An Exposure-Response Curve for Copper Excess and Deficiency

范畴变量 医学 毒性 线性回归 风险评估 统计 动物科学 数学 内科学 生物 计算机科学 计算机安全
作者
Andrea Chambers,Daniel Krewski,Nicholas Birkett,Laura M. Plunkett,Richard C. Hertzberg,Ruth Danzeisen,Peter Aggett,Thomas B. Starr,Scott Baker,Michael Dourson,P.G. Jones,Carl L. Keen,Bette Meek,Rita Schoeny,Wout Slob
出处
期刊:Journal of Toxicology and Environmental Health-part B-critical Reviews [Taylor & Francis]
卷期号:13 (7-8): 546-578 被引量:69
标识
DOI:10.1080/10937404.2010.538657
摘要

There is a need to define exposure-response curves for both Cu excess and deficiency to assist in determining the acceptable range of oral intake. A comprehensive database has been developed where different health outcomes from elevated and deficient Cu intakes were assigned ordinal severity scores to create common measures of response. A generalized linear model for ordinal data was used to estimate the probability of response associated with dose, duration and severity. The model can account for differences in animal species, the exposure medium (drinking water and feed), age, sex, and solubility. Using this model, an optimal intake level of 2.6 mg Cu/d was determined. This value is higher than the current U.S. recommended dietary intake (RDI; 0.9 mg/d) that protects against toxicity from Cu deficiency. It is also lower than the current tolerable upper intake level (UL; 10 mg/d) that protects against toxicity from Cu excess. Compared to traditional risk assessment approaches, categorical regression can provide risk managers with more information, including a range of intake levels associated with different levels of severity and probability of response. To weigh the relative harms of deficiency and excess, it is important that the results be interpreted along with the available information on the nature of the responses that were assigned to each severity score.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
大饼饼饼完成签到,获得积分10
1秒前
2秒前
2秒前
理解完成签到,获得积分10
2秒前
TW完成签到,获得积分10
2秒前
淘宝叮咚完成签到,获得积分10
3秒前
AllenLau1031完成签到,获得积分10
3秒前
严怜梦完成签到 ,获得积分10
4秒前
GG完成签到,获得积分10
4秒前
4秒前
飞雨听澜完成签到,获得积分10
4秒前
于归故城完成签到,获得积分10
4秒前
低级趣味完成签到,获得积分10
5秒前
5秒前
Hi完成签到,获得积分10
5秒前
5秒前
Yang完成签到,获得积分10
5秒前
野猪完成签到,获得积分10
6秒前
海屿你完成签到,获得积分20
6秒前
li完成签到,获得积分10
6秒前
一口娴蛋黄完成签到,获得积分10
6秒前
ABCDE完成签到,获得积分10
6秒前
Akim应助Jun采纳,获得10
6秒前
六神曲完成签到,获得积分10
7秒前
科研通AI6.3应助认真幼萱采纳,获得10
7秒前
Zhangqiang发布了新的文献求助10
7秒前
任罗川完成签到,获得积分10
7秒前
cczzhh发布了新的文献求助10
8秒前
花谢完成签到,获得积分10
9秒前
科研通AI6.4应助墨痕采纳,获得10
9秒前
三万五完成签到,获得积分10
9秒前
王俊1314完成签到 ,获得积分10
10秒前
111完成签到,获得积分10
10秒前
诚心的白昼完成签到,获得积分10
11秒前
Zhy完成签到,获得积分10
11秒前
考马斯亮蓝完成签到 ,获得积分10
11秒前
爱喝佳得乐完成签到,获得积分10
12秒前
宁燕完成签到,获得积分10
12秒前
爆米花应助zzz采纳,获得10
13秒前
暮商零七应助栗子采纳,获得10
13秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7253079
求助须知:如何正确求助?哪些是违规求助? 8875200
关于积分的说明 18735568
捐赠科研通 6933688
什么是DOI,文献DOI怎么找? 3199860
关于科研通互助平台的介绍 2374606
邀请新用户注册赠送积分活动 2174524