Arsenic Speciation and Localization in Horticultural Produce Grown in a Historically Impacted Mining Region

A field and market basket study (similar to 1300 samples) of locally grown fruits and vegetables from historically mined regions of southwest (SW) England (Cornwall and Devon), and as reference, a market basket study of similarly locally grown produce from the northeast (NE) of Scotland (Aberdeenshire) was conducted to determine the concentration of total and inorganic arsenic present in produce from these two geogenically different areas of the U.K. On average 98.5% of the total arsenic found was present in the inorganic form. For both the market basket and the field survey, the highest total arsenic was present in open leaf structure produce (i.e., kale, chard, lettuce, greens, and spinach) being most likely to soil/dust contamination of the open leaf structure. The concentration of total arsenic in potatoes, swedes, and carrots was lower in peeled produce compared to unpeeled produce. For baked potatoes, the concentration of total arsenic in the skin was higher compared to the total arsenic concentration of the potato flesh, this difference in localization being confirmed by laser ablation inductively coupled plasma mass spectroscopy (LA-ICP-MS). For all above ground produce (e.g., apples), peeling did not have a significant effect on the concentration of total arsenic present.

In silico mining identifies IGFBP3 as a novel target of methylation in prostate cancer

Promoter hypermethylation is central in deregulating gene expression in cancer. Identification of novel methylation targets in specific cancers provides a basis for their use as biomarkers of disease occurrence and progression. We developed an in silico strategy to globally identify potential targets of promoter hypermethylation in prostate cancer by screening for 5' CpG islands in 631 genes that were reported as downregulated in prostate cancer. A virtual archive of 338 potential targets of methylation was produced. One candidate, IGFBP3, was selected for investigation, along with glutathione-S-transferase pi (GSTP1), a well-known methylation target in prostate cancer. Methylation of IGFBP3 was detected by quantitative methylation-specific PCR in 49/79 primary prostate adenocarcinoma and 7/14 adjacent preinvasive high-grade prostatic intraepithelial neoplasia, but in only 5/37 benign prostatic hyperplasia (P < 0.0001) and in 0/39 histologically normal adjacent prostate tissue, which implies that methylation of IGFBP3 may be involved in the early stages of prostate cancer development. Hypermethylation of IGFBP3 was only detected in samples that also demonstrated methylation of GSTP1 and was also correlated with Gleason score > or =7 (P=0.01), indicating that it has potential as a prognostic marker. In addition, pharmacological demethylation induced strong expression of IGFBP3 in LNCaP prostate cancer cells. Our concept of a methylation candidate gene bank was successful in identifying a novel target of frequent hypermethylation in early-stage prostate cancer. Evaluation of further relevant genes could contribute towards a methylation signature of this disease.

Differential efficiency of the endocytic machinery in tonic and phasic synapses

Efficient synaptic vesicle membrane recycling is one of the key factors required to sustain neurotransmission. We investigated potential differences in the compensatory endocytic machineries in two glutamatergic synapses with phasic and tonic patterns of activity in the lamprey spinal cord. Post-embedding immunocytochemistry demonstrated that proteins involved in synaptic vesicle recycling, including dynamin, intersectin, and synapsin, occur at higher levels (labeling per vesicle) in tonic dorsal column synapses than in phasic reticulospinal synapses. Synaptic vesicle protein 2 occurred at similar levels in the two types of synapse. After challenging the synapses with high potassium stimulation for 30 min the vesicle pool in the tonic synapse was maintained at a normal level, while that in the phasic synapse was partly depleted along with expansion of the plasma membrane and accumulation of clathrin-coated intermediates at the periactive zone. Thus, our results indicate that an increased efficiency of the endocytic machinery in a synapse may be one of the factors underlying the ability to sustain neurotransmission at high rates.

