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145 results on '"Mendelsohn, Simon"'

1. Classification of early tuberculosis states to guide research for improved care and prevention: an international Delphi consensus exercise

Author

Alland, David, Behr, Marcel A, Beko, Busisiwe B, Burhan, Erlina, Churchyard, Gavin, Cobelens, Frank, Denholm, Justin T, Dinkele, Ryan, Ellner, Jerrold J, Fatima, Razia, Haigh, Kate A, Hatherill, Mark, Horton, Katherine C, Kendall, Emily A, Khan, Palwasha Y, MacPherson, Peter, Malherbe, Stephanus T, Mave, Vidya, Mendelsohn, Simon C, Musvosvi, Munyaradzi, Nemes, Elisa, Penn-Nicholson, Adam, Ramamurthy, Dharanidharan, Rangaka, Molebogeng X, Sahu, Suvanand, Schwalb, Alvaro, Shah, Divya K, Sheerin, Dylan, Simon, Donald, Steyn, Adrie J C, Thu Anh, Nguyen, Walzl, Gerhard, Weller, Charlotte L, Williams, Caroline ML, Wong, Emily B, Wood, Robin, Xie, Yingda L, Yi, Siyan, Coussens, Anna K, Zaidi, Syed M A, Allwood, Brian W, Dewan, Puneet K, Gray, Glenda, Kohli, Mikashmi, Kredo, Tamara, Marais, Ben J, Marks, Guy B, Martinez, Leo, Ruhwald, Morten, Scriba, Thomas J, Seddon, James A, Tisile, Phumeza, Warner, Digby F, Wilkinson, Robert J, Esmail, Hanif, and Houben, Rein M G J

Published
2024
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2. Probabilistic Predictions of People Perusing: Evaluating Metrics of Language Model Performance for Psycholinguistic Modeling

Author

Hao, Yiding, Mendelsohn, Simon, Sterneck, Rachel, Martinez, Randi, and Frank, Robert

Subjects
Computer Science - Computation and Language, Computer Science - Neural and Evolutionary Computing
Abstract

By positing a relationship between naturalistic reading times and information-theoretic surprisal, surprisal theory (Hale, 2001; Levy, 2008) provides a natural interface between language models and psycholinguistic models. This paper re-evaluates a claim due to Goodkind and Bicknell (2018) that a language model's ability to model reading times is a linear function of its perplexity. By extending Goodkind and Bicknell's analysis to modern neural architectures, we show that the proposed relation does not always hold for Long Short-Term Memory networks, Transformers, and pre-trained models. We introduce an alternate measure of language modeling performance called predictability norm correlation based on Cloze probabilities measured from human subjects. Our new metric yields a more robust relationship between language model quality and psycholinguistic modeling performance that allows for comparison between models with different training configurations., Comment: To appear in the proceedings of the Cognitive Modeling and Computational Linguistics workshop (CMCL) at EMNLP 2020

Published
2020

3. Finding Syntactic Representations in Neural Stacks

Author

Merrill, William, Khazan, Lenny, Amsel, Noah, Hao, Yiding, Mendelsohn, Simon, and Frank, Robert

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Neural network architectures have been augmented with differentiable stacks in order to introduce a bias toward learning hierarchy-sensitive regularities. It has, however, proven difficult to assess the degree to which such a bias is effective, as the operation of the differentiable stack is not always interpretable. In this paper, we attempt to detect the presence of latent representations of hierarchical structure through an exploration of the unsupervised learning of constituency structure. Using a technique due to Shen et al. (2018a,b), we extract syntactic trees from the pushing behavior of stack RNNs trained on language modeling and classification objectives. We find that our models produce parses that reflect natural language syntactic constituencies, demonstrating that stack RNNs do indeed infer linguistically relevant hierarchical structure., Comment: To appear in the Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP

Published
2019

4. RISK6, a 6-gene transcriptomic signature of TB disease risk, diagnosis and treatment response

Author

Penn-Nicholson, Adam, Mbandi, Stanley Kimbung, Thompson, Ethan, Mendelsohn, Simon C, Suliman, Sara, Chegou, Novel N, Malherbe, Stephanus T, Darboe, Fatoumatta, Erasmus, Mzwandile, Hanekom, Willem A, Bilek, Nicole, Fisher, Michelle, Kaufmann, Stefan HE, Winter, Jill, Murphy, Melissa, Wood, Robin, Morrow, Carl, Van Rhijn, Ildiko, Moody, Branch, Murray, Megan, Andrade, Bruno B, Sterling, Timothy R, Sutherland, Jayne, Naidoo, Kogieleum, Padayatchi, Nesri, Walzl, Gerhard, Hatherill, Mark, Zak, Daniel, and Scriba, Thomas J

