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PubMed1987

Effectiveness of mine rehabilitation in relation to water quality.

When mining is completed the sites may be completely restored to the original ecosystem, rehabilitated for some desirable environmental characteristics, desirable alternative ecosystems created or just neglected. The strategy adopted will depend on the intended uses of the parts of the environment (including water) affected by the mining. An example of rehabilitation of a metal mine near the Australian Federal Capital is used to illustrate the problems that may be encountered. These include: lack of controls while mining is underway; catastrophic events, such as the collapse of a settling dam, lack of site specific understanding of pyrite oxidation processes, particularly those that are biologically enhanced; the need for adequate biological information on which to base decisions to meet biological information on which to base decisions to meet biological objectives. Experience has shown that biological collections such studies should be stored in museums where they will be valuable for comparisons of changes over long periods.

Environmental Pollution↗
PubMed1987

Effect of phosphate on different blood parameters of labourers at Rusaifa Phosphate Mines, Jordan.

The effect of phosphate on PCV, Hb, platelet count, WBC count and differential leukocytic count were investigated in 36 phosphate mine labourers and 21 office employees (not exposed to phosphate dust) at Rusaifa Phosphate Mines, Jordan. Their age range was 30-40 years and they had worked in the mines for 5 to 10 years. Most parameters were significantly higher in the mine labourers as compared to those of office employees.

Adult↗
PubMed1983

[Fire fighting with nitrogen in the German coal mining industry].

Fire-fighting methods using inert gases have been known for decades. In December 1974, for the first time in the German coalmining industry, liquid nitrogen was gasified at the surface and fed to a mine fire underground. This developed into a standard fire-fighting procedure in mines and has been used in numerous cases. The great advantage of this method for the mine rescue operations is the elimination of explosion hazards and the possibility to create better working conditions. The example of a large scale fire in 1982 illustrates how fire zones can be stopped and reopened in immediate succession, if some requirements are fulfilled. The neutralization method sets new technical and safety tasks for the mine rescue services. Instruction on working in a low oxygen environment now represents a particularly important part of their training.

Coal Mining↗
PubMed1978

The levels of immunoglobulins (IgG. IgA. IgM) under the effect of age and exposure to the mining environment in uranium industry.

IgG, IgA, and IgM levels were measured in 347 miners working in the underground of uranium mines; in 156 men entering into the work in mines, and in 101 men working in food industry and food distribution, all in the region of Central Bohemia. Significantly elevated IgG and IgM levels were found in the subgroup of miners exposed a short time (less than five years) to the mining environment, whereas elevated IgA levels were found in the subgroup exposed more than 15 years. The comparison of differences with age-matched controls has shown that the levels of IgM are significantly increased in the miners subgroup exposed to the mining environment no more than five years. In miners subgroups above 31 years a significant decline of IgG levels occurs. The expression of Ig levels' changes is not uniform in all exposed persons; an apparent heterogeneity occurs in miners population. Some differences in IgG and IgM levels were found between the two 31- to 40-year-old control subgroups. The possible conditions for differences found are discussed from the point of view of the effect of ionizing radiation and from the point of view of the stressing influence of environment and employment.

Adult↗
PubMed1982

Interaction between underground mining and smoking in the causation of lung cancer: a study of nonuranium miners in northern Sweden.

Combined effects of underground mining (nonuranium mines) and smoking were analyzed in a case-control study of male lung cancer in northern Sweden. Lung cancer cases exposed to underground mining had a considerably lower average cumulative tobacco consumption than other lung cancer cases, indicating that smoking is especially dangerous for underground miners. When relative risks were estimated, a synergistic effect of multiplicative type was found between smoking and underground mining.

Humans↗
PubMed1994

Knowledge and attitudes of a group of South African mine workers towards noise induced hearing loss and the use of hearing protective devices.

