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Bayesian computational markers of relapse in methamphetamine dependence

Katia M. Harlé, Angela J. Yu, Martin P. Paulus
2019 NeuroImage: Clinical  
in a standard inhibitory paradigm (stopsignal task, SST), such that dynamic fluctuations in their reaction time and performance are consistent with a Bayesian sequential adjustment of their beliefs (Yu  ...  To more specifically isolate neural activity related to belief updating processes vs uncertainty tracking (Harlé et al., 2014; Yu and Cohen, 2009 ), a second GLM was created with two types of trial-wise  ... 
doi:10.1016/j.nicl.2019.101794 pmid:30928810 pmcid:PMC6444286 fatcat:2fy4dzgcgzf2vdcxt4tfwssope

Estimating RNA structure chemical probing reactivities from reverse transcriptase stops and mutations [article]

Angela M Yu, Molly E. Evans, Julius B. Lucks
2018 bioRxiv   pre-print
Since log(L (h)) = m log(h) + n log(h − 1), ∂ log(L (h)) ∂ h = m h − n 1−h = 0, which has the solutionĥ = m m+n .  ...  Given h, the likelihood of us observing m heads and n tails in a series of m + n flips is: L (h) = h m (1 − h) n . Suppose we do not know h, but we have observed m and n.  ... 
doi:10.1101/292532 fatcat:xvrwks52wvbqldp6lsrkjis2k4

Host proteostasis modulates influenza evolution

Angela M Phillips, Luna O Gonzalez, Emmanuel E Nekongo, Anna I Ponomarenko, Sean M McHugh, Vincent L Butty, Stuart S Levine, Yu-Shan Lin, Leonid A Mirny, Matthew D Shoulders
2017 eLife  
Transparent reporting form DOI: Zhou B, Donnelly ME, Scholes DT, St George K, Hatta M, Kawaoka Y, Wentworth DE. 2009.  ...  For qPCR of influenza-infected cells, a standard curve was prepared with a pDZ plasmid backbone containing the Influenza PR8 M segment to determine influenza Matrix copy number, which was used as a positive  ... 
doi:10.7554/elife.28652 pmid:28949290 pmcid:PMC5614556 fatcat:uh4niopqore2jgzsbvnhl5umyy

Nanopore Sequencing in Microgravity [article]

Alexa B.R. McIntyre, Lindsay Rizzardi, Angela M Yu, Gail L. Rosen, Noah Alexander, Douglas J. Botkin, Kristen K. John, Sarah L. Castro-Wallace, Aaron S. Burton, Andrew Feinberg, Christopher E. Mason
2015 bioRxiv   pre-print
The ability to perform remote,in situsequencing and diagnostics has been a long-sought goal for point-of-care medicine and portable DNA/RNA measurements. This technological advancement extends to missions beyond Earth as well, both for crew health and astrobiology applications. However, most commercially available sequencing technologies are ill-suited for space flight for a variety of reasons, including excessive volume and mass, and insufficient ruggedization for spaceflight. Portable and
more » ... tweight nanopore-based sequencers, which analyze nucleic acids electrochemically, are inherently much better suited to spaceflight, and could potentially be incorporated into future missions with only minimal modification. As a first step toward evaluating the performance of nanopore sequencers in a microgravity environment, we tested the Oxford Nanopore Technologies MinIONTMin a parabolic flight simulator to examine the effect of reduced gravity on DNA sequencing. The instrument successfully generated three reads, averaging 2,371 bases. However, the median current was shifted across all reads and the error profiles changed compared with operation of the sequencer on the ground, indicating that distinct computational methods may be needed for such data. We evaluated existing methods and propose two new methods; the first new method is based on a wave-fingerprint method similar to that of the Shazam model for matching periodicity information in music, and the second is based on entropy signal mapping. These tools provide a unique opportunity for nucleic acid sequencing in reduced gravity environments. Finally, we discuss the lessons learned from the parabolic flight as they would apply to performing DNA sequencing with the MinIONTMaboard the International Space Station.
doi:10.1101/032342 fatcat:3m4kwghwgfgwbbbiobxlti5lze