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Research, Prevention, Infectious Diseases, HIV/AIDS, Lung, Tuberculosis, Rare Diseases, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Infection, Good Health and Well Being, Adolescent, Area Under Curve, Biomarkers, Cohort Studies, Female, HIV Infections, Humans, Male, Mycobacterium tuberculosis, Point-of-Care Systems, Positron-Emission Tomography, Prognosis, RNA, Bacterial, ROC Curve, Real-Time Polymerase Chain Reaction, Sensitivity and Specificity, Adolescent Cohort Study team, GC6-74 Consortium, SATVI Clinical and Laboratory Team, ScreenTB Consortium, AE-TBC Consortium, RePORT Brazil Team, Peruvian Household Contacts Cohort Team, CAPRISA IMPRESS team
Abstract

Improved tuberculosis diagnostics and tools for monitoring treatment response are urgently needed. We developed a robust and simple, PCR-based host-blood transcriptomic signature, RISK6, for multiple applications: identifying individuals at risk of incident disease, as a screening test for subclinical or clinical tuberculosis, and for monitoring tuberculosis treatment. RISK6 utility was validated by blind prediction using quantitative real-time (qRT) PCR in seven independent cohorts. Prognostic performance significantly exceeded that of previous signatures discovered in the same cohort. Performance for diagnosing subclinical and clinical disease in HIV-uninfected and HIV-infected persons, assessed by area under the receiver-operating characteristic curve, exceeded 85%. As a screening test for tuberculosis, the sensitivity at 90% specificity met or approached the benchmarks set out in World Health Organization target product profiles for non-sputum-based tests. RISK6 scores correlated with lung immunopathology activity, measured by positron emission tomography, and tracked treatment response, demonstrating utility as treatment response biomarker, while predicting treatment failure prior to treatment initiation. Performance of the test in capillary blood samples collected by finger-prick was noninferior to venous blood collected in PAXgene tubes. These results support incorporation of RISK6 into rapid, capillary blood-based point-of-care PCR devices for prospective assessment in field studies.

Published
2020

5. Context-Free Transductions with Neural Stacks

Author

Hao, Yiding, Merrill, William, Angluin, Dana, Frank, Robert, Amsel, Noah, Benz, Andrew, and Mendelsohn, Simon

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

This paper analyzes the behavior of stack-augmented recurrent neural network (RNN) models. Due to the architectural similarity between stack RNNs and pushdown transducers, we train stack RNN models on a number of tasks, including string reversal, context-free language modelling, and cumulative XOR evaluation. Examining the behavior of our networks, we show that stack-augmented RNNs can discover intuitive stack-based strategies for solving our tasks. However, stack RNNs are more difficult to train than classical architectures such as LSTMs. Rather than employ stack-based strategies, more complex networks often find approximate solutions by using the stack as unstructured memory., Comment: To appear in the proceedings of the Analyzing and Interpreting Neural Networks for NLP workshop at EMNLP 2018

Published
2018

7. Transcriptomic Signatures of Progression to Tuberculosis Disease Among Close Contacts in Brazil.

Author

Mendelsohn, Simon C, Andrade, Bruno B, Mbandi, Stanley Kimbung, Andrade, Alice M S, Muwanga, Vanessa M, Figueiredo, Marina C, Erasmus, Mzwandile, Rolla, Valeria C, Thami, Prisca K, Cordeiro-Santos, Marcelo, Penn-Nicholson, Adam, Kritski, Afranio L, Hatherill, Mark, Sterling, Timothy R, Scriba, Thomas J, and Consortia, the RePORT–South Africa and RePORT–Brazil

Subjects
*EXTRAPULMONARY tuberculosis, *RECEIVER operating characteristic curves, *MYCOBACTERIUM tuberculosis, *POLYMERASE chain reaction, *PROGNOSTIC tests
Abstract

Background Approximately 5% of people infected with Mycobacterium tuberculosis progress to tuberculosis (TB) disease without preventive therapy. There is a need for a prognostic test to identify those at highest risk of incident TB so that therapy can be targeted. We evaluated host blood transcriptomic signatures for progression to TB disease. Methods Close contacts (≥4 hours of exposure per week) of adult patients with culture-confirmed pulmonary TB were enrolled in Brazil. Investigation for incident, microbiologically confirmed, or clinically diagnosed pulmonary or extrapulmonary TB disease through 24 months of follow-up was symptom triggered. Twenty previously validated blood TB transcriptomic signatures were measured at baseline by real-time quantitative polymerase chain reaction. Prognostic performance for incident TB was tested by receiver operating characteristic curve analysis at 6, 9, 12, and 24 months of follow-up. Results Between June 2015 and June 2019, 1854 close contacts were enrolled. Twenty-five progressed to incident TB, of whom 13 had microbiologically confirmed disease. Baseline transcriptomic signature scores were measured in 1789 close contacts. Prognostic performance for all signatures was best within 6 months of diagnosis. Seven signatures (Gliddon4, Suliman4, Roe3, Roe1, Penn-Nicholson6, Francisco2, and Rajan5) met the minimum World Health Organization target product profile for a prognostic test through 6 months and 3 signatures (Gliddon4, Rajan5, and Duffy9) through 9 months. None met the target product profile threshold through ≥12 months of follow-up. Conclusions Blood transcriptomic signatures may be useful for predicting TB risk within 9 months of measurement among TB-exposed contacts to target preventive therapy administration. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Prospective multicentre head-to-head validation of host blood transcriptomic biomarkers for pulmonary tuberculosis by real-time PCR

