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PubMed1998

Effects of Metal Mining and Milling on Boundary Waters of Yellowstone National Park, USA.

/ Aquatic resources in Soda Butte Creek within Yellowstone National Park, USA, continue to be threatened by heavy metals from historical mining and milling activities that occurred upstream of the park's boundary. This includes the residue of gold, silver, and copper ore mining and processing in the early 1900s near Cooke City, Montana, just downstream of the creek's headwaters. Toxicity tests, using surrogate test species, and analyses of metals in water, sediments, and macroinvertebrate tissue were conducted from 1993 to 1995. Chronic toxicity to test species was greater in the spring than the fall and metal concentrations were elevated in the spring with copper exceeding water quality criteria in 1995. Tests with amphipods using pore water and whole sediment from the creek and copper concentrations in the tissue of macroinvertebrates and fish also suggest that copper is the metal of concern in the watershed. In order to understand current conditions in Soda Butte Creek, heavy metals, especially copper, must be considered important factors in the aquatic and riparian ecosystems within and along the creek extending into Yellowstone National Park.KEY WORDS: Mining; Metals; Toxicity; Biomonitoring; Copper; Yellowstone National Park

Journal Article↗
PubMed1996

Injuries of the lower limbs caused by antipersonnel mines: the experience of the International Committee of the Red Cross.

Antipersonnel mines are used frequently in armed conflicts. Victims do not sustain their injuries only during the conflict, but sometimes years after it has ended. The object of this paper is to describe the treatment of patients with mine injuries in terms of mortality and the drain on hospital resources. A group of patients with fresh mine injuries who were treated at hospitals of the International Committee of the Red Cross was analysed retrospectively. About 25 per cent of patients need an amputation. The most common surgical amputation is below the knee. The study shows that the level of the amputation is closely connected with the number of operations, the number of units of blood transfused and the number of days of hospitalization.

Amputation, Surgical↗
PubMed1992

Microbiological and chemical characteristics of an acidic stream draining a disused copper mine.

Water samples draining a disused copper mine (Parys Mountain) in Anglesey, North Wales, were analysed for distribution of acidophilic bacteria (iron oxidising and heterotrophic) and for changes in physicochemical composition along the length of the drainage stream. Ten samples were taken at regular distance intervals along a 1 km stretch from the source of the acid mine drainage. The stream remained highly acidic (pH < 2.8) although a slight decrease (0.6 pH unit) in acidity with distance from source was observed. Concentrations of most metals measured decreased with distance along the length of the stream, although some showed a gradual increase and others peaked at c. 200 m from source. Most dissolved iron was in the ferrous form in the upper reaches of the stream, but ferric iron became increasingly dominant downstream as a result of microbial oxidation. Although concentrations of nutrients such as nitrogen and phosphorus were low in the acid mine drainage, they were not limiting rates of bacterial iron oxidation, which appeared to be limited more by temperature. The iron oxidising bacteria Thiobacillus ferrooxidans and Leptospirillum ferrooxidans were both isolated from all sampling sites, although their relative abundances varied; L. ferrooxidans accounted for 57% of all iron oxidising isolates. Numbers of iron oxidising bacteria decreased with distance from drainage source, in contrast to those of acidophilic heterotrophic bacteria which increased. The diversity of heterotrophic isolates also increased with distance. The relationship between the chemistry and microbiology of the stream is discussed.

Journal Article↗
PubMed1996

Mercury levels in surface waters of the Carson River-Lahontan Reservoir system, Nevada: Influence of historic mining activities.

Total mercury (HgT), methylmercury (MeHg), and other operationally defined Hg species were determined on water samples collected from a river-reservoir system impacted by historic mine wastes. Simultaneously, a comprehensive study was undertaken to determine the influence of some major physico-chemical parameters on the fate of Hg within the system. Total Hg levels showed an increase from background concentrations of 4 ng liter(-1) upstream of mining activity, to peak values of 1500-2100 ng liter(-1) downstream of Hg contaminated mine tailings piles. MeHg concentrations varied from 0.1 to 7 ng liter(-1) in surface waters. In both cases, peak values were associated with the highest concentrations of total suspended solids (TSS). Particulate Hg (HgP) was typically >50% of HgT and increased downstream. The dissolved fraction of MeHg (MeHgD) always constituted a large portion of total methylmercury (MeHgT). The [MeHgT]/[HgT] ratio decreased downstream suggesting either a high percentage of inorganic Hg input from point sources, or low specific rates of MeHg production within the aquatic system. The latter could be due to the combined effects on microbial populations of both high levels of Hg concentrations found in water and sediments, and other factors related to the aqueous geochemistry of the system. Concentrations of HgT in the water column appeared to be enhanced by inputs of contaminated particles from the watershed during spring snow melt. In the reservoir, significant losses of Hg from the water column were observed. In addition to losses of Hg bound to particles by sedimentation, the removal through volatilization of dissolved gaseous Hg could be an important pathway.

