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Nanoparticles

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Electrospray mode discrimination with current signal using deep convolutional neural network and class activation map.

Scientific reports
The electrospray process has been extensively applied in various fields, including energy, display, sensor, and biomedical engineering owing to its ability to generate of functional micro/nanoparticles. Although the mode of the electrospray process h...

Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning.

ACS nano
High-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) can be acquired together with energy dispersive X-ray (EDX) spectroscopy to give complementary information on the nanoparticles being imaged. Recent deep learning ...

A Flexible Artificial Sensory Nerve Enabled by Nanoparticle-Assembled Synaptic Devices for Neuromorphic Tactile Recognition.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Tactile perception enabled by somatosensory system in human is essential for dexterous tool usage, communication, and interaction. Imparting tactile recognition functions to advanced robots and interactive systems can potentially improve their cognit...

Influence of Garlic (Allium sativum) Clove-Based Selenium Nanoparticles on Status of Nutritional, Biochemical, Enzymological, and Gene Expressions in the Freshwater Prawn Macrobrachium rosenbergii (De Man, 1879).

Biological trace element research
Selenium (Se) is one of the essential micronutrients for performing vital body functions. This study aims at examining the influence of dietary supplementation of garlic clove-based green-synthesized selenium nanoparticles (GBGS-SeNPs, 48-87 nm) on c...

High relaxivity Gd-based organic nanoparticles for efficient magnetic resonance angiography.

Journal of nanobiotechnology
Contrast-enhanced MR angiography (MRA) is a critical technique for vascular imaging. Nevertheless, the efficacy of MRA is often limited by the low rate of relaxation, short blood-circulation time, and metal ion-released potential long-term toxicity o...

High Resolution of Plasmonic Resonance Scattering Imaging with Deep Learning.

Analytical chemistry
The dark-field microscopy (DFM) imaging technology has the advantage of a high signal-to-noise ratio, and it is often used for real-time monitoring of plasmonic resonance scattering and biological imaging at the single-nanoparticle level. Due to the ...

Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions.

Proceedings of the National Academy of Sciences of the United States of America
SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamag...

Biofilm inhibition in Candida albicans with biogenic hierarchical zinc-oxide nanoparticles.

Biomaterials advances
The present study demonstrates lignin (L), fragments of lignin (FL), and oxidized fragmented lignin (OFL) as templates for the synthesis of zinc oxide nanoparticles (ZnO NPs) viz., lignin-ZnO (L-ZnO), hierarchical FL-ZnO, and OFL-ZnO NPs. The X-ray d...

Ultrasound Elastography under Deep Learning Algorithm to Analyze the Therapeutic Effect of Clustered Regularly Interspaced Short Palindromic Repeats Short Hairpin Ribonucleic Acid Nanoparticles on Cervical Cancer.

Journal of healthcare engineering
This study aimed to analyze the effect of the deep learning algorithm on ultrasound elastography on the treatment of cervical cancer with clustered regularly interspaced short palindromic repeats (CRISPR) short hairpin ribonucleic acid (shRNA) nanopa...

Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning.

International journal of molecular sciences
The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built to predict the probability of different ...