Scientific Paper Summary
Citation: Feng Cheng et al, (2011). In vitro transcriptomic prediction of hepatotoxicity for early drug discovery. J Theor Biol. 2011 December 7; 290: 27–36.
Statistical Tool: Two-Sample T-Test
Specific Hypothesis (null hypothesis): Multi-gene model is capable of distinguishing between different doses of the same compounds, toxic, and non-toxic compounds.
Summary: this article focuses on the examination of the effectiveness of multi-gene model in distinguishing different doses, toxic, and non-toxic compounds (Feng Cheng et al, 2011).
Results: the results in relation to this experiment indicate that the multi-gene model has the ability to distinguish between the doses of the same compounds. It also has the ability to evaluate differences between the toxic and non-toxic compounds. Figure 4 focuses on the illustration of high correlation between predicted scores and the context of the experimental ALT levels with reference to the independent set Rat2 (Feng Cheng et al, 2011). Figure 5 focuses on the illustration of projection or prediction of in vitro data sets in relation to Human1 and Human2 (Feng Cheng et al, 2011).
Conclusion: the article concludes that in vitro derived models are efficient in the prediction of the drug hepatotoxicity focusing on in vivo animals and in vitro liver cells (Feng Cheng et al, 2011). It is also essential to note the model was efficient in stratifying rat and human liver cells under the influence of liver toxicity compounds (Feng Cheng et al, 2011).
Critique: this article is readable because of clarity and precise in the presentation of the main points. The authors implement technique, methods, and processes in relation to the collection and analysis of data.
Response
I agree with the author in identification of the main points of the article in order to develop an effective and appropriate summary. The author organizes the presentation adequately thus making it easier to grasp the main points in relation to specific hypothesis, results, and components of the research article. I also agree with the author on identification of the right statistical tool in the evaluation of the data for the realization of quality and efficient research with reference to the specific hypothesis.
