MetaSystems proudly announces the opening of our first subsidiary in the Southern hemisphere. The new office is located in Buenos Aires, Argentina and bears the name MetaSystems Latinoamérica SAS (MetaSystems LatAm). The foundation has been the response to the growing demand on technical knowledge and 'know how' experienced in the last years all over the Latin American territories. MetaSystems LatAm takes care for the organization of sales, support, and customer relation activities in all countries in Latin America. It will manage distributor companies and contacts in the region, and it will facilitate communication between end-users, distributors and headquarters in Germany.
Your application does not match any of the other categories? MetaSystems may anyway be able to find a solution for your imaging problem.
MetaSystems devices excel through a unique combination of flexibility and reliability. This makes it easy to adapt a MetaSystems product like the Metafer slide scanning platform to new applications. Please see below some success stories - maybe your application can also be automated?
A few years ago, MetaSystems was approached by a renowned marine research institute. The request involved imaging, and identifying diatoms in samples obtained from the sea floor and other places. Diatoms, a major group of algae, are important indicators for environmental conditions. Diatoms are enclosed with a cell wall made of silica showing a large diversity in appearance. A Metafer system and an adapted viewer software were installed and configured to communicate with existing diatom identification software. Now, the high-quality diatom images from Metafer are used routinely as a basis for automated diatom detection and identification.
To visualize RNA expression in Drosophila larvae, the central imaging facility of a large biotechnology lab wanted to combine Nomarski phase contrast images with fluorescence. Since Metafer has the flexibility to support any contrasting method the microscope offers, it was easily possible to create an adapted workflow. The resulting images contain a color image of the Drosophila larvae acquired with Nomarski phase contrast, and a fluorescence channel showing the spatial distribution of RNA expression in the larvae.
Microscopic analysis of thin mineral sections is a common tool to evaluate the micro-texture and structure of rocks. Characteristics observed under the microscope include color and color variations under polarized light (pleochroism). Using the manifold possibilities of Metafer, and the microscope features for polarized light, it has been possible to create a system for automated imaging of thin rock sections.
Arabidopsis thaliana is a 20-25 cm tall flowering plant native to Europe, Asia, and northwestern Africa with a rapid life cycle of six weeks. It is used extensively as a model organism in plant biology and genetics. With about 157 million base pairs and five chromosomes, Arabidopsis has one of the smallest genomes among plants, and it was the first one to be sequenced in 2000.
It is known that two A. thaliana genes, QRT1 and QRT2, are required for pollen separation during normal development. In certain mutants, however, pollen grains are released in tetrads. A tetrad is a cluster of 4 pollen grains that are the 4 products of one meiosis and which are still attached together. In a visual assay utilizing transgenic marker constructs it is possible to encode pollen-expressed fluorescent proteins of three colors in the quartet mutant background. This bears the possibility to study the results of one single meiosis and to analyze the crossing over interference (inhibition of nearby crossing overs) based on the specific fluorescence color pattern of the tetrads.
After harvesting, however, the fluorescence of the fluorescent reporter proteins in the tetrads vanishes within 4 hours. Therefore, the number of analyzed tetrads is limited if manual microscopy is used. An automated imaging protocol based on the possibilities of the Metafer slide scanning platform, however, is capable of finding and identifying tetrads on the sample automatically. Thus, far more tetrads can be analyzed in the time before the markers vanish. Analysis of the tetrads is also automated by classifying the different color patterns. All data are conveniently summarized in automated reports.