Middle East respiratory syndrome

The Middle East respiratory syndrome coronavirus (MERS-CoV) is a lethal zoonotic pathogen that was first identified in humans in Saudi Arabia and Jordan in 2012. Intermittent sporadic cases, community clusters, and nosocomial outbreaks of MERS-CoV continue to occur. Between April 2012 and December 2019, 2499 laboratory-confirmed cases of MERS-CoV infection, including 858 deaths (34·3% mortality) were reported from 27 countries to WHO, the majority of which were reported by Saudi Arabia (2106 cases, 780 deaths). Large outbreaks of human-to-human transmission have occurred, the largest in Riyadh and Jeddah in 2014 and in South Korea in 2015. MERS-CoV remains a high-threat pathogen identified by WHO as a priority pathogen because it causes severe disease that has a high mortality rate, epidemic potential, and no medical countermeasures. This Seminar provides an update on the current knowledge and perspectives on MERS epidemiology, virology, mode of transmission, pathogenesis, diagnosis, clinical features, management, infection control, development of new therapeutics and vaccines, and highlights unanswered questions and priorities for research, improved management, and prevention

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

Testing the paradox of enrichment along a land use gradient in a multitrophic aboveground and belowground community

In the light of ongoing land use changes, it is important to understand how multitrophic communities perform at different land use intensities. The paradox of enrichment predicts that fertilization leads to destabilization and extinction of predator-prey systems. We tested this prediction for a land use intensity gradient from natural to highly fertilized agricultural ecosystems. We included multiple aboveground and belowground trophic levels and land use-dependent searching efficiencies of insects. To overcome logistic constraints of field experiments, we used a successfully validated simulation model to investigate plant responses to removal of herbivores and their enemies. Consistent with our predictions, instability measured by herbivore-induced plant mortality increased with increasing land use intensity. Simultaneously, the balance between herbivores and natural enemies turned increasingly towards herbivore dominance and natural enemy failure. Under natural conditions, there were more frequently significant effects of belowground herbivores and their natural enemies on plant performance, whereas there were more aboveground effects in agroecosystems. This result was partly due to the “boom-bust” behavior of the shoot herbivore population. Plant responses to herbivore or natural enemy removal were much more abrupt than the imposed smooth land use intensity gradient. This may be due to the presence of multiple trophic levels aboveground and belowground. Our model suggests that destabilization and extinction are more likely to occur in agroecosystems than in natural communities, but the shape of the relationship is nonlinear under the influence of multiple trophic interactions.

Gender-sensitive Risks and Options Assessment for Decision making (ROAD) to support WiF2

The Gender-Sensitive Risks and Options Assessment for Decision Making (ROAD) to Support WiF-2 (ROAD migration project), a partnership coordinated by the International Food Policy Research Institute (IFPRI), Australian National University, American University Beirut, Lincoln University, and University of Dhaka, evaluated the ILO-DFID Partnership Programme on Fair Recruitment and Decent Work for Women Migrant Workers in South Asia and the Middle East (Work in Freedom, Phase 2 project [WiF-2]), which operated from 2018 to 2023. The WiF-2 project specifically aimed “to reduce vulnerability to trafficking and forced labour of women and girls across migration pathways leading to the care sector and textiles, clothing, leather and footwear industries (TCLFI) of South Asia and Arab States” (ToC WiF-2)

Optimization and Reproducibility of Aortic Valve 18F-Fluoride Positron Emission Tomography in Patients With Aortic Stenosis

