scholarly journals ‘Swabs’ then and now: cotton to flocked nylon

2010 ◽  
Vol 31 (3) ◽  
pp. 133 ◽  
Author(s):  
Joan Faoagali
Keyword(s):  
Molecular Detection ◽  
Detection Methods ◽  
Sample Collection ◽  
Forensic Dna ◽  
Microbial Detection ◽  
Human Dna ◽  
Pcr Inhibitor ◽  
Microbiological Sample ◽  
Polymerase Chain ◽  
Collection Methods

Microbiological sample collections using cotton-tipped swabs (with or without serum), Dacron?, rayon and calcium alginate, with shafts of wood, plastic and various thicknesses and types of metal have all been used over the years. The swabs have been contained in glass or plastic tubes with and without various types of transport media. Swabs are an easy and popular method of sample collection, although microbiology laboratories traditionally prefer tissue, body fluids or aspirates ahead of swabs. As microbiology laboratories increasingly adopt near patient testing and molecular detection methods to reduce test turnaround times, new sample collection methods are required to maximise the sensitivity of these expensive tests and reduce the possibility of failed tests due to sample inhibitors or poor collection techniques. Flocked nylon swabs have been developed by Copan in the last decade and are produced using a technique of spraying nylon fibres onto a rigid core. This has the effect of increasing the surface area for sample collection and also provides easy elution of the collected material. These swabs are polymerase chain reaction (PCR) inhibitor-free, RNase-negative and DNase-free and there is in addition a range of flocked swabs, specifically intended for forensic DNA investigations that are certified human DNA-free. The advantages, disadvantages and appropriate use of swab collections for microbial detection in the 21st century will be presented.

scholarly journals Gleaning a Human DNA Profile from Trace Swabs Collected from Animal Hairs

2016 ◽  
Vol 66 (2) ◽  
pp. 187-202 ◽  
Author(s):  
Branimira Špoljarić ◽  
Maja Popović ◽  
Josip Crnjac ◽  
Zrinka Žderić Savatović ◽  
Martina Ratko ◽  
...  
Keyword(s):  
Dna Extraction ◽  
Sample Collection ◽  
Dna Profile ◽  
Human Dna ◽  
Intraspecific Variations ◽  
Morphological Differences ◽  
Dna Profiles ◽  
Collection Methods

Abstract Animal hairs are an apt surface for retention of forensic trace epithelial samples. The aim of this study was threefold: to evaluate different methods of sample collection (moistened and dry swabs) and DNA extraction (Chelex® 100 method, Qiagen EZ1® DNA Investigator Kit), as well as to examine the morphological differences of hair fibres between two species (dog, sheep) and their ultimate impact on sample collection and processing. Our preliminary findings suggest that the use of EZ1® DNA Investigator Kit yields donor DNA profiles of higher quality. The results of different sample collection methods have shown intraspecific variations that require further investigation. The ability of retention and subsequent extraction of trace DNA appears to be similar between the two species, despite significant morphological differences between their coat hairs.

scholarly journals Performance of saliva specimens for the molecular detection of SARS-CoV-2 in the community setting: does sample collection method matter?

2020 ◽  
Author(s):  
Marta Fernández-González ◽  
Vanesa Agulló ◽  
Alba de la Rica ◽  
Ana Infante ◽  
Mar Carvajal ◽  
...  
Keyword(s):  
Molecular Detection ◽  
Real Life ◽  
Community Setting ◽  
Sample Collection ◽  
Rt Pcr ◽  
Life Conditions ◽  
Ambulatory Patients ◽  
Asymptomatic Individuals ◽  
Positive Results ◽  
Collection Methods

