Radiographers and COVID-19 pneumonia: diagnostic performance using CO-RADS

Introduction: A more structured role of radiographers is advisable to speed up the management of patients with suspected COVID-19. The purpose of our study was to evaluate the diagnostic performance of radiographers in the detection of COVID-19 pneumonia on chest CT using CO-RADS descriptors. Methods: CT images of patients who underwent RT-PCR and chest CT due to COVID-19 suspicion between March and July 2020 were analysed retrospectively. Six readers, including two radiologists, two highly experienced radiographers and two less experienced radiographers, independently scored each CT using the CO-RADS lexicon. ROC curves were used to investigate diagnostic accuracy, and Fleiss’κ statistics to evaluate inter-rater agreement. Results: 714 patients (419 men; 295 women; mean age: 64 years ±19SD) were evaluated. CO-RADS> 3 was identified as optimal diagnostic threshold. Highly experienced radiographers achieved an average sensitivity of 58.7% (95%CI: 52.5–64.7), an average specificity of 81.8% (95%CI: 77.9–85.2), and a mean AUC of 0.72 (95%CI: 0.68–0.75). Among less experienced radiographers, an average sensitivity of 56.3% (95%CI: 50.1–62.2) and an average specificity of 81.5% (95%CI: 77.6–84.9) were observed, with a mean AUC of 0.71 (95%CI: 0.68–0.74). Consultant radiologists achieved an average sensitivity of 60.0% (95%CI: 53.7–65.8), an average specificity of 81.7% (95%CI: 77.8–85.1), and a mean AUC of 0.73 (95%CI: 0.70–0.77). Conclusion: Radiographers can adequately recognise the classic appearances of COVID-19 on CT, as described by the CO-RADS assessment scheme, in a way comparable to expert radiologists. Implications for practice: Radiographers, as the first healthcare professionals to evaluate CT images in patients with suspected SARS-CoV-2 infection, could diagnose COVID-19 pneumonia by means of a categorical reporting scheme at CT in a reliable way, hence playing a primary role in the early management of these patients

Diagnostic accuracy and interobserver variability of CO-RADS in patients with suspected coronavirus disease-2019: a multireader validation study

Objective: To conduct a multireader validation study to evaluate the interobserver variability and the diagnostic accuracy for the lung involvement by COVID-19 of COVID-19 Reporting and Data System (CO-RADS) score. Methods: This retrospective study included consecutive symptomatic patients who underwent chest CT and reverse transcriptase-polymerase chain reaction (RT-PCR) from March 2020 to May 2020 for suspected COVID-19. Twelve readers with different levels of expertise independently scored each CT using the CO-RADS scheme for detecting pulmonary involvement by COVID-19. Receiver operating characteristic (ROC) curves were computed to investigate diagnostic yield. Fleiss’ kappa statistics was used to evaluate interreader agreement. Results: A total of 572 patients (mean age, 63 ± 20 [standard deviation]; 329 men; 142 patients with COVID-19 and 430 patients without COVID-19) were evaluated. There was a moderate agreement for CO-RADS rating among all readers (Fleiss’ K = 0.43 [95% CI 0.42–0.44]) with a substantial agreement for CO-RADS 1 category (Fleiss’ K = 0.61 [95% CI 0.60–0.62]) and moderate agreement for CO-RADS 5 category (Fleiss’ K = 0.60 [95% CI 0.58–0.61]). ROC analysis showed the CO-RADS score ≥ 4 as the optimal threshold, with a cumulative area under the curve of 0.72 (95% CI 66–78%), sensitivity 61% (95% CI 52–69%), and specificity 81% (95% CI 77–84%). Conclusion: CO-RADS showed high diagnostic accuracy and moderate interrater agreement across readers with different levels of expertise. Specificity is higher than previously thought and that could lead to reconsider the role of CT in this clinical setting. Key Points: • COVID-19 Reporting and Data System (CO-RADS) demonstrated a good diagnostic accuracy for lung involvement by COVID-19 with an average AUC of 0.72 (95% CI 67–75%). • When a threshold of ≥ 4 was used, sensitivity and specificity were 61% (95% CI 52–69%) and 81% (95% CI 76–84%), respectively. • There was an overall moderate agreement for CO-RADS rating across readers with different levels of expertise (Fleiss’ K = 0.43 [95% CI 0.42–0.44])

Uncertainties in the Anti-neutrino Production at Nuclear Reactors

Anti-neutrino emission rates from nuclear reactors are determined from thermal power measurements and fission rate calculations. The uncertainties in these quantities for commercial power plants and their impact on the calculated interaction rates in electron anti-neutrino detectors is examined. We discuss reactor-to-reactor correlations between the leading uncertainties and their relevance to reactor anti-neutrino experiments.Comment: Submitted to Phys Rev

Genomic variation in baboons from central Mozambique unveils complex evolutionary relationships with other Papio species

