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1. Ad Libitum Feeding in Broiler Breeder Hens Alters the Transcriptome of Granulosa Cells of Pre-Hierarchal Follicles

Author

Laurie Francoeur, Claire S. Stephens, and Patricia A. Johnson

Subjects
broiler breeder, nutrition and reproduction, egg production, follicle development, granulosa cell, RNA sequencing, Veterinary medicine, SF600-1100, Zoology, QL1-991
Abstract

Intense selective breeding of chickens has resulted in suboptimal egg production in broiler breeder hens. This reproductive phenotype is exacerbated by ad libitum feeding, which leads to excessive and disorganized follicular growth. One strategy used to improve broiler breeder hens’ reproductive efficiency is restricted feeding. In this study, we sought to identify transcriptional changes, which translate the level of dietary intake into increased follicle selection. Broiler breeder hens (n = 16 per group) were raised according to commercial guidelines until 28 weeks of age and then randomly assigned to an ad libitum diet (FF) or continued on a restricted diet (RF) for 6 weeks. Following dietary treatment, FF hens (n = 2) with excessive follicle selection and RF hens (n = 3) with normal follicle selection were selected for RNA-sequencing. Transcriptomes of granulosa cells from 6–8-mm follicles were sequenced to identify transcriptional differences in the follicle population from which selection was made for the preovulatory stage. Differential expression analysis identified several genes known to play a role in follicle development (CYP11A1, STAR, INHA, and INHBB) that are upregulated in FF hens. These changes in gene expression suggest earlier granulosa cell differentiation and steroidogenic competency in the granulosa layer from FF hens.

Published
2021
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2. Accelerated MRI reconstructions via variational network and feature domain learning

Author

Ilias I. Giannakopoulos, Matthew J. Muckley, Jesi Kim, Matthew Breen, Patricia M. Johnson, Yvonne W. Lui, and Riccardo Lattanzi

Subjects
Attention, Compressed sensing, Cross-domain learning, Parallel imaging, Variational network, Medicine, Science
Abstract

Abstract We introduce three architecture modifications to enhance the performance of the end-to-end (E2E) variational network (VarNet) for undersampled MRI reconstructions. We first implemented the Feature VarNet, which propagates information throughout the cascades of the network in an N-channel feature-space instead of a 2-channel feature-space. Then, we add an attention layer that utilizes the spatial locations of Cartesian undersampling artifacts to further improve performance. Lastly, we combined the Feature and E2E VarNets into the Feature-Image (FI) VarNet, to facilitate cross-domain learning and boost accuracy. Reconstructions were evaluated on the fastMRI dataset using standard metrics and clinical scoring by three neuroradiologists. Feature and FI VarNets outperformed the E2E VarNet for 4 $$\times$$ × , 5 $$\times$$ × and 8 $$\times$$ × Cartesian undersampling in all studied metrics. FI VarNet secured second place in the public fastMRI leaderboard for 4 $$\times$$ × Cartesian undersampling, outperforming all open-source models in the leaderboard. Radiologists rated FI VarNet brain reconstructions with higher quality and sharpness than the E2E VarNet reconstructions. FI VarNet excelled in preserving anatomical details, including blood vessels, whereas E2E VarNet discarded or blurred them in some cases. The proposed FI VarNet enhances the reconstruction quality of undersampled MRI and could enable clinically acceptable reconstructions at higher acceleration factors than currently possible.

Published
2024
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3. FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging

Author

Radhika Tibrewala, Tarun Dutt, Angela Tong, Luke Ginocchio, Riccardo Lattanzi, Mahesh B. Keerthivasan, Steven H. Baete, Sumit Chopra, Yvonne W. Lui, Daniel K. Sodickson, Hersh Chandarana, and Patricia M. Johnson

Subjects
Science
Abstract

Abstract Magnetic resonance imaging (MRI) has experienced remarkable advancements in the integration of artificial intelligence (AI) for image acquisition and reconstruction. The availability of raw k-space data is crucial for training AI models in such tasks, but public MRI datasets are mostly restricted to DICOM images only. To address this limitation, the fastMRI initiative released brain and knee k-space datasets, which have since seen vigorous use. In May 2023, fastMRI was expanded to include biparametric (T2- and diffusion-weighted) prostate MRI data from a clinical population. Biparametric MRI plays a vital role in the diagnosis and management of prostate cancer. Advances in imaging methods, such as reconstructing under-sampled data from accelerated acquisitions, can improve cost-effectiveness and accessibility of prostate MRI. Raw k-space data, reconstructed images and slice, volume and exam level annotations for likelihood of prostate cancer are provided in this dataset for 47468 slices corresponding to 1560 volumes from 312 patients. This dataset facilitates AI and algorithm development for prostate image reconstruction, with the ultimate goal of enhancing prostate cancer diagnosis.

Published
2024
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4. Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

Author

Melanie K. Hess, Hannah E. Hodgkinson, Andrew S. Hess, Larissa Zetouni, Juliana C. C. Budel, Hannah Henry, Alistair Donaldson, Timothy P. Bilton, Tracey C. van Stijn, Michelle R. Kirk, Ken G. Dodds, Rudiger Brauning, Alan F. McCulloch, Sharon M. Hickey, Patricia L. Johnson, Arjan Jonker, Nickolas Morton, Shaun Hendy, V. Hutton Oddy, Peter H. Janssen, John C. McEwan, and Suzanne J. Rowe

Subjects
Genotyping-by-sequencing, Restriction enzyme reduced representation sequencing, Rumen microbiome, Metagenome, Genetics, Reference based, Biotechnology, TP248.13-248.65, QH426-470
Abstract

Abstract Background Producing animal protein while reducing the animal’s impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. Results Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. Conclusions Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual’s future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Published
2023
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6. Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits

Author

Melanie K. Hess, Larissa Zetouni, Andrew S. Hess, Juliana Budel, Ken G. Dodds, Hannah M. Henry, Rudiger Brauning, Alan F. McCulloch, Sharon M. Hickey, Patricia L. Johnson, Sara Elmes, Janine Wing, Brooke Bryson, Kevin Knowler, Dianne Hyndman, Hayley Baird, Kathryn M. McRae, Arjan Jonker, Peter H. Janssen, John C. McEwan, and Suzanne J. Rowe

Subjects
Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract Background Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. Results Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. Conclusions This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log10 proportions of each tag normalized within cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Published
2023
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7. Trichomonas vaginalis adherence phenotypes and extracellular vesicles impact parasite survival in a novel in vivo model of pathogenesis.

Author

Brenda M Molgora, Sandip Kumar Mukherjee, Sharon Baumel-Alterzon, Fernanda M Santiago, Katherine A Muratore, Anthony E Sisk, Frances Mercer, and Patricia J Johnson

Subjects
Arctic medicine. Tropical medicine, RC955-962, Public aspects of medicine, RA1-1270
Abstract

Trichomonas vaginalis is a human infective parasite responsible for trichomoniasis-the most common, non-viral, sexually transmitted infection worldwide. T. vaginalis resides exclusively in the urogenital tract of both men and women. In women, T. vaginalis has been found colonizing the cervix and vaginal tract while in men it has been identified in the upper and lower urogenital tract and in secreted fluids such as semen, urethral discharge, urine, and prostatic fluid. Despite the over 270 million cases of trichomoniasis annually worldwide, T. vaginalis continues to be a highly neglected organism and thus poorly studied. Here we have developed a male mouse model for studying T. vaginalis pathogenesis in vivo by delivering parasites into the murine urogenital tract (MUT) via transurethral catheterization. Parasite burden was assessed ex-vivo using a nanoluciferase-based gene expression assay which allowed quantification of parasites pre- and post-inoculation. Using this model and read-out approach, we show that T. vaginalis can be found within MUT tissue up to 72 hrs post-inoculation. Furthermore, we also demonstrate that parasites that exhibit increased parasite adherence in vitro also have higher parasite burden in mice in vivo. These data provide evidence that parasite adherence to host cells aids in parasite persistence in vivo and molecular determinants found to correlate with host cell adherence in vitro are applicable to infection in vivo. Finally, we show that co-inoculation of T. vaginalis extracellular vesicles (TvEVs) and parasites results in higher parasite burden in vivo. These findings confirm our previous in vitro-based predictions that TvEVs assist the parasite in colonizing the host. The establishment of this pathogenesis model for T. vaginalis sets the stage for identifying and examining parasite factors that contribute to and influence infection outcomes.

Published
2023
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8. The political economy of the supercars Newcastle 500 event

Author

Patricia C. Johnson, Phoebe Everingham, and Christine Everingham

Subjects
Investigative research, Information asymmetry, Motor racing events, Political economy, Public/private partnerships, Neoliberal governance, Recreation. Leisure, GV1-1860
Abstract

Public/private partnerships staging urban motor-racing events promise a range of dubious ‘benefits’ to the host destination. These high-octane events are notorious for creating controversy over the disruptions they create. This study employs an investigative research method to explore the political economy of the Supercars Newcastle 500 in New South Wales, Australia. Results revealed how strategic misrepresentation and information asymmetry are used as tactics to avoid public scrutiny. The term ‘magic of major events mathematics’ is coined to explain how public expenditure is ‘hidden’ from public view, how costs are transformed into benefits, and how attendance numbers are ghosted. The research examines links between major events and touted leisure and tourism benefits as it questions the ethics of neoliberal governance practices.

Published
2023
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11. Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge.

Author

Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan 0001, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen 0013, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, and Florian Knoll

Published
2021
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13. Genetic parameters for residual feed intake, methane emissions, and body composition in New Zealand maternal sheep

Author

Patricia L. Johnson, Sharon Hickey, Kevin Knowler, Janine Wing, Brooke Bryson, Melanie Hall, Arjan Jonker, Peter H. Janssen, Ken G. Dodds, John C. McEwan, and Suzanne J. Rowe

Subjects
residual feed intake, methane, sheep, heritability, body composition, Genetics, QH426-470
Abstract

There is simultaneous interest in improving the feed efficiency of ruminant livestock and reducing methane (CH4) emissions. The relationship (genetic and phenotypic) between feed efficiency (characterized as residual feed intake: RFI) and greenhouse gases [methane (CH4) and carbon dioxide (CO2)] traits in New Zealand (NZ) maternal sheep has not previously been investigated, nor has their relationship with detailed estimates of body composition. To investigate these relationships in NZ maternal sheep, a feed intake facility was established at AgResearch Invermay, Mosgiel, NZ in 2015, comprising automated feeders that record individual feeding events. Individual measures of feed intake, feeding behavior (length and duration of eating events), and gas emissions (estimated using portable accumulation chambers) were generated on 986 growing maternal ewe lambs sourced from three pedigree recorded flocks registered in the Sheep Improvement Limited database (www.sil.co.nz). Additional data were generated from a subset of 591 animals for body composition (estimated using ultrasound and computed tomography scanning). The heritability estimates for RFI, CH4, and CH4/(CH4+CO2) were 0.42 ± 0.09, 0.32 ± 0.08, and 0.29 ± 0.06, respectively. The heritability estimates for the body composition traits were high for carcass lean and fat traits; for example, the heritability for visceral fat (adjusted for body weight) was 0.93 ± 0.19. The relationship between RFI and CH4 emissions was complex, and although less feed eaten will lead to a lowered absolute amount of CH4 emitted, there was a negative phenotypic and genetic correlation between RFI and CH4/(CH4+CO2) of −0.13 ± 0.03 and −0.41 ± 0.15, respectively. There were also genetic correlations, that were different from zero, between both RFI and CH4 traits with body composition including a negative correlation between the proportion of visceral fat in the body and RFI (−0.52 ± 0.16) and a positive correlation between the proportion of lean in the body and CH4 (0.54 ± 0.12). Together the results provide the first accurate estimates of the genetic correlations between RFI, CH4 emissions, and the body composition (lean and fat) in sheep. These correlations will need to be accounted for in genetic improvement programs.

