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

Noise2Contrast: Multi-Contrast Fusion Enables Self-Supervised Tomographic Image Denoising

Self-supervised image denoising techniques emerged as convenient methods that allow training denoising models without requiring ground-truth noise-free data. Existing methods usually optimize loss metrics that are calculated from multiple noisy realizations of similar images, e.g., from neighboring tomographic slices. However, those approaches fail to utilize the multiple contrasts that are routinely acquired in medical imaging modalities like MRI or dual-energy CT. In this work, we propose the new self-supervised training scheme Noise2Contrast that combines information from multiple measured image contrasts to train a denoising model. We stack denoising with domain-transfer operators to utilize the independent noise realizations of different image contrasts to derive a self-supervised loss. The trained denoising operator achieves convincing quantitative and qualitative results, outperforming state-of-the-art self-supervised methods by 4.7-11.0%/4.8-7.3% (PSNR/SSIM) on brain MRI data and by 43.6-50.5%/57.1-77.1% (PSNR/SSIM) on dual-energy CT X-ray microscopy data with respect to the noisy baseline. Our experiments on different real measured data sets indicate that Noise2Contrast training generalizes to other multi-contrast imaging modalities

IL-33-induced metabolic reprogramming controls the differentiation of alternatively activated macrophages and the resolution of inflammation

Alternatively activated macrophages (AAMs) contribute to the resolution of inflammation and tissue repair. However, molecular pathways that govern their differentiation have remained incompletely understood. Here, we show that uncoupling protein-2-mediated mitochondrial reprogramming and the transcription factor GATA3 specifically controlled the differentiation of pro-resolving AAMs in response to the alarmin IL-33. In macrophages, IL-33 sequentially triggered early expression of pro-inflammatory genes and subsequent differentiation into AAMs. Global analysis of underlying signaling events revealed that IL-33 induced a rapid metabolic rewiring of macrophages that involved uncoupling of the respiratory chain and increased production of the metabolite itaconate, which subsequently triggered a GATA3-mediated AAM polarization. Conditional deletion of GATA3 in mononuclear phagocytes accordingly abrogated IL-33-induced differentiation of AAMs and tissue repair upon muscle injury. Our data thus identify an IL-4-independent and GATA3-dependent pathway in mononuclear phagocytes that results from mitochondrial rewiring and controls macrophage plasticity and the resolution of inflammation

The nuclear receptor Nr4a1 mediates anti-inflammatory effects of apoptotic cells

Uptake of apoptotic cells (ACs) by macrophages ensures the nonimmunogenic clearance of dying cells, as well as the maintenance of self-tolerance to AC-derived autoantigens. Upon ingestion, ACs exert an inhibitory influence on the inflammatory signaling within the phagocyte. However, the molecular signals that mediate these immune-modulatory properties of ACs are incompletely understood. In this article, we show that the phagocytosis of apoptotic thymocytes was enhanced in tissue-resident macrophages where this process resulted in the inhibition of NF-κB signaling and repression of inflammatory cytokines, such as IL-12. In parallel, ACs induced a robust expression of a panel of immediate early genes, which included the Nr4a subfamily of nuclear receptors. Notably, deletion of Nr4a1 interfered with the anti-inflammatory effects of ACs in macrophages and restored both NF-κB signaling and IL-12 expression. Accordingly, Nr4a1 mediated the anti-inflammatory properties of ACs in vivo and was required for maintenance of self-tolerance in the murine model of pristane-induced lupus. Thus, our data point toward a key role for Nr4a1 as regulator of the immune response to ACs and of the maintenance of tolerance to “dying self.

Autophagy regulates TNFα-mediated joint destruction in experimental arthritis

OBJECTIVES: Autophagy is a homeostatic process to recycle dispensable and damaged cell organelles. Dysregulation of autophagic pathways has recently been implicated in the pathogenesis of various diseases. Here, we investigated the role of autophagy during joint destruction in arthritis. METHODS: Autophagy in osteoclasts was analysed in vitro and ex vivo by transmission electron microscopy, Western blotting and immunohistochemistry for Beclin1 and Atg7. Small molecule inhibitors, LysMCre-mediated knockout of Atg7 and lentiviral overexpression of Beclin1 were used to modulate autophagy in vitro and in vivo. Osteoclast differentiation markers were quantified by real-time PCR. The extent of bone and cartilage destruction was analysed in human tumour necrosis factor α transgenic (hTNFα tg) mice after adoptive transfer with myeloid specific Atg7-deficient bone marrow. RESULTS: Autophagy was activated in osteoclasts of human rheumatoid arthritis (RA) showing increased expression of Beclin1 and Atg7. TNFα potently induced the expression of autophagy-related genes and activated autophagy in vitro and in vivo. Activation of autophagy by overexpression of Beclin1-induced osteoclastogenesis and enhanced the resorptive capacity of cultured osteoclasts, whereas pharmacologic or genetic inactivation of autophagy prevented osteoclast differentiation. Arthritic hTNFα tg mice transplanted with Atg7(fl/fl)×LysMCre(+) bone marrow cells (BMC) showed reduced numbers of osteoclasts and were protected from TNFα-induced bone erosion, proteoglycan loss and chondrocyte death. CONCLUSIONS: These findings demonstrate that autophagy is activated in RA in a TNFα-dependent manner and regulates osteoclast differentiation and bone resorption. We thus provide evidence for a central role of autophagy in joint destruction in RA

