AIMC Topic: Limit of Detection

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Machine learning-assisted SERS detection of pyrethroid pesticides in edible fungi using a magnetic nanosensor.

Mikrochimica acta
Pyrethroid pesticide residues pose a significant global public health challenge, particularly in complex edible fungus matrices where trace, structurally similar pesticides are difficult to distinguish and detect. To address this critical gap, a nove...

Development of liquid biopsy for screening colorectal cancer through the combination of an antibody microarray-based metal-enhanced sandwich immunofluorescent assay of cytokines with machine learning.

The Analyst
The simultaneous determination of the expression levels of multiple inflammation-associated cytokines in blood holds great promise for the early screening of cancer including colorectal cancer (CRC). Herein, an antibody microarray-based sandwich meta...

High Na-Adducted Ion Selectivity in Laser Desorption/Ionization Mass Spectrometry with a Steric-Tuned COF.

Analytical chemistry
Laser desorption-ionization mass spectrometry (LDI-MS) is prized for its rapidity, simplicity, low sample consumption, and high throughput in metabolic analysis, with great potential as a diagnostic tool. Herein, an LDI-MS method with sulfone-contain...

Entropy-driven signal amplification integrated with machine learning in multiplex lateral flow immunoassay for sensitive Point-of-Care colon cancer diagnosis.

Journal of nanobiotechnology
Investigations on epithelial-mesenchymal transition (EMT) events occurring on circulating tumor cells (CTCs) are poised to significantly advance nanoliquid biopsy methodologies. This study presented a colorimetric multiplex lateral flow immunoassay s...

Deep Learning Algorithms Enabled Visual Detection of Anthrax Biomarkers by MnO Nanozyme-Based Colorimetric Sensor Array.

Analytical chemistry
This study develops an innovative approach that integrates a colorimetric sensor array (CSA) composed of phenylalanine-modified MnO nanozymes with advanced algorithms, aiming to detect the anthrax biomarker 2,6-pyridine dicarboxylic acid (2,6-PDA) an...

Machine learning-integrated electrochemical sensing of ciprofloxacin for digital point-of-care therapeutic drug monitoring.

Mikrochimica acta
Timely and precise therapeutic drug monitoring (TDM) is critical for managing pharmacokinetic variability and optimizing individualized therapy, particularly during public health crises such as the COVID-19 pandemic. Herein, we optimized integrated m...

AI-Assisted Microfluidic Paper-Based Analytical Device with Au-Pt Nanoparticles for Multiplex, Interference-Resistant Quantification of Urinary Biomarkers.

Analytical chemistry
Urinary glucose, creatinine, and uric acid are vital biomarkers for diabetes and kidney disease management. However, multiplex point-of-care detection faces challenges due to insufficient sensitivity in complex urine matrices and signal cross-talk fr...

Machine Learning-Assisted Ratiometric Fluorescence Electrospun Nanofiber Films for Portable and Intelligent Monitoring of Multiple Alkylresorcinol Homologues in Whole Wheat Foods.

ACS applied materials & interfaces
The intelligent authentication of whole wheat products remains a significant challenge due to the difficulty in simultaneously monitoring multiple alkylresorcinol (AR) homologues within complex food matrices. To address this, we have developed a nove...

Flexible Porous ACH/Ag Surface-Enhanced Raman Scattering Platform for Sensitive Detection and Machine-Learning-Assisted Classification of Multiple Pathogenic Bacteria.

Analytical chemistry
Pathogenic bacteria pose serious threats to public health and environmental safety. Conventional colony counting, a standard method for bacterial detection, is time-consuming and unsuitable for rapid on-site detection. In this work, a flexible ACH/Ag...

Machine learning-assisted multicolor identification and quantification of antidepressant drugs by waste-derived fluorescent nanoprobes: Towards green AI-based electronic tongue.

Analytica chimica acta
Recently, the severe side effects related to the widespread consumption of antidepressants (ADs) have alarmingly created a global challenge for clinics and forensic laboratories. This study introduces a machine learning-empowered multicolor fluoresce...