Author

Mendelsohn, Simon C., Mbandi, Stanley Kimbung, Fiore-Gartland, Andrew, Penn-Nicholson, Adam, Musvosvi, Munyaradzi, Mulenga, Humphrey, Fisher, Michelle, Hadley, Katie, Erasmus, Mzwandile, Nombida, Onke, Tameris, Michèle, Walzl, Gerhard, Naidoo, Kogieleum, Churchyard, Gavin, Hatherill, Mark, and Scriba, Thomas J.

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

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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12. Biomarker-guided tuberculosis preventive therapy (CORTIS): a randomised controlled trial

Author

Baepanye, Kesenogile, Baepanye, Tshepiso, Clarke, Ken, Collignon, Marelize, Dlamini, Audrey, Eyre, Candice, Feni, Tebogo, Fikizolo, Moogo, Galane, Phinda, Goliath, Thelma, Gangat, Alia, Malefo-Grootboom, Shirley, Janse van Rensburg, Elba, Janse van Rensburg, Bonita, Kekana, Sophy, Zietsman, Marietjie, Kock, Adrianne, Kunene, Israel, Lakhi, Aneessa, Langa, Nondumiso, Ledwaba, Hilda, Luphoko, Marillyn, Mabasa, Immaculate, Mabe, Dorah, Mabuza, Nkosinathi, Majola, Molly, Makhetha, Mantai, Makoanyane, Mpho, Makhubalo, Blossom, Malay, Vernon, Market, Juanita, Matshego, Selvy, Mbipa, Nontsikelelo, Mmotsa, Tsiamo, Modipa, Sylvester, Mopati, Samuel, Moswegu, Palesa, Mothaga, Primrose, Muller, Dorothy, Nchwe, Grace, Nel, Maryna, Nhlangulela, Lindiwe, Ntamo, Bantubonke, Ntoahae, Lawerence, Ntshauba, Tedrius, Sanyaka, Nomsa, Seabela, Letlhogonolo, Selepe, Pearl, Senne, Melissa, Serake, MG, Thlapi, Maria, Tshikovhi, Vincent, Tswaile, Lebogang, van Aswegen, Amanda, Mbata, Lungile, Takavamanya, Constance, Pinho, Pedro, Mdlulu, John, Taljaard, Marthinette, Slabbert, Naydene, Sayed, Sharfuddin, Nielson, Tanya, Ni Sein, Ni, Govender, Dhineshree, Chinappa, Tilagavathy, Zulu, Mbali Ignatia, Maphanga, Nonhle Bridgette, Hlathi, Senzo Ralph, Gumede, Goodness Khanyisile, Shezi, Thandiwe Yvonne, Maphanga, Jabulisiwe Lethabo, Jali, Zandile Patrica, Cwele, Thobelani, Gwamanda, Nonhlanhla Zanele Elsie, Dlamini, Celaphiwe, Sing, Zibuyile Phindile Penlee, Ntanjana, Ntombozuko Gloria, Nzimande, Sphelele Simo, Mbatha, Siyabonga, Maharaj, Bhavna, Moosa, Atika, Corris, Cara-Mia, Kafaar, Fazlin, Geldenhuys, Hennie, Luabeya, Angelique Kany Kany, Shenje, Justin, Botes, Natasja, Rossouw, Susan, Africa, Hadn, Diamond, Bongani, Braaf, Samentra, Stryers, Sonia, Carstens, Alida, Jansen, Ruwiyda, Mabwe, Simbarashe, Mulenga, Humphrey, Herling, Roxane, Veldsman, Ashley, Makhete, Lebohgang, Steyn, Marcia, Buhlungu, Sivuyile, Erasmus, Margareth, Davids, Ilse, Plaatjie, Patiswa, Companie, Alessandro, Ratangee, Frances, Veldtsman, Helen, Petersen, Christel, Abrahams, Charmaine, Moses, Miriam, Kelepu, Xoliswa, Gregg, Yolande, Swanepoel, Liticia, Magawu, Nomsitho, Cetywayo, Nompumelelo, Mactavie, Lauren, Valley, Habibullah, Filander, Elizabeth, Nqakala, Nambitha, Maasdorp, Elizna, Khoury, Justine, Kriel, Belinda, Smith, Bronwyn, Muller, Liesel, Tonsing, Susanne, Loxton, Andre, Hiemstra, Andriette, Ahlers, Petri, Flinn, Marika, Chung, Eva, Chung, Michelle, Sato, Alicia, Scriba, Thomas J, Fiore-Gartland, Andrew, Penn-Nicholson, Adam, Kimbung Mbandi, Stanley, Borate, Bhavesh, Mendelsohn, Simon C, Hadley, Katie, Hikuam, Chris, Kaskar, Masooda, Musvosvi, Munyaradzi, Bilek, Nicole, Self, Steven, Sumner, Tom, White, Richard G, Erasmus, Mzwandile, Jaxa, Lungisa, Raphela, Rodney, Innes, Craig, Brumskine, William, Hiemstra, Andriëtte, Malherbe, Stephanus T, Hassan-Moosa, Razia, Tameris, Michèle, Walzl, Gerhard, Naidoo, Kogieleum, Churchyard, Gavin, and Hatherill, Mark

