Search

Your search keyword '"Ward, Jennifer"' showing total 8 results
Start Over Author "Ward, Jennifer" Language undetermined
8 results on '"Ward, Jennifer"'

1. Correcting for selection bias in HIV prevalence estimates: an application of sample selection models using data from population-based HIV surveys in seven sub-Saharan African countries

Author

Palma, Anton M, Marra, Giampiero, Bray, Rachel, Saito, Suzue, Awor, Anna Colletar, Jalloh, Mohamed F, Kailembo, Alexander, Kirungi, Wilford, Mgomella, George S, Njau, Prosper, Voetsch, Andrew C, Ward, Jennifer A, Bärnighausen, Till, Harling, Guy, Palma, Anton M [0000-0003-1009-4701], Harling, Guy [0000-0001-6604-491X], and Apollo - University of Cambridge Repository

Subjects
Adult, Male, Adolescent, selection models, population surveys, non-participation, HIV Infections, Middle Aged, RESEARCH ARTICLES, RESEARCH ARTICLE, non‐participation, HIV prevalence, missing data, Young Adult, Cross-Sectional Studies, surveillance, Prevalence, Humans, Africa South of the Sahara, Selection Bias
Abstract

INTRODUCTION: Population-based biomarker surveys are the gold standard for estimating HIV prevalence but are susceptible to substantial non-participation (up to 30%). Analytical missing data methods, including inverse-probability weighting (IPW) and multiple imputation (MI), are biased when data are missing-not-at-random, for example when people living with HIV more frequently decline participation. Heckman-type selection models can, under certain assumptions, recover unbiased prevalence estimates in such scenarios. METHODS: We pooled data from 142,706 participants aged 15-49 years from nationally representative cross-sectional Population-based HIV Impact Assessments in seven countries in sub-Saharan Africa, conducted between 2015 and 2018 in Tanzania, Uganda, Malawi, Zambia, Zimbabwe, Lesotho and Eswatini. We compared sex-stratified HIV prevalence estimates from unadjusted, IPW, MI and selection models, controlling for household and individual-level predictors of non-participation, and assessed the sensitivity of selection models to the copula function specifying the correlation between study participation and HIV status. RESULTS: In total, 84.1% of participants provided a blood sample to determine HIV serostatus (range: 76% in Malawi to 95% in Uganda). HIV prevalence estimates from selection models diverged from IPW and MI models by up to 5% in Lesotho, without substantial precision loss. In Tanzania, the IPW model yielded lower HIV prevalence estimates among males than the best-fitting copula selection model (3.8% vs. 7.9%). CONCLUSIONS: We demonstrate how HIV prevalence estimates from selection models can differ from those obtained under missing-at-random assumptions. Further benefits include exploration of plausible relationships between participation and outcome. While selection models require additional assumptions and careful specification, they are an important tool for triangulating prevalence estimates in surveys with substantial missing data due to non-participation.

Published
2022
Full Text
View/download PDF

2. Additional file 1 of Trends of notification rates and treatment outcomes of tuberculosis cases with and without HIV co-infection in eight rural districts of Uganda (2015 – 2019)

Author

Baluku, Joseph Baruch, Nanyonjo, Resty, Ayo, Jolly, Obwalatum, Jehu Eleazer, Nakaweesi, Jane, Senyimba, Catherine, Lukoye, Deus, Lubwama, Joseph, Ward, Jennifer, and Mukasa, Barbara

Abstract

Additional file 1: Appendix 1. Trends of TB treatment outcomes among men and women in rural Ugandadisaggregated by HIV status (2015 - 2019). Supplementary table 1. Population estimates for people with and without HIVin eight districts of rural Uganda.

