Technology & Data Science for Enhanced Patient Care

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JMSACL

Projects

Special Issue Development

Antibody Analysis

Guest Editor: David Barnidge

This special Issue will strive to present all facets of antibody analysis with a focus on using mass spectrometry from intact antibody analysis to sequencing methods such as top-down, middle-down, and bottom-up. Specific applications, such as quantifying endogenous antibodies in serum as a biomarker of disease to determining PTMs on therapeutic mAbs as part of drug development will also be a focus. The goal is to provide readers a comprehensive insight into the increasingly important role antibody analysis plays in both clinical and research laboratories.

Lipidomics

Guest Editor: Anne Bendt

The mindboggling structural diversity of lipids reflect their varied functions in health and disease, and, hence, the multitude of existing and potential clinical applications.

In this SI, we give an overview of ongoing developments in the field, expanding from well-established lipids (i.e., cholesterol, triglycerides, bile acids, acylcarnitines) to emerging markers such as ceramides and oxylipins as well as promising multi-analyte panels for metabolic disorders. With a focus on applicability for routine clinical services, we plan to cover sample extraction, mass spec workflows, data analysis, and ongoing harmonization efforts towards clinical adoption.

This SI will comprise a range of formats including research articles on lipid-related pathophysiologies, novel method developments, reviews on biomarkers, tutorials on reference materials and ring trials, and opinion articles of clinical translation and regulatory requirements.

Data Science

Guest Editor(s) : Dustin Bunch & Daniel Holmes

This special issue will focus on the emerging discipline of Data Science as it applies to Laboratory Medicine. Data Science resides at the confluence of computer science, statistics, and mathematics. Laboratory Medicine is an ideal context to apply Data Science tools because the data sets are frequently too large for spreadsheet analysis, but laboratorian domain knowledge permits rapid analysis with actionable results. Authors who have applied or developed novel data science tools to laboratory medicine for data visualization, automated reporting, dashboard development, decision support, data processing/automation, image analysis, machine learning/AI are welcome to submit.

Novel Instrumentation

Guest Editor(s) : Chris Chouinard & Phil Mach