Published
2021
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14. Therapeutic Monoclonal Antibodies for Ebola Virus Infection Derived from Vaccinated Humans

Author

Rijal, Pramila, Elias, Sean C., Machado, Samara Rosendo, Xiao, Julie, Schimanski, Lisa, O’Dowd, Victoria, Baker, Terry, Barry, Emily, Mendelsohn, Simon C., Cherry, Catherine J., Jin, Jing, Labbé, Geneviève M., Donnellan, Francesca R., Rampling, Tommy, Dowall, Stuart, Rayner, Emma, Findlay-Wilson, Stephen, Carroll, Miles, Guo, Jia, Xu, Xiao-Ning, Huang, Kuan-Ying A., Takada, Ayato, Burgess, Gillian, McMillan, David, Popplewell, Andy, Lightwood, Daniel J., Draper, Simon J., and Townsend, Alain R.

Published
2019
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16. OA-490 Safety, reactogenicity and immunogenicity of MTBVAC in newborns in a TB endemic area: a phase 2a randomized, double-blind, dose-defining trial

Author

Tameris, Michele, primary, Barja, Sara, additional, Rozot, Virginie, additional, Imbratta, Claire, additional, Musvosvi, Munyaradzi, additional, Jelsbak, Ingrid Murillo, additional, Geldenhuys, Hennie, additional, Shenje, Justin, additional, Luabeya, Angelique, additional, Mendelsohn, Simon, additional, Tredoux, Nicolette, additional, Fisher, Michelle, additional, Bilek, Nicole, additional, Asma, Toefy, additional, Mabwe, Simbarashe, additional, Doce, Juana, additional, Aguilo, Nacho, additional, Marinova, Dessislava, additional, Puentes, Eugenia, additional, Martin, Carlos, additional, Mukherjee, Rajat, additional, Scriba, Thomas, additional, and Hatherill, Mark, additional

Published
2023
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20. Diagnostic Performance of Host Blood Transcriptomic Signatures for Pulmonary Tuberculosis in a Multi-Cohort Study of Symptomatic Patients in Africa

Author

Muwanga, Vanessa, primary, Mendelsohn, Simon C., additional, Leukes, Vinzeigh, additional, Stanley, Kim, additional, Mbandi, Stanley Kimbung, additional, Erasmus, Mzwandile, additional, Flinn, Marika, additional, Fisher, Tarryn-Lee, additional, Raphela, Rodney, additional, Bilek, Nicole, additional, Malherbe, Stephanus T., additional, Tromp, Gerard, additional, Van der Spuy, Gian, additional, Walzl, Gerhard, additional, Chegou, Novel N., additional, and Scriba, Thomas J., additional

Published
2023
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21. Live-Attenuated M. Tuberculosis Vaccine, MTBVAC, in Adults with or Without M. Tuberculosis Sensitization: A Phase 1b/2a Randomized, Controlled, Double-Blind, Dose-Escalation Trial

Author

Luabeya, Angelique Kany Kany, primary, Rozot, Virginie, additional, Imbratta, Claire, additional, Ratangee, Frances, additional, Shenje, Justin, additional, Tameris, Michèle, additional, Mendelsohn, Simon C., additional, Geldenhuys, Hennie, additional, Fisher, Michelle, additional, Musvosvi, Munyaradzi, additional, Mulenga, Humphrey, additional, Bilek, Nicole, additional, Mabwe, Simbarashe, additional, Murillo Jelsbak, Ingrid, additional, Rodríguez, Esteban, additional, Puentes, Eugenia, additional, Doce, Juana, additional, Aguilo, Nacho, additional, Martin, Carlos, additional, Pillay, Cadwill, additional, Tait, Dereck, additional, Schrager, Lewis, additional, Russell, Marisa, additional, Rutkowski, Kathryn, additional, Hunt, Devin, additional, Scriba, Thomas J., additional, and Hatherill, Mark, additional

