Pneumatocele formation following COVID-19 pneumonia

A 61-year-old man with no significant medical history presented to the emergency department with worsening dyspnea a week after close con-tact with someonewhohad COVID-19. Hewas unvaccinated. He washypoxemic, and the chest radiograph showed bilateralopacities consistent withCOVID-19 pneumonia and tested positive for RNA from SARS-CoV-2. Blood tests showed raised inflammatory markers. Computed tomography (CT)of the chest demonstrated bilateralground-glass opacities. Thepatient washospitalized andtreated with high-flow nasaloxygentherapy, dexameth-asone, and sarilumab. His clinical status improved, and hewas discharged home after 1 week of hospitalization.Three weekslater, hepresented againwith worsening dyspnea, fever, and pleuritic chest pain. A CT pulmonary angiography ruled out pulmonary embolism (Fig. 1A, B) but demonstrated athin-walled cystic lesion with an air–fluid level (Fig. 1A, arrowheads) that suggested an infected pneumatocele. The patient was managed conserva-tively with amoxicillin/clavulanic acid for 3 weeks. During the follow-up, the patient reported the disappearance of symptomatology

OPTIMADE, an API for exchanging materials data.

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

OPTIMADE, an API for exchanging materials data

: The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

Pneumatocele formation following COVID-19 pneumonia

A 61-year-old man with no significant medical history presented to the emergency department with worsening dyspnea a week after close con-tact with someonewhohad COVID-19. Hewas unvaccinated. He washypoxemic, and the chest radiograph showed bilateralopacities consistent withCOVID-19 pneumonia and tested positive for RNA from SARS-CoV-2. Blood tests showed raised inflammatory markers. Computed tomography (CT)of the chest demonstrated bilateralground-glass opacities. Thepatient washospitalized andtreated with high-flow nasaloxygentherapy, dexameth-asone, and sarilumab. His clinical status improved, and hewas discharged home after 1 week of hospitalization.Three weekslater, hepresented againwith worsening dyspnea, fever, and pleuritic chest pain. A CT pulmonary angiography ruled out pulmonary embolism (Fig. 1A, B) but demonstrated athin-walled cystic lesion with an air–fluid level (Fig. 1A, arrowheads) that suggested an infected pneumatocele. The patient was managed conserva-tively with amoxicillin/clavulanic acid for 3 weeks. During the follow-up, the patient reported the disappearance of symptomatology

Using Public Landslide Inventories for Landslide Susceptibility Assessment at the Basin Scale: Application to the Torto River Basin (Central-Northern Sicily, Italy)

In statistical landslide susceptibility evaluation, the quality of the model and its prediction image heavily depends on the quality of the landslide inventories used for calibration. However, regional-scale inventories made available by public territorial administrations are typically affected by an unknown grade of incompleteness and mapping inaccuracy. In this research, a procedure is proposed for verifying and solving such limits by applying a two-step susceptibility modeling procedure. In the Torto River basin (central-northern Sicily, Italy), using an available regional landslide inventory (267 slide and 78 flow cases), two SUFRA_1 models were first prepared and used to assign a landslide susceptibility level to each slope unit (SLU) in which the study area was partitioned. For each of the four susceptibility classes that were obtained, 30% of the mapping units were randomly selected and their stable/unstable status was checked by remote analysis. The new, increased inventories were finally used to recalibrate two SUFRA_2 models. The prediction skills of the SUFRA_1 and SUFRA_2 models were then compared by testing their accuracy in matching landslide distribution in a test sub-basin where a high-resolution systematic inventory had been prepared. According to the results, the strong limits of the SUFRA_1 models (sensitivity: 0.67 and 0.57 for slide and flow, respectively) were largely solved by the SUFRA_2 model (sensitivity: 1 for both slide and flow), suggesting the proposed procedure as a possibly suitable modeling strategy for regional susceptibility studies