Published
2022
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15. Sex Modulates the Pathological Aging Effect on Caudate Functional Connectivity in Mild Cognitive Impairment

Author

Zhengshi Yang, Jessica Z. K. Caldwell, Jeffrey L. Cummings, Aaron Ritter, Jefferson W. Kinney, Dietmar Cordes, The Alzheimer's Disease Neuroimaging Initiative (ADNI), Michael Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Enchi Liu, Tom Montine, Anthony Gamst, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Danielle Harvey, John Kornak, Anders Dale, Matthew Bernstein, Joel Felmlee, Nick Fox, Paul Thompson, Norbert Schuff, Gene Alexander, Charles DeCArli, Dan Bandy, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Nigel J. Cairns, Lisa Taylor-Reinwald, J. Q. Trojanowki, Les Shaw, Virginia M.Y. Lee, Magdalena Korecka, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Zaven Khachaturian, Richard Frank, Peter J. Snyder, Susan Molchan, Jeffrey Kaye, Joseph Quinn, Betty Lind, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Bryan M. Spann, James Brewer, Helen Vanderswag, Judith L. Heidebrink, Joanne L. Lord, Kris Johnson, Rachelle S. Doody, Javier Villanueva-Meyer, Munir Chowdhury, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, John C. Morris, Beau Ances, Maria Carroll, Sue Leon, Mark A. Mintun, Stacy Schneider, Daniel Marson, Randall Griffith, David Clark, Hillel Grossman, Effie Mitsis, Aliza Romirowsky, Leyla deToledo-Morrell, Raj C. Shah, Ranjan Duara, Daniel Varon, Peggy Roberts, Marilyn Albert, Chiadi Onyike, Stephanie Kielb, Henry Rusinek, Mony J de Leon, Lidia Glodzik, P. Murali Doraiswamy, Jeffrey R. Petrella, Edward R. Coleman, Steven E. Arnold, Jason H. Karlawish, David Wolk, Charles D. Smith, Greg Jicha, Peter Hardy, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Ruth A. Mulnard, Gaby Thai, Catherine Mc-Adams-Ortiz, Ramon Diaz-Arrastia, Kristen Martin-Cook, Michael DeVous, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Heather S Anderson, Russell H. Swerdlow, Liana Apostolova, Po H. Lu, George Bartzokis, Daniel H.S. Silverman, Neill R Graff-Radford, Francine Parfitt, Heather Johnson, Martin Farlow, Scott Herring, Ann M. Hake, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Howard Feldman, Michele Assaly, Andrew KertesZ, John Rogers, Dick Trost, Charles Bernick, Donna Munic, Diana Kerwin, Marek-Marsel Mesulam, Kristine Lipowski, Chuang-Kuo Wu, Nancy Johnson, Carl Sadowsky, Walter Martinez, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Meghan Frey, Allyson Rosen, Jared Tinklenberg, Marwan Sabbagh, Christine Belden, Sandra Jacobson, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Salome K. Bwayo, Alan Lerner, Leon Hudson, Paula Ogrocki, Evan Fletcher, Owen Carmichael, John Olichney, Charles DeCarli, Smita Kittur, Michael Borrie, T-Y Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Steven G. Potkin, Adrian Preda, Dana Nguyen, Pierre Tariot, Adam Fleisher, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Barry A. Hendin, Douglas W. Scharre, Maria Kataki, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Robert B. Santulli, Eben S. Schwartz, Kaycee M. Sink, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Henry Querfurth, Geoffrey Tremont, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, Jacobo Mintzer, Crystal Flynn Longmire, and Kenneth Spicer

Subjects
aging effect, caudate, mild cognitive impairment, functional connectivity, Alzheimer's Disease, sex difference, Psychiatry, RC435-571
Abstract

PurposeTo assess the pathological aging effect on caudate functional connectivity among mild cognitive impairment (MCI) participants and examine whether and how sex and amyloid contribute to this process.Materials and MethodsTwo hundred and seventy-seven functional magnetic resonance imaging (fMRI) sessions from 163 cognitive normal (CN) older adults and 309 sessions from 139 participants with MCI were included as the main sample in our analysis. Pearson's correlation was used to characterize the functional connectivity (FC) between caudate nuclei and each brain region, then caudate nodal strength was computed to quantify the overall caudate FC strength. Association analysis between caudate nodal strength and age was carried out in MCI and CN separately using linear mixed effect (LME) model with covariates (education, handedness, sex, Apolipoprotein E4, and intra-subject effect). Analysis of covariance was conducted to investigate sex, amyloid status, and their interaction effects on aging with the fMRI data subset having amyloid status available. LME model was applied to women and men separately within MCI group to evaluate aging effects on caudate nodal strength and each region's connectivity with caudate nuclei. We then evaluated the roles of sex and amyloid status in the associations of neuropsychological scores with age or caudate nodal strength. An independent cohort was used to validate the sex-dependent aging effects in MCI.ResultsThe MCI group had significantly stronger age-related increase of caudate nodal strength compared to the CN group. Analyzing women and men separately revealed that the aging effect on caudate nodal strength among MCI participants was significant only for women (left: P = 6.23 × 10−7, right: P = 3.37 × 10−8), but not for men (P > 0.3 for bilateral caudate nuclei). The aging effects on caudate nodal strength were not significantly mediated by brain amyloid burden. Caudate connectivity with ventral prefrontal cortex substantially contributed to the aging effect on caudate nodal strength in women with MCI. Higher caudate nodal strength is significantly related to worse cognitive performance in women but not in men with MCI.ConclusionSex modulates the pathological aging effects on caudate nodal strength in MCI regardless of amyloid status. Caudate nodal strength may be a sensitive biomarker of pathological aging in women with MCI.

Published
2022
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16. Genetic parameter analysis of bareness and tail traits in New Zealand sheep

Author

Patricia L Johnson, David R Scobie, Ken G Dodds, Sarah-Jane H Powdrell, Suzanne J Rowe, and Kathryn M McRae

Subjects
Genetics, Animal Science and Zoology, General Medicine, Food Science
Abstract

Physical traits that improve welfare and disease outcomes for sheep are becoming increasingly important due to both increased climate challenges and societal expectations. Such traits include tail length, the amount of skin (versus wool) on the underside of the tail, and the area of no-wool (hair) on the belly and breech areas (surrounding the anus) of the animal. An industry dataset consisting of records from individual stud breeders and industry progeny tests was available to estimate the genetic parameters associated with these traits and to investigate the potential for within-breed genetic selection. The heritability estimate for tail length was 0.68 ± 0.01 when breed was not fitted, and 0.63 ± 0.01 when breed was fitted. Similar trends were observed for breech and belly bareness which had heritability estimates around 0.50 (± 0.01). The estimates for these bareness traits are both higher than previous reports from animals of the same age. There was, however, between breed variation in the starting point for these traits, with some breeds having significantly longer tails and a wooly breech and belly, and limited variability. Overall, the results of this study show that flocks exhibiting some variation will be able to make rapid genetic progress in selecting for bareness and tail length traits, and therefore have the potential to make progress towards a sheep that is easier to look after and suffers fewer welfare insults. For those breeds that showed limited within-breed variation, outcrossing may be required to introduce genotypes that exhibit shorter tail length and bareness of belly and breech to increase the rate of genetic gain. Whatever approach is taken by the industry, these results support that genetic improvement can be used to breed “ethically improved sheep”.

Published
2023

17. The Influence of Cerebrospinal Fluid Abnormalities and APOE 4 on PHF-Tau Protein: Evidence From Voxel Analysis and Graph Theory

Author

Yuan Li, Zhijun Yao, Yue Yu, Yu Fu, Ying Zou, Bin Hu, for the Alzheimer’s Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Michael Weiner, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, M. Marcel Mesulam, William Potter, Peter Snyder, Tom Montine, Gustavo Jimenez, Michael Donohue, Devon Gessert, Kelly Harless, Jennifer Salazar, Yuliana Cabrera, Sarah Walter, Lindsey Hergesheimer, Danielle Harvey, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCArli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, John C. Morris, Nigel J. Cairns, Erin Franklin, Lisa Taylor-Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Kelley Faber, Sungeun Kim, Kwangsik Nho, Lean Thal, Leon Thal, Neil Buckholtz, Peter J. Snyder, Marilyn Albert, Richard Frank, John Hsiao, Joseph Quinn, Lisa C. Silbert, Betty Lind, Jeffrey A. Kaye, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Jaimie Ziolkowski, Judith L. Heidebrink, Joanne L. Lord, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Javier Villanueva-Meyer, Valory Pavlik, Nathaniel Pacini, Ashley Lamb, Joseph S. Kass, Rachelle S. Doody, Victoria Shibley, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Randy Yeh, Beau Ances, David Winkfield, Maria Carroll, Angela Oliver, Mary L. Creech, Mark A. Mintun, Stacy Schneider, Daniel Marson, David Geldmacher, Marissa Natelson Love, Randall Griffith, David Clark, John Brockington, Hillel Grossman, Effie Mitsis, Raj C. Shah, Melissa Lamar, Patricia Samuels, Ranjan Duara, Maria T. Greig-Custo, Rosemarie Rodriguez, Chiadi Onyike, Daniel D’Agostino, Stephanie Kielb, Martin Sadowski, Mohammed O. Sheikh, Jamika Singleton-Garvin, Anaztasia Ulysse, Mrunalini Gaikwad, P. Murali Doraiswamy, Jeffrey R. Petrella, Olga James, Salvador Borges-Neto, Terence Z. Wong, Edward Coleman, Jason H. Karlawish, David A. Wolk, Sanjeev Vaishnavi, Christopher M. Clark, Steven E. Arnold, Charles D. Smith, Greg Jicha, Peter Hardy, Riham El Khouli, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Kim Martin, Nancy Kowalksi, Melanie Keltz, Bonnie S. Goldstein, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Gaby Thai, Aimee Pierce, Beatriz Yanez, Elizabeth Sosa, Megan Witbracht, Kyle Womack, Dana Mathews, Mary Quiceno, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Russell H. Swerdlow, William M. Brooks, Ellen Woo, Daniel H.S. Silverman, Edmond Teng, Sarah Kremen, Liana Apostolova, Kathleen Tingus, Po H. Lu, George Bartzokis, Neill R Graff-Radford, Francine Parfitt, Kim Poki-Walker, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, Christopher H. van Dyck, Richard E. Carson, Pradeep Varma, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Chris (Chinthaka) Heyn, Ging-Yuek Robin Hsiung, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternack, William Pavlosky, Irina Rachinsky, Dick Drost, Andrew Kertesz, Charles Bernick, Donna Munic, Marek-Marsel Mesulam, Emily Rogalski, Kristine Lipowski, Sandra Weintraub, Borna Bonakdarpour, Diana Kerwin, Chuang-Kuo Wu, Nancy Johnson, Carl Sadowsky, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad A. Marshall, Jerome Yesavage, Joy L. Taylor, Steven Chao, Barton Lane, Allyson Rosen, Jared Tinklenberg, Edward Zamrini, Christine M. Belden, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Ntekim E. Oyonumo, Joanne Allard, Olu Ogunlana, Alan Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Evan Fletcher, Pauline Maillard, John Olichney, Charles DeCarli, Owen Carmichael, Smita Kittur, Michael Borrie, T-Y Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Pierre Tariot, Anna Burke, Joel Hetelle, Kathryn DeMarco, Nadira Trncic, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Rawan Tarawneh, Earl A. Zimmerman, Dzintra Celmins, David Hart, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Kaycee M. Sink, Mia Yang, Akiva Mintz, Rhode Island, Brian R. Ott, Geoffrey Tremont, Lori A. Daiello, Courtney Bodge, Stephen Salloway, Paul Malloy, Stephen Correia, Athena Lee, Howard J. Rosen, Bruce L. Miller, David Perry, Jacobo Mintzer, Kenneth Spicer, David Bachman, Stephen Pasternak, John Rogers, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Delwyn D. Miller, Karen Ekstam Smith, Hristina Koleva, Ki Won Nam, Hyungsub Shim, Susan K. Schultz, Norman Relkin, Gloria Chiang, Michael Lin, Lisa Ravdin, Amanda Smith, Christi Leach, Balebail Ashok Raj, Kristin Fargher, Thomas Neylan, Jordan Grafman, Lindsey Hergesheimen, Jacqueline Hayes, Shannon Finley, Susan Landau, Erin Householder, Karl Friedl, Debra Fleischman, Konstantinos Arfanakis, Daniel Varon, Maria T Greig, Bonnie Goldstein, Kimberly S. Martin, Steven G. Potkin, Adrian Preda, Dana Nguyen, Dino Massoglia, Olga Brawman-Mintzer, Walter Martinez, Howard Rosen, Kelly Behan, Gad Marshall, Marwan N. Sabbagh, Sandra A. Jacobson, Saba Wolday, Sterling C. Johnson, J. Jay Fruehling, Sandra Harding, Elaine R. Peskind, Eric C. Petrie, Gail Li, Jerome A. Yesavage, Ansgar J. Furst, Scott Mackin, Rema Raman, Erin Drake, Mike Donohue, Elizabeth Shaffer, Craig Nelson, David Bickford, Meryl Butters, Michelle Zmuda, Denise Reyes, Kelley M. Faber, Kelly N. Nudelman, Yiu Ho Au, Kelly Scherer, Daniel Catalinotto, Samuel Stark, Elise Ong, and Dariella Fernandez

