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Your search keyword '"Wilson, Francis P."' showing total 108 results
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108 results on '"Wilson, Francis P."'

1. An atlas of healthy and injured cell states and niches in the human kidney.

Author

Lake, Blue, Menon, Rajasree, Winfree, Seth, Hu, Qiwen, Ferreira, Ricardo, Kalhor, Kian, Barwinska, Daria, Otto, Edgar, Ferkowicz, Michael, Diep, Dinh, Plongthongkum, Nongluk, Knoten, Amanda, Urata, Sarah, Mariani, Laura, Naik, Abhijit, Eddy, Sean, Zhang, Bo, Wu, Yan, Salamon, Diane, Williams, James, Wang, Xin, Balderrama, Karol, Hoover, Paul, Murray, Evan, Marshall, Jamie, Noel, Teia, Vijayan, Anitha, Hartman, Austin, Chen, Fei, Waikar, Sushrut, Rosas, Sylvia, Wilson, Francis, Palevsky, Paul, Kiryluk, Krzysztof, Sedor, John, Toto, Robert, Parikh, Chirag, Kim, Eric, Satija, Rahul, Greka, Anna, Macosko, Evan, Kharchenko, Peter, Gaut, Joseph, Hodgin, Jeffrey, Eadon, Michael, Dagher, Pierre, El-Achkar, Tarek, Kretzler, Matthias, Jain, Sanjay, and Zhang, Kun

Subjects
Humans, Cell Nucleus, Gene Expression Profiling, Kidney, Kidney Diseases, Transcriptome, Single-Cell Analysis, Case-Control Studies, Imaging, Three-Dimensional
Abstract

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Published
2023

3. Precision Medicine in Nephrology: An Integrative Framework of Multidimensional Data in the Kidney Precision Medicine Project

Author

Lake, Blue, Zhang, Kun, Lecker, Stewart, Morales, Alexander, Bogen, Steve, Amodu, Afolarin A., Beck, Laurence, Henderson, Joel, Ilori, Titlayo, Maikhor, Shana, Onul, Ingrid, Schmidt, Insa, Verma, Ashish, Waikar, Sushrut, Yadati, Pranav, Yu, Guanghao, Colona, Mia R., McMahon, Gearoid, Hacohen, Nir, Greka, Anna, Hoover, Paul J., Marshall, Jamie L., Aulisio, Mark, Bush, William, Chen, Yijiang, Crawford, Dana, Madabhushi, Anant, Viswanathan, Vidya S., Bush, Lakeshia, Cooperman, Leslie, Gadegbeku, Crystal, Herlitz, Leal, Jolly, Stacey, Nguyen, Jane, O’Malley, Charles, O’Toole, John, Palmer, Ellen, Poggio, Emilio, Spates-Harden, Kassandra, Sedor, John, Sendrey, Dianna, Taliercio, Jonathan, Appelbaum, Paul, Balderes, Olivia, Barasch, Jonathan, Berroue, Cecilia, Bomback, Andrew, Canetta, Pietro A., D’Agati, Vivette, Kiryluk, Krzysztof, Kudose, Satoru, Mehl, Karla, Sabatello, Maya, Shang, Ning, de Pinho Gonçalves, Joana, Lardenoije, Roy, Migas, Lukasz, Van de Plas, Raf, Rennke, Helmut, Azeloglu, Evren, Campbell, Kirk, Coca, Steven, He, Cijang, He, John, Iyengar, Srinivas Ravi, Lefferts, Seanee, Nadkarni, Girish, Patel, Marissa, Tokita, Joji, Ward, Stephen, Xiong, Yuguang, Verdoes, Abraham, Sabo, Angela, Barwinska, Daria, Gisch, Debora Lidia, Williams, James, Kelly, Katherine, Dunn, Kenneth, Asghari, Mahla, Eadon, Michael, Ferkowicz, Michael, Dagher, Pierre, Ferreira, Ricardo Melo, Winfree, Seth, Bledsoe, Sharon, Wofford, Stephanie, El-Achkar, Tarek, Sutton, Timothy, Bowen, William, Cheng, Ying-Hua, Slade, Austen, Record, Elizabeth, Cheng, Yinghua, Borner, Katy, Herr, Bruce, Jain, Yashvardhan, Quardokus, Ellen, Atta, Mohamed, Bernard, Lauren, Menez, Steven, Parikh, Chirag, Corona Villalobos, Celia Pamela, Wang, Ashley, Wen, Yumeng, Xu, Alan, Chen, Sarah, Donohoe, Isabel, Johansen, Camille, Rosas, Sylvia, Sun, Jennifer, Ardayfio, Joseph, Bebiak, Jack, Campbell, Taneisha, Fox, Monica, Knight, Richard, Koewler, Robert, Pinkeney, Roy, Saul, John, Shpigel, Anna, Prasad, Pottumarthi, Madhavan, Sethu M., Parikh, Samir, Rovin, Brad, Shapiro, John P., Anderton, Christopher, Lukowski, Jessica, Pasa-Tolic, Ljiljana, Velickovic, Dusan, Oliver, George, Mao, Weiguang, Sealfon, Rachel, Troyanskaya, Olga, Pollack, Ari, Goltsev, Yury, Ginley, Brandon, Anjani, Kavya, Laszik, Zoltan G., Mukatash, Tariq, Nolan, Garry, Beyda, David, Bracamonte, Erika, Brosius, Frank, Campos, Baltazar, Marquez, Nicole, Mendoza, Katherine, Scott, Raymond, Thajudeen, Bijin, Tsosie, Rebecca, Woodhead, Gregory, Saunders, Milda, Alloway, Rita R., Lee, Paul J., Rike, Adele, Shi, Tiffany, Woodle, E. Steve, Bjornstad, Petter, Hsieh, Elena, Kendrick, Jessica, Pyle, Laura, Thurman, Joshua, Vinovskis, Carissa, Wrobel, Julia, Lucarelli, Nicholas, Sarder, Pinaki, Bui, James, Carmona-Powell; Ron Gaba, Eunice, Kelly, Tanika, Lash, James, Meza, Natalie, Redmond, Devona, Renteria, Amada, Ricardo, Ana, Setty, Suman, Srivastava, Anand, Alakwaa, Fadhl, Ascani, Heather, Balis, Ul, Bitzer, Markus, Blanc, Victoria, Bonevich, Nikki, Conser, Ninive, Demeke, Dawit, Dull, Rachel, Eddy, Sean, Frey, Renee, Hartman, John, He, Yongqun Oliver, Hodgin, Jeffrey, Kretzler, Matthias, Lienczewski, Chrysta, Luo, Jinghui, Mariani, Laura, McCown, Phillip, Menon, Rajasree, Nair, Viji, Otto, Edgar, Reamy, Rebecca, Rose, Michael, Schaub, Jennifer, Steck, Becky, Wright, Zachary, Coleman, Alyson, Henderson-Brown; Jerica Berge, Dorisann, Caramori, Maria Luiza, Adeyi, Oyedele, Nachman, Patrick, Safadi, Sami, Flanagan, Siobhan, Ma, Sisi, Klett, Susan, Wolf, Susan, Harindhanavudhi, Tasma, Rao, Via, Bream, Peter, Froment, Anne, Kelley, Sara, Mottl, Amy, Chaudhury; Evan Zeitler, Prabir Roy, Bender, Filitsa, Elder, Michele, Gilliam, Matthew, Hall, Daniel E., Kellum, John A., Murugan, Raghavan, Palevsky, Paul, Rosengart, Matthew, Tan, Roderick, Tublin, Mitchell, Winters, James, Bansal, Shweta, Montellano, Richard, Pamreddy, Annapurna, Sharma, Kumar, Venkatachalam, Manjeri, Ye, Hongping, Zhang, Guanshi, Basit, Mujeeb, Cai, Qi, Hendricks, Allen, Hedayati, Susan, Kermani, Asra, Lee, Simon C., Ma, Shihong, Miller, Richard Tyler, Moe, Orson W., Park, Harold, Patel, Jiten, Pillai, Anil, Sambandam, Kamalanathan, Torrealba, Jose, Toto, Robert D., Vazquez, Miguel, Wang, Nancy, Wen, Natasha, Zhang, Dianbo, Alpers, Charles, Berglund, Ashley, Berry, Brooke, Blank, Kristina, Brown, Keith, Carson, Jonas, Daniel, Stephen, de Boer, Ian H., Dighe, Ashveena L., Dowd, Frederick, Grewenow, Stephanie M., Himmelfarb, Jonathan, Hoofnagle, Andrew, Jefferson, Nichole, Larson, Brandon, Limonte, Christine, McClelland, Robyn, Mooney, Sean, Nam, Yunbi, Park, Christopher, Phuong, Jimmy, Rezaei, Kasra, Roberts, Glenda, Sarkisova, Natalya, Shankland, Stuart, Snyder, Jaime, Stutzke, Christy, Tuttle, Katherine, Wangperawong, Artit, Wilcox, Adam, Williams, Kayleen, Young, Bessie, Allen, Jamie, Caprioli, Richard M., de Caestecker, Mark, Djambazova, Katerina, Dufresne, Martin, Farrow, Melissa, Fogo, Agnes, Sharman, Kavya, Spraggins, Jeffrey, Basta, Jeannine, Conlon, Kristine, Diettman, Sabine M., Gaut, Joseph, Kaushal, Madhurima, Jain, Sanjay, Knoten, Amanda, Minor, Brittany, Nwanne, Gerald, Vijayan, Anitha, Zhang, Bo, Arora, Tanima, Cantley, Lloyd, Victoria Castro, Angela M., Kakade, Vijayakumar, Moeckel, Gilbert, Moledina, Dennis, Shaw, Melissa, Wilson, Francis P., El-Achkar, Tarek M., and Eadon, Michael T.

