AIMC Topic: Copper

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Application of copper based single-atom nanozymes in wound healing and tumor treatment.

Journal of materials chemistry. B
Single-atom nanozymes (SANs) with transition metals as their core are nanomaterials characterized by atomically dispersed active sites and intrinsic enzyme-mimicking activity, exhibiting ultrahigh catalytic efficiency. As an essential trace element a...

Deep Learning Exploration Expands the Natural Diversity of Metallothioneins in the Archaea Domain.

Journal of agricultural and food chemistry
The diversity and functions of metallothioneins (MTs) in Archaea remain poorly understood. This study identifies 180 archaeal MTs from 406 genomes, revealing distinct evolutionary lineages and structural diversity. Phylogenetic analysis suggests a no...

Integrating AI-assisted SERS Biosensing and Photoactivated Antibacterial Therapy in Au@CuSe for Combating Multidrug-Resistant Bacteria.

Analytical chemistry
The escalating global crisis of multidrug-resistant (MDR) bacteria demands innovative strategies that bypass conventional antibiotic limitations. This study introduced a multifunctional Au@CuSe core-shell nanoplatform integrating artificial intellige...

Early diagnosis of transient ischemic attack facilitated by SERS-based artificial intelligence sensors.

Mikrochimica acta
Transient ischemic attack (TIA) serves as a critical early warning sign for ischemic stroke. Its timely identification holds significant clinical value in reducing recurrence risk and improving patient prognosis. However, existing detection methods e...

Machine learning-assisted multi-channel nanozyme sensor arrays for multiple pesticide tracking, tracing and metabolism analysis.

Biosensors & bioelectronics
To achieve precise pesticide residue detection and metabolic analysis, we innovatively proposed a machine learning-assisted multi-channel nanozyme sensor array. Five Cu-carboxylate nanozymes with outstanding laccase-like and peroxidase-like activitie...

Bridging Dissolved Organic Matter Reactivity to Ozonation Catalysts for Cu@AlO from the Molecular Level by Machine Learning.

Environmental science & technology
Catalytic ozonation is a widely used advanced oxidation process for treating refractory organic wastewater; yet, the variability in dissolved organic matter (DOM) composition complicates reaction mechanisms. A critical challenge lies in designing opt...

Kinetic and Mechanistic Discrepancies of Single/Dual-Atom Nanozymes Drive a Triple-Channel Sensing Array for Machine Learning-Assisted Antioxidant Discrimination.

Analytical chemistry
Current colorimetric sensing arrays for antioxidant detection often struggle with discrimination due to cross-reactive signals from individual nanozymes. These signals are typically modulated by external factors such as pH or chromogenic substrates, ...

Synthesis and characterization of lignin-copper nanohybrids for colorimetric acetaminophen detection: a combined physical chemistry and machine learning study.

Physical chemistry chemical physics : PCCP
Acetaminophen ranks among the most widely used pharmaceutical and personal care products today. Following consumption, the drug and its metabolites are excreted into sewage systems, wastewater treatment plants, and various aquatic environments, leadi...

Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite.

Scientific reports
This research proposes a machine learning controlled method for removing the antibiotic oxytetracycline (OTC) from liquids through the use of nanostructured cupric oxide (CuO) nanoparticles. These nanoparticles are attached to magnetic chitosan/algin...

Photocatalytic microrobots for treating bacterial infections deep within sinuses.

Science robotics
Microrobotic techniques are promising for treating biofilm infections located deep within the human body. However, the presence of highly viscous pus presents a formidable biological barrier, severely restricting targeted and minimally invasive treat...