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

Regulating in vivo calcification of alginate microbeads

Alginate calcification has been previously reported clinically and during animal implantation; however no study has investigated the mechanism, extensively characterized the mineral, or evaluated multiple methods to regulate or eliminate mineralization. In the present study, alginate calcification was first studied in vitro: calcium-crosslinked alginate beads sequestered surrounding phosphate while forming traces of hydroxyapatite. Calcification in vivo was then examined in nude mice using alginate microbeads with and without adipose stem cells (ASCs). Variables included the delivery method, site of delivery, sex of the animal, time in vivo, crosslinking solution, and method of storage prior to delivery. Calciumcrosslinked alginate microbeads mineralized when injected subcutaneously or implanted intramuscularly after 1e6 months. More extensive analysis with histology, microCT, FTIR, XRD, and EDS showed calcium phosphate deposits throughout the microbeads with surface mineralization that closely matched hydroxyapatite found in bone. Incorporating 25 mM bisphosphonate reduced alginate calcification whereas using barium chloride eliminated mineralization. Buffering the crosslinking solution with HEPES at pH 7.3 while washing and storing samples in basal media prior to implantation also eliminated calcification in vivo. This study shows that alginate processing prior to implantation can significantly influence bulk hydroxyapatite formation and presents a method to regulate alginate calcificationAlginate calcification has been previously reported clinically and during animal implantation; however no study has investigated the mechanism, extensively characterized the mineral, or evaluated multiple methods to regulate or eliminate mineralization. In the present study, alginate calcification was first studied in vitro: calcium-crosslinked alginate beads sequestered surrounding phosphate while forming traces of hydroxyapatite. Calcification in vivo was then examined in nude mice using alginate microbeads with and without adipose stem cells (ASCs). Variables included the delivery method, site of delivery, sex of the animal, time in vivo, crosslinking solution, and method of storage prior to delivery. Calciumcrosslinked alginate microbeads mineralized when injected subcutaneously or implanted intramuscularly after 1e6 months. More extensive analysis with histology, microCT, FTIR, XRD, and EDS showed calcium phosphate deposits throughout the microbeads with surface mineralization that closely matched hydroxyapatite found in bone. Incorporating 25 mM bisphosphonate reduced alginate calcification whereas using barium chloride eliminated mineralization. Buffering the crosslinking solution with HEPES at pH 7.3 while washing and storing samples in basal media prior to implantation also eliminated calcification in vivo. This study shows that alginate processing prior to implantation can significantly influence bulk hydroxyapatite formation and presents a method to regulate alginate calcificatio

High infestation of invasive Aedes mosquitoes in used tires along the local transport network of Panama

Background: The long‑distance dispersal of the invasive disease vectors Aedes aegypti and Aedes albopictus has intro‑ duced arthropod‑borne viruses into new geographical regions, causing a significant medical and economic burden. The used‑tire industry is an effective means of Aedes dispersal, yet studies to determine Aedes occurrence and the factors influencing their distribution along local transport networks are lacking. To assess infestation along the primary transport network of Panama we documented all existing garages that trade used tires on the highway and surveyed a subset for Ae. aegypti and Ae. albopictus. We also assess the ability of a mass spectrometry approach to classify mos‑ quito eggs by comparing our findings to those based on traditional larval surveillance. Results: Both Aedes species had a high infestation rate in garages trading used tires along the highways, providing a conduit for rapid dispersal across Panama. However, generalized linear models revealed that the presence of Ae. aegypti is associated with an increase in road density by a log‑odds of 0.44 (0.73 ± 0.16; P = 0.002), while the presence of Ae. albopictus is associated with a decrease in road density by a log‑odds of 0.36 (0.09 ± 0.63; P = 0.008). Identifica‑ tion of mosquito eggs by mass spectrometry depicted similar occurrence patterns for both Aedes species as that obtained with traditional rearing methods. Conclusions: Garages trading used tires along highways should be targeted for the surveillance and control of Aedes‑mosquitoes and the diseases they transmit. The identification of mosquito eggs using mass spectrometry allows for the rapid evaluation of Aedes presence, affording time and cost advantages over traditional vector surveil‑ lance; this is of importance for disease risk assessment.Background: The long‑distance dispersal of the invasive disease vectors Aedes aegypti and Aedes albopictus has intro‑ duced arthropod‑borne viruses into new geographical regions, causing a significant medical and economic burden. The used‑tire industry is an effective means of Aedes dispersal, yet studies to determine Aedes occurrence and the factors influencing their distribution along local transport networks are lacking. To assess infestation along the primary transport network of Panama we documented all existing garages that trade used tires on the highway and surveyed a subset for Ae. aegypti and Ae. albopictus. We also assess the ability of a mass spectrometry approach to classify mos‑ quito eggs by comparing our findings to those based on traditional larval surveillance. Results: Both Aedes species had a high infestation rate in garages trading used tires along the highways, providing a conduit for rapid dispersal across Panama. However, generalized linear models revealed that the presence of Ae. aegypti is associated with an increase in road density by a log‑odds of 0.44 (0.73 ± 0.16; P = 0.002), while the presence of Ae. albopictus is associated with a decrease in road density by a log‑odds of 0.36 (0.09 ± 0.63; P = 0.008). Identifica‑ tion of mosquito eggs by mass spectrometry depicted similar occurrence patterns for both Aedes species as that obtained with traditional rearing methods. Conclusions: Garages trading used tires along highways should be targeted for the surveillance and control of Aedes‑mosquitoes and the diseases they transmit. The identification of mosquito eggs using mass spectrometry allows for the rapid evaluation of Aedes presence, affording time and cost advantages over traditional vector surveil‑ lance; this is of importance for disease risk assessment

