This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
Picosecond infrared laser mass spectrometry (PIRL-MS) is shown, through a retrospective patient tissue study, to differentiate medulloblastoma cancers from pilocytic astrocytoma and two molecular subtypes of ependymoma (PF-EPN-A, ST-EPN-RELA) using laser-extracted lipids profiled with PIRL-MS in 10 s of sampling and analysis time. The average sensitivity and specificity values for this classification, taking genomic profiling data as standard, were 96.41 and 99.54%, and this classification used many molecular features resolvable in 10 s PIRL-MS spectra. Data analysis and liquid chromatography coupled with tandem high-resolution mass spectrometry (LC-MS/MS) further allowed us to reduce the molecular feature list to only 18 metabolic lipid markers most strongly involved in this classification. The identified 'metabolite array' was comprised of a variety of phosphatidic and fatty acids, ceramides, and phosphatidylcholine/ethanolamine and could mediate the above-mentioned classification with average sensitivity and specificity values of 94.39 and 98.78%, respectively, at a 95% confidence in prediction probability threshold. Therefore, a rapid and accurate pathology classification of select pediatric brain cancer types from 10 s PIRL-MS analysis using known metabolic biomarkers can now be available to the neurosurgeon. Based on retrospective mining of 'survival' versus 'extent-of-resection' data, we further identified pediatric cancer types that may benefit from actionable 10 s PIRL-MS pathology feedback. In such cases, aggressiveness of the surgical resection can be optimized in a manner that is expected to benefit the patient's overall or progression-free survival. PIRL-MS is a promising tool to drive such personalized decision-making in the operating theater.
Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter your papers by.
From here we'll present any options for the literature, such as exporting your current results.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Year:
Count: