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11 results on '"Ferreira, Juanita"'

1. Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

Author

Conroy, Lindsey R., Clarke, Harrison A., Allison, Derek B., Valenca, Samuel Santos, Sun, Qi, Hawkinson, Tara R., Young, Lyndsay E. A., Ferreira, Juanita E., Hammonds, Autumn V., Dunne, Jaclyn B., McDonald, Robert J., Absher, Kimberly J., Dong, Brittany E., Bruntz, Ronald C., Markussen, Kia H., Juras, Jelena A., Alilain, Warren J., Liu, Jinze, Gentry, Matthew S., Angel, Peggi M., Waters, Christopher M., and Sun, Ramon C.

Published
2023
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5. Validation of a host blood transcriptomic biomarker for pulmonary tuberculosis in people living with HIV: a prospective diagnostic and prognostic accuracy study

Author

Abrahams, Charmaine, Africa, Hadn, Ahlers, Petri, Arendsen, Denis, Badimo, Tebogo, Baepanye, Kagiso, Baepanye, Kesenogile Edna, Bande, Bianca, Batyi, Nomfuneko Cynthia, Beukes, Roslyn, Bontsi, Laudicia Tshenolo, Booi, Obakeng Peter, Botha, Mari Cathrin, Braaf, Samentra, Buhlungu, Sivuyile, Carstens, Alida, Chauke, Kgomotso Violet, Chinappa, Thilagavathy, Chung, Eva, Chung, Michelle, Clarke, Ken, Cloete, Yolundi, Coetzee, Lorraine, Collignon, Marelize, Companie, Alessandro, Corris, Cara-mia, Cwaile, Mooketsi Theophillius, Cwele, Thobelani, Davids, Ilse, Davies, Isabella Johanna, De Klerk, Emilia, de Kock, Marwou, Dhlamini, Audrey Lebohang, Diamond, Bongani, Didloff, Maria, Dlamini, Celaphiwe, Dolo, Palesa, Eyre, Candice, Feni, Tebogo, Ferreira, Juanita, Ferus, Christal, Fisher, Michelle, Flinn, Marika, Fransman, Bernadine, Galane, Welseh Phindile, Geldenhuys, Hennie, Gempies, Diann, Goliath, Thelma, Govender, Dhineshree, Gregg, Yolande, Gumede, Goodness, Gwamada, Zanele, Halti, Senzo, Hassiem, Rieyaat, Herling, Roxane, Herselman, Yulandi, Hughes, Ellis, Issel, Henry, Iyemosolo, Blanchard Mbay, Jali, Zandile, Janse Van Rensburg, Bonita, Jansen, Ruwiyda, Jeleni, James Michael, Jonkane, Olebogeng, Julies, Fabio, Kafaar, Fazlin, Kasongo, Christian Mabika, Keffers, Sophie, Kekana, Boitumelo Sophy, Kekana, Sebaetseng Jeanette, Kelepu, Xoliswa, Khanyile, Lungile, Khobedi, Gomotsegang Virginia, Khomba, Gloria, Khoza, Lucky Sipho, King, Marietjie, Kolobe, Gloria Keitumetse, Kruger, Sandra, Kruger, Jaftha, Kunene, Ndlela Israel, Lakay, Sunelza, Lakhi, Aneesa, Langa, Nondumiso, Ledwaba, Hildah, Lekagane, Lerato Julia, Lekotloane, Sheiley Christina, Leopeng, Thelma, Louw, Ilze Jeanette, Luabeya, Angelique Kany Kany, Lusale, Sarah Teboso, Maatjie, Perfect Tiisetso, Mabasa, Immaculate, Mabe, Tshegofatso Dorah, Mabena, Kamogelo Fortunate, Mabuza, Nkosinathi Charles, Mabwe, Simbarashe, Madikwe, Johanna Thapelo, Madikwe, Octavia Mahkosazana, Maebana, Rapontwana Letlhogonolo, Magwasha, Malobisa Sylvester, Majola, Molly, Makhetha, Mantai, Makhethe, Lebohang, Malay, Vernon, Manzini, Vutlhari-I-Vunhenha Fairlord, Maphanga, Jabu, Maphanga, Nonhle, Market, Juanita, Maroele, Isholedi