Nutritional lipidomics: Molecular metabolism, analytics, and diagnostics

Jennifer T. Smilowitz, Angela M. Zivkovic, Yu-Jui Yvonne Wan, Steve M. Watkins, Malin L. Nording, Bruce D. Hammock, J. Bruce German
2013 Molecular Nutrition & Food Research  
Figure 3 . 3 Reprinted from Metabolomics, Volume 8, Issue 6, 2012, 1102-1113, Angela M. Zivkovic, Jun Yang, Katrin Georgi, Christine Hegedus, Malin L. Nording, Aifric O'Sullivan, J.  ... 
doi:10.1002/mnfr.201200808 pmid:23818328 pmcid:PMC3806310 fatcat:tbkldp73d5g2dmstzmnphgynby

Computationally Reconstructing Cotranscriptional RNA Folding Pathways from Experimental Data Reveals Rearrangement of Non-Native Folding Intermediates [article]

Angela M Yu, Paul M. Gasper, Eric J. Strobel, Kyle E. Watters, Alan A. Chen, Julius B. Lucks
2018 bioRxiv   pre-print
The SHAPE-directed MFE folding pathway prediction was done similarly, but with ρ reactivities and m = 1.1 and b = -0.3 for lengths where SHAPE data was available in specified datasets.  ...  Detailed studies of toehold strand displacement reactions in designed in vitro systems have demonstrated their speed, with reactions proceeding with rates on the order of 10 6 /M/s for a bimolecular strand  ... 
doi:10.1101/379222 fatcat:cynifjgz6fbfhhujrfyob5pyra

New insights into the thermal reduction of graphene oxide: Impact of oxygen clustering

Priyank V. Kumar, Neelkanth M. Bardhan, Guan-Yu Chen, Zeyang Li, Angela M. Belcher, Jeffrey C. Grossman
2016 Carbon  
In case of the former, 100 μL of the stock solution (4 mg/ml) was deposited on silicon substrates forming ~2 μm-thick films (~1 cm in diameter).  ...  The resulting solution was vacuumfiltered to obtain ~10 μm-thick films (~2.5 cm in diameter). Both these thin films were dried overnight at room temperature.  ... 
doi:10.1016/j.carbon.2015.12.087 fatcat:q32fuv5wazf57gxetmc432dpny

Efficient digest of high-throughput sequencing data in a reproducible report

Zhe Zhang, Jeremy Leipzig, Ariella Sasson, Angela M Yu, Juan C Perin, Hongbo M Xie, Mahdi Sarmady, Patrick V Warren, Peter S White
2013 BMC Bioinformatics  
(B) Base-level mismatch information, where M = matched bases; I = inserted bases; D = deleted bases; and S = soft clipping bases due to mismatches.  ... 
doi:10.1186/1471-2105-14-s11-s3 pmid:24564231 pmcid:PMC3846741 fatcat:glvvga2zxjeotkdd4mvso26yde

Enhanced Cell Capture on Functionalized Graphene Oxide Nanosheets through Oxygen Clustering

Neelkanth M. Bardhan, Priyank V. Kumar, Zeyang Li, Hidde L. Ploegh, Jeffrey C. Grossman, Angela M. Belcher, Guan-Yu Chen
2017 ACS Nano  
Scale bar is 50 μm for all images.  ...  Scale bar is 100 μm for the top panel and 5 μm for the bottom panel images. Figure 4 . 4 Figure 4. Figure 5 . 5 Figure 5.  ... 
doi:10.1021/acsnano.6b06979 pmid:28085249 pmcid:PMC5804333 fatcat:sbm7rfvwbrht7pvyzgmlbjc4fy

The landscape epidemiology of echinococcoses

Angela M. Cadavid Restrepo, Yu Rong Yang, Donald P. McManus, Darren J. Gray, Patrick Giraudoux, Tamsin S. Barnes, Gail M. Williams, Ricardo J. Soares Magalhães, Nicholas A. S. Hamm, Archie C. A. Clements
2016 Infectious Diseases of Poverty  
Echinococcoses are parasitic diseases of major public health importance globally. Human infection results in chronic disease with poor prognosis and serious medical, social and economic consequences for vulnerable populations. According to recent estimates, the geographical distribution of Echinococcus spp. infections is expanding and becoming an emerging and re-emerging problem in several regions of the world. Echinococcosis endemicity is geographically heterogeneous and over time it may be
more » ... ected by global environmental change. Therefore, landscape epidemiology offers a unique opportunity to quantify and predict the ecological risk of infection at multiple spatial and temporal scales. Here, we review the most relevant environmental sources of spatial variation in human echinococcosis risk, and describe the potential applications of landscape epidemiological studies to characterise the current patterns of parasite transmission across natural and human-altered landscapes. We advocate future work promoting the use of this approach as a support tool for decision-making that facilitates the design, implementation and monitoring of spatially targeted interventions to reduce the burden of human echinococcoses in disease-endemic areas.
doi:10.1186/s40249-016-0109-x pmid:26895758 pmcid:PMC4759770 fatcat:2poqfh45mvcvbairr2qmwc53iq

