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Toxicology aims to comprehend and envisage the adverse outcomes of chemicals and xenobiotics on the biological system. Predicting toxicity on the biological system is a complex and immense process. In-vivo, in-vitro, pre-, clinical and –omics level experimental approaches have been utilized to describe the toxicological impact of these chemicals and this has generated a vast wealth of data. Hence, there now exist a need for a system that can interrelate and provide accurate and robust extrapolation of these data across various systems. Therefore, it is essential to re-shift our notion from empirical, animal-based testing to a mechanistic understanding. Systems biology is one such system that can extrapolate and interrelate these vast biological system data. Systems biology is a computational and mathematical modelling approach developed to understand interrelationships between networks of biological systems. The use of systems biology to answer toxicology-related questions is termed as systems toxicology. In this review we will look at the standard and classical toxicology experimentations and how we can use mechanistic data (systems biology) to answer toxicology-related questions using systems toxicology and what are the future opportunities in systems toxicology. The advancement of systems toxicology heralds new dawn of technologies that will aid in our quest to better comprehend and envisage the adverse outcomes of chemicals and xenobiotics on the biological system.

Background: This study was undertaken to evaluate Staphylococcus aureus carriage and persistence in health sciences students at the Faculty of Medicine and Health Sciences, Universiti Putra Malaysia. Methods: Consent form and self-administered questionnaires on socio-demographics, hygienic practices, medical and medication history were distributed followed by nasal swab collection; sampling was done twice in one month interval in October and November 2013. Bacterial identification followed the standard phenotypic methods. Antibiotic susceptibility of isolates against oxacillin and cefoxitin was tested by disc diffusion method. Methicillin resistance determinant gene (mecA) was detected through polymerase chain reaction-assay. Results: S. aureus was isolated from 31.3% (60/192) and 33.3% (60/180) of the student population during the first and second sampling respectively. Among the S. aureus-positive participants, about 65% of them were persistent carrier (S. aureus was detected during both sampling exercises). Six methicillin-resistant S. aureus (MRSA) were detected (four and two isolates in the two sampling events respectively) as inferred by decreased susceptibility to oxacillin and cefoxitin and presence of mecA gene; two of the strains were from a single individual. Fisher’s exact test showed no significant correlation between carriage and the tested risk factors except for the habit of touching nose and chronic illnesses (P < 0.05), with a higher incidence of S. aureus among those associated with the two risk factors. Conclusions: As far as the limited sampling period is concerned, these findings indicate that a proportion of the student population may be at infection risk. Avoiding frequent nose-touching could be one of the preventive measures. Keywords: Staphylococcus aureus, Infection risk, Nasal carriage, MRSA