METHODS: Pooled urine samples of patients with BTG (n=10), patients with PTC (n=9) and healthy controls (n=10) were subjected to iTRAQ analysis and immunoblotting.
RESULTS: The ITRAQ analysis of the urine samples detected 646 proteins, 18 of which showed significant altered levels (p<0.01; fold-change>1.5) between patients and controls. Whilst four urinary proteins were commonly altered in both BTG and PTC patients, 14 were unique to either BTG or PTC. Amongst these, four proteins were further chosen for validation using immunoblotting, and the enhanced levels of osteopontin in BTG patients and increased levels of a truncated gelsolin fragment in PTC patients, relative to controls, appeared to corroborate the findings of the iTRAQ analysis.
CONCLUSION: The data of the present study is suggestive of the potential application of urinary osteopontin and gelsolin to discriminate patients with BTG from those with PTC non-invasively. However, this needs to be further validated in studies of individual urine samples.
METHODS: Cross-sectional study of 231 market workers and food handlers in wet markets and food premises from two localities in central Malaysia. Respondents' background information was obtained using a questionnaire. Serum samples were tested for leptospiral antibodies using ELISA and microscopic agglutination test (MAT).
RESULTS: Seroprevalence of leptospirosis among healthy workers was 46.3%. Detection of seropositivity was higher by MAT (46%) than ELISA (15%). We observed high seropositivity among local workers (49%), food handlers (49.5%), females (60.8%) and those aged 34 years and older (46.3%). Local strain LEP175 was the predominant serovar, followed by WHO strain Patoc.
CONCLUSION: Overall seroprevalence among healthy food handlers and market workers was high in this study. The workplace places susceptible individuals at risk of leptospirosis.
STUDY DESIGN: The present study was conducted on 151 women with gynecological cancers as the case group and 152 healthy women with no history of such cancers as control group. The dematographic details of participants from both control and case groups were collected using a checklist, and the pattern of their fingerprints was prepared and examined. The data were analyzed for their significance using chi-square test and t- test. Odds ratio with 95% confidence intervals were calculated.
RESULTS: Dermatoglyphic analysis showed that arch and loop patterns significantly changed in cases group as compared to control. However, the odds ratio suggested that loop pattern in 6 or more fingers might be a risk factor for developing gynecological cancers.
CONCLUSION: Our results showed that there is an association between fingerprint patterns and gynecological cancers and so, dermatoglyphic analysis may aid in the early diagnosis of these cancers.