We
present DEIMoS: Data Extraction for Integrated Multidimensional
Spectrometry, a Python application programming interface (API) and
command-line tool for high-dimensional mass spectrometry data analysis
workflows that offers ease of development and access to efficient
algorithmic implementations. Functionality includes feature detection,
feature alignment, collision cross section (CCS) calibration, isotope
detection, and MS/MS spectral deconvolution, with the output comprising
detected features aligned across study samples and characterized by
mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS
operates on N-dimensional data, largely agnostic
to acquisition instrumentation; algorithm implementations simultaneously
utilize all dimensions to (i) offer greater separation between features,
thus improving detection sensitivity, (ii) increase alignment/feature
matching confidence among data sets, and (iii) mitigate convolution
artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS
metabolomics data to illustrate the advantages of a multidimensional
approach in each data processing step.
Proton affinity is
a major factor in the atmospheric pressure chemical
ionization of illicit drugs. The detection of illicit drugs by mass
spectrometry and ion mobility spectrometry relies on the analytes
having greater proton affinities than background species. Evaluating
proton affinities for fentanyl and its analogues is informative for
predicting the likelihood of ionization in different environments
and for optimizing the compounds’ ionization and detection,
such as through the addition of dopant chemicals. Herein, density
functional theory was used to computationally determine the proton
affinity and gas-phase basicity of 15 fentanyl compounds and several
relevant molecules as a reference point. The range of proton affinities
for the fentanyl compounds was from 1018 to 1078 kJ/mol. Fentanyl
compounds with the higher proton affinity values appeared to form
a bridge between the oxygen on the amide and the protonated nitrogen
on the piperidine ring based on models and calculated bond distances.
Experiments with fragmentation of proton-bound clusters using atmospheric
flow tube-mass spectrometry (AFT-MS) provided estimates of relative
proton affinities and showed proton affinity values of fentanyl compounds
>1000 kJ/mol, which were consistent with the computational results.
The high proton affinities of fentanyl compounds facilitate their
detection by ambient ionization techniques in complex environments.
The detection limits of the fentanyl compounds with AFT-MS are in
the low femtogram range, which demonstrates the feasibility of trace
vapor drug detection.
Localized cutaneous neurofibromas (cNFs) are benign tumors that arise in the dermis of patients affected by Neurofibromatosis Type 1 syndrome (NF1). cNFs are fundamentally benign lesions: they do not undergo malignant transformation or metastasize. Nevertheless, in NF1 patients, they can cover a significant proportion of the body, with some individuals developing hundreds to thousands of lesions. cNFs can cause pain, itching, and disfigurement with substantial socio-emotional repercussions. To date, surgical removal or laser desiccation are the only treatment options, but can result in scarring and the leave a potential for regrowth. To support drug discovery efforts focused on identifying effective systemic therapies for cNF, we introduce an approach to routinely establish and screen cNF tumor organoids. We optimized conditions to support ex vivo growth of genomically-diverse cNFs. Patient-derived cNF organoids closely recapitulate the molecular and cellular heterogeneity of these tumors as measured by immunohistopathology, DNA methylation, RNA-seq and flow cytometry. Our tractable patient-derived cNF organoid platform enables rapid screening of hundreds of compounds in a patient- and tumor-specific manner.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.