Samuel, Masibi, Omphile Petunia, Mathabanzini, July Rocky, Mathode, Tendamudzimu Ivan, Matsane, Ellen Ditaba, Mbata, Lungile, Meyer, Faheema, Mhandire, Nyasha Karen, Miga, Thembisiwe, Mkhize, Nosisa Charity Thandeka, Mkhokho, Caroline, Mkwalase, Neo Hilda, Mnqonywa, Nondzakazi, Moche, Karabo, Modisaotsile, Brenda Matshidiso, Mokgetsengoane, Patricia Pakiso, Mokone, Selemeng Matseliso Carol, Molatlhegi, Kegomoditswe Magdeline, Molefe, Thuso Andrew, Moloko, Joseph Panie, Molosi, Kabelo, Molotsi, Motlatsi Evelyn, Montwedi, Tebogo Edwin, Monyemangene, Boikanyo Dinah, Mooketsi, Hellen Mokopi, Moses, Miriam, Mosito, Boitumelo, Mosito, Tshplpfelo Mapula, Mosweu, Ireen Lesebang, Mothaga, Primrose, Motlagomang, Banyana Olga, Mouton, Angelique, Mpofu, Onesisa, Mthembu, Funeka Nomvula, Mtlali, Mpho, Ndlovu, Nhlamulo, Ngcobo, Nompumelelo, Noble, Julia, Ntamo, Bantubonke Bertrum, Ntanjana, Gloria, Ntshauba, Tedrius, Opperman, Fajwa, Padayatchi, Nesri, Papalagae, Thandiwe, Petersen, Christel, Phakathi, Themba, Phatshwane, Mapule Ozma, Plaatjie, Patiswa, Pretorius, Abe, Rameetse, Victor Kgothatso, Ramjit, Dirhona, Ratangee, Frances, Ratangee, Maigan, Sanyaka, Pearl Nomsa, Sato, Alicia, Schoeman, Elisma, Schreuder, Constance, Seabela, Letlhogonolo, Segaetsho, Kelebogile Magdeline, Sein, Ni Ni, Selepe, Raesibe Agnes Pearl, Senne, Melissa Neo, September, Alison, September, Cashwin, Serake, Moeti, Shenje, Justin, Shezi, Thandiwe, Shezi, Sifiso Cornelius, Sing, Phindile, Singh, Chandrapharbha, Sithetho, Zona, Solomons, Dorothy, Stanley, Kim, Steyn, Marcia, Stofile, Bongiwe, Stryers, Sonia, Swanepoel, Liticia, Swarts, Anne, Thaba, Mando Mmakhora, Theko, Lethabo Collen, Thembela, Philile, Thompo, Mugwena, Toefy, Asma, Toto, Khayalethu, Tsagae, Dimakatso Sylvia, Tsamane, Ayanda, Tshikovhi, Vincent, Tswaile, Lebogang Isaac, Tyambetyu, Petrus, Tönsing, Susanne, Valley, Habibullah, van der Merwe, Linda, van Rooyen, Elma, Veldsman, Ashley, Veldtsman, Helen, Vollenhoven, Kelvin, Zaca, Londiwe, Zimri, Elaine, Zulu, Mbali, Mendelsohn, Simon C, Fiore-Gartland, Andrew, Penn-Nicholson, Adam, Mulenga, Humphrey, Mbandi, Stanley Kimbung, Borate, Bhavesh, Hadley, Katie, Hikuam, Chris, Musvosvi, Munyaradzi, Bilek, Nicole, Erasmus, Mzwandile, Jaxa, Lungisa, Raphela, Rodney, Nombida, Onke, Kaskar, Masooda, Sumner, Tom, White, Richard G, Innes, Craig, Brumskine, William, Hiemstra, Andriëtte, Malherbe, Stephanus T, Hassan-Moosa, Razia, Tameris, Michèle, Walzl, Gerhard, Naidoo, Kogieleum, Churchyard, Gavin, Scriba, Thomas J, and Hatherill, Mark

Published
2021
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6. Lymph Node Metastases in Papillary Thyroid Carcinoma can be Predicted by a Convolutional Neural Network: a Multi-Institution Study.

Author

Esce, Antoinette, Redemann, Jordan P., Olson, Garth T., Hanson, Joshua A., Agarwal, Shweta, Yenwongfai, Leonard, Ferreira, Juanita, Boyd, Nathan H., Bocklage, Thèrése, and Martin, David R.

