Standardization of SARS-CoV-2 Nucleic Acid Amplification Techniques by Calibration and Quantification to the First WHO International Standard for SARS-CoV-2 RNA.

Clinical decision-making regarding isolation of SARS-CoV-2 patients is usually based on semiquantitative cycle-threshold (Ct) values without standardization. However, not all molecular assays produce Ct values, and there is ongoing discussion about whether Ct values can be safely used for decision-making. In this study, we standardized two molecular assays which use different nucleic acid amplification techniques (NAAT): the Hologic Aptima SARS-CoV-2/Flu (TMA) and Roche Cobas 6800 SARS-CoV-2 assays.

Classification and specific primer design for accurate detection of SARS-CoV-2 using deep learning.

In this paper, deep learning is coupled with explainable artificial intelligence techniques for the discovery of representative genomic sequences in SARS-CoV-2. A convolutional neural network classifier is first trained on 553 sequences from the National Genomics Data Center repository, separating the genome of different virus strains from the Coronavirus family with 98.73% accuracy.

Performance evaluation of the Panther Fusion® respiratory tract panel.

Background: Respiratory tract infections are among the most common infections during winter season. Rapid diagnostics is required for clinical decision making regarding isolation of patients and appropriate therapy.

Objectives: The aim of this study was to evaluate the analytical and clinical performance characteristics of the Panther Fusion® respiratory panel using published laboratory-developed real-time PCR assays (LDT).