AIMC Topic: Gold

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Comparative examination of the chemistry and biology of AI-driven gold NPs in Theranostics: New insights into biosensing, bioimaging, genomics, diagnostics, and therapy.

Nanomedicine : nanotechnology, biology, and medicine
Integrating artificial intelligence (AI) with nanomedicine is transforming Theranostics, driving advances in biosensing, bioimaging, genomics, diagnostics, and treatment. This review highlights the latest advancements in AI-driven nanomedicine, focus...

Physically grounded deep learning-enabled gold nanoparticle localization and quantification in photonic resonator absorption microscopy for digital resolution molecular diagnostics.

Biosensors & bioelectronics
Accurate molecular biomarker detection with digital-resolution sensitivity is essential for applications such as disease diagnostics, therapeutic studies, and biomedical research. Here, we present LOCA-PRAM (LOcalization with Context Awareness), a de...

Single-Component Double-Emissive Ratiometric Probe: Toward Machine Learning Driven Detection and Discrimination of Neurological Biomarkers.

Analytical chemistry
This study presents an attractive single-component ratiometric fluorescent sensor that utilizes the oxidation of BSA-protected Au nanoclusters (BSA-Au NCs) by -Bromosuccinimide (NBS) to detect catecholamine neurotransmitters and their metabolites, wh...

Deep Learning-driven Microfluidic-SERS to Characterize the Heterogeneity in Exosomes for Classifying Non-Small Cell Lung Cancer Subtypes.

ACS sensors
Lung cancer exhibits strong heterogeneity, and its early diagnosis and precise subtyping are of great importance, as they can increase the ability to deliver personalized medicines by tailoring therapy regimens. Tissue biopsy, albeit the gold standar...

Gold nanorods as multidimensional optical nanomaterials: machine learning-enhanced quantitative fingerprinting of proteins for diagnostic applications.

Nanoscale
The rapid and precise quantification and identification of proteins as key diagnostic biomarkers hold significant promise in allergy testing, disease diagnosis, clinical treatment, and proteomics. This is crucial because alterations in disease-associ...

Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning.

Analytical chemistry
Gold nanoparticles (GNPs), which appear red, are widely used as labels in lateral flow assays (LFAs) for visual detection. However, in blood-derived samples, hemolysis─caused by the rupture of red blood cells and the release of hemoglobin─creates a r...

A new approach to dilution prediction of underground mine gold using computing techniques.

Anais da Academia Brasileira de Ciencias
Controlling ore dilution in underground mining is challenging. In this study, data from a Brazilian gold mine were analyzed, covering 70 chambers and 26 variables. Six key variables were identified through decision tree analysis, forming the basis of...

Fast screening of COVID-19 inpatient samples by integrating machine learning and label-free SERS methods.

Analytica chimica acta
BACKGROUND: Advances in bio-analyte detection demonstrate the need for innovation to overcome the limitations of traditional methods. Emerging viruses evolve into variants, driving the need for fast screening to minimize the time required for positiv...

Rapid and Differential Diagnosis of Sepsis Stages Using an Advanced 3D Plasmonic Bimetallic Alloy Nanoarchitecture-Based SERS Biosensor Combined with Machine Learning for Multiple Analyte Identification.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Rapid and accurate differential diagnosis of infections, sepsis, and septic shock is essential for preventing unnecessary antibiotic overuse and improving the chance of patient survival. To address this, a 3D gold nanogranule decorated gold-silver al...

Dual-Mode Colorimetric/SERS Lateral Flow Immunoassay with Machine Learning-Driven Optimization for Ultrasensitive Mycotoxin Detection.

Analytical chemistry
Detecting and quantifying mycotoxins using LFIA are challenging due to the need for high sensitivity and accuracy. To address this, a dual-mode colorimetric-SERS LFIA was developed for detecting deoxynivalenol (DON). Rhodium nanocores provided strong...