Subjects
PHF-Tau, graph theory, network properties, APOE 4, CSF-Tau, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Mild cognitive impairment (MCI) is a transitional state between the cognitive changes in normal aging and Alzheimer’s disease (AD), which induces abnormalities in specific brain regions. Previous studies showed that paired helical filaments Tau (PHF-Tau) protein is a potential pathogenic protein which may cause abnormal brain function and structure in MCI and AD patients. However, the understanding of the PHF-Tau protein network in MCI patients is limited. In this study, 225 subjects with PHF-Tau Positron Emission Tomography (PET) images were divided into four groups based on whether they carried Apolipoprotein E ε4 (APOE 4) or abnormal cerebrospinal fluid Total-Tau (CSF T-Tau). They are two important pathogenic factors that might cause cognitive function impairment. The four groups were: individuals harboring CSF T-Tau pathology but no APOE 4 (APOE 4−T+); APOE 4 carriers with normal CSF T-Tau (APOE 4+T−); APOE 4 carriers with abnormal CSF T-Tau (APOE 4+T+); and APOE 4 noncarriers with abnormal CSF T-Tau (APOE 4−T−). We explored the topological organization of PHF-Tau networks in these four groups and calculated five kinds of network properties: clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Our findings showed that compared with APOE 4−T− group, the other three groups showed different alterations in the clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Simultaneously, voxel-level analysis was conducted and the results showed that compared with APOE 4−T− group, the other three groups were found increased PHF-Tau distribution in some brain regions. For APOE 4+T+ group, positive correlation was found between the value of PHF-Tau distribution in altered regions and Functional Assessment Questionnaire (FAQ) score. Our results indicated that the effects of APOE 4 and abnormal CSF T-Tau may induce abnormalities of PHF-Tau protein and APOE 4 has a greater impact on PHF-Tau than abnormal CSF T-Tau. Our results may be particularly helpful in uncovering the pathophysiology underlying the cognitive dysfunction in MCI patients.

Published
2019
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18. New Perspective for Non-invasive Brain Stimulation Site Selection in Mild Cognitive Impairment: Based on Meta- and Functional Connectivity Analyses

Author

Jiao Liu, Binlong Zhang, Georgia Wilson, Jian Kong, the Alzheimer’s Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Michael Weiner, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, M. Marcel Mesulam, William Potter, Peter Snyder, Adam Schwartz, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Archana B. Balasubramanian, Jennifer Mason, Iris Sim, Danielle Harvey, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCArli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, John C. Morris, Nigel J. Cairns, Erin Franklin, Lisa Taylor-Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Kelley Faber, Sungeun Kim, Kwangsik Nho, Lean Thal, Leon Thal, Neil Buckholtz, Peter J. Snyder, Marilyn Albert, Richard Frank, John Hsiao, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne L. Lord, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva-Meyer, Valory Pavlik, Victoria Shibley, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau Ances, Maria Carroll, Mary L. Creech, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, David Geldmacher, Marissa Natelson Love, Randall Griffith, David Clark, John Brockington, Erik Roberson, Hillel Grossman, Effie Mitsis, Raj C. Shah, Leyla deToledo-Morrell, Ranjan Duara, Maria T. Greig-Custo, Warren Barker, Chiadi Onyike, Daniel D'Agostino, Stephanie Kielb, Martin Sadowski, Mohammed O. Sheikh, Ulysse Anaztasia, Gaikwad Mrunalini, P. Murali Doraiswamy, Jeffrey R. Petrella, Salvador Borges-Neto, Terence Z. Wong, Edward Coleman, Steven E. Arnold, Jason H. Karlawish, David A. Wolk, Christopher M. Clark, Charles D. Smith, Greg Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Steven G. Potkin, Adrian Preda, Dana Nguyen, Kyle Womack, Dana Mathews, Mary Quiceno, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Russell H. Swerdlow, William M. Brooks, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel H.S. Silverman, Po H. Lu, George Bartzokis, Neill R Graff-Radford, Francine Parfitt, Kim Poki-Walker, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Pradeep Varma, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternack, Irina Rachisky, Dick Trost, Andrew Kertesz, Charles Bernick, Donna Munic, Marek-Marsel Mesulam, Emily Rogalski, Kristine Lipowski, Sandra Weintraub, Borna Bonakdarpour, Diana Kerwin, Chuang-Kuo Wu, Nancy Johnson, Carl Sadowsky, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Jerome Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Evan Fletcher, Pauline Maillard, John Olichney, Charles DeCarli, Owen Carmichael, Smita Kittur, Michael Borrie, T-Y Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Pierre Tariot, Anna Burke, Ann Marie Milliken, Nadira Trncic, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Brendan Kelley, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Kaycee M. Sink, Gordineer Leslie, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Geoffrey Tremont, Lori A. Daiello, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, David Perry, Jacobo Mintzer, Kenneth Spicer, David Bachman, Stephen Pasternak, Irina Rachinsky, John Rogers, Dick Drost, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Karen Ekstam Smith, Hristina Koleva, Ki Won Nam, Hyungsub Shim, Norman Relkin, Gloria Chiang, Michael Lin, Lisa Ravdin, Amanda Smith, Balebail Ashok Raj, Kristin Fargher, Thomas Neylan, Jordan Grafman, Gessert Devon, Davis Melissa, Rosemary Morrison, Hayes Jacqueline, Finley Shannon, Kantarci Kejal, Ward Chad, Erin Householder, Crawford Karen, Neu Scott, Friedl Karl, Becerra Mauricio, Debra Fleischman, Konstantinos Arfanakis, Daniel Varon, Maria T Greig, Olga James, Bonnie Goldstein, Kimberly S. Martin, Dino Massoglia, Olga Brawman-Mintzer, Walter Martinez, Howard Rosen, Kelly Behan, Sterling C. Johnson, J. Jay Fruehling, Sandra Harding, Elaine R. Peskind, Eric C. Petrie, Gail Li, Jerome A. Yesavage, Ansgar J. Furst, and Steven Chao

Subjects
mild cognitive impairment, non-invasive brain stimulation, stimulation site, meta-analysis, resting state functional connectivity, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

BackgroundNon-invasive brain stimulation (NIBS) has been widely used to treat mild cognitive impairment (MCI). However, there exists no consensus on the best stimulation sites.ObjectiveTo explore potential stimulation locations for NIBS treatment in patients with MCI, combining meta- and resting state functional connectivity (rsFC) analyses.MethodsThe meta-analysis was conducted to identify brain regions associated with MCI. Regions of interest (ROIs) were extracted based on this meta-analysis. The rsFC analysis was applied to 45 MCI patients to determine brain surface regions that are functionally connected with the above ROIs.ResultsWe found that the dorsolateral prefrontal cortex (DLPFC) and inferior frontal gyrus (IFG) were the overlapping brain regions between our results and those of previous studies. In addition, we recommend that the temporoparietal junction (including the angular gyrus), which was found in both the meta- and rsFC analysis, should be considered in NIBS treatment of MCI. Furthermore, the bilateral orbital prefrontal gyrus, inferior temporal gyrus, medial superior frontal gyrus, and right inferior occipital gyrus may be potential brain stimulation sites for NIBS treatment of MCI.ConclusionOur results provide several potential sites for NIBS, such as the DLFPC and IFG, and may shed light on the locations of NIBS sites in the treatment of patients with MCI.

Published
2019
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19. Performing Sparse Regularization and Dimension Reduction Simultaneously in Multimodal Data Fusion

Author

Zhengshi Yang, Xiaowei Zhuang, Christopher Bird, Karthik Sreenivasan, Virendra Mishra, Sarah Banks, Dietmar Cordes, the Alzheimer's Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Michael Weiner, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, M. Marcel Mesulam, William Potter, Peter Snyder, Adam Schwartz, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Archana B. Balasubramanian, Jennifer Mason, Iris Sim, Danielle Harvey, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCArli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, John C. Morris, Nigel J. Cairns, Erin Franklin, Lisa Taylor-Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Kelley Faber, Sungeun Kim, Kwangsik Nho, Lean Thal, Leon Thal, Neil Buckholtz, Peter J. Snyder, Marilyn Albert, Richard Frank, John Hsiao, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne L. Lord, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva-Meyer, Valory Pavlik, Victoria Shibley, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau Ances, Maria Carroll, Mary L. Creech, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, David Geldmacher, Marissa Natelson Love, Randall Griffith, David Clark, John Brockington, Erik Roberson, Hillel Grossman, Effie Mitsis, Raj C. Shah, Leyla deToledo-Morrell, Ranjan Duara, Maria T. Greig-Custo, Warren Barker, Chiadi Onyike, Daniel D'Agostino, Stephanie Kielb, Martin Sadowski, Mohammed O. Sheikh, Ulysse Anaztasia, Gaikwad Mrunalini, P. Murali Doraiswamy, Jeffrey R. Petrella, Salvador Borges-Neto, Terence Z. Wong, Edward Coleman, Steven E. Arnold, Jason H. Karlawish, David A. Wolk, Christopher M. Clark, Charles D. Smith, Greg Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Steven G. Potkin, Adrian Preda, Dana Nguyen, Kyle Womack, Dana Mathews, Mary Quiceno, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Russell H. Swerdlow, William M. Brooks, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel H.S. Silverman, Po H. Lu, George Bartzokis, Neill R Graff-Radford, Francine Parfitt, Kim Poki-Walker, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Pradeep Varma, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternack, Irina Rachisky, Dick Trost, Andrew Kertesz, Charles Bernick, Donna Munic, Marek-Marsel Mesulam, Emily Rogalski, Kristine Lipowski, Sandra Weintraub, Borna Bonakdarpour, Diana Kerwin, Chuang-Kuo Wu, Nancy Johnson, Carl Sadowsky, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Jerome Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Evan Fletcher, Pauline Maillard, John Olichney, Charles DeCarli, Owen Carmichael, Smita Kittur, Michael Borrie, T-Y Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Pierre Tariot, Anna Burke, Ann Marie Milliken, Nadira Trncic, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Brendan Kelley, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Kaycee M. Sink, Gordineer Leslie, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Geoffrey Tremont, Lori A. Daiello, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, David Perry, Jacobo Mintzer, Kenneth Spicer, David Bachman, Stephen Pasternak, Irina Rachinsky, John Rogers, Dick Drost, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Karen Ekstam Smith, Hristina Koleva, Ki Won Nam, Hyungsub Shim, Norman Relkin, Gloria Chiang, Michael Lin, Lisa Ravdin, Amanda Smith, Balebail Ashok Raj, Kristin Fargher, Thomas Neylan, Jordan Grafman, Gessert Devon, Davis Melissa, Rosemary Morrison, Hayes Jacqueline, Finley Shannon, Kantarci Kejal, Ward Chad, Erin Householder, Crawford Karen, Neu Scott, Friedl Karl, Becerra Mauricio, Debra Fleischman, Konstantinos Arfanakis, Daniel Varon, Maria T Greig, Olga James, Bonnie Goldstein, Kimberly S. Martin, Dino Massoglia, Olga Brawman-Mintzer, Walter Martinez, Howard Rosen, Kelly Behan, Sterling C. Johnson, J. Jay Fruehling, Sandra Harding, Elaine R. Peskind, Eric C. Petrie, Gail Li, Jerome A. Yesavage, Ansgar J. Furst, Steven Chao, Scott Mackin, Rema Raman, Erin Drake, Mike Donohue, Gustavo Jimenez, Kelly Harless, Jennifer Salazar, Yuliana Cabrera, Lindsey Hergesheimer, Elizabeth Shaffer, Craig Nelson, David Bickford, Meryl Butters, Michelle Zmuda, Denise Reyes, Kelley M. Faber, Kelly N. Nudelman, Yiu Ho Au, Kelly Scherer, Daniel Catalinotto, Samuel Stark, Elise Ong, and Dariella Fernandez

Subjects
sparse principal component analysis, PCA, canonical correlation analysis, CCA, data fusion, mild cognitive impairment, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Collecting multiple modalities of neuroimaging data on the same subject is increasingly becoming the norm in clinical practice and research. Fusing multiple modalities to find related patterns is a challenge in neuroimaging analysis. Canonical correlation analysis (CCA) is commonly used as a symmetric data fusion technique to find related patterns among multiple modalities. In CCA-based data fusion, principal component analysis (PCA) is frequently applied as a preprocessing step to reduce data dimension followed by CCA on dimension-reduced data. PCA, however, does not differentiate between informative voxels from non-informative voxels in the dimension reduction step. Sparse PCA (sPCA) extends traditional PCA by adding sparse regularization that assigns zero weights to non-informative voxels. In this study, sPCA is incorporated into CCA-based fusion analysis and applied on neuroimaging data. A cross-validation method is developed and validated to optimize the parameters in sPCA. Different simulations are carried out to evaluate the improvement by introducing sparsity constraint to PCA. Four fusion methods including sPCA+CCA, PCA+CCA, parallel ICA and sparse CCA were applied on structural and functional magnetic resonance imaging data of mild cognitive impairment subjects and normal controls. Our results indicate that sPCA significantly can reduce the impact of non-informative voxels and lead to improved statistical power in uncovering disease-related patterns by a fusion analysis.