Published
2024
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4. Participant Experience with Protocol Research Kidney Biopsies in the Kidney Precision Medicine Project

Author

Victoria-Castro, Angela M., Corona-Villalobos, Celia P., Xu, Alan Y., Onul, Ingrid, Huynh, Courtney, Chen, Sarah W., Ugwuowo, Ugochukwu, Sarkisova, Natalya, Dighe, Ashveena L., Blank, Kristina N., Blanc, Victoria M., Rose, Michael P., Himmelfarb, Jonathan, de Boer, Ian H., Tuttle, Katherine R., Roberts, Glenda V., Alexandrov, Theodore, Alloway, Rita R., Alpers, Charles E., Amodu, Afolarin A., Anderton, Christopher R., Anjani, Kavya, Appelbaum, Paul, Ardayfio, Joseph, Arora, Tanima, Ascani, Heather, El-Achkar, Tarek M., Aulisio, Mark, Azeloglu, Evren U., Balderes, Olivia, Balis, Ulysses G.J., Bansal, Shweta, Barasch, Jonathan M., Bansal, Shweta, Barkell, Alex, Barwinska, Daria, Basit, Mujeeb, Basta, Jeanine, Bebiak, Jack, Beck, Laurence H., Bender, Filitsa, Berglund, Ashley, Bernard, Lauren, Berrouet, Cecilia, Berry, Brooke, Bjornstad, Petter M., Blanc, Victoria M., Blank, Kristina N., Bledsoe, Sharon, Boada, Patrick, Bogen, Steve, Bomback, Andrew S., Bonevich, Nikole, Borner, Katy, Brown, Keith, Bueckle, Andreas, Burg, Ashley R., Burgess, Adam, Bush, Lakeshia, Bush, William S., Campbell, Catherine E., Campbell, Taneisha, Canetta, Pietro A., Cantley, Lloyd G., Caprioli, Richard M., Carson, Jonas, Chen, Sarah, Chen, Yijiang M., Cheng, Yinghua, Cimino, Jim, Colona, Mia R., Conser, Ninive C., Cooperman, Leslie, Crawford, Dana C., DʼAgati, Vivette D., Dagher, Pierre C., Daniel, Stephen, Daratha, Kenn, de Boer, Ian H., Diettman, Sabine M., Dighe, Ashveena L., Donohoe, Isabel, Dowd, Frederick, Dunn, Kenneth W., Eadon, Michael T., Eddy, Sean, Elder, Michele M., Ferkowicz, Michael J., Frey, Renee, Gadegbeku, Crystal A., Gaut, Joseph P., Gilliam, Matthew, Ginley, Brandon, Gisch, Debora, Goltsev, Yury, Gonzalez-Vicente, Agustin, Greka, Anna, Grewenow, Stephanie M., Hacohen, Nir, Hall, Daniel E., Hansen, Jens, Hayashi, Lynda, He, Cijang, He, Yougqun, Hedayati, S. Susan, Henderson, Joel M., Hendricks, Allen H., Herlitz, Leal, Herr, Bruce W., Himmelfarb, Jonathan, Hodgin, Jeffrey B., Hoofnagle, Andrew N., Hoover, Paul J., Ilori, Titlayo, Iyengar, Ravi, Jain, Sanjay, Jain, Yashvardhan, Janowczyk, Andrew, Jefferson, Nichole, Johansen, Camille, Jolly, Stacey, Kakade, Vijaykumar R., Kellum, John A., Kelly, Katherine J., Kermani, Asra, Kiryluk, Krzysztof, Knight, Richard, Koewler, Robert, Kretzler, Matthias, Kudose, Satoru, Lake, Blue B., Larson, Brandon, Laszik, Zoltan G., Lecker, Stewart H., Lee, Paul J., Lee, Simon C., Lienczewski, Chrysta, Limonte, Christine, Lu, Christopher Y., Lucarelli, Nicholas, Lukowski, Jessica, Luo, Jinghui, Lutnick, Brendon, Ma, Shihong, Madabhushi, Anant, Madhavan, Sethu M., Maikhor, Shana, Mariani, Laura H., Marshall, Jamie L., McClelland, Robyn L., McMahon, Gearoid M., Mehl, Karla, Ferreira, Ricardo Melo, Menez, Steven, Menon, Rajasree, Miller, R. Tyler, Moe, Orson W., Moledina, Dennis, Montellano, Richard, Mooney, Sean D., Morales, Martha Catalina, Mukatash, Tariq, Murugan, Raghavan, Nam, Yunbi, Nguyen, Jane, Nolan, Garry, Oʼtoole, John, Oliver, George (Holt), Onul, Ingrid, Otto, Edgar, Palevsky, Paul M., Palmer, Ellen, Pamreddy, Annapurna, Parikh, Chirag R., Parikh, Samir, Park, Christopher, Park, Harold, Pasa-Tolic, Ljiljana, Patel, Jiten, Patterson, Nathan, Phuong, Jim, Pillai, Anil, Pinkeney, Roy, Poggio, Emilio, Pollack, Ari, Prasad, Pottumarthi, Pyle, Laura, Quardokus, Ellen M., Randhawa, Parmjeet, Rauchman, Michael I., Record, Elizabeth, Rennke, Helmut, Rezaei, Kasra, Rike, Adele, Rivera, Marcelino, Roberts, Glenda V., Rosas, Sylvia E., Rosenberg, Avi, Rosengart, Matthew, Rovin, Brad, Roy, Neil, Sabatello, Maya, Sambandam, Kamalanathan, Sarder, Pinaki, Sarkisova, Natalya, Sarwal, Minnie, Saul, John, Schaub, Jennifer, Schmidt, Insa, Sealfon, Rachel, Sedor, John, Sendrey, Dianna, Shang, Ning, Shankland, Stuart, Shapiro, John P., Sharma, Kumar, Sharman, Kavya, Shaw, Melissa M., Shi, Tiffany, Shpigel, Anna, Sigdel, Tara, Slade, Austen, Snyder, Jamie, Spates-Harden, Kassandra, Spraggins, Jeffrey M., Srivastava, Anand, Steck, Becky, Stillman, Isaac, Stutzke, Christy, Su, Jing, Sun, Jennifer, Sutton, Timothy A., Taliercio, Jonathan, Tan, Roderick, Torrealba, Jose, Toto, Robert D., Troyanskaya, Olga, Tublin, Mitchell, Tuttle, Katherine R., Ugwuowo, Ugochukwu, Valerius, M. Todd, Van de Plas, Raf, Varela, German, Vazquez, Miguel, Velickovic, Dusan, Venkatachalam, Manjeri, Verma, Ashish, Victoria-Castro, Angela M., Vijayan, Anitha, Corona-Villalobos, Celia P., Vinovskis, Carissa, Viswanathan, Vidya S., Vita, Tina, Waikar, Sushrut, Wang, Ashley, Wang, Ruikang, Wang, Nancy, Weins, Astrid, Wen, Natasha, Wen, Yumeng, Wilcox, Adam, Williams, James C., Jr., Kayleen Williams, Williams, Mark, Wilson, Francis P., Winfree, Seth, Winters, James, Wofford, Stephanie, Wong, Aaron, Woodle, E. Steve, Xiong, Yuguang, Xu, Alan, Yadati, Pranav, Ye, Hongping, Yu, Guanghao, Zhang, Dianbo, Zhang, Guanshi, and Zhang, Kun

