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Nausea threshold in apparently healthy individuals who drink fluids containing graded concentrations of copper. Age and copper intake do not affect copper 65 absorption, measured with the use of Cu as a tracer, in young infants. Copper in infant nutrition: safety of World Health Organization provisional guideline value for copper content of drinking water. Compositions of particles from selected sources in Philadelphia for receptor modeling applications. Influence of copper on the early post-implantation mouse embryo: An in vivo and in vitro study. Copper-induced microtubule degeneration and filamentous inclusions in the neuroepithelium of the mouse embryo. Mussels and algae as bioindicators for long-term tendencies of element pollution in marine ecosystems. Bioaccumulation of heavy metals in thionic fluvisols by a marine polycheate: the role of metal studies. The abundance of some elements in hair and nail from the Machakos District of Kenya. A study of the distribution of lead, cadmium and copper between water and kaolin, bemtonite and a river sediment. Comparison of groundwater and surface water for patterns and levels of contamination by toxic substances. Copper neurotoxicity is dependent on dopamine mediated copper uptake and one-electron reduction of aminochrome in a rat substantia nigra neuronal cell line. The effect of copper on (H)-tryptophan metabolism in organ cultures of rat pineal glands. Bioavailability of metals and arsenic to small mammals at a mining waste-contaminated wetland. Food chain analysis of exposures and risks to wildlife at metals-contaminated wetland. Iron, copper and zinc status in rats fed on diets containing various concentrations of tin. Mineral content of foods and total diets: the selected minerals in foods survery, 1982-1984. Copper transport from ceruloplasmin: Characterization of the cellular uptake mechanism. Vomitting and diarrhea are the most common symptoms in children who drink water with high levels of copper.
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These are known as "inclusion terms" and are given, in addition to the title, as examples of the diagnostic statements to be classified to that rubric. Many of the items listed relate to important or common terms belonging to the rubric. Others are borderline conditions or sites listed to distinguish the boundary between one subcategory and another. This usually occurs when the inclusion terms are elaborating lists of sites or pharmaceutical products, where appropriate words from the titles. General diagnostic descriptions common to a range of categories, or to all the subcategories in a three-character category, are to be found in notes headed "Includes", immediately following a chapter, block or category title. These are terms which, although the rubric title might suggest that they were to be classified there, are in fact classified elsewhere. To enclose the dagger code for an asterisk category and as asterisk code for a dagger category. For example, in K36, "Other appendicitis", the diagnosis "appendicitis" is to be classified there only if qualified by the words "chronic" or "recurrent". Any of the terms before the brace should be qualified by one or more of the terms that follow it. Sometimes an unqualified term is nevertheless classified to a rubric for a more specific type of the condition. For example, "mitral stenosis" is commonly used to mean "rheumatic mitral stenosis". For example, before the Eighth Revision, an unqualified aortic aneurysm was assumed to be due to syphilis. For example: J16 Pneumonia due to other infectious organisms, not elsewhere classified this category includes J16. G03 Meningitis due to other and unspecified causes, Excludes: meningoencephalitis (G04. Identify the type of statement to be coded and refer to the appropriate section of the Alphabetical Index. However, some conditions expressed as adjectives or eponyms are included in the Index as lead terms. He noted that the Tenth Revision would have a new title, International Statistical Classification of Diseases and Related Health Problems, to emphasize its statistical purpose and reflect the widening of its scope. The Conference adopted an agenda dealing with the proposed content of the chapters of the Tenth Revision, and material to be incorporated in the published manual; the process for its introduction; and the family of classifications and related matters. While early revisions of the classification had been concerned only with causes of death, its scope had been extended at the Sixth Revision in 1948 to include non-fatal diseases. In addition, at the International Conference for the Ninth Revision (Geneva, 1975) (1), recommendations had been made and approved for the publication for trial purposes of supplementary classifications of procedures in medicine and of impairments, disabilities, and handicaps. Even with a new structure, it was plain that one classification could not cope with the extremes of the requirements. Decisions made on these matters had paved the way for the preparation of successive drafts of chapter proposals for the Tenth Revision.
