A warm welcome to our newest graduate student Jada Gray!

This work by Xin MA entitled “Advances in mass spectrometry imaging for spatial cancer metabolomics” published in Mass Spectrometry Reviews provides a comprehensive review of the fundamentals, recent advancements in imaging applications generally as well as with particular interest in cancer research, and the implementation of emerging research fields such as machine learning/artificial intelligence. Check it out using the link below:

https://doi.org/10.3390/cancers14092262

Congratulations to Facundo for his reappointment for this esteemed position at Georgia Tech!

Read more about the College of Sciences announcement here

Congratulations to Emily for being awarded a full travel award to participate in the annual Targeted Mass Spectrometry Course at the University of Washington – was held June 27- July 1, 2022, and for the first time in three years the course was in-person! This course offered a focus on methods and approaches of targeted MS. For mor information click here

This work lead by Samyukta Sah entitled “Targeted Microchip Capillary Electrophoresis-Orbitrap Mass Spectrometry Metabolomics to Monitor Ovarian Cancer Progression” in Metabolites aims to develop new targeted biomarker assays for screening of high-grade serous carcinomas for the early detection of ovarian cancer. Check it out using the link below:

https://doi.org/10.3390/cancers14092262

This work in collaboration with Erin Baker titled “Uncovering PFAS and Other Xenobiotics in the Dark Metabolome Using Ion Mobility Spectrometry, Mass Defect Analysis, and Machine Learning” in Environmental Science & Technology identifies features specifice to PFAS, but reveals that there are still many unknowns in untargeted studies, but by incorporating xenobiotics more confident annotations can be achieved. Check it out using the link below:

https://doi.org/10.3390/cancers14092262

A warm welcome to our newest postdoctoral researcher Ziad Mahmoud who will be doing some exciting research on chemical evolution of polymeric systems.

MP 342 – Samyukta Sah: Ovarian Cancer Metabolomics: Targeted Microchip Capillary Electrophoresis-Mass Spectrometry to Track Disease Progression

MP 365 – Alex Van Grouw: Non-Targeted Metabolomics Identification of Predictive Potency Markers in MSCs

MP 371 – Ying Liu: Metabolic Phenotypes Predict Immunodulatory Potential for Mesenchymal Stromal Cells

TP 181 – Dmitry Leontyev: Lipidome Alterations in Mild Traumatic Brain Injury Mapped via FTICR Mass Spectrometry Imaging

TP 500 – Joseph Corstvet: Towards Single-Cell Shotgun Lipidomics for Monitoring Mesenchymal Stromal Cell Senescence

WOF 08:30 AM – David Gaul: How Training Alters the Rat Liver Lipidome Profile in Response to Exercise

WP 083 – Olatomiwa Bifarin: Ovarian Cancer Lipidome Dynamics in a Dicer-Pten Double-Knockout Mouse Model

WP 284 – Xin Ma: Spatially Resolved Lipidomic Profiling of Ovarian Cancer Using Ultrahigh Resolution Mass Spectrometry Imaging

WP 311 – Markace Rainey: CCS Predictor 2.0: An Open-Source Tool for Filtering Out False Positives in Metabolomics

WP 372 – Carter Asef: Ion Mobility for Unknown Metabolite Identification: Hope or Hype?

ThP 002 – Daniel Vallejo: Native Protein Structures and Stabilities Measured at Nanomolar and Picoliter Quantities using Triboelectric Nanogenerator Ion Mobility-Mass Spectrometry

Carter Asef received the Dave Atkinson Student Travel Award to attend the 2022 International Society for Ion Mobility Spectrometry conference in Memphis, Tennessee. His abstract titled “Ion Mobility for Unknown Metabolite Identification: Hope or Hype?” will be presented, discussing current challenges and limitations of leveraging ion mobility data to aid in traditional metabolomics studies.  

Click here to read more about the ISIMS conference

This work by Samyukta Sah and Xin Ma titled “Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model” in Cancers follows the first 10-month time-resolved serum metabolic profile of a triple mutant (TKO) HGSC mouse model, along with the spatial lipidome profile of its entire reproductive system. Check it out using the link below:

https://doi.org/10.3390/cancers14092262