AbstractBackgroundData on the performance of saliva specimens for diagnosing COVID-19 in ambulatory patients are scarce and inconsistent. We assessed saliva-based specimens for detecting SARS-CoV-2 by RT-PCR in the community setting and compared three different collection methods.MethodProspective study conducted in three primary care centres. RT-PCR was performed in paired nasopharyngeal swabs (NPS) and saliva samples collected from outpatients with a broad clinical spectrum of illness. To assess differences in collection methods, saliva specimens were obtained in a different way in each of the participating centres: supervised collection (SVC), oropharyngeal washing (OPW) and self-collection (SC).ResultsNPS and saliva pairs of samples from 577 patients (median age 39 years, 44% men, 42% asymptomatic) were collected and tested, and 120 (20.8%) gave positive results. The overall agreement with NPS and kappa coefficients (KƘ) for SVC, OPW and SC were 95% (Ƙ=0.85), 93.4% (Ƙ=0.76), and 93.3% (Ƙ=0.76), respectively. The sensitivity (95% CI) of the saliva specimens varied from 86% (72.6-93.7) for SVC to 66.7% (50.4-80) for SC samples. The sensitivity was higher in samples with lower cycle threshold (Ct) values. The best performance of RT-PCR was observed for SVC, with sensitivity (95% CI) for Ct values ≤32 of 97% (82.5-99.8) in symptomatic, and 88.9% (50.7-99.4) in asymptomatic individuals.ConclusionsSaliva is an acceptable specimen for the detection of SARS-CoV-2 in the community setting. Specimens collected under supervision perform comparably to NPS and can effectively identify individuals with higher risk of transmission in real life conditions.

scholarly journals Cross-contamination in the Molecular Detection of Bartonella from Paraffin-embedded Tissues

2009 ◽  
Vol 46 (5) ◽  
pp. 940-944 ◽  
Author(s):  
M. Varanat ◽  
R. G. Maggi ◽  
K. E. Linder ◽  
S. Horton ◽  
E. B. Breitschwerdt
Keyword(s):  
Molecular Detection ◽  
Liquid Paraffin ◽  
Cross Contamination ◽  
Test Results ◽  
Sample Collection ◽  
Tissue Samples ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Polymerase Chain ◽  
Formalin Fixed

The genus Bartonella comprises a group of gram-negative, fastidious bacteria. Because of diagnostic limitations of culture and serologic testing, polymerase chain reaction (PCR) has become a powerful tool for the detection of Bartonella spp. in blood and tissue samples. However, because many wild and domestic animals harbor Bartonella spp., transfer of Bartonella DNA during sample collection or histologic processing could result in false-positive PCR test results. In this study, we describe evidence of Bartonella DNA dissemination and transfer in the necropsy room and during the subsequent processing of formalin-fixed paraffin-embedded tissues. Bartonella DNA was amplified from different areas of the necropsy room, from the liquid paraffin in the tissue processor, and from different parts of the microtome. Unless stringent procedures are established and followed to avoid cross-contamination, the molecular detection of Bartonella spp. from tissue samples obtained at necropsy or processed in a multispecies histopathology laboratory will not be reliable.

scholarly journals Comparison of Whole-Tissue and Xylem Fluid Collection Techniques to Detect Xylella fastidiosa in Grapevine and Oleander

Plant Disease ◽  
2004 ◽  
Vol 88 (6) ◽  
pp. 600-604 ◽  
Author(s):  
Blake R. Bextine ◽  
Thomas A. Miller
Keyword(s):  
Pathogen Detection ◽  
Xylella Fastidiosa ◽  
Fluid Collection ◽  
Detection Methods ◽  
Enzyme Linked Immunosorbent Assay ◽  
Sample Collection ◽  
Chain Reaction ◽  
Tissue Samples ◽  
Xylem Fluid ◽  
Polymerase Chain

Xylella fastidiosa is the xylem-limited bacterium that causes Pierce's disease of grapevine and oleander leaf scorch. Detection of this pathogen prior to symptom development is critical for improved management of the disease. Enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) currently are used for routine detection of the pathogen; however, both detection methods are limited by low titer or patchy distribution of the bacterium within a host plant. In the study reported here, we directly compared X. fastidiosa detection in whole-tissue samples with xylem fluid samples from grapevine and oleander. Collection of xylem fluid samples improved sensitivity of pathogen detection by ELISA (41.0%) compared with whole-tissue samples (20.5%) in asymptomatic grapevine. Additionally, pathogen detection in asymptomatic grapevine by PCR also was improved when xylem samples were tested (66.7%) compared with whole-tissue samples (23.1%). There were no differences in frequency of detection of X. fastidiosa in symptomatic grapevines by ELISA or PCR dependent upon sample collection method. Assays of xylem fluid samples did not improve detection of X. fastidiosa in symptomatic or asymptomatic oleander compared with assays of whole tissue. Finally, in a direct comparison of ELISA and PCR, we found no significant differences in frequencies of positive grapevine or oleander samples detected.

