A 1H-NMR-based metabolomic analysis of propolis from Santa Catarina state

16th IUFoST World Congress of Food Science and Technology: Addressing Global Food Security and Wellness through Food Science and TechnologyPropolis is a resinous biomass produced by honeybees from exudates of local flora. It has been used since ancient times in folk medicine and in recent years has been added to foods and beverages to improve health and prevent diseases. The chemical composition of propolis is highly variable and depends on the climate, season, specie of bee, and mainly the local flora visited by bees to collect resin. In order to identify groups of chemical similarity among samples (n=20 autumn, n=16 winter, n=19 spring, n=17 summer) of propolis produced in Santa Catarina (SC) state (southern Brazil - 2010), lyophilized ethanolic extracts (200 mg/ml, EtOH 70%, v/v) were solubilized in MeOD3 (700l) and analyzed by NMR spectroscopy. One-dimensional 1HNMR spectra were acquired at a magnetic field strength of 500,13/125,03 MHz using a Varian Inova 500 MHz equipment and standard conditions of data acquisition. The 1H-NMR peak list data set was processed under MetaboAnalyst 2.0. suite, computing the resonances at 0.80- 12ppm spectral window. Principal Components Analysis (PCA) score scatter plots (PC1 88.2% x PC2 2.2%) clearly demonstrated samples discriminated mainly according to the season of production. These results suggest that not only geographical origin is important for the classification of propolis, but the seasonal effects as well. Since seasons directly influence the flora available from where bees collect resin, the propolis chemical profile can be significantly modified over the seasons even from a same geographical origin.info:eu-repo/semantics/publishedVersio

A machine learning and chemometrics assisted interpretation of spectroscopic data: a NMR-based metabolomics platform for the assessment of Brazilian propolis

In this work, a metabolomics dataset from 1H nuclear magnetic resonance spectroscopy of Brazilian propolis was analyzed using machine learning algorithms, including feature selection and classification methods. Partial least square-discriminant analysis (PLS-DA), random forest (RF), and wrapper methods combining decision trees and rules with evolutionary algorithms (EA) showed to be complementary approaches, allowing to obtain relevant information as to the importance of a given set of features, mostly related to the structural fingerprint of aliphatic and aromatic compounds typically found in propolis, e.g., fatty acids and phenolic compounds. The feature selection and decision tree-based algorithms used appear to be suitable tools for building classification models for the Brazilian propolis metabolomics regarding its geographic origin, with consistency, high accuracy, and avoiding redundant information as to the metabolic signature of relevant compounds.The work is partially funded by ERDF -European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and PEstOE/ EEI/UI0752/2011. RC's work is funded by a PhD grant from the Portuguese FCT ( ref. SFRH/BD/66201/2009)

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.Financial support for this investigation by National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Biosciences National Laboratory (LNBioCNPEM/MCTI), Foundation for Support of Scientific and Technological Research in the State of Santa Catarina (FAPESC), and Portuguese Foundation for Science and Technology (FCT) is acknowledged. The research fellowship granted by CNPq to the first author is also acknowledged. The work was partially funded by a CNPq and FCT agreement through the PropMine grant

Assessment of the environmental status in Hellenic coastal waters (Eastern Mediterranean): from the Water Framework Directive to the Marine Strategy Water Framework Directive.

A  methodology is presented to assess the environmental status sensu the Marine Strategy Water Framework Directive (MSFD) based on data obtained from the monitoring of water quality in the Hellenic coastal waters within the Water Framework Directive (WFD).   An adapted decision tree used for integrating the results of the WFD in the Basque country was applied. Modifications lie to the evaluation of the physicochemical status based on a eutrophication index developed for Eastern Mediterranean waters. Results on hydromorphological, physicochemical and biological elements are presented. The chemical status was evaluated based on measurements of heavy metals in water. The evaluation of the biological quality was based on the use of metrics developed for phytoplankton biomass, benthic macroinvertebrates and macroalgae updated to accommodate MSFD needs. Results on the integrative status of the water bodies were validated by correlating classification results with a pressure index and environmental indicators in water column and sediment. Following this decision tree the majority of stations expected to be at risk of achieving the good status were found in moderate status. Benthos was found to be the element with the closest agreement with the integrated final status having an increased weighting in the decision tree. The quality of benthos and in some  limited cases  the eutrophication index determined largely the final status. The highest disagreement with the integrative classification was produced by macroalgae. All indicators used correlated with water and sediment parameters but benthos correlated better with sediment factors while phytoplankton and eutrophication index with water column parameters

