The performance of a lateral flow SARS-CoV-2 antibody assay and semi-autonomous SARS-CoV-2 antisense and sense RNA fluorescence in situ hybridization assay in a prospective cohort pilot study within a Dutch military population.

At the beginning of the COVID-19 pandemic, diagnostic testing was not accessible for mildly ill or asymptomatic individuals. Military operational circumstances exclude the usage of reference laboratory tests. For that reason, at the beginning of the pandemic alternative test methods were needed in order to gain insight into the SARS-CoV-2 status of military personnel.

Evaluation of a fluorescence in situ hybridization (FISH)-based method for detection of SARS-CoV-2 in saliva.

The use of a non-invasive fluorescence in situ hybridization (FISH)-based method on saliva for the detection of SARS-CoV-2 is evaluated in a proof-of-concept study and thereafter utilized in an outpatient setting with the Biotrack-MED® analyzer. For a proof-of-concept study, saliva samples were obtained from 28 persons with mild or moderate COVID-19-related symptoms who were tested RT-PCR positive or negative for SARS-CoV-2. In an outpatient setting, 972 individual saliva samples were utilized.

Direct detection of SARS-CoV-2 antisense and sense genomic RNA in human saliva by semi-autonomous fluorescence in situ hybridization: A proxy for contagiousness?

Saliva is a matrix which may act as a vector for pathogen transmission and may serve as a possible proxy for SARS-CoV-2 contagiousness. Therefore, the possibility of detection of intracellular SARS-CoV-2 in saliva by means of fluorescence in situ hybridization is tested, utilizing probes targeting the antisense or sense genomic RNA of SARS-CoV-2. This method was applied in a pilot study with saliva samples collected from healthy persons and those presenting with mild or moderate COVID-19 symptoms.

Development and validation of an alternative parameter for quantification of signals emitted by fluorescently labelled bacteria in microscopic images.

In this study, an alternative parameter for quantifying the signals of fluorescently labelled bacteria (e.g. propidium iodide, Cyanine 3, etc.

Different binarization processes validated against manual counts of fluorescent bacterial cells.

State of the art software methods (such as fixed value approaches or statistical approaches) to create a binary image of fluorescent bacterial cells are not as accurate and precise as they should be for counting bacteria and measuring their area. To overcome these bottlenecks, we introduce biological significance to obtain a binary image from a greyscale microscopic image. Using our biological significance approach we are able to automatically count about the same number of cells as an individual researcher would do by manual/visual counting.