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Search Results: 1 - 10 of 298834 matches for " J. Frederic Mushinski "
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Histological staining methods preparatory to laser capture microdissection significantly affect the integrity of the cellular RNA
Hongyang Wang, James D Owens, Joanna H Shih, Ming-Chung Li, Robert F Bonner, J Frederic Mushinski
BMC Genomics , 2006, DOI: 10.1186/1471-2164-7-97
Abstract: The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases.RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts.Microarray hybridization has been used to study the global gene expression from many different kinds of tissues and cell lines [1-4]. When it is desired to apply this technique only to certain cells that exist in a heterogeneous tissue, surrounded by cells of other types such as connective tissue cells, it is essential to minimize the contribution of mRNA from undesirable cells by enriching the percentage of desirable cell types [5]. Laser Capture Microdissection (LCM) is a valuable tool that makes this possible via the visual (microscopic) identification of cells of interest in intact tissues, followed by their excision and subsequent RNA extraction and analysis by microarray hybridization analysis [6-8]. Frozen sections are highly recommended to maximize quantity and quality of RNA recovery [9,10]. However, in frozen sections it is often difficult to recognize histological details after routine staining, such as hematoxylin & eosin (H&E), in part because LCM requires desiccated sections with no cover slip. Specialized staining methods may be helpful for distinguishing cells of interest from surrounding stroma, e.g., Nissl stain (NS), Immunofluorescence (IF), and Immunohistochemistry (IHC) [7,11,12], but these reagents potentially could result in RNA damage. Methyl Green Pyronin (MGP) is a special stain that has been useful in identifying plasma cells, a ma
Heterologous Tissue Culture Expression Signature Predicts Human Breast Cancer Prognosis
Eun Sung Park, Ju-Seog Lee, Hyun Goo Woo, Fenghuang Zhan, Joanna H. Shih, John D. Shaughnessy, J. Frederic Mushinski
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000145
Abstract: Background Cancer patients have highly variable clinical outcomes owing to many factors, among which are genes that determine the likelihood of invasion and metastasis. This predisposition can be reflected in the gene expression pattern of the primary tumor, which may predict outcomes and guide the choice of treatment better than other clinical predictors. Methodology/Principal Findings We developed an mRNA expression-based model that can predict prognosis/outcomes of human breast cancer patients regardless of microarray platform and patient group. Our model was developed using genes differentially expressed in mouse plasma cell tumors growing in vivo versus those growing in vitro. The prediction system was validated using published data from three cohorts of patients for whom microarray and clinical data had been compiled. The model stratified patients into four independent survival groups (BEST, GOOD, BAD, and WORST: log-rank test p = 1.7×10?8). Conclusions Our model significantly improved the survival prediction over other expression-based models and permitted recognition of patients with different prognoses within the estrogen receptor-positive group and within a single pathological tumor class. Basing our predictor on a dataset that originated in a different species and a different cell type may have rendered it less sensitive to proliferation differences and endowed it with wide applicability. Significance Prognosis prediction for patients with breast cancer is currently based on histopathological typing and estrogen receptor positivity. Yet both assays define groups that are heterogeneous in survival. Gene expression profiling allows subdivision of these groups and recognition of patients whose tumors are very unlikely to be lethal and those with much grimmer outlooks, which can augment the predictive power of conventional tumor analysis and aid the clinician in choosing relaxed vs. aggressive therapy.
Gene expression profiling reveals different pathways related to Abl and other genes that cooperate with c-Myc in a model of plasma cell neoplasia
Eun Sung Park, John D Shaughnessy, Shalu Gupta, Hongyang Wang, Ju-Seog Lee, Hyun Goo Woo, Fenghuang Zhan, James D Owens, Michael Potter, Siegfried Janz, J Frederic Mushinski
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-302
Abstract: Unsupervised hierarchical cluster analysis exhibited two main sub-clusters of samples: a B-cell lymphoma cluster and a plasma cell tumor cluster with subclusters reflecting mechanism of induction. This report represents the first step in using global gene expression to investigate molecular signatures related to the role of cooperating oncogenes in a model of Myc-induced carcinogenesis. Within a single subgroup, e.g., ABPCs, plasma cell tumors that contained typical T(12;15) chromosomal translocations did not display gene expression patterns distinct from those with variant T(6;15) translocations, in which the breakpoint was in the Pvt-1 locus, 230 kb 3' of c-Myc, suggesting that c-Myc activation was the initiating factor in both. When integrated with previously published Affymetrix array data from human multiple myelomas, the IL-6-transgenic subset of mouse plasma cell tumors clustered more closely with MM1 subsets of human myelomas, slow-appearing plasma cell tumors clustered together with MM2, while plasma cell tumors accelerated by v-Abl clustered with the more aggressive MM3-MM4 myeloma subsets. Slow-appearing plasma cell tumors expressed Socs1 and Socs2 but v-Abl-accelerated plasma cell tumors expressed 4–5 times as much. Both v-Abl-accelerated and non-v-Abl-associated tumors exhibited phosphorylated STAT 1 and 3, but only v-Abl-accelerated plasma cell tumors lost viability and STAT 1 and 3 phosphorylation when cultured in the presence of the v-Abl kinase inhibitor, STI-571. These data suggest that the Jak/Stat pathway was critical in the transformation acceleration by v-Abl and that v-Abl activity remained essential throughout the life of the tumors, not just in their acceleration. A different pathway appears to predominate in the more slowly arising plasma cell tumors.Gene expression profiling differentiates not only B-cell lymphomas from plasma cell tumors but also distinguishes slow from accelerated plasma cell tumors. These data and those obtained from th
La dimensió europea a la universitat
Frederic J. Company Franquesa
Temps d'Educació , 1991,
Abstract:
Presentació
Frederic J. Company Franquesa
Temps d'Educació , 1991,
Abstract:
LIPSCHITZ SOLUTIONS OF OPTIMAL CONTROL PROBLEMS WITH STATE CONSTRAINTS OF ARBITRARY ORDER
J. Frederic Bonnans
Mathematics and its Applications : Annals of the Academy of Romanian Scientists , 2010,
Abstract: In this paper we generalize to an arbitrary order, under minimalhypotheses, some suffient conditions for Lipschitz continuity of theoptimal control. The proof combines the approach by Hager in 1979for dealing with first-order state constraints, and the high-order alternative formulation of the optimality conditions. It takes into account the restrictive sign conditions taken into account in some recent papers.
