Search results for "laboratoriotekniikka"
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Versailles project on advanced materials and standards (VAMAS) interlaboratory study on measuring the number concentration of colloidal gold nanopart…
2022
The advancement of analytical methods for nanoparticle measurements is critical both for the growing industrial exploitation of engineered nanoparticles and for developing robust strategies to understand and control the concentration of nanomaterials in humans and the environment. For high value nanoparticles, the measurement of nanoparticle number concentration in a liquid directly impacts the ability to assess the scale and reproducibility of the production process, it allows optimisation of efficiency and supports regulatory compliance. This measurement is also useful to monitor and control the intentional or accidental release of engineered nanoparticles into the environment at the produc…
DNA recovery from Droplet Digital™ PCR emulsions using liquid nitrogen
2020
Droplet microfluidics is a technology that enables the production and manipulation of small volumes. In biosciences, the most popular application of this technology is Droplet Digital™ PCR (ddPCR™), where parallel nanoliter-scale PCR assays are used to provide a high sensitivity and specificity for DNA detection. However, the recovery of PCR products for downstream applications such as sequencing can be challenging due to the droplets' stability. Here we compared five methods for disrupting the droplets to recover DNA. We found that rapid freezing in liquid nitrogen results in a clear phase separation and recovery of up to 70% of the DNA content. Liquid nitrogen freezing can thus offer a si…
H&E Multi-Laboratory Staining Variance Exploration with Machine Learning
2022
In diagnostic histopathology, hematoxylin and eosin (H&E) staining is a critical process that highlights salient histological features. Staining results vary between laboratories regardless of the histopathological task, although the method does not change. This variance can impair the accuracy of algorithms and histopathologists’ time-to-insight. Investigating this variance can help calibrate stain normalization tasks to reverse this negative potential. With machine learning, this study evaluated the staining variance between different laboratories on three tissue types. We received H&E-stained slides from 66 different laboratories. Each slide contained kidney, skin, and colon tissue sampl…