Journal Article↗
PubMed2005

Predicting survival time for kidney dialysis patients: a data mining approach.

The cost for providing care for patients on hemodialysis due to end stage kidney disease is high. Finding ways to improve patient outcomes and reduce the cost of dialysis is important. Dialysis care is intricate and multiple factors may influence patient survival. Over 50 parameters may be monitored on a regular basis in providing kidney dialysis treatments. Understanding the collective role of these parameters in determining outcomes for an individual patient and administering individualized treatments allowing specific interventions is a challenge. Individual patient survival may depend on a complex interrelationship between multiple demographic and clinical parameters, medications, medical interventions, and the dialysis treatment prescription. In this research, data preprocessing, data transformations, and a data mining approach are used to elicit knowledge about the interaction between many of these measured parameters and patient survival. Two different data mining algorithms were employed for extracting knowledge in the form of decision rules. These rules were used by a decision-making algorithm, which predicts survival of new unseen patients. Important parameters identified by data mining are interpreted for their medical significance. The concepts introduced in this research have been applied and tested using data collected at four dialysis sites. The computational results are reported in the paper.

Algorithms↗
PubMed2006

MRI in long-term evaluation of reconstructed hind-feet of land-mine trauma patients.

INTRODUCTION: The purpose of this study was to assess the flap reconstructed hind feet of patients with MRI who were traumatized by land-mine. MATERIALS AND METHODS: T1 and T2 weighted images were obtained in 7 patients, 12 months later the reconstruction of their hind feet by myocutaneous flaps after land-mine trauma. RESULTS: In all patients T2 signal intensities of the myocutaneous flaps were slightly high compared to normal undisturbed muscle. Slight vascular engorgement was noted in the vicinity of the flaps in all cases. There were ankle joint ankylose (n=1), tarsal coalition (n=3), sklerosis within the calcaneus (n=1), bone cortex irregularities (n=3), absence of calcaneus (n=4), deformity in talus and bone marrow edema (n=1), navicular edema (n=2), remodeling in the superior aspect of talus neck (n=2), absence of talus (n=2), talocalcaneal ankylose (n=1), small collection in the superior aspect of flap (n=1), drenage canules (n=1). CONCLUSION: In reconstructed hind feet by myocutaneus flaps done for land-mine traumas, MRI presents useful information by displaying detailed anatomy of the flaps, bones, joints, soft tissues and associated complications.

Adult↗
PubMed2026

Rapid and exceptionally small-scale adaptation of the alpine plant Cardamine resedifolia to mining-contaminated soils in multi-stress condition.

The mechanisms by which plants tolerate soil contamination have been studied in details in controlled laboratory conditions, but they still remain largely unexplored in natural conditions where mixtures of contaminants are present in soils and their effects might interact with other environmental variables. This is especially true in high-altitude alpine environments, where abiotic stress is naturally heightened, but which so far have received little attention in environmental pollution studies. As we were interested in the tolerance mechanisms at play on very fine spatiotemporal scales for alpine plants growing under multi-stress conditions, we chose Cardamine resedifolia as our biological model. This plant is indeed frequently found in areas contaminated by Trace Metals and Metalloids and Polycyclic Aromatic Hydrocarbons in high elevation. We studied populations from former copper, silver-lead, and coal mines in alpine environments, along with populations growing on nearby reference soils. We measured genetic variability within populations as well as genetic differentiation between them, and tested for local adaptation to soil contamination using reciprocal transplants. Population pairs showing signs of local adaptation were then examined using genome scans to identify genes potentially under selection. We found high levels of genetic differentiation between populations growing on contaminated and reference soils a few dozen meters apart. In most cases local adaptation was detected, especially in former copper mines. Genome scans identified genes involved in metal stress management as potentially being under selection. This study provides evidence for rapid adaptation to human-induced pollution in alpine plants at remarkably small spatial scales. It offers new insights into the short-term ecological and evolutionary consequences of mining activities in alpine ecosystems, particularly in relation to substrate-driven differentiation.

Alpine plants↗
PubMed2004

Macromolecule mass spectrometry: citation mining of user documents.