Subjects
STATISTICS, PREDICTIVE tests, THYROIDECTOMY, PAPILLARY carcinoma, THYROID gland tumors, LYMPH nodes, METASTASIS, ARTIFICIAL intelligence, HEAD & neck cancer, RISK assessment, LYMPHATIC diseases, DESCRIPTIVE statistics, ARTIFICIAL neural networks, RECEIVER operating characteristic curves, DATA analysis, SENSITIVITY & specificity (Statistics), MULTIHOSPITAL systems, ALGORITHMS, DISEASE risk factors
Abstract

Objectives: The presence of nodal metastases in patients with papillary thyroid carcinoma (PTC) has both staging and treatment implications. However, lymph nodes are often not removed during thyroidectomy. Prior work has demonstrated the capability of artificial intelligence (AI) to predict the presence of nodal metastases in PTC based on the primary tumor histopathology alone. This study aimed to replicate these results with multi-institutional data. Methods: Cases of conventional PTC were identified from the records of 2 large academic institutions. Only patients with complete pathology data, including at least 3 sampled lymph nodes, were included in the study. Tumors were designated "positive" if they had at least 5 positive lymph node metastases. First, algorithms were trained separately on each institution's data and tested independently on the other institution's data. Then, the data sets were combined and new algorithms were developed and tested. The primary tumors were randomized into 2 groups, one to train the algorithm and another to test it. A low level of supervision was used to train the algorithm. Board-certified pathologists annotated the slides. HALO-AI convolutional neural network and image software was used to perform training and testing. Receiver operator characteristic curves and the Youden J statistic were used for primary analysis. Results: There were 420 cases used in analyses, 45% of which were negative. The best performing single institution algorithm had an area under the curve (AUC) of 0.64 with a sensitivity and specificity of 65% and 61% respectively, when tested on the other institution's data. The best performing combined institution algorithm had an AUC of 0.84 with a sensitivity and specificity of 68% and 91% respectively. Conclusion: A convolutional neural network can produce an accurate and robust algorithm that is capable of predicting nodal metastases from primary PTC histopathology alone even in the setting of multi-institutional data. [ABSTRACT FROM AUTHOR]

Published
2023
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9. Cytopathological features of gastroesophageal junction adenocarcinoma with enteroblastic differentiation and histopathological correlation.

Author

Ferreira, Juanita E., Mbagwu, Emmy, Lee, Eun Y., Shelman, Nathan R., and Allison, Derek B.

Subjects
*ESOPHAGOGASTRIC junction, *HISTOPATHOLOGY, *ADENOCARCINOMA
Abstract

The authors report a case of gastroesophageal adenocarcinoma with enteroblastic differentiation (GAED) presenting as an unknown primary and offer the first description of this tumour on cytological preparation with histopathological correlation. Although challenging, a specific diagnosis can be made in the right clinical scenario. [ABSTRACT FROM AUTHOR]

Published
2023
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10. Integration of Spatial Metabolomics and Machine Learning Reveal Glycogen as an Actionable Target for Pulmonary Fibrosis

Author

Conroy, Lindsey R., primary, Allison, Derek B., additional, Sun, Qi, additional, Valenca, Samuel S., additional, Young, Lyndsay EA, additional, Clarke, Harrison A., additional, Hawkinson, Tara R., additional, Ferreira, Juanita E., additional, Hammonds, Autumn V., additional, McDonald, Robert J., additional, Absher, Kimberly J., additional, Dong, Brittany E., additional, Alilain, Warren J., additional, Gentry, Matthew S., additional, Liu, Jinze, additional, Waters, Christopher M., additional, and Sun, Ramon, additional

Published
2022
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11. Validation of a host blood transcriptomic biomarker for pulmonary tuberculosis in people living with HIV: a prospective diagnostic and prognostic accuracy study

