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- Bygdell, Maria, et al.
(författare)
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Psychiatric adverse drug reactions reported during a 10-year period in the Swedish pediatric population.
- 2012
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Ingår i: Pharmacoepidemiology and drug safety. - : Wiley. - 1099-1557 .- 1053-8569. ; 21:1, s. 79-86
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Tidskriftsartikel (refereegranskat)abstract
- Purpose Psychiatric Adverse Drug Reactions (ADRs) are frequent in the pediatric population. The aim of the present study was to analyze spontaneously reported psychiatric ADRs in children during a 10-year period. Methods All spontaneously reported Individual Case Safety Reports (ICSRs) concerning children (<18 years old) and psychiatric adverse reactions assessed as at least possible, registered in the Swedish Drug Information System (SWEDIS) during the period 2001–2010, were extracted and characterized. Age and sex distribution and labeling/registration status were studied. Results A total of 600 ICSRs concerning 744 psychiatric adverse reactions were identified and included in the analysis. Boys were overrepresented among included ICSRs (60.3% vs. 39.7%; p < .001). After exclusion of vaccines, the three most frequently suspected drugs were montelukast, centrally working sympathomimetic drugs, and inhaled glucocorticoids. Serious adverse reactions were reported more frequently for drugs used off-label than for drugs used according to the Swedish Physician’s Desk Reference. Aggressiveness was reported more frequently for boys than for girls as were suicidal conditions. Conclusions Psychiatric ADRs in the pediatric population have been reported for a wide range of reactions and drugs and display age and sex differences including a higher number of suicidal reactions in boys. An association was seen between serious reactions and off-label drug use. Further studies are needed to elucidate safety aspects of unlicensed drugs and drugs used off-label and whether there are differences in children’s susceptibility to develop ADRs.
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| 2. |
- Srivastava, Vaibhav, et al.
(författare)
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OnPLS integration of transcriptomic, proteomic and metabolomic data shows multi-level oxidative stress responses in the cambium of transgenic hipI- superoxide dismutase Populus plants
- 2013
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Ingår i: BMC Genomics. - : BioMed Central. - 1471-2164. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Reactive oxygen species (ROS) are involved in the regulation of diverse physiological processes in plants, including various biotic and abiotic stress responses. Thus, oxidative stress tolerance mechanisms in plants are complex, and diverse responses at multiple levels need to be characterized in order to understand them. Here we present system responses to oxidative stress in Populus by integrating data from analyses of the cambial region of wild-type controls and plants expressing high-isoelectric-point superoxide dismutase (hipI-SOD) transcripts in antisense orientation showing a higher production of superoxide. The cambium, a thin cell layer, generates cells that differentiate to form either phloem or xylem and is hypothesized to be a major reason for phenotypic perturbations in the transgenic plants. Data from multiple platforms including transcriptomics (microarray analysis), proteomics (UPLC/QTOF-MS), and metabolomics (GC-TOF/MS, UPLC/MS, and UHPLC-LTQ/MS) were integrated using the most recent development of orthogonal projections to latent structures called OnPLS. OnPLS is a symmetrical multi-block method that does not depend on the order of analysis when more than two blocks are analysed. Significantly affected genes, proteins and metabolites were then visualized in painted pathway diagrams.RESULTS: The main categories that appear to be significantly influenced in the transgenic plants were pathways related to redox regulation, carbon metabolism and protein degradation, e.g. the glycolysis and pentose phosphate pathways (PPP). The results provide system-level information on ROS metabolism and responses to oxidative stress, and indicate that some initial responses to oxidative stress may share common pathways.CONCLUSION: The proposed data evaluation strategy shows an efficient way of compiling complex, multi-platform datasets to obtain significant biological information.
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