ALBERT

Description: Previously, carnosic acid and carnosol have demonstrated anti-proliferative activity against different types of cancer. To obtain extracts enriched in these two key phenolic compounds, two different processes have been developed in the present work based on the use of two-step sequential supercritical fluid extraction (SFE). By removing the interfering, less active fractions in a first step (150 or 300 bar, 40°C, neat CO2, 60 min), suitable enrichment is achieved in the second step (150 bar, 40°C, CO2 + 7% ethanol, 120 min), and this leads to carnosic acid concentrations in the extract as high as 40% of total dry weight, which are among the highest concentrations that have been described with this type of process. The enriched extracts were tested against the HT-29 human adenocarcinoma cell line, showing enhancement of their antiproliferative activity by approximately 3-fold compared to previously reported SFE rosemary extracts and higher inhibitory effects at lower concentrations (30 µg mL−1 of extract). Thus, the proposed two-step SFE process effectively improves the carnosic acid and carnosol recovery in shorter processing times (180 min vs. 300 min). Moreover, the obtained extracts possess higher anti-proliferative activity and consume less solvent.

Description: Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), regression trees (RTs), random forest (RF) and support vector machines (SVMs) are powerful data driven methods that are relatively less widely used in the mapping of mineral prospectivity, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a series of MLAs, namely, artificial neural networks (ANNs), regression trees (RTs), random forest (RF) and support vector machines (SVMs) in mineral prospectivity modelling are compared based on the following criteria: i) the accuracy in the delineation of prospective areas; ii) the sensitivity to the estimation of hyper-parameters; iii) the sensitivity to the size of training data; and iv) the interpretability of model parameters. The results of applying the above algorithms to epithermal Au prospectivity mapping of the Rodalquilar district, Spain, indicate that the RF outperformed the other MLA algorithms (ANNs, RTs and SVMs). The RF algorithm showed higher stability and robustness with varying training parameters and better success rates and ROC analysis results. On the other hand, all MLA algorithms can be used when ore deposit evidences are scarce. Moreover the model parameters of RF and RT can be interpreted to gain insights into the geological controls of mineralization.

Description: The tropical Atlantic is home to multiple coupled climate variations covering a wide range of timescales and impacting societally relevant phenomena such as continental rainfall, Atlantic hurricane activity, oceanic biological productivity, and atmospheric circulation in the equatorial Pacific. The tropical Atlantic also connects the southern and northern branches of the Atlantic meridional overturning circulation and receives freshwater input from some of the world’s largest rivers. To address these diverse, unique, and interconnected research challenges, a rich network of ocean observations has developed, building on the backbone of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). This network has evolved naturally over time and out of necessity in order to address the most important outstanding scientific questions and to improve predictions of tropical Atlantic severe weather and global climate variability and change. The tropical Atlantic observing system is motivated by goals to understand and better predict phenomena such as tropical Atlantic interannual to decadal variability and climate change; multidecadal variability and its links to the meridional overturning circulation; air-sea fluxes of CO2 and their implications for the fate of anthropogenic CO2; the Amazon River plume and its interactions with biogeochemistry, vertical mixing, and hurricanes; the highly productive eastern boundary and equatorial upwelling systems; and oceanic oxygen minimum zones, their impacts on biogeochemical cycles and marine ecosystems, and their feedbacks to climate. Past success of the tropical Atlantic observing system is the result of an international commitment to sustained observations and scientific cooperation, a willingness to evolve with changing research and monitoring needs, and a desire to share data openly with the scientific community and operational centers. The observing system must continue to evolve in order to meet an expanding set of research priorities and operational challenges. This paper discusses the tropical Atlantic observing system, including emerging scientific questions that demand sustained ocean observations, the potential for further integration of the observing system, and the requirements for sustaining and enhancing the tropical Atlantic observing system.

Description: Trace metal micronutrients are integral to the functioning of marine ecosystems and the export of particulate carbon to the deep ocean. Although much progress has been made in mapping the distributions of metal micronutrients throughout the ocean over the last 30 years, there remain information gaps, most notable during seasonal transitions and in remote regions. The next challenge is to develop in situ sensing technologies necessary to capture the spatial and temporal variabilities of micronutrients characterized with short residence times, highly variable source terms, and sub-nanomolar concentrations in open ocean settings. Such an effort will allow investigation of the biogeochemical processes at the necessary resolution to constrain fluxes, residence times, and the biological and chemical responses to varying metal inputs in a changing ocean. Here, we discuss the current state of the art and analytical challenges associated with metal micronutrient determinations and highlight existing and emerging technologies, namely in situ chemical analyzers, electrochemical sensors, passive preconcentration samplers, and autonomous trace metal clean samplers, which could form the basis of autonomous observing systems for trace metals within the next decade. We suggest that several existing assets can already be deployed in regions of enhanced metal concentrations and argue that, upon further development, a combination of wet chemical analyzers with electrochemical sensors may provide the best compromise between analytical precision, detection limits, metal speciation, and longevity for autonomous open ocean determinations. To meet this goal, resources must be invested to: (1) improve the sensitivity of existing sensors including the development of novel chemical assays; (2) reduce sensor size and power requirements; (3) develop an open-source “Do-It-Yourself” infrastructure to facilitate sensor development, uptake by end-users and foster a mechanism by which scientists can rapidly adapt commercially available technologies to in situ applications; and (4) develop a community-led standardized protocol to demonstrate the endurance and comparability of in situ sensor data with established techniques. Such a vision will be best served through ongoing collaborations between trace metal geochemists, analytical chemists, the engineering community, and commercial partners, which will accelerate the delivery of new technologies for in situ metal sensing in the decade following OceanObs’19.

Description: The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.