Estimation of the atmospheric flux of nutrients and trace metals to the Eastern Tropical North Atlantic Ocean

Atmospheric deposition contributes potentially significant amounts of the nutrients iron, nitrogen and phosphorus (via mineral dust and anthropogenic aerosols) to the oligotrophic tropical North Atlantic Ocean. Transport pathways, deposition processes and source strengths contributing to this atmospheric flux are all highly variable in space and time. Atmospheric sampling was conducted during 28 research cruises through the Eastern Tropical North Atlantic (ETNA) over a 12 year period and a substantial dataset of measured concentrations of nutrients and trace metals in aerosol and rainfall over the region was acquired. This database was used to quantify (on a spatial- and seasonal-basis) the atmospheric input of ammonium, nitrate, soluble phosphorus and soluble and total iron, aluminium and manganese to the ETNA. The magnitude of atmospheric input varies strongly across the region, with high rainfall rates associated with the Inter-tropical Convergence Zone contributing to high wet deposition fluxes in the south, particularly for soluble species. Dry deposition fluxes of species associated with mineral dust exhibited strong seasonality, with highest fluxes associated with winter-time low-level transport of Saharan dust. Overall (wet plus dry) atmospheric inputs of soluble and total trace metals were used to estimate their soluble fractions. These also varied with season and were generally lower in the dry north than in the wet south. The ratio of ammonium plus nitrate to soluble iron in deposition to the ETNA was lower than the N:Fe requirement for algal growth in all cases, indicating the importance of the atmosphere as a source of excess iron

Artificial intelligence for dementia drug discovery and trials optimization

Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data analytics and machine learning tools for drug discovery and utilizing them to inform successful clinical trial design has the potential to accelerate progress. Opportunities arise at multiple stages in the therapy pipeline and the growing availability of large medical data sets opens possibilities for big data analyses to answer key questions in clinical and therapeutic challenges. However, before this goal is reached, several challenges need to be overcome and only a multi-disciplinary approach can promote data-driven decision-making to its full potential. Herein we review the current state of machine learning applications to clinical trial design and drug discovery, while presenting opportunities and recommendations that can break down the barriers to implementation

Artificial intelligence for dementia drug discovery and trials optimization

Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data analytics and machine learning tools for drug discovery and utilizing them to inform successful clinical trial design has the potential to accelerate progress. Opportunities arise at multiple stages in the therapy pipeline and the growing availability of large medical data sets opens possibilities for big data analyses to answer key questions in clinical and therapeutic challenges. However, before this goal is reached, several challenges need to be overcome and only a multi-disciplinary approach can promote data-driven decision-making to its full potential. Herein we review the current state of machine learning applications to clinical trial design and drug discovery, while presenting opportunities and recommendations that can break down the barriers to implementation

Chapter 6. Primary Production, Cycling of Nutrients, Surface Layer and Plankton.

RADIALES (IEO)Versión del edito

Atmospheric aerosols at the Pierre Auger Observatory and environmental implications

The Pierre Auger Observatory detects the highest energy cosmic rays. Calorimetric measurements of extensive air showers induced by cosmic rays are performed with a fluorescence detector. Thus, one of the main challenges is the atmospheric monitoring, especially for aerosols in suspension in the atmosphere. Several methods are described which have been developed to measure the aerosol optical depth profile and aerosol phase function, using lasers and other light sources as recorded by the fluorescence detector. The origin of atmospheric aerosols traveling through the Auger site is also presented, highlighting the effect of surrounding areas to atmospheric properties. In the aim to extend the Pierre Auger Observatory to an atmospheric research platform, a discussion about a collaborative project is presented.Comment: Regular Article, 16 pages, 12 figure

Nematicidal effects of cysteine proteinases against sedentary plant parasitic nematodes

Cysteine proteinases from the fruit and latex of plants, such as papaya, pineapple and fig, have previously been shown to have substantial anthelmintic efficacy, in vitro and in vivo, against a range of animal parasitic nematodes. In this paper, we describe the in vitro effects of these plant extracts against 2 sedentary plant parasitic nematodes of the genera Meloidogyne and Globodera. All the plant extracts examined caused digestion of the cuticle and decreased the activity of the tested nematodes. The specific inhibitor of cysteine proteinases, E-64, blocked this activity completely, indicating that it was essentially mediated by cysteine proteinases. In vitro, plant cysteine proteinases are active against second-stage juveniles of M. incognita and M. javanica, and some cysteine proteinases also affect the second-stage juveniles of Globodera rostochiensis. It is not known yet whether these plant extracts will interfere with, or prevent invasion of, host plants

The vertical distribution of soluble gases in the troposphere

The thermodynamic properties of several water‐soluble gases are reviewed to determine the likely effect of the atmospheric water cycle on their vertical profiles. We find that gaseous HCl, HNO3, and HBr are sufficiently soluble in water to suggest that their vertical profiles in the troposphere have a similar shape to that of water vapor. Thus we predict that HCl, HNO3, and HBr exhibit a steep negative gradient with altitude roughly equal to the altitude gradient of water vapor. Therefore, ground‐based sources of inorganic chlorine, odd nitrogen, and inorganic bromine compounds are not likely to directly affect the stratosphere in the mean. Calculations also show that while SO2 and NH3 are significantly affected by the atmospheric water cycle, their abundances may not decrease with altitude as rapidly as does water vapor. Copyright 1974 by the American Geophysical Union

Reduced mRNA abundance of the main enzymes involved in methionine metabolism in human liver cirrhosis and hepatocellular carcinoma

BACKGROUND/AIMS: It has been known for at least 50 years that alterations in methionine metabolism occur in human liver cirrhosis. However, the molecular basis of this alteration is not completely understood. In order to gain more insight into the mechanisms behind this condition, mRNA levels of methionine adenosyltransferase (MAT1A), glycine methyltransferase (GNMT), methionine synthase (MS), betaine homocysteine methyltransferase (BHMT) and cystathionine beta-synthase (CBS) were examined in 26 cirrhotic livers, five hepatocellular carcinoma (HCC) tissues and ten control livers. METHODS: The expression of the above-mentioned genes was determined by quantitative RT-PCR analysis. Methylation of MAT1A promoter was assessed by methylation-sensitive restriction enzyme digestion of genomic DNA. RESULTS: When compared to normal livers MAT1A, GNMT, BHMT, CBS and MS mRNA contents were significantly reduced in liver cirrhosis. Interestingly, MAT1A promoter was hypermethylated in the cirrhotic liver. HCC tissues also showed decreased mRNA levels of these enzymes. CONCLUSIONS: These findings establish that the abundance of the mRNA of the main genes involved in methionine metabolism is markedly reduced in human cirrhosis and HCC. Hypermethylation of MAT1A promoter could participate in its reduced expression in cirrhosis. These observations help to explain the hypermethioninemia, hyperhomocysteinemia and reduced hepatic glutathione content observed in cirrhosis

Systems, interactions and macrotheory

A significant proportion of early HCI research was guided by one very clear vision: that the existing theory base in psychology and cognitive science could be developed to yield engineering tools for use in the interdisciplinary context of HCI design. While interface technologies and heuristic methods for behavioral evaluation have rapidly advanced in both capability and breadth of application, progress toward deeper theory has been modest, and some now believe it to be unnecessary. A case is presented for developing new forms of theory, based around generic “systems of interactors.” An overlapping, layered structure of macro- and microtheories could then serve an explanatory role, and could also bind together contributions from the different disciplines. Novel routes to formalizing and applying such theories provide a host of interesting and tractable problems for future basic research in HCI