Mining Money: the generative capacities of scientific and legal knowledge practices in the making of resource economies

In 1997 a scandal associated with Bre-X, a junior mining firm, and its prospecting activities in Indonesia, exposed to public scrutiny the ways in which mineral exploration firms acquire, assess and report on scientific claims about the natural environment. At stake here was not just how investors understood the provisional nature of scientific knowledge, but also evidence of fraud. Contemporaneous mining scandals not only included the salting of cores, but also unreliable proprietary sample preparation and assay methods, mis-representations of visual field estimates as drilling results and ‘overly optimistic’ geological reports. This paper reports on initiatives taken in the wake of these scandals and prompted by the Mining Standards Task Force (TSE/OSC 1999). For regulators, mandated to increase investor confidence in Canada’s leading role within the global mining industry, efforts focused first and foremost upon identifying and removing sources of error and wilfulness within the production and circulation of scientific knowledge claims. A common goal cross-cutting these initiatives was ‘a faithful representation of nature’ (Daston and Galison 2010), however, as the paper argues, this was manifest in an assemblage of practices governed by distinct and rival regulative visions of science and the making of markets in claims about ‘nature’. These ‘practices of fidelity’, it is argued, can be consequential in shaping the spatial and temporal dynamics of the marketization of nature.

Fast Rule Mining over Multi-dimensional Windows

Association rule mining is an indispensable tool for discovering
insights from large databases and data warehouses.
The data in a warehouse being multi-dimensional, it is often
useful to mine rules over subsets of data defined by selections
over the dimensions. Such interactive rule mining
over multi-dimensional query windows is difficult since rule
mining is computationally expensive. Current methods using
pre-computation of frequent itemsets require counting
of some itemsets by revisiting the transaction database at
query time, which is very expensive. We develop a method
(RMW) that identifies the minimal set of itemsets to compute
and store for each cell, so that rule mining over any
query window may be performed without going back to the
transaction database. We give formal proofs that the set of
itemsets chosen by RMW is sufficient to answer any query
and also prove that it is the optimal set to be computed
for 1 dimensional queries. We demonstrate through an extensive
empirical evaluation that RMW achieves extremely
fast query response time compared to existing methods, with
only moderate overhead in pre-computation and storage

Fast Mining of Interesting Phrases from Subsets of Text Corpora

We address the problem of mining interesting phrases from subsets of a text corpus where the subset is specified using a set of features such as keywords that form a query. Previous algorithms for the problem have proposed solutions that involve sifting through a phrase dictionary based index or a document-based index where the solution is linear in either the phrase dictionary size or the size of the document subset. We propose the usage of an independence assumption between query keywords given the top correlated phrases, wherein the pre-processing could be reduced to discovering phrases from among the top phrases per each feature in the query. We then outline an indexing mechanism where per-keyword phrase lists are stored either in disk or memory, so that popular aggregation algorithms such as No Random Access and Sort-merge Join may be adapted to do the scoring at real-time to identify the top interesting phrases. Though such an approach is expected to be approximate, we empirically illustrate that very high accuracies (of over 90%) are achieved against the results of exact algorithms. Due to the simplified list-aggregation, we are also able to provide response times that are orders of magnitude better than state-of-the-art algorithms. Interestingly, our disk-based approach outperforms the in-memory baselines by up to hundred times and sometimes more, confirming the superiority of the proposed method.

A primer for the Environmental Impact Assessment of mining at seafloor massive sulfide deposits

Seafloor massive sulfides (SMS) contain commercially viable quantities of high grade ores, making them attractive prospect sites for marine mining. SMS deposits may also contain hydrothermal vent ecosystems populated by high conservation value vent-endemic species. Responsible environmental management of these resources is best achieved by the adoption of a precautionary approach. Part of this precautionary approach involves the Environmental Impact Assessment (EIA) of exploration and exploitative activities at SMS deposits. The VentBase 2012 workshop provided a forum for stakeholders and scientists to discuss issues surrounding SMS exploration and exploitation. This forum recognised the requirement for a primer which would relate concepts underpinning EIA at SMS deposits. The purpose of this primer is to inform policy makers about EIA at SMS deposits in order to aid management decisions. The primer offers a basic introduction to SMS deposits and their associated ecology, and the basic requirements for EIA at SMS deposits; including initial data and information scoping, environmental survey, and ecological risk assessment. © 2013 Elsevier Ltd.

