scholarly journals The Application of Dose-Response Models to Determine the Median Effective Adsorbent Bone Char Dose to Remove Fluoride From Drinking Aqueous Solutions

2016 ◽  
Vol 23 (3) ◽  
pp. 237-248
Author(s):  
Sara Zebarjadi ◽  
Ali Reza Soltanian ◽  
Javad Faradmal ◽  
Ghorban Asgari ◽  
Keyword(s):  
Aqueous Solutions ◽  
Dose Response ◽  
Bone Char ◽  
Response Models

scholarly journals Investigation of the transport characteristics of Pb(II) in sand-bone char columns

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110236
Author(s):  
Gang Li ◽  
Jinli Zhang ◽  
Jia Liu ◽  
Tao Luo ◽  
Yu Xi
Keyword(s):  
Adsorption Capacity ◽  
Flow Rate ◽  
Dose Response ◽  
Construction Materials ◽  
Column Height ◽  
Maximum Adsorption Capacity ◽  
Complexation Reaction ◽  
Bone Char ◽  
Inlet Flow ◽  
Inlet Flow Rate

Pb(II) leakage from batteries, dyes, construction materials, and gasoline threaten human health and environmental safety, and suitable adsorption materials are vitally important for Pb(II) removal. Bone char is an outstanding adsorbent material for water treatment, and the effectiveness in Pb(II) removing need to be verified. In this paper, the transport characteristics of Pb(II) in columns filled with a sand and bone char mixture were studied at the laboratory scale, and the influences of the initial concentration, column height, inlet flow rate, and competing ion Cu(II) on Pb(II) adsorption and transport were analyzed. The Thomas and Dose-Response models were used to predict the test results, and the mechanisms of Pb(II) adsorption on bone char were investigated. The results showed that the adsorption capacity of the bone char increased with increasing column height and decreased with increasing initial Pb(II) concentration, flow rate, and Cu(II) concentration. The maximum adsorption capacity reached 38.466 mg/g and the saturation rate was 95.8% at an initial Pb(II) concentration of 200 mg/L, inlet flow rate of 4 mL/min, and column height of 30 cm. In the competitive binary system, the higher the Cu(II) concentration was, the greater the decreases in the breakthrough and termination times, and the faster the decrease in the Pb(II) adsorption capacity of the bone char. The predicted results of the Dose-Response model agreed well with the experimental results and were significantly better than those of the Thomas model. The main mechanisms of Pb(II) adsorption on bone char include a surface complexation reaction and the decomposition-replacement-precipitation of calcium hydroxyapatite (CaHA). Based on selectivity, sensitivity, and cost analyses, it can be concluded that bone char is a potential adsorbent for Pb(II)-containing wastewater treatment.

scholarly journals Weighted mixed-effects dose–response models for tables of correlated contrasts

2021 ◽  
Vol 21 (2) ◽  
pp. 320-347
Author(s):  
Nicola Orsini
Keyword(s):  
Dose Response ◽  
Response Pattern ◽  
Mixed Effects ◽  
Data Generation ◽  
Measures Of Association ◽  
Response Models ◽  
Response Data ◽  
Hazard Ratios ◽  
Health Related ◽  
Generation Mechanisms

Recognizing a dose–response pattern based on heterogeneous tables of contrasts is hard. Specification of a statistical model that can consider the possible dose–response data-generating mechanism, including its variation across studies, is crucial for statistical inference. The aim of this article is to increase the understanding of mixed-effects dose–response models suitable for tables of correlated estimates. One can use the command drmeta with additive (mean difference) and multiplicative (odds ratios, hazard ratios) measures of association. The postestimation command drmeta_graph greatly facilitates the visualization of predicted average and study-specific dose–response relationships. I illustrate applications of the drmeta command with regression splines in experimental and observational data based on nonlinear and random-effects data-generation mechanisms that can be encountered in health-related sciences.

Development of Dose-Response Models to Predict the Relationship for HumanToxoplasma gondiiInfection Associated with Meat Consumption

Risk Analysis ◽  
2015 ◽  
Vol 36 (5) ◽  
pp. 926-938 ◽  
Author(s):  
Miao Guo ◽  
Abhinav Mishra ◽  
Robert L. Buchanan ◽  
Jitender P. Dubey ◽  
Dolores E. Hill ◽  
...  
Keyword(s):  
Dose Response ◽  
Meat Consumption ◽  
Response Models ◽  
The Relationship

Improving the Development and Use of Biologically Based Dose Response Models (BBDR) in Risk Assessment

2001 ◽  
Vol 7 (5) ◽  
pp. 1091-1120 ◽  
Author(s):  
Robert S. DeWoskin ◽  
Stan Barone ◽  
Harvey J. Clewell ◽  
R. Woodrow Setzer
Keyword(s):  
Risk Assessment ◽  
Dose Response ◽  
Response Models

scholarly journals Evaluation of the 50% Infectious Dose of Human Norovirus Cin-2 in Gnotobiotic Pigs: A Comparison of Classical and Contemporary Methods for Endpoint Estimation

Viruses ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 955
Author(s):  
Ashwin K. Ramesh ◽  
Viviana Parreño ◽  
Philip J. Schmidt ◽  
Shaohua Lei ◽  
Weiming Zhong ◽  
...  
Keyword(s):  
Dose Response ◽  
Response Models ◽  
Infectious Dose ◽  
Clinical Data Analysis ◽  
Causative Agents ◽  
Gnotobiotic Pigs ◽  
Gnotobiotic Pig ◽  
Response Modelling ◽  
Sporadic Acute Gastroenteritis ◽  
Endpoint Estimation

Human noroviruses (HuNoVs) are the leading causative agents of epidemic and sporadic acute gastroenteritis that affect people of all ages worldwide. However, very few dose–response studies have been carried out to determine the median infectious dose of HuNoVs. In this study, we evaluated the median infectious dose (ID50) and diarrhea dose (DD50) of the GII.4/2003 variant of HuNoV (Cin-2) in the gnotobiotic pig model of HuNoV infection and disease. Using various mathematical approaches (Reed–Muench, Dragstedt–Behrens, Spearman–Karber, logistic regression, and exponential and approximate beta-Poisson dose–response models), we estimated the ID50 and DD50 to be between 2400–3400 RNA copies, and 21,000–38,000 RNA copies, respectively. Contemporary dose–response models offer greater flexibility and accuracy in estimating ID50. In contrast to classical methods of endpoint estimation, dose–response modelling allows seamless analyses of data that may include inconsistent dilution factors between doses or numbers of subjects per dose group, or small numbers of subjects. Although this investigation is consistent with state-of-the-art ID50 determinations and offers an advancement in clinical data analysis, it is important to underscore that such analyses remain confounded by pathogen aggregation. Regardless, challenging virus strain ID50 determination is crucial for identifying the true infectiousness of HuNoVs and for the accurate evaluation of protective efficacies in pre-clinical studies of therapeutics, vaccines and other prophylactics using this reliable animal model.

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