Published
2019
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20. Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

Author

Qian Zhao, Min Liu, Lingxia Ha, Yun Zhou, Alzheimer's Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Michael Weiner, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, M. Marcel Mesulam, William Potter, Peter Snyder, Adam Schwartz, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Archana B. Balasubramanian, Jennifer Mason, Iris Sim, Danielle Harvey, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCArli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, John C. Morris, Nigel J. Cairns, Erin Franklin, Lisa Taylor-Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Kelley Faber, Sungeun Kim, Kwangsik Nho, Lean Thal, Leon Thal, Neil Buckholtz, Peter J. Snyder, Marilyn Albert, Richard Frank, John Hsiao, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne L. Lord, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva-Meyer, Valory Pavlik, Victoria Shibley, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau Ances, Maria Carroll, Mary L. Creech, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, David Geldmacher, Marissa Natelson Love, Randall Griffith, David Clark, John Brockington, Erik Roberson, Hillel Grossman, Effie Mitsis, Raj C. Shah, Leyla deToledo-Morrell, Ranjan Duara, Maria T. Greig-Custo, Warren Barker, Chiadi Onyike, Daniel D'Agostino, Stephanie Kielb, Martin Sadowski, Mohammed O. Sheikh, Ulysse Anaztasia, Gaikwad Mrunalini, P. Murali Doraiswamy, Jeffrey R. Petrella, Salvador Borges-Neto, Terence Z. Wong, Edward Coleman, Steven E. Arnold, Jason H. Karlawish, David A. Wolk, Christopher M. Clark, Charles D. Smith, Greg Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Steven G. Potkin, Adrian Preda, Dana Nguyen, Kyle Womack, Dana Mathews, Mary Quiceno, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Russell H. Swerdlow, William M. Brooks, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel H.S. Silverman, Po H. Lu, George Bartzokis, Neill R Graff-Radford, Francine Parfitt, Kim Poki-Walker, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Pradeep Varma, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternack, Irina Rachisky, Dick Trost, Andrew Kertesz, Charles Bernick, Donna Munic, Marek-Marsel Mesulam, Emily Rogalski, Kristine Lipowski, Sandra Weintraub, Borna Bonakdarpour, Diana Kerwin, Chuang-Kuo Wu, Nancy Johnson, Carl Sadowsky, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Jerome Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Evan Fletcher, Pauline Maillard, John Olichney, Charles DeCarli, Owen Carmichael, Smita Kittur, Michael Borrie, T-Y Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Pierre Tariot, Anna Burke, Ann Marie Milliken, Nadira Trncic, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Brendan Kelley, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Kaycee M. Sink, Gordineer Leslie, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Geoffrey Tremont, Lori A. Daiello, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, David Perry, Jacobo Mintzer, Kenneth Spicer, David Bachman, Stephen Pasternak, Irina Rachinsky, John Rogers, Dick Drost, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Karen Ekstam Smith, Hristina Koleva, Ki Won Nam, Hyungsub Shim, Norman Relkin, Gloria Chiang, Michael Lin, Lisa Ravdin, Amanda Smith, Balebail Ashok Raj, Kristin Fargher, Thomas Neylan, Jordan Grafman, Gessert Devon, Davis Melissa, Rosemary Morrison, Hayes Jacqueline, Finley Shannon, Kantarci Kejal, Ward Chad, Erin Householder, Crawford Karen, Neu Scott, Friedl Karl, Becerra Mauricio, Debra Fleischman, Konstantinos Arfanakis, Daniel Varon, Maria T Greig, Olga James, Bonnie Goldstein, Kimberly S. Martin, Dino Massoglia, Olga Brawman-Mintzer, Walter Martinez, Howard Rosen, Kelly Behan, Sterling C. Johnson, J. Jay Fruehling, Sandra Harding, Elaine R. Peskind, Eric C. Petrie, Gail Li, Jerome A. Yesavage, Ansgar J. Furst, Steven Chao, Scott Mackin, Rema Raman, Erin Drake, Mike Donohue, Gustavo Jimenez, Kelly Harless, Jennifer Salazar, Yuliana Cabrera, Lindsey Hergesheimer, Elizabeth Shaffer, Craig Nelson, David Bickford, Meryl Butters, Michelle Zmuda, Denise Reyes, Kelley M. Faber, Kelly N. Nudelman, Yiu Ho Au, Kelly Scherer, Daniel Catalinotto, Samuel Stark, Elise Ong, and Dariella Fernandez

Subjects
18F-AV1451, Tau PET, cognitively normal, mild cognition impairment, Alzheimer's disease, Neurology. Diseases of the nervous system, RC346-429
Abstract

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification.

Published
2019
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22. Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI

Author

Patricia M. Johnson, Dana J. Lin, Jure Zbontar, C. Lawrence Zitnick, Anuroop Sriram, Matthew Muckley, James S. Babb, Mitchell Kline, Gina Ciavarra, Erin Alaia, Mohammad Samim, William R. Walter, Liz Calderon, Thomas Pock, Daniel K. Sodickson, Michael P. Recht, and Florian Knoll

Subjects
Radiology, Nuclear Medicine and imaging
Published
2023

23. Diagnosis, Prognosticators, and Management of Acute Invasive Fungal Rhinosinusitis: Multidisciplinary Consensus Statement and Evidence‐Based Review with Recommendations

Author

Lauren T. Roland, Ian M. Humphreys, Christopher H. Le, Jennifer M. Babik, Christopher E. Bailey, Lilangi S. Ediriwickrema, Monica Fung, Joshua A. Lieberman, Kelly R. Magliocca, Hannah H. Nam, Neville W. Teo, Penelope C. Thomas, Blair A. Winegar, Jack L. Birkenbeuel, Abel P. David, Khodayar Goshtasbi, Patricia G. Johnson, Elaine C. Martin, Theodore V. Nguyen, Neil N. Patel, Hannan A. Qureshi, Kaijun Tay, Milind Vasudev, Waleed M. Abuzeid, Peter H. Hwang, Aria Jafari, Matthew S. Russell, Justin H. Turner, Sarah K. Wise, and Edward C. Kuan

Subjects
Otorhinolaryngology, Immunology and Allergy
Published
2023

24. Feeding level is associated with altered liver transcriptome and follicle selection in hen

Author

Claire S, Stephens, Alexandra, Hill-Ricciuti, Laurie, Francoeur, and Patricia A, Johnson

Subjects
Liver, Ovarian Follicle, Reproductive Medicine, Reproduction, Animals, Female, Cell Biology, General Medicine, Transcriptome, Animal Feed, Chickens, Diet
Abstract

Genetic selection for particular traits in domestic animals may have altered the optimal feedback regulation among systems regulating appetite, growth, and reproduction. Broiler breeder chickens have been selected for fast and efficient growth and, unless feed restricted, consume excessively resulting in poor reproductive efficiency. We examined the effect of dietary treatment in full-fed and restricted-fed broiler breeder hens on ovarian responses, liver morphology, and transcriptome associated with reproductive function. Although full-fed broiler breeder hens had lower egg production (P 8 mm (P 2-fold in response to feeding level (P

Published
2022

25. Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits

Author

Melanie Hess, Larissa Zetouni, Andrew S. Hess, Juliana Budel, Ken G. Dodds, Hannah M. Henry, Rudiger Brauning, Alan F. McCulloch, Sharon M. Hickey, Patricia L. Johnson, Sara Elmes, Janine Wing, Brooke Bryson, Kevin Knowler, Dianne Hyndman, Hayley Baird, Kathryn M. McRae, Arjan Jonker, Peter H. Janssen, John C. McEwan, and Suzanne J. Rowe

Abstract

Background Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3,139 rumen samples, collected from 1,200 dual purpose ewes, using Restriction Enzyme-Reduced Representation Sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (Residual Feed Intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. Results Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. Conclusions This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log10 proportions of each tag normalized within Cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Published
2022

26. The COPHELA (Cooperation in Quality Assurance for Pharmacy Education and Training between Europe and Latin America) Project

Author

Antonio Sánchez-Pozo, Afonso Miguel Cavaco, Paolo Blasi, Mariana Ortiz Reynoso, Carlos Tomas Quirino-Barreda, Patricia Acuña Johnson, Fernando Torres Moscoso, Selma Rodrigues de Castilho, Claudia Fegadolli, Sergio Slan Zarwar, Jeffrey Atkinson, and on behalf of the COPHELA Associated Partners

Subjects
pharmacy, education, specialization, master degree, distance learning, european union, latin america, cooperation, patient safety, pharmaceutical industry, Pharmacy and materia medica, RS1-441
Abstract

COPHELA (Cooperation in Quality Assurance for Pharmacy Education and Training between Europe and Latin America), a collaborative project between the European Union (EU) and Latin America, will produce on-line courses for the master degree in pharmacy. The program runs from 2019 through 2021. It is funded by the Erasmus+ program of the Education, Audio-visual and Culture Executive Agency (EACEA) of the European Commission. The partners are EU and Latin American universities. These are accompanied by associated partners from EU and Latin American universities, as well as from governmental and non-governmental organizations, such as pharmacy chambers and educational associations. The project is coordinated by the University of Granada, Spain (first author of this paper). It will produce distance learning master degree courses in a dozen fields of specialized pharmaceutical science education and practice, ranging from patient care to industrial pharmacy. This paper describes the design of the project and is intended to evoke constructive comments. It also represents a call for the recruitment of additional associated partners.

Published
2020
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27. Influenza infection directly alters innate IL-23 and IL-12p70 and subsequent IL-17A and IFN-γ responses to pneumococcus in vitro in human monocytes.

Author

Sinead T Loughran, Patrick A Power, Paula T Maguire, Samantha L McQuaid, Paul J Buchanan, Ingileif Jonsdottir, Robert W Newman, Ruth Harvey, and Patricia A Johnson

Subjects
Medicine, Science
Abstract

IMPORTANCE:Influenza virus is highly contagious and poses substantial public health problems due to its strong association with morbidity and mortality. Approximately 250,000-500,000 deaths are caused by seasonal influenza virus annually, and this figure increases during periods of pandemic infections. Most of these deaths are due to secondary bacterial pneumonia. Influenza-bacterial superinfection can result in hospitalisation and/or death of both patients with pre-existing lung disease or previously healthy individuals. The importance of our research is in determining that influenza and its component haemagglutinin has a direct effect on the classic pneumococcus induced pathways to IL-17A in our human ex vivo model. Our understanding of the mechanism which leaves people exposed to influenza infection during superinfection remain unresolved. This paper demonstrates that early infection of monocytes inhibits an arm of immunity crucial to bacterial clearance. Understanding this mechanism may provide alternative interventions in the case of superinfection with antimicrobial resistant strains of bacteria.