The study aimed to explore the knowledge and attitudes of a group of mine workers regarding noise induced hearing loss and the use of hearing protective devices. These aims were investigated via a questionnaire administered in a group setting to 55 underground mine workers. The main finding that emerged from the study was that respondents were poorly informed regarding the fact that noise was a health hazard. Furthermore, the knowledge that respondents did possess, appeared to have been derived from the personal experience of working in noisy environments for many years, rather than from educational input. Contrary to expectations, respondents did not view deafness as a status symbol but rather as a negative attribute. Consequently, they were motivated to protect themselves from hearing impairment and to be educated about hearing and the effects of noise. The mine workers complained about discomfort when wearing hearing protective devices as well as feelings of insecurity due to inhibition of communication and the inability to hear warning signals. For these reasons, noise protection was mainly worn in situations perceived as noisy by workers themselves. These results are discussed in terms of their implications for the clinical practice of audiology; hearing conservation in the mining industry; further research; and the training and education of speech-language pathologists and audiologists.

Ear Protective Devices↗
PubMedDate not supplied

Relationship between soil and dust lead in a lead mining area and blood lead levels.

UNLABELLED: The relationship between lead mining waste and childhood lead poisoning is poorly understood. This study evaluates the contribution of soil lead to blood lead levels. METHODS: 125 children between 6 and 71 months of age living in a lead mining area of southwestern Missouri were evaluated for blood lead and their homes tested for lead in soil, dust, and paint. These results were compared to 26 control children. RESULTS: Homes in the lead mining area had significantly increased soil and dust lead levels and significantly higher blood lead levels. The primary source of dust lead was soil lead. There was a strong relationship between blood lead levels and dust, soil, and paint lead. CONCLUSION: Soil lead related to mining operations plays a significant role in contributing to blood lead levels in children.

Child, Preschool↗
PubMed2005

PolyMAPr: programs for polymorphism database mining, annotation, and functional analysis.

Pharmacogenomic and disease-association studies rely on identifying a comprehensive set of polymorphisms within candidate genes. Public SNP databases are a rich source of polymorphism data, but mining them effectively requires overcoming at least four challenges: ensuring accurate annotations for genes and polymorphisms, eliminating both inter- and intra-database redundancy, integrating data from multiple public sources with data generated locally, and prioritizing the variants for further study. PolyMAPr (Polymorphism Mining and Annotation Programs)' was developed to overcome these challenges and to improve the efficiency of database mining and polymorphism annotation. PolyMAPr takes as input a file containing a list of genes to be processed and files containing each annotated gene sequence. Polymorphic sequences obtained from public databases (dbSNP, CGAP, and JSNP) or through local SNP discovery efforts, as well as oligonucleotide sequences (e.g., PCR primers), are mapped to the annotated gene sequences and named according to suggested nomenclature guidelines. The functional effects of nonsynonymous coding-region SNPs (cSNPs) and any variants that might alter exon splicing enhancer (ESE) sites, putative transcription factor binding sites, or intron-exon splice sites are predicted. The output files are accessible though a browser interface. In addition, the results are also provided in Extensible Markup Language (XML) format to facilitate uploading them into a local relational database. PolyMAPr increases the efficiency of mining public databases for genetic variants within candidate genes and provides a mechanism by which data from multiple sources (both public and private) can be uniformly integrated, thereby significantly reducing the effort required to obtain a comprehensive set of polymorphisms for pharmacogenomic and disease-association studies. PolyMAPr can be obtained from http://pharmacogenomics.wustl.edu.

Databases, Nucleic Acid↗
PubMed2002

Computation of the physio-chemical properties and data mining of large molecular collections.

Very large data sets of molecules screened against a broad range of targets have become available due to the advent of combinatorial chemistry. This information has led to the realization that ADME (absorption, distribution, metabolism, and excretion) and toxicity issues are important to consider prior to library synthesis. Furthermore, these large data sets provide a unique and important source of information regarding what types of molecular shapes may interact with specific receptor or target classes. Thus, the requirement for rapid and accurate data mining tools became paramount. To address these issues Pharmacopeia, Inc. formed a computational research group, The Center for Informatics and Drug Discovery (CIDD).* In this review we cover the work done by this group to address both in silico ADME modeling and data mining issues faced by Pharmacopeia because of the availability of a large and diverse collection (over 6 million discrete compounds) of drug-like molecules. In particular, in the data mining arena we discuss rapid docking tools and how we employ them, and we describe a novel data mining tool based on a ID representation of a molecule followed by a molecular sequence alignment step. For the ADME area we discuss the development and application of absorption, blood-brain barrier (BBB) and solubility models. Finally, we summarize the impact the tools and approaches might have on the drug discovery process.