Published
2024
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5. Rationale and design of the Kidney Precision Medicine Project

Author

de Boer, Ian H, Alpers, Charles E, Azeloglu, Evren U, Balis, Ulysses GJ, Barasch, Jonathan M, Barisoni, Laura, Blank, Kristina N, Bomback, Andrew S, Brown, Keith, Dagher, Pierre C, Dighe, Ashveena L, Eadon, Michael T, El-Achkar, Tarek M, Gaut, Joseph P, Hacohen, Nir, He, Yongqun, Hodgin, Jeffrey B, Jain, Sanjay, Kellum, John A, Kiryluk, Krzysztof, Knight, Richard, Laszik, Zoltan G, Lienczewski, Chrysta, Mariani, Laura H, McClelland, Robyn L, Menez, Steven, Moledina, Dennis G, Mooney, Sean D, O’Toole, John F, Palevsky, Paul M, Parikh, Chirag R, Poggio, Emilio D, Rosas, Sylvia E, Rosengart, Matthew R, Sarwal, Minnie M, Schaub, Jennifer A, Sedor, John R, Sharma, Kumar, Steck, Becky, Toto, Robert D, Troyanskaya, Olga G, Tuttle, Katherine R, Vazquez, Miguel A, Waikar, Sushrut S, Williams, Kayleen, Wilson, Francis Perry, Zhang, Kun, Iyengar, Ravi, Kretzler, Matthias, Himmelfarb, Jonathan, Project, Kidney Precision Medicine, Lecker, Stewart, Stillman, Isaac, Waikar, Sushrut, Mcmahon, Gearoid, Weins, Astrid, Short, Samuel, Hoover, Paul, Aulisio, Mark, Cooperman, Leslie, Herlitz, Leal, O’Toole, John, Poggio, Emilio, Sedor, John, Jolly, Stacey, Appelbaum, Paul, Balderes, Olivia, Barasch, Jonathan, Bomback, Andrew, Canetta, Pietro A, d’Agati, Vivette D, Kudose, Satoru, Mehl, Karla, Radhakrishnan, Jai, Weng, Chenhua, Alexandrov, Theodore, Ashkar, Tarek, Barwinska, Daria, Dagher, Pierre, Dunn, Kenneth, Eadon, Michael, Ferkowicz, Michael, Kelly, Katherine, Sutton, Timothy, Winfree, Seth, Parikh, Chirag, Rosenberg, Avi, Villalobos, Pam, Malik, Rubab, Fine, Derek, Atta, Mohammed, Trujillo, Jose Manuel Monroy, Slack, Alison, Rosas, Sylvia, and Williams, Mark

Subjects
Clinical Research, Transplantation, Kidney Disease, Prevention, Renal and urogenital, Good Health and Well Being, Acute Kidney Injury, Adult, Humans, Kidney, Precision Medicine, Prospective Studies, Proteomics, Renal Insufficiency, Chronic, acute kidney injury, chronic kidney disease, diabetes, hypertension, precision medicine, Kidney Precision Medicine Project, Clinical Sciences, Urology & Nephrology
Abstract

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

Published
2021

8. Effect on Survival of Concurrent Hemoconcentration and Increase in Creatinine During Treatment of Acute Decompensated Heart Failure

Author

Griffin, Matthew, Rao, Veena S, Fleming, James, Raghavendra, Parinita, Turner, Jeffrey, Mahoney, Devin, Wettersten, Nicholas, Maisel, Alan, Ivey-Miranda, Juan B, Inker, Lesley, Tang, Wai Hong Wilson, Wilson, Francis Perry, and Testani, Jeffrey M

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Cardiovascular, Clinical Research, Acute Disease, Aged, Biomarkers, Creatinine, Diuretics, Female, Heart Failure, Hospital Mortality, Humans, Male, Prognosis, Retrospective Studies, Survival Rate, United States, Water-Electrolyte Imbalance, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

Hemoconcentration during the treatment of acute decompensated heart failure is a surrogate for plasma volume reduction and is associated with improved survival, but most definitions only allow for hemoconcentration to be determined retrospectively. An increase in serum creatinine can also be a marker of aggressive decongestion, but in isolation is not specific. Our objective was to determine if combined hemoconcentration and worsening creatinine could better identify patients that were aggressively treated and, as such, may have improved postdischarge outcomes. A total of 4,181 patients hospitalized with acute decompensated heart failure were evaluated. Those who experienced both hemoconcentration and worsening creatinine at any point had a profile consistent with aggressive in-hospital treatment and longer length of stay (p

Published
2019

9. Group analysis identifies differentially elevated biomarkers with distinct outcomes for advanced acute kidney injury in cardiac surgery

Author

Lin, Haiqun, Scherzer, Rebecca, Philbrook, Heather Thiessen, Coca, Steven G, Wilson, Francis Perry, Garg, Amit X, Shlipak, Michael G, and Parikh, Chirag R

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Clinical Research, Kidney Disease, Patient Safety, Cardiovascular, Renal and urogenital, Good Health and Well Being, Acute Kidney Injury, Aged, Aged, 80 and over, Biomarkers, Cardiac Surgical Procedures, Female, Humans, Male, Middle Aged, Postoperative Complications, advanced AKI, biomarkers of AKI, group-based analysis, Medicinal and Biomolecular Chemistry, Medical Biochemistry and Metabolomics, Oncology & Carcinogenesis, Clinical sciences, Medical biochemistry and metabolomics, Medicinal and biomolecular chemistry
Abstract

AIM:To investigate early postoperative biomarkers for risk discrimination of advanced acute kidney injury (AKI). MATERIALS & METHODS:Postoperative plasma biomarkers including NGAL, h-FABP, CK-MB, hsTNT, NT-proBNP, IL-6, IL-10 and VEGF were analyzed using group-based method among 426 patients with AKI after cardiac surgery. RESULTS:Six patient groups with distinct biomarker patterns were identified. Individual biomarker displayed significant difference across the groups. The groups showed better discrimination for advanced AKI than any single biomarker either with or without adjusting for clinical variables. Average concentration of a single biomarker within each group, mortality and risk of a secondary outcome all demonstrated an approximately U-shaped relationship with proportion of advanced AKI within each group. CONCLUSION:The group-based analysis revealed that the order of the patient groups with an increasing likelihood of advanced AKI had a nonlinear relationship with average concentration of an individual biomarker, mortality and risk of other outcomes.

