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Metal Nanoparticles

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A deep learning approach to gold nanoparticle quantification in computed tomography.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
INTRODUCTION: Deep learning (DL) is used to classify, detect, and quantify gold nanoparticles (AuNPs) in a human-sized phantom with a clinical MDCT scanner.

A deep learning approach to identifying immunogold particles in electron microscopy images.

Scientific reports
Electron microscopy (EM) enables high-resolution visualization of protein distributions in biological tissues. For detection, gold nanoparticles are typically used as an electron-dense marker for immunohistochemically labeled proteins. Manual annotat...

Machine learning predictions of concentration-specific aggregate hazard scores of inorganic nanomaterials in embryonic zebrafish.

Nanotoxicology
The possibility of employing computational approaches like nano-QSAR or nano-read-across to predict nanomaterial hazard is attractive from both a financial, and most importantly, where in vivo tests are required, ethical perspective. In the present w...

Hg(II) sensing, catalytic, antioxidant, antimicrobial, and anticancer potential of Garcinia mangostana and α-mangostin mediated silver nanoparticles.

Chemosphere
This study reports synthesis of Garcinia mangostana fruit pericarp (unwanted waste material) and α-mangostin mediated silver nanoparticles (AgNPs). These AgNPs were efficiently produced using 1:10 (extract and salt) ratio under stirring and heating, ...

An antibody-free liver cancer screening approach based on nanoplasmonics biosensing chips via spectrum-based deep learning.

NanoImpact
The clinical needs of rapidly screening liver cancer in large populations have asked for a facile and low-cost point-of-care testing (POCT) method. We present a nanoplasmonics biosensing chip (NBC) that would empower antibody-free detection with simp...

Machine-Learning-Based Approach to Decode the Influence of Nanomaterial Properties on Their Interaction with Cells.

ACS applied materials & interfaces
In an nanotoxicity system, cell-nanoparticle (NP) interaction leads to the surface adsorption, uptake, and changes into nuclei/cell phenotype and chemistry, as an indicator of oxidative stress, genotoxicity, and carcinogenicity. Different types of n...

Label-Free Detection of Based on Bacteria-Imprinted Polymer and Turn-on Fluorescence Probes.

ACS applied bio materials
The effective identification and quantitative determination of is a major public health concern. Here, an innovative strategy that combines a bacteria-imprinted polydimethylsiloxane film for bacterial recognition and fluorescence resonance energy tr...

Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning.

ACS nano
Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious diseases. However, the high variability in cellphone image data acquisition and the common need for l...

Improved Antibiotic Detection in Raw Milk Using Machine Learning Tools over the Absorption Spectra of a Problem-Specific Nanobiosensor.

Sensors (Basel, Switzerland)
In this article we present the development of a biosensor system that integrates nanotechnology, optomechanics and a spectral detection algorithm for sensitive quantification of antibiotic residues in raw milk of cow. Firstly, nanobiosensors were des...

Bioinspired Soft Microrobots with Precise Magneto-Collective Control for Microvascular Thrombolysis.

Advanced materials (Deerfield Beach, Fla.)
New-era soft microrobots for biomedical applications need to mimic the essential structures and collective functions of creatures from nature. Biocompatible interfaces, intelligent functionalities, and precise locomotion control in a collective manne...