Identifying research users, applications, and impact is important for research performers, managers, evaluators, and sponsors. Identification of the user audience and the research impact is complex and time consuming due to the many indirect pathways through which fundamental research can impact applications. This paper identified the literature pathways through which two highly-cited papers of 2002 Chemistry Nobel Laureates Fenn and Tanaka impacted research, technology development, and applications. Citation Mining, an integration of citation bibliometrics and text mining, was applied to the >1600 first generation Science Citation Index (SCI) citing papers to Fenn's 1989 Science paper on Electrospray Ionization for Mass Spectrometry, and to the >400 first generation SCI citing papers to Tanaka's 1988 Rapid Communications in Mass Spectrometry paper on Laser Ionization Time-of-Flight Mass Spectrometry. Bibliometrics was performed on the citing papers to profile the user characteristics. Text mining was performed on the citing papers to identify the technical areas impacted by the research, and the relationships among these technical areas.

Authorship↗
PubMed2006

Applying hybrid reasoning to mine for associative features in biological data.

We develop the means to mine for associative features in biological data. The hybrid reasoning schema for deterministic machine learning and its implementation via logic programming is presented. The methodology of mining for correlation between features is illustrated by the prediction tasks for protein secondary structure and phylogenetic profiles. The suggested methodology leads to a clearer approach to hierarchical classification of proteins and a novel way to represent evolutionary relationships. Comparative analysis of Jasmine and other statistical and deterministic systems (including Explanation-Based Learning and Inductive Logic Programming) are outlined. Advantages of using deterministic versus statistical data mining approaches for high-level exploration of correlation structure are analyzed.

Algorithms↗
PubMed2005

Distribution and mobility of mercury in soils from an old mining area in Mieres, Asturias (Spain).

Mercury content in soils near abandoned mine wastes in the mercury mining area of Mieres (Asturias, Spain) is highly elevated as a result of the long period of mining and abundant Hg production. In this work, an evaluation of Hg concentration, distribution, and mobility in three soil samples from the immediate vicinity of a chimney used for vapour evacuation during pyrometallurgical treatment of the ore was carried out. For that purpose, total Hg contents were determined for the original samples and their grain-size subsamples. The study of mercury mobility in the original samples and in the different particle-size subsamples was made by the application of a sequential extraction method. Results showed that Hg concentration in soils decreases directly with the distance from the chimney and the dispersion of Hg is not influenced by the topographic height of the site tested. The sample collected in the base of the chimney exhibited appreciable amounts of mobile Hg. In general, a higher Hg concentration was found for the finest particle-size subsamples. Hg mobility was found to be higher for quite developed soils. The sample collected downstream from the chimney showed a significant Hg mobile content as a result of a more intensive weathering. An increase of Hg mobility at decreasing particle size was found in all three analysed samples.

Journal Article↗
PubMed1997

Toxicity and occupational health hazards of coal fly ash (CFA). A review of data and comparison to coal mine dust.

Coal fly ashes (CFA) are complex particles of a variable composition, which is mainly dependent on the combustion process, the source of coal and the precipitation technique. Toxic constituents in these particles are considered to be metals, polycyclic aromatic hydrocarbons and silica. The purpose of this review was to study the in vitro and in vivo data on coal fly ash and relate the studied endpoints to the role of (crystalline) silica, considering its recent classification as a human carcinogen. For most of the effects coal mine dust was chosen as a reference, since it contains up to 10% of crystalline silica (alpha-quartz) and is well studied both in vivo and in vitro. Most studies on fly ash toxicity were not designed to elucidate the effect of its silica-content nor did they include coal mine dust as a reference. Taking this into account, both in vitro and in vivo experimental studies show lower toxicity, inflammatory potential and fibrogenicity of CFA compared to silica and coal mine dust. Although in vitro and in vivo studies suggest genotoxic effects of fly ash, the data are limited and do not clarify the role of silica. Epidemiological studies in fly ash exposed working populations have found no evidence for effects commonly seen in coal workers (pneumoconiosis, emphysema) with the exception of airway obstruction at high exposure. In conclusion, the available data suggest that the hazard of coal fly ash is not to be assessed by merely adding the hazards of individual components. A closer investigation of 'matrix' effects on silica's toxicity in general seems an obligatory step in future risk assessment on fly ashes and other particles that incorporate silica as a component.

Animals↗
PubMed2005

The hidden structure of neuropsychology: text mining of the journal Cortex: 1991--2001.

