MATERIALS AND METHODS: This was an investigator-initiated, single-center, randomized, controlled, clinical trial in patients with T2DM and DKD, comparing 12-weeks of low carbohydrate diet (<20g daily intake) versus standard low protein (0.8g/kg/day) and low salt diet. Patients in the VLCBD group underwent 2-weekly monitoring including their 3-day food diaries. In addition, Dual-energy x-ray absorptiometry (DEXA) was performed to estimate body fat percentages.
RESULTS: The study population (n = 30) had a median age of 57 years old and a BMI of 30.68kg/m2. Both groups showed similar total calorie intake, i.e. 739.33 (IQR288.48) vs 789.92 (IQR522.4) kcal, by the end of the study. The VLCBD group showed significantly lower daily carbohydrate intake 27 (IQR25) g vs 89.33 (IQR77.4) g, p<0.001, significantly higher protein intake per day 44.08 (IQR21.98) g vs 29.63 (IQR16.35) g, p<0.05 and no difference in in daily fat intake. Both groups showed no worsening of serum creatinine at study end, with consistent declines in HbA1c (1.3(1.1) vs 0.7(1.25) %) and fasting blood glucose (1.5(3.37) vs 1.3(5.7) mmol/L). The VLCBD group showed significant reductions in total daily insulin dose (39(22) vs 0 IU, p<0.001), increased LDL-C and HDL-C, decline in IL-6 levels; with contrasting results in the control group. This was associated with significant weight reduction (-4.0(3.9) vs 0.2(4.2) kg, p = <0.001) and improvements in body fat percentages. WC was significantly reduced in the VLCBD group, even after adjustments to age, HbA1c, weight and creatinine changes. Both dietary interventions were well received with no reported adverse events.
CONCLUSION: This study demonstrated that dietary intervention of very low carbohydrate diet in patients with underlying diabetic kidney disease was safe and associated with significant improvements in glycemic control, anthropometric measurements including weight, abdominal adiposity and IL-6. Renal outcomes remained unchanged. These findings would strengthen the importance of this dietary intervention as part of the management of patients with diabetic kidney disease.
METHODS: Over six months in 2018, we recruited 368 adults who met the WHO 2009 criteria for probable dengue infection. They underwent the following blood tests: full blood count, dengue virus (DENV) rapid diagnostic test (RDT), ELISA (dengue IgM and IgG), nested RT-PCR for dengue, multiplex qRT-PCR for Zika, Chikungunya and dengue as well as PCR tests for Leptopspira spp., Japanese encephalitis and West Nile virus.
RESULTS: Laboratory-confirmed dengue infections (defined by positive tests in NS1, IgM, high-titre IgG or nested RT-PCR) were found in 167 (45.4%) patients. Of these 167 dengue patients, only 104 (62.3%) were positive on rapid diagnostic testing. Dengue infection was significantly associated with the following features: family or neighbours with dengue in the past week (AOR: 3.59, 95% CI:2.14-6.00, p<0.001), cutaneous rash (AOR: 3.58, 95% CI:1.77-7.23, p<0.001), increased temperature (AOR: 1.33, 95% CI:1.04-1.70, p = 0.021), leucopenia (white cell count < 4,000/μL) (AOR: 3.44, 95% CI:1.72-6.89, p<0.001) and thrombocytopenia (platelet count <150,000/μL)(AOR: 4.63, 95% CI:2.33-9.21, p<0.001). Dengue infection was negatively associated with runny nose (AOR: 0.47, 95% CI:0.29-0.78, p = 0.003) and arthralgia (AOR: 0.42, 95% CI:0.24-0.75, p = 0.004). Serotyping by nested RT-PCR revealed mostly mono-infections with DENV-2 (n = 64), DENV-1 (n = 32) and DENV-3 (n = 17); 14 co-infections occurred with DENV-1/DENV-2 (n = 13) and DENV-1/DENV-4 (n = 1). Besides dengue, none of the pathogens above were found in patients' serum.
