Unravelling migratory connectivity in marine turtles using multiple methods

Comprehensive knowledge of the fundamental spatial ecology of marine species is critical to allow the identification of key habitats and the likely sources of anthropogenic threats, thus informing effective conservation strategies. 2. Research on migratory marine vertebrates has lagged behind many similar terrestrial animal groups, but studies using electronic tagging systems and molecular techniques offer great insights. 3. Marine turtles have complex life history patterns, spanning wide spatio-temporal scales. As a result of this multidimensional complexity, and despite extensive effort, there are no populations for which a truly holistic understanding of the spatial aspects of the life history has been attained. There is a particular lack of information regarding the distribution and habitats utilized during the first few years of life. 4. We used satellite tracking technology to track individual turtles following nesting at the green turtle Chelonia mydas nesting colony at Poilão Island, Guinea Bissau; the largest breeding aggregation in the eastern Atlantic. 5. We further contextualize these data with pan-Atlantic molecular data and oceanographic current modelling to gain insights into likely dispersal patterns of hatchlings and small pelagic juveniles. 6. All adult turtles remained in the waters of West Africa, with strong connectivity demonstrated with Banc D’Arguin, Mauritania. 7. Despite shortcomings in current molecular markers, we demonstrate evidence for profound sub-structuring of marine turtle stocks across the Atlantic; with a high likelihood based on oceanographic modelling that most turtles from Guinea-Bissau are found in the eastern Atlantic. 8. Synthesis and applications. There is an increased need for a better understanding of spatial distribution of marine vertebrates demonstrating life histories with spatio-temporal complexity. We propose the synergistic use of the technologies and modelling used here as a working framework for the future rapid elucidation of the range and likely key habitats used by the different life stages from such species

Immunomodulatory properties of Musa paradisiaca L. inflorescence in Combined Allergic Rhinitis and Asthma Syndrome (CARAS) model towards NFκB pathway inhibition

Musa paradisiaca L. (Musaceae), a tropical plant named banana is used as food and as medicine in Brazil. Banana inflorescence, popularly known as mangará, presents several biological activities including anti-inflammatory effects. Here, we demonstrated the immunomodulatory activity of banana inflorescence extract (HEM) on a mice model of combined allergic rhinitis and asthma syndrome (CARAS) and in human macrophages. The HEM inhibited the eosinophil migration, production of cytokines as IL-4, IL-5, IL-13, and IL-17A dependent on IFN-¿ production in the airway. The mechanism of the extract was, in part, by the NF-¿B signaling pathway inhibition. Besides, the HEM decreased expression of the CD86 and HLA-DR receptors on human M1 macrophages independently of M2 modulation. Therefore, we infer that the inflorescence, a disposable material from the banana crops, has anti-allergic property in the CARAS model and modulates the human macrophages, characterizing it as biologically important material for the production of phytomedicine.This work was supported by Brazilian agencies National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Institute for Research and Innovation in Health (I3S) and National Institute of Biomedical Engineering (INEB). The authors would like to thank Serviço de Imunohemoterapia of Centro Hospitalar Universitário de São João (CHUSJ), Porto, Portugal, for kindly donating Buffy Coats. The authors are also grateful for the valuable assistance provided by agencies, institutes and collaborators. This work was supported by Brazilian agencies National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Institute for Research and Innovation in Health (I3S) and National Institute of Biomedical Engineering (INEB). The authors would like to thank Serviço de Imunohemoterapia of Centro Hospitalar Universitário de São João (CHUSJ), Porto, Portugal, for kindly donating Buffy Coats. The authors are also grateful for the valuable assistance provided by agencies, institutes and collaborators

Privacy-Preserving Ridge Regression with only Linearly-Homomorphic Encryption

Linear regression with 2-norm regularization (i.e., ridge regression) is an important statistical technique that models the relationship between some explanatory values and an outcome value using a linear function. In many applications (e.g., predictive modelling in personalised health care), these values represent sensitive data owned by several different parties who are unwilling to share them. In this setting, training a linear regression model becomes challenging and needs specific cryptographic solutions. This problem was elegantly addressed by Nikolaenko et al. in S&P (Oakland) 2013. They suggested a two-server system that uses linearly-homomorphic encryption (LHE) and Yao’s two-party protocol (garbled circuits). In this work, we propose a novel system that can train a ridge linear regression model using only LHE (i.e., without using Yao’s protocol). This greatly improves the overall performance (both in computation and communication) as Yao’s protocol was the main bottleneck in the previous solution. The efficiency of the proposed system is validated both on synthetically-generated and real-world datasets