111 research outputs found
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Imaging of PARP1/2-Overexpressing Cancers with Novel AZD2281-Derived Probes
Get PDFPoly(ADP-ribose)polymerase-1 and -2 (PARP1/2) are nuclear proteins involved in DNA repair. Tumors with defects in homologous recombination, including BRCA1- and BRCA2-deficient cancers, have been shown to be sensitive to PARP inhibition.
The Weissleder group has synthesized fluorescent and radioactive derivatives of the PARP1/2 inhibitor AZD2281. We hypothesized that fluorescent and radioactive AZD2281-based imaging agents would quantify PARP1/2 expression in vitro and in vivo.
To test this hypothesis, a panel of pancreatic ductal adenocarcinoma and ovarian carcinoma cell lines were characterized by immunocytochemistry for PARP1/2 expression. AZD2281-derived fluorescence signal correlated with anti-PARP antibody fluorescence signal strength in vitro.
Four cell lines representing a range of PARP1/2 expression levels were then xenografted into Nu/Nu mice. Mice bearing four tumor types each were imaged with AZD2281-derived imaging agents, sacrificed, and their tumors excised for stand-alone imaging and Western blot. AZD2281-derived signal correlated with tumor PARP1/2 expression determined by Western blot, indicating that PARP1/2 expression level is a determinant of fluorescent signal strength and SUVs of AZD2281-derived agents in vivo.
These data indicate that AZD2281-derived agents are useful tools for quantifying intracellular PARP1/2 both in vitro and in vivo, which could one day enable prospective identification of tumors likely to respond to PARP inhibitors
Pressures and Preferences Affecting Willingness to Apply Beef Manure on Crops in the Colorado High Plains
Get PDFLittle is known about producers' willingness to use manure. Past studies have focused on substitutability for fertilizers. We surveyed crop producers in a cattle-dense region of the Colorado Plains about whether and why they apply manure, focusing on how pressures (like owning cattle) or preferences (pro and con) affect their adoption. Using logistic regression, findings show that pressure and preference (PS/PF) significantly affect adoption. A producer with high PS/PF was 10 times more likely to use manure than one with low PS/PF. Policy and decision makers can use such findings to inform education and policy aimed at increasing the land application of manure.cattle, economic benefits, economic costs, management, manure application, Crop Production/Industries,
Speech and language therapy students’ experience of peer assisted learning:Undergraduates investigate PAL as a means of enhancing academic and professional development
Get PDFThe implementation of Peer Assisted Learning (PAL) on healthcare courses in Higher Education Institutions has been explored in a number of studies. This paper presents research into the experience of PAL on a BSc Speech & Language Therapy (SLT) programme. The research was conducted by final year undergraduate SLT students to form the basis for their final dissertations. The focus for their research was on the effects of PAL on academic and professional development for both mentees and mentors on the same course. Data were generated from standard PAL evaluations and focus groups. Findings indicate that mentees benefit from PAL in terms of their university experience and learning. Mentors benefited from opportunities to develop and practice skills for their future employment. Engagement with PAL is attributed to its structured yet informal nature and the enthusiasm of the mentors. However, the collaborative nature of PAL takes time to develop, impacting on the behaviours of both mentees and mentors. Overall PAL offers mentees and mentors opportunities which enhance their academic learning and professional development
Accuracy of a pulse-coherent acoustic Doppler profiler in a wave-dominated flow
Get PDFThis paper is not subject to U.S. copyright. The definitive version was published in Journal of Atmospheric and Oceanic Technology 21 (2004): 1448–1461, doi:10.1175/1520-0426(2004)0212.0.CO;2.The accuracy of velocities measured by a pulse-coherent acoustic Doppler profiler (PCADP) in the bottom boundary layer of a wave-dominated inner-shelf environment is evaluated. The downward-looking PCADP measured velocities in eight 10-cm cells at 1 Hz. Velocities measured by the PCADP are compared to those measured by an acoustic Doppler velocimeter for wave orbital velocities up to 95 cm s−1 and currents up to 40 cm s−1. An algorithm for correcting ambiguity errors using the resolution velocities was developed. Instrument