Algorithms↗
PubMed2005

Comparing data mining methods on the VAERS database.

PURPOSE: Data mining may enhance traditional surveillance of vaccine adverse events by identifying events that are reported more commonly after administering one vaccine than other vaccines. Data mining methods find signals as the proportion of times a condition or group of conditions is reported soon after the administration of a vaccine; thus it is a relative proportion compared across vaccines, and not an absolute rate for the condition. The Vaccine Adverse Event Reporting System (VAERS) contains approximately 150 000 reports of adverse events that are possibly associated with vaccine administration. METHODS: We studied four data mining techniques: empirical Bayes geometric mean (EBGM), lower-bound of the EBGM's 90% confidence interval (EB05), proportional reporting ratio (PRR), and screened PRR (SPRR). We applied these to the VAERS database and compared the agreement among methods and other performance properties, particularly focusing on the vaccine-event combinations with the highest numerical scores in the various methods. RESULTS: The vaccine-event combinations with the highest numerical scores varied substantially among the methods. Not all combinations representing known associations appeared in the top 100 vaccine-event pairs for all methods. CONCLUSIONS: The four methods differ in their ranking of vaccine-COSTART pairs. A given method may be superior in certain situations but inferior in others. This paper examines the statistical relationships among the four estimators. Determining which method is best for public health will require additional analysis that focuses on the true alarm and false alarm rates using known vaccine-event associations. Evaluating the properties of these data mining methods will help determine the value of such methods in vaccine safety surveillance.

Adverse Drug Reaction Reporting Systems↗
PubMed2002

Data mining the protein data bank: residue interactions.

The protein databank contains a vast wealth of structural and functional information. The analysis of this macromolecular information has been the subject of considerable work in order to advance knowledge beyond the collection of molecular coordinates. This article presents a method that determines local structural information within proteins using mathematical data mining techniques. The mine program described returns many known configurations of residues such as the catalytic triad, metal binding sites and the N-linked glycosylation site; as well as many other multiple residue interactions not previously categorized. Because mathematical constructs are used as targets, this method can identify new information not previously known, and also provide unbiased results of typical structure and their expected deviations. Because the results are defined mathematically, they cannot indicate the biological implications of the results. Therefore two support programs are described that provide insight into the biological context for the mine results. The first allows a weighted RMSD search between a template set of coordinates and a list of PDB files, and the second allows the labeling of a protein with the template results from mining to aid in the classification of this protein.

Algorithms↗
PubMed2006

Kinetic speciation of nickel in mining and municipal effluents.

This study presents the results of kinetic speciation of nickel in undiluted mining and municipal effluents and effluents diluted with receiving freshwaters from the surrounding environment. The dilution ratios used for the dilution of the effluents were arbitrarily chosen, but were representative of the prevailing mining practices. The purpose of the this dilution was to mimic dilution with natural waters that result from dilution of the mining and municipal effluents with receiving freshwaters, so that this study would reveal environmental realities that are of concern to the managers and regulators of water resources. Ligand exchange kinetics using the competing ligand exchange method (CLEM) was studied using two independent techniques: graphite furnace atomic absorption spectrometry (GFAAS) with Chelex 100 resin as the competing ligand, and adsorptive cathodic stripping voltammetry (AdCSV) with dimethylglyoxime (DMG) as the competing ligand to determine the percentage of Ni metal released from Ni(II)-DOC complexes and the rate of dissociation of Ni(II)-DOC complexes. Using a sample containing a mixture of 30% Copper Cliff Mine effluent, 40% Sudbury municipal effluent and 30% Vermillion River water, both techniques gave results showing that the dilution of the effluent samples increased the percentage of nickel released from Ni(II)-DOC complexes. This increase in the release of nickel from the Ni(II)-DOC complexes may be of concern to managers and regulators of water resources. Agreement between the results of these two techniques has enhanced the validity of the competing ligand exchange method used by both techniques.

