Nature medicine
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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has dramatically expedited global vaccine development efforts1-3, most targeting the viral 'spike' glycoprotein (S). S localizes on the virion surface and mediates recognition of cellular receptor angiotensin-converting enzyme 2 (ACE2)4-6. Eliciting neutralizing antibodies that block S-ACE2 interaction7-9, or indirectly prevent membrane fusion10, constitute an attractive modality for vaccine-elicited protection11. ⋯ Comparatively low frequencies of B cells or cTFH specific for the receptor binding domain of S were elicited. Notably, the phenotype of S-specific cTFH differentiated subjects with potent neutralizing responses, providing a potential biomarker of potency for S-based vaccines entering the clinic. Overall, although patients who recovered from COVID-19 displayed multiple hallmarks of effective immune recognition of S, the wide spectrum of neutralizing activity observed suggests that vaccines might require strategies to selectively target the most potent neutralizing epitopes.
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As of 10 April 2020, New York State had 180,458 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 9,385 reported deaths. Patients with cancer comprised 8.4% of deceased individuals1. Population-based studies from China and Italy suggested a higher coronavirus disease 2019 (COVID-19) death rate in patients with cancer2,3, although there is a knowledge gap as to which aspects of cancer and its treatment confer risk of severe COVID-194. ⋯ Age older than 65 years and treatment with immune checkpoint inhibitors (ICIs) were predictors for hospitalization and severe disease, whereas receipt of chemotherapy and major surgery were not. Overall, COVID-19 in patients with cancer is marked by substantial rates of hospitalization and severe outcomes. The association observed between ICI and COVID-19 outcomes in our study will need further interrogation in tumor-specific cohorts.
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For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. ⋯ In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT-PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.