Published
2023
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23. IL27 gene expression distinguishes multisystem inflammatory syndrome in children from febrile illness in a South African cohort

Author

Spracklen, Timothy F., primary, Mendelsohn, Simon C., additional, Butters, Claire, additional, Facey-Thomas, Heidi, additional, Stander, Raphaella, additional, Abrahams, Debbie, additional, Erasmus, Mzwandile, additional, Baguma, Richard, additional, Day, Jonathan, additional, Scott, Christiaan, additional, Zühlke, Liesl J., additional, Kassiotis, George, additional, Scriba, Thomas J., additional, and Webb, Kate, additional

Published
2022
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24. Isoniazid preventive therapy and tuberculosis transcriptional signatures in people with HIV

Author

Valinetz, Ethan D., primary, Matemo, Daniel, additional, Gersh, Jill K., additional, Joudeh, Lara L., additional, Mendelsohn, Simon C., additional, Scriba, Thomas J., additional, Hatherill, Mark, additional, Kinuthia, John, additional, Wald, Anna, additional, Cangelosi, Gerard A., additional, Barnabas, Ruanne V., additional, Hawn, Thomas R., additional, and Horne, David J., additional

Published
2022
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25. Mycobacterium tuberculosis infection, immune activation, and risk of HIV acquisition

Author

Bender Ignacio, Rachel A., primary, Long, Jessica, additional, Saha, Aparajita, additional, Nguyen, Felicia K., additional, Joudeh, Lara, additional, Valinetz, Ethan, additional, Mendelsohn, Simon C., additional, Scriba, Thomas J., additional, Hatherill, Mark, additional, Janes, Holly, additional, Churchyard, Gavin, additional, Buchbinder, Susan, additional, Duerr, Ann, additional, Shah, Javeed A., additional, and Hawn, Thomas R., additional

Published
2022
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26. Molecular Detection of Airborne Mycobacterium tuberculosis in South African High Schools

Author

Bunyasi, Erick W., primary, Middelkoop, Keren, additional, Koch, Anastasia, additional, Hoosen, Zeenat, additional, Mulenga, Humphrey, additional, Luabeya, Angelique K. K., additional, Shenje, Justin, additional, Mendelsohn, Simon C., additional, Tameris, Michele, additional, Scriba, Thomas J., additional, Warner, Digby F., additional, Wood, Robin, additional, Andrews, Jason R., additional, and Hatherill, Mark, additional

Published
2022
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27. Mycobacterium tuberculosisinfection, immune activation, and risk of HIV acquisition

Author

Bender Ignacio, Rachel A., primary, Long, Jessica, additional, Saha, Aparajita, additional, Nguyen, Felicia K., additional, Joudeh, Lara, additional, Valinetz, Ethan, additional, Mendelsohn, Simon C., additional, Scriba, Thomas J., additional, Hatherill, Mark, additional, Janes, Holly, additional, Churchyard, Gavin, additional, Buchbinder, Susan, additional, Duerr, Ann, additional, Shah, Javeed A., additional, and Hawn, Thomas R., additional

Published
2021
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29. Utility of a three-gene transcriptomic signature in the diagnosis of tuberculosis in a low-endemic hospital setting.

Author

Chendi, Bih Hycenta, Jooste, Tracey, Scriba, Thomas Jens, Kidd, Martin, Mendelsohn, Simon, Tonby, Kristian, Walzl, Gerhard, Dyrhol-Riise, Anne M., and Chegou, Novel Njweipi

Subjects
RECEIVER operating characteristic curves, TUBERCULOSIS, TRANSCRIPTOMES, RESPIRATORY infections, SYMPTOMS
Abstract

