METHODS: A randomized control trial was conducted among 2120 cancer patients from April 2016 to January 2017 in ten selected government hospitals in Peninsular Malaysia. Cancer patients were randomly assigned to intervention and control groups. The intervention group received chemotherapy counselling by pharmacists based on the "Managing Patients on Chemotherapy" module. The outcomes were assessed at baseline, 1st, 2nd and 3rd follow-ups after counselling. In the course of data analysis; independent sample t-test, chi-square and two-way repeated measures ANOVA were conducted.
RESULTS: Mean scores of self-esteem in the intervention group had significant difference in comparison with those of the control group in the 1st, 2nd and 3rd follow-ups after counselling (P
RESULTS: This work describes a computational methodology to achieve this analysis, with data of dengue, West Nile, hepatitis A, HIV-1, and influenza A viruses as examples. Our methodology has been implemented as an analytical pipeline that brings significant advancement to the field of reverse vaccinology, enabling systematic screening of known sequence data in nature for identification of vaccine targets. This includes key steps (i) comprehensive and extensive collection of sequence data of viral proteomes (the virome), (ii) data cleaning, (iii) large-scale sequence alignments, (iv) peptide entropy analysis, (v) intra- and inter-species variation analysis of conserved sequences, including human homology analysis, and (vi) functional and immunological relevance analysis.
CONCLUSION: These steps are combined into the pipeline ensuring that a more refined process, as compared to a simple evolutionary conservation analysis, will facilitate a better selection of vaccine targets and their prioritization for subsequent experimental validation.