Background: Gorongosa National Park in Mozambique hosts a large population of baboons, numbering over 200 troops. Gorongosa baboons have been tentatively identified as part of Papio ursinus on the basis of previous limited morphological analysis and a handful of mitochondrial DNA sequences. However, a recent morphological and morphometric analysis of Gorongosa baboons pinpointed the occurrence of several traits intermediate between P. ursinus and P. cynocephalus, leaving open the possibility of past and/or ongoing gene flow in the baboon population of Gorongosa National Park. In order to investigate the evolutionary history of baboons in Gorongosa, we generated high and low coverage whole genome sequence data of Gorongosa baboons and compared it to available Papio genomes. Results: We confirmed that P. ursinus is the species closest to Gorongosa baboons. However, the Gorongosa baboon genomes share more derived alleles with P. cynocephalus than P. ursinus does, but no recent gene flow between P. ursinus and P. cynocephalus was detected when available Papio genomes were analyzed. Our results, based on the analysis of autosomal, mitochondrial and Y chromosome data, suggest complex, possibly male-biased, gene flow between Gorongosa baboons and P. cynocephalus, hinting to direct or indirect contributions from baboons belonging to the “northern” Papio clade, and signal the presence of population structure within P. ursinus. Conclusions: The analysis of genome data generated from baboon samples collected in central Mozambique highlighted a complex set of evolutionary relationships with other baboons. Our results provided new insights in the population dynamics that have shaped baboon diversity

A Computational Study of Elongation Factor G (EFG) Duplicated Genes: Diverged Nature Underlying the Innovation on the Same Structural Template

BACKGROUND: Elongation factor G (EFG) is a core translational protein that catalyzes the elongation and recycling phases of translation. A more complex picture of EFG's evolution and function than previously accepted is emerging from analyzes of heterogeneous EFG family members. Whereas the gene duplication is postulated to be a prominent factor creating functional novelty, the striking divergence between EFG paralogs can be interpreted in terms of innovation in gene function. METHODOLOGY/PRINCIPAL FINDINGS: We present a computational study of the EFG protein family to cover the role of gene duplication in the evolution of protein function. Using phylogenetic methods, genome context conservation and insertion/deletion (indel) analysis we demonstrate that the EFG gene copies form four subfamilies: EFG I, spdEFG1, spdEFG2, and EFG II. These ancient gene families differ by their indispensability, degree of divergence and number of indels. We show the distribution of EFG subfamilies and describe evidences for lateral gene transfer and recent duplications. Extended studies of the EFG II subfamily concern its diverged nature. Remarkably, EFG II appears to be a widely distributed and a much-diversified subfamily whose subdivisions correlate with phylum or class borders. The EFG II subfamily specific characteristics are low conservation of the GTPase domain, domains II and III; absence of the trGTPase specific G2 consensus motif "RGITI"; and twelve conserved positions common to the whole subfamily. The EFG II specific functional changes could be related to changes in the properties of nucleotide binding and hydrolysis and strengthened ionic interactions between EFG II and the ribosome, particularly between parts of the decoding site and loop I of domain IV. CONCLUSIONS/SIGNIFICANCE: Our work, for the first time, comprehensively identifies and describes EFG subfamilies and improves our understanding of the function and evolution of EFG duplicated genes

Identification of Functional Networks of Estrogen- and c-Myc-Responsive Genes and Their Relationship to Response to Tamoxifen Therapy in Breast Cancer

BACKGROUND: Estrogen is a pivotal regulator of cell proliferation in the normal breast and breast cancer. Endocrine therapies targeting the estrogen receptor are effective in breast cancer, but their success is limited by intrinsic and acquired resistance. METHODOLOGY/PRINCIPAL FINDINGS: With the goal of gaining mechanistic insights into estrogen action and endocrine resistance, we classified estrogen-regulated genes by function, and determined the relationship between functionally-related genesets and the response to tamoxifen in breast cancer patients. Estrogen-responsive genes were identified by transcript profiling of MCF-7 breast cancer cells. Pathway analysis based on functional annotation of these estrogen-regulated genes identified gene signatures with known or predicted roles in cell cycle control, cell growth (i.e. ribosome biogenesis and protein synthesis), cell death/survival signaling and transcriptional regulation. Since inducible expression of c-Myc in antiestrogen-arrested cells can recapitulate many of the effects of estrogen on molecular endpoints related to cell cycle progression, the estrogen-regulated genes that were also targets of c-Myc were identified using cells inducibly expressing c-Myc. Selected genes classified as estrogen and c-Myc targets displayed similar levels of regulation by estrogen and c-Myc and were not estrogen-regulated in the presence of siMyc. Genes regulated by c-Myc accounted for 50% of all acutely estrogen-regulated genes but comprised 85% (110/129 genes) in the cell growth signature. siRNA-mediated inhibition of c-Myc induction impaired estrogen regulation of ribosome biogenesis and protein synthesis, consistent with the prediction that estrogen regulates cell growth principally via c-Myc. The 'cell cycle', 'cell growth' and 'cell death' gene signatures each identified patients with an attenuated response in a cohort of 246 tamoxifen-treated patients. In multivariate analysis the cell death signature was predictive independent of the cell cycle and cell growth signatures. CONCLUSIONS/SIGNIFICANCE: These functionally-based gene signatures can stratify patients treated with tamoxifen into groups with differing outcome, and potentially identify distinct mechanisms of tamoxifen resistance