Patenting Part-Human Chimeras, Transgenics And Stem Cells For Transplantation In The United States, Canada, And Europe

The perceived need for part-human materials – considered to be biological materials containing human genetic material for the purposes of this paper – is at least twofold. First, given the continued shortage of human organs and other human biological materials suitable for transplantation, thousands of persons will suffer illness and death each year

COVID-19 pandemic in Panama: lessons of the unique risks and research opportunities for Latin America

The Republic of Panama has the second most unequally distributed wealth in Central America, has recently entered the list of countries affected by the COVID-19 pandemic, and has one of the largest testing rate per inhabitant in the region and consequently the highest incidence rate of COVID-19, making it an ideal location to discuss potential scenarios for assessing epidemic preparedness, and to outline research opportunities in the Region of the Americas. We address two timely important questions: What are the unique risks of COVID-19 in Panama that could help other countries in the Region be better prepared? And what kind of scientific knowledge can Panama contribute to the regional and global study of COVID-19? This paper provides suggestions about how the research community could support local health authorities plan for different scenarios and decrease public anxiety. It also presents basic scientific opportunities about emerging pandemic pathogens towards promoting global health from the perspective of a middle income countryThe Republic of Panama has the second most unequally distributed wealth in Central America, has recently entered the list of countries affected by the COVID-19 pandemic, and has one of the largest testing rate per inhabitant in the region and consequently the highest incidence rate of COVID-19, making it an ideal location to discuss potential scenarios for assessing epidemic preparedness, and to outline research opportunities in the Region of the Americas. We address two timely important questions: What are the unique risks of COVID-19 in Panama that could help other countries in the Region be better prepared? And what kind of scientific knowledge can Panama contribute to the regional and global study of COVID-19? This paper provides suggestions about how the research community could support local health authorities plan for different scenarios and decrease public anxiety. It also presents basic scientific opportunities about emerging pandemic pathogens towards promoting global health from the perspective of a middle income countr

BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees

The rising volume of datasets has made training machine learning (ML) models a major computational cost in the enterprise. Given the iterative nature of model and parameter tuning, many analysts use a small sample of their entire data during their initial stage of analysis to make quick decisions (e.g., what features or hyperparameters to use) and use the entire dataset only in later stages (i.e., when they have converged to a specific model). This sampling, however, is performed in an ad-hoc fashion. Most practitioners cannot precisely capture the effect of sampling on the quality of their model, and eventually on their decision-making process during the tuning phase. Moreover, without systematic support for sampling operators, many optimizations and reuse opportunities are lost. In this paper, we introduce BlinkML, a system for fast, quality-guaranteed ML training. BlinkML allows users to make error-computation tradeoffs: instead of training a model on their full data (i.e., full model), BlinkML can quickly train an approximate model with quality guarantees using a sample. The quality guarantees ensure that, with high probability, the approximate model makes the same predictions as the full model. BlinkML currently supports any ML model that relies on maximum likelihood estimation (MLE), which includes Generalized Linear Models (e.g., linear regression, logistic regression, max entropy classifier, Poisson regression) as well as PPCA (Probabilistic Principal Component Analysis). Our experiments show that BlinkML can speed up the training of large-scale ML tasks by 6.26x-629x while guaranteeing the same predictions, with 95% probability, as the full model.Comment: 22 pages, SIGMOD 201

13-Series resolvins mediate the leukocyte-platelet actions of atorvastatin and pravastatin in inflammatory arthritis

This work was supported by funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (Grant 677542), a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant 107613/Z/15/Z), and the Barts Charity (Grant MGU0343). This work was also funded, in part, by Medical Research Council Advance Course Masters (Grant MR/J015741/1). The authors declare no conflicts of interest

Designing informative warning signals: Effects of indicator type, modality, and task demand on recognition speed and accuracy