BACKGROUND: The stated mission of Cortex is "the study of the inter-relations of the nervous system and behavior, particularly as these are reflected in the effects of brain lesions on cognitive functions." The purpose of this paper is to explore the relationship between the stated mission and the executed mission as reflected by the characteristics of papers published in Cortex. In addition, we examine whether the results and conclusions of an analysis of this kind are affected by the level of description of the published papers. OBJECTIVES: A) Identify characteristics of contributors to Cortex; B) Identify characteristics of those who cite Cortex; C) Identify recurring themes; D) Identify the relationships among the recurring themes; E) Compare recurring themes and determine their relationships to the mission of Cortex; F) Identify the sensitivity of these results to the level of description of the Cortex papers used as the source database. G) Compare Cortex characteristics with those of Neuropsychologia, another Europe-based international neuropsychology journal. METHODS: Text mining (extraction of useful information from text) was used to generate the characteristics of the journal Cortex. Bibliometrics provided the Cortex contributor infrastructure (author/ organization/ country/ citation distributions), and computational linguistics identified the recurring technical themes and their inter-relationships. Citation mining (the integration of citation bibliometrics and text mining) was used to profile the research user community. Four levels of published article description were compared for the analysis: Full Text, Abstract, Title, Keywords. RESULTS AND CONCLUSIONS: Highly cited documents were compared among Cortex, Neuropsychologia, and Brain, and a number of interesting parametric trends were observed. The characteristics of the papers that cite Cortex papers were examined, and some interesting insights were generated. Finally, the document clustering taxonomy showed that papers in Cortex can be reasonably divided into four categories (papers in each category in parenthesis): Semantic Memory (151); Handedness (145); Amnesia (119); and Neglect (66). It is concluded that Cortex needs to take steps to attract a more diverse group of contributors outside its continental Western European base if it wishes to capture a greater share of seminal neuropsychology papers. Further investigation of the critical citation differences reported in the paper is recommended.

Abstracting and Indexing↗
PubMed2003

ARTMAP neural networks for information fusion and data mining: map production and target recognition methodologies.

The Sensor Exploitation Group of MIT Lincoln Laboratory incorporated an early version of the ARTMAP neural network as the recognition engine of a hierarchical system for fusion and data mining of registered geospatial images. The Lincoln Lab system has been successfully fielded, but is limited to target/non-target identifications and does not produce whole maps. Procedures defined here extend these capabilities by means of a mapping method that learns to identify and distribute arbitrarily many target classes. This new spatial data mining system is designed particularly to cope with the highly skewed class distributions of typical mapping problems. Specification of canonical algorithms and a benchmark testbed has enabled the evaluation of candidate recognition networks as well as pre- and post-processing and feature selection options. The resulting mapping methodology sets a standard for a variety of spatial data mining tasks. In particular, training pixels are drawn from a region that is spatially distinct from the mapped region, which could feature an output class mix that is substantially different from that of the training set. The system recognition component, default ARTMAP, with its fully specified set of canonical parameter values, has become the a priori system of choice among this family of neural networks for a wide variety of applications.

Computer Simulation↗
PubMedDate not supplied

Mining association rules with improved semantics in medical databases.

The discovery of new knowledge by mining medical databases is crucial in order to make an effective use of stored data, enhancing patient management tasks. One of the main objectives of data mining methods is to provide a clear and understandable description of patterns held in data. We introduce a new approach to find association rules among quantitative values in relational databases. The semantics of such rules are improved by introducing imprecise terms in both the antecedent and the consequent, as these terms are the most commonly used in human conversation and reasoning. The terms are modeled by means of fuzzy sets defined in the appropriate domains. However, the mining task is performed on the precise data. These "fuzzy association rules" are more informative than rules relating precise values. We also introduce a new measure of accuracy, based on Shortliffe and Buchanan's certainty factors [Shortliffe E, Buchanan B. Math Biosci 1975;23:351-79]. Also, the semantics of the usual measure of usefulness of an association rule, called support are discussed and some new criteria are introduced. Our new measures have been shown to be more understandable and appropriate than ordinary ones. Several experiments on large medical databases show that our new approach can provide useful knowledge with better semantics in this field.

Databases, Factual↗
PubMedDate not supplied

Data mining a diabetic data warehouse.