Published
2022
Full Text
View/download PDF

3. Tool development to study ubiquitination machinery

Author

Ward, Jennifer, Tate, Ed, Lam, Eric, Fuchter, Matthew, AstraZeneca, and Engineering and Physical Sciences Research Council

Abstract

Ubiquitination is a diverse post-translational modification, involved in a plethora of eukaryotic processes. At least three different enzymes are required for ubiquitination to occur: an ubiquitin-activating enzyme (E1), an ubiquitin-conjugating enzyme (E2) and an ubiquitin ligase (E3). Conversely, deubiquitinating enzymes (DUBs) regulate the removal of ubiquitin modifications. Together, this enzymatic machinery facilitates a wide array of ubiquitin modifications and further ubiquitin-like modifications. Such modifications play a significant role in the regulation of vital biological processes including proteasomal degradation, DNA damage response (DDR) and NF-κB signalling. Ubiquitination machinery can be studied using a chemical proteomics approach. Activity-based probes (ABPs) which covalently trap enzymes can be employed. Such probes possess bioorthogonal handles, which on ligation to complementary reporter groups enable enrichment of probe-enzyme complexes prior to LC-MS/MS, western blot, or fluorescent analysis. The design, synthesis, and development of six inhibitor-inspired ABPs for ubiquitin machinery is described. Both small molecule and peptide probes were explored, and assessed for their ability to act as ubiquitin machinery probes both in intact cells and cell lysate. Spike-in SILAC methodology was employed to quantify probe targets under competitive conditions against parent inhibitors, and in a DNA damage response model. An alternative to using literature inhibitors is to derive novel starting points for tool design through a fragment-based drug discovery approach. A high throughput screen against the minimal catalytic core of HOIP, an E3 ligase, is described together with subsequent validation and characterisation of hit fragments by waterLOGSY NMR and Micro-scale thermophoresis, and crystallography attempts. Finally, a model system for the structural analysis of transient enzyme complexes is explored, to further our understanding of these interactions and ultimately to assess the applicability of these complexes for future drug discovery. The design and synthesis of a maleimide trap is described, along with its application to covalently trap an Ub-E2-E3 complex. Open Access

Published
2016

4. Women in Medieval Europe, 1200-1500

Author

Ward, Jennifer C. and Ward, Jennifer C.

Subjects
Women--History--Middle Ages, 500-1500.--Euro, Women--Social conditions.--Europe, Women and religion--History--To 1500.--Europ, Women--Political activity--History--To 1500, Vrouwen
Abstract

Women in Medieval Europe were expected to be submissive, but such a broad picture ignores great areas of female experience. Between the thirteenth and fifteenth centuries, women are found in the workplace as well as the home, and some women were numbered among the key rulers, saints and mystics of the medieval world. Opportunities and activities changed over time, and by 1500 the world of work was becoming increasingly restricted for women. Women of all social groups were primarily engaged with their families, looking after husband and children, and running the household. Patterns of work varied geographically. In the northern towns, women engaged in a wide range of crafts, with a small number becoming entrepreneurs. Many of the poor made a living as servants and labourers. Prostitution flourished in many medieval towns. Some women turned to the religious life, and here opportunities burgeoned in the thirteenth century. The Middle Ages are not remote from the twenty-first century; the lives of medieval women evoke a response today. The medieval mother faced similar problems to her modern counterpart. The sheer variety of women's experience in the later Middle Ages is fully brought out in this book.

