Journal of microscopy最新文献

We present the analytical solution to the diffraction integral that describes the Rayleigh length for a focused Gaussian beam with any value of a spherical truncating aperture. This exact solution is in precise agreement with numerical calculations for the light distribution in the near focal area. The solution arises under assumption of the paraxial approximation, which also provides the basis for the classical Rayleigh length definition. It will be shown that the non-paraxial regime can be included by adding an empirical term (C_np) to the solution of the diffraction integral. This extends the validity of the expression to high numerical apertures (NA) up to n times 0.95, with n being the refractive index of the immersion medium. Thus, the entire practical range of NA, encountered in optical microscopy, is covered with a calculated error of less than 0.4% in the non-paraxial limit. This theoretical result is important in the design of optical instrumentation, where overall light efficiency in excitation and detection and spatial resolution must be optimised together.

Electron ptychography provides a promising avenue towards dose-efficient, high-resolution materials characterisation. Prior work demonstrates the feasibility of this approach, but an overarching view on the reliability of ptychographic images in low-dose scenarios is required. Here, we address this limitation with a systematic study of image clarity across dose, thickness and convergence semi-angle, on a range of materials science specimens. With the now widespread adoption of 4D-STEM and ptychographic imaging, the establishment of the practical parameter space in which one can anticipate a reliably interpretable phase image is urgently needed. In some cases, our parameter space exploration confirms high-resolution imaging at doses of 200 $�e^{-}$Å$�{}^{�-�2�}$.

In this study, we present a protocol to visualise, track and distinguish between two different binder components commonly used for batteries, styrene butadiene rubber (SBR) and sodium carboxymethyl cellulose (CMC), within a composite hard carbon electrode for sodium-ion batteries using a two-step staining method. The application of osmium tetroxide (OsO₄) vapour followed by uranyl acetate (UA) solution enables the staining of different functional groups and the individual tracing of SBR and CMC by energy dispersive X-ray spectroscopy (EDX) measurements using the osmium (Os) and uranium (U) content. This staining procedure and the filling of the pore space with conductive platinum carbon (PtC) composite via local electron-beam-induced deposition (EBID) results in an excellent contrast for all components of the electrode material. The tracking and visualisation of the binder components are demonstrated with secondary electron (SE) imaging and EDX mappings at focused ion beam (FIB) prepared facets as well as with focused ion beam/scanning electron microscopy (FIB/SEM) tomography.

LAY DESCRIPTION: In this study, a sample preparation protocol for hard carbon (HC) composite electrode material is presented which allows to clearly distinguish between the HC particle and the two binder components, styrene butadiene rubber (SBR) and sodium carboxymethyl cellulose (CMC) in focused ion beam/scanning electron microscopy (FIB/SEM) tomography and energy dispersive X-ray spectroscopy (EDX) measurements. For that, the material was stained with osmium tetroxide (OsO₄) and uranyl acetate (UA) and pore space was locally filled with electron-beam-induced deposition (EBID) of platinum carbon (PtC).

The axial positioning accuracy in confocal microscopy measurements is determined by the peak extraction algorithm of the intensity response curve. Existing peak extraction algorithms struggle to balance solution precision and computational efficiency, making it difficult to achieve online measurement. This paper proposes a fast Gaussian fitting method that transforms the nonlinear iterative fitting problem into a linear solution problem through Gaussian function linearisation, significantly improving computational efficiency. Experimental validation shows that the difference in solution accuracy between the fast Gaussian method and the traditional fitting method is no more than 3 nm, with a computational efficiency increasing at least 144 times.

Doughnut-shaped vortex beams are widely used to enhance lateral resolution in super-resolution fluorescence microscopy and subtractive second harmonic generation microscopy. The influence of polarisation states on the axial point spread function is investigated theoretically and experimentally in subtractive second harmonic generation microscopy using a first-order Laguerre–Gaussian vortex beam. The influence of left-handed circular, right-handed circular and linear polarised states are analysed for second harmonic generation imaging and compared with results of fluorescence imaging. The results exhibit great agreement with theoretical predictions, and demonstrate the superiority of left-handed circular polarisation in achieving a complete dark central spot and an extended axial point spread function.

Mesenchymal stem cells (MSC) undergo replicative senescence, a state of irreversible cell cycle arrest that limits their utility in regenerative medicine applications. To identify novel markers of senescence useful to enhance the quality of MSC-based therapies, we compared young and senescent human bone marrow-derived mesenchymal stem cells (hMSCs) using a non-invasive, label-free approach based on quantitative phase imaging (QPI) with the Livecyte microscope. Senescent hMSCs demonstrated substantial morphological alterations, including a threefold increase in cell area, elevated dry mass, reduced thickness, and decreased sphericity compared to their younger counterparts. Additionally, motility metrics such as instantaneous velocity and displacement were significantly reduced in senescent cells, underscoring functional impairments that could hinder their therapeutic potential in regenerative medicine. The application of QPI offers a promising tool for monitoring cellular health, identifying, and potentially eliminating, senescent cells to improve the quality and effectiveness of MSC-based therapies.

Musculoskeletal tissues present complex hierarchical structures and mechanical heterogeneity across multiple length scales, making them difficult to characterise accurately. Digital volume correlation (DVC) is a non-destructive imaging technique that enables quantification of internal 3D strain fields under realistic loading conditions, offering a unique tool to investigate the biomechanics of biological tissues and biomaterials. This review highlights recent advancements in DVC, focusing on its applications across scales ranging from organ- to tissue-level mechanics in both mineralised and soft tissues. Instead of a traditional systematic review, we identify key technical challenges including the treatment of tissue interfaces, border effects, and the quantification of uncertainty in DVC outputs. Strategies for improving measurement accuracy and reliability are discussed. We also report on the increasing use of DVC in in vivo applications, its coupling with computational modelling to inform and validate biomechanical simulations, and its recent integration with data-driven methods such as deep learning to directly predict displacement and strain fields. Additionally, we examine its application in tissue engineering and implant–tissue interface assessment. By addressing such areas, we outline current limitations and emerging opportunities for future research. These include advancing precision, enabling clinical translation, and leveraging machine learning to create more robust, automated, and predictive DVC workflows for musculoskeletal health and tissue engineering.

The Pearson Correlation Coefficient can be calculated using three different criteria for pixel selection. These criteria carry different implications for interpretation of the metric. Different image analysis tools use these different criteria, and it is important that users know which criteria they have used. We maintain that this is important information for the community to consider and that we accurately addressed this topic. Adler and Parmryd have identified a flaw in our analysis in Figure 2 and here we explain how this came about and provide a correction. Alder and Parmryd's letter maligns our intent and competency – we refute all accusations and we object to the use of ad hominem arguments in scientific discourse.