bias, measured as the average error in burst mean speed, is −0.4 cm s−1 (standard deviation = 0.8). The accuracy (root-mean-square error) of instantaneous velocities has a mean of 8.6 cm s−1 (standard deviation = 6.5) for eastward velocities (the predominant direction of waves), 6.5 cm s−1 (standard deviation = 4.4) for northward velocities, and 2.4 cm s−1 (standard deviation = 1.6) for vertical velocities. Both burst mean and root-mean-square errors are greater for bursts with ub ≥ 50 cm s−1. Profiles of burst mean speeds from the bottom five cells were fit to logarithmic curves: 92% of bursts with mean speed ≥ 5 cm s−1 have a correlation coefficient R2 > 0.96. In cells close to the transducer, instantaneous velocities are noisy, burst mean velocities are biased low, and bottom orbital velocities are biased high. With adequate blanking distances for both the profile and resolution velocities, the PCADP provides sufficient accuracy to measure velocities in the bottom boundary layer under moderately energetic inner-shelf conditions.This work was funded
by the U.S. Geological Survey as part of the Southwest
Washington Coastal Erosion Stud
Accuracy of a Pulse-Coherent Acoustic Doppler Profiler in a Wave-Dominated Flow
Get PDFThis paper is not subject to U.S. copyright. The definitive version was published in Journal of Atmospheric and Oceanic Technology 21 (2004): 1448–1461, doi:10.1175/1520-0426(2004)0212.0.CO;2.The accuracy of velocities measured by a pulse-coherent acoustic Doppler profiler (PCADP) in the bottom boundary layer of a wave-dominated inner-shelf environment is evaluated. The downward-looking PCADP measured velocities in eight 10-cm cells at 1 Hz. Velocities measured by the PCADP are compared to those measured by an acoustic Doppler velocimeter for wave orbital velocities up to 95 cm s−1 and currents up to 40 cm s−1. An algorithm for correcting ambiguity errors using the resolution velocities was developed. Instrument bias, measured as the average error in burst mean speed, is −0.4 cm s−1 (standard deviation = 0.8). The accuracy (root-mean-square error) of instantaneous velocities has a mean of 8.6 cm s−1 (standard deviation = 6.5) for eastward velocities (the predominant direction of waves), 6.5 cm s−1 (standard deviation = 4.4) for northward velocities, and 2.4 cm s−1 (standard deviation = 1.6) for vertical velocities. Both burst mean and root-mean-square errors are greater for bursts with ub ≥ 50 cm s−1. Profiles of burst mean speeds from the bottom five cells were fit to logarithmic curves: 92% of bursts with mean speed ≥ 5 cm s−1 have a correlation coefficient R2 > 0.96. In cells close to the transducer, instantaneous velocities are noisy, burst mean velocities are biased low, and bottom orbital velocities are biased high. With adequate blanking distances for both the profile and resolution velocities, the PCADP provides sufficient accuracy to measure velocities in the bottom boundary layer under moderately energetic inner-shelf conditions.This work was funded
by the U.S. Geological Survey as part of the Southwest
Washington Coastal Erosion Stud
Error margin analysis for feature gene extraction
Get PDF<p>Abstract</p> <p>Background</p> <p>Feature gene extraction is a fundamental issue in microarray-based biomarker discovery. It is normally treated as an optimization problem of finding the best predictive feature genes that can effectively and stably discriminate distinct types of disease conditions, e.g. tumors and normals. Since gene microarray data normally involves thousands of genes at, tens or hundreds of samples, the gene extraction process may fall into local optimums if the gene set is optimized according to the maximization of classification accuracy of the classifier built from it.</p> <p>Results</p> <p>In this paper, we propose a novel gene extraction method of error margin analysis to optimize the feature genes. The proposed algorithm has been tested upon one synthetic dataset and two real microarray datasets. Meanwhile, it has been compared with five existing gene extraction algorithms on each dataset. On the synthetic dataset, the results show that the feature set extracted by our algorithm is the closest to the actual gene set. For the two real datasets, our algorithm is superior in terms of balancing the size and the validation accuracy of the resultant gene set when comparing to other algorithms.</p> <p>Conclusion</p> <p>Because of its distinct features, error margin analysis method can stably extract the relevant feature genes from microarray data for high-performance classification.</p
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