Published
2014

5. Isotope ratios of H, C, and O in CO₂ and H₂O of the martian atmosphere

Author

Webster, Chris R, Mahaffy, Paul R, Flesch, Gregory J, Niles, Paul B, Jones, John H, Leshin, Laurie A, Atreya, Sushil K, Stern, Jennifer C, Christensen, Lance E, Owen, Tobias, Franz, Heather, Pepin, Robert O, Steele, Andrew and the MSL Science Team, Achilles, Cherie, Agard, Christophe, Alves Verdasca, José Alexandre, Anderson, Robert, Anderson, Ryan, Archer, Doug, Armiens-Aparicio, Carlos, Arvidson, Ray, Atlaskin, Evgeny, Aubrey, Andrew, Baker, Burt, Baker, Michael, Balic-Zunic, Tonci, Baratoux, David, Baroukh, Julien, Barraclough, Bruce, Bean, Keri, Beegle, Luther, Behar, Alberto, Bell, James, Bender, Steve, Benna, Mehdi, Bentz, Jennifer, Berger, Gilles, Berger, Jeff, Berman, Daniel, Bish, David, Blake, David F, Blanco Avalos, Juan J, Blaney, Diana, Blank, Jen, Blau, Hannah, Bleacher, Lora, Boehm, Eckart, Botta, Oliver, Böttcher, Stephan, Boucher, Thomas, Bower, Hannah, Boyd, Nick, Boynton, Bill, Breves, Elly, Bridges, John, Bridges, Nathan, Brinckerhoff, William, Brinza, David, Bristow, Thomas, Brunet, Claude, Brunner, Anna, Brunner, Will, Buch, Arnaud, Bullock, Mark, Burmeister, Sönke, Cabane, Michel, Calef, Fred, Cameron, James, Campbell, John, Cantor, Bruce, Caplinger, Michael, Caride Rodríguez, Javier, Carmosino, Marco, Carrasco Blázquez, Isaías, Charpentier, Antoine, Chipera, Steve, Choi, David, Clark, Benton, Clegg, Sam, Cleghorn, Timothy, Cloutis, Ed, Cody, George, Coll, Patrice, Conrad, Pamela, Coscia, David, Cousin, Agnès, Cremers, David, Crisp, Joy, Cros, Alain, Cucinotta, Frank, d'Uston, Claude, Davis, Scott, Day, Mackenzie, de la Torre Juarez, Manuel, DeFlores, Lauren, DeLapp, Dorothea, DeMarines, Julia, DesMarais, David, Dietrich, William, Dingler, Robert, Donny, Christophe, Downs, Bob, Drake, Darrell, Dromart, Gilles, Dupont, Audrey, Duston, Brian, Dworkin, Jason, Dyar, M Darby, Edgar, Lauren, Edgett, Kenneth, Edwards, Christopher, Edwards, Laurence, Ehlmann, Bethany, Ehresmann, Bent, Eigenbrode, Jen, Elliott, Beverley, Elliott, Harvey, Ewing, Ryan, Fabre, Cécile, Fairén, Alberto, Farley, Ken, Farmer, Jack, Fassett, Caleb, Favot, Laurent, Fay, Donald, Fedosov, Fedor, Feldman, Jason, Feldman, Sabrina, Fisk, Marty, Fitzgibbon, Mike, Floyd, Melissa, Flückiger, Lorenzo, Forni, Olivier, Fraeman, Abby, Francis, Raymond, François, Pascaline, Freissinet, Caroline, French, Katherine Louise, Frydenvang, Jens, Gaboriaud, Alain, Gailhanou, Marc, Garvin, James, Gasnault, Olivier, Geffroy, Claude, Gellert, Ralf, Genzer, Maria, Glavin, Daniel, Godber, Austin, Goesmann, Fred, Goetz, Walter, Golovin, Dmitry, Gómez Gómez, Felipe, Gómez-Elvira, Javier, Gondet, Brigitte, Gordon, Suzanne, Gorevan, Stephen, Grant, John, Griffes, Jennifer, Grinspoon, David, Grotzinger, John, Guillemot, Philippe, Guo, Jingnan, Gupta, Sanjeev, Guzewich, Scott, Haberle, Robert, Halleaux, Douglas, Hallet, Bernard, Hamilton, Vicky, Hardgrove, Craig, Harker, David, Harpold, Daniel, Harri, Ari-Matti, Harshman, Karl, Hassler, Donald, Haukka, Harri, Hayes, Alex, Herkenhoff, Ken, Herrera, Paul, Hettrich, Sebastian, Heydari, Ezat, Hipkin, Victoria, Hoehler, Tori, Hollingsworth, Jeff, Hudgins, Judy, Huntress, Wesley, Hurowitz, Joel, Hviid, Stubbe, Iagnemma, Karl, Indyk, Steve, Israël, Guy, Jackson, Ryan, Jacob, Samantha, Jakosky, Bruce, Jensen, Elsa, Jensen, Jaqueline Kløvgaard, Johnson, Jeffrey, Johnson, Micah, Johnstone, Steve, Jones, Andrea, Joseph, Jonathan, Jun, Insoo, Kah, Linda, Kahanpää, Henrik, Kahre, Melinda, Karpushkina, Natalya, Kasprzak, Wayne, Kauhanen, Janne, Keely, Leslie, Kemppinen, Osku, Keymeulen, Didier, Kim, Myung-Hee, Kinch, Kjartan, King, Penny, Kirkland, Laurel, Kocurek, Gary, Koefoed, Asmus, Köhler, Jan, Kortmann, Onno, Kozyrev, Alexander, Krezoski, Jill, Krysak, Daniel, Kuzmin, Ruslan, Lacour, Jean Luc, Lafaille, Vivian, Langevin, Yves, Lanza, Nina, Lasue, Jeremie, Le