AIMC Topic: Particle Size

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Anticoagulation colloidal microrobots based on heparin-mimicking polymers.

Journal of colloid and interface science
Coagulation within blood vessels is a major cause of cardiovascular disease and global mortality, highlighting the urgent need for effective anticoagulant strategies. In this study, we introduce a dynamic and highly efficient anticoagulant platform, ...

Machine Learning-Driven Multi-Emission Fluorescence Array for Simultaneous Size Discrimination and Quantification of Gold Nanoparticles.

Analytical chemistry
Gold nanoparticles (AuNPs) exhibit size-dependent environmental behaviors and bioaccumulation risks, necessitating precise characterization of their hydrodynamic dimensions and concentrations for toxicity assessment. Existing analytical platforms are...

Identification and Classification of Functional Split G-Quadruplexes Using Machine Learning-Guided Activity Screening.

ACS applied bio materials
Split G-quadruplexes are considered excellent tools for biosensing and diagnostics, but splitting G-quadruplexes may often lead to a loss of function, limiting their effectiveness. This study aims to identify and classify functional split G-quadruple...

Exploring nanoparticles in lungs under COPD conditions for nanospray drug flow and deposition: CFD simulations and AI predictions.

International journal of pharmaceutics
Chronic obstructive pulmonary disease (COPD) plays a heavy burden on individuals and the social health system, not only causing direct medical costs but also economic losses. Today, treatments for COPD include drugs, bronchodilators, and oxygen thera...

Unsupervised Adaptive Deep Learning Framework for Video Denoising in Light Scattering Imaging.

Analytical chemistry
Light scattering is a powerful tool that has been widely applied in various scenarios, such as nanoparticle analysis, single-cell measurement, and blood flow monitoring. However, noise is always a concerning and challenging issue in light scattering ...

The Application of Anisotropically Collapsing Gels, Deep Learning, and Optical Microscopy for Chemical Characterization of Nanoparticles and Nanoplastics.

Langmuir : the ACS journal of surfaces and colloids
The surface chemistry of nanomaterials, particularly the density of functional groups, governs their behavior in applications such as bioanalysis, bioimaging, and environmental impact studies. Here, we report a precise method to quantify carboxyl gro...

Machine learning predictions of drug release from isocyanate-derived aerogels.

Journal of materials chemistry. B
This work utilized machine learning (ML) algorithms to predict and validate the drug release kinetics of a short worm-like nanostructured isocyanate-derived aerogel: the first time ML has been employed to study the drug delivery properties of this i...

Machine-Learning Framework to Predict the Performance of Lipid Nanoparticles for Nucleic Acid Delivery.

ACS applied bio materials
Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucleic acids across biological membranes, low cytotoxicity, improved pharmacokinetics, and scalability....

Machine learning-assisted prediction and identification of key factors affecting nitrogen metabolism for aerobic granular sludge.

Environmental research
To achieve higher denitrification efficiency with reduced energy consumption in aerobic granular sludge (AGS) system, a systematic evaluation of the carbon and nitrogen metabolism process for AGS under different stage is essential. Herein, this study...

Analysis of TEM micrographs with deep learning reveals APOE genotype-specific associations between HDL particle diameter and Alzheimer's dementia.

Cell reports methods
High-density lipoprotein (HDL) particle diameter distribution is informative in the diagnosis of many conditions, including Alzheimer's disease (AD). However, obtaining an accurate HDL size measurement is challenging. We demonstrated the utility of m...