The complement system drives local inflammatory tissue priming by metabolic reprogramming of synovial fibroblasts.

Arthritis typically involves recurrence and progressive worsening at specific predilection sites, but the checkpoints between remission and persistence remain unknown. Here, we defined the molecular and cellular mechanisms of this inflammation-mediated tissue priming. Re-exposure to inflammatory stimuli caused aggravated arthritis in rodent models. Tissue priming developed locally and independently of adaptive immunity. Repeatedly stimulated primed synovial fibroblasts (SFs) exhibited enhanced metabolic activity inducing functional changes with intensified migration, invasiveness and osteoclastogenesis. Meanwhile, human SF from patients with established arthritis displayed a similar primed phenotype. Transcriptomic and epigenomic analyses as well as genetic and pharmacological targeting demonstrated that inflammatory tissue priming relies on intracellular complement C3- and C3a receptor-activation and downstream mammalian target of rapamycin- and hypoxia-inducible factor 1α-mediated metabolic SF invigoration that prevents activation-induced senescence, enhances NLRP3 inflammasome activity, and in consequence sensitizes tissue for inflammation. Our study suggests possibilities for therapeutic intervention abrogating tissue priming without immunosuppression.

Imaging innate immunity.

Innate immunity is the first line of defense against infectious intruders and also plays a major role in the development of sterile inflammation. Direct microscopic imaging of the involved immune cells, especially neutrophil granulocytes, monocytes, and macrophages, has been performed since more than 150 years, and we still obtain novel insights on a frequent basis. Initially, intravital microscopy was limited to small-sized animal species, which were often invertebrates. In this review, we will discuss recent results on the biology of neutrophils and macrophages that have been obtained using confocal and two-photon microscopy of individual cells or subcellular structures as well as light-sheet microscopy of entire organs. This includes the role of these cells in infection defense and sterile inflammation in mammalian disease models relevant for human patients. We discuss their protective but also disease-enhancing activities during tumor growth and ischemia-reperfusion damage of the heart and brain. Finally, we provide two visions, one experimental and one applied, how our knowledge on the function of innate immune cells might be further enhanced and also be used in novel ways for disease diagnostics in the future.

Calibration by differentiation - Self-supervised calibration for X-ray microscopy using a differentiable cone-beam reconstruction operator.

High-resolution X-ray microscopy (XRM) is gaining interest for biological investigations of extremely small-scale structures. XRM imaging of bones in living mice could provide new insights into the emergence and treatment of osteoporosis by observing osteocyte lacunae, which are holes in the bone of few micrometres in size. Imaging living animals at that resolution, however, is extremely challenging and requires very sophisticated data processing converting the raw XRM detector output into reconstructed images. This paper presents an open-source, differentiable reconstruction pipeline for XRM data which analytically computes the final image from the raw measurements. In contrast to most proprietary reconstruction software, it offers the user full control over each processing step and, additionally, makes the entire pipeline deep learning compatible by ensuring differentiability. This allows fitting trainable modules both before and after the actual reconstruction step in a purely data-driven way using the gradient-based optimizers of common deep learning frameworks. The value of such differentiability is demonstrated by calibrating the parameters of a simple cupping correction module operating on the raw projection images using only a self-supervisory quality metric based on the reconstructed volume and no further calibration measurements. The retrospective calibration directly improves image quality as it avoids cupping artefacts and decreases the difference in grey values between outer and inner bone by 68-94%. Furthermore, it makes the reconstruction process entirely independent of the XRM manufacturer and paves the way to explore modern deep learning reconstruction methods for arbitrary XRM and, potentially, other flat-panel computed tomography systems. This exemplifies how differentiable reconstruction can be leveraged in the context of XRM and, hence, is an important step towards the goal of reducing the resolution limit of in vivo bone imaging to the single micrometre domain.

Regulatory eosinophils induce the resolution of experimental arthritis and appear in remission state of human rheumatoid arthritis.