CONCLUSIONS: Acute undifferentiated febrile infections are a diagnostic challenge for community-based clinicians. Rapid diagnostic tests are increasingly used to diagnose dengue infection but negative tests should be interpreted with caution as they fail to detect a considerable proportion of dengue infection. Certain clinical features and haematological parameters are important in the clinical diagnosis of dengue infection.
METHODS: A sample of 3895 individuals without known diabetes underwent detailed interview and health examination, including anthropometric and biochemical evaluation, between 2004 and 2007. Pearson's correlation, analysis of variance and multiple linear regression analyses were used to examine the influence of ethnicity on HbA(1c) .
RESULTS: As fasting plasma glucose increased, HbA(1c) increased more in Malays and Indians compared with Chinese after adjustment for age, gender, waist circumference, serum cholesterol, serum triglyceride and homeostasis model assessment of insulin resistance (P-interaction < 0.001). This translates to an HbA(1c) difference of 1.1 mmol/mol (0.1%, Indians vs. Chinese), and 0.9 mmol/mol (0.08%, Malays vs. Chinese) at fasting plasma glucose 5.6 mmol/l (the American Diabetes Association criterion for impaired fasting glycaemia); and 2.1 mmol/mol (0.19%, Indians vs. Chinese) and 2.6 mmol/mol (0.24%, Malays vs. Chinese) at fasting plasma glucose 7.0 mmol/l, the diagnostic criterion for diabetes mellitus.
CONCLUSIONS: Using HbA(1c) in place of fasting plasma glucose will reclassify different proportions of the population in different ethnic groups. This may have implications in interpretation of HbA(1c) results across ethnic groups and the use of HbA(1c) for diagnosing diabetes mellitus.
METHOD: One hundred and twenty male C57BL/6 inbred mice were divided into three age groups: young (6 months old), middle-aged (12 months old), and old (18 months old). Each age group consisted of two control groups (distilled water and olive oil) and three treatment groups: Piper betle (50 mg/kg body weight), tocotrienol-rich fraction (30 mg/kg), and Chlorella vulgaris (50 mg/kg). The duration of treatment for all three age groups was two months. Blood was withdrawn from the orbital sinus to determine the antioxidant enzyme activity and the malondialdehyde level.
RESULTS: Piper betle increased the activities of catalase, glutathione peroxidase, and superoxide dismutase in the young, middle, and old age groups, respectively, when compared to control. The tocotrienol-rich fraction decreased the superoxide dismutase activity in the middle and the old age groups but had no effect on catalase or glutathione peroxidase activity for all age groups. Chlorella vulgaris had no effect on superoxide dismutase activity for all age groups but increased glutathione peroxidase and decreased catalase activity in the middle and the young age groups, respectively. Chlorella vulgaris reduced lipid peroxidation (malondialdehyde levels) in all age groups, but no significant changes were observed with the tocotrienol-rich fraction and the Piper betle treatments.
CONCLUSION: We found equivocal age-related changes in erythrocyte antioxidant enzyme activity when mice were treated with Piper betle, the tocotrienol-rich fraction, and Chlorella vulgaris. However, Piper betle treatment showed increased antioxidant enzymes activity during aging.
METHODS: This hospital based case control study conducted in the Western part of Nepal covered a total of 93 cancer patients with or without alcohol intake and smoking habits, along with 94 age, sex and habit-matched individuals serving as controls. Plasma thiobarbituric acid reacting substances (TBARS), total antioxidant activity (TAA), vitamin C, α-tocopherol and erythrocyte reduced glutathione (GSH) were estimated and compared.
RESULTS: The TBARS level was found to be significantly higher (p≤0.001) in all types of cancer patients when compared to controls, being aggravated in alcoholics with a smoking habit. No statistical significance (p≥0.05) was observed in the level of vitamin C and α-tocopherol. GSH and TAA level were significantly decreased (p≤0.001) in all the groups except those who consumed both branded as well as homemade alcohol and non-alcoholics without smoking habit.
CONCLUSION: Alcohol, irrespective of its commercial brand, increases oxidative stress in all types of cancer patients. This is even higher when alcohol intake is combined with a smoking habit. Decreased TAA and GSH are major risk factors for cancer development.