Journal Article↗
PubMed1999

Distribution of trace elements in streambed sediment associated with mining activities in the upper colorado river basin, colorado, USA, 1995-96

Streambed-sediment samples were collected in the Southern Rocky Mountains physiographic province in the Upper Colorado River Basin in Colorado to characterize the occurrence and distribution of trace elements in mined and nonmined areas of the basin. During October 1995 and September 1996, streambed sediment was collected at 37 sites, and the samples were analyzed for trace elements. The ranges in concentrations of As, Cd, Cu, Pb, and Zn at mining sites generally were orders of magnitude higher than the ranges of concentrations at nonmining sites. Sampling sites located in two predominant rock types in mining areas were not significantly different (p > 0.05) for concentrations of As, Cd, Pb, and Zn. Cu was significantly different (p < 0.05) between sites in the two predominant rock types. Concentrations of As, Cd, Cu, Pb, and Zn were not significantly different (p > 0.05) between main-stem sites and tributary sites. Concentrations of As, Cd, Cu, Pb, and Zn exceeded established guidelines for adverse effects on aquatic biota at some sites in the study area. The patterns in concentrations of Cd and Zn, Cd and Pb, and Pb and Zn were highly correlated to one another in this study. Concentrations of trace elements in the <63-&mgr;m fraction were higher than in the total particle-size fraction analysis. Comparison of reference sites to sites affected by a mine source indicated that trace-element concentrations initially increased downstream of the source and then gradually decreased in concentration with distance from the source.http://link. springer-ny.com/link/service/journals/00244/bibs/37n1p7.html

Journal Article↗
PubMed2004

A novel data mining approach to the identification of effective drugs or combinations for targeted endpoints--application to chronic heart failure as a new form of evidence-based medicine.

BACKGROUND: Data mining is a technique for discovering useful information hidden in a database, which has recently been used by the chemical, financial, pharmaceutical, and insurance industries. It may enable us to detect the interesting and hidden data on useful drugs especially in the field of cardiovascular disease. METHODS AND RESULTS: We evaluated the current treatments for chronic heart failure (CHF) in our institute using a decision tree method of data mining and compared the results with those of large-scale clinical trials. We enrolled 1,100 patients with CHF (NYHA classes II-IV and EF < 40%) who were hospitalized at the National Cardiovascular Center during the past 31 months. Drugs prescribed at discharge were extracted from the clinical database. Both echocardiograms and plasma BNP level at 6-12 months after discharge were determined prospectively. It was found that beta-blockers, angiotensin converting enzyme inhibitors, and angiotensin II receptor antagonists independently improve both the plasma BNP level and %fractional shortening (FS), while oral inotropic agents increased the plasma BNP level and decreased %FS. These findings agree with evidence accumulated from several large-scale trials. Interestingly, statins, histamine receptor blockers, and alpha-glucosidase inhibitors also attenuated the severity of CHF, suggesting the possibility of new treatment of CHF. CONCLUSION: Clinical data mining using Japanese CHF patients yielded almost identical data to the results of large-scale trials, and also suggested novel and unexpected candidates for CHF therapy. Further validation of the data mining approved in the cardiovascular field is warranted.

Chronic Disease↗
PubMed2006

Application of data mining approaches to drug delivery.