Evidence-based teaching in contact lenses education: Teaching and learning strategies

Contact lens (CL) practice is an ever-changing field with clinical knowledge, techniques and equipment continuously evolving. These new developments are backed with clinical trials and research to ensure that practitioners feel confident that there is an evidence base to support these advances. Evidence-based practice is now a crucial part of CL practice, and its importance also filters down to CL education. For example, lectures are one of the most popular tools for an educator but, is standing at the front of a lecture theatre full of students a more effective way of teaching than providing the same material for students to read by themselves? What evidence exists specific to CL education

Field observations of canopy flows over complex terrain

The investigation of airflow over and within forests in complex terrain has been, until recently, limited to a handful of modelling and laboratory studies. Here, we present an observational dataset of airflow measurements inside and above a forest situated on a ridge on the Isle of Arran, Scotland. The spatial coverage of the observations all the way across the ridge makes this a unique dataset. Two case studies of across-ridge flow under near-neutral conditions are presented and compared with recent idealized two-dimensional modelling studies. Changes in the canopy profiles of both mean wind and turbulent quantities across the ridge are broadly consistent with these idealized studies. Flow separation over the lee slope is seen as a ubiquitous feature of the flow. The three-dimensional nature of the terrain and the heterogeneous forest canopy does however lead to significant variations in the flow separation across the ridge, particularly over the less steep western slope. Furthermore, strong directional shear with height in regions of flow separation has a significant impact on the Reynolds stress terms and other turbulent statistics. Also observed is a decrease in the variability of the wind speed over the summit and lee slope, which has not been seen in previous studies. This dataset should provide a valuable resource for validating models of canopy flow over real, complex terrain

Meeting of the Ecosystem Approach Correspondence Group on on Pollution Monitoring (CorMon Pollution)

In accordance with the UNEP/MAP Programme of Work adopted by COP 21 for the biennium 2020-2021, the United Nations Environment Programme/Mediterranean Action Plan-Barcelona Convention Secretariat (UNEP/MAP) and its Programme for the Assessment and Control of Marine Pollution in the Mediterranean (MED POL) organized the Meeting of the Ecosystem Approach Correspondence Group on Pollution Monitoring (CorMon on Pollution Monitoring). The Meeting was held via videoconference on 26-27 April 2021. 2. The main objectives of the Meeting were to: a) Review the Monitoring Guidelines/Protocols for IMAP Common Indicator 18, as well as the Monitoring Guidelines/Protocols for Analytical Quality Assurance and Reporting of Monitoring Data for IMAP Common Indicators 13, 14, 17, 18 and 20; b) Take stock of the state of play of inter-laboratory testing and good laboratory practice related to IMAP Ecological Objectives 5 and 9; c) Analyze the proposal for the integration and aggregation rules for IMAP Ecological Objectives 5, 9 and 10 and assessment criteria for contaminants and nutrients; d) Recommend the ways and means to strengthen implementation of IMAP Pollution Cluster towards preparation of the 2023 MED Quality Status Report

Viruses: incredible nanomachines. New advances with filamentous phages

During recent decades, bacteriophages have been at the cutting edge of new developments in molecular biology, biophysics, and, more recently, bionanotechnology. In particular filamentous viruses, for example bacteriophage M13, have a virion architecture that enables precision building of ordered and defect-free two and three-dimensional structures on a nanometre scale. This could not have been possible without detailed knowledge of coat protein structure and dynamics during the virus reproduction cycle. The results of the spectroscopic studies conducted in our group compellingly demonstrate a critical role of membrane embedment of the protein both during infectious entry of the virus into the host cell and during assembly of the new virion in the host membrane. The protein is effectively embedded in the membrane by a strong C-terminal interfacial anchor, which together with a simple tilt mechanism and a subtle structural adjustment of the extreme end of its N terminus provides favourable thermodynamical association of the protein in the lipid bilayer. This basic physicochemical rule cannot be violated and any new bionanotechnology that will emerge from bacteriophage M13 should take this into account