Mouélic, Stéphane, Lee, Ella Mae, Lee, Qiu-Mei, Lees, David, Lefavor, Matthew, Lemmon, Mark, Lepinette Malvitte, Alain, Léveillé, Richard, Lewin-Carpintier, Éric, Lewis, Kevin, Li, Shuai, Lipkaman, Leslie, Little, Cynthia, Litvak, Maxim, Lorigny, Eric, Lugmair, Guenter, Lundberg, Angela, Lyness, Eric, Madsen, Morten, Maki, Justin, Malakhov, Alexey, Malespin, Charles, Malin, Michael, Mangold, Nicolas, Manhes, Gérard, Manning, Heidi, Marchand, Geneviève, Marín Jiménez, Mercedes, Martín García, César, Martin, Dave, Martin, Mildred, Martínez-Frías, Jesús, Martín-Soler, Javier, Martín-Torres, F Javier, Mauchien, Patrick, Maurice, Sylvestre, McAdam, Amy, McCartney, Elaina, McConnochie, Timothy, McCullough, Emily, McEwan, Ian, McKay, Christopher, McLennan, Scott, McNair, Sean, Melikechi, Noureddine, Meslin, Pierre-Yves, Meyer, Michael, Mezzacappa, Alissa, Miller, Hayden, Miller, Kristen, Milliken, Ralph, Ming, Douglas, Minitti, Michelle, Mischna, Michael, Mitrofanov, Igor, Moersch, Jeff, Mokrousov, Maxim, Molina Jurado, Antonio, Moores, John, Mora-Sotomayor, Luis, Morookian, John Michael, Morris, Richard, Morrison, Shaunna, Mueller-Mellin, Reinhold, Muller, Jan-Peter, Muñoz Caro, Guillermo, Nachon, Marion, Navarro López, Sara, Navarro-González, Rafael, Nealson, Kenneth, Nefian, Ara, Nelson, Tony, Newcombe, Megan, Newman, Claire, Newsom, Horton, Nikiforov, Sergey, Nixon, Brian, Noe Dobrea, Eldar, Nolan, Thomas, Oehler, Dorothy, Ollila, Ann, Olson, Timothy, de Pablo Hernández, Miguel Ángel, Paillet, Alexis, Pallier, Etienne, Palucis, Marisa, Parker, Timothy, Parot, Yann, Patel, Kiran, Paton, Mark, Paulsen, Gale, Pavlov, Alex, Pavri, Betina, Peinado-González, Verónica, Peret, Laurent, Perez, Rene, Perrett, Glynis, Peterson, Joe, Pilorget, Cedric, Pinet, Patrick, Pla-García, Jorge, Plante, Ianik, Poitrasson, Franck, Polkko, Jouni, Popa, Radu, Posiolova, Liliya, Posner, Arik, Pradler, Irina, Prats, Benito, Prokhorov, Vasily, Purdy, Sharon Wilson, Raaen, Eric, Radziemski, Leon, Rafkin, Scot, Ramos, Miguel, Rampe, Elizabeth, Raulin, François, Ravine, Michael, Reitz, Günther, Rennó, Nilton, Rice, Melissa, Richardson, Mark, Robert, François, Robertson, Kevin, Rodriguez Manfredi, José Antonio, Romeral-Planelló, Julio J, Rowland, Scott, Rubin, David, Saccoccio, Muriel, Salamon, Andrew, Sandoval, Jennifer, Sanin, Anton, Sans Fuentes, Sara Alejandra, Saper, Lee, Sarrazin, Philippe, Sautter, Violaine, Savijärvi, Hannu, Schieber, Juergen, Schmidt, Mariek, Schmidt, Walter, Scholes, Daniel, Schoppers, Marcel, Schröder, Susanne, Schwenzer, Susanne, Sebastian Martinez, Eduardo, Sengstacken, Aaron, Shterts, Ruslan, Siebach, Kirsten, Siili, Tero, Simmonds, Jeff, Sirven, Jean-Baptiste, Slavney, Susie, Sletten, Ronald, Smith, Michael, Sobrón Sánchez, Pablo, Spanovich, Nicole, Spray, John, Squyres, Steven, Stack, Katie, Stalport, Fabien, Stein, Thomas, Stewart, Noel, Stipp, Susan Louise Svane, Stoiber, Kevin, Stolper, Ed, Sucharski, Bob, Sullivan, Rob, Summons, Roger, Sumner, Dawn, Sun, Vivian, Supulver, Kimberley, Sutter, Brad, Szopa, Cyril, Tan, Florence, Tate, Christopher, Teinturier, Samuel, ten Kate, Inge, Thomas, Peter, Thompson, Lucy, Tokar, Robert, Toplis, Mike, Torres Redondo, Josefina, Trainer, Melissa, Treiman, Allan, Tretyakov, Vladislav, Urqui-O'Callaghan, Roser, Van Beek, Jason, Van Beek, Tessa, VanBommel, Scott, Vaniman, David, Varenikov, Alexey, Vasavada, Ashwin, Vasconcelos, Paulo, Vicenzi, Edward, Vostrukhin, Andrey, Voytek, Mary, Wadhwa, Meenakshi, Ward, Jennifer, Weigle, Eddie, Wellington, Danika, Westall, Frances, Wiens, Roger Craig, Wilhelm, Mary Beth, Williams, Amy, Williams, Joshua, Williams, Rebecca, Williams, Richard B, Wilson, Mike, Wimmer-Schweingruber, Robert, Wolff, Mike, Wong, Mike, Wray, James, Wu, Megan, Yana, Charles, Yen, Albert, Yingst, Aileen, Zeitlin, Cary, Zimdar, Robert, and Zorzano Mier, María-Paz