Published
2017

10. Cadherin-11, Sparc-related modular calcium binding protein-2, and Pigment epithelium-derived factor are promising non-invasive biomarkers of kidney fibrosis

Author

Knight, Richard, Lecker, Stewart H., Stillman, Isaac, Bogen, Steve, Amodu, Afolarin A., Ilori, Titlayo, Maikhor, Shana, Schmidt, Insa M., Beck, Laurence H., Henderson, Joel M., Onul, Ingrid, Verma, Ashish, McMahon, Gearoid M., Valerius, M. Todd, Waikar, Sushrut, Weins, Astrid, Colona, Mia R., Greka, Anna, Hacohen, Nir, Hoover, Paul J., Marshall, Jamie L., Aulisio, Mark, Chen, Yijiang M., Janowczyk, Andrew, Jayapandian, Catherine, Viswanathan, Vidya S., Bush, William S., Crawford, Dana C., Madabhushi, Anant, Bush, Lakeshia, Cooperman, Leslie, Gonzalez-Vicente, Agustin, Herlitz, Leal, Jolly, Stacey, Nguyen, Jane, O’toole, John, Palmer, Ellen, Poggio, Emilio, Sedor, John, Sendrey, Dianna, Spates-Harden, Kassandra, Taliercio, Jonathan, Bjornstad, Petter M., Pyle, Laura, Vinovskis, Carissa, Appelbaum, Paul, Balderes, Olivia, Barasch, Jonathan M., Bomback, Andrew S., Canetta, Pietro A., D’Agati, Vivette D., Kiryluk, Krzysztof, Kudose, Satoru, Mehl, Karla, Shang, Ning, Bansal, Shweta, Alexandrov, Theodore, Rennke, Helmut, El-Achkar, Tarek M., Barwinska, Daria, Bledso, Sharon, Borner, Katy, Bueckle, Andreas, Cheng, Yinghua, Dagher, Pierre C., Dunn, Kenneth W., Eadon, Michael T., Ferkowicz, Michael J., Herr, Bruce W., Kelly, Katherine J., Ferreira, Ricardo Melo, Quardokus, Ellen M., Record, Elizabeth, Rivera, Marcelino, Su, Jing, Sutton, Timothy A., Williams, James C., Jr., Winfree, Seth, Jain, Yashvardhan, Menez, Steven, Parikh, Chirag R., Rosenberg, Avi, Corona-Villalobos, Celia P., Wen, Yumeng, Johansen, Camille, Rosas, Sylvia E., Roy, Neil, Sun, Jennifer, Williams, Mark, Azeloglu, Evren U., Hansen, Jens, He, Cijang, Iyengar, Ravi, Xiong, Yuguang, Prasad, Pottumarthi, Srivastava, Anand, Madhavan, Sethu M., Parikh, Samir, Rovin, Brad, Shapiro, John P., Anderton, Christopher R., Lukowski, Jessica, Pasa-Tolic, Ljiljana, Velickovic, Dusan, Oliver, George (Holt), Ardayfio, Joseph, Bebiak, Jack, Brown, Keith, Campbell, Taneisha, Campbell, Catherine E., Hayashi, Lynda, Jefferson, Nichole, Roberts, Glenda V., Saul, John, Shpigel, Anna, Stutzke, Christy, Koewler, Robert, Pinkeney, Roy, Sealfon, Rachel, Troyanskaya, Olga, Wong, Aaron, Tuttle, Katherine R., Pollack, Ari, Goltsev, Yury, Ginley, Brandon, Lucarelli, Nicholas, Lutnick, Brendon, Sarder, Pinaki, Lake, Blue B., Zhang, Kun, Boada, Patrick, Laszik, Zoltan G., Nolan, Garry, Anjani, Kavya, Sarwal, Minnie, Mukatash, Tariq, Sigdel, Tara, Alloway, Rita R., Burg, Ashley R., Lee, Paul J., Rike, Adele, Shi, Tiffany, Woodle, E. Steve, Ascani, Heather, Balis, Ulysses G.J., Blanc, Victoria M., Conser, Ninive C., Eddy, Sean, Frey, Renee, He, Yougqun, Hodgin, Jeffrey B., Kretzler, Matthias, Lienczewski, Chrysta, Luo, Jinghui, Mariani, Laura H., Menon, Rajasree, Otto, Edgar, Schaub, Jennifer, Steck, Becky, Elder, Michele M., Gilliam, Matthew, Hall, Daniel E., Murugan, Raghavan, Palevsky, Paul M., Randhawa, Parmjeet, Rosengart, Matthew, Tublin, Mitchell, Vita, Tina, Winters, James, Kellum, John A., Alpers, Charles E., Berglund, Ashley, Berry, Brooke, Blank, Kristina N., Carson, Jonas, Daniel, Stephen, De Boer, Ian H., Dighe, Ashveena L., Dowd, Frederick, Grewenow, Stephanie M., Himmelfarb, Jonathan, Hoofnagle, Andrew N., Limonte, Christine, McClelland, Robyn L., Mooney, Sean D., Rezaei, Kasra, Shankland, Stuart, Snyder, Jamie, Wang, Ruikang, Wilcox, Adam, Williams, Kayleen, Park, Christopher, Montellano, Richard, Pamreddy, Annapurna, Sharma, Kumar, Venkatachalam, Manjeri, Ye, Hongping, Zhang, Guanshi, Basit, Mujeeb, Hedayati, S. Susan, Kermani, Asra, Lee, Simon C., Lu, Christopher Y., Miller, R. Tyler, Moe, Orson W., Patel, Jiten, Pillai, Anil, Sambandam, Kamalanathan, Torrealba, Jose, Toto, Robert D., Vazquez, Miguel, Wang, Nancy, Wen, Natasha, Zhang, Dianbo, Park, Harold, Caprioli, Richard M., Patterson, Nathan, Sharman, Kavya, Spraggins, Jeffrey M., Van de Plas, Raf, Basta, Jeanine, Diettman, Sabine M., Gaut, Joseph P., Jain, Sanjay, Rauchman, Michael I., Vijayan, Anitha, Cantley, Lloyd G., Kakade, Vijaykumar R., Moledina, Dennis, Shaw, Melissa M., Ugwuowo, Ugochukwu, Wilson, Francis P., Arora, Tanima, Kestenbaum, Bryan R., Alexopoulos, Leonidas G., Palsson, Ragnar, Liu, Jing, Stillman, Isaac E., Rennke, Helmut G., Vaidya, Vishal S., Wu, Haojia, Humphreys, Benjamin D., and Waikar, Sushrut S.

Published
2021
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14. Urine biomarkers of tubular injury do not improve on the clinical model predicting chronic kidney disease progression.

Author

Hsu, Chi-Yuan, Xie, Dawei, Waikar, Sushrut S, Bonventre, Joseph V, Zhang, Xiaoming, Sabbisetti, Venkata, Mifflin, Theodore E, Coresh, Josef, Diamantidis, Clarissa J, He, Jiang, Lora, Claudia M, Miller, Edgar R, Nelson, Robert G, Ojo, Akinlolu O, Rahman, Mahboob, Schelling, Jeffrey R, Wilson, Francis P, Kimmel, Paul L, Feldman, Harold I, Vasan, Ramachandran S, Liu, Kathleen D, CRIC Study Investigators, and CKD Biomarkers Consortium

Subjects
CRIC Study Investigators, CKD Biomarkers Consortium, Kidney Tubules, Humans, Kidney Failure, Chronic, Albuminuria, Disease Progression, Creatinine, Acetylglucosaminidase, Glomerular Filtration Rate, Proportional Hazards Models, Risk Assessment, Risk Factors, Follow-Up Studies, Prospective Studies, Aged, Middle Aged, Female, Male, Fatty Acid-Binding Proteins, Renal Insufficiency, Chronic, Biomarkers, Lipocalin-2, Hepatitis A Virus Cellular Receptor 1, chronic kidney disease, microalbuminuria, proteinuria, Kidney Disease, Patient Safety, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Renal and urogenital, Good Health and Well Being, Clinical Sciences, Urology & Nephrology
Abstract

Few investigations have evaluated the incremental usefulness of tubular injury biomarkers for improved prediction of chronic kidney disease (CKD) progression. As such, we measured urinary kidney injury molecule-1, neutrophil gelatinase-associated lipocalin, N-acetyl-ß-D-glucosaminidase and liver fatty acid binding protein under highly standardized conditions among 2466 enrollees of the prospective Chronic Renal Insufficiency Cohort Study. During 9433 person-years of follow-up, there were 581 cases of CKD progression defined as incident end-stage renal disease or halving of the estimated glomerular filtration rate. Levels of the urine injury biomarkers, normalized for urine creatinine, were strongly associated with CKD progression in unadjusted Cox proportional hazard models with hazard ratios in the range of 7 to 15 comparing the highest with the lowest quintiles. However, after controlling for the serum creatinine-based estimated glomerular filtration rate and urinary albumin/creatinine ratio, none of the normalized biomarkers was independently associated with CKD progression. None of the biomarkers improved on the high (0.89) C-statistic for the base clinical model. Thus, among patients with CKD, risk prediction with a clinical model that includes the serum creatinine-based estimated glomerular filtration rate and the urinary albumin/creatinine ratio is not improved on with the addition of renal tubular injury biomarkers.