Host transcriptomic blood signatures have demonstrated diagnostic potential for tuberculosis (TB), requiring further validation across different geographical settings. Discriminating TB from other diseases with similar clinical manifestations is crucial for the development of an accurate immunodiagnostic tool. In this exploratory cohort study, we evaluated the performance of potential blood-based transcriptomic signatures in distinguishing TB disease from non-TB lower respiratory tract infections in hospitalised patients in a TB low-endemic country. Quantitative real-time polymerase chain reaction qPCR) was used to evaluate 26 previously published genes in blood from 31 patients (14 TB and 17 lower respiratory tract infection cases) admitted to Oslo University Hospital in Norway. The diagnostic accuracies of differentially expressed genes were determined by receiver operating characteristic curves. A significant difference (p <.01) in the age distribution was observed between patients with TB (mean age, 40 ± 15 years) and lower respiratory tract infection (mean age 59 ± 12 years). Following adjustment for age, ETV7, GBP1, GBP5, P2RY14 and BLK were significantly differentially expressed between patients with TB and those with LRI. A general discriminant analysis generated a three-gene signature (BAFT2, ETV7 and CD1C), which diagnosed TB with an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, 0.69 − 1.00), sensitivity of 69.23% (95% CI, 38.57%−90.91%) and specificity of 94.12% (95% CI, 71.31%−99.85%). The three-genes signature may have potential to improve diagnosis of TB in a hospitalised low-burden setting. However, the influence of confounding variables or covariates such as age requires further evaluation in larger studies. [ABSTRACT FROM AUTHOR]

Published
2023
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32. Additional file 1 of The impact of blood transcriptomic biomarker targeted tuberculosis preventive therapy in people living with HIV: a mathematical modelling study

Author

Sumner, Tom, Mendelsohn, Simon C., Scriba, Thomas J., Hatherill, Mark, and White, Richard G.

Abstract

Additional file 1. Additional details of model, results of model fitting and results of parameter sensitivity analysis. Figure S1. Model structure. Figure S2. Cumulative incidence of TB by time since infection used to calculate the model parameters. Table S1. Parameters used to distribute new infections to recent latent states. Table S2. Prior parameter distributions used in model fitting. Table S3. Observed and fitted TB incidence (per 100 person years). Table S4. Posterior parameter ranges by sub-group. Figure S3. Partial rank correlation coefficients for the model parameters.

Published
2021
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33. 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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34. Biomarker-guided tuberculosis preventive therapy (CORTIS): a randomised controlled trial

Author

Scriba, Thomas J, primary, Fiore-Gartland, Andrew, additional, Penn-Nicholson, Adam, additional, Mulenga, Humphrey, additional, Kimbung Mbandi, Stanley, additional, Borate, Bhavesh, additional, Mendelsohn, Simon C, additional, Hadley, Katie, additional, Hikuam, Chris, additional, Kaskar, Masooda, additional, Musvosvi, Munyaradzi, additional, Bilek, Nicole, additional, Self, Steven, additional, Sumner, Tom, additional, White, Richard G, additional, Erasmus, Mzwandile, additional, Jaxa, Lungisa, additional, Raphela, Rodney, 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, Hatherill, Mark, additional, Baepanye, Kesenogile, additional, Baepanye, Tshepiso, additional, Clarke, Ken, additional, Collignon, Marelize, additional, Dlamini, Audrey, additional, Eyre, Candice, additional, Feni, Tebogo, additional, Fikizolo, Moogo, additional, Galane, Phinda, additional, Goliath, Thelma, additional, Gangat, Alia, additional, Malefo-Grootboom, Shirley, additional, Janse van Rensburg, Elba, additional, Janse van Rensburg, Bonita, additional, Kekana, Sophy, additional, Zietsman, Marietjie, additional, Kock, Adrianne, additional, Kunene, Israel, additional, Lakhi, Aneessa, additional, Langa, Nondumiso, additional, Ledwaba, Hilda, additional, Luphoko, Marillyn, additional, Mabasa, Immaculate, additional, Mabe, Dorah, additional, Mabuza, Nkosinathi, additional, Majola, Molly, additional, Makhetha, Mantai, additional, Makoanyane, Mpho, additional, Makhubalo, Blossom, additional, Malay, Vernon, additional, Market, Juanita, additional, Matshego, Selvy, additional, Mbipa, Nontsikelelo, additional, Mmotsa, Tsiamo, additional, Modipa, Sylvester, additional, Mopati, Samuel, additional, Moswegu, Palesa, additional, Mothaga, Primrose, additional, Muller, Dorothy, additional, Nchwe, Grace, additional, Nel, Maryna, additional, Nhlangulela, Lindiwe, additional, Ntamo, Bantubonke, additional, Ntoahae, Lawerence, additional, Ntshauba, Tedrius, additional, Sanyaka, Nomsa, additional, Seabela, Letlhogonolo, additional, Selepe, Pearl, additional, Senne, Melissa, additional, Serake, MG, additional, Thlapi, Maria, additional, Tshikovhi, Vincent, additional, Tswaile, Lebogang, additional, van Aswegen, Amanda, additional, Mbata, Lungile, additional, Takavamanya, Constance, additional, Pinho, Pedro, additional, Mdlulu, John, additional, Taljaard, Marthinette, additional, Slabbert, Naydene, additional, Sayed, Sharfuddin, additional, Nielson, Tanya, additional, Ni Sein, Ni, additional, Govender, Dhineshree, additional, Chinappa, Tilagavathy, additional, Zulu, Mbali Ignatia, additional, Maphanga, Nonhle Bridgette, additional, Hlathi, Senzo Ralph, additional, Gumede, Goodness Khanyisile, additional, Shezi, Thandiwe Yvonne, additional, Maphanga, Jabulisiwe Lethabo, additional, Jali, Zandile Patrica, additional, Cwele, Thobelani, additional, Gwamanda, Nonhlanhla Zanele Elsie, additional, Dlamini, Celaphiwe, additional, Sing, Zibuyile Phindile Penlee, additional, Ntanjana, Ntombozuko Gloria, additional, Nzimande, Sphelele Simo, additional, Mbatha, Siyabonga, additional, Maharaj, Bhavna, additional, Moosa, Atika, additional, Corris, Cara-Mia, additional, Kafaar, Fazlin, additional, Geldenhuys, Hennie, additional, Luabeya, Angelique Kany Kany, additional, Shenje, Justin, additional, Botes, Natasja, additional, Rossouw, Susan, additional, Africa, Hadn, additional, Diamond, Bongani, additional, Braaf, Samentra, additional, Stryers, Sonia, additional, Carstens, Alida, additional, Jansen, Ruwiyda, additional, Mabwe, Simbarashe, additional, Herling, Roxane, additional, Veldsman, Ashley, additional, Makhete, Lebohgang, additional, Steyn, Marcia, additional, Buhlungu, Sivuyile, additional, Erasmus, Margareth, additional, Davids, Ilse, additional, Plaatjie, Patiswa, additional, Companie, Alessandro, additional, Ratangee, Frances, additional, Veldtsman, Helen, additional, Petersen, Christel, additional, Abrahams, Charmaine, additional, Moses, Miriam, additional, Kelepu, Xoliswa, additional, Gregg, Yolande, additional, Swanepoel, Liticia, additional, Magawu, Nomsitho, additional, Cetywayo, Nompumelelo, additional, Mactavie, Lauren, additional, Valley, Habibullah, additional, Filander, Elizabeth, additional, Nqakala, Nambitha, additional, Maasdorp, Elizna, additional, Khoury, Justine, additional, Kriel, Belinda, additional, Smith, Bronwyn, additional, Muller, Liesel, additional, Tonsing, Susanne, additional, Loxton, Andre, additional, Hiemstra, Andriette, additional, Ahlers, Petri, additional, Flinn, Marika, additional, Chung, Eva, additional, Chung, Michelle, additional, and Sato, Alicia, additional

