Journal of microscopy最新文献

Auer, J. M. T., Murphy, L. C., Xiao, D., Li, D. U. & Wheeler, A. P., J. Microsc. 2023; 291, 1, p. 43–56.

In Acknowledgements, we did not acknowledge the support from Medical Research Scotland for Dong Xiao's time in this work.

We want to add ‘We also want to thank Medical Research Scotland for supporting Dong Xiao's research.’

In the author list, ‘David U. Li' should be corrected as' David D.-U. Li’.

We apologize for these two errors.

Super-resolution (SR) microscopy is a cutting-edge method that can provide detailed structural information with high resolution. However, the thickness of the specimen has been a major limitation for SR methods, and large biological structures have posed a challenge. To overcome this, the key step is to optimise sample preparation to ensure optical homogeneity and clarity, which can enhance the capabilities of SR methods for the acquisition of thicker structures.

Oocytes are the largest cells in the mammalian body and are crucial objects in reproductive biology. They are especially useful for studying membrane proteins. However, oocytes are extremely fragile and sensitive to mechanical manipulation and osmotic shocks, making sample preparation a critical and challenging step.

We present an innovative, simple and sensitive approach to oocyte sample preparation for 3D STED acquisition. This involves alcohol dehydration and mounting into a high refractive index medium. This extended preparation procedure allowed us to successfully obtain a unique two-channel 3D STED SR image of an entire mouse oocyte. By optimising sample preparation, it is possible to overcome current limitations of SR methods and obtain high-resolution images of large biological structures, such as oocytes, in order to study fundamental biological processes.

Lay Abstract: Super-resolution (SR) microscopy is a cutting-edge tool that allows scientists to view incredibly fine details in biological samples. However, it struggles with larger, thicker specimens, as they need to be optically clear and uniform for the best imaging results. In this study, we refined the sample preparation process to make it more suitable for SR microscopy. Our method includes carefully dehydrating biological samples with alcohol and then transferring them into a mounting medium that enhances optical clarity. This improved protocol enables high-resolution imaging of thick biological structures, which was previously challenging. By optimizing this preparation method, we hope to expand the use of SR microscopy for studying large biological samples, helping scientists better understand complex biological structures.

Changes in the surrounding environment, if transmitted to the electron microscope, are frequently perceived as noise that diminishes the quality of the images. However, in fact, ‘noises’ contain rich information about the environment. This work reports a very rare event where aberration-corrected HAADF-STEM images were acquired during the impact of seismic waves, resulted from a mild earthquake. By analysing these images, we found that the drift and vibration of the sample are detectable and quantifiable. Despite many potential challenges, this work demonstrates the utilisation of electron microscopes in detecting and monitoring seismic waves with high spatial resolution, which may lead to unique applications in the low-frequency regime.

Single-molecule localization microscopy (SMLM), which has revolutionized nanoscale imaging, faces challenges in densely labelled samples due to fluorophore clustering, leading to compromised localization accuracy. In this paper, we propose a novel convolutional neural network (CNN)-assisted approach to address the issue of locating the clustered fluorophores. Our CNN is trained on a diverse data set of simulated SMLM images where it learns to predict point spread function (PSF) locations by generating Gaussian blobs as output. Through rigorous evaluation, we demonstrate significant improvements in PSF localization accuracy, especially in densely labelled samples where traditional methods struggle. In addition, we employ blob detection as a post-processing technique to refine the predicted PSF locations and enhance localization precision. Our study underscores the efficacy of CNN in addressing clustering challenges in SMLM, thereby advancing spatial resolution and enabling deeper insights into complex biological structures.