Computational approaches play a key role in all areas of the pharmaceutical industry from data mining, experimental and clinical data capture to pharmacoeconomics and adverse events monitoring. They will likely continue to be indispensable assets along with a growing library of software applications. This is primarily due to the increasingly massive amount of biology, chemistry and clinical data, which is now entering the public domain mainly as a result of NIH and commercially funded projects. We are therefore in need of new methods for mining this mountain of data in order to enable new hypothesis generation. The computational approaches include, but are not limited to, database compilation, quantitative structure activity relationships (QSAR), pharmacophores, network visualization models, decision trees, machine learning algorithms and multidimensional data visualization software that could be used to improve drug delivery after mining public and/or proprietary data. We will discuss some areas of unmet needs in the area of data mining for drug delivery that can be addressed with new software tools or databases of relevance to future pharmaceutical projects.

Computer Simulation↗
PubMed2004

Data mining techniques for cancer detection using serum proteomic profiling.

OBJECTIVE: Pathological changes in an organ or tissue may be reflected in proteomic patterns in serum. It is possible that unique serum proteomic patterns could be used to discriminate cancer samples from non-cancer ones. Due to the complexity of proteomic profiling, a higher order analysis such as data mining is needed to uncover the differences in complex proteomic patterns. The objectives of this paper are (1) to briefly review the application of data mining techniques in proteomics for cancer detection/diagnosis; (2) to explore a novel analytic method with different feature selection methods; (3) to compare the results obtained on different datasets and that reported by Petricoin et al. in terms of detection performance and selected proteomic patterns. METHODS AND MATERIAL: Three serum SELDI MS data sets were used in this research to identify serum proteomic patterns that distinguish the serum of ovarian cancer cases from non-cancer controls. A support vector machine-based method is applied in this study, in which statistical testing and genetic algorithm-based methods are used for feature selection respectively. Leave-one-out cross validation with receiver operating characteristic (ROC) curve is used for evaluation and comparison of cancer detection performance. RESULTS AND CONCLUSIONS: The results showed that (1) data mining techniques can be successfully applied to ovarian cancer detection with a reasonably high performance; (2) the classification using features selected by the genetic algorithm consistently outperformed those selected by statistical testing in terms of accuracy and robustness; (3) the discriminatory features (proteomic patterns) can be very different from one selection method to another. In other words, the pattern selection and its classification efficiency are highly classifier dependent. Therefore, when using data mining techniques, the discrimination of cancer from normal does not depend solely upon the identity and origination of cancer-related proteins.

Biomarkers, Tumor↗
PubMed2004

Applying data mining techniques to library design, lead generation and lead optimization.

Many data mining techniques have been applied to activity and ADMET datasets and the resulting models are being used to understand quantitative structure-activity relationships and design new libraries. This review summarizes data mining concepts and discuss their application to library design, lead generation (particularly for sequential screening) and lead optimization (specifically for generating and interpreting QSAR models). Also, this review discusses recent comparative studies between data mining techniques and draws some conclusions about the patterns emerging in the drug discovery data mining field.

Algorithms↗
PubMed2004

iProLINK: an integrated protein resource for literature mining.

The exponential growth of large-scale molecular sequence data and of the PubMed scientific literature has prompted active research in biological literature mining and information extraction to facilitate genome/proteome annotation and improve the quality of biological databases. Motivated by the promise of text mining methodologies, but at the same time, the lack of adequate curated data for training and benchmarking, the Protein Information Resource (PIR) has developed a resource for protein literature mining--iProLINK (integrated Protein Literature INformation and Knowledge). As PIR focuses its effort on the curation of the UniProt protein sequence database, the goal of iProLINK is to provide curated data sources that can be utilized for text mining research in the areas of bibliography mapping, annotation extraction, protein named entity recognition, and protein ontology development. The data sources for bibliography mapping and annotation extraction include mapped citations (PubMed ID to protein entry and feature line mapping) and annotation-tagged literature corpora. The latter includes several hundred abstracts and full-text articles tagged with experimentally validated post-translational modifications (PTMs) annotated in the PIR protein sequence database. The data sources for entity recognition and ontology development include a protein name dictionary, word token dictionaries, protein name-tagged literature corpora along with tagging guidelines, as well as a protein ontology based on PIRSF protein family names. iProLINK is freely accessible at http://pir.georgetown.edu/iprolink, with hypertext links for all downloadable files.

Computational Biology↗