$\textbf{BACKGROUND}$: 18F-Fluoride positron emission tomography (PET) and computed tomography (CT) can measure disease activity and progression in aortic stenosis. Our objectives were to optimize the methodology, analysis, and scan-rescan reproducibility of aortic valve 18F-fluoride PET-CT imaging. $\textbf{METHODS AND RESULTS}$: Fifteen patients with aortic stenosis underwent repeated 18F-fluoride PET-CT. We compared nongated PET and noncontrast CT, with a modified approach that incorporated contrast CT and ECG-gated PET. We explored a range of image analysis techniques, including estimation of blood-pool activity at differing vascular sites and a most diseased segment approach. Contrast-enhanced ECG-gated PET-CT permitted localization of 18F-fluoride uptake to individual valve leaflets. Uptake was most commonly observed at sites of maximal mechanical stress: the leaflet tips and the commissures. Scan-rescan reproducibility was markedly improved using enhanced analysis techniques leading to a reduction in percentage error from ±63% to ±10% (tissue to background ratio MDS mean of 1.55, bias -0.05, limits of agreement -0·20 to +0·11). $\textbf{CONCLUSIONS}$: Optimized 18F-fluoride PET-CT allows reproducible localization of calcification activity to different regions of the aortic valve leaflet and commonly to areas of increased mechanical stress. This technique holds major promise in improving our understanding of the pathophysiology of aortic stenosis and as a biomarker end point in clinical trials of novel therapies. $\textbf{CLINICAL TRIAL REGISTRATION}$ - URL: http://www.clinicaltrials.gov. Unique identifier: NCT02132026.The study was funded by the British Heart Foundation (FS/14/78/31020). Drs Pawade, Cartlidge, Jenkins, Dweck, and Newby are supported by the British Heart Foundation (SS/CH/09/002/26360, FS/13/77/30488, SS/CH/09/002/2636, FS/14/78/31020, and CH/09/002). Dr Newby is the recipient of a Wellcome Trust Senior Investigator Award (WT103782AIA). Dr Dweck is the recipient of the Sir Jules Thorn Award for Biomedical Research 2015. Dr Adamson is supported by New Zealand Overseas Training and Research Fellowship (1607) and Edinburgh and Lothians Health Foundation (50–534). The Wellcome Trust Clinical Research Facility and the Clinical Research Imaging Centre are supported by NHS Research Scotland (NRS) through NHS Lothian. Dr Rudd is partly supported by the NIHR Cambridge Biomedical Research Centre, the British Heart Foundation, and the Wellcome Trust

Biomarker analyses of second-line ramucirumab in patients with advanced gastric cancer from RAINBOW, a global, randomized, double-blind, phase 3 study.

BACKGROUND: The RAINBOW trial showed that second-line ramucirumab with paclitaxel prolongs overall survival (OS) and progression-free survival (PFS) compared with placebo plus paclitaxel for treatment of advanced gastric/gastroesophageal junction cancer. Plasma samples were collected from patients during the trial and tested to identify predictive and prognostic biomarkers. PATIENTS AND METHODS: Circulating factors in plasma samples from mutually exclusive subsets of RAINBOW patients were assayed using: Intertek assays (24 markers, 380 samples, 57% of patients) and Lilly-developed assay (LDA) platform (5 markers, 257 samples, 39% of patients). Time-trend plots were generated for each marker from the Intertek assays. Baseline patient data were dichotomized into low- and high-marker subgroups. Markers were analyzed for predictive effects using interaction models and for prognostic effects using main-effects models. RESULTS: The Intertek and LDA populations were representative of the full trial population. Plasma levels of VEGF-D and PlGF increased from baseline levels during treatment, then declined after treatment discontinued. Angiopoietin-2 exhibited a decrease during treatment, then increased after treatment discontinuation. No clear time trend was evident with the other markers. Analyses of baseline biomarker expression and its relationship with efficacy variables found no biomarker was predictive for efficacy outcomes, including VEGF-D. However, CRP, HGF, ICAM-3, IL-8, SAA, and VCAM-1 were identified as potential prognostic markers with low baseline levels corresponding to longer OS and PFS. CONCLUSIONS: Pharmacodynamic and prognostic relationships were found from the exploratory biomarker analyses in RAINBOW; however, no predictive markers for ramucirumab in gastric cancer were identified in this trial. ispartof: Eur J Cancer vol:127 pages:150-157 ispartof: location:England status: publishe

Simulation of arterial dissection by a penetrating external body using cohesive zone modelling

In this paper, we study the dissection of arterial layers by means of a stiff, planar, penetrating external body (a ‘wedge’), and formulate a novel model of the process using cohesive zone formalism. The work is motivated by a need for better understanding of, and numerical tools for simulating catheter-induced dissection, which is a potentially catastrophic complication whose mechanisms remain little understood. As well as the large deformations and rupture of the tissue, models of such a process must accurately capture the interaction between the tissue and the external body driving the dissection. The latter feature, in particular, distinguishes catheter-induced dissection from, for example, straightforward peeling, which is relatively well-studied. As a step towards such models, we study a scenario involving a geometrically simpler penetrating object (the wedge), which affords more reliable comparison with experimental observations, but which retains the key feature of dissection driven by an external body, as described. Particular emphasis is placed on assessing the reliability of cohesive zone approaches in this context. A series of wedge-driven dissection experiments on porcine aorta were undertaken, from which tissue elastic and fracture parameters were estimated. Finite element models of the experimental configuration, with tissue considered to be a hyperelastic medium, and evolution of tissue rupture modelled with a consistent large-displacement cohesive formulation, were then constructed. Model-predicted and experimentally measured reaction forces on the wedge throughout the dissection process were compared and found to agree well. The performance of the cohesive formulation in modelling externally driven dissection is finally assessed, and the prospects for numerical models of catheter-induced dissection using such approaches is considered