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?