Published
2021
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35. Clinical Predictors of Pulmonary Tuberculosis Among South African Adults With HIV

Author

Mendelsohn, Simon C., primary, Fiore-Gartland, Andrew, additional, Awany, Denis, additional, Mulenga, Humphrey, additional, Mbandi, Stanley Kimbung, additional, Tameris, Michèle, additional, Walzl, Gerhard, additional, Naidoo, Kogieleum, additional, Churchyard, Gavin, additional, Scriba, Thomas J., additional, Hatherill, Mark, additional, and Team, CORTIS-HR Study, additional

Published
2021
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38. Peripheral Blood Mucosal-Associated Invariant T Cells in Tuberculosis Patients and Healthy Mycobacterium tuberculosis-Exposed Controls

Author

Suliman, Sara, primary, Gela, Anele, additional, Mendelsohn, Simon C, additional, Iwany, Sarah K, additional, Tamara, Kattya Lopez, additional, Mabwe, Simbarashe, additional, Bilek, Nicole, additional, Darboe, Fatoumatta, additional, Fisher, Michelle, additional, Corbett, Alexandra J, additional, Kjer-Nielsen, Lars, additional, Eckle, Sidonia B G, additional, Huang, Chuan-Chin, additional, Zhang, Zibiao, additional, Lewinsohn, David M, additional, McCluskey, James, additional, Rossjohn, Jamie, additional, Hatherill, Mark, additional, León, Segundo R, additional, Calderon, Roger I, additional, Lecca, Leonid, additional, Murray, Megan, additional, Scriba, Thomas J, additional, Van Rhijn, Ildiko, additional, and Moody, D Branch, additional

Published
2020
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40. Molecular Detection of Airborne in South African High Schools.