VentBase:Developing a consensus among stakeholders in the deep-sea regarding environmental impact assessment for deep-sea mining-A workshop report

Mining seafloor massive sulfides for metals is an emergent industry faced with environmental management challenges. These revolve largely around limits to our current understanding of biological variability in marine systems, a challenge common to all marine environmental management. VentBase was established as a forum where academic, commercial, governmental, and non-governmental stakeholders can develop a consensus regarding the management of exploitative activities in the deep-sea. Participants advocate a precautionary approach with the incorporation of lessons learned from coastal studies. This workshop report from VentBase encourages the standardization of sampling methodologies for deep-sea environmental impact assessment. VentBase stresses the need for the collation of spatial data and importance of datasets amenable to robust statistical analyses. VentBase supports the identification of set-asides to prevent the local extirpation of vent-endemic communities and for the post-extraction recolonization of mine sites. © 2013.

A primer for use of genetic tools in selecting and testing the suitability of set-aside sites protected from deep-sea seafloor massive sulfide mining activities

Seafloor massive sulfide (SMS) mining will likely occur at hydrothermal systems in the near future. Alongside their mineral wealth, SMS deposits also have considerable biological value. Active SMS deposits host endemic hydrothermal vent communities, whilst inactive deposits support communities of deep water corals and other suspension feeders. Mining activities are expected to remove all large organisms and suitable habitat in the immediate area, making vent endemic organisms particularly at risk from habitat loss and localised extinction. As part of environmental management strategies designed to mitigate the effects of mining, areas of seabed need to be protected to preserve biodiversity that is lost at the mine site and to preserve communities that support connectivity among populations of vent animals in the surrounding region. These "set-aside" areas need to be biologically similar to the mine site and be suitably connected, mostly by transport of larvae, to neighbouring sites to ensure exchange of genetic material among remaining populations. Establishing suitable set-asides can be a formidable task for environmental managers, however the application of genetic approaches can aid set-aside identification, suitability assessment and monitoring. There are many genetic tools available, including analysis of mitochondrial DNA (mtDNA) sequences (e.g. COI or other suitable mtDNA genes) and appropriate nuclear DNA markers (e.g. microsatellites, single nucleotide polymorphisms), environmental DNA (eDNA) techniques and microbial metagenomics. When used in concert with traditional biological survey techniques, these tools can help to identify species, assess the genetic connectivity among populations and assess the diversity of communities. How these techniques can be applied to set-aside decision making is discussed and recommendations are made for the genetic characteristics of set-aside sites. A checklist for environmental regulators forms a guide to aid decision making on the suitability of set-aside design and assessment using genetic tools. This non-technical primer document represents the views of participants in the VentBase 2014 workshop.

Integration of geochemical and biological modifications in mining areas: waters, sediments and diatoms

