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Journal articleKraaij T, Kamerling SWA, van Dam LS, et al., 2018,
Excessive neutrophil extracellular trap formation in ANCA-associated vasculitis is independent of ANCA
, Kidney International, Vol: 94, Pages: 139-149, ISSN: 0085-2538Neutrophil extracellular traps (NETs) are auto-antigenic strands of extracellular DNA covered with myeloperoxidase (MPO) and proteinase3 (PR3) that can be a source for the formation of anti-neutrophil cytoplasmic autoantibodies (ANCAs). The presence of NETs was recently demonstrated in renal tissue of patients with ANCA-associated vasculitis (AAV). NET formation was enhanced in AAV, suggesting that MPO-ANCA could trigger NET formation, supporting a vicious circle placing NETs in the center of AAV pathogenesis. Here we investigated NET formation in 99 patients with AAV by a novel highly sensitive and automated assay. There was a significant excess of ex vivo NET formation in both MPO-ANCA- and PR3-ANCA-positive patients with AAV compared to healthy individuals. Excessive NET formation did not correlate with serum ANCA levels. Likewise, immunoglobulin G depletion had no effect on excessive NET formation in patients with AAV, indicating an ANCA-independent process. Next, we explored the relation of excessive NET formation to clinical disease in ten patients with AAV and showed that excessive NET formation was predominantly found during active disease, more so than during remission. Excessive NET formation was found in patients with AAV hospitalized for disease relapse but not during severe infection. Thus, excessive NET formation in AAV is independent of ANCA, and an excess of ex vivo NET formation was related to active clinical disease in patients with AAV and a marker of autoimmunity rather than infection.
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Journal articleYang G, Yu S, Hao D, et al., 2018,
DAGAN: deep de-aliasing generative adversarial networks for fast compressed sensing MRI reconstruction
, IEEE Transactions on Medical Imaging, Vol: 37, Pages: 1310-1321, ISSN: 0278-0062Compressed Sensing Magnetic Resonance Imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging based fast MRI, which utilises multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training datasets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN) is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilise our U-Net based generator, which provides an endto-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CSMRI reconstruction methods and newly investigated deep learning approaches. Compared to these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.
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Conference paperPrendecki M, Bhatt T, Dudhiya F, et al., 2018,
SPLEEN TYROSINE KINASE EXPRESSION IN HUMAN NEUTROPHILS IN AAV
, 55th Congress of the European-Renal-Association (ERA) and European-Dialysis-and-Transplantation-Association (EDTA), Publisher: OXFORD UNIV PRESS, ISSN: 0931-0509 -
Journal articleAlrashed F, Calay D, Lang M, et al., 2018,
Celecoxib exerts protective effects in the vascular endothelium via COX-2-independent activation of AMPK-CREB-Nrf2 signalling
, Scientific Reports, Vol: 8, ISSN: 2045-2322Although concern remains about the athero-thrombotic risk posed by cyclo-oxygenase (COX)-2-selective inhibitors, recent data implicates rofecoxib, while celecoxib appears equivalent to NSAIDs naproxen and ibuprofen. We investigated the hypothesis that celecoxib activates AMP kinase (AMPK) signalling to enhance vascular endothelial protection. In human arterial and venous endothelial cells (EC), and in contrast to ibuprofen and naproxen, celecoxib induced the protective protein heme oxygenase-1 (HO-1). Celecoxib derivative 2,5-dimethyl-celecoxib (DMC) which lacks COX-2 inhibition also upregulated HO-1, implicating a COX-2-independent mechanism. Celecoxib activated AMPKα(Thr172) and CREB-1(Ser133) phosphorylation leading to Nrf2 nuclear translocation. Importantly, these responses were not reproduced by ibuprofen or naproxen, while AMPKα silencing abrogated celecoxib-mediated CREB and Nrf2 activation. Moreover, celecoxib induced H-ferritin via the same pathway, and increased HO-1 and H-ferritin in the aortic endothelium of mice fed celecoxib (1000 ppm) or control chow. Functionally, celecoxib inhibited TNF-α-induced NF-κB p65(Ser536) phosphorylation by activating AMPK. This attenuated VCAM-1 upregulation via induction of HO-1, a response reproduced by DMC but not ibuprofen or naproxen. Similarly, celecoxib prevented IL-1β-mediated induction of IL-6. Celecoxib enhances vascular protection via AMPK-CREB-Nrf2 signalling, a mechanism which may mitigate cardiovascular risk in patients prescribed celecoxib. Understanding NSAID heterogeneity and COX-2-independent signalling will ultimately lead to safer anti-inflammatory drugs.
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Journal articleYang G, Zhuang X, Khan H, et al., 2018,
Fully automatic segmentation and objective assessment of atrial scars for long-standing persistent atrial fibrillation patients using late gadolinium-enhanced MRI.
, Med Phys, Vol: 45, Pages: 1562-1576PURPOSE: Atrial fibrillation (AF) is the most common heart rhythm disorder and causes considerable morbidity and mortality, resulting in a large public health burden that is increasing as the population ages. It is associated with atrial fibrosis, the amount and distribution of which can be used to stratify patients and to guide subsequent electrophysiology ablation treatment. Atrial fibrosis may be assessed noninvasively using late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI) where scar tissue is visualized as a region of signal enhancement. However, manual segmentation of the heart chambers and of the atrial scar tissue is time consuming and subject to interoperator variability, particularly as image quality in AF is often poor. In this study, we propose a novel fully automatic pipeline to achieve accurate and objective segmentation of the heart (from MRI Roadmap data) and of scar tissue within the heart (from LGE MRI data) acquired in patients with AF. METHODS: Our fully automatic pipeline uniquely combines: (a) a multiatlas-based whole heart segmentation (MA-WHS) to determine the cardiac anatomy from an MRI Roadmap acquisition which is then mapped to LGE MRI, and (b) a super-pixel and supervised learning based approach to delineate the distribution and extent of atrial scarring in LGE MRI. We compared the accuracy of the automatic analysis to manual ground truth segmentations in 37 patients with persistent long-standing AF. RESULTS: Both our MA-WHS and atrial scarring segmentations showed accurate delineations of cardiac anatomy (mean Dice = 89%) and atrial scarring (mean Dice = 79%), respectively, compared to the established ground truth from manual segmentation. In addition, compared to the ground truth, we obtained 88% segmentation accuracy, with 90% sensitivity and 79% specificity. Receiver operating characteristic analysis achieved an average area under the curve of 0.91. CONCLUSION: Compared with previously studied methods with manual interve
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Journal articlePrendecki M, Martin L, Tanna A, et al., 2018,
Increased prevalence of thyroid disease in patients with antineutrophil cytoplasmic antibodies-associated vasculitis
, Journal of Rheumatology, Vol: 45, ISSN: 0315-162XOBJECTIVE: Antineutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV) has been linked with thyroid disease as a result of antithyroid medications. We assessed the prevalence of thyroid disease in our patients with AAV. METHODS: Clinical records of 279 patients with AAV diagnosed between 1991 and 2014 were analyzed. RESULTS: Thyroid disease was identified in 21.5% of patients, but only 2 had previously received propylthiouracil. There was a greater proportion of female patients, patients with antimyeloperoxidase antibodies, and patients with renal disease in the group with thyroid disease. CONCLUSION: Our data show a higher prevalence of thyroid disease in patients with AAV than the general population. This was not attributable to antithyroid drugs.
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Conference papervan Daalen EE, Jennette JC, McAdoo SP, et al., 2018,
Predicting Outcome in Patients with Anti-GBM Glomerulonephritis
, 18th International Vasculitis and ANCA Workshop, Publisher: AMER SOC NEPHROLOGY, Pages: 63-72, ISSN: 1555-9041- Author Web Link
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- Citations: 80
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Conference paperDong S, Gao Z, Sun S, et al., 2018,
Holistic and deep feature pyramids for saliency detection
Saliency detection has been increasingly gaining research interest in recent years since many computer vision applications need to derive object attentions from images in the first steps. Multi-scale awareness of the saliency detector becomes essential to find thin and small attention regions as well as keeping high-level semantics. In this paper, we propose a novel holistic and deep feature pyramid neural network architecture that can leverage multi-scale semantics in feature encoding stage and saliency region prediction (decoding) stage. In the encoding stage, we exploit multi-scale and pyramidal hierarchy of feature maps via the densely connected network with variable-size dilated convolutions as well as a pyramid pooling. In the decoding stage, we fuse multi-level feature maps via up-sampling and convolution. In addition, we utilize the multi-level deep supervision via plugging in loss functions at every feature fusion level. Multi-loss supervision regularizes weights searching space among different tasks minimizing over-fitting and enhances gradient signal during backpropagation, and thus enables us training the network from scratch. This architecture builds an inherent multi-level semantic pyramidal feature maps at different scales and enhances model's capability in the saliency detection task. We validated our approach on six benchmark datasets and compared with eleven state-of-the-art methods. The results demonstrated that the design effectiveness and our approach outperformed the compared methods.
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Conference paperLi M, Dong S, Zhang K, et al., 2018,
Deep Learning intra-image and inter-images features for Co-saliency detection
In this paper, we propose a novel deep end-to-end co-saliency detection approach to extract common salient objects from images group. The existing approaches rely heavily on manually designed metrics to characterize co-saliency. However, these methods are so subjective and not flexible enough that leads to poor generalization ability. Furthermore, most approaches separate the process of single image features and group images features extraction, which ignore the correlation between these two features that can promote the model performance. The proposed approach solves these two problems by multistage representation to extract features based on high-spatial resolution CNN. In addition, we utilize the modified CAE to explore the learnable consistency. Finally, the intra-image contrast and the inter-images consistency are fused to generate the final co-saliency maps automatically among group images by multistage learning. Experiment results demonstrate the effectiveness and superiority of our approach beyond the state-of-the-art methods.
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Journal articleMcAdoo SP, Medjeral-Thomas N, Gopaluni S, et al.,
Long-term Follow-up of a Combined Rituximab and Cyclophosphamide Regimen in Renal ANCA-associated Vasculitis
, Nephrology Dialysis Transplantation, ISSN: 0931-0509
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