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A comprehensive benchmarking for evaluating TCR embeddings in modeling TCR-epitope interactions.
Brief Bioinform
November 2024
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, 999077, China.
The complexity of T cell receptor (TCR) sequences, particularly within the complementarity-determining region 3 (CDR3), requires efficient embedding methods for applying machine learning to immunology. While various TCR CDR3 embedding strategies have been proposed, the absence of their systematic evaluations created perplexity in the community. Here, we extracted CDR3 embedding models from 19 existing methods and benchmarked these models with four curated datasets by accessing their impact on the performance of TCR downstream tasks, including TCR-epitope binding affinity prediction, epitope-specific TCR identification, TCR clustering, and visualization analysis.
View Article and Find Full Text PDFAnalytical and Clinical Validation of the Plasma-Based Guardant360 CDx Test for Assessing HER2 (ERBB2) Mutation Status in Patients with Non-Small-Cell Lung Cancer for Treatment with Trastuzumab Deruxtecan in DESTINY-Lung01/02.
J Mol Diagn
February 2025
Daiichi Sankyo, Inc., Basking Ridge, New Jersey.
This study demonstrates the analytical and clinical validity of the approved (United States and Japan) plasma-based Guardant360 companion diagnostic (CDx) test for selecting patients with human epidermal growth factor receptor 2 (HER2 [ERBB2])-mutated (HER2m) non-small-cell lung cancer (NSCLC) for trastuzumab deruxtecan (T-DXd) treatment. Concordance between the Guardant360 CDx test and the plasma-based AVENIO ctDNA Expanded Kit Assay (AVENIO), as well as the tissue-based clinical trial assays (CTAs) was investigated. Clinical utility was assessed by comparing T-DXd clinical efficacy results of patients in DESTINY-Lung01/02 who tested positive for HER2 mutations using the Guardant360 CDx test to benchmark efficacy results from DESTINY-Lung01/02.
View Article and Find Full Text PDFA quantitative prediction method utilizing whole omics data for biosensing.
Sci Rep
January 2025
BioResource Research Center, RIKEN, 3-1-1, Koyadai, Tsukuba, 305-0074, Ibaraki, Japan.
Omics data provide a plethora of quantifiable information that can potentially be used to identify biomarkers targeting the physiological processes and ecological phenomena of organisms. However, omics data have not been fully utilized because current prediction methods in biomarker construction are susceptible to data multidimensionality and noise. We developed OmicSense, a quantitative prediction method that uses a mixture of Gaussian distributions as the probability distribution, yielding the most likely objective variable predicted for each biomarker.
View Article and Find Full Text PDFStandard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics.
Nat Commun
January 2025
School of Biological Science and Medical Engineering & School of Engineering Medicine, Beihang University, Beijing, China.
Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography-mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms.
View Article and Find Full Text PDFUltrasound-Assisted Enzymatic Extraction of the Active Components from Stem and Bioactivity Comparison with .
Molecules
January 2025
Key Laboratory of Forest Plant Ecology of Ministry of Education, Northeast Forestry University, Hexing Road 26, Harbin 150040, China.
(ASC) contains a variety of bioactive compounds and serves as an important traditional Chinese medicinal resource. However, its prolonged growth cycle and reliance on wild populations limit its practical use. To explore the potential of (ASF) as an alternative, this study focused on optimizing the extraction process and assessing the bioactivity of stem extracts.
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