An experiment investigated the assumption that natural indicators which exploit existing learned associations between a signal and an event make more effective warnings than previously unlearned symbolic indicators. Signal modality (visual, auditory) and task demand (low, high) were also manipulated. Warning effectiveness was indexed by accuracy and reaction time (RT) recorded during training and dual task test phases. Thirty-six participants were trained to recognize 4 natural and 4 symbolic indicators, either visual or auditory, paired with critical incidents from an aviation context. As hypothesized, accuracy was greater and RT was faster in response to natural indicators during the training phase. This pattern of responding was upheld in test phase conditions with respect to accuracy but observed in RT only in test phase conditions involving high demand and the auditory modality. Using the experiment as a specific example, we argue for the importance of considering the cognitive contribution of the user (viz., prior learned associations) in the warning design process. Drawing on semiotics and cognitive psychology, we highlight the indexical nature of so-called auditory icons or natural indicators and argue that the cogniser is an indispensable element in the tripartite nature of signification

Thin Polymer Brush Decouples Biomaterial's Micro-/Nano-Topology and Stem Cell Adhesion

Surface morphology and chemistry of polymers used as biomaterials, such as tissue engineering scaffolds, have a strong influence on the adhesion and behavior of human mesenchymal stem cells. Here we studied semicrystalline poly(ε-caprolactone) (PCL) substrate scaffolds, which exhibited a variation of surface morphologies and roughness originating from different spherulitic superstructures. Different substrates were obtained by varying the parameters of the thermal processing, i.e. crystallization conditions. The cells attached to these polymer substrates adopted different morphologies responding to variations in spherulite density and size. In order to decouple substrate topology effects on the cells, sub-100 nm bio-adhesive polymer brush coatings of oligo(ethylene glycol) methacrylates were grafted from PCL and functionalized with fibronectin. On surfaces featuring different surface textures, dense and sub-100 nm thick brush coatings determined the response of cells, irrespective to the underlying topology. Thus, polymer brushes decouple substrate micro-/nano-topology and the adhesion of stem cells

Improving hospital-based opioid substitution therapy (iHOST): protocol for a mixed-methods evaluation

Background Opioid substitution therapy is associated with improved health and social outcomes for people who use heroin and other illicit opioids. It is typically managed in the community and is not always continued when people are admitted to hospital. This causes opioid withdrawal, discharge against medical advice, and increased costs. We are establishing a project called iHOST (improving hospital opioid substitution therapy) to address these problems. This is an applied health research project in which we will develop and evaluate an intervention that aims to improve opioid substitution therapy in three acute hospitals in England. The intervention was developed in collaboration with stakeholders including people who use opioids, hospital staff, and other professionals who work with this group. It includes five components: (1) a card that patients can use to help hospital clinicians confirm their opioid substitution therapy, (2) a helpline for patients and staff, (3) an online training module for staff, (4) a clinical guideline for managing opioid withdrawal in hospital, and (5) ‘champion’ roles at each hospital. Methods We will do a mixed-methods study including a quasi-experimental quantitative study and a qualitative process evaluation. The primary outcomes for the quantitative study are discharge against medical advice and emergency readmission within 28 days. We will do a difference-in-difference analysis comparing changes in these outcomes for patients at iHOST sites with changes for patients at control hospitals. The process evaluation will use in-depth interviews, focus groups, and site observations with people who use opioids and staff. We will assess acceptability of the intervention, barriers and facilitators to implementation, and contextual factors impacting outcomes. Impact We anticipate that iHOST will improve care for hospital patients who use illicit opioids and/or are receiving community-based opioid substitution therapy. Depending on the results, we will promote the intervention at hospitals across the UK. Dissemination, including through publication, will inform hospital-based services for people who use drugs both in the UK and other countries

Self-assembled monolayers of alendronate on Ti6Al4V alloy surfaces enhance osteogenesis in mesenchymal stem cells

Phosphonates have emerged as an alternative for functionalization of titanium surfaces by the formation of homogeneous self-assembled monolayers (SAMs) via Ti-O-P linkages. This study presents results from an investigation of the modification of Ti6Al4V alloy by chemisorption of osseoinductive alendronate using a simple, effective and clean methodology. The modified surfaces showed a tailored topography and surface chemistry as determined by SEM microscopy and RAMAN spectroscopy. X-ray photoelectron spectroscopy revealed that an effective mode of bonding is created between the metal oxide surface and the phosphate residue of alendronate, leading to formation of homogenous drug distribution along the surface. In-vitro studies showed that alendronate SAMs induce differentiation of hMSC to a bone cell phenotype and promote bone formation on modified surfaces. Here we show that this novel method for the preparation of functional coatings on titanium-based medical devices provides osseoinductive bioactive molecules to promote enhanced integration at the site of implantation