Published
2017

18. Machine Learning Prediction of Death in Critically Ill Patients With Coronavirus Disease 2019

Author

Churpek, Matthew M., Gupta, Shruti, Spicer, Alexandra B., Hayek, Salim S., Srivastava, Anand, Chan, Lili, Melamed, Michal L., Brenner, Samantha K., Radbel, Jared, Madhani-Lovely, Farah, Bhatraju, Pavan K., Bansal, Anip, Green, Adam, Goyal, Nitender, Shaefi, Shahzad, Parikh, Chirag R., Semler, Matthew W., Leaf, David E., Walther, Carol P., Anumudu, Samaya J., Arunthamakun, Justin, Kopecky, Kathleen F., Milligan, Gregory P., McCullough, Peter A., Nguyen, ThuyDuyen, Shaefi, Shahzad, Krajewski, Megan L., Shankar, Sidharth, Pannu, Ameeka, Valencia, Juan D., Waikar, Sushrut S., Kibbelaar, Zoe A., Athavale, Ambarish M., Hart, Peter, Ajiboye, Oyintayo, Itteera, Matthew, Green, Adam, Rachoin, Jean-Sebastien, Schorr, Christa A., Shea, Lisa, Edmonston, Daniel L., Mosher, Christopher L., Shehata, Alexandre M., Cohen, Zaza, Allusson, Valerie, Bambrick-Santoyo, Gabriela, Bhatti, Noor ul aain, Metha, Bijal, Williams, Aquino, Brenner, Samantha K., Walters, Patricia, Go, Ronaldo C., Rose, Keith M., Hernán, Miguel A., Zhou, Amy M., Kim, Ethan C., Lisk, Rebecca, Chan, Lili, Mathews, Kusum S., Coca, Steven G., Altman, Deena R., Saha, Aparna, Soh, Howard, Wen, Huei Hsun, Bose, Sonali, Leven, Emily, Wang, Jing G., Mosoyan, Gohar, Nadkarni, Girish N., Friedman, Allon N., Guirguis, John, Kapoor, Rajat, Meshberger, Christopher, Parikh, Chirag R., Garibaldi, Brian T., Corona-Villalobos, Celia P., Wen, Yumeng, Menez, Steven, Malik, Rubab F., Cervantes, Carmen Elena, Gautam, Samir C., Chang, Crystal, Nguyen, H. Bryant, Ahoubim, Afshin, Thomas, Leslie F., Guru, Pramod K., Bergl, Paul A., Zhou, Yan, Rodriguez, Jesus, Shah, Jatan A., Gupta, Mrigank S., Kumar, Princy N., Lazarous, Deepa G., Kassaye, Seble G., Melamed, Michal L., Johns, Tanya S., Mocerino, Ryan, Prudhvi, Kalyan, Zhu, Denzel, Levy, Rebecca V., Azzi, Yorg, Fisher, Molly, Yunes, Milagros, Sedaliu, Kaltrina, Golestaneh, Ladan, Brogan, Maureen, Thakkar, Jyotsana, Kumar, Neelja, Ross, Michael J., Chang, Michael, Raichoudhury, Ritesh, Schenck, Edward J., Cho, Soo Jung, Plataki, Maria, Alvarez-Mulett, Sergio L., Gomez-Escobar, Luis G., Pan, Di, Lee, Stefi, Krishnan, Jamuna, Whalen, William, Charytan, David, Macina, Ashley, Ross, Daniel W., Srivastava, Anand, Leidner, Alexander S., Martinez, Carlos, Kruser, Jacqueline M., Wunderink, Richard G., Hodakowski, Alexander J., Velez, Juan Carlos Q., Price-Haywood, Eboni G., Matute-Trochez, Luis A., Hasty, Anna E., Mohamed, Muner MB., Avasare, Rupali S., Zonies, David, Leaf, David E., Gupta, Shruti, Baron, Rebecca M., Sise, Meghan E., Newman, Erik T., Omar, Samah Abu, Pokharel, Kapil K., Sharma, Shreyak, Singh, Harkarandeep, Gaviria, Simon Correa, Shaukat, Tanveer, Kamal, Omer, Wang, Wei, Yang, Heather, Boateng, Jeffery O., Lee, Meghan, Strohbehn, Ian A., Li, Jiahua, Muhsin, Saif A., Mandel, Ernest I., Mueller, Ariel L., Cairl, Nicholas S., Madhani-Lovely, Farah, Rowan, Chris, Madhai-Lovely, Farah, Peev, Vasil, Reiser, Jochen, Byun, John J., Vissing, Andrew, Kapania, Esha M., Post, Zoe, Patel, Nilam P., Hermes, Joy-Marie, Sutherland, Anne K., Patrawalla, Amee, Finkel, Diana G., Danek, Barbara A., Arikapudi, Sowminya, Paer, Jeffrey M., Radbel, Jared, Puri, Sonika, Sunderram, Jag, Scharf, Matthew T., Ahmed, Ayesha, Berim, Ilya, Vatson, Jayanth, Anand, Shuchi, Levitt, Joseph E., Garcia, Pablo, Boyle, Suzanne M., Song, Rui, Zhang, Jingjing, Sharshir, Moh’d A., Rusnak, Vadym V., Bansal, Anip, Podoll, Amber S., Chonchol, Michel, Sharma, Sunita, Burnham, Ellen L., Rashidi, Arash, Hejal, Rana, Judd, Eric, Latta, Laura, Tolwani, Ashita, Albertson, Timothy E., Adams, Jason Y., Chang, Steven Y., Beutler, Rebecca M., Schulze, Carl E., Macedo, Etienne, Rhee, Harin, Liu, Kathleen D., Jotwani, Vasantha K., Koyner, Jay L., Shah, Chintan V., Jaikaransingh, Vishal, Toth-Manikowski, Stephanie M., Joo, Min J., Lash, James P., Neyra, Javier A., Chaaban, Nourhan, Iardino, Alfredo, Au, Elizabeth H., Sharma, Jill H., Anne Sosa, Marie, Taldone, Sabrina, Contreras, Gabriel, De La Zerda, David, Gershengorn, Hayley B., Hayek, Salim S., Blakely, Pennelope, Berlin, Hanna, Azam, Tariq U., Shadid, Husam, Pan, Michael, Hayer, Patrick O’, Meloche, Chelsea, Feroze, Rafey, Padalia, Kishan J., Leya, Jeff, Donnelly, John P., Admon, Andrew J., Flythe, Jennifer E., Tugman, Matthew J., Brown, Brent R., Leonberg-Yoo, Amanda K., Spiardi, Ryan C., Miano, Todd A., Roche, Meaghan S., Vasquez, Charles R., Bansal, Amar D., Ernecoff, Natalie C., Kovesdy, Csaba P., Molnar, Miklos Z., Hedayati, S. Susan, Nadamuni, Mridula V., Khan, Sadaf S., Willett, Duwayne L., Short, Samuel A.P., Renaghan, Amanda D., Bhatraju, Pavan, Malik, A. Bilal, Semler, Matthew W., Vijayan, Anitha, Mariyam Joy, Christina, Li, Tingting, Goldberg, Seth, Kao, Patricia F., Schumaker, Greg L., Goyal, Nitender, Faugno, Anthony J., Schumaker, Greg L., Hsu, Caroline M., Tariq, Asma, Meyer, Leah, Christov, Marta, Wilson, Francis P., Arora, Tanima, and Ugwuowo, Ugochukwu

Published
2021
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19. Podocyte histone deacetylase activity regulates murine and human glomerular diseases

Author

Inoue, Kazunori, Gan, Geliang, Ciarleglio, Maria, Zhang, Yan, Tian, Xuefei, Pedigo, Christopher E., Cavanaugh, Corey, Tate, Janet, Wang, Ying, Cross, Elizabeth, Groener, Marwin, Chai, Nathan, Wang, Zhen, Justice, Amy, Zhang, Zhenhai, Parikh, Chirag R., Wilson, Francis P., and Ishibe, Shuta

Subjects
Gene expression -- Research, Histones -- Research, Kidney diseases -- Genetic aspects -- Development and progression -- Research, Valproic acid, Vorinostat, Lamotrigine, Proteinuria, Genes, Messenger RNA, Levetiracetam, RNA, Criminal investigation, Digital map services, Chronic kidney failure, Health care industry
Abstract