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

Proteomic fingerprint identification of Neotropical hard tick species (Acari: Ixodidae) using a self-curated mass spectra reference library

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry is an analytical method that detects macromolecules that can be used as biomarkers for taxonomic identification in arthropods. The conventional MALDI approach uses fresh laboratory-reared arthropod specimens to build a reference mass spectra library with high-quality standards required to achieve reliable identification. However, this may not be possible to accomplish in some arthropod groups that are difficult to rear under laboratory conditions, or for which only alcohol preserved samples are available. Here, we generated MALDI mass spectra of highly abundant proteins from the legs of 18 Neotropical species of adult field-collected hard ticks, several of which had not been analyzed by mass spectrometry before. We then used their mass spectra as fingerprints to identify each tick species by applying machine learning and pattern recognition algorithms that combined unsupervised and supervised clustering approaches. Both principal component analysis (PCA) and linear discriminant analysis (LDA) classification algorithms were able to identify spectra from different tick species, with LDA achieving the best performance when applied to field-collected specimens that did have an existing entry in a reference library of arthropod protein spectra. These findings contribute to the growing literature that ascertains mass spectrometry as a rapid and effective method for taxonomic identification of disease vectors, which is the first step to predict and manage arthropod-borne pathogens. Author Summary Hard ticks (Ixodidae) are external parasites that feed on the blood of almost every species of terrestrial vertebrate on earth, including humans. Due to a complete dependency on blood, both sexes and even immature stages, are capable of transmitting disease agents to their hosts, causing distress and sometimes death. Despite the public health significance of ixodid ticks, accurate species identification remains problematic. Vector species identification is core to developing effective vector control schemes. Herein, we provide the first report of MALDI identification of several species of field-collected Neotropical tick specimens preserved in ethanol for up to four years. Our methodology shows that identification does not depend on a commercial reference library of lab-reared samples, but with the help of machine learning it can rely on a self-curated reference library. In addition, our approach offers greater accuracy and lower cost per sample than conventional and modern identification approaches such as morphology and molecular barcoding.Matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry is an analytical method that detects macromolecules that can be used as biomarkers for taxonomic identification in arthropods. The conventional MALDI approach uses fresh laboratory-reared arthropod specimens to build a reference mass spectra library with high-quality standards required to achieve reliable identification. However, this may not be possible to accomplish in some arthropod groups that are difficult to rear under laboratory conditions, or for which only alcohol preserved samples are available. Here, we generated MALDI mass spectra of highly abundant proteins from the legs of 18 Neotropical species of adult field-collected hard ticks, several of which had not been analyzed by mass spectrometry before. We then used their mass spectra as fingerprints to identify each tick species by applying machine learning and pattern recognition algorithms that combined unsupervised and supervised clustering approaches. Both principal component analysis (PCA) and linear discriminant analysis (LDA) classification algorithms were able to identify spectra from different tick species, with LDA achieving the best performance when applied to field-collected specimens that did have an existing entry in a reference library of arthropod protein spectra. These findings contribute to the growing literature that ascertains mass spectrometry as a rapid and effective method for taxonomic identification of disease vectors, which is the first step to predict and manage arthropod-borne pathogens. Author Summary Hard ticks (Ixodidae) are external parasites that feed on the blood of almost every species of terrestrial vertebrate on earth, including humans. Due to a complete dependency on blood, both sexes and even immature stages, are capable of transmitting disease agents to their hosts, causing distress and sometimes death. Despite the public health significance of ixodid ticks, accurate species identification remains problematic. Vector species identification is core to developing effective vector control schemes. Herein, we provide the first report of MALDI identification of several species of field-collected Neotropical tick specimens preserved in ethanol for up to four years. Our methodology shows that identification does not depend on a commercial reference library of lab-reared samples, but with the help of machine learning it can rely on a self-curated reference library. In addition, our approach offers greater accuracy and lower cost per sample than conventional and modern identification approaches such as morphology and molecular barcoding

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