Breast cancer (BC) is characterised by a high level of heterogeneity, which is influenced by the interaction of neoplastic cells with the tumour microenvironment. The diagnostic and prognostic role of the tumour stroma in BC remains to be defined. Differential interference contrast (DIC) microscopy is a label-free imaging technique well suited to visualise weak optical phase objects such as cells and tissue. This study aims to compare stromal collagen fibre characteristics between in situ and invasive breast tumours using DIC microscopy and investigate the prognostic value of collagen parameters in BC. A tissue microarray was generated from 200 cases, comprising ductal carcinoma in situ (DCIS; n = 100) and invasive tumours (n = 100) with an extra 50 (25 invasive BC and 25 DCIS) cases for validation was utilised. Two sections per case were used: one stained with haematoxylin and eosin (H&E) stain for histological review and one unstained for examination using DIC microscopy. Collagen fibre parameters including orientation angle, fibre alignment, fibre density, fibre width, fibre length and fibre straightness were measured. Collagen fibre density was higher in the stroma of invasive BC (161.68 ± 11.2 fibre/µm²) compared to DCIS (p < 0.0001). The collagen fibres were thinner (13.78 ± 1.08 µm), straighter (0.96 ± 0.006, on a scale of 0–1), more disorganised (95.07° ± 11.39°) and less aligned (0.20 ± 0.09, on a 0–1 scale) in the invasive BC compared to DCIS (all p < 0.0001). A model considering these features was developed that could distinguish between DCIS and invasive tumours with 94% accuracy. There were strong correlations between fibre characteristics and clinicopathological parameters in both groups. A statistically significant association between fibre characteristics and patients’ outcomes (breast cancer specific survival, and recurrence free survival) was observed in the invasive group but not in DCIS. Although invasive BC and DCIS were both associated with stromal reaction, the structural features of collagen fibres were significantly different in the two disease stages. Analysis of the stroma fibre characteristics in the preoperative core biopsy specimen may help to differentiate pure DCIS from those associated with invasion.

Light-sheet fluorescence microscopy (LSFM), a prominent fluorescence microscopy technique, offers enhanced temporal resolution for imaging biological samples in four dimensions (4D; x, y, z, time). Some of the most recent implementations, including inverted selective plane illumination microscopy (iSPIM) and lattice light-sheet microscopy (LLSM), move the sample substrate at an oblique angle relative to the detection objective's optical axis. Data from such tilted-sample-scan LSFMs require subsequent deskewing and rotation for proper visualisation and analysis. Such data preprocessing operations currently demand substantial memory allocation and pose significant computational challenges for large 4D dataset. The consequence is prolonged data preprocessing time compared to data acquisition time, which limits the ability for live-viewing the data as it is being captured by the microscope. To enable the fast preprocessing of large light-sheet microscopy datasets without significant hardware demand, we have developed WH-Transform, a memory-efficient transformation algorithm for deskewing and rotating the raw dataset, significantly reducing memory usage and the run time by more than 10-fold for large image stacks. Benchmarked against the conventional method and existing software, our approach demonstrates linear runtime compared to the cubic and quadratic runtime of the other approaches. Preprocessing a raw 3D volume of 2 GB (512 × 1536 × 600 pixels) can be accomplished in 3 s using a GPU with 24 GB of memory on a single workstation. Applied to 4D LLSM datasets of human hepatocytes, lung organoid tissue and brain organoid tissue, our method provided rapid and accurate preprocessing within seconds. Importantly, such preprocessing speeds now allow visualisation of the raw microscope data stream in real time, significantly improving the usability of LLSM in biology. In summary, this advancement holds transformative potential for light-sheet microscopy, enabling real-time, on-the-fly data preprocessing, visualisation, and analysis on standard workstations, thereby revolutionising biological imaging applications for LLSM and similar microscopes.

Tissue slices can undergo distortions during processing into resin for light and electron microscopy as a result of differential shrinkage of the various tissue components, and this may necessitate removal of a considerable amount of material from the final resin-embedded tissue block to ensure production of complete sections of the sample. To mitigate this problem, a number of techniques have been devised that ensure the sample is held flat during the final curing/polymerisation of the resin. For embedding in acrylic resins, oxygen must be excluded as it inhibits polymerisation, and methods devised for epoxy resin embedding are generally unsuitable. The method describes the preparation and use of air-tight flat-embedding chambers prepared from Melinex film and provides an inexpensive, technically simpler, and versatile alternative to chambers formed from either Thermanox coverslips or Aclar films that have previously been advocated for such purposes.

Lay description: Tissue slices can undergo distortions during processing into resin for light and electron microscopy as a result of differential shrinkage of the various tissue components. Such distortions may necessitate removal of a considerable amount of material to ensure production of complete sections of the sample. For embedding in acrylic resins, oxygen must be excluded as it inhibits polymerisation, and methods devised for epoxy resin flat-embedding are generally unsuitable. Air-tight flat-embedding chambers prepared from either Thermanox coverslips, or a combination of PTFE-coated glass slides, polycarbonate film gaskets, and Aclar film have been advocated for such purposes. Thermanox coverslips are expensive and limited in size to 22 mm × 60 mm, and the alternative method is technically complicated. Melinex film is commercially available as 210 mm × 297 mm sheets and is approximately 1/20th the price of Thermanox and less than half the price of Aclar film. The method describes the preparation and use of embedding chambers made from Melinex film, glass slides and double-sided adhesive tape as a technically simpler, inexpensive and versatile alternative to both Thermanox coverslips and the Aclar film method.