The development of mining activities over thousands of years in the region of Aljustrel is nowadays visible as a vast area of ore tailings, slag and host rocks of sulphides mineralization. The generation of acidic waters by the alteration of pyritic minerals - Acid Mine Drainage (AMD) - causes a significant impact on the river system both in the south of the village (Rib ª. Água Forte) and in the north of it (Rib ª. Água Azeda and Barranco do Farrobo), which is reflected in extremely low pH values (< 3) and high concentrations of As, Cd, Cu, Fe, Mn, Pb, Zn and sulphates. This study aimed to assess the environmental impacts extent, integrating geochemical (surface waters and stream sediments) and biological (diatoms) parameters. Three groups of sites were defined, based on sediments and water analysis, which integration with diatom data showed the same association of groups: Group 1- impacted, with acidic pH (1.9-5.1), high metal contents (0.4-1975 mg L-1) and Fe-Mg-sulphate waters, being metals more bioavailable in waters in cationic form (Me2+); mineralogically the sediments were characterized by phyllosilicates and sulphates/oxy-hydroxysulphate phases, easily solubilized, retaining a high amount of metals when precipitated; dominant taxon was Pinnularia aljustrelica (a new species); Group 2- slightly impacted, weak acid to neutral pH (5.0-6.8), metal contents not so high (0.2-25 mg L-1) and Fe-Mg-sulphate to Mg-chloride waters; dominant taxa were Brachysira neglectissima and Achnanthidium minutissimum; Group 3- unimpacted, alkaline pH (7.0-8.4), low metal contents (0-7 mg L-1) with Mg-chloride waters. In this group, metals were associated to the primary phases (e.g. sulphides), not so easily available; the existence of high chloride contents explained the presence of typical taxa of brackish/marine (e.g. Entomoneis paludosa) waters. Taxonomical aspects of the diatoms were studied (discovery of a new species: Pinnularia aljustrelica Luis, Almeida et Ector sp. nov.), as well as morphometric (size decrease of diatoms valves, as well as the appearance of deformed valves of Eunotia exigua in Group 1 and A. minutissimum in Group 2) and physiological (effective to assess the effects of metals/acidity in the photosynthetic efficiency through PAM Fluorometry) aspects. A study was carried out in an artificial river system (microcosm) that aimed to mimic Aljustrel’s extreme conditions in controlled laboratory conditions. The chronic effects of Fe, SO42- and acidity in field biofilms, inoculated in the artificial rivers, were evaluated as well as their contribution to the communities’ tolerance to metal toxicity, through acute tests with two metals (Cu and Zn). In general, the effects caused by low pH values and high concentrations of Fe and SO42- were reflected at the community level by the decrease in diversity, the predominance of acidophilic species, the decrease in photosynthetic efficiency and the increase of enzymatic (e.g. catalase, superoxide dismutase) and non-enzymatic activities (e.g. total glutathione and total phytochelatins). However, it was possible to verify that acidity performed a protective effect in the communities, upon Cu and Zn addition. A comparative study between Aljustrel mining area and New Brunswick mining area was carried out, both with similar mining and geological conditions, reflected in similar diatom communities in both mines, but in very different geographic and climatic areas.

Mining biomedical information from scientific literature

The rapid evolution and proliferation of a world-wide computerized network, the Internet, resulted in an overwhelming and constantly growing amount of publicly available data and information, a fact that was also verified in biomedicine. However, the lack of structure of textual data inhibits its direct processing by computational solutions. Information extraction is the task of text mining that intends to automatically collect information from unstructured text data sources. The goal of the work described in this thesis was to build innovative solutions for biomedical information extraction from scientific literature, through the development of simple software artifacts for developers and biocurators, delivering more accurate, usable and faster results. We started by tackling named entity recognition - a crucial initial task - with the development of Gimli, a machine-learning-based solution that follows an incremental approach to optimize extracted linguistic characteristics for each concept type. Afterwards, Totum was built to harmonize concept names provided by heterogeneous systems, delivering a robust solution with improved performance results. Such approach takes advantage of heterogenous corpora to deliver cross-corpus harmonization that is not constrained to specific characteristics. Since previous solutions do not provide links to knowledge bases, Neji was built to streamline the development of complex and custom solutions for biomedical concept name recognition and normalization. This was achieved through a modular and flexible framework focused on speed and performance, integrating a large amount of processing modules optimized for the biomedical domain. To offer on-demand heterogenous biomedical concept identification, we developed BeCAS, a web application, service and widget. We also tackled relation mining by developing TrigNER, a machine-learning-based solution for biomedical event trigger recognition, which applies an automatic algorithm to obtain the best linguistic features and model parameters for each event type. Finally, in order to assist biocurators, Egas was developed to support rapid, interactive and real-time collaborative curation of biomedical documents, through manual and automatic in-line annotation of concepts and relations. Overall, the research work presented in this thesis contributed to a more accurate update of current biomedical knowledge bases, towards improved hypothesis generation and knowledge discovery.