METHOD: A total of 140 urine samples were collected from trapped rats. These samples were cultured in EMJH enriched media and 18 of these samples (12.9%) were found to be positive when observed under x40 by dark field microscope. Genomic DNA was extracted from all the 18 native isolates for PCR.
RESULT: All the 18 isolates generated the expected 786 base pair band when the set of primers known to amplify LipL32 gene were utilized. These results showed that the primers were suitable to be used for the identification of pathogenic leptospira from the 18 rat samples.
CONCLUSION: The sequencing of the PCR products and BLAST analysis performed on each representative isolates confirmed the pathogenic status of all these native isolates as the LipL32 gene was detected in all the Leptospira isolates. This indicates that the rats are carriers of the pathogenic leptospira in the study area, and therefore are of public health importance.
Methods: This case-control study was carried out on 113 patients with PV and 100 healthy controls. Total cholesterol, high-density lipoprotein (HDL) and triglycerides (TG) levels were measured and low-density lipoprotein (LDL), non-HDL cholesterol (non-HDL-C) and atherogenic index of plasma (AIP) were calculated. Chi-squared test and independent Student t-test (or their alternatives) were used for group comparison.
Results: The mean age and BMI of patients and controls were 47.7 ± 14.5 and 28 ± 6.2 and, 44.5 ± 18.5 and 25.5 ± 5.1, respectively. Total cholesterol, LDL, HDL, non-HDL-C and TG were statistically different between the two groups (P values < 0.001; < 0.001; < 0.001; < 0.001 and 0.021, respectively). However, AIP was not significantly different (P-value = 0.752).
Conclusion: The serum lipid profile was significantly higher in PV patients compared to healthy controls. Therefore, PV patients may be more prone to develop atherosclerosis and this finding can be important in the overall management of these patients.
Objective: This review aims to summarize the clinical evidence regarding the use of chia seed for a wide variety of health conditions.
Data Sources: A number of databases, including PubMed and Embase, were searched systematically.
Study Selection: Randomized controlled trials that assessed the clinical effects of chia seed consumption in human participants were included. The quality of trials was assessed using the Cochrane Risk of Bias Tool.
Data Extraction: Data on study design, blinding status, characteristics of participants, chia seed intervention, comparator, clinical assessment, duration of intake, interval of assessment, and study funding status were extracted. Meta-analysis was performed.
Results: Twelve trials were included. Participants included healthy persons, athletes, diabetic patients, and individuals with metabolic syndrome. Pooling of results showed no significant differences except for the following findings of subgroup analysis at higher doses of chia seed: (1) lower postprandial blood glucose level (mean difference [MD] of -33.95 incremental area under the curve [iAUC] [mmol/L × 2 h] [95%CI, -61.85, -6.05] and -51.60 iAUC [mmol/L × 2 h] [95%CI, -79.64, -23.56] at medium doses and high doses, respectively); (2) lower high-density lipoprotein in serum (MD of -0.10 mmol/L [95%CI, -0.20, -0.01]); and (3) lower diastolic blood pressure (MD of -7.14 mmHg [95%CI, -11.08, -3.19]). The quality of all evidence assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was low or very low. All trials employed only surrogate markers as outcomes.
Conclusions: Future trials with improved methodological quality, well-described clinical events, and validated surrogate markers as outcomes are needed to support the potential health benefits of chia seed consumption.
Systematic Review Registration: PROSPERO registration no. CRD42015029990.
MATERIALS AND METHODS: This cross-sectional study included 150 subjects aged 30 years and above who attended a health screening in a Malaysian tertiary institution. Sociodemographics, clinical characteristics and laboratory parameters (lipids, glucose, and sdLDL) were obtained. Lipoprotein subfraction was analysed using the polyacrylamide gel electrophoresis method.
RESULTS: Malays and females made up the majority of subjects and the median age was 37 years. Normolipidaemic Pattern B was significantly higher in women (p=0.008). Significant independent predictors of Pattern B were gender (p=0.02), race (p=0.01), body mass index (BMI) [p=0.02] and lipid status (p=0.01). Triglyceride was the only independent predictor of sdLDL (p=0.001).
CONCLUSION: The prevalence of Pattern B of 33% in this study was comparatively high, of which 6.7% were normolipidaemic. Chinese males with dyslipidaemia and increased BMI independently predicted Pattern B. Differences in triglyceride levels alone among these ethnic groups do not fully explain the differences in the prevalence of Pattern B although it was the only lipid parameter to independently predict sdLDL. Individuals with atherogenic normolipidaemia are at greater risk for a CVD event as they are not included in the protective measures of primary CVD prevention.