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In the last decade, grating-based phase-contrast computed tomography (gbPC-CT) has received growing interest. It provides additional information about the refractive index decrement in the sample. This signal shows an increased soft-tissue contrast. However, the resolution dependence of the signal poses a challenge: its contrast enhancement is overcompensated by the low resolution in low-dose applications such as clinical computed tomography. As a result, the implementation of gbPC-CT is currently tied to a higher dose. To reduce the dose, we introduce the self-supervised deep learning network Noise2Inverse into the field of gbPC-CT. We evaluate the behavior of the Noise2Inverse parameters on the phase-contrast results. Afterward, we compare its results with other denoising methods, namely the Statistical Iterative Reconstruction, Block Matching 3D, and Patchwise Phase Retrieval. In the example of Noise2Inverse, we show that deep learning networks can deliver superior denoising results with respect to the investigated image quality metrics. Their application allows to increase the resolution while maintaining the dose. At higher resolutions, gbPC-CT can naturally deliver higher contrast than conventional absorption-based CT. Therefore, the application of machine learning-based denoisers shifts the dose-normalized image quality in favor of gbPC-CT, bringing it one step closer to medical application., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Nanotomography with hard X-rays is a widely used technique for high-resolution imaging, providing insights into the structure and composition of various materials. In recent years, tomographic approaches based on simultaneous illuminations of the same sample region from different angles by multiple beams have been developed at micrometre image resolution. Transferring these techniques to the nanoscale is challenging due to the loss in photon flux by focusing the X-ray beam. We present an approach for multi-beam nanotomography using a dual-beam Fresnel zone plate (dFZP) in a near-field holography setup. The dFZP generates two nano-focused beams that overlap in the sample plane, enabling the simultaneous acquisition of two projections from slightly different angles. This first proof-of-principle implementation of the dual-beam setup allows for the efficient removal of ring artifacts and noise using machine-learning approaches. The results open new possibilities for full-field multi-beam nanotomography and pave the way for future advancements in fast holotomography and artifact-reduction techniques., (open access.)

Vivid structural colours in butterflies are caused by photonic nanostructures scattering light. Structural colours evolved for numerous biological signalling functions and have important technological applications. Optically, such structures are well understood, however insight into their development in vivo remains scarce. We show that actin is intimately involved in structural colour formation in butterfly wing scales. Using comparisons between iridescent (structurally coloured) and non-iridescent scales in adult and developing H. sara, we show that iridescent scales have more densely packed actin bundles leading to an increased density of reflective ridges. Super-resolution microscopy across three distantly related butterfly species reveals that actin is repeatedly re-arranged during scale development and crucially when the optical nanostructures are forming. Furthermore, actin perturbation experiments at these later developmental stages resulted in near total loss of structural colour in H. sara. Overall, this shows that actin plays a vital and direct templating role during structural colour formation in butterfly scales, providing ridge patterning mechanisms that are likely universal across lepidoptera., (© 2024. The Author(s).)

The phase problem is a well known ill-posed reconstruction problem of coherent lens-less microscopic imaging, where only the squared magnitude of a complex wavefront is measured by a detector while the phase information of the wave field is lost. To retrieve the lost information, common algorithms rely either on multiple data acquisitions under varying measurement conditions or on the application of strong constraints such as a spatial support. In X-ray near-field holography, however, these methods are rendered impractical in the setting of time sensitive in situ and operando measurements. In this paper, we will forego the spatial support constraint and propose a projected gradient descent (PGD) based reconstruction scheme in combination with proper preprocessing and regularization that significantly reduces artifacts for refractive reconstructions from only a single acquired hologram without a spatial support constraint. We demonstrate the feasibility and robustness of our approach on different data sets obtained at the nano imaging endstation of P05 at PETRA III (DESY, Hamburg) operated by Helmholtz-Zentrum Hereon.

The utilization of biodegradable magnesium (Mg)-based implants for restoration of bone function following trauma represents a transformative approach in orthopaedic application. One such alloy, magnesium-10 weight percent gadolinium (Mg-10Gd), has been specifically developed to address the rapid degradation of Mg while enhancing its mechanical properties to promote bone healing. Previous studies have demonstrated that Mg-10Gd exhibits favorable osseointegration; however, it exhibits distinct ultrastructural adaptation in comparison to conventional implants like titanium (Ti). A crucial aspect that remains unexplored is the impact of Mg-10Gd degradation on the bone microarchitecture. To address this, we employed hierarchical three-dimensional imaging using synchrotron radiation in conjunction with image-based finite element modelling. By using the methods outlined, the vascular porosity, lacunar porosity and the lacunar-canaliculi network (LCN) morphology of bone around Mg-10Gd in comparison to Ti in a rat model from 4 weeks to 20 weeks post-implantation was investigated. Our investigation revealed that within our observation period, the degradation of Mg-10Gd implants was associated with significantly lower (p < 0.05) lacunar density in the surrounding bone, compared to Ti. Remarkably, the LCN morphology and the fluid flow analysis did not significantly differ for both implant types. In summary, a more pronounced lower lacunae distribution rather than their morphological changes was detected in the surrounding bone upon the degradation of Mg-10Gd implants. This implies potential disparities in bone remodelling rates when compared to Ti implants. Our findings shed light on the intricate relationship between Mg-10Gd degradation and bone microarchitecture, contributing to a deeper understanding of the implications for successful osseointegration., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors.)