We identified 2 genes, histone deacetylase 1 (HDAC1) and HDAC2, contributing to the pathogenesis of proteinuric kidney diseases, the leading cause of end-stage kidney disease. mRNA expression profiling from proteinuric mouse glomeruli was linked to Connectivity Map databases, identifying HDAC1 and HDAC2 with the differentially expressed gene set reversible by HDAC inhibitors. In numerous progressive glomerular disease models, treatment with valproic acid (a class I HDAC inhibitor) or SAHA (a pan-HDAC inhibitor) mitigated the degree of proteinuria and glomerulosclerosis, leading to a striking increase in survival. Podocyte HDAC1 and HDAC2 activities were increased in mice podocytopathy models, and podocyte-associated Hdacl and [Hdac2.sup.fl/fl] genetic ablation improved proteinuria and glomerulosclerosis. Podocyte early growth response 1 (EGR1) was increased in proteinuric patients and mice in an HDAC1- and HDAC2-dependent manner. Loss of EGR1 in mice reduced proteinuria and glomerulosclerosis. Longitudinal analysis of the multicenter Veterans Aging Cohort Study demonstrated a 30% reduction in mean annual loss of estimated glomerular filtration rate, and this effect was more pronounced in proteinuric patients receiving valproic acid. These results strongly suggest that inhibition of HDAC1 and HDAC2 activities may suppress the progression of human proteinuric kidney diseases through the regulation of EGR1., Introduction The kidney filtration barrier is composed of fenestrated endothelial cells, the glomerular basement membrane, and the podocytes. The podocyte is a terminally differentiated epithelial cell, which in concert with [...]

Published
2019
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22. Designing and Assessing Online Learning in English Literary Studies

Author

Colbert, Benjamin, Miles, Rosie, Wilson, Francis, and Weeks, Hilary

Abstract

This article offers an account of online experimentation and innovation that has taken place in the English department of the University of Wolverhampton from 2003 to 2005. Focusing on an introductory first-year module and two third-year modules, it explores how and to what extent a virtual learning environment (VLE) can enhance the teaching of English literary studies in higher education. Using a "blended learning" model of English teaching, in which face-to-face and online teaching are integrated, the study examines how VLEs can be incorporated into a coordinated assessment regime within individual modules, and considers the strategies for implementing VLE assessment in a staged progression across an English programme. The authors argue that online activities need to be both integrated into English courses and assessed. When balanced properly, VLE work offers no "easy option" for students but effectively complements more traditional forms of assessment in English, such as essays and exams. (Contains 3 notes and 1 table.)

Published
2007
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23. Integrated single-cell sequencing and histopathological analyses reveal diverse injury and repair responses in a participant with acute kidney injury: a clinical-molecular-pathologic correlation

Author

Knight, Richard, Lecker, Stewart H., Stillman, Isaac, Bogen, Steve, Beck, Laurence H., Waikar, Sushrut, McMahon, Gearoid M., Weins, Astrid, Colona, Mia R., Hacohen, Nir, Hoover, Paul J., Aulisio, Mark, Bush, William S., Crawford, Dana C., O'toole, John, Poggio, Emilio, Sedor, John, Cooperman, Leslie, Jolly, Stacey, Herlitz, Leal, Nguyen, Jane, Gonzalez-Vicente, Agustin, Palmer, Ellen, Sendrey, Dianna, Vinovskis, Carissa, Bjornstad, Petter M., Appelbaum, Paul, Barasch, Jonathan M., Bomback, Andrew S., D'Agati, Vivette D., Kiryluk, Krzysztof, Mehl, Karla, Canetta, Pietro A., Shang, Ning, Balderes, Olivia, Kudose, Satoru, Bansal, Shweta, Alexandrov, Theodore, Rennke, Helmut, El-Achkar, Tarek M., Cheng, Yinghua, Dagher, Pierre C., Eadon, Michael T., Dunn, Kenneth W., Kelly, Katherine J., Sutton, Timothy A., Barwinska, Daria, Ferkowicz, Michael J., Winfree, Seth, Bledsoe, Sharon, Rivera, Marcelino, Williams, James C., Jr., Ferreira, Ricardo Melo, Parikh, Chirag R., Corona-Villalobos, Celia P., Menez, Steven, Rosenberg, Avi, Rosas, Sylvia E., Roy, Neil, Williams, Mark, Azeloglu, Evren U., He, Cijang, Iyengar, Ravi, Hansen, Jens, Xiong, Yuguang, Rovin, Brad, Parikh, Samir, Shapiro, John P., Anderton, Christopher R., Pasa-Tolic, Ljiljana, Velickovic, Dusan, Lukowski, Jessica, Oliver, George, Ardayfio, Joseph, Bebiak, Jack, Brown, Keith, Campbell, Catherine E., Saul, John, Shpigel, Anna, Stutzke, Christy, Koewler, Robert, Campbell, Taneisha, Hayashi, Lynda, Jefferson, Nichole, Roberts, Glenda V., Pinkeney, Roy, Troyanskaya, Olga, Sealfon, Rachel, Tuttle, Katherine R., Goltsev, Yury, Zhang, Kun, Lake, Blue B., Laszik, Zoltan G., Nolan, Garry, Boada, Patrick, Sarwal, Minnie, Sigdel, Tara, Lee, Paul J., Alloway, Rita R., Woodle, E. Steve, Ascani, Heather, Balis, Ulysses G.J., Hodgin, Jeffrey B., Kretzler, Matthias, Lienczewski, Chrysta, Mariani, Laura H., Menon, Rajasree, Steck, Becky, He, Yougqun, Otto, Edgar, Schaub, Jennifer, Blanc, Victoria M., Eddy, Sean, Conser, Ninive C., Luo, Jinghui, Palevsky, Paul M., Rosengart, Matthew, Kellum, John A., Hall, Daniel E., Randhawa, Parmjeet, Tublin, Mitchell, Murugan, Raghavan, Elder, Michele M., Winters, James, Alpers, Charles E., Blank, Kristina N., Carson, Jonas, De Boer, Ian H., Dighe, Ashveena L., Himmelfarb, Jonathan, Mooney, Sean D., Shankland, Stuart, Williams, Kayleen, Park, Christopher, Dowd, Frederick, McClelland, Robyn L., Daniel, Stephen, Hoofnagle, Andrew N., Wilcox, Adam, Grewenow, Stephanie M., Sharma, Kumar, Venkatachalam, Manjeri, Zhang, Guanshi, Pamreddy, Annapurna, Ye, Hongping, Montellano, Richard, Toto, Robert D., Vazquez, Miguel, Lee, Simon C., Miller, R. Tyler, Moe, Orson W., Torrealba, Jose, Wang, Nancy, Kermani, Asra, Sambandam, Kamalanathan, Park, Harold, Hedayati, S. Susan, Lu, Christopher Y., Jain, Sanjay, Vijayan, Anitha, Gaut, Joseph P., Moledina, Dennis, Wilson, Francis P., Ugwuowo, Ugochukwu, Arora, Tanima, and D’Agati, Vivette D.

Published
2022
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25. Pragmatic trial of messaging to providers about treatment of acute heart failure: The PROMPT-AHF trial.

