AIMC Topic: Microscopy, Electron, Transmission

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Impact of dental pulp cells-derived small extracellular vesicles on the properties and behavior of dental pulp cells: an in-vitro study.

BMC oral health
BACKGROUND: Dental pulp cells-derived small extracellular vesicles (DPCs-sEVs) had shown immunomodulatory, anti-inflammatory, and tissue function restorative abilities. Therefore, DPCs-sEVs should be considered as a promising regenerative tool for de...

Heterogeneous virus classification using a functional deep learning model based on transmission electron microscopy images.

Scientific reports
Viruses are submicroscopic agents that can infect other lifeforms and use their hosts' cells to replicate themselves. Despite having simplistic genetic structures among all living beings, viruses are highly adaptable, resilient, and capable of causin...

Classification of rotation-invariant biomedical images using equivariant neural networks.

Scientific reports
Transmission electron microscopy (TEM) is an imaging technique used to visualize and analyze nano-sized structures and objects such as virus particles. Light microscopy can be used to diagnose diseases or characterize e.g. blood cells. Since samples ...

Deep Neural Network-Based Electron Microscopy Image Recognition for Source Distinguishing of Anthropogenic and Natural Magnetic Particles.

Environmental science & technology
Deep learning models excel at image recognition of macroscopic objects, but their applications to nanoscale particles are limited. Here, we explored their potential for source-distinguishing environmental particles. Transmission electron microscopy (...

Measuring cryo-TEM sample thickness using reflected light microscopy and machine learning.

Journal of structural biology
In cryo-transmission electron microscopy (cryo-TEM), sample thickness is one of the most important parameters that governs image quality. When combining cryo-TEM with other imaging methods, such as light microscopy, measuring and controlling the samp...

Automated Image Analysis for Single-Atom Detection in Catalytic Materials by Transmission Electron Microscopy.

Journal of the American Chemical Society
Single-atom catalytic sites may have existed in all supported transition metal catalysts since their first application. Yet, interest in the design of single-atom heterogeneous catalysts (SACs) only really grew when advances in transmission electron ...

High-throughput segmentation of unmyelinated axons by deep learning.

Scientific reports
Axonal characterizations of connectomes in healthy and disease phenotypes are surprisingly incomplete and biased because unmyelinated axons, the most prevalent type of fibers in the nervous system, have largely been ignored as their quantitative asse...

TEM virus images: Benchmark dataset and deep learning classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To achieve the full potential of deep learning (DL) models, such as understanding the interplay between model (size), training strategy, and amount of training data, researchers and developers need access to new dedicated im...

Deep learning-based predictive identification of neural stem cell differentiation.

Nature communications
The differentiation of neural stem cells (NSCs) into neurons is proposed to be critical in devising potential cell-based therapeutic strategies for central nervous system (CNS) diseases, however, the determination and prediction of differentiation is...

Learning-based defect recognition for quasi-periodic HRSTEM images.

Micron (Oxford, England : 1993)
Controlling crystalline material defects is crucial, as they affect properties of the material that may be detrimental or beneficial for the final performance of a device. Defect analysis on the sub-nanometer scale is enabled by high-resolution scann...