AIMC Topic: Silver

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Rapid identification and quantitative analysis of malachite green in fish via SERS and 1D convolutional neural network.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Rapid and quantitative detection of malachite green (MG) in aquaculture products is very important for safety assurance in food supply. Here, we develop a point-of-care testing (POCT) platform that combines a flexible and transparent surface-enhanced...

Precision classification and quantitative analysis of bacteria biomarkers via surface-enhanced Raman spectroscopy and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The SERS spectra of six bacterial biomarkers, 2,3-DHBA, 2,5-DHBA, Pyocyanin, lipoteichoic acid (LTA), Enterobactin, and β-carotene, of various concentrations, were obtained from silver nanorod array substrates, and the spectral peaks and the correspo...

Rapid Detection of SARS-CoV-2 Variants Using an Angiotensin-Converting Enzyme 2-Based Surface-Enhanced Raman Spectroscopy Sensor Enhanced by CoVari Deep Learning Algorithms.

ACS sensors
An integrated approach combining surface-enhanced Raman spectroscopy (SERS) with a specialized deep learning algorithm to rapidly and accurately detect and quantify SARS-CoV-2 variants is developed based on an angiotensin-converting enzyme 2 (ACE2)-f...

Multispectral 3D DNA Machine Combined with Multimodal Machine Learning for Noninvasive Precise Diagnosis of Bladder Cancer.

Analytical chemistry
Extracellular vesicle (EV) molecular phenotyping offers enormous opportunities for cancer diagnostics. However, the majority of the associated studies adopted biomarker-based unimodal analysis to achieve cancer diagnosis, which has high false positiv...

Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid screening is the research focus of surface-enhanced Raman scattering (SERS) technology. In this study, gold@silver-porous silicon (Au@Ag-PSi) composite ...

Optimization of pullulan production by Aureobasidium pullulans using semi-solid-state fermentation and artificial neural networks: Characterization and antibacterial activity of pullulan impregnated with Ag-TiO nanocomposite.

International journal of biological macromolecules
This study presents a novel and efficient approach for pullulan production using artificial neural networks (ANNs) to optimize semi-solid-state fermentation (S-SSF) on faba bean biomass (FBB). This method achieved a record-breaking pullulan yield of ...

Discrimination of Genetic Biomarkers of Disease through Machine-Learning-Based Hypothesis Testing of Direct SERS Spectra of DNA and RNA.

ACS sensors
Cancer is globally a leading cause of death that would benefit from diagnostic approaches detecting it in its early stages. However, despite much research and investment, cancer early diagnosis is still underdeveloped. Owing to its high sensitivity, ...

Improving the detection accuracy of the dual SERS aptasensor system with uncontrollable SERS "hot spot" using machine learning tools.

Analytica chimica acta
BACKGROUND: Simultaneous detection of food contaminants is crucial in addressing the collective health hazards arising from the presence of multiple contaminants. However, traditional multi-competitive surface-enhanced Raman scattering (SERS) aptasen...

Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinach.

Journal of hazardous materials
This study introduces an innovative strategy for the rapid and accurate identification of pesticide residues in agricultural products by combining surface-enhanced Raman spectroscopy (SERS) with a state-of-the-art transformer model, termed SERSFormer...