Functional materials feature hierarchical microstructures that define their unique set of properties. The prediction and tailoring of these require a multiscale knowledge of the mechanistic interaction of microstructure and property. An important material in this respect is biodegradable magnesium alloys used for implant applications. To correlate the relationship between the microstructure and the nonlinear degradation process, high-resolution in situ three-dimensional (3D) imaging experiments must be performed. For this purpose, a novel experimental flow cell is presented which allows for the in situ 3D-nano imaging of the biodegradation process of materials with nominal resolutions below 100 nm using nanofocused hard X-ray radiation from a synchrotron source. The flow cell setup can operate under adjustable physiological and hydrodynamic conditions. As a model material, the biodegradation of thin Mg-4Ag wires in simulated body fluid under physiological conditions and a flow rate of 1 mL/min is studied. The use of two full-field nanotomographic imaging techniques, namely transmission X-ray microscopy and near-field holotomography, is compared, revealing holotomography as the superior imaging technique for this purpose. Additionally, the importance of maintaining physiological conditions is highlighted by the preliminary results. Supporting measurements using electron microscopy to investigate the chemical composition of the samples after degradation are performed.

Full-field X-ray nanoimaging is a widely used tool in a broad range of scientific areas. In particular, for low-absorbing biological or medical samples, phase contrast methods have to be considered. Three well established phase contrast methods at the nanoscale are transmission X-ray microscopy with Zernike phase contrast, near-field holography and near-field ptychography. The high spatial resolution, however, often comes with the drawback of a lower signal-to-noise ratio and significantly longer scan times, compared with microimaging. In order to tackle these challenges a single-photon-counting detector has been implemented at the nanoimaging endstation of the beamline P05 at PETRA III (DESY, Hamburg) operated by Helmholtz-Zentrum Hereon. Thanks to the long sample-to-detector distance available, spatial resolutions of below 100 nm were reached in all three presented nanoimaging techniques. This work shows that a single-photon-counting detector in combination with a long sample-to-detector distance allows one to increase the time resolution for in situ nanoimaging, while keeping a high signal-to-noise level., (open access.)

An increasing prevalence of bone-related injuries and aging geriatric populations continue to drive the orthopaedic implant market. A hierarchical analysis of bone remodelling after material implantation is necessary to better understand the relationship between implant and bone. Osteocytes, which are housed and communicate through the lacuno-canalicular network (LCN), are integral to bone health and remodelling processes. Therefore, it is essential to examine the framework of the LCN in response to implant materials or surface treatments. Biodegradable materials offer an alternative solution to permanent implants, which may require revision or removal surgeries. Magnesium alloys have resurfaced as promising materials due to their bone-like properties and safe degradation in vivo . To further tailor their degradation capabilities, surface treatments such as plasma electrolytic oxidation (PEO) have demonstrated to slow degradation. For the first time, the influence of a biodegradable material on the LCN is investigated by means of non-destructive 3D imaging. In this pilot study, we hypothesize noticeable variations in the LCN caused by altered chemical stimuli introduced by the PEO-coating. Utilising synchrotron-based transmission X-ray microscopy, we have characterised morphological LCN differences around uncoated and PEO-coated WE43 screws implanted into sheep bone. Bone specimens were explanted after 4, 8, and 12 weeks and regions near the implant surface were prepared for imaging. Findings from this investigation indicate that the slower degradation of PEO-coated WE43 induces healthier lacunar shapes within the LCN. However, the stimuli perceived by the uncoated material with higher degradation rates induces a greater connected LCN better prepared for bone disturbance., Competing Interests: Syntellix AG is a medical technology manufacturer of metallic and bio-absorbable clinical implants. Authors Espiritu and Seitz are employed as Research Associate and Chief Technical Officer, respectively., (© 2023 The Authors.)

The advent of hard X-ray free-electron lasers enables nanoscopic X-ray imaging with sub-picosecond temporal resolution. X-ray grating interferometry offers a phase-sensitive full-field imaging technique where the phase retrieval can be carried out from a single exposure alone. Thus, the method is attractive for imaging applications at X-ray free-electron lasers where intrinsic pulse-to-pulse fluctuations pose a major challenge. In this work, the single-exposure phase imaging capabilities of grating interferometry are characterized by an implementation at the I13-1 beamline of Diamond Light Source (Oxfordshire, UK). For comparison purposes, propagation-based phase contrast imaging was also performed at the same instrument. The characterization is carried out in terms of the quantitativeness and the contrast-to-noise ratio of the phase reconstructions as well as via the achievable spatial resolution. By using a statistical image reconstruction scheme, previous limitations of grating interferometry regarding the spatial resolution can be mitigated as well as the experimental applicability of the technique., (open access.)

High-resolution X-ray nanotomography is a quantitative tool for investigating specimens from a wide range of research areas. However, the quality of the reconstructed tomogram is often obscured by noise and therefore not suitable for automatic segmentation. Filtering methods are often required for a detailed quantitative analysis. However, most filters induce blurring in the reconstructed tomograms. Here, machine learning (ML) techniques offer a powerful alternative to conventional filtering methods. In this article, we verify that a self-supervised denoising ML technique can be used in a very efficient way for eliminating noise from nanotomography data. The technique presented is applied to high-resolution nanotomography data and compared to conventional filters, such as a median filter and a nonlocal means filter, optimized for tomographic data sets. The ML approach proves to be a very powerful tool that outperforms conventional filters by eliminating noise without blurring relevant structural features, thus enabling efficient quantitative analysis in different scientific fields., (open access.)