Author

Mendelsohn, Simon C, primary, Fiore-Gartland, Andrew, additional, Penn-Nicholson, Adam, additional, Mulenga, Humphrey, additional, Mbandi, Stanley Kimbung, additional, Borate, Bhavesh, additional, Hadley, Katie, additional, Hikuam, Chris, additional, Musvosvi, Munyaradzi, additional, Bilek, Nicole, additional, Erasmus, Mzwandile, additional, Jaxa, Lungisa, additional, Raphela, Rodney, additional, Nombida, Onke, additional, Kaskar, Masooda, additional, Sumner, Tom, additional, White, Richard G, additional, Innes, Craig, additional, Brumskine, William, additional, Hiemstra, Andriëtte, additional, Malherbe, Stephanus T, additional, Hassan-Moosa, Razia, additional, Tameris, Michèle, additional, Walzl, Gerhard, additional, Naidoo, Kogieleum, additional, Churchyard, Gavin, additional, Scriba, Thomas J, additional, Hatherill, Mark, additional, Abrahams, Charmaine, additional, Africa, Hadn, additional, Ahlers, Petri, additional, Arendsen, Denis, additional, Badimo, Tebogo, additional, Baepanye, Kagiso, additional, Baepanye, Kesenogile Edna, additional, Bande, Bianca, additional, Batyi, Nomfuneko Cynthia, additional, Beukes, Roslyn, additional, Bontsi, Laudicia Tshenolo, additional, Booi, Obakeng Peter, additional, Botha, Mari Cathrin, additional, Braaf, Samentra, additional, Buhlungu, Sivuyile, additional, Carstens, Alida, additional, Chauke, Kgomotso Violet, additional, Chinappa, Thilagavathy, additional, Chung, Eva, additional, Chung, Michelle, additional, Clarke, Ken, additional, Cloete, Yolundi, additional, Coetzee, Lorraine, additional, Collignon, Marelize, additional, Companie, Alessandro, additional, Corris, Cara-mia, additional, Cwaile, Mooketsi Theophillius, additional, Cwele, Thobelani, additional, Davids, Ilse, additional, Davies, Isabella Johanna, additional, De Klerk, Emilia, additional, de Kock, Marwou, additional, Dhlamini, Audrey Lebohang, additional, Diamond, Bongani, additional, Didloff, Maria, additional, Dlamini, Celaphiwe, additional, Dolo, Palesa, additional, Eyre, Candice, additional, Feni, Tebogo, additional, Ferreira, Juanita, additional, Ferus, Christal, additional, Fisher, Michelle, additional, Flinn, Marika, additional, Fransman, Bernadine, additional, Galane, Welseh Phindile, additional, Geldenhuys, Hennie, additional, Gempies, Diann, additional, Goliath, Thelma, additional, Govender, Dhineshree, additional, Gregg, Yolande, additional, Gumede, Goodness, additional, Gwamada, Zanele, additional, Halti, Senzo, additional, Hassiem, Rieyaat, additional, Herling, Roxane, additional, Herselman, Yulandi, additional, Hughes, Ellis, additional, Issel, Henry, additional, Iyemosolo, Blanchard Mbay, additional, Jali, Zandile, additional, Janse Van Rensburg, Bonita, additional, Jansen, Ruwiyda, additional, Jeleni, James Michael, additional, Jonkane, Olebogeng, additional, Julies, Fabio, additional, Kafaar, Fazlin, additional, Kasongo, Christian Mabika, additional, Keffers, Sophie, additional, Kekana, Boitumelo Sophy, additional, Kekana, Sebaetseng Jeanette, additional, Kelepu, Xoliswa, additional, Khanyile, Lungile, additional, Khobedi, Gomotsegang Virginia, additional, Khomba, Gloria, additional, Khoza, Lucky Sipho, additional, King, Marietjie, additional, Kolobe, Gloria Keitumetse, additional, Kruger, Sandra, additional, Kruger, Jaftha, additional, Kunene, Ndlela Israel, additional, Lakay, Sunelza, additional, Lakhi, Aneesa, additional, Langa, Nondumiso, additional, Ledwaba, Hildah, additional, Lekagane, Lerato Julia, additional, Lekotloane, Sheiley Christina, additional, Leopeng, Thelma, additional, Louw, Ilze Jeanette, additional, Luabeya, Angelique Kany Kany, additional, Lusale, Sarah Teboso, additional, Maatjie, Perfect Tiisetso, additional, Mabasa, Immaculate, additional, Mabe, Tshegofatso Dorah, additional, Mabena, Kamogelo