Joint action of chemicals in algal toxicity tests: Influence of response level and dose-response regression model

2001 ◽  
Vol 20 (10) ◽  
pp. 2361-2369
Author(s):  
Erik R. Christensen ◽  
Dongxu Chen ◽  
Niels Nyholm ◽  
K. Ole Kusk
Keyword(s):  
Regression Model ◽  
Dose Response ◽  
Joint Action ◽  
Toxicity Tests ◽  
Response Level ◽  
Algal Toxicity

Testing for Trends in Dose-Response Microarray Experiments: A Comparison of Several Testing Procedures, Multiplicity and Resampling-Based Inference

2007 ◽  
Vol 6 (1) ◽  
Author(s):  
Dan Lin ◽  
Ziv Shkedy ◽  
Dani Yekutieli ◽  
Tomasz Burzykowski ◽  
Hinrich W.H. Göhlmann ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dose Response ◽  
Multiple Testing ◽  
Pharmaceutical Research ◽  
Ratio Test ◽  
Familywise Error Rate ◽  
Response Level ◽  
Data Set ◽  
Monotonic Trend ◽  
Testing Procedures

Dose-response studies are commonly used in experiments in pharmaceutical research in order to investigate the dependence of the response on dose, i.e., a trend of the response level toxicity with respect to dose. In this paper we focus on dose-response experiments within a microarray setting in which several microarrays are available for a sequence of increasing dose levels. A gene is called differentially expressed if there is a monotonic trend (with respect to dose) in the gene expression. We review several testing procedures which can be used in order to test equality among the gene expression means against ordered alternatives with respect to dose, namely Williams' (Williams 1971 and 1972), Marcus' (Marcus 1976), global likelihood ratio test (Bartholomew 1961, Barlow et al. 1972, and Robertson et al. 1988), and M (Hu et al. 2005) statistics. Additionally we introduce a modification to the standard error of the M statistic. We compare the performance of these five test statistics. Moreover, we discuss the issue of one-sided versus two-sided testing procedures. False Discovery Rate (Benjamni and Hochberg 1995, Ge et al. 2003), and resampling-based Familywise Error Rate (Westfall and Young 1993) are used to handle the multiple testing issue. The methods above are applied to a data set with 4 doses (3 arrays per dose) and 16,998 genes. Results on the number of significant genes from each statistic are discussed. A simulation study is conducted to investigate the power of each statistic. A R library IsoGene implementing the methods is available from the first author.

MINUTOCELLUS POLYMORPHUS: A NEW MARINE DIATOM FOR USE IN ALGAL TOXICITY TESTS - Short Communication

1988 ◽  
Vol 7 (11) ◽  
pp. 925 ◽  
Author(s):  
Gerald E. Walsh ◽  
Leslie L. McLaughlin ◽  
Mark J. Yoder ◽  
Paul H. Moody ◽  
Emile M. Lores ◽  
...  
Keyword(s):  
Short Communication ◽  
Marine Diatom ◽  
Toxicity Tests ◽  
Algal Toxicity ◽  
Minutocellus Polymorphus

Minutocellus polymorphus: A new marine diatom for use in algal toxicity tests

1988 ◽  
Vol 7 (11) ◽  
pp. 925-929 ◽  
Author(s):  
Gerald E. Walsh ◽  
Leslie L. McLaughlin ◽  
Mark J. Yoder ◽  
Paul H. Moody ◽  
Emile M. Lores ◽  
...  
Keyword(s):  
Marine Diatom ◽  
Toxicity Tests ◽  
Algal Toxicity ◽  
Minutocellus Polymorphus

scholarly journals A regularized functional regression model enabling transcriptome-wide dosage-dependent association study of cancer drug response

2020 ◽  
Author(s):  
Evanthia Koukouli ◽  
Dennis Wang ◽  
Frank Dondelinger ◽  
Juhyun Park
Keyword(s):  
Gene Expression ◽  
Regression Model ◽  
Cell Line ◽  
Cell Lines ◽  
Dose Response ◽  
Drug Response ◽  
Drug Sensitivity ◽  
Cancer Drug ◽  
Functional Regression ◽  
Response Curves