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About 1,400,000,000 pounds (640,000,000,000 grams) of copper were released into the environment by industries in 2000. Copper is often found near mines, smelters, industrial settings, landfills, and waste disposal sites. When copper is released into soil, it can become strongly attached to the organic material and other components. Even though copper binds strongly to suspended particles and sediments, there is evidence to suggest that some water-soluble copper compounds do enter groundwater. Copper that enters water eventually collects in the sediments of rivers, lakes, and estuaries. Copper is carried on particles emitted from smelters and ore processing plants, and is then carried back to earth through gravity or in rain or snow. Indoor release of copper comes mainly from combustion processes (for example, kerosene heaters). Copper can be found in plants and animals, and at high concentrations in filter feeders such as mussels and oysters. Copper is also found in a range of concentrations in many foods and beverages that we eat and drink, including drinking water. You will find additional information on the fate of copper in the environment in Chapters 5 and 6. You may be exposed to copper by breathing air, drinking water, eating food, and by skin contact with soil, water and other copper-containing substances. Most copper compounds found in air, water, sediment, soil and rock are strongly attached to dust and dirt or imbedded in minerals. You can take copper into your body upon ingestion of water or soil that contains copper or by inhalation of copper-containing dust. Some copper in the environment is less tightly bound to soil or particles in water and may be soluble enough in water to be taken up by plants and animals. In the general population, soluble copper compounds (those that dissolve in water), which are most commonly used in agriculture, are more likely to threaten your health. When soluble copper compounds are released into lakes and rivers, they generally become attached to particles in the water within approximately 1 day. This could lessen your exposure to copper in water, depending on how strongly the copper is bound to the particles and how much of the particles settle into lake and river sediments. Therefore, at high fine particle concentrations, both exposure and uptake can be considerable even under conditions of tight copper binding to the suspended particulates. The concentration of copper in air ranges from a few nanograms (1 nanogram equals 3 1/1,000,000,000 of a gram or 4/100,000,000,000 of an ounce) in a cubic meter of air (ng/m) to 3 3 about 200 ng/m. Near 3 smelters, which process copper ore into metal, concentrations may reach 5,000 ng/m. You may breathe high levels of copper-containing dust if you live or work near copper mines or processing facilities. You may be exposed to levels of soluble copper in your drinking water that are above the acceptable drinking water standard of 1,300 parts copper per billion parts of water (ppb), especially if your water is corrosive and you have copper plumbing and brass water fixtures.
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However, these Belgian, Danish, and Dutch studies have poten tial relevance only to female Vietnam veterans with pregnancy subsequent to military service. These have included studies from the Dutch LifeLines cohort study, a multidis ciplinary prospective population-based cohort study examining health and health related behaviors of persons living in the northern region of the Netherlands (de Jong et al. For the current update, the subjects of studies of the effects of environmental exposures have included populations in Belgium (Den Hond et al. Three areas were defned on the basis of soil sampling: Zone A (556 people), the most heavily contaminated, from which all residents were permanently evacuated within 20 days; Zone B (3,920), an area of lower contamination that all children and women in the frst trimester of pregnancy were urged to avoid during daytime; and Zone R (26,227), a region with some contamination in which the consumption of local crops was prohibited (Bertazzi et al. The sample sizes differ among follow-up studies, presumably because of migration; the sample sizes given above were reported in Bertazzi et al. Adults seemed much less likely than children to develop chloracne after acute exposure, but surveillance bias could have affected that fnding. Several cohort studies have been conducted using the Zone A, Zone B, and Zone R exposure categories. There have been multiple long-term follow-up inves tigations of the health outcomes, especially cancers, of Seveso residents. Bertazzi and colleagues, for example, conducted 10-year mortality follow-up studies of adults (Bertazzi et al. Cause-specifc mortality was determined for each zone, compared with that in the comparison cohort, and adjusted for presence at the accident, sex, age, and time since the Seveso accident. They recommended that a distribution based multiple-imputation method be used to analyze environmental data when substantial proportions of observations have non-detectable readings. All the women were interviewed by a nurse blinded to their exposure status, and each subset received gynecologic examinations. M edical records of those who reported ever having received a diagnosis of cancer were obtained and subjected to blind review by a pathologist. Adding the questionnaire data improved the regression model to the point that it explained 42% of the variability. Of the 981 women who had participated in the frst study, 833 were located, alive, and willing to participate in the second. Each was re-interviewed, provided clinical measurements, and consented to a medical record review to confrm her cancer diagnosis.
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