Force Spectroscopy of Mammalian Prion Protein Folding and Misfolding

Hao Yu, Xia Liu, Angela M. Brigley, Allison Solanki, Amar N. Gupta, Iveta Sosova, Michael T. Woodside
2011 Biophysical Journal  
This represents the first step of infection and requires multiple simultaneous interactions since the affinity between one single HA-SA pair is very low (10-13 M-1).  ...  1 , Xia Liu 1 , Angela M.  ...  This represents the first step of infection and requires multiple simultaneous interactions since the affinity between one single HA-SA pair is very low (10-13 M-1).  ... 
doi:10.1016/j.bpj.2010.12.332 fatcat:vtgz2565fvbbtmapbaech6devm

DUETT quantitatively identifies known and novel events in nascent RNA structural dynamics from chemical probing data [article]

Albert Y. Xue, Angela M Yu, Julius B. Lucks, Neda Bagheri
2018 bioRxiv   pre-print
These identifications are consistent with recent computational modeling (Yu et al., 2018) and single molecule optical tweezer experiments (Fukuda et al., 2018) that propose the rearrangement of H1  ...  of native base pairs and loops after the formation of H1, but before the rearrangement of H1 into the final native structure (Wong et al., 2007; Watters, Strobel, et al., 2016; Fukuda et al., 2018; Yu  ... 
doi:10.1101/458703 fatcat:tqfu4qiy25asjmny5nf4m7mqke

Cytoplasmic retention of protein tyrosine kinase 6 promotes growth of prostate tumor cells

Patrick M. Brauer, Yu Zheng, Lin Wang, Angela Tyner
2010 Cell Cycle  
The size bar corresponds to 20 μm.  ...  The size bar corresponds to 20 μm.  ... 
doi:10.4161/cc.9.20.13518 pmid:20953141 pmcid:PMC3055202 fatcat:fb74wszyvrcovagukxxngrb7km

Heritability and Inter-Population Differences in Lipid Profiles of Drosophila melanogaster

Cornelia J. F. Scheitz, Yu Guo, Angela M. Early, Lawrence G. Harshman, Andrew G. Clark, Jill C. Bettinger
2013 PLoS ONE  
Loss of 141.0 (NL 141.0); PG, [M+NH4] + in positive ion mode with NL 189.0 for PG; lysoPG, [M -H] 2 in negative mode with Pre 152.9; PI, [M+NH4] + in positive ion mode with NL 277.0; PS, [M+NH4] + in  ...  containing 17:1, [M+NH4] + in positive ion mode with NL 285.2; DAG and TAG containing 16:1, [M+NH4] + in positive ion mode with NL 271.2;and DAG and TAG containing 18:1, [M+NH4] + in positive ion mode  ... 
doi:10.1371/journal.pone.0072726 pmid:24013349 pmcid:PMC3754969 fatcat:rfoedefptfdodop4dvbmasclfq

MFN2 mutations cause compensatory mitochondrial DNA proliferation

Kamil S. Sitarz, Patrick Yu-Wai-Man, Angela Pyle, Joanna D. Stewart, Bernd Rautenstrauss, Pavel Seeman, Mary M. Reilly, Rita Horvath, Patrick F. Chinnery
2012 Brain  
., 2008; Yu-Wai-Man et al., 2010a) .  ...  polymerase chain reaction assay on a MyiQ TM real-time polymerase chain reaction detection system (Biorad), with MTND1 as the mitochondrial template and GAPDH as the nuclear-encoded housekeeping template (Yu-Wai-Man  ... 
doi:10.1093/brain/aws049 pmid:22492563 pmcid:PMC3407419 fatcat:hpbvn7xjajejra2pzc6ebwgaka
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