METHODOLOGY: The literatures published after April, 2015 up to December, 2016 on k13 mutant alleles for artemisinin resistance in Plasmodium falciparum and relevant literatures were comprehensively reviewed.
RESULTS: To date, 13 non-synonymous mutations of k13 gene have been observed to have slow parasite clearance. Worldwide mapping of k13 mutant alleles have shown mutants associated with artemisinin resistance were confined to southeast Asia and China and did not invade to African countries. Although in vitro ring stage survival assay of 0-3 h was a recently developed assay, it was useful for rapid detection of artemisinin resistance associated k13 allelic marker in the parasite. Recently, dissemination of k13 mutant alleles was recommended to be investigated by identity of haplotypes. Significant characteristics of well described alleles in the reports were mentioned in this review for the benefit of future studies.
CONCLUSION: According to the updates in the review, it can be concluded artemisinin resistance does not disseminate to India and African countries within short period whereas regular tracking of these mutants is necessary.
METHODOLOGY: Literatures on RIF resistant mutations published between 2010 and 2016 were thoroughly reviewed.
RESULTS: The most commonly mutated codons in RRDR of rpoB gene are 531, 526 and 516. The possibilities of absence of mutation in RRDR of rpoB gene in MDR-TB isolates in few studies was due to existence of other rare rpoB mutations outside RRDR or different mechanism of rifampicin resistance.
CONCLUSION: Molecular methods which can identify extensive mutations associated with multiple anti-tuberculous drugs are in urgent need so that the research on drug resistant mutations should be extended.
PURPOSE: The purpose of this study is to investigate the genetic diversity of V.cholerae in Sabah and whether V.cholerae in Sabah belong to atypical El Tor biotype.
METHODS: ERIC-PCR, a DNA fingerprinting method for bacterial pathogens based on the enterobacterial repetitive intergenic consensus sequence, was used to study the genetic diversity of 65 clinical V.cholerae O1 isolates from 3 districts (Kudat, Beluran, Sandakan) in Sabah and one environmental isolate from coastal sea water in Kudat district. In addition, we studied the biotype-specific genetic traits in these isolates to establish their biotype.
RESULTS: Different fingerprint patterns were seen in isolates from these three districts but one of the patterns was seen in more than one district. Clinical isolates and environmental isolate have different patterns. In addition, Sabah isolates harbor genetic traits specific to both classical biotype (ctxB-1, rstRCla) and El Tor biotype (rstRET, rstC, tcpAET, rtxC, VC2346).
CONCLUSION: This study revealed that V.cholerae in Sabah were genetically diverse and were atypical El Tor strains. Fingerprint patterns of these isolates will be useful in tracing the origin of this pathogen in the future.
OBJECTIVE: To assess the association of premenopausal and postmenopausal breast cancer risk with fat and fat subtypes intake.
METHODOLOGY: This is a population based case-control study conducted in Kuala Lumpur, Malaysia from January 2006 to December 2007. Food intake pattern was collected from 382 breast cancer patients and 382 control group via an interviewer-administered food frequency questionnaire. Logistic regression was used to compute odds ratios (OR) with 95% confidence intervals (CI) and a broad range of potential confounders was included in analysis.
RESULTS: This study showed that both premenopausal and postmenopausal breast cancer risk did not increase significantly with greater intake of total fat [quartile (Q) 4 versus Q1 OR=0.76, 95% CI, 0.23-2.45 and OR=1.36, 95% CI, 0.30-3.12], saturated fat (ORQ4 to Q1=1.43, 95% CI, 0.51-3.98 and ORQ4 to Q1=1.75, 95% CI, 0.62-3.40), monounsaturated fat (ORQ4 to Q1=0.96, 95% CI, 0.34-1.72 and ORQ4 to Q1=1.74, 95% CI, 0.22-2.79), polyunsaturated fat (ORQ4 to Q1=0.64, 95% CI, 0.23-1.73 and ORQ4 to Q1=0.74, 95% CI, 0.39-1.81), n-3 polyunsaturated fat (ORQ4 to Q1=1.10, 95% CI, 0.49-2.48 and ORQ4 to Q1=0.78, 95% CI, 0.28-2.18), n-6 polyunsaturated fat (ORQ4 to Q1=0.67, 95% CI, 0.24-1.84 and ORQ4 to Q1=0.71, 95% CI, 0.29-1.04) or energy intake (ORQ4 to Q1=1.52, 95% CI, 0.68-3.38 and ORQ4 to Q1=2.21, 95% CI, 0.93-3.36).
CONCLUSION: Total fat and fat subtypes were not associated with pre- and postmenopausal breast cancer risk after controlling for age, other breast cancer risk factors and energy intake. Despite the lack of association, the effects of total fat and fat subtypes intake during premenopausal years towards postmenopausal breast cancer risk still warrant investigation.
METHODS: A retrospective cohort study was conducted at six tertiary centers in Malaysia. All women with newly diagnosed breast cancer were interviewed, and a medical records review was conducted using a structured questionnaire. The BCC timeliness framework showed that the total time between a woman discovering their first breast changes and the date of initial treatment was divided into three distinct intervals: presentation interval, diagnostic interval, and treatment interval. Four diagnosis subintervals, referral, biopsy, report, and diagnosis resolution intervals, were also looked into.
RESULTS: The BCC timeliness framework was used to capture important time points. The median total time, presentation interval, diagnostic interval, and treatment interval were 4.9 months (range, 1 month to 10 years), 2.4 months (range, 7 days to 10 years), 26 days (range, 4 days to 9.3 months), and 21 days (range, 1 day to 7.2 months), respectively. Meanwhile, the median time for the diagnosis subinterval of referral, biopsy, report, and diagnosis resolution was 8 days (range, 0 day to 8 months), 0 day (range, 0 day to 20 days), 7 days (range, 3 days to 3.5 months), and 4 days (range, 1 day to 1.8 months), respectively.
CONCLUSION: The BCC timeliness framework is based on the current sequenced trajectory of the BCC journey. Clarity in the measurement of timeliness provides a standardized language for monitoring and outcome research. It can serve as a quality indicator for community and hospital-based breast cancer programs.