Published
2018
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28. Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

Author

Melanie K. Hess, Hannah E. Hodgkinson, Andrew S. Hess, Larissa Zetouni, Juliana C.C. Budel, Hannah M. Henry, Alistair Donaldson, Timothy P. Bilton, Tracey C. van Stijn, Michelle R. Kirk, Ken G. Dodds, Rudiger Brauning, Alan F. McCulloch, Sharon M. Hickey, Patricia L. Johnson, Arjan Jonker, Nickolas Morton, Shaun Hendy, V. Hutton Oddy, Peter H. Janssen, John C. McEwan, and Suzanne J. Rowe

Abstract

Background Producing animal protein while reducing the animal’s impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. Results Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. Conclusions Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual’s future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Published
2022

29. Grazing Behavior, Forage Quality, and Intake Rates of Livestock Grazing Pastures Occupied by Prairie Dogs

Author

Jameson R. Brennan, Janna J Block, Patricia S. Johnson, Kenneth C. Olson, and Christopher S. Schauer

Subjects
0106 biological sciences, geography, geography.geographical_feature_category, Ecology, business.industry, Forage, Plant community, 04 agricultural and veterinary sciences, Prairie dog, Management, Monitoring, Policy and Law, Biology, 01 natural sciences, Pasture, 010601 ecology, Animal science, biology.animal, Grazing, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Forb, Animal Science and Zoology, Livestock, Rangeland, business, Nature and Landscape Conservation
Abstract

Prairie dogs can reduce the carrying capacity on rangelands by up to 50% through direct consumption of vegetation and by clipping plants. Studies have shown that forage quality and digestibility are greater on prairie dog towns than off town; however, research is lacking that quantifies rates of forage and nutrition intake by cattle. In 2012−2016, a study was conducted in South Dakota to evaluate livestock grazing behavior, diet quality, and forage intake on three plant communities in pastures occupied by prairie dogs. Plant communities studied were grass dominated on-town sites (PDOG-GRASS), forb dominated on-town sites (PDOG-FORB), and grass dominated off-town sites (NO-PDOG). Three pastures with varying levels of prairie dog occupation (0%, 20%, and 40%) were studied. Each pasture was grazed by a herd of yearling steers, a subset of which were fitted with Global Positioning System (GPS) collars. Daily time spent grazing was estimated for each plant community. Forage quality and intake were estimated using ruminally fistulated steers that were allowed to graze in 30-min increments within each plant community for June, July, and August of each year. Rumen samples were weighed and analyzed for forage quality. Intake was calculated as the rate of organic matter per minute and multiplied by average grazing time based on GPS collar data. Livestock grazing preference decreased linearly (P

Published
2021

30. Corrigendum: Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Author

Shengwen Guo, Chunren Lai, Congling Wu, Guiyin Cen, The Alzheimer's Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Michael Weiner, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, M. Marcel Mesulam, William Potter, Peter Snyder, Adam Schwartz, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Archana B. Balasubramanian, Jennifer Mason, Iris Sim, Danielle Harvey, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCArli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, John C. Morris, Nigel J. Cairns, Erin Franklin, Lisa Taylor-Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Kelley Faber, Sungeun Kim, Kwangsik Nho, Lean Thal, Leon Thal, Neil Buckholtz, Peter J. Snyder, Marilyn Albert, Richard Frank, John Hsiao, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne L. Lord, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva-Meyer, Valory Pavlik, Victoria Shibley, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau Ances, Maria Carroll, Mary L. Creech, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, David Geldmacher, Marissa Natelson Love, Randall Griffith, David Clark, John Brockington, Erik Roberson, Hillel Grossman, Effie Mitsis, Raj C. Shah, Leyla deToledo-Morrell, Ranjan Duara, Maria T. Greig-Custo, Warren Barker, Chiadi Onyike, Daniel D'Agostino, Stephanie Kielb, Martin Sadowski, Mohammed O. Sheikh, Ulysse Anaztasia, Gaikwad Mrunalini, P. Murali Doraiswamy, Jeffrey R. Petrella, Salvador Borges-Neto, Terence Z. Wong, Edward Coleman, Steven E. Arnold, Jason H. Karlawish, David A. Wolk, Christopher M. Clark, Charles D. Smith, Greg Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Steven G. Potkin, Adrian Preda, Dana Nguyen, Kyle Womack, Dana Mathews, Mary Quiceno, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Russell H. Swerdlow, William M. Brooks, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel H.S. Silverman, Po H. Lu, George Bartzokis, Neill R Graff-Radford, Francine Parfitt, Kim Poki-Walker, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Pradeep Varma, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternack, Irina Rachisky, Dick Trost, Andrew Kertesz, Charles Bernick, Donna Munic, Marek-Marsel Mesulam, Emily Rogalski, Kristine Lipowski, Sandra Weintraub, Borna Bonakdarpour, Diana Kerwin, Chuang-Kuo Wu, Nancy Johnson, Carl Sadowsky, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Jerome Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Evan Fletcher, Pauline Maillard, John Olichney, Charles DeCarli, Owen Carmichael, Smita Kittur, Michael Borrie, T-Y Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Pierre Tariot, Anna Burke, Ann Marie Milliken, Nadira Trncic, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Brendan Kelley, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Kaycee M. Sink, Gordineer Leslie, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Geoffrey Tremont, Lori A. Daiello, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, David Perry, Jacobo Mintzer, Kenneth Spicer, David Bachman, Stephen Pasternak, Irina Rachinsky, John Rogers, Dick Drost, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Karen Ekstam Smith, Hristina Koleva, Ki Won Nam, Hyungsub Shim, Norman Relkin, Gloria Chiang, Michael Lin, Lisa Ravdin, Amanda Smith, Balebail Ashok Raj, Kristin Fargher, Thomas Neylan, Jordan Grafman, Gessert Devon, Davis Melissa, Rosemary Morrison, Hayes Jacqueline, Finley Shannon, Kantarci Kejal, Ward Chad, Erin Householder, Crawford Karen, Neu Scott, Friedl Karl, Becerra Mauricio, Debra Fleischman, Konstantinos Arfanakis, Daniel Varon, Maria T Greig, Olga James, Bonnie Goldstein, Kimberly S. Martin, Dino Massoglia, Olga Brawman-Mintzer, Walter Martinez, Howard Rosen, Kelly Behan, Sterling C. Johnson, J. Jay Fruehling, Sandra Harding, Elaine R. Peskind, Eric C. Petrie, Gail Li, Jerome A. Yesavage, Ansgar J. Furst, and Steven Chao

Subjects
mild cognitive impairment, conversion, cortical feature, sparse-constrained regression, feature reduction, classification, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Published
2017
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31. Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Author

Shengwen Guo, Chunren Lai, Congling Wu, Guiyin Cen, The Alzheimer's Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Michael Weiner, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, M. Marcel Mesulam, William Potter, Peter Snyder, Adam Schwartz, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Archana B. Balasubramanian, Jennifer Mason, Iris Sim, Danielle Harvey, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCArli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, John C. Morris, Nigel J. Cairns, Erin Franklin, Lisa Taylor-Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Kelley Faber, Sungeun Kim, Kwangsik Nho, Lean Thal, Leon Thal, Neil Buckholtz, Peter J. Snyder, Marilyn Albert, Richard Frank, John Hsiao, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne L. Lord, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva-Meyer, Valory Pavlik, Victoria Shibley, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau Ances, Maria Carroll, Mary L. Creech, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, David Geldmacher, Marissa Natelson Love, Randall Griffith, David Clark, John Brockington, Erik Roberson, Hillel Grossman, Effie Mitsis, Raj C. Shah, Leyla deToledo-Morrell, Ranjan Duara, Maria T. Greig-Custo, Warren Barker, Chiadi Onyike, Daniel D'Agostino, Stephanie Kielb, Martin Sadowski, Mohammed O. Sheikh, Ulysse Anaztasia, Gaikwad Mrunalini, P. Murali Doraiswamy, Jeffrey R. Petrella, Salvador Borges-Neto, Terence Z. Wong, Edward Coleman, Steven E. Arnold, Jason H. Karlawish, David A. Wolk, Christopher M. Clark, Charles D. Smith, Greg Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Steven G. Potkin, Adrian Preda, Dana Nguyen, Kyle Womack, Dana Mathews, Mary Quiceno, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Russell H. Swerdlow, William M. Brooks, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel H.S. Silverman, Po H. Lu, George Bartzokis, Neill R Graff-Radford, Francine Parfitt, Kim Poki-Walker, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Pradeep Varma, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternack, Irina Rachisky, Dick Trost, Andrew Kertesz, Charles Bernick, Donna Munic, Marek-Marsel Mesulam, Emily Rogalski, Kristine Lipowski, Sandra Weintraub, Borna Bonakdarpour, Diana Kerwin, Chuang-Kuo Wu, Nancy Johnson, Carl Sadowsky, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Jerome Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Evan Fletcher, Pauline Maillard, John Olichney, Charles DeCarli, Owen Carmichael, Smita Kittur, Michael Borrie, T-Y Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Pierre Tariot, Anna Burke, Ann Marie Milliken, Nadira Trncic, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Brendan Kelley, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Kaycee M. Sink, Gordineer Leslie, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Geoffrey Tremont, Lori A. Daiello, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, David Perry, Jacobo Mintzer, Kenneth Spicer, David Bachman, Stephen Pasternak, Irina Rachinsky, John Rogers, Dick Drost, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Karen Ekstam Smith, Hristina Koleva, Ki Won Nam, Hyungsub Shim, Norman Relkin, Gloria Chiang, Michael Lin, Lisa Ravdin, Amanda Smith, Balebail Ashok Raj, Kristin Fargher, Thomas Neylan, Jordan Grafman, Gessert Devon, Davis Melissa, Rosemary Morrison, Hayes Jacqueline, Finley Shannon, Kantarci Kejal, Ward Chad, Erin Householder, Crawford Karen, Neu Scott, Friedl Karl, Becerra Mauricio, Debra Fleischman, Konstantinos Arfanakis, Daniel Varon, Maria T Greig, Olga James, Bonnie Goldstein, Kimberly S. Martin, Dino Massoglia, Olga Brawman-Mintzer, Walter Martinez, Howard Rosen, Kelly Behan, Sterling C. Johnson, J. Jay Fruehling, Sandra Harding, Elaine R. Peskind, Eric C. Petrie, Gail Li, Jerome A. Yesavage, Ansgar J. Furst, and Steven Chao

Subjects
mild cognitive impairment, conversion, cortical feature, sparse-constrained regression, feature reduction, classification, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease.

Published
2017
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32. Sustainable production of housefly (Musca domestica) larvae as a protein-rich feed ingredient by utilizing cattle manure.

Author

Mahmoud Hussein, Viju V Pillai, Joshua M Goddard, Hui G Park, Kumar S Kothapalli, Deborah A Ross, Quirine M Ketterings, J Thomas Brenna, Mark B Milstein, Helene Marquis, Patricia A Johnson, Jan P Nyrop, and Vimal Selvaraj

Subjects
Medicine, Science
Abstract

The common housefly, Musca domestica, is a considerable component of nutrient recycling in the environment. Use of housefly larvae to biodegrade manure presents an opportunity to reduce waste disposal while the rapidly assimilated insect biomass can also be used as a protein rich animal feed. In this study, we examine the biodegradation of dairy cattle manure using housefly larvae, and the nutritional value of the resulting larva meal as a feed ingredient. Our results demonstrated that dairy cattle manure presents a balanced substrate for larval growth, and the spent manure showed reductions in concentration of total nitrogen (24.9%) and phosphorus (6.2%) with an overall reduction in mass. Larva yield at an optimum density was approximately 2% of manure weight. Nutritional analysis of M. domestica larva meal showed values comparable to most high protein feed ingredients. Larva meal was 60% protein with a well-balanced amino acid profile, and 20% fat with 57% monounsaturated fatty acids, and 39% saturated fatty acids. Larva meal lacked any significant amount of omega-3 fatty acids. Evaluation of micronutrients in larva meal suggested that it is a good source of calcium and phosphorus (0.5% and 1.1% respectively). The nutritional value of larva meal closely matches that of fishmeal, making it a potentially attractive alternative for use as a protein-rich feed ingredient for livestock and aquaculture operations.

Published
2017
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33. 329-OR: Videoconferencing for Diabetes Self-Management Support—A Viable Option for Meeting the Needs of High-Risk Patients in Rural Areas?

