scholarly journals Satellite-like Gold Nanocomposites for Targeted Mass Spectrometry Imaging of Tumor Tissues

2017 ◽  
Vol 1 (2) ◽  
pp. 141-153 ◽  
Author(s):  
Yu-Ting Tseng ◽  
Scott G. Harroun ◽  
Chien-Wei Wu ◽  
Ju-Yi Mao ◽  
Huan-Tsung Chang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Imaging ◽  
Tumor Tissues ◽  
Gold Nanocomposites

scholarly journals A Nanostructured Matrices Assessment to Study Drug Distribution in Solid Tumor Tissues by Mass Spectrometry Imaging

Nanomaterials ◽  
2017 ◽  
Vol 7 (3) ◽  
pp. 71 ◽  
Author(s):  
Silvia Giordano ◽  
Valentina Pifferi ◽  
Lavinia Morosi ◽  
Melinda Morelli ◽  
Luigi Falciola ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Solid Tumor ◽  
Mass Spectrometry Imaging ◽  
Drug Distribution ◽  
Study Drug ◽  
Tumor Tissues

scholarly journals The Impact of Histological Annotations for Accurate Tissue Classification Using Mass Spectrometry Imaging

Metabolites ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 752
Author(s):  
Juliana Pereira Lopes Gonçalves ◽  
Christine Bollwein ◽  
Anna Melissa Schlitter ◽  
Benedikt Martin ◽  
Bruno Märkl ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Classification Accuracy ◽  
Mass Spectrometry Imaging ◽  
Ductal Adenocarcinoma ◽  
Accurate Information ◽  
Learning Approaches ◽  
Kidney Tumors ◽  
Diagnosis And Prognosis ◽  
Tumor Tissues ◽  
The Impact

Knowing the precise location of analytes in the tissue has the potential to provide information about the organs’ function and predict its behavior. It is especially powerful when used in diagnosis and prognosis prediction of pathologies, such as cancer. Spatial proteomics, in particular mass spectrometry imaging, together with machine learning approaches, has been proven to be a very helpful tool in answering some histopathology conundrums. To gain accurate information about the tissue, there is a need to build robust classification models. We have investigated the impact of histological annotation on the classification accuracy of different tumor tissues. Intrinsic tissue heterogeneity directly impacts the efficacy of the annotations, having a more pronounced effect on more heterogeneous tissues, as pancreatic ductal adenocarcinoma, where the impact is over 20% in accuracy. On the other hand, in more homogeneous samples, such as kidney tumors, histological annotations have a slenderer impact on the classification accuracy.

scholarly journals Sample preparation strategy for the detection of steroid-like compounds using MALDI mass spectrometry imaging: pulmonary distribution of budesonide as a case study

2021 ◽  
Author(s):  
Riccardo Zecchi ◽  
Pietro Franceschi ◽  
Laura Tigli ◽  
Davide Amidani ◽  
Chiara Catozzi ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Sample Preparation ◽  
Mass Spectrometry Imaging ◽  
Maldi Mass Spectrometry ◽  
Adult Rabbit ◽  
Chronic Obstructive ◽  
Ionization Mass ◽  
Obstructive Pulmonary Disease ◽  
Imaging Protocol ◽  
Girard’S Reagent

AbstractCorticosteroids as budesonide can be effective in reducing topic inflammation processes in different organs. Therapeutic use of budesonide in respiratory diseases, like asthma, chronic obstructive pulmonary disease, and allergic rhinitis is well known. However, the pulmonary distribution of budesonide is not well understood, mainly due to the difficulties in tracing the molecule in lung samples without the addition of a label. In this paper, we present a matrix-assisted laser desorption/ionization mass spectrometry imaging protocol that can be used to visualize the pulmonary distribution of budesonide administered to a surfactant-depleted adult rabbit. Considering that budesonide is not easily ionized by MALDI, we developed an on-tissue derivatization method with Girard’s reagent P followed by ferulic acid deposition as MALDI matrix. Interestingly, this sample preparation protocol results as a very effective strategy to raise the sensitivity towards not only budesonide but also other corticosteroids, allowing us to track its distribution and quantify the drug inside lung samples. Graphical abstract

scholarly journals Shotgun lipidomics and mass spectrometry imaging unveil diversity and dynamics in Gammarus fossarum lipid composition

iScience ◽  
2021 ◽  
Vol 24 (2) ◽  
pp. 102115
Author(s):  
Tingting Fu ◽  
Oskar Knittelfelder ◽  
Olivier Geffard ◽  
Yohann Clément ◽  
Eric Testet ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Lipid Composition ◽  
Mass Spectrometry Imaging ◽  
Shotgun Lipidomics ◽  
Gammarus Fossarum

scholarly journals Diagnosis of Agglomeration and Crystallinity of Active Pharmaceutical Ingredients in Over the Counter Headache Medication by Electrospray Laser Desorption Ionization Mass Spectrometry Imaging

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 610
Author(s):  
Mariann Inga Van Meter ◽  
Salah M. Khan ◽  
Brynne V. Taulbee-Cotton ◽  
Nathan H. Dimmitt ◽  
Nathan D. Hubbard ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Imaging ◽  
Laser Desorption ◽  
Ionization Mass Spectrometry ◽  
Ionization Mass ◽  
Active Pharmaceutical Ingredients ◽  
Laser Desorption Ionization ◽  
Over The Counter ◽  
Pharmaceutical Ingredients ◽  
Desorption Ionization

Agglomeration of active pharmaceutical ingredients (API) in tablets can lead to decreased bioavailability in some enabling formulations. In a previous study, we determined that crystalline APIs can be detected as agglomeration in tablets formulated with amorphous acetaminophen tablets. Multiple method advancements are presented to better resolve agglomeration caused by crystallinity in standard tablets. In this study, we also evaluate three “budget” over-the-counter headache medications (subsequently labeled as brands A, B, and C) for agglomeration of the three APIs in the formulation: Acetaminophen, aspirin, and caffeine. Electrospray laser desorption ionization mass spectrometry imaging (ELDI-MSI) was used to diagnose agglomeration in the tablets by creating molecular images and observing the spatial distributions of the APIs. Brand A had virtually no agglomeration or clustering of the active ingredients. Brand B had extensive clustering of aspirin and caffeine, but acetaminophen was observed in near equal abundance across the tablet. Brand C also had extensive clustering of aspirin and caffeine, and minor clustering of acetaminophen. These results show that agglomeration with active ingredients in over-the-counter tablets can be simultaneously detected using ELDI-MS imaging.

Sign in / Sign up

Export Citation Format

Share Document