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Briggs, James

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Briggs

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Briggs, James
Author's Publications: search.filters.isAuthorOfPublication.5c932fed-1c52-4ddf-9e4e-c9cb598e48a4

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    Publication
    Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing
    (Springer Science and Business Media LLC, 2020-08-26) Allen, William; Altae-Tran, Han; Briggs, James; Jin, Xin; McGee, Glen; Shi, Andy; Raghavan, Rumya; Kamariza, Mireille; Nova, Nicole; Pereta, Albert; Danford, Chris; Kamel, Amine; Gothe, Patrik; Milam, Evrhet; Aurambault, Jean; Primke, Thorben; Li, Weijie; Inkenbrandt, Josh; Huynh, Tuan; Chen, Evan; Lee, Christina; Croatto, Michael; Bentley, Helen; Lu, Wendy; Murray, Robert; Travassos, Mark; Coull, Brent; Openshaw, John; Greene, Casey S.; Shalem, Ophir; King, Gary; Probasco, Ryan; Cheng, David R.; Silbermann, Ben; Zhang, Feng; Lin, Xihong
    Despite the widespread implementation of public health measures, COVID-19 continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, show a variety of exposure, occupation, and demographic risk factors for COVID-19 beyond symptoms, reveal factors for which users have been SARS-CoV-2 PCR tested, and highlight the temporal dynamics of symptoms and self-isolation behavior. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure, and behavioral self-reported data to fight the COVID-19 pandemic.
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    Publication
    Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behaviour, and Testing
    (Nature Human Behaviour, 2020-08-26) Allen, William E.; Altae-Tran, Han; Briggs, James; Jin, Xin; McGee, Glen; Shi, Andy; Raghavan, Rumya; Kamariza, Mireille; Nova, Nicole; Pereta, Albert; Danford, Chris; Kamel, Amine; Gothe, Patrik; Milam, Evrhet; Aurambault, Jean; Primke, Thorben; Li, Weijie; Inkenbrandt, Josh; Huynh, Tuan; Chen, Evan; Lee, Christina; Croatto, Michael; Bentley, Helen; Lu, Wendy; Murray, Robert; Travassos, Mark; Coull, Brent; Openshaw, John; Greene, Casey S.; Shalem, Ophir; King, Gary; Probasco, Ryan; Cheng, David R.; Silbermann, Ben; Zhang, Feng; Lin, Xihong
    Despite the widespread implementation of public health measures, COVID-19 continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, show a variety of exposure, occupation, and demographic risk factors for COVID-19 beyond symptoms, reveal factors for which users have been SARS-CoV-2 PCR tested, and highlight the temporal dynamics of symptoms and self-isolation behavior. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure, and behavioral self-reported data to fight the COVID-19 pandemic.
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    Publication
    Mouse embryonic stem cells can differentiate via multiple paths to the same state
    (eLife Sciences Publications, Ltd, 2017) Briggs, James; Li, Victor; Lee, Seungkyu; Woolf, Clifford; Klein, Allon; Kirschner, Marc
    In embryonic development, cells differentiate through stereotypical sequences of intermediate states to generate particular mature fates. By contrast, driving differentiation by ectopically expressing terminal transcription factors (direct programming) can generate similar fates by alternative routes. How differentiation in direct programming relates to embryonic differentiation is unclear. We applied single-cell RNA sequencing to compare two motor neuron differentiation protocols: a standard protocol approximating the embryonic lineage, and a direct programming method. Both initially undergo similar early neural commitment. Later, the direct programming path diverges into a novel transitional state rather than following the expected embryonic spinal intermediates. The novel state in direct programming has specific and uncharacteristic gene expression. It forms a loop in gene expression space that converges separately onto the same final motor neuron state as the standard path. Despite their different developmental histories, motor neurons from both protocols structurally, functionally, and transcriptionally resemble motor neurons isolated from embryos.