AIMC Topic: Platinum
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Ligand Microenvironment-Regulated Nanozymes Enabled Machine Learning-Assisted Sensor Array for Simultaneous Identification of Phenolic Pollutants.
ACS sensors
Jul 15, 2025
Phenolic pollutants pose a great threat to human health due to high toxicity, whereas existing methods are difficult to achieve the rapid recognition of multiple phenolic pollutants. In this study, we developed a novel machine learning-assisted senso...
Microrobots for Antibiotic-Resistant Skin Colony Eradication.
ACS applied materials & interfaces
Jun 25, 2025
Self-propelled nano- and micromachines have immense potential as autonomous seek-and-act devices in biomedical applications. In this study, we present microrobots constructed with inherently biocompatible materials and propulsion systems tailored to ...
Split DNA Tetrahedron-Mediated Spatiotemporal-Hierarchy CRISPR Cascade Integrated with Au@Pt Nanolabels and Artificial Intelligence for a Cervical Cancer MicroRNA Bioassay.
ACS nano
Jun 11, 2025
The screening and monitoring of microRNAs as cancer molecular biomarkers is clinically significant, but traditional methods lack sufficient sensitivity, accuracy, and convenience. The CRISPR-colorimetric lateral flow assay (CLFA) integration offers a...
Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning.
Analytical chemistry
Mar 27, 2025
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...
Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes.
Journal of inorganic biochemistry
Mar 10, 2025
Predicting the solubility and lipophilicity of platinum(II, IV) complexes is essential for prioritizing potential anticancer candidates in drug discovery. This study introduces the first publicly available online model for predicting the solubility o...
Active Microrobots for Dual Removal of Biofilms via Chemical and Physical Mechanisms.
ACS applied materials & interfaces
Jan 2, 2025
Bacterial biofilms are complex multicellular communities that adhere firmly to solid surfaces. They are widely recognized as major threats to human health, contributing to issues such as persistent infections on medical implants and severe contaminat...
Smartphone-Assisted Nanozyme Colorimetric Sensor Array Combined "Image Segmentation-Feature Extraction" Deep Learning for Detecting Unsaturated Fatty Acids.
ACS sensors
Sep 19, 2024
Conventional methods for detecting unsaturated fatty acids (UFAs) pose challenges for rapid analyses due to the need for complex pretreatment and expensive instruments. Here, we developed an intelligent platform for facile and low-cost analysis of UF...
Deep Learning Artificial Intelligence Predicts Homologous Recombination Deficiency and Platinum Response From Histologic Slides.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Jul 31, 2024
PURPOSE: Cancers with homologous recombination deficiency (HRD) can benefit from platinum salts and poly(ADP-ribose) polymerase inhibitors. Standard diagnostic tests for detecting HRD require molecular profiling, which is not universally available.
Application of triple-branch artificial neural network system for catalytic pellets combustion.
Journal of environmental management
Jul 10, 2024
On the international level, it is common to act on reducing emissions from energy systems. However, in addition to industrial emissions, low-stack emissions also make a significant contribution. A good step in reducing its environmental impact, is to...
Potential prediction and coupling relationship revealing for recovery of platinum group metals from spent auto-exhaust catalysts based on machine learning.
Journal of environmental management
Jun 24, 2024
As hazardous waste, the massive generation of spent auto-exhaust catalysts (SACs) puts enormous pressure on environmental management, but provides a rare opportunity for platinum group metals (PGMs) recycling. In this study, machine learning (ML) met...
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