OBJECTIVES: Eosinophils possess pro-inflammatory functions in asthma. However, our recent studies have suggested that innate lymphoid cells type 2 (ILC2s) and eosinophils have proresolving properties in rheumatoid arthritis (RA). Nothing is known yet about the mechanisms determining the double-edged role of eosinophils. Therefore, we investigated whether asthma, a paradigm eosinophilic disease, can elicit resolution of chronic arthritis. METHODS: Ovalbumin-triggered eosinophilic asthma was combined with K/BxN serum-induced arthritis, where lung and synovial eosinophil subsets were compared by single-cell RNA sequencing (scRNA-seq). To investigate the involvement of the ILC2-interleukin-5 (IL-5) axis, hydrodynamic injection (HDI) of IL-25 and IL-33 plasmids, IL-5 reporter mice and anti-IL-5 antibody treatment were used. In patients with RA, the presence of distinct eosinophil subsets was examined in peripheral blood and synovial tissue. Disease activity of patients with RA with concomitant asthma was monitored before and after mepolizumab (anti-IL-5 antibody) therapy. RESULTS: The induction of eosinophilic asthma caused resolution of murine arthritis and joint tissue protection. ScRNA-seq revealed a specific subset of regulatory eosinophils (rEos) in the joints, distinct from inflammatory eosinophils in the lungs. Mechanistically, synovial rEos expanded on systemic upregulation of IL-5 released by lung ILC2s. Eosinophil depletion abolished the beneficial effect of asthma on arthritis. rEos were consistently present in the synovium of patients with RA in remission, but not in active stage. Remarkably, in patients with RA with concomitant asthma, mepolizumab treatment induced relapse of arthritis. CONCLUSION: These findings point to a hitherto undiscovered proresolving signature in an eosinophil subset that stimulates arthritis resolution.

Ultralow-parameter denoising: Trainable bilateral filter layers in computed tomography.

BACKGROUND: Computed tomography (CT) is widely used as an imaging tool to visualize three-dimensional structures with expressive bone-soft tissue contrast. However, CT resolution can be severely degraded through low-dose acquisitions, highlighting the importance of effective denoising algorithms. PURPOSE: Most data-driven denoising techniques are based on deep neural networks, and therefore, contain hundreds of thousands of trainable parameters, making them incomprehensible and prone to prediction failures. Developing understandable and robust denoising algorithms achieving state-of-the-art performance helps to minimize radiation dose while maintaining data integrity. METHODS: This work presents an open-source CT denoising framework based on the idea of bilateral filtering. We propose a bilateral filter that can be incorporated into any deep learning pipeline and optimized in a purely data-driven way by calculating the gradient flow toward its hyperparameters and its input. Denoising in pure image-to-image pipelines and across different domains such as raw detector data and reconstructed volume, using a differentiable backprojection layer, is demonstrated. In contrast to other models, our bilateral filter layer consists of only four trainable parameters and constrains the applied operation to follow the traditional bilateral filter algorithm by design. RESULTS: Although only using three spatial parameters and one intensity range parameter per filter layer, the proposed denoising pipelines can compete with deep state-of-the-art denoising architectures with several hundred thousand parameters. Competitive denoising performance is achieved on x-ray microscope bone data and the 2016 Low Dose CT Grand Challenge data set. We report structural similarity index measures of 0.7094 and 0.9674 and peak signal-to-noise ratio values of 33.17 and 43.07 on the respective data sets. CONCLUSIONS: Due to the extremely low number of trainable parameters with well-defined effect, prediction reliance and data integrity is guaranteed at any time in the proposed pipelines, in contrast to most other deep learning-based denoising architectures.

Prospective analysis of mid-facial fractures in a single-center pediatric-adolescent cohort.

BACKGROUND: The complex architecture of the midface renders diagnosing and treating fractures challenging, especially for young patients who present the additional risk of suffering growth and development deficiencies, which is to be avoided at all costs. OBJECTIVES: This study sought to characterize pediatric mid-facial fractures considering the possible complications. METHODS: Between September 2008 and September 2018, data was collected on inpatients aged <18 years, treated for mid-facial fractures at the Halle University Hospital. Evaluated parameters were age, gender, cause and type of fracture, associated injuries, treatment, and complications. RESULTS: In total, 31 patients were examined; 20 were boys. The most common cause of injury was road traffic accident (41.9%). Orbital floor fracture was the most common type of injury (58.1%). In 54.8% of cases, surgery was performed. CONCLUSION: The incidence of complications associated with mid-facial fractures was low (n = 7), requiring treatment in only three cases (orthodontic, ophthalmological).