PREDIKSI PERINGKAT OBLIGASI SYARIAH DI INDONESIA

2014 ◽  
Vol 11 (3) ◽  
pp. 1-15
Author(s):  
Ike Arisanti ◽  
Isti Fadah ◽  
Novi Puspitasari
Keyword(s):  
Profit Sharing ◽  
Sample Collection ◽  
Purposive Sampling ◽  
Financial Factors ◽  
Financial Factor ◽  
Independent Variable ◽  
Rating Prediction ◽  
Collection Methods

This study purposes to analyze the influence of financial and non financial factors to prediction of the rating islamic bond in indonesia. The study used independent variable,that is financial factor (growth, size, profit sharing/fee, liquidity) and non financial factor ( secure and maturity) and dependent variable that is the rating of islamic bond. This study applied logistic regresion analysis with sample collection methods using purposive sampling. After selecting fixed criterias, there were 25 islamic bonds chosen with the numbers of 75 investigation from periods of 2010-2012. The result of this study showed that significantly effect the variable growth (X1) , size(X2), profit sharing/ fee (X3), liquidity (X4), secure (X5), maturity (X6) simultaneously to the rating prediction of islamic bond in indonesia. Partially, variable variables of growth (X1) , size (X2), profit sharing/ fee (X3) which referred not significant affecting to the rating prediction of islamic bond in indonesia. Meanwhile, variables of liquidity (X4), secure (X5), maturity ( X6) referred significant affecting to the rating prediction of islamic bond in indonesia.

scholarly journals A generalised approach for high-throughput instance segmentation of stomata in microscope images

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Hiranya Jayakody ◽  
Paul Petrie ◽  
Hugo Jan de Boer ◽  
Mark Whitty
Keyword(s):  
High Throughput ◽  
Imaging Techniques ◽  
Detection Algorithm ◽  
Input Image ◽  
Detection Methods ◽  
Sample Collection ◽  
High Throughput Analysis ◽  
General Applicability ◽  
Additional Image ◽  
Bounding Boxes

Abstract Background Stomata analysis using microscope imagery provides important insight into plant physiology, health and the surrounding environmental conditions. Plant scientists are now able to conduct automated high-throughput analysis of stomata in microscope data, however, existing detection methods are sensitive to the appearance of stomata in the training images, thereby limiting general applicability. In addition, existing methods only generate bounding-boxes around detected stomata, which require users to implement additional image processing steps to study stomata morphology. In this paper, we develop a fully automated, robust stomata detection algorithm which can also identify individual stomata boundaries regardless of the plant species, sample collection method, imaging technique and magnification level. Results The proposed solution consists of three stages. First, the input image is pre-processed to remove any colour space biases occurring from different sample collection and imaging techniques. Then, a Mask R-CNN is applied to estimate individual stomata boundaries. The feature pyramid network embedded in the Mask R-CNN is utilised to identify stomata at different scales. Finally, a statistical filter is implemented at the Mask R-CNN output to reduce the number of false positive generated by the network. The algorithm was tested using 16 datasets from 12 sources, containing over 60,000 stomata. For the first time in this domain, the proposed solution was tested against 7 microscope datasets never seen by the algorithm to show the generalisability of the solution. Results indicated that the proposed approach can detect stomata with a precision, recall, and F-score of 95.10%, 83.34%, and 88.61%, respectively. A separate test conducted by comparing estimated stomata boundary values with manually measured data showed that the proposed method has an IoU score of 0.70; a 7% improvement over the bounding-box approach. Conclusions The proposed method shows robust performance across multiple microscope image datasets of different quality and scale. This generalised stomata detection algorithm allows plant scientists to conduct stomata analysis whilst eliminating the need to re-label and re-train for each new dataset. The open-source code shared with this project can be directly deployed in Google Colab or any other Tensorflow environment.

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