AIMC Topic: Immunoglobulin G
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B lymphocyte subset-based stratification in primary Sjögren's syndrome: implications for lymphoma risk and personalized treatment.
Clinical rheumatology
Apr 29, 2025
OBJECTIVE: This study aimed to perform a detailed stratification analysis of B lymphocyte subsets in patients with primary Sjögren's syndrome (pSS) and to investigate their associations with lymphoma risk, clinical phenotypes, and disease activity.
Surface-Induced Unfolding Reveals Unique Structural Features and Enhances Machine Learning Classification Models.
Analytical chemistry
Mar 14, 2025
Native ion mobility-mass spectrometry combined with collision-induced unfolding (CIU) is a powerful analytical method for protein characterization, offering insights into structural stability and enabling the differentiation of analytes with similar ...
TimePAD─Unveiling Temporal Sequence ELISA Signal by Deep Learning for Rapid Readout and Improved Accuracy in a Microfluidic Paper-Based Analytical Platform.
Analytical chemistry
Feb 17, 2025
The integration of paper-based microfluidics with deep learning represents a pivotal trend in enhancing diagnostic capabilities. This paper introduces a new approach to improve the performance of a paper-based microfluidic enzyme-linked immunosorbent...
Humoral and cell-mediated immune responses to COVID-19 vaccines up to 6 months post three-dose primary series in adults with inborn errors of immunity and their breakthrough infections.
Frontiers in immunology
Jan 21, 2025
PURPOSE: Many individuals with inborn errors of immunity (IEIs) have poor humoral immune (HI) vaccine responses. Only a few studies have examined specific cell-mediated immune (CMI) responses to coronavirus disease 2019 (COVID-19) vaccines in this po...
Application of one-class classification using deep learning technique improves the classification of subvisible particles.
Journal of pharmaceutical sciences
Nov 29, 2024
Capturing subvisible particles using flow imaging microscopy is useful for evaluating protein aggregates that may induce immunogenicity. Automated labeling is desirable to distinguish harmless components such as silicone oil (SO) from subvisible part...
Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG.
Biosensors
Oct 29, 2024
This work reports an efficient method to detect SARS-CoV-2 antibodies in blood samples based on SERS combined with a machine learning tool. For this purpose, gold nanoparticles directly conjugated with spike protein were used in human blood samples t...
Deep humoral profiling coupled to interpretable machine learning unveils diagnostic markers and pathophysiology of schistosomiasis.
Science translational medicine
Sep 18, 2024
Schistosomiasis, a highly prevalent parasitic disease, affects more than 200 million people worldwide. Current diagnostics based on parasite egg detection in stool detect infection only at a late stage, and current antibody-based tests cannot disting...
Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition.
International journal of molecular sciences
Sep 16, 2024
In immunoglobulin G (IgG), -glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates...
COVID-19 IgG antibodies detection based on CNN-BiLSTM algorithm combined with fiber-optic dataset.
Journal of virological methods
Aug 16, 2024
The urgent need for efficient and accurate automated screening tools for COVID-19 detection has led to research efforts exploring various approaches. In this study, we present pioneering research on COVID-19 detection using a hybrid model that combin...
Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19.
Talanta
Jul 31, 2024
This study explores the molecular alterations and disease progression in COVID-19 patients using ATR-FTIR spectroscopy combined with spectrochemical and explainable artificial intelligence (XAI) approaches. Blood serum samples from intubated patients...
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