Author

RAWAN HAMMOUDEH, JODI S. KRALL, PATRICIA A. JOHNSON, SHARI L. REYNOLDS, KRISTINE RUPPERT, JASON NG, and LINDA M. SIMINERIO

Subjects
Endocrinology, Diabetes and Metabolism, Internal Medicine
Abstract

Ongoing support is critical for effective diabetes (DM) self-management, but difficult to deliver, particularly in areas with limited resources. The purpose of the study was to assess the impact of a virtual support model on DM outcomes for high-risk patients in rural underserved communities. Methods: Patients with HbA1c>9% receiving care in federally qualified centers were referred to the Telemedicine for Reach, Education, Access, Treatment and Ongoing Support (TREAT-ON) program, where a Diabetes Care and Education Specialist (DCES) provided in person diabetes self-management education and ongoing support through videoconferencing. Participant demographics, BMI and HbA1c were collected from patient records. Participants completed the DM Summary of Self-Care Activities, Distress and Empowerment Scales and Morisky Medication Adherence Measure at baseline and 6 months, and the Telehealth Usability Questionnaire at study completion. Pre/post values were compared for HbA1c, self-care, psychosocial and process outcomes. Results: Participants (n=37) were 84% white, mean age 46.1 years with mean BMI 37.5. Glycemia improved with a mean reduction in HbA1c from 11.2% at baseline to 9.1% at follow-up (p Conclusions: Findings offer evidence of significant benefits and acceptability of a video-conferencing delivery model for DM self-management support. Future research should explore additional ways to empower individuals to continue and sustain improvements. Disclosure R.Hammoudeh: None. J.S.Krall: Research Support; Becton, Dickinson and Company, Sanofi. P.A.Johnson: None. S.L.Reynolds: None. K.Ruppert: None. J.Ng: Research Support; Sanofi. L.M.Siminerio: Advisory Panel; Abbott, Bayer AG, Research Support; Becton, Dickinson and Company, Sanofi. Funding National Institute of Diabetes Digestive and Kidney Diseases of the National Institutes of Health (R34DK123370) .

Published
2022

34. 521-P: Care Partner in Virtual Diabetes Self-Management Education and Support

Author

MARGARET ZUPA, PATRICIA A. JOHNSON, JODI S. KRALL, JASON NG, SHARI L. REYNOLDS, ANN-MARIE ROSLAND, and LINDA M. SIMINERIO

Subjects
Endocrinology, Diabetes and Metabolism, Internal Medicine
Abstract

Background: Support from care partners (CPs) , family or friends who are involved in diabetes management, is associated with improved self-management and clinical outcomes for adults with type 2 diabetes (T2D) . Therefore, guidelines recommend active CP involvement in diabetes self-management education and support (DSMES) . Telemedicine is increasingly being used to deliver DSMES and may facilitate CP involvement. Objective: To examine the frequency and type of CP involvement in virtual DSMES sessions delivered to patients in their homes over 12 months as part of the Telemedicine for Reach, Education, Access, Treatment, and Ongoing Support study, designed to evaluate the impact of longitudinal DSMES conducted via videoconferencing. Methods: 43 patients with T2D and an HbA1c>9% were enrolled from rural federally qualified health centers. A diabetes care and education specialist (DCES) performed an initial in-person needs assessment, followed by individualized virtual DSMES sessions via videoconferencing over 12 months. Participants were surveyed on the presence and roles of CPs at baseline, and DCES recorded CP involvement at each DSMES session. Twenty participants identified a diabetes CP at baseline; 75% lived with their CP and 60% of CPs were the patient’s significant other. Patients reported that CPs regularly helped with self-management by encouraging healthy eating (80%) , medication adherence (70%) , and discussing home blood glucose results (70%) . Nine participants had a CP involved in at least one virtual DSMES session; CPs performed diverse functions, including assisting with technology, setting up continuous glucose monitors, reviewing nutrition recommendations, and facilitating information sharing between participants and DCES. Conclusions and Future Direction: For adults with T2D, virtual visits offer opportunities for CPs to support and enhance DSMES. Efforts to more actively engage existing CPs could better leverage this resource to support ongoing diabetes self-management. Disclosure M.Zupa: None. P.A.Johnson: None. J.S.Krall: Research Support; Becton, Dickinson and Company, Sanofi. J.Ng: Research Support; Sanofi. S.L.Reynolds: None. A.Rosland: None. L.M.Siminerio: Advisory Panel; Abbott, Bayer AG, Research Support; Becton, Dickinson and Company, Sanofi. Funding NIDDK (R34DK123370) NCATS (TR001856)

Published
2022

35. Using Deep Learning to Accelerate Knee MRI at 3 T: Results of an Interchangeability Study

Author

Matthew J. Muckley, Jure Zbontar, William R. Walter, Mohammad Samim, Tullie Murrell, Aaron Defazio, Nafissa Yakubova, Leon Rybak, Gina A. Ciavarra, C. Lawrence Zitnick, Zhengnan Huang, Dana J Lin, Florian Knoll, Mitchell J Kline, Erin F. Alaia, Michael G. Rabbat, Ruben Stern, Anuroop Sriram, Michael P. Recht, Yvonne W. Lui, Patricia M. Johnson, and Daniel K. Sodickson

Subjects
Adult, Male, Adolescent, Knee Joint, Image quality, Knee Injuries, Iterative reconstruction, Signal-To-Noise Ratio, Interchangeability, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Acceleration, Deep Learning, 0302 clinical medicine, Data acquisition, Knee mri, Image Processing, Computer-Assisted, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Aged, Aged, 80 and over, business.industry, Deep learning, Pattern recognition, General Medicine, Middle Aged, Magnetic Resonance Imaging, Feature (computer vision), 030220 oncology & carcinogenesis, Female, Artificial intelligence, business
Abstract

OBJECTIVE: Deep learning (DL) image reconstruction has the potential to disrupt the current state of MRI by significantly decreasing the time required for MRI examinations. Our goal was to use DL to accelerate MRI to allow a 5-minute comprehensive examination of the knee without compromising image quality or diagnostic accuracy. MATERIALS AND METHODS. A DL model for image reconstruction using a variational network was optimized. The model was trained using dedicated multisequence training, in which a single reconstruction model was trained with data from multiple sequences with different contrast and orientations. After training, data from 108 patients were retrospectively undersampled in a manner that would correspond with a net 3.49-fold acceleration of fully sampled data acquisition and a 1.88-fold acceleration compared with our standard twofold accelerated parallel acquisition. An interchangeability study was performed, in which the ability of six readers to detect internal derangement of the knee was compared for clinical and DL-accelerated images. RESULTS. We found a high degree of interchangeability between standard and DL-accelerated images. In particular, results showed that interchanging the sequences would produce discordant clinical opinions no more than 4% of the time for any feature evaluated. Moreover, the accelerated sequence was judged by all six readers to have better quality than the clinical sequence. CONCLUSION. An optimized DL model allowed acceleration of knee images that performed interchangeably with standard images for detection of internal derangement of the knee. Importantly, readers preferred the quality of accelerated images to that of standard clinical images.

Published
2020

36. Rapid mono and biexponential 3D-T1ρ mapping of knee cartilage using variational networks

Author

Kerstin Hammernik, Patricia M. Johnson, Ravinder R. Regatte, Marcelo V. W. Zibetti, Florian Knoll, and Azadeh Sharafi

Subjects
Multidisciplinary, Coefficient of variation, lcsh:R, lcsh:Medicine, Image processing, 030218 nuclear medicine & medical imaging, Knee cartilage, Scan time, Absolute deviation, 03 medical and health sciences, T1ρ mapping, 0302 clinical medicine, Compressed sensing, Three dimensional imaging, lcsh:Q, lcsh:Science, 030217 neurology & neurosurgery, Mathematics, Biomedical engineering
Abstract

In this study we use undersampled MRI acquisition methods to obtain accelerated 3D mono and biexponential spin–lattice relaxation time in the rotating frame (T1ρ) mapping of knee cartilage, reducing the usual long scan time. We compare the accelerated T1ρ maps obtained by deep learning-based variational network (VN) and compressed sensing (CS). Both methods were compared with spatial (S) and spatio-temporal (ST) filters. Complex-valued fitting was used for T1ρ parameters estimation. We tested with seven in vivo and six synthetic datasets, with acceleration factors (AF) from 2 to 10. Median normalized absolute deviation (MNAD), analysis of variance (ANOVA), and coefficient of variation (CV) were used for analysis. The methods CS-ST, VN-S, and VN-ST performed well for accelerating monoexponential T1ρ mapping, with MNAD around 5% for AF = 2, which increases almost linearly with the AF to an MNAD of 13% for AF = 8, with all methods. For biexponential mapping, the VN-ST was the best method starting with MNAD of 7.4% for AF = 2 and reaching MNAD of 13.1% for AF = 8. The VN was able to produce 3D-T1ρ mapping of knee cartilage with lower error than CS. The best results were obtained by VN-ST, improving CS-ST method by nearly 7.5%.

Published
2020

37. New-Generation Low-Field Magnetic Resonance Imaging of Hip Arthroplasty Implants Using Slice Encoding for Metal Artifact Correction: First In Vitro Experience at 0.55 T and Comparison With 1.5 T

Author

Iman Khodarahmi, Inge M. Brinkmann, Dana J. Lin, Mary Bruno, Patricia M. Johnson, Florian Knoll, Mahesh B. Keerthivasan, Hersh Chandarana, and Jan Fritz

Subjects
Chromium, Titanium, Arthroplasty, Replacement, Hip, Radiology, Nuclear Medicine and imaging, General Medicine, Cobalt, Artifacts, Image Enhancement, Magnetic Resonance Imaging, Article
Abstract

OBJECTIVES: Despite significant progress, artifact-free visualization of the bone and soft tissues around hip arthroplasty implants remains an unmet clinical need. New-generation low-field magnetic resonance imaging (MRI) systems now include slice encoding for metal artifact correction (SEMAC), which may result in smaller metallic artifacts and better image quality than standard-of-care 1.5 T MRI. This study aims to assess the feasibility of SEMAC on a new-generation 0.55 T system, optimize the pulse protocol parameters, and compare the results with those of a standard-of-care 1.5 T MRI. MATERIALS AND METHODS: Titanium (Ti) and cobalt-chromium total hip arthroplasty implants embedded in a tissue-mimicking American Society for Testing and Materials gel phantom were evaluated using turbo spin echo, view angle tilting (VAT), and combined VAT and SEMAC (VAT + SEMAC) pulse sequences. To refine an MRI protocol at 0.55 T, the type of metal artifact reduction techniques and the effect of various pulse sequence parameters on metal artifacts were assessed through qualitative ranking of the images by 3 expert readers while taking measured spatial resolution, signal-to-noise ratios, and acquisition times into consideration. Signal-to-noise ratio efficiency and artifact size of the optimized 0.55 T protocols were compared with the 1.5 T standard and compressed-sensing SEMAC sequences. RESULTS: Overall, the VAT + SEMAC sequence with at least 6 SEMAC encoding steps for Ti and 9 for cobalt-chromium implants was ranked higher than other sequences for metal reduction (P < 0.05). Additional SEMAC encoding partitions did not result in further metal artifact reductions. Permitting minimal residual artifacts, low magnetic susceptibility Ti constructs may be sufficiently imaged with optimized turbo spin echo sequences obviating the need for SEMAC. In cross-platform comparison, 0.55 T acquisitions using the optimized protocols are associated with 45% to 64% smaller artifacts than 1.5 T VAT + SEMAC and VAT + compressed-sensing/SEMAC protocols at the expense of a 17% to 28% reduction in signal-to-noise ratio efficiency. B(1)-related artifacts are invariably smaller at 0.55 T than 1.5 T; however, artifacts related to B(0) distortion, although frequently smaller, may appear as signal pileups at 0.55 T. CONCLUSIONS: Our results suggest that new-generation low-field SEMAC MRI reduces metal artifacts around hip arthroplasty implants to better advantage than current 1.5 T MRI standard of care. While the appearance of B(0)-related artifacts changes, reduction in B(1)-related artifacts plays a major role in the overall benefit of 0.55 T.