Testing the Accuracy of Redshift Space Group Finding Algorithms
James J. Frederic
Physics , 1994, DOI: 10.1086/192142
Abstract: Using simulated redshift surveys generated from a high resolution N-body cosmological structure simulation, we study algorithms used to identify groups of galaxies in redshift space. Two algorithms are investigated; both are friends-of-friends schemes with variable linking lengths in the radial and transverse dimensions. The chief difference between the algorithms is in the redshift linking length. The algorithm proposed by Huchra \& Geller (1982) uses a generous linking length designed to find ``fingers of god'' while that of Nolthenius \& White (1987) uses a smaller linking length to minimize contamination by projection. We find that neither of the algorithms studied is intrinsically superior to the other; rather, the ideal algorithm as well as the ideal algorithm parameters depend on the purpose for which groups are to be studied. The Huchra/Geller algorithm misses few real groups, at the cost of including some spurious groups and members, while the Nolthenius/White algorithm misses high velocity dispersion groups and members but is less likely to include interlopers in its group assignments. In a companion paper we investigate the accuracy of virial mass estimates and clustering properties of groups identified using these algorithms.
Assessing the Accuracy of Masses and Spatial Correlations of Galaxy Groups
James J. Frederic
Physics , 1994, DOI: 10.1086/192143
Abstract: Two algorithms for the identification of galaxy groups from redshift surveys are tested by application to simulated data derived from N-body simulation. The accuracy of the membership assignments by these algorithms is studied in a companion to this paper (Frederic 1994). Here we evaluate the accuracy of group mass estimates and the group-group correlation function. We find a strong bias to low values in the virial mass estimates of groups identified using the algorithm of Nolthenius \& White (1987). The Huchra \& Geller (1982) algorithm gives virial mass estimates which are correct on average. These two algorithms result in group catalogs with similar two-point correlations. We find that groups in a CDM model have excessively large mass to light ratios even when the group richness distribution agrees with observations. We also find that our CDM groups are more strongly correlated than individual halos (galaxies), unlike the groups in the CfA redshift survey extension.
Many-body trial wave functions for atomic systems and ground states of small noble gas clusters
Andrei Mushinski,M. P. Nightingale
Physics , 1994, DOI: 10.1063/1.468076
Abstract: Clusters of sizes ranging from two to five are studied by variational quantum Monte Carlo techniques. The clusters consist of Ar, Ne and hypothetical lighter (``$1 \over 2$-Ne") atoms. A general form of trial function is developed for which the variational bias is considerably smaller than the statistical error of currently available diffusion Monte Carlo estimates. The trial functions are designed by a careful analysis of long- and short-range behavior as a function of inter-atomic distance; at intermediate distances, on the order of the average nearest neighbor distance, the trial functions are constructed to have considerable variational freedom. A systematic study of the relative importance of $n$-body contributions to the quality of the optimized trial wave function is made with $2\le n \le 5$. Algebraic invariants are employed to deal efficiently with the many-body interactions.
Intense or Spatially Heterogeneous Predation Can Select against Prey Dispersal
Frederic Barraquand, David J. Murrell
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0028924
Abstract: Dispersal theory generally predicts kin competition, inbreeding, and temporal variation in habitat quality should select for dispersal, whereas spatial variation in habitat quality should select against dispersal. The effect of predation on the evolution of dispersal is currently not well-known: because predation can be variable in both space and time, it is not clear whether or when predation will promote dispersal within prey. Moreover, the evolution of prey dispersal affects strongly the encounter rate of predator and prey individuals, which greatly determines the ecological dynamics, and in turn changes the selection pressures for prey dispersal, in an eco-evolutionary feedback loop. When taken all together the effect of predation on prey dispersal is rather difficult to predict. We analyze a spatially explicit, individual-based predator-prey model and its mathematical approximation to investigate the evolution of prey dispersal. Competition and predation depend on local, rather than landscape-scale densities, and the spatial pattern of predation corresponds well to that of predators using restricted home ranges (e.g. central-place foragers). Analyses show the balance between the level of competition and predation pressure an individual is expected to experience determines whether prey should disperse or stay close to their parents and siblings, and more predation selects for less prey dispersal. Predators with smaller home ranges also select for less prey dispersal; more prey dispersal is favoured if predators have large home ranges, are very mobile, and/or are evenly distributed across the landscape.
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