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(1) In children with CKD, decreased sKl might be a marker of elevated central blood pressure. (2) Both sKl decrease and FGF23 increase could possibly contribute to left ventricular hypertrophy in this group of patients.

(1) In children with CKD, decreased sKl might be a marker of elevated central blood pressure. (2) Both sKl decrease and FGF23 increase could possibly contribute to left ventricular hypertrophy in this group of patients.Introduction. Linezolid-resistant (LZR) Staphylococcus capitis has recently emerged in our hospital, and its potential resistance mechanisms are still not clear.Aim. This study aimed to investigate the epidemiology, clinical and genetic characteristics, resistance mechanisms and biofilm formation capacity of LZR S. capitis isolated from patients at Huashan Hospital, Shanghai, PR China between 2012 and 2018.Methodology. Strains were subjected to antimicrobial susceptibility testing (AST) with antibiotics using the broth microdilution method according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. The presence of cfr, optrA and poxtA, as well as mutations in the 23S ribosomal (r)RNA and ribosomal proteins, was investigated using PCR and sequencing techniques. The genetic relationship between isolates was analysed using pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing (WGS). Biofilm biomasses were detected by using crystal violet staining.Results. Twenty-one LZR S. capitis strains displayed MICs of 32-512 μg ml-1. All LZR strains showed G2576T and C2104T mutations in the 23S rRNA V region. Cytarabine cost Besides G2576T and C2104T, no base mutations were detected in the V region. The cfr was detected in 12 strains, while optrA and poxtA were not amplified in 21 S. capitis strains. PFGE showed that the LZR S. capitis strains belonged to a single clone. The phylogenetic tree showed that 20 LZR S. capitis strains were highly similar to LNZR-1, isolated from Harbin (located in the north of China) in 2013, which showed resistance to linezolid.Conclusions. In this research, cfr-negative strains displayed linezolid MICs of 32 μg ml-1. In comparison, cfr-positive strains exhibited linezolid MICs of 128-512 μg ml-1, indicating that high levels of linezolid resistance appear to be related to the presence of cfr. The outbreak of LZR S. capitis in our hospital needs to be monitored closely.Background Neurologic complications in coronavirus disease 2019 (COVID-19) have been described, but the understanding of their pathophysiologic causes and neuroanatomical correlates remains limited. Purpose To report on the frequency and type of neuroradiological findings in COVID-19. Materials and Methods In this retrospective study, all consecutive adult hospitalized patients with polymerase chain reaction positivity for severe acute respiratory syndrome coronavirus 2 and who underwent neuroimaging at Karolinska University Hospital between March 2 and May 24, 2020, were included. All examinations were systematically re-evaluated by 12 readers. Summary descriptive statistics were calculated. Results A total of 185 patients with COVID-19 (62 years ± 14 [standard deviation]; 138 men) underwent neuroimaging. In total, 222 brain CT, 47 brain MRI, and seven spinal MRI examinations were performed. Intra-axial susceptibility abnormalities were the most common finding (29 of 39; 74%, 95% CI 58, 87) in patients who utient each, respectively, which is suggestive of dynamic processes. Conclusion Patients with coronavirus disease 2019 had a wide spectrum of vascular and inflammatory involvement of both the central and peripheral nervous system. © RSNA, 2020 Online supplemental material is available for this article.The World Health Organization (WHO) undertook the development of a rapid guide on the use of chest imaging in the diagnosis and management of coronavirus disease 2019 (COVID-19). The rapid guide was developed over 2 months by using standard WHO processes, except for the use of "rapid reviews" and online meetings of the panel. The evidence review was supplemented by a survey of stakeholders regarding their views on the acceptability, feasibility, impact on equity, and resource use of the relevant chest imaging modalities (chest radiography, chest CT, and lung US). The guideline development group had broad expertise and country representation. The rapid guide includes three diagnosis recommendations and four management recommendations. The recommendations cover patients with confirmed or who are suspected of having COVID-19 with different levels of disease severity, throughout the care pathway from outpatient facility or hospital entry to home discharge. All recommendations are conditional and are based on low certainty evidence (n = 2), very low certainty evidence (n = 2), or expert opinion (n = 3). The remarks accompanying the recommendations suggest which patients are likely to benefit from chest imaging and what factors should be considered when choosing the specific imaging modality. The guidance offers considerations about implementation, monitoring, and evaluation, and also identifies research needs. Published under a CC BY 4.0 license. Online supplemental material is available for this article.Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may be of assistance when results from definitive viral testing are delayed. Purpose To develop and validate an artificial intelligence (AI) system to score the likelihood and extent of pulmonary COVID-19 on chest CT scans using the COVID-19 Reporting and Data System (CO-RADS) and CT severity scoring systems. Materials and Methods The CO-RADS AI system consists of three deep-learning algorithms that automatically segment the five pulmonary lobes, assign a CO-RADS score for the suspicion of COVID-19, and assign a CT severity score for the degree of parenchymal involvement per lobe. This study retrospectively included patients who underwent a nonenhanced chest CT examination because of clinical suspicion of COVID-19 at two medical centers. The system was trained, validated, and tested with data from one of the centers.