The 12/15-lipoxygenase pathway counteracts fibroblast activation and experimental fibrosis

BACKGROUND: Idiopathic and inflammation-dependent fibrotic diseases such systemic sclerosis (SSc) impose a major burden on modern societies. Understanding endogenous mechanisms, which counteract fibrosis, may yield new therapeutic approaches. Lipoxins are highly potent lipid mediators, which have recently been found to be decreased in SSc. OBJECTIVES: To determine the potential role of 12/15-lipoxygenase (12/15-LO), the key enzyme for the synthesis of lipoxins, in fibrosis. METHODS: Two mouse models for experimental dermal fibrosis (bleomycin-induced dermal fibrosis and tight-skin 1 mouse model) together with bone marrow transfers were used in wildtype and 12/15-LO(-/-) mice to elucidate the role of this enzyme during dermal fibrosis. Primary dermal fibroblasts of wildtype and 12/15-LO(-/-) mice, and 12/15-LO-derived eicosanoids, were used to identify underlying molecular mechanisms RESULTS: In both models, 12/15-LO(-/-) mice exhibited a significant exacerbation of the fibrotic tissue response. Bone marrow transfer experiments disclosed a predominant role of mesenchymal cell-derived 12/15-LO in these antifibrotic effects. Indeed, 12/15-LO(-/-) fibroblasts showed an enhanced activation of the mitogen-activated protein-kinase pathway and an increased col 1a2 mRNA expression in response to stimulation with transforming growth factor β (TGFβ), whereas 12/15-LO-derived eicosanoids blocked these TGFβ-induced effects. CONCLUSIONS: These data indicate that 12/15-LO and its metabolites have a prominent antifibrotic role during dermal fibrosis. This opens new opportunities for therapeutic approaches in the treatment of fibrotic diseases

12/15-Lipoxygenase Orchestrates the Clearance of Apoptotic Cells and Maintains Immunologic Tolerance

Noninflammatory clearance of apoptotic cells (ACs) is crucial to maintain self-tolerance. Here, we have reported a role for the enzyme 12/15-lipoxygenase (12/15-LO) as a central factor governing the sorting of ACs into differentially activated monocyte subpopulations. During inflammation, uptake of ACs was confined to a population of 12/15-LO-expressing, alternatively activated resident macrophages (resMΦ), which blocked uptake of ACs into freshly recruited inflammatory Ly6Chi monocytes in a 12/15-LO-dependent manner. ResMΦ exposed 12/15-LO-derived oxidation products of phosphatidylethanolamine (oxPE) on their plasma membranes and thereby generated a sink for distinct soluble receptors for ACs such as milk fat globule-EGF factor 8, which were essential for the uptake of ACs into inflammatory monocytes. Loss of 12/15-LO activity, in turn, resulted in an aberrant phagocytosis of ACs by inflammatory monocytes, subsequent antigen presentation of AC-derived antigens, and a lupus-like autoimmune disease. Our data reveal an unexpected key role for enzymatic lipid oxidation during the maintenance of self-tolerance

Activation of liver X receptors inhibits experimental fibrosis by interfering with interleukin-6 release from macrophages

OBJECTIVES: To investigate the role of liver X receptors (LXRs) in experimental skin fibrosis and evaluate their potential as novel antifibrotic targets. METHODS: We studied the role of LXRs in bleomycin-induced skin fibrosis, in the model of sclerodermatous graft-versus-host disease (sclGvHD) and in tight skin-1 (Tsk-1) mice, reflecting different subtypes of fibrotic disease. We examined both LXR isoforms using LXRα-, LXRβ- and LXR-α/β-double-knockout mice. Finally, we investigated the effects of LXRs on fibroblasts and macrophages to establish the antifibrotic mode of action of LXRs. RESULTS: LXR activation by the agonist T0901317 had antifibrotic effects in bleomycin-induced skin fibrosis, in the sclGvHD model and in Tsk-1 mice. The antifibrotic activity of LXRs was particularly prominent in the inflammation-driven bleomycin and sclGvHD models. LXRα-, LXRβ- and LXRα/β-double-knockout mice showed a similar response to bleomycin as wildtype animals. Low levels of the LXR target gene ABCA-1 in the skin of bleomycin-challenged and control mice suggested a low baseline activation of the antifibrotic LXR signalling, which, however, could be specifically activated by T0901317. Fibroblasts were not the direct target cells of LXRs agonists, but LXR activation inhibited fibrosis by interfering with infiltration of macrophages and their release of the pro-fibrotic interleukin-6. CONCLUSIONS: We identified LXRs as novel targets for antifibrotic therapies, a yet unknown aspect of these nuclear receptors. Our data suggest that LXR activation might be particularly effective in patients with inflammatory disease subtypes. Activation of LXRs interfered with the release of interleukin-6 from macrophages and, thus, inhibited fibroblast activation and collagen release