronic hypoxic conditions in the prostate. These epigenetic signatures may represent an additional mechanism to promote and maintain a hypoxic-adapted cellular phenotype with a potential role in tumour development.

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PURPOSE: Conventional staging methods are inadequate to identify patients with stage II colon cancer (CC) who are at high risk of recurrence after surgery with curative intent. ColDx is a gene expression, microarray-based assay shown to be independently prognostic for recurrence-free interval (RFI) and overall survival in CC. The objective of this study was to further validate ColDx using formalin-fixed, paraffin-embedded specimens collected as part of the Alliance phase III trial, C9581.

PATIENTS AND METHODS: C9581 evaluated edrecolomab versus observation in patients with stage II CC and reported no survival benefit. Under an initial case-cohort sampling design, a randomly selected subcohort (RS) comprised 514 patients from 901 eligible patients with available tissue. Forty-nine additional patients with recurrence events were included in the analysis. Final analysis comprised 393 patients: 360 RS (58 events) and 33 non-RS events. Risk status was determined for each patient by ColDx. The Self-Prentice method was used to test the association between the resulting ColDx risk score and RFI adjusting for standard prognostic variables.

RESULTS: Fifty-five percent of patients (216 of 393) were classified as high risk. After adjustment for prognostic variables that included mismatch repair (MMR) deficiency, ColDx high-risk patients exhibited significantly worse RFI (multivariable hazard ratio, 2.13; 95% CI, 1.3 to 3.5; P < .01). Age and MMR status were marginally significant. RFI at 5 years for patients classified as high risk was 82% (95% CI, 79% to 85%), compared with 91% (95% CI, 89% to 93%) for patients classified as low risk.

CONCLUSION: ColDx is associated with RFI in the C9581 subsample in the presence of other prognostic factors, including MMR deficiency. ColDx could be incorporated with the traditional clinical markers of risk to refine patient prognosis.

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Purpose: Prompted by the extensive biases in the immunoglobulin (IG) gene repertoire of splenic marginal-zone lymphoma (SMZL), supporting antigen selection in SMZL ontogeny, we sought to investigate whether antigen involvement is also relevant post-transformation.

Experimental Design: We conducted a large-scale subcloning study of the IG rearrangements of 40 SMZL cases aimed at assessing intraclonal diversification (ID) due to ongoing somatic hypermutation (SHM).

Results: ID was identified in 17 of 21 (81%) rearrangements using the immunoglobulin heavy variable (IGHV)1-2*04 gene versus 8 of 19 (40%) rearrangements utilizing other IGHV genes (P= 0.001). ID was also evident in most analyzed IG light chain gene rearrangements, albeit was more limited compared with IG heavy chains. Identical sequence changes were shared by subclones from different patients utilizing the IGHV1-2*04 gene, confirming restricted ongoing SHM profiles. Non-IGHV1-2*04 cases displayed both a lower number of ongoing SHMs and a lack of shared mutations (per group of cases utilizing the same IGHV gene).

Conclusions: These findings support ongoing antigen involvement in a sizable portion of SMZL and further argue that IGHV1-2*04 SMZL may represent a distinct molecular subtype of the disease.