2023 Academy Distinguished Abstracts Winners

The the Academy of Diagnostics & Laboratory Medicine is pleased to announce the winners of the 2023 Distinguished Abstracts Awards. A group of Fellows selected these 22 abstracts for their scientific excellence from a pool of more than 780 abstracts accepted for the the Association for Diagnostics & Laboratory Medicine (formerly AACC) Annual Scientific Meeting.

Winning abstracts displayed the Academy blue ribbon during the the Association for Diagnostics & Laboratory Medicine (ADLM) Annual Scientific Meeting poster sessions.

A-031 – Linmin Zhu, Tianjin, China
Global Discovery of Serological Metabolome Uncovers Unique Molecular Signature for Early Onset of Type 2 Diabetes Mellitus: A Retrospective Study in Chinese Population

A-203 – Anna Wolska, PhD, Bethesda, MD
An Equation based on the Standard Lipid Panel for Calculating Low-Density Lipoproteins-Triglycerides

A-208 – Tatiana Coverdell, PhD, Bethesda, MD
An Improved Formula for Predicting Low LDL-C Based on an Enhanced Sampson-NIH Equation

A-242 – Dongsheng Han, MD, Hangzhou, China
Integrating Respiratory Metagenomics and Metatranscriptomics for Diagnosis of Lung Cancer and Infection in Patients with Pulmonary Diseases

B-025 – Dan Figdore, Rochester, MN
Evaluation of Bias Between Alzheimer’s Disease Blood-Based Biomarkers Assays and Their Concordance With Amyloid-PET on the Fujirebio Lumipulse and Quanterix Simoa Platforms

B-075 – Matt Sorrells, PhD, San Francisco, CA
Biophysical Changes of Leukocyte Activation (and NETosis) in the Cellular Host Response to Sepsis

B-123 – Jian Zhong, BA/BS, Beijing, China
Utilization of Five Data Mining Algorithms Combined with Simplified Preprocessing to Establish Reference Intervals of Thyroid Related Hormones for Nonelderly Adults

B-134 – Raj Gopalan, MD, Tarrytown, NY
Artificial Intelligence (AI)-Driven Clinical Decision Support: Potential to Predict the Risk for Multiple Sclerosis

B-144 – Seung Yeob Lee, MD, PhD, Jeonju, Republic of Korea
A Comparative Analysis of Unsupervised Machine Learning Algorithms for Polyploidy Analysis Using Flow Cytometry

B-145 – Steven Cotton, PhD, Chapel Hill, NC
An R Shiny App for Automated Peak Deconvolution, Interpretation, and Quantitation of Monoclonal Proteins Using Capillary Electrophoresis Immunotyping Data

B-169 – Robin Kemperman, PhD, Philadelphia, PA
Beta-hydroxybutyrate/acetoacetate Ratio as Indicator for Mitochondrial Diseases Utilizing a Novel LC-MS/MS Based Ketone Body Panel

B-180 – Gabriella Lakos, PhD, Birmingham, United Kingdom
The EXENT® Solution Provides Evidence for High Prevalence of Multiple M-proteins in Monoclonal Gammopathies

B-200 – Rachel DeHoog, PhD, Houston, TX
Preoperative Classification of Thyroid Nodules by Desorption Electrospray Ionization Mass Spectrometry Imaging of Fine Needle Aspiration Biopsies

-225 – Jordan Stachelski, BA/BS, San Diego, CA
Assessment of the Genotype Frequency of Thiopurine Methyltransferase (TPMT) Deficiency in a Large Cohort of Patients With Immune Mediated Inflammatory Disease and Cancer

B-230 – Young-Jin Kim, MD, PhD, Yongin City, Gyeonggi-do, Republic of Korea
Monitoring SARS-CoV-2 Subvariants for Evaluation of the Diagnostic Kit’s Annealing Site using Nanopore Sequencing

B-252 – Jessica Nayara de Araujo, Natal, Brazil
In Vitro Expression Analysis of Variants in the Upstream Region of Genes Related to Familial Hypercholesterolemia

B-292 – Shubhdeep Kaur, BA/BS, Delhi, India
Drug Repurposing via Host-Pathogen Protein-Protein Interaction for the Treatment of COVID-19

B-327 – Gemma Campbell, BA/BS, Nashville, TN
Evidence of Missed Novel Psychoactive Substances (NPS) in Unexpected Fentanyl Positives

B-382 – Chuanxin Wang, PhD, Jinan, China
Accurate and Early Detection of Colorectal Cancer using a Multilocus DNA Methylation Markers-based Testing in Peripheral Blood Mononuclear Cells

B-383 – Zhaodan Xin, Chengdu, China
Exosomal PRPSAP1 in Plasma Predicts Microvascular Invasion in Hepatocellular Carcinoma

B-385 – Lutao Du, Jinan, China
Multi-omics to Reveal the Characteristics of the Gut Microbiome and Metabolome in Patients with Colorectal Cancer Liver Metastasis

B-391 – Danielle Zauli, PhD, Vespasiano, Brazil
Is Comprehensive Cancer Panel by Next-Generation Sequencing (NGS) More Efficient than Cancer-specific NGS Panel in the Management of Non-small Cell Lung Cancer Patients?

Academy of Diagnostics & Laboratory Medicine Designation

Fellows of the Academy use the designation of FADLM. This designation is equivalent to FACB and FAACC, the previous designations used by fellows of the National Academy of Clinical Biochemistry and AACC Academy. Those groups were rebranded as Academy of Diagnostics & Laboratory Medicine in 2023.