AIMC Topic: Colorimetry

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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...

Morphological characterization and machine learning-based hyperspectral identification of naturally pigmented traditional Chinese starches.

Food chemistry
As an intangible cultural heritage, food products derived from naturally pigmented traditional starches are facing a market trust crisis due to the adulteration of dyed starch. This study aimed to develop an integrated identification system to differ...

Machine Learning-Assisted Fe-N-C Single-Atom Nanozyme Rapid Screening Platform for Acetylcholinesterase Inhibitors.

Analytical chemistry
Traditional screening methods for acetylcholinesterase inhibitors (AChEIs) encounter significant challenges due to two primary factors: subjective errors in colorimetric analysis and reliance on laboratory instruments. To overcome these limitations, ...

Colorimetric sensor array enabled by deep eutectic solvent-regulated anthocyanins and electrospun polylactic acid nanofiber for pork freshness monitoring.

Food chemistry
In this study, we constructed a bilayer colorimetric sensor array with carboxymethyl cellulose, deep eutectic solvent-regulated anthocyanins, and electrospun polylactic acid nanofibers for real-time monitoring pork freshness. The nanofibers were laye...

Colorimetric sensor array for flavonoids recognition based on peroxidase-like FeCo nanosheet.

Food chemistry
Flavonoids themselves have antioxidant, anti-inflammatory, anticancer, and antiviral effects, so it is necessary to conduct rapid, efficient, and intelligent identification and quantitative analysis of flavonoids. Herein, based on the differential co...

Rapid colorimetric antimicrobial susceptibilities direct from positive blood culture for Gram-negative bacteria.

Microbiology spectrum
UNLABELLED: Bloodstream infections (BSIs) have become increasingly challenging to treat due to emerging antimicrobial resistance (AMR). As rapid administration of appropriate antimicrobials is crucial to positive patient outcomes, clinical alternativ...

Machine learning-assisted detection of single-point mutations DNA-templated gold nanoparticle growth.

Nanoscale
Detecting single point mutations, such as PIK3CA mutations, is vital for precision diagnostics but remains challenging due to subtle sequence differences. This study introduces a machine learning-assisted colorimetric biosensor that utilizes DNA-temp...

Efficacious paper-based colorimetric detection of bacterial contamination in vegetables utilizing indicator dyes and machine learning.

Food chemistry
Food contamination from bacteria and resulting spoilage has been a persistent problem in the supply chain, leading to substantial waste and financial loss. Likewise, vegetables are prone to microbial contamination due to poor/unhygienic agricultural ...

A Machine Learning-Driven Cyclic Optimizing Strategy for the Construction of Paper-Based Microfluidic Devices in the Early Diagnosis of Periodontitis.

ACS sensors
The lack of effective optimization strategies hinders the optimal performance of paper-based microfluidic analytical devices (μPADs). In this work, a Machine Learning-driven Computer vision-BP Neural Networks-Genetic Algorithm-based Cyclic Optimizing...