Published
2022

38. Comparing stability in random forest models to map Northern Great Plains plant communities in pastures occupied by prairie dogs using Pleiades imagery

Author

Jameson R. Brennan, Patricia S. Johnson, and Niall P. Hanan

Subjects
010504 meteorology & atmospheric sciences, 0211 other engineering and technologies, lcsh:Life, 02 engineering and technology, Prairie dog, 01 natural sciences, Grassland, biology.animal, lcsh:QH540-549.5, Keystone species, Ecology, Evolution, Behavior and Systematics, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Earth-Surface Processes, Biomass (ecology), geography, geography.geographical_feature_category, biology, business.industry, lcsh:QE1-996.5, Plant community, biology.organism_classification, lcsh:Geology, Cynomys ludovicianus, lcsh:QH501-531, Livestock, Physical geography, lcsh:Ecology, Rangeland, business
Abstract

Black-tailed prairie dogs (Cynomys ludovicianus) have been described as a keystone species and are important for grassland conservation, yet many concerns exist over the impact of prairie dogs on plant biomass production and consequently livestock production. The ability to map plant communities in pastures colonized by prairie dogs can provide land managers with an opportunity to optimize rangeland production while balancing conservation goals. The aim of this study was to test the ability of random forest (RF) models to classify five plant communities located on and off prairie dog towns in mixed-grass prairie landscapes of north central South Dakota, assess the stability of RF models among different years, and determine the utility of utilizing remote sensing techniques to identify prairie dog colony extent. During 2015 and 2016, Pleiades satellites were tasked to image the study site for a total of five monthly collections each summer (June–October). Training polygons were mapped in 2016 for the five plant communities and used to train RF models. Both the 2015 and 2016 RF models had low (1 %) out-of-bag error rates. However, comparisons between the predicted plant community maps using the 2015 imagery and one created with the 2016 imagery indicate over 32.9 % of pixels changed plant community class between 2015 and 2016. The results show that while RF models may predict with a high degree of accuracy, overlap of plant communities and interannual differences in rainfall may cause instability in fitted models. A final RF model combining both 2015 and 2016 data yielded the lowest error rates and was also highly accurate in determining prairie dog colony boundaries.

Published
2020

39. Gender gap among rhinology and skull base surgeons

Author

Patricia G Johnson, Kristen A Echanique, Chandala Chitguppi, Jivianne T Lee, and Elina Toskala

Subjects
Skull Base, Surgeons, Sex Factors, Otorhinolaryngology, Immunology and Allergy, Humans, Endoscopy
Published
2022

40. The Effect of a Single Dose of Prophylactic Vancomycin Prior to Peripherally Inserted Central Catheter Removal on Sepsis

Author

Mark Baker, Bikash Bhattarai, Patricia J. Johnson, Christine Wade, Becky Micetic, and Kartik Mody

Subjects
Research, Pediatrics, Perinatology and Child Health, Pharmacology (medical)
Abstract

OBJECTIVE To evaluate the effect of a single dose of prophylactic vancomycin prior to the removal of a peripherally inserted central catheter (PICC) in decreasing sepsis evaluations, positive cultures, and antibiotic usage in neonates. METHODS A retrospective review was conducted from December 1, 2015, through November 30, 2019, to evaluate outcomes of sepsis evaluations, positive cultures, and antibiotic usage in neonates not receiving prophylactic vancomycin prior to the discontinuation of a PICC as compared with those receiving prophylaxis vancomycin in a neonatal intensive care unit (NICU). RESULTS Of the 138 neonates enrolled in the study, 82 did not receive vancomycin prophylaxis (Cohort 1), and 56 did (Cohort 2). Both cohorts were similar in sex distribution, gestational age, and PICC days. The frequency of sepsis evaluations, positive cultures, and the need for antibiotics was not found to be significant (p = 0.404, 0.703, 0.808) (Table 2). CONCLUSIONS The results did not show a statistically significant improvement in the incidence of sepsis in neonates who received prophylactic vancomycin prior to PICC discontinuation. However, there were lower percentages of sepsis evaluations, positive cultures, and antibiotics administered in the Cohort 2 patients. Although the advantage of implementing this antibiotic policy is uncertain based on this study, further research across multiple centers including a larger number of subjects may provide more conclusive results.

Published
2022

41. A Trichomonas vaginalis Rhomboid Protease and Its Substrate Modulate Parasite Attachment and Cytolysis of Host Cells.

Author

Angelica M Riestra, Shiv Gandhi, Michael J Sweredoski, Annie Moradian, Sonja Hess, Sinisa Urban, and Patricia J Johnson

Subjects
Immunologic diseases. Allergy, RC581-607, Biology (General), QH301-705.5
Abstract

Trichomonas vaginalis is an extracellular eukaryotic parasite that causes the most common, non-viral sexually transmitted infection worldwide. Although disease burden is high, molecular mechanisms underlying T. vaginalis pathogenesis are poorly understood. Here, we identify a family of putative T. vaginalis rhomboid proteases and demonstrate catalytic activity for two, TvROM1 and TvROM3, using a heterologous cell cleavage assay. The two T. vaginalis intramembrane serine proteases display different subcellular localization and substrate specificities. TvROM1 is a cell surface membrane protein and cleaves atypical model rhomboid protease substrates, whereas TvROM3 appears to localize to the Golgi apparatus and recognizes a typical model substrate. To identify TvROM substrates, we interrogated the T. vaginalis surface proteome using both quantitative proteomic and bioinformatic approaches. Of the nine candidates identified, TVAG_166850 and TVAG_280090 were shown to be cleaved by TvROM1. Comparison of amino acid residues surrounding the predicted cleavage sites of TvROM1 substrates revealed a preference for small amino acids in the predicted transmembrane domain. Over-expression of TvROM1 increased attachment to and cytolysis of host ectocervical cells. Similarly, mutations that block the cleavage of a TvROM1 substrate lead to its accumulation on the cell surface and increased parasite adherence to host cells. Together, these data indicate a role for TvROM1 and its substrate(s) in modulating attachment to and lysis of host cells, which are key processes in T. vaginalis pathogenesis.

Published
2015
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42. Deep learning reconstruction enables highly accelerated biparametric MR imaging of the prostate

Author

Patricia M. Johnson, Angela Tong, Awani Donthireddy, Kira Melamud, Robert Petrocelli, Paul Smereka, Kun Qian, Mahesh B. Keerthivasan, Hersh Chandarana, and Florian Knoll

Subjects
Male, Deep Learning, Diffusion Magnetic Resonance Imaging, Prostate, Humans, Prostatic Neoplasms, Radiology, Nuclear Medicine and imaging, Magnetic Resonance Imaging, Article, Retrospective Studies
Abstract

BACKGROUND: Early diagnosis and treatment of prostate cancer (PCa) can be curative, however prostate specific antigen is a suboptimal screening test for clinically significant PCa. While prostate MRI has demonstrated value for the diagnosis of PCa, the acquisition time is too long for a first-line screening modality. PURPOSE: To accelerate prostate MRI exams, utilizing a variational network (VN) for image reconstruction. STUDY TYPE: Retrospective SUBJECTS: 113 subjects (train/val/test: 70/13/30) undergoing prostate MRI. FIELD STRENGTH/SEQUENCE: 3.0 T; A T2 Turbo spin echo (TSE) T2 weighted image (T2WI) sequence in axial and coronal planes, and axial echo-planar diffusion weighted imaging (DWI). ASSESSMENT: Four abdominal radiologists evaluated the image quality of VN reconstructions of retrospectively under-sampled biparametric MRIs (bpMRI), and standard bpMRI reconstructions for 20 test subjects (studies). The studies included axial and coronal T2WI, DWI B50 s/mm(2) and B1000 s/mm (4-fold T2WI, 3-fold DWI), all of which were evaluated separately for image quality on a Likert scale (1: non-diagnostic to 5: excellent quality). In another 10 test subjects, three readers graded lesions on bi-parametric MRIs (bpMRI) – which additionally included calculated B1500 s/mm(2), and apparent diffusion coefficient (ADC) map – according to the Prostate Imaging Reporting and Data System (PI-RADS v2.1), for both VN and standard reconstructions. Accuracy of PI-RADS ≥ 3 for clinically significant cancer was computed. Projected scan time of the retrospectively under-sampled bi-parametric exam was also computed. STATISTICAL TESTS: One-sided Wilcoxon signed-rank test was used for comparison of image quality. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for lesion detection and grading. Generalized estimating equation with cluster effect was used to compare differences between standard and VN bpMRI. A p value of

Published
2021

43. Modeling sub-boreal forest canopy bulk density in Minnesota, USA, using synthetic aperture radar and optical satellite sensor data

Author

Peter T. Wolter, Patricia J. Johnson, and Jacob J. Olbrich

Subjects
Synthetic aperture radar, Canopy, Forestry, Environmental Science (miscellaneous), law.invention, Lidar, law, Range (statistics), Environmental science, Satellite, Radar, Visibility, Ecology, Evolution, Behavior and Systematics, Zenith, Remote sensing
Abstract

Background National estimates of canopy bulk density (CBD; kg m−3) for fire behavior modeling are generated and supported by the LANDFIRE program. However, locally derived estimates of CBD at finer scales are preferred over national estimates if they exist, as the absolute accuracy of the LANDFIRE CBD product is low and varies regionally. Active sensors (e.g., lidar or radar) are better suited for this task, as passive sensors are ill equipped to detect differences among key vertical fuel structures, such as coniferous surface fuels (≤2 m high) and canopy fuels above this threshold—a key categorical fuel distinction in fire behavior modeling. However, previous efforts to map CBD using lidar sensor data in the Superior National Forest (SNF) of Minnesota, USA, yielded substandard results. Therefore, we use a combination of dormant-season synthetic aperture radar (SAR) and optical satellite sensor data to (1) expand detectability of coniferous fuels among mixed forest canopies to improve the accuracy of CBD modeling and (2) better understand the influence of surface fuels in this regard. Response variables included FuelCalc output and indirect estimates of maximum burnable fuel based on canopy gap fraction (CGF) measured at ground level and 2 m above ground level. Results SAR variables were important predictors of CBD and total fuel density (TFD) in all independent model calibrations with ground data, in which we define TFD as the sum of CBD and primarily live coniferous surface fuel density (SFD) 0 to 2 m above ground. Exploratory estimates of TFD appeared biased to the presence of sapling-stage conifer fuel on measures of CGF at the ground level. Thus, modeling efforts to calibrate SFD with satellite sensor data failed. Both CGF-based and FuelCalc-based field estimates of CBD yielded close unity with satellite-calibrated estimates, although substantial differences in data distributions existed. Estimates of CBD from the widest CGF zenith angle range (0 to 38°) correlated best with FuelCalc-based CBD estimates, while both resulted in maximum biomass values that exceeded those considered typical for the SNF. Model results from the narrowest zenith angle range (0 to 7°) produced estimates of CBD that were more in line with values considered typical. LANDFIRE’s estimates of CBD were weakly, but significantly (P = 0.05), correlated to both narrow- and wide-angle CGF-based estimates of CBD, but not with FuelCalc-based estimates. Conclusions The combined use of field estimates of CBD, based on indirect measures of CGF according to Keane et al. (Canadian Journal of Forest Research 35:724–739, 2005), with SAR and optical satellite sensor data demonstrates the potential of this method for mapping CBD in the Upper Midwest, USA. Results suggested that the presence of live, coniferous surface fuels neither confounds remote detection nor precludes mapping of CBD in this region using SAR satellite sensor data, as C- and L-band idiosyncrasies likely limit the visibility of these smaller understory fuels from space. Nevertheless, research using direct measures of burnable SFD for calibrations with SAR satellite sensor data should be conducted to more definitively answer this remote detection question, as we suspect substantial bias among measures of CGF from ground level when estimating SFD as the difference between TFD and CBD.

Published
2021

44. Ad Libitum Feeding in Broiler Breeder Hens Alters the Transcriptome of Granulosa Cells of Pre-Hierarchal Follicles

Author

Patricia A. Johnson, Laurie Francoeur, and Claire S. Stephens

Subjects
endocrine system, Granulosa cell, Veterinary medicine, animal diseases, Population, Biology, Selective breeding, Article, Andrology, Transcriptome, Follicle, Follicular phase, SF600-1100, broiler breeder, education, nutrition and reproduction, Granulosa cell differentiation, education.field_of_study, General Veterinary, digestive, oral, and skin physiology, food and beverages, RNA sequencing, egg production, follicle development, granulosa cell, INHBB, QL1-991, Animal Science and Zoology, Zoology
Abstract

Simple Summary Broiler breeds of chickens have been bred for fast growth and feed efficiency, while laying breeds have been bred for optimal egg production. As a consequence of intense selective breeding in broiler breeds, egg production is greatly reduced and leads to inefficient reproduction. One strategy used by producers to improve egg production in broiler breeds has been to limit feed allowance. In this study, we aimed to identify differences in ovarian gene expression between broiler breeder hens fed high (ad libitum) and low feed allowances. Several differences in gene expression were identified, which may explain the decreased egg production seen in broiler breeder hens fed ad libitum. These results inform the poultry industry on the biology of broiler breeder hens fed ad libitum and how levels of high feed intake affect reproductive efficiency. Abstract Intense selective breeding of chickens has resulted in suboptimal egg production in broiler breeder hens. This reproductive phenotype is exacerbated by ad libitum feeding, which leads to excessive and disorganized follicular growth. One strategy used to improve broiler breeder hens’ reproductive efficiency is restricted feeding. In this study, we sought to identify transcriptional changes, which translate the level of dietary intake into increased follicle selection. Broiler breeder hens (n = 16 per group) were raised according to commercial guidelines until 28 weeks of age and then randomly assigned to an ad libitum diet (FF) or continued on a restricted diet (RF) for 6 weeks. Following dietary treatment, FF hens (n = 2) with excessive follicle selection and RF hens (n = 3) with normal follicle selection were selected for RNA-sequencing. Transcriptomes of granulosa cells from 6–8-mm follicles were sequenced to identify transcriptional differences in the follicle population from which selection was made for the preovulatory stage. Differential expression analysis identified several genes known to play a role in follicle development (CYP11A1, STAR, INHA, and INHBB) that are upregulated in FF hens. These changes in gene expression suggest earlier granulosa cell differentiation and steroidogenic competency in the granulosa layer from FF hens.