AbstractCancer treatments can be highly toxic and frequently only a subset of the patient population will benefit from a given treatment. Tumour genetic makeup plays an important role in cancer drug sensitivity. We suspect that gene expression markers could be used as a decision aid for treatment selection or dosage tuning. Using in vitro cancer cell line dose-response and gene expression data from the Genomics of Drug Sensitivity in Cancer (GDSC) project, we build a dose-varying regression model. Unlike existing approaches, this allows us to estimate dosage-dependent associations with gene expression. We include the transcriptomic profiles as dose-invariant covariates into the regression model and assume that their effect varies smoothly over the dosage levels. A two-stage variable selection algorithm (variable screening followed by penalised regression) is used to identify genetic factors that are associated with drug response over the varying dosages. We evaluate the effectiveness of our method using simulation studies focusing on the choice of tuning parameters and cross-validation for predictive accuracy assessment. We further apply the model to data from five BRAF targeted compounds applied to different cancer cell lines under different dosage levels. We highlight the dosage-dependent dynamics of the associations between the selected genes and drug response, and we perform pathway enrichment analysis to show that the selected genes play an important role in pathways related to tumourgenesis and DNA damage response.Author SummaryTumour cell lines allow scientists to test anticancer drugs in a laboratory environment. Cells are exposed to the drug in increasing concentrations, and the drug response, or amount of surviving cells, is measured. Generally, drug response is summarized via a single number such as the concentration at which 50% of the cells have died (IC50). To avoid relying on such summary measures, we adopted a functional regression approach that takes the dose-response curves as inputs, and uses them to find biomarkers of drug response. One major advantage of our approach is that it describes how the effect of a biomarker on the drug response changes with the drug dosage. This is useful for determining optimal treatment dosages and predicting drug response curves for unseen drug-cell line combinations. Our method scales to large numbers of biomarkers by using regularisation and, in contrast with existing literature, selects the most informative genes by accounting for drug response at untested dosages. We demonstrate its value using data from the Genomics of Drug Sensitivity in Cancer project to identify genes whose expression is associated with drug response. We show that the selected genes recapitulate prior biological knowledge, and belong to known cancer pathways.

scholarly journals Analysis of a dose-response assay in Scaptotrigona bipunctata bees, Lepeletier, 1836 (Hymenoptera: Apidae) using the logistic regression model under the Bayesian approach

2021 ◽  
Vol 43 ◽  
pp. e57781
Author(s):  
Breno Gabriel da Silva ◽  
Paula Ribeiro Santos ◽  
Cristian Marcelo Villegas Lobos ◽  
Tamiris de Oliveira Diniz ◽  
Naiara Climas Pereira ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Bayesian Approach ◽  
Dose Response ◽  
Lead Time ◽  
Logistic Regression Model ◽  
Prior Information ◽  
Alternative Approach ◽  
Dose Response Study ◽  
The Bayesian Approach

This paper shows the results of a dose-response study in Scaptotrigona bipunctata bees, Lepeletier, 1836 (Hymenoptera: Apidae) exposed to the insecticide Fastac Duo. The aim was to evaluate the lethal concentration that causes the death of 50% of bees (LC50) and investigate the odd of mortality after exposure to different concentrations, using the logistic regression model under the Bayesian approach. In this approach, it is possible to incorporate a prior information and gives more accurate inferential results. Three independent dose-response experiments were analyzed, dissimilar in their lead time according to guidelines from the Organisation for Economic Co-operation and Development (OECD), in which each assay contained four replicates at the concentration levels investigated, including control. Observing exposure to the agrochemical, it was identified that the higher the concentration, the greater the odd of mortality. Regarding the estimated lethal concentrations for each experiment, the following values were found, 0.03 g a.i. L-1, for 24 hours, 0.04 g a.i. L-1, for 48 hours and 0.06 g a.i. L-1 for 72 hours, showing that in experiments with longer exposure times there was an increase in LC50. Concluding, the study showed an alternative approach to classical methods for dose-response studies in Scaptotrigona bipunctata bees exposed to the insecticide Fastac Duo.

Estimating low-toxic-effect concentrations in closed-system algal toxicity tests

2009 ◽  
Vol 72 (5) ◽  
pp. 1514-1522 ◽  
Author(s):  
Chung Yuan Chen ◽  
Yun Ju Wang ◽  
Chao Fen Yang
Keyword(s):  
Toxic Effect ◽  
Closed System ◽  
Toxicity Tests ◽  
Algal Toxicity ◽  
Low Toxic
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