Diabetes is a major health problem in the United States. There is a long history of diabetic registries and databases with systematically collected patient information. We examine one such diabetic data warehouse, showing a method of applying data mining techniques, and some of the data issues, analysis problems, and results. The diabetic data warehouse is from a large integrated health care system in the New Orleans area with 30,383 diabetic patients. Methods for translating a complex relational database with time series and sequencing information to a flat file suitable for data mining are challenging. We discuss two variables in detail, a comorbidity index and the HgbA1c, a measure of glycemic control related to outcomes. We used the classification tree approach in Classification and Regression Trees (CART) with a binary target variable of HgbA1c >9.5 and 10 predictors: age, sex, emergency department visits, office visits, comorbidity index, dyslipidemia, hypertension, cardiovascular disease, retinopathy, end-stage renal disease. Unexpectedly, the most important variable associated with bad glycemic control is younger age, not the comorbiditity index or whether patients have related diseases. If we want to target diabetics with bad HgbA1c values, the odds of finding them is 3.2 times as high in those <65 years of age than those older. Data mining can discover novel associations that are useful to clinicians and administrators [corrected].

Adult↗
PubMed2001

Topological regulation of cell division in E. coli. spatiotemporal oscillation of MinD requires stimulation of its ATPase by MinE and phospholipid.

Topological regulation of cell division in E. coli requires positioning a cell division inhibitor, MinC, at the poles of the cell, thus restricting the potential for division to midcell. This positioning is achieved through a rapid oscillation of MinC from pole to pole, a process requiring MinD and MinE. However, the mechanistic basis for this oscillation is not known. Here we report that MinE stimulates MinD ATPase activity, but only in the presence of phospholipid vesicles. Analysis of MinE mutants demonstrates that this stimulation is required for MinD oscillation and suggests that the level of stimulation determines the period of the oscillation. A model is presented in which the requirements for the MinD ATPase contribute spatial and temporal inputs that provide the mechanistic basis for the oscillation.

Adenosine Triphosphatases↗
PubMedDate not supplied

Web-based tools for mining the NCI databases for anticancer drug discovery.

In this paper, we describe the development of a set of integrated Web-based tools for mining the National Cancer Institute's (NCI) anticancer databases for anticancer drug discovery. For data mining, three different correlation algorithms were implemented, which included the commonly used Pearson's correlation algorithm available from the NCI's COMPARE program, the Spearman's and Kendall's correlation algorithms. In addition, we implemented the p-value test to evaluate the significance of the correlation results. These Web-based data mining tools allow robust analysis of the correlation between the in vitro anticancer activity of the drugs in the NCI anticancer database, the protein levels and mRNA levels of molecular targets (genes) in the NCI 60 human cancer cell lines for identification of potential lead compounds for a specific molecular target and for study of the molecular mechanism action of a drug. Examples were provided to identify PKC ligands using a lead compound and to identify potential ErbB-2 inhibitors using the mRNA levels of ErbB-2 in the NCI 60 tumor cell lines.

Antineoplastic Agents↗
PubMed2004

Application of predictive QSAR models to database mining: identification and experimental validation of novel anticonvulsant compounds.

We have developed a drug discovery strategy that employs variable selection quantitative structure-activity relationship (QSAR) models for chemical database mining. The approach starts with the development of rigorously validated QSAR models obtained with the variable selection k nearest neighbor (kNN) method (or, in principle, with any other robust model-building technique). Model validation is based on several statistical criteria, including the randomization of the target property (Y-randomization), independent assessment of the training set model's predictive power using external test sets, and the establishment of the model's applicability domain. All successful models are employed in database mining concurrently; in each case, only variables selected as a result of model building (termed descriptor pharmacophore) are used in chemical similarity searches comparing active compounds of the training set (queries) with those in chemical databases. Specific biological activity (characteristic of the training set compounds) of external database entries found to be within a predefined similarity threshold of the training set molecules is predicted on the basis of the validated QSAR models using the applicability domain criteria. Compounds judged to have high predicted activities by all or the majority of all models are considered as consensus hits. We report on the application of this computational strategy for the first time for the discovery of anticonvulsant agents in the Maybridge and National Cancer Institute (NCI) databases containing ca. 250,000 compounds combined. Forty-eight anticonvulsant agents of the functionalized amino acid (FAA) series were used to build kNN variable selection QSAR models. The 10 best models were applied to mining chemical databases, and 22 compounds were selected as consensus hits. Nine compounds were synthesized and tested at the NIH Epilepsy Branch, Rockville, MD using the same biological test that was employed to assess the anticonvulsant activity of the training set compounds; of these nine, four were exact database hits and five were derived from the hits by minor chemical modifications. Seven of these nine compounds were confirmed to be active, indicating an exceptionally high hit rate. The approach described in this report can be used as a general rational drug discovery tool.

Amides↗