Author

Ghazi, Lama, O'Connor, Kyle, Yamamoto, Yu, Fuery, Michael, Sen, Sounok, Samsky, Marc, Riello III, Ralph J., Huang, Joanna, Olufade, Temitope, McDermott, James, Inzucchi, Silvio E., Velazquez, Eric J., Wilson, Francis Perry, Desai, Nihar R., and Ahmad, Tariq

Abstract

Acute Heart failure (AHF) is among the most frequent causes of hospitalization in the United States, contributing to substantial health care costs, morbidity, and mortality. Inpatient initiation of guideline-directed medical therapy (GDMT) is recommended for patients with heart failure with reduced ejection fraction (HFrEF) to reduce the risk of cardiovascular death or HF hospitalization. However, underutilization of GDMT prior to discharge is pervasive, representing a valuable missed opportunity to optimize evidence-based care. The PR agmatic Trial O f Messaging to P roviders about T reatment of A cute H eart F ailure tests the effectiveness of an electronic health record embedded clinical decision support system that informs providers during hospital management about indicated but not yet prescribed GDMT for eligible AHF patients with HFrEF. PR agmatic Trial O f Messaging to P roviders about T reatment of A cute H eart F ailureis an open-label, multicenter, pragmatic randomized controlled trial of 1,012 patients hospitalized with HFrEF. Eligible patients randomized to the intervention group are exposed to a tailored best practice advisory embedded within the electronic health record that alerts providers to prescribe omitted GDMT. The primary outcome is an increase in the proportion of additional GDMT medication classes prescribed at the time of discharge compared to those in the usual care arm. [ABSTRACT FROM AUTHOR]

Published
2023
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26. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study

Author

Huang, Chenxi, Murugiah, Karthik, Mahajan, Shiwani, Li, Shu-Xia, Dhruva, Sanket S., Haimovich, Julian S., Wang, Yongfei, Schulz, Wade L., Testani, Jeffrey M., Wilson, Francis P., Mena, Carlos I., Masoudi, Frederick A., Rumsfeld, John S., Spertus, John A., Mortazavi, Bobak J., and Krumholz, Harlan M.

Subjects
Machine learning -- Usage, Acute kidney failure -- Complications and side effects -- Care and treatment, Postoperative complications -- Risk factors, Cardiac patients, Cardiology, Balloon angioplasty, Biological sciences
Abstract

Background The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether models using machine learning techniques could significantly improve AKI risk prediction after PCI. Methods and findings We used the same cohort and candidate variables used to develop the current NCDR CathPCI Registry AKI model, including 947,091 patients who underwent PCI procedures between June 1, 2009, and June 30, 2011. The mean age of these patients was 64.8 years, and 32.8% were women, with a total of 69,826 (7.4%) AKI events. We replicated the current AKI model as the baseline model and compared it with a series of new models. Temporal validation was performed using data from 970,869 patients undergoing PCIs between July 1, 2016, and March 31, 2017, with a mean age of 65.7 years; 31.9% were women, and 72,954 (7.5%) had AKI events. Each model was derived by implementing one of two strategies for preprocessing candidate variables (preselecting and transforming candidate variables or using all candidate variables in their original forms), one of three variable-selection methods (stepwise backward selection, lasso regularization, or permutation-based selection), and one of two methods to model the relationship between variables and outcome (logistic regression or gradient descent boosting). The cohort was divided into different training (70%) and test (30%) sets using 100 different random splits, and the performance of the models was evaluated internally in the test sets. The best model, according to the internal evaluation, was derived by using all available candidate variables in their original form, permutation-based variable selection, and gradient descent boosting. Compared with the baseline model that uses 11 variables, the best model used 13 variables and achieved a significantly better area under the receiver operating characteristic curve (AUC) of 0.752 (95% confidence interval [CI] 0.749-0.754) versus 0.711 (95% CI 0.708-0.714), a significantly better Brier score of 0.0617 (95% CI 0.0615-0.0618) versus 0.0636 (95% CI 0.0634-0.0638), and a better calibration slope of observed versus predicted rate of 1.008 (95% CI 0.988-1.028) versus 1.036 (95% CI 1.015-1.056). The best model also had a significantly wider predictive range (25.3% versus 21.6%, p < 0.001) and was more accurate in stratifying AKI risk for patients. Evaluated on a more contemporary CathPCI cohort (July 1, 2015-March 31, 2017), the best model consistently achieved significantly better performance than the baseline model in AUC (0.785 versus 0.753), Brier score (0.0610 versus 0.0627), calibration slope (1.003 versus 1.062), and predictive range (29.4% versus 26.2%). The current study does not address implementation for risk calculation at the point of care, and potential challenges include the availability and accessibility of the predictors. Conclusions Machine learning techniques and data-driven approaches resulted in improved prediction of AKI risk after PCI. The results support the potential of these techniques for improving risk prediction models and identification of patients who may benefit from risk-mitigation strategies., Author(s): Chenxi Huang 1, Karthik Murugiah 2, Shiwani Mahajan 1, Shu-Xia Li 1, Sanket S. Dhruva 3,4, Julian S. Haimovich 5, Yongfei Wang 1, Wade L. Schulz 1,6, Jeffrey M. [...]

Published
2018
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28. Pragmatic randomized trial assessing the impact of digital health technology on quality of life in patients with heart failure: Design, rationale and implementation.

Author

Victoria‐Castro, Angela M., Martin, Melissa, Yamamoto, Yu, Ahmad, Tariq, Arora, Tanima, Calderon, Frida, Desai, Nihar, Gerber, Brett, Lee, Kyoung A., Jacoby, Daniel, Melchinger, Hannah, Nguyen, Andrew, Shaw, Melissa, Simonov, Michael, Williams, Alyssa, Weinstein, Jason, and Wilson, Francis P.

Subjects
HEART failure, DIGITAL health, HEART failure patients, DESIGN failures, PATIENT participation, HEALTH self-care
Abstract

Background: Self‐care and patient engagement are important elements of heart failure (HF) care, endorsed in the guidelines. Digital health tools may improve quality of life (QOL) in HF patients by promoting care, knowledge, and engagement. This manuscript describes the rationale and challenges of the design and implementation of a pragmatic randomized controlled trial to evaluate the efficacy of three digital health technologies in improving QOL for patients with HF. Hypothesis: We hypothesize that digital health interventions will improve QOL of HF patients through the early detection of warning signs of disease exacerbation, the opportunity of self‐tracking symptoms, and the education provided, which enhances patient empowerment. Methods: Using a fully electronic enrollment and consent platform, the trial will randomize 200 patients across HF clinics in the Yale New Haven Health system to receive either usual care or one of three digital technologies designed to promote self‐management and provide critical data to clinicians. The primary outcome is the change in QOL as assessed by the Kansas City Cardiomyopathy Questionnaire at 3 months. Results: First enrollment occurred in September 2021. Recruitment was anticipated to last 6–8 months and participants were followed for 6 months after randomization. Our recruitment efforts have highlighted the large digital divide in our population of interest. Conclusion: Assessing clinical outcomes, patient usability, and ease of clinical integration of digital technologies will be beneficial in determining the feasibility of the integration of such technologies into the healthcare system. [ABSTRACT FROM AUTHOR]

Published
2022
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29. Excessive Blood Pressure Response to Clonidine in Hospitalized Patients With Asymptomatic Severe Hypertension.

Author

Hanna, Jonathan, Ghazi, Lama, Yamamoto, Yu, Simonov, Michael, Shah, Tayyab, Wilson, Francis P, and Peixoto, Aldo J

Subjects
BLOOD pressure, ASYMPTOMATIC patients, CLONIDINE, DIASTOLIC blood pressure, HOSPITAL patients
Abstract

Background There are limited and nonconcordant data on the rapidity and safety of blood pressure response to clonidine in the setting of asymptomatic severe hypertension. We evaluated the blood pressure response to clonidine in hospitalized patients with asymptomatic severe hypertension. Methods We performed a review of hospitalized, noncritically ill patients receiving clonidine within 6 hours of developing asymptomatic severe hypertension (systolic blood pressure [SBP] >180 or diastolic blood pressure [DBP] >110 mm Hg in the absence of acute hypertension-mediated target organ damage). The incidence of mean arterial pressure (MAP) reduction by ≥30% at 4 hours after clonidine was the primary endpoint. Results We identified 200 relevant patient encounters (median age 63 years, 48.5% women). Median time to clonidine following asymptomatic severe hypertension was 2.8 hours. A total of 20 (10%) patients had ≥30% MAP reduction within 4 hours after clonidine, and 32 (16%) patients had ≥30% reduction in either SBP, DBP, or MAP. Older age, female sex, and preexisting vascular disease were associated with ≥30% MAP reductions (P < 0.05). Only patient sex and clonidine dose of 0.3 mg were significant in multivariable models. There were 14 adverse events observed within 24 hours of administration of clonidine; most (9) were acute kidney injury. There were no ischemic (myocardial, cerebrovascular) events. Conclusions A substantial minority of hospitalized patients with asymptomatic severe hypertension experience precipitous blood pressure decline with clonidine, and though blood pressure declines more precipitously in women and those receiving higher doses (0.3 mg specifically), the response to clonidine is generally not predictable on clinical grounds. [ABSTRACT FROM AUTHOR]

Published
2022
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34. 2‑Arylbenzo[d]oxazole Phosphinate Esters as Second-Generation Modulators of Utrophin for the Treatment of Duchenne Muscular Dystrophy.