Fortunate, additional, Mabuza, Nkosinathi Charles, additional, Mabwe, Simbarashe, additional, Madikwe, Johanna Thapelo, additional, Madikwe, Octavia Mahkosazana, additional, Maebana, Rapontwana Letlhogonolo, additional, Magwasha, Malobisa Sylvester, additional, Majola, Molly, additional, Makhetha, Mantai, additional, Makhethe, Lebohang, additional, Malay, Vernon, additional, Manzini, Vutlhari-I-Vunhenha Fairlord, additional, Maphanga, Jabu, additional, Maphanga, Nonhle, additional, Market, Juanita, additional, Maroele, Isholedi Samuel, additional, Masibi, Omphile Petunia, additional, Mathabanzini, July Rocky, additional, Mathode, Tendamudzimu Ivan, additional, Matsane, Ellen Ditaba, additional, Mbata, Lungile, additional, Meyer, Faheema, additional, Mhandire, Nyasha Karen, additional, Miga, Thembisiwe, additional, Mkhize, Nosisa Charity Thandeka, additional, Mkhokho, Caroline, additional, Mkwalase, Neo Hilda, additional, Mnqonywa, Nondzakazi, additional, Moche, Karabo, additional, Modisaotsile, Brenda Matshidiso, additional, Mokgetsengoane, Patricia Pakiso, additional, Mokone, Selemeng Matseliso Carol, additional, Molatlhegi, Kegomoditswe Magdeline, additional, Molefe, Thuso Andrew, additional, Moloko, Joseph Panie, additional, Molosi, Kabelo, additional, Molotsi, Motlatsi Evelyn, additional, Montwedi, Tebogo Edwin, additional, Monyemangene, Boikanyo Dinah, additional, Mooketsi, Hellen Mokopi, additional, Moses, Miriam, additional, Mosito, Boitumelo, additional, Mosito, Tshplpfelo Mapula, additional, Mosweu, Ireen Lesebang, additional, Mothaga, Primrose, additional, Motlagomang, Banyana Olga, additional, Mouton, Angelique, additional, Mpofu, Onesisa, additional, Mthembu, Funeka Nomvula, additional, Mtlali, Mpho, additional, Ndlovu, Nhlamulo, additional, Ngcobo, Nompumelelo, additional, Noble, Julia, additional, Ntamo, Bantubonke Bertrum, additional, Ntanjana, Gloria, additional, Ntshauba, Tedrius, additional, Opperman, Fajwa, additional, Padayatchi, Nesri, additional, Papalagae, Thandiwe, additional, Petersen, Christel, additional, Phakathi, Themba, additional, Phatshwane, Mapule Ozma, additional, Plaatjie, Patiswa, additional, Pretorius, Abe, additional, Rameetse, Victor Kgothatso, additional, Ramjit, Dirhona, additional, Ratangee, Frances, additional, Ratangee, Maigan, additional, Sanyaka, Pearl Nomsa, additional, Sato, Alicia, additional, Schoeman, Elisma, additional, Schreuder, Constance, additional, Seabela, Letlhogonolo, additional, Segaetsho, Kelebogile Magdeline, additional, Sein, Ni Ni, additional, Selepe, Raesibe Agnes Pearl, additional, Senne, Melissa Neo, additional, September, Alison, additional, September, Cashwin, additional, Serake, Moeti, additional, Shenje, Justin, additional, Shezi, Thandiwe, additional, Shezi, Sifiso Cornelius, additional, Sing, Phindile, additional, Singh, Chandrapharbha, additional, Sithetho, Zona, additional, Solomons, Dorothy, additional, Stanley, Kim, additional, Steyn, Marcia, additional, Stofile, Bongiwe, additional, Stryers, Sonia, additional, Swanepoel, Liticia, additional, Swarts, Anne, additional, Thaba, Mando Mmakhora, additional, Theko, Lethabo Collen, additional, Thembela, Philile, additional, Thompo, Mugwena, additional, Toefy, Asma, additional, Toto, Khayalethu, additional, Tsagae, Dimakatso Sylvia, additional, Tsamane, Ayanda, additional, Tshikovhi, Vincent, additional, Tswaile, Lebogang Isaac, additional, Tyambetyu, Petrus, additional, Tönsing, Susanne, additional, Valley, Habibullah, additional, van der Merwe, Linda, additional, van Rooyen, Elma, additional, Veldsman, Ashley, additional, Veldtsman, Helen, additional, Vollenhoven, Kelvin, additional, Zaca, Londiwe, additional, Zimri, Elaine, additional, and Zulu, Mbali, additional

Published
2021
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