Subjects
isotope ratios, MSL-Radiation, Mars
Published
2013

6. There Was an Odd Princess Who Swallowed a Pea

Author

Ward, Jennifer, Calderon, Lee, Ward, Jennifer, and Calderon, Lee

Subjects
Children's songs, English--England--Texts, Folk songs, English--England--Texts, Songs, Folk songs, Nonsense verses
Abstract

'A wacky fairy tale–inspired version of the popular song, “There Was an Old Lady Who Swallowed a Fly”'

Published
2011

7. e-Science and data support services: a survey of ARL members

Author

Soehner, Catherine, Steeves, Catherine, and Ward, Jennifer

Abstract

After working for several years to promote research library support for e-science and e-research, the Association of Research Libraries E-science Working Group surveyed member libraries in the Fall of 2009 to gather data on the state of engagement with e-science issues. ARL members include the largest research libraries in the US and Canada and collectively support a substantial proportion of the North American research enterprise. The survey provides a current snapshot of data curation and e-science support activities, documenting a range of approaches and strategies evolving at research institutions and among research libraries. The research libraries reported on widespread planning and development at their institutions and described a variety of models for service provision and infrastructure development. Library engagement in data curation was also common. Respondents provided information on library services, organizational structures, staffing patterns and staff development, and involvement in research grants, along with perspectives on pressure points for service development.

Published
2010

8. Origins And Development Of Forensic Medicine And Forensic Science In England, 1823-1946

Author

Ward, Jennifer

Subjects
ComputingMilieux_COMPUTERSANDSOCIETY, ComputingMilieux_LEGALASPECTSOFCOMPUTING
Abstract

This study traces the development of forensic medicine, forensic science and police science from their roots in nineteenth-century England and shows that the main factors which make up the present-day disciplines were in place well before the First World War. The elite practice of forensic medicine had evolved into the laboratory-based sciences of special pathology and Home Office toxicological analysis by the 1900s and it is shown that in creating forensic science in the 1930s on this elite medical model as an aid to police investigations, other science and medicine in court, particularly in the civil courts, were excluded from the meaning of the new term 'forensic science' and perhaps also from the far older and wider 'forensic medicine'. There is confusion in the public mind as to the difference between forensic medicine and forensic science, or whether one is included in the other. By outlining the history of the separate specialities the meanings of the terms is clarified, not only for the present day, but at each earlier stage. Forensic medicine's role working for the state in criminal cases has always been badly funded, as the discipline has been unable to compete for public funds against more pressing needs. poor teaching and little or no original research. The creation of the Forensic Science Service was an attempt in part to salvage forensic medicine and to put it finally on an institutionalised footing, but this failed, and as the period of review closed in 1946 forensic medicine was still struggling for survival. Forensic science too looked set for failure as the government had made no provision for research or for training the new 'forensic scientists'.

Published
1993
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results