Published
2021

45. 816-P: Diabetes Education and Cost Savings with Telemedicine Delivery in Rural Communities

Author

Jason Ng, Emily Gammoh, Jodi Krall, Linda M. Siminerio, Archana Bandi, and Patricia A. Johnson

Subjects
Telemedicine, medicine.medical_specialty, education.field_of_study, High prevalence, business.industry, Endocrinology, Diabetes and Metabolism, Population, Retrospective cohort study, Diabetes education, Cost savings, Travel time, Family medicine, Internal Medicine, medicine, business, education, Average cost
Abstract

The high prevalence of diabetes mellitus (DM) and shortage of Diabetes Care and Education Specialists (DCES) in rural communities requires providers and patients to travel long distances to access care. This burden impedes optimal DM management and increases cost. Telemedicine for Reach, Education, Access, Treatment, and Ongoing Support (TREAT-ON) is a Diabetes Education and Support (DSMES) model, where a DCES provides DSMES to patients identified as high risk (A1c >9% or unplanned care). TREAT-ON was initiated in February 2020, where DSMES was provided via telemedicine (TM) visits, previously delivered face-to-face (F2F) to high-risk patients. In this retrospective study, the DCES overall costs (fuel, tolls, and postage), travel time for care delivery, and number of patients seen over a 6-month period (March-August 2019) was compared to (March-August 2020) after TM practices were adopted. From March to August 2019, 59 of 91 patient referrals were completed, compared to 110 of 167 referrals from March to August 2020. The percentage of successful referrals were similar in both groups (64.8% vs. 65.9%). However, the percent of referrals declined by patients were higher in 2019 (18.7%) vs. 2020 (9.0%). Of 59 referrals completed in 2019, 54 were F2F and five TM whereas in 2020 twelve were F2F and 98 TM. Lower average cost per patient was noted in 2020 ($38.85 vs. $6.20). A similar reduction in average travel time per patient was seen, 99 min vs. 16 min in 2020. TREAT-ON model translated to a direct cost savings of $1,606 and reduction of DCES travel time of 67.6 hours equating to a gain of 8.4 workdays opening care opportunities for an additional 67 new referrals. DSMES is a pillar of DM care and alternative methods to expand DSMES services remain imperative. Our early TREAT-ON data shows that telemedicine offers a time and cost-effective approach to DSMES with potential to reach a larger population when compared to traditional F2F visits, and helps to address a current DSCES shortage. Disclosure E. Gammoh: None. P. A. Johnson: None. J. S. Krall: Research Support; Self; Becton, Dickinson and Company, Sanofi. J. Ng: Research Support; Self; Sanofi-Aventis. L. M. Siminerio: Advisory Panel; Self; Abbott Diabetes, Bayer U. S., Research Support; Self; Becton, Dickinson and Company. A. Bandi: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (1R34DK123370-01)

Published
2021

46. 473-P: Feasibility and Acceptability of a Direct-to-Home Diabetes Self-Management Education and Support Telemedicine Program (DSMES) with High-Risk Patients in a Rural, Underserved Area

Author

Shari L. Reynolds, Patricia A. Johnson, Jodi Krall, Linda M. Siminerio, and Jason Ng

Subjects
medicine.medical_specialty, Telemedicine, High risk patients, business.industry, Endocrinology, Diabetes and Metabolism, Diabetes self management, Usability, Telehealth, computer.software_genre, Videoconferencing, Family medicine, Internal Medicine, medicine, Duration (project management), business, Medicaid, computer
Abstract

Ongoing support is critical to DSMES effectiveness, but difficult to realize, particularly in underserved areas with limited resources. The purpose of this study, initiated February 2020, was to evaluate the feasibility and acceptability of Telemedicine for Reach, Education, Access, Treatment, and Ongoing Support (TREAT-ON), a DSMES model delivered primarily through direct-to-home videoconferencing. Methods: High risk patients with diabetes (A1c >9% or unplanned care) from rural federally qualified health centers were referred to TREAT-ON. Participants completed an initial face-to-face or virtual visit with a Diabetes Care and Education Specialist (DCES) to assess needs and develop self-management treatment plan and behavioral goals. Planned follow-up visits, used to support achieving and sustaining goals and outcomes, were conducted through videoconferencing. To assess feasibility and acceptability over first 3-months of participation, visit frequency, duration, completion rates, and technology issues were tracked and patients completed the Telehealth Usability Questionnaire (TUQ). Results: Participants (n=25) were 60% female, 92% White, mean age 47.6±13.6y, mean A1c 11.5±1.8% and 76% had Medicare or Medicaid. They participated in 3 video visits, on average, lasting a mean of 35 minutes/visit. Of all scheduled video visits (n=99), 71% were successfully completed and 23% had technology issues (difficulty setting up system, connectivity issues). The TUQ revealed that participants were highly satisfied with the TREAT-ON videoconferencing approach (4.7/5), finding it useful (4.5/5), easy to learn/use (4.5/5), reliable (4.3/5), with quality interface (4.6/5) and interaction (4.7/5). Conclusion: This telehealth DSMES model offers a promising approach to improve opportunities for ongoing support to vulnerable individuals in underserved communities. Disclosure J. S. Krall: Research Support; Self; Becton, Dickinson and Company, Sanofi. J. Ng: Research Support; Self; Sanofi-Aventis. P. A. Johnson: None. S. L. Reynolds: None. L. M. Siminerio: Advisory Panel; Self; Abbott Diabetes, Bayer U. S., Research Support; Self; Becton, Dickinson and Company. Funding National Institute of Diabetes And Digestive and Kidney Diseases (R34DK123370)

Published
2021

47. Trichomonas vaginalis extracellular vesicles are internalized by host cells using proteoglycans and caveolin-dependent endocytosis

Author

Anand Kumar Rai and Patricia J. Johnson

Subjects
Cell type, media_common.quotation_subject, Protozoan Proteins, Endocytosis, Caveolins, Host-Parasite Interactions, Extracellular Vesicles, chemistry.chemical_compound, Trichomonas vaginalis, Humans, 2.1 Biological and endogenous factors, 2.2 Factors relating to the physical environment, Aetiology, Internalization, media_common, Host cell surface, Multidisciplinary, Vesicle, lipid raft-mediated endocytosis, Biological Transport, Heparan sulfate, Biological Sciences, clathrin independent, Cell biology, Cholesterol, Infectious Diseases, Good Health and Well Being, glycosaminoglycans, chemistry, Cell culture, Interaction with host, Sexually Transmitted Infections, Proteoglycans, Female, Trichomonas Vaginitis, Infection
Abstract

Trichomonas vaginalis, a human-infective parasite, causes the most prevalent nonviral sexually transmitted infection worldwide. This pathogen secretes extracellular vesicles (EVs) that mediate its interaction with host cells. Here, we have developed assays to study the interface between parasite EVs and mammalian host cells and to quantify EV internalization by mammalian cells. We show that T. vaginalis EVs interact with glycosaminoglycans on the surface of host cells and specifically bind to heparan sulfate (HS) present on host cell surface proteoglycans. Moreover, competition assays using HS or removal of HS from the host cell surface strongly inhibit EV uptake, directly demonstrating that HS proteoglycans facilitate EV internalization. We identified an abundant protein on the surface of T. vaginalis EVs, 4-α-glucanotransferase (Tv4AGT), and show using isothermal titration calorimetry that this protein binds HS. Tv4AGT also competitively inhibits EV uptake, defining it as an EV ligand critical for EV internalization. Finally, we demonstrate that T. vaginalis EV uptake is dependent on host cell cholesterol and caveolin-1 and that internalization proceeds via clathrin-independent, lipid raft-mediated endocytosis. These studies reveal mechanisms used to drive host:pathogen interactions and further our understanding of how EVs are internalized by target cells to allow cross-talk between different cell types.

Published
2019

49. Technical Note: Method to Streamline Processing of Livestock Global Positioning System Collar Data

Author

Patricia S. Johnson, Jameson R. Brennan, and Kenneth C. Olson

Subjects
0106 biological sciences, Geographic information system, Ecology, Computer science, business.industry, Technical note, 04 agricultural and veterinary sciences, Management, Monitoring, Policy and Law, Gps collar, computer.software_genre, 01 natural sciences, Collar, 010601 ecology, Software, 040103 agronomy & agriculture, Global Positioning System, 0401 agriculture, forestry, and fisheries, Animal Science and Zoology, Data mining, business, computer, Motion sensors, Nature and Landscape Conservation, Coding (social sciences)
Abstract

The use of global positioning system (GPS) technology to study livestock movement has been widely adopted in range and animal sciences; however, the methods for processing GPS collar data are varied among researchers and often involve repetitive, time-consuming steps to get data into a format available to view in geographic information system (GIS) software. The objective of this technical note is to present a method for quickly processing uniform datasets using a commonly available commercial GPS collar and Program R. Data generated by a Lotek 3300LR GPS collar were processed in seconds using “Lotek_Function,” which was developed using R coding. Traditional hand-processing of the same data generally requires 30 or more minutes and is prone to error due to the tedious, repetitive nature of the task. Due to the open-source nature of Program R, base codes can be modified to fit specific researchers’ needs when incorporating GIS data layers or models to assess behavior based on motion sensor data output from collars.

Published
2019

50. Distribution and Productivity of Naturalized Alfalfa in Mixed-Grass Prairie

Author

Roger N. Gates, Lan Xu, Christopher G. Misar, Patricia S. Johnson, and Arvid Boe

Subjects
0106 biological sciences, Biomass (ecology), education.field_of_study, geography, geography.geographical_feature_category, fungi, Population, food and beverages, Species diversity, 04 agricultural and veterinary sciences, General Medicine, biochemical phenomena, metabolism, and nutrition, Mixed grass prairie, Biology, 01 natural sciences, Grassland, Agronomy, Loam, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Species richness, Rangeland, education, 010606 plant biology & botany
Abstract

Alfalfa (Medicago sativa L.) is an important forage and conservation crop in North America but occurrences of naturalized alfalfa in rangelands are rare. A naturalized population of yellow-flowered alfalfa in mixed-grass prairie on the Grand River National Grassland in South Dakota has potential agricultural value for the region. Despite this value, the distribution pattern of this alfalfa among and within native plant communities in the northern Great Plains is unknown. Field studies were conducted from 2003 through 2006 along topographic positions at two sites where yellow-flowered alfalfa was naturalized to evaluate the relationships of yellow-flowered alfalfa on biomass production, cover, species diversity, and alfalfa seedbank distribution characteristics. High yellow-flowered alfalfa cover (>50%) was associated with increased total biomass and occurred exclusively in swales and toeslopes that had silty loam soils. However, species diversity and non-alfalfa biomass were reduced when yellow-flowered alfalfa cover was high. Yellow-flowered alfalfa cover was lower and species richness was higher on backslopes and shoulder areas where sandy loam soils were present. A strong positive linear association existed between yellow-flowered alfalfa cover and alfalfa seedbank density (r values ranged from 0.76 to 0.82, P < 0.0001). Greater than 99% of the seeds were viable but germination rate was only 4%, indicating a high percentage of hard seed in this alfalfa population. Naturalized yellow-flowered alfalfa was a dominant component of a stable, low diversity plant community composed of mainly introduced species in rich soils of swales/toeslopes that contributed to forage production and quality in mixed-grass prairie in the northern Great Plains.

Published
2019

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