Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 5 de 5
Filtrar
Más filtros

Bases de datos
Tipo del documento
Asunto de la revista
País de afiliación
Intervalo de año de publicación
1.
Wellcome Open Res ; 9: 296, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39309225

RESUMEN

The experimental limitations with optics observed in many microscopy and astronomy instruments result in detrimental effects for the imaging of objects. This can be generally described mathematically as a convolution of the real object image with the point spread function that characterizes the optical system. The popular Richardson-Lucy (RL) deconvolution algorithm is widely used for the inverse process of restoring the data without these optical aberrations, often a critical step in data processing of experimental data. Here we present the versatile RedLionfish python package, that was written to make the RL deconvolution of volumetric (3D) data easier to run, very fast (by exploiting GPU computing capabilities) and with automatic handling of hardware limitations for large datasets. It can be used programmatically in Python/numpy using conda or PyPi package managers, or with a graphical user interface as a napari plugin.


In order to observe biological phenomena at microscopic scale, light or fluorescent microscopes are often used. These instruments use optical devices such as lenses and mirrors to guide light and help form an image that can be recorded and analyzed. Modern optical methods and techniques have been developed so that scientists can obtain 3D images of microscopic objects of interest, such as confocal microscopy or light sheet microscopy. Currently, optical instruments can readily observe cells and their contents down to a few nanometers resolution (e.g.: chromosomes). However, there are physical limitations that prevent the resolution of images below a nanometer. One such limitation comes from the inherent property of light itself as an electromagnetic wave with wavelengths in the hundreds of nanometers range. Another major limitation comes from the guiding optics used to both illuminate the object and to probe the samples being studied. This results in images that are unavoidably blurry preventing differentiation of small, nearby details. Fortunately, with a good understanding of what causes the blurriness, it is possible to use a filter to reverse it, and recover the image to closely match its non-blurred form. This filter is widely used by scientists and is called the Richardson-Lucy deconvolution algorithm. Although this filter is widely available in many scientific software packages, its implementation is often slow and limited to particular imaging analysis applications, with poor programmatic access. With the popularity of the Python programming language, and an open-source image viewer (napari) we have developed the Redlionfish package to apply the RL filter to 3D image data in a speed optimized manner, while also being easy to use and to install.

2.
Nat Commun ; 14(1): 629, 2023 02 06.
Artículo en Inglés | MEDLINE | ID: mdl-36746945

RESUMEN

Structural biology studies inside cells and tissues require methods to thin vitrified specimens to electron transparency. Until now, focused ion beams based on gallium have been used. However, ion implantation, changes to surface chemistry and an inability to access high currents limit gallium application. Here, we show that plasma-coupled ion sources can produce cryogenic lamellae of vitrified human cells in a robust and automated manner, with quality sufficient for pseudo-atomic structure determination. Lamellae were produced in a prototype microscope equipped for long cryogenic run times (> 1 week) and with multi-specimen support fully compatible with modern-day transmission electron microscopes. We demonstrate that plasma ion sources can be used for structural biology within cells, determining a structure in situ to 4.9 Å, and characterise the resolution dependence on particle distance from the lamella edge. We describe a workflow upon which different plasmas can be examined to further streamline lamella fabrication.


Asunto(s)
Electrones , Microscopía , Humanos , Flujo de Trabajo , Carmustina
3.
Biol Imaging ; 3: e10, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-38487693

RESUMEN

Electron cryo-tomography is an imaging technique for probing 3D structures with at the nanometer scale. This technique has been used extensively in the biomedical field to study the complex structures of proteins and other macromolecules. With the advancement in technology, microscopes are currently capable of producing images amounting to terabytes of data per day, posing great challenges for scientists as the speed of processing of the images cannot keep up with the ever-higher throughput of the microscopes. Therefore, automation is an essential and natural pathway on which image processing-from individual micrographs to full tomograms-is developing. In this paper, we present Ot2Rec, an open-source pipelining tool which aims to enable scientists to build their own processing workflows in a flexible and automatic manner. The basic building blocks of Ot2Rec are plugins which follow a unified application programming interface structure, making it simple for scientists to contribute to Ot2Rec by adding features which are not already available. In this paper, we also present three case studies of image processing using Ot2Rec, through which we demonstrate the speedup of using a semi-automatic workflow over a manual one, the possibility of writing and using custom (prototype) plugins, and the flexibility of Ot2Rec which enables the mix-and-match of plugins. We also demonstrate, in the Supplementary Material, a built-in reporting feature in Ot2Rec which aggregates the metadata from all process being run, and output them in the Jupyter Notebook and/or HTML formats for quick review of image processing quality. Ot2Rec can be found at https://github.com/rosalindfranklininstitute/ot2rec.

4.
Biol Imaging ; 3: e9, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-38487692

RESUMEN

An emergent volume electron microscopy technique called cryogenic serial plasma focused ion beam milling scanning electron microscopy (pFIB/SEM) can decipher complex biological structures by building a three-dimensional picture of biological samples at mesoscale resolution. This is achieved by collecting consecutive SEM images after successive rounds of FIB milling that expose a new surface after each milling step. Due to instrumental limitations, some image processing is necessary before 3D visualization and analysis of the data is possible. SEM images are affected by noise, drift, and charging effects, that can make precise 3D reconstruction of biological features difficult. This article presents Okapi-EM, an open-source napari plugin developed to process and analyze cryogenic serial pFIB/SEM images. Okapi-EM enables automated image registration of slices, evaluation of image quality metrics specific to pFIB-SEM imaging, and mitigation of charging artifacts. Implementation of Okapi-EM within the napari framework ensures that the tools are both user- and developer-friendly, through provision of a graphical user interface and access to Python programming.

5.
Elife ; 122023 02 21.
Artículo en Inglés | MEDLINE | ID: mdl-36805107

RESUMEN

Serial focussed ion beam scanning electron microscopy (FIB/SEM) enables imaging and assessment of subcellular structures on the mesoscale (10 nm to 10 µm). When applied to vitrified samples, serial FIB/SEM is also a means to target specific structures in cells and tissues while maintaining constituents' hydration shells for in situ structural biology downstream. However, the application of serial FIB/SEM imaging of non-stained cryogenic biological samples is limited due to low contrast, curtaining, and charging artefacts. We address these challenges using a cryogenic plasma FIB/SEM. We evaluated the choice of plasma ion source and imaging regimes to produce high-quality SEM images of a range of different biological samples. Using an automated workflow we produced three-dimensional volumes of bacteria, human cells, and tissue, and calculated estimates for their resolution, typically achieving 20-50 nm. Additionally, a tag-free localisation tool for regions of interest is needed to drive the application of in situ structural biology towards tissue. The combination of serial FIB/SEM with plasma-based ion sources promises a framework for targeting specific features in bulk-frozen samples (>100 µm) to produce lamellae for cryogenic electron tomography.


Asunto(s)
Tomografía con Microscopio Electrónico , Imagenología Tridimensional , Humanos , Microscopía Electrónica de Rastreo , Tomografía con Microscopio Electrónico/métodos , Iones , Imagenología Tridimensional/métodos
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA