Recasting West Tankers in the deep water: how Gazprom and recast Brussels I reconcile Brussels I with international arbitration

The central argument which is advanced by this article is that, whilst there is no outright obligation in Brussels I which prevents parallel proceedings between a court action and arbitration between the same parties and concerning a similar cause of action, the revisions in the recast Brussels I, along with the Gazprom interpretation of key non-revised parts of Brussels I, do certainly provide improved support for international commercial arbitration. These do so by giving more scope to national courts to restrict Parallel Proceedings; through anti-suit injunctions issued by an arbitral tribunal; through finding parties taking parallel court action to be in breach of the arbitration agreement; and by giving primacy to the arbitral award where it is irreconcilable with a parallel court judgment. The authors particularly demonstrate that this is made possible because of a changed (diminished) role which is given to the principle of effectiveness of EU law (effet utile) post Gazprom and Brussels I

Frustrated at the interface between court litigation and arbitration? Don’t blame it on Brussels I! Finding reason in the decision of West Tankers, and the recast Brussels I

The West Tankers decision was criticised for having a regressive impact on the system of international commercial arbitration. Many had hoped that the European Court would deliver a decision which would be informed by pragmatism, and one which would prevent numerous court and tribunal related parallel proceedings occurring across a number of jurisdictions within the EU. Instead, the European Court delivered a principled judgment declaring an anti-suit injunction prohibiting a party from continuing proceedings before a court of a Member State to be contrary to EU law. This chapter is significant because it introduces a complete account of the normative framework that regulates the interface between court litigation and arbitration. It identifies the approach under the system of the Brussels I Regulation, including the recent amendments brought by the revised version of Brussels I. The main finding of this chapter is that the reasoning of the European Court in West Tankers was consistent with EU jurisprudence and the core values of Brussels I. In particular it shows that the critiques of West Tankers often ignore important values that are fundamental to the system of Brussels I and EU constitutional values. It is submitted that West Tankers has essentially magnified the diversity and cultural distinction among Member States in their approach to parallel proceedings between a court and arbitration

Antiviral activity of bone morphogenetic proteins and activins

Understanding the control of viral infections is of broad importance. Chronic hepatitis C virus (HCV) infection causes decreased expression of the iron hormone hepcidin, which is regulated by hepatic bone morphogenetic protein (BMP)/SMAD signalling. We found that HCV infection and the BMP/SMAD pathway are mutually antagonistic. HCV blunted induction of hepcidin expression by BMP6, probably via tumour necrosis factor (TNF)-mediated downregulation of the BMP co-receptor haemojuvelin. In HCV-infected patients, disruption of the BMP6/hepcidin axis and genetic variation associated with the BMP/SMAD pathway predicted the outcome of infection, suggesting that BMP/SMAD activity influences antiviral immunity. Correspondingly, BMP6 regulated a gene repertoire reminiscent of type I interferon (IFN) signalling, including upregulating interferon regulatory factors (IRFs) and downregulating an inhibitor of IFN signalling, USP18. Moreover, in BMP-stimulated cells, SMAD1 occupied loci across the genome, similar to those bound by IRF1 in IFN-stimulated cells. Functionally, BMP6 enhanced the transcriptional and antiviral response to IFN, but BMP6 and related activin proteins also potently blocked HCV replication independently of IFN. Furthermore, BMP6 and activin A suppressed growth of HBV in cell culture, and activin A inhibited Zika virus replication alone and in combination with IFN. The data establish an unappreciated important role for BMPs and activins in cellular antiviral immunity, which acts independently of, and modulates, IFN

Label-free macrophage phenotype classification using machine learning methods

Abstract Macrophages are heterogeneous innate immune cells that are functionally shaped by their surrounding microenvironment. Diverse macrophage populations have multifaceted differences related to their morphology, metabolism, expressed markers, and functions, where the identification of the different phenotypes is of an utmost importance in modelling immune response. While expressed markers are the most used signature to classify phenotypes, multiple reports indicate that macrophage morphology and autofluorescence are also valuable clues that can be used in the identification process. In this work, we investigated macrophage autofluorescence as a distinct feature for classifying six different macrophage phenotypes, namely: M0, M1, M2a, M2b, M2c, and M2d. The identification was based on extracted signals from multi-channel/multi-wavelength flow cytometer. To achieve the identification, we constructed a dataset containing 152,438 cell events each having a response vector of 45 optical signals fingerprint. Based on this dataset, we applied different supervised machine learning methods to detect phenotype specific fingerprint from the response vector, where the fully connected neural network architecture provided the highest classification accuracy of 75.8% for the six phenotypes compared simultaneously. Furthermore, by restricting the number of phenotypes in the experiment, the proposed framework produces higher classification accuracies, averaging 92.0%, 91.9%, 84.2%, and 80.4% for a pool of two, three, four, five phenotypes, respectively. These results indicate the potential of the intrinsic autofluorescence for classifying macrophage phenotypes, with the proposed method being quick, simple, and cost-effective way to accelerate the discovery of macrophage phenotypical diversity

Recent developments in modeling, imaging, and monitoring of cardiovascular diseases using machine learning

Cardiovascular diseases are the leading cause of mortality, morbidity, and hospitalization around the world. Recent technological advances have facilitated analyzing, visualizing, and monitoring cardiovascular diseases using emerging computational fluid dynamics, blood flow imaging, and wearable sensing technologies. Yet, computational cost, limited spatiotemporal resolution, and obstacles for thorough data analysis have hindered the utility of such techniques to curb cardiovascular diseases. We herein discuss how leveraging machine learning techniques, and in particular deep learning methods, could overcome these limitations and offer promise for translation. We discuss the remarkable capacity of recently developed machine learning techniques to accelerate flow modeling, enhance the resolution while reduce the noise and scanning time of current blood flow imaging techniques, and accurate detection of cardiovascular diseases using a plethora of data collected by wearable sensors