Sex-specific regulation of chemokine Cxcl5/6 controls neutrophil recruitment and tissue injury in acute inflammatory states

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Barts and The London Trustees Studentship (SM), Marie Curie fellowships (MB, JD), Arthritis Research UK career development fellowship (JW), William Harvey Research Foundation grant (JW/RSS), Kidney Research UK fellowship (NSAP), Barts and The London Vacation Scholarship (ISN), Wellcome Trust senior fellowship (DWG), and a Wellcome Trust career development fellowship (RSS). This work forms part of the research themes contributing to the translational research portfolio of Barts and The London Cardiovascular Biomedical Research Unit, which is supported and funded by National Institute for Health Researc

When Health Systems Are Barriers to Health Care: Challenges Faced by Uninsured Mexican Kidney Patients

BACKGROUND: Chronic Kidney Disease disproportionately affects the poor in Low and Middle Income Countries (LMICs). Mexico exemplifies the difficulties faced in supporting Renal Replacement Therapy (RRT) and providing equitable patient care, despite recent attempts at health reform. The objective of this study is to document the challenges faced by uninsured, poor Mexican families when attempting to access RRT. METHODS: The article takes an ethnographic approach, using interviewing and observation to generate detailed accounts of the problems that accompany attempts to secure care. The study, based in the state of Jalisco, comprised interviews with patients, their caregivers, health and social care professionals, among others. Observations were carried out in both clinical and social settings. RESULTS: In the absence of organised health information and stable pathways to renal care, patients and their families work extraordinarily hard and at great expense to secure care in a mixed public-private healthcare system. As part of this work, they must navigate challenging health and social care environments, negotiate treatments and costs, resource and finance healthcare and manage a wide range of formal and informal health information. CONCLUSIONS: Examining commonalities across pathways to adequate healthcare reveals major failings in the Mexican system. These systemic problems serve to reproduce and deepen health inequalities. A system, in which the costs of renal care are disproportionately borne by those who can least afford them, faces major difficulties around the sustainability and resourcing of RRTs. Attempts to increase access to renal therapies, therefore, need to take into account the complex social and economic demands this places on those who need access most. This paper further shows that ethnographic studies of the concrete ways in which healthcare is accessed in practice provide important insights into the plight of CKD patients and so constitute an important source of evidence in that effort

How machine learning can support cyberattack detection in smart grids

This chapter addresses the application of machine learning algorithms to detect attacks against smart grids. Smart grids are the result of a long process of transformation that power systems have been through, relying on Information and Communication Technology (ICT) to improve their monitoring and control. Although an objective of this convergence of power systems and ICT is to increase their reliability, the dependency on information technology has brought new cybersecurity vulnerabilities to this scenario. Therefore, developing new cybersecurity measures for smart grids is a key factor in their success. One of these measures is attack detection, which allows the timely mitigation of attacks with the aim of limiting possible damages to the targets. As machine learning algorithms have been widely applied as powerful tools to support the design of cybersecurity solutions in multiple areas, they also have huge potential for addressing the new challenges that smart grids pose. With this as the foundational perspective, this study starts by presenting an overview of smart grids, followed by possible attacks. After this discussion, we examine the background concepts for attack detection and machine learning. Then, we discuss the existing solutions, showing in detail how they address the particularities of smart grids and their attack types using machine learning algorithms. This is supplemented by a discussion of the open issues in the use of machine learning for smart grid attack detection, followed by some future research directions