Our new Obvious+ tissue clearing procedure is the one approach that delipidates samples with no improve in morphology and with small effect on structural integrity.
Megatome is really a vibrating microtome created to area a wide number of samples, from organoids and biopsy samples to expanded rodent brains and intact human organs. With high blade vibrating frequency and minimized blade deflection, Megatome enables higher-throughput tissue sectioning with uniform surface area profile, along with nominal tissue hurt and data decline.
Ask for a quotation or demo Uniformly portion significant tissues & sample arrays Megatome is the only real microtome that can section samples as large as intact nonhuman primate and human organs, making it invaluable for fields such as neuropathology.
Working the CLI directly from a Gradle job isn't presently supported. A distribution must be created via gradlew :j2d-cli:distZip to create a zip file made up of everything required to operate.
Clone the job or get the most recent release. Functioning the utility will change a tad according to how you retrieve the project.
Our preformulated EasyIndex Alternative raises and homogenize the refractive index of delipidated tissue samples, rendering them thoroughly clear. This enables light penetration in the sample and assures the acquisition of large-resolution, in-focus graphic knowledge.
Megatome is often a novel microtome that permits for top-precision sectioning of a wide array of tissue samples – from organoids, to arrays of animal organs, to intact human brain hemispheres – with small tissue harm and data reduction.
It’s time and energy to improve your microtome to Megatome. With exact large-frequency slicing for an unmatched number of sample measurements and kinds – from organoids and tumors to expanded tissues, sample arrays, and intact primate organs – Megatome is optimized for various purposes.
Fully delipidate total mouse brains or comparably sized megatomi.com samples in just one day with SmartBatch+, or in a single week with our passive clearing package.
Docset generation involves at minimum two options: the title of the docset and The placement of your Javadoc information to incorporate within the docset.
This could create a docset named Sample in The present Listing. Docset creation could be tailored with optional arguments:
SHIELD avoids the variability of hydrogel embedding and the data reduction from PFA preservation, guarding specimens for many rounds of processing.
--displayName: Will set the title as demonstrated in Sprint. This is useful in case you make a docset with name SampleProject but Show title Sample Job instead. This setting will default to the value of --title if omitted.
Our novel Protect tissue preservation technique forms intramolecular bonds utilizing polyfunctional, versatile epoxides to stabilize tissue architecture and safeguard the sample’s endogenous fluorescence, protein antigenicity and nucleic acids.