Journal of microscopy最新文献

The curtaining effect is a common challenge in focused ion beam (FIB) surface preparation. This study investigates methods to reduce this effect during plasma FIB milling of Inconel 718 (nickel-based superalloy). Platinum deposition, silicon mask and XeF₂ gas injection were explored as potential solutions. These methods were evaluated for two ion beam current conditions; a high ion beam intensity condition (30 kV–1 µA) and a medium one (30 kV–100 nA) and their impact on curtaining reduction and resulting cross-section quality was assessed quantitatively thanks to topographic measurements done by atomic force microscopy (AFM). XeF₂ assistance notably improved cross-section quality at medium current level. Pt deposition and Si mask individually mitigated the curtaining effect, with greater efficacy at 100 nA. Both methods also contributed to reducing cross-section curvature, with the Si mask outperforming Pt deposition. However, combining Pt deposition and Si mask with XeF₂ injection led to deterioration of these protective layers and the reappearance of the curtaining effect after a quite short exposure time.

Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data-driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers. To remain competitive and at the forefront of research, implementing the FAIR principles into daily routines is an essential but challenging task for researchers and research infrastructures. Imaging core facilities, well-established providers of access to imaging equipment and expertise, are in an excellent position to lead this transformation in bioimaging research data management. They are positioned at the intersection of research groups, IT infrastructure providers, the institution´s administration, and microscope vendors. In the frame of German BioImaging – Society for Microscopy and Image Analysis (GerBI-GMB), cross-institutional working groups and third-party funded projects were initiated in recent years to advance the bioimaging community's capability and capacity for FAIR bioimage data management. Here, we provide an imaging-core-facility-centric perspective outlining the experience and current strategies in Germany to facilitate the practical adoption of the FAIR principles closely aligned with the international bioimaging community. We highlight which tools and services are ready to be implemented and what the future directions for FAIR bioimage data have to offer.

In September 2023, the two largest bioimaging networks in the Americas, Latin America Bioimaging (LABI) and BioImaging North America (BINA), came together during a 1-week meeting in Mexico. This meeting provided opportunities for participants to interact closely with decision-makers from imaging core facilities across the Americas. The meeting was held in a hybrid format and attended in-person by imaging scientists from across the Americas, including Canada, the United States, Mexico, Colombia, Peru, Argentina, Chile, Brazil and Uruguay. The aims of the meeting were to discuss progress achieved over the past year, to foster networking and collaborative efforts among members of both communities, to bring together key members of the international imaging community to promote the exchange of experience and expertise, to engage with industry partners, and to establish future directions within each individual network, as well as common goals. This meeting report summarises the discussions exchanged, the achievements shared, and the goals set during the LABIxBINA2023: Bioimaging across the Americas meeting.

Arbuscular mycorrhizal (AM) symbiosis, the nutritional partnership between AM fungi and most plant species, is globally ubiquitous and of great ecological and agricultural importance. Studying the processes of AM symbiosis is confounded by its highly spatiotemporally dynamic nature. While microscopy methods exist to probe the spatial side of this plant-fungal interaction, the temporal side remains more challenging, as reliable deep-tissue time-lapse imaging requires both symbiotic partners to remain undisturbed over prolonged time periods. Here, we introduce the AMSlide: a noninvasive, high-resolution, live-imaging system optimised for AM symbiosis research. We demonstrate the AMSlide's applications in confocal microscopy of mycorrhizal roots, from whole colonisation zones to subcellular structures, over timeframes from minutes to weeks. The AMSlide's versatility for different microscope set-ups, imaging techniques, and plant and fungal species is also outlined. It is hoped that the AMSlide will be applied in future research to fill in the temporal blanks in our understanding of AM symbiosis, as well as broader root and rhizosphere processes.

Light microscopy facilities vary in the number of imaging systems and the scope of technologies they support. Each facility must craft an identity through the selection of equipment and development of staff in order to serve the needs of its local research environment. The process of crafting a light microscopy facility can be compared to curation of an art exhibition: great care should be given to the selection and placement of each object in order to make a coherent statement.

Lay Description: Light microscopy facilities vary in the number of imaging systems and the scope of technologies they support. Each facility must develop an identity through the selection of equipment and development of staff in order to serve the needs of its local research environment. The process of crafting a light microscopy facility can be compared to curation of an art exhibition: great care should be given to the selection and placement of each object in order to make a coherent statement.

The successful operation of a light microscopy core facility depends also on the initial setup of its infrastructure. This article covers the aspects of location selection and room planning and what environmental factors need to be considered. These include light, temperature, vibrations as well as the basic installations needed for microscope operation.

Here we show that compressive sensing allows 4-dimensional (4-D) STEM data to be obtained and accurately reconstructed with both high-speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4-D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal-to-noise ratio in the recovered phase using 0.3% of the total data.

Lay abstract: Four-dimensional scanning transmission electron microscopy (4-D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2-dimensional signal is acquired at each 2-D probe location, equating to a 4-D dataset.

Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4-D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100-1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4-D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination.

Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10-100 times. The acquired data is then processed to fill-in or inpaint the missing data, taking advantage of the inherently low-complex signals which can be linearly combined to recover the information.

In this work, similar methods are demonstrated for the acquisition of 4-D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4-D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100-300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

Centralised core facilities have evolved into vital components of life science research, transitioning from a primary focus on centralising equipment to ensuring access to technology experts across all facets of an experimental workflow. Herein, we put forward a seven-pillar model to define what a core facility needs to meet its overarching goal of facilitating research. The seven equally weighted pillars are Technology, Core Facility Team, Training, Career Tracks, Technical Support, Community and Transparency. These seven pillars stand on a solid foundation of cultural, operational and framework policies including the elements of transparent and stable funding strategies, modern human resources support, progressive facility leadership and management as well as clear institute strategies and policies. This foundation, among other things, ensures a tight alignment of the core facilities to the vision and mission of the institute. To future-proof core facilities, it is crucial to foster all seven of these pillars, particularly focusing on newly identified pillars such as career tracks, thus enabling core facilities to continue supporting research and catalysing scientific advancement.

Lay abstract: In research, there is a growing trend to bring advanced, high-performance equipment together into a centralised location. This is done to streamline how the equipment purchase is financed, how the equipment is maintained, and to enable an easier approach for research scientists to access these tools in a location that is supported by a team of technology experts who can help scientists use the equipment. These centralised equipment centres are called Core Facilities.

The core facility model is relatively new in science and it requires an adapted approach to how core facilities are built and managed. In this paper, we put forward a seven-pillar model of the important supporting elements of core facilities. These supporting elements are: Technology (the instruments themselves), Core Facility Team (the technology experts who operate the instruments), Training (of the staff and research community), Career Tracks (for the core facility staff), Technical Support (the process of providing help to apply the technology to a scientific question), Community (of research scientist, technology experts and developers) and Transparency (of how the core facility works and the costs associated with using the service). These pillars stand on the bigger foundation of clear policies, guidelines, and leadership approaches at the institutional level. With a focus on these elements, the authors feel core facilities will be well positioned to support scientific discovery in the future.