Author

Babbs, Arran, Berg, Adam, Chatzopoulou, Maria, Davies, Kay E., Davies, Stephen G., Edwards, Benjamin, Elsey, David J., Emer, Enrico, Guiraud, Simon, Harriman, Shawn, Lecci, Cristina, Moir, Lee, Peters, David, Robinson, Neil, Rowley, Jessica A., Russell, Angela J., Squire, Sarah E., Tinsley, Jonathon M., Wilson, Francis X., and Wynne, Graham M.

Published
2020
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35. A History of the Anglo-European College of Chiropractic.

Author

WILSON, FRANCIS J. H.

Abstract

In 2017 the Anglo-European College of Chiropractic (AECC) became the AECC University College, a change in name which denoted new status and an important transition in the institution's development. The AECC University College, formally the Anglo-European College of Chiropractic, is the oldest existing chiropractic school in Europe. Many of the chiropractors who practice in Europe today were trained at the AECC and its graduates have been influential in shaping the chiropractic profession not only within Europe, but also globally. Anthony Metcalfe, a graduate of the AECC, served as president of the World Federation of Chiropractic (WFC) between 2004 and 2006. The current secretary general of the WFC, Richard Brown, is a graduate of the AECC. This paper provides an overview of the history of the School from its origins to the attainment of university college title. [ABSTRACT FROM AUTHOR]

Published
2019

37. Electronic Alerts for Acute Kidney Injury Amelioration (ELAIA-1): a completely electronic, multicentre, randomised controlled trial: design and rationale.

Author

Mutter, Marina, Martin, Melissa, Yu Yamamoto, Biswas, Aditya, Etropolski, Boian, Feldman, Harold, Garg, Amit, Gourlie, Noah, Latham, Stephen, Haiqun Lin, Palevsky, Paul M., Parikh, Chirag, Moreira, Erica, Ugwuowo, Ugochukwu, and Wilson, Francis P.

Abstract

Introduction Acute kidney injury (AKI) is common among hospitalised patients and under-recognised by providers and yet carries a significant risk of morbidity and mortality. Electronic alerts for AKI have become more common despite a lack of strong evidence of their benefits. We designed a multicentre, randomised, controlled trial to evaluate the effectiveness of AKI alerts. Our aim is to highlight several challenges faced in the design of this trial, which uses electronic screening, enrolment, randomisation, intervention and data collection. Methods and analysis The design and implementation of an electronic alert system for AKI was a reiterative process involving several challenges and limitations set by the confines of the electronic medical record system. The trial will electronically identify and randomise 6030 adults with AKI at six hospitals over a 1.5-2 year period to usual care versus an electronic alert containing an AKI-specific order set. Our primary outcome will be a composite of AKI progression, inpatient dialysis and inpatient death within 14 days of randomisation. During a 1-month pilot in the medical intensive care unit of Yale New Haven Hospital, we have demonstrated feasibility of automating enrolment and data collection. Feedback from providers exposed to the alerts was used to continually improve alert clarity, user friendliness and alert specificity through refined inclusion and exclusion criteria. Ethics and dissemination This study has been approved by the appropriate ethics committees for each of our study sites. Our study qualified for a waiver of informed consent as it presents no more than minimal risk and cannot be feasibly conducted in the absence of a waiver. We are committed to open dissemination of our data through clinicaltrials. gov and submission of results to the NIH data sharing repository. Results of our trial will be submitted for publication in a peer-reviewed journal. [ABSTRACT FROM AUTHOR]

Published
2019
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40. Co-operation is Better than Confrontation: An Interview with Dr. Michael Howitt Wilson.

Author

WILSON, FRANCIS J. H.

Abstract

Excerpts from a semi-structured interview with Dr. Michael Howitt Wilson (1938-2016) provide a basis for understanding the lived experiences of this English clinician who practiced both as a medical doctor and chiropractor. Emergent themes invite the reader to consider positive and negative aspects of tribalism in chiropractic and medicine, the consequences of bold claims by chiropractors on the perceptions of external observers, and approaches to the training of qualified healthcare practitioners in chiropractic. [ABSTRACT FROM AUTHOR]

Published
2017

44. Taxidermy, Documentation, and the 'Liveness' of Death.

Author

MOSELEY WILSON, FRANCIS MARION

Abstract

Taxidermy is an old craft that requires a confrontation and even intimacy with dead animals; it is also a process that is not often seen or experienced by the general public in Western societies. I am an artist using the taxidermy process as the material for time-based work. My 2014 work cuddle involves swapping the insides and eyes of a dead rabbit and a teddy bear. One section of the work involves the display of these artefacts alongside video documentation. In this article the experience and somatic awareness of dead animal bodies serves as the cross section of ideas in posthumanism, phenomenology, and psychoanalysis. I provide an analysis of cuddle and examine how video documentation alongside dead animal bodies intersects with concepts of 'liveness' and presence in performance art. Using both Peggy Phelan and Phillip Auslander's concepts of 'liveness' and performance, I argue the potential of the olfactory in live performance, particularly the smell of dead animal bodies, and how our senses that have not yet been mediatised contribute to our experiences of live art. This analysis of cuddle combines these theories of 'liveness' with Aurel Kolnai's On Disgust, Julia Kristeva's concept of abjection, and Phelan and Herbert Blau's readings of mortality in the experience of an artwork as a live performance. [ABSTRACT FROM AUTHOR]

Published
2016

46. Determinants of surgical decision making: a national survey.

Author

Wilson, Niamey P., Wilson, Francis P., Neuman, Mark, Epstein, Andrew, Bell, Richard, Armstrong, Katrina, and Murayama, Kenric

Subjects
*SURGEONS, *REGRESSION analysis, *MONETARY incentives, *SURGICAL indications, *WAGES
Abstract

BACKGROUND: We conducted a national survey of general surgeons to address the association be-tween surgeon characteristics and the tendency to recommend surgery. METHODS: We used a web-based survey with 25 hypothetical clinical scenarios with clinical equi-poise regarding the decision to operate. The respondent-level tendency to operate (TTO) score was cal-culated as the average score over the 25 scenarios. Surgical volume was based on self-report. Linear regression models were used to evaluate the associations between TTO, other covariates of interest, and surgical volume. RESULTS: There were 907 respondents. The mean surgical TTO was 3.05 ± .43. Surgeons had sig-nificantly lower TTO scores when responding to questions within their area of practice (P < .0001). There was no association between TTO and malpractice concerns, financial incentives, or compensa-tion structure. CONCLUSIONS: Surgeons recommend intervention far less frequently within their area of speciali-zation. Malpractice concerns, volume, and financial compensation do not significantly affect surgical decision making. [ABSTRACT FROM AUTHOR]

Published
2013
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48. C-Branched Iminosugars: α-Glucosidase Inhibition by Enantiomers of isoDMDP, isoDGDP, and isoDAB-L-isoDMDP Compared to Miglitol and Miglustat.

Author

Jenkinson, Sarah F., Best, Daniel, Saville, A. Waldo, Mui, James, Martínez, R. Fernando, Shinpei Nakagawa, Takahito Kunimatsu, Alonzi, Dominic S., Butters, Terry D., Norez, Caroline, Becq, Frederic, Blériot, Yves, Wilson, Francis X., Weymouth-Wilson, Alexander C., Atsushi Kato, and Fleet, George W. J.

Published
2013
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50. A Pictorial History of the Anglo-European College of Chiropractic.

Author

Wilson, Francis J. H.

Abstract

The Anglo-European College of Chiropractic (AECC) is the oldest of Europe's chiropractic schools. For more than forty years the college and its faculty have stood at the forefront of European chiropractic education. The AECC has been, and remains, a forward looking institution, striving to provide the very best in chiropractic education, training and research. What follows is a short pictorial history of the school, from its beginnings in the 1960s, to the present day. [ABSTRACT FROM AUTHOR]

Published
2007

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