Author

Bunyasi, Erick W., Middelkoop, Keren, Koch, Anastasia, Hoosen, Zeenat, Mulenga, Humphrey, Luabeya, Angelique K. K., Shenje, Justin, Mendelsohn, Simon C., Tameris, Michele, Scriba, Thomas J., Warner, Digby F., Wood, Robin, Andrews, Jason R., and Hatherill, Mark

Abstract

Rationale: South African adolescents carry a high tuberculosis disease burden. It is not known if schools are high-risk settings for Mycobacterium tuberculosis (MTB) transmission. Objectives: To detect airborne MTB genomic DNA in classrooms. Methods: We studied 72 classrooms occupied by 2,262 students in two South African schools. High-volume air filtration was performed for median 40 (interquartile range [IQR], 35-54) minutes and assayed by droplet digital PCR (ddPCR)-targeting MTB region of difference 9 (RD9), with concurrent CO2 concentration measurement. Classroom data were benchmarked against public health clinics. Students who consented to individual tuberculosis screening completed a questionnaire and sputum collection (Xpert MTB/RIF Ultra) if symptom positive. Poisson statistics were used for MTB RD9 copy quantification. Measurements and Main Results: ddPCR assays were positive in 13/72 (18.1%) classrooms and 4/39 (10.3%) clinic measurements (P = 0.276). Median ambient CO2 concentration was 886 (IQR, 747-1223) ppm in classrooms versus 490 (IQR, 405-587) ppm in clinics (P < 0.001). Average airborne concentration of MTB RD9 was 3.61 copies per 180,000 liters in classrooms versus 1.74 copies per 180,000 liters in clinics (P = 0.280). Across all classrooms, the average risk of an occupant inhaling one MTB RD9 copy was estimated as 0.71% during one standard lesson of 35 minutes. Among 1,836/2,262 (81.2%) students who consented to screening, 21/90 (23.3%) symptomatic students produced a sputum sample, of which one was Xpert MTB/RIF Ultra positive. Conclusions: Airborne MTB genomic DNA was detected frequently in high school classrooms. Instantaneous risk of classroom exposure was similar to the risk in public health clinics. [ABSTRACT FROM AUTHOR]

Published
2022
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41. Longitudinal Dynamics of a Blood Transcriptomic Signature of Tuberculosis.

Author

Mulenga, Humphrey, Musvosvi, Munyaradzi, Mendelsohn, Simon C., Penn-Nicholson, Adam, Mbandi, Stanley Kimbung, Fiore-Gartland, Andrew, Tameris, Michele, Mabwe, Simbarashe, Africa, Hadn, Bilek, Nicole, Kafaar, Fazlin, Khader, Shabaana A., Carstens, Balie, Hadley, Katie, Hikuam, Chris, Erasmus, Mzwandile, Jaxa, Lungisa, Raphela, Rodney, Nombida, Onke, and Kaskar, Masooda

Subjects
TUBERCULOSIS, BIOMARKERS, RESPIRATORY infections, HIV, MESSENGER RNA
Abstract

Rationale: Performance of blood transcriptomic tuberculosis (TB) signatures in longitudinal studies and effects of TB-preventive therapy and coinfection with HIV or respiratory organisms on transcriptomic signatures has not been systematically studied. Objectives: We evaluated longitudinal kinetics of an 11-gene blood transcriptomic TB signature, RISK11, and effects of TB-preventive therapy (TPT) and respiratory organisms on RISK11 signature score, in HIV-uninfected and HIV-infected individuals. Methods: RISK11 was measured in a longitudinal study of RISK11-guided TPT in HIV-uninfected adults, a cross-sectional respiratory organisms cohort, or a longitudinal study in people living with HIV (PLHIV). HIV-uninfected RISK11+ participants were randomized to TPT or no TPT; RISK11- participants received no TPT. PLHIV received standard-of-care antiretroviral therapy and TPT. In the cross-sectional respiratory organisms cohort, viruses and bacteria in nasopharyngeal and oropharyngeal swabs were quantified by real-time quantitative PCR. Measurements and Main Results: RISK11+ status was transient in most of the 128 HIV-negative participants with longitudinal samples; more than 70% of RISK11+ participants reverted to RISK11- by 3 months, irrespective of TPT. By comparison, reversion from a RISK11+ state was less common in 645 PLHIV (42.1%). Non-HIV viral and nontuberculous bacterial organisms were detected in 7.2% and 38.9% of the 1,000 respiratory organisms cohort participants, respectively, and among those investigated for TB, 3.8% had prevalent disease. Median RISK11 scores (%) were higher in participants with viral organisms alone (46.7%), viral and bacterial organisms (42.8%), or prevalent TB (85.7%) than those with bacterial organisms other than TB (13.4%) or no organisms (14.2%). RISK11 could not discriminate between prevalent TB and viral organisms. Conclusions: Positive RISK11 signature status is often transient, possibly due to intercurrent viral infection, highlighting potentially important challenges for implementation of these biomarkers as new tools for TB control. [ABSTRACT FROM AUTHOR]

Published
2021
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42. Prospective Validation of a Host Blood Transcriptomic Biomarker for Pulmonary Tuberculosis in People Living with HIV: A 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, and Team, CORTIS-HR Study, additional

Published
2020
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