BackgroundIncreasing evidence is demonstrating that a patient’s unique genetic profile can be used to detect the disease’s onset, prevent its progression, and optimize its treatment. This led to the increased global efforts to implement personalized medicine (PM) and pharmacogenomics (PG) in clinical practice. Here we investigated the perceptions of students from different universities in Bosnia and Herzegovina (BH) towards PG/PM as well as related ethical, legal, and social implications (ELSI). This descriptive, cross-sectional study is based on the survey of 559 students from the Faculties of Medicine, Pharmacy, Health Studies, Genetics, and Bioengineering and other study programs.ResultsOur results showed that 50% of students heard about personal genome testing companies and 69% consider having a genetic test done. A majority of students (57%) agreed that PM represents a promising healthcare model, and 40% of students agreed that their study program is well designed for understanding PG/PM. This latter opinion seems to be particularly influenced by the field of study (7.23, CI 1.99–26.2, p = 0.003). Students with this opinion are also more willing to continue their postgraduate education in the PM (OR = 4.68, CI 2.59–8.47, p < 0.001). Furthermore, 45% of students are aware of different ethical aspects of genetic testing, with most of them (46%) being concerned about the patient’s privacy.ConclusionsOur results indicate a positive attitude of biomedical students in Bosnia and Herzegovina towards genetic testing and personalized medicine. Importantly, our results emphasize the key importance of pharmacogenomic education for more efficient translation of precision medicine into clinical practice.Electronic supplementary materialThe online version of this article (10.1186/s40246-018-0182-2) contains supplementary material, which is available to authorized users.
A measurement of leaf area is apparently simple and fundamental. Various methods are available to measure leaf area. Available methods are time consuming, humdrum and laborious. Less expensive methods involving image processing based on video camera images and computer programs for analysis of these images have been alternative for all other techniques for leaf area assessment. In this paper we introduce a computer program that can calculate leaf area meter based on the pixel count in very short time and highly accurate by image processing. This program provides very fast, inexpensive and highly accurate measurement.
Experimental methods used for characterizing epitopes that play a vital role in the development of peptide vaccines, in diagnosis of diseases, and also for allergy research are time consuming and need There are many online epitope prediction tools that can help experimenters in short listing the candidate peptides. To predict B epitopes in an antigenic sequence, Jordan recurrent neural network (JRNN) are found to be more successful. To train and test neural networks, 262.583 B epitopes are retrieved from IEDB database. 99.9% of these epitopes have lengths in the interval 6-25 amino acids. For each of these lengths, committees of 11 expert recurrent neural networks are trained. To train these experts alongside epitopes, non needed. Non-epitopes are created as random sequences of amino acids of the same length followed by a filtering process. To distinguish epitopes and non-epitopes, the votes of eleven experts are aggrega vote. An overall accuracy of 97.23% is achieved. Then these experts are used to predict the linear b epitopes of antigen, ESAT6 (Tuberculosis).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.