Objective: This study presents a preliminary report on the chest radiographic and computed tomography (CT) findings of the 2019 novel coronavirus disease (COVID-19) pneumonia in Korea. Materials and Methods: As part of a multi-institutional collaboration coordinated by the Korean Society of Thoracic Radiology, we collected nine patients with COVID-19 infections who had undergone chest radiography and CT scans. We analyzed the radiographic and CT findings of COVID-19 pneumonia at baseline. Fisher's exact test was used to compare CT findings depending on the shape of pulmonary lesions. Results: Three of the nine patients (33.3%) had parenchymal abnormalities detected by chest radiography, and most of the abnormalities were peripheral consolidations. Chest CT images showed bilateral involvement in eight of the nine patients, and a unilobar reversed halo sign in the other patient. In total, 77 pulmonary lesions were found, including patchy lesions (39%), large confluent lesions (13%), and small nodular lesions (48%). The peripheral and posterior lung fields were involved in 78% and 67% of the lesions, respectively. The lesions were typically ill-defined and were composed of mixed ground-glass opacities and consolidation or pure ground-glass opacities. Patchy to confluent lesions were primarily distributed in the lower lobes (p = 0.040) and along the pleura (p < 0.001), whereas nodular lesions were primarily distributed along the bronchovascular bundles (p = 0.006). Conclusion: COVID-19 pneumonia in Korea primarily manifested as pure to mixed ground-glass opacities with a patchy to confluent or nodular shape in the bilateral peripheral posterior lungs. A considerable proportion of patients with COVID-19 pneumonia had normal chest radiographs.

Bridged-ring systems are widely found in natural products and successful syntheses of them frequently feature intramolecular Diels-Alder (IMDA) reactions. These reactions are subclassified as either type I or type II IMDAs depending on how the diene motif is tethered to the rest of the substrate - type I are tethered at the 1-position of the diene and type II at the 2-position. While the type I IMDA has been used to great success, the molecular scaffolds accessible by type II IMDAs are limited by the strain inherent in the formation of a sp2-carbon at a bridgehead position. Here, we describe a complementary approach that provides access to these structures through the C−C activation of cyclobutanones and their coupling with olefins. Various alkenes have been coupled with cyclobutanones to provide a range of bridged skeletons. The ketone group of the products serves as a convenient handle for downstream functionalization.

In COVID-19 patients, considerable variation was found in the QCTmass (72.4±120.8 g; range, 0.7-420.7 g) and relative 3D opacity extent on CT (3.2±5.8% of lung area; range, 0.1-19.8%). 2. Chest radiographs in patients under investigation for COVID-19 provided a sensitivity of 25% (5/20) and specificity of 90% (18/20) for COVID-19-related opacities. 3. The QCTmass (p<.001) and the 3D opacity volume on CT (p<.001) significantly affected the visibility of COVID-19-related opacities on radiographs. I n p r e s s Summary Statement Quantitative opacity mass and 3D opacity volume on CT were quantifiable metrics affecting the visibility of COVID-19-related opacities on chest radiographs.

Here we report the first highly enantioselective Rh-catalyzed carboacylation of olefins via C-C bond activation of benzocyclobutenones. Good yields and excellent enantioselectivities (92-99% ee, 14 examples) were obtained for substrates with various steric and electronic properties. In addition, fully saturated poly-fused rings were prepared from the carboacylation products through a challenging catalytic reductive dearomatization approach. These investigations provide a distinct way to prepare chiral carbon frameworks that are nontrivial to access with conventional methods.

This erratum corrects an error in the software listed for automatic generation of a volumetric mask of the lungs, lobes, intrapulmonary vessels, and airways. In Quantitative CT analysis, first paragraph, first sentence, the software should be listed as follows: "After uploading CT images from each patient to commercially available segmentation software (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd., Seoul, Korea), a deep neural network (Deep Catch v1.0.0.0, MEDICALIP Co. Ltd., Seoul, Korea), automatically generated a volumetric mask of the lungs, lobes, intrapulmonary vessels, and airways. The change was made online on April 6, 2020.