METHOD: Blood samples were obtained from 20 healthy blood donors, 30 RA patients who presented with anaemia and 30 patients who had pure iron deficiency anaemia (IDA). The samples were analysed for full blood count, iron, ferritin, transferrin, soluble transferrin receptor and prohepcidin.
RESULTS: The mean prohepcidin level in the control subjects was 256 microg/L. The prohepcidin level was significantly lower in IDA patients (100 microg/L; p < 0.0001) but not significantly different from that of control in RA patients (250 microg/L; p > 0.05). Higher serum soluble transferrin receptor (sTfR) levels were observed in IDA (p < 0.0001) but not in RA compared with that of control (p > 0.05). RA patients were divided into iron depleted and iron repleted subgroups based on the ferritin level. Prohepcidin in the iron depleted group was significantly lower than the iron repleted group and the control (p < 0.0001) and higher levels were observed in the iron repleted group (p < 0.01). sTfR levels in the iron depleted group were significantly higher than the control and the iron repleted patients (p < 0.001). In the iron repleted group, sTfR level was not statistically different from that of control (p > 0.05).
CONCLUSION: Serum prohepcidin is clearly reduced in uncomplicated iron deficiency anaemia. The reduced prohepcidin levels in the iron depleted RA patients suggests that there may be conflicting signals regulating hepcidin production in RA patients. In RA patients who have reduced hepcidin in the iron depleted group (ferritin <60 microg/L) where sTfR levels are increased suggests that these patients are iron deficient. Further studies with a larger cohort of patients are required to substantiate this point.
METHODOLOGY: This randomised, blinded end-point, placebo-controlled clinical trial with a parallel design involved 36 healthy male subjects who took either an oral placebo or TRE at doses of 80, 160 or 320 mg daily for 2 mo. Baseline and end-of-treatment measurements of vitamin E concentration, arterial compliance [assessed by aortic femoral pulse wave velocity (PWV) and augmentation index (AI)], ASBP, plasma TAS, serum TC and LDL-C were taken.
RESULTS: Baseline tocotrienol isomer concentrations were low and not detectable in some subjects. Upon supplementation, all TRE-treated groups showed significant difference from placebo for their change in alpha, gamma and delta tocotrienol concentrations from baseline to end of treatment. There was a linear dose and blood level relationship for all the isomers. There was no significant difference between groups for their change in PWV, AI, plasma TAS, ASBP, TC or LDL-C from baseline to end of treatment. Groups 160 mg (p = 0.024) and 320 mg (p = 0.049) showed significant reductions in their ASBP. Group 320 mg showed a significant 9.2% improvement in TAS.
CONCLUSION: TRE at doses up to 320 mg daily were well tolerated. Treatment significantly increased alpha, delta, and gamma tocotrienol concentrations but did not significantly affect arterial compliance, plasma TAS, serum TC or LDL-C levels in normal subjects.
METHODS: Blood donation data of 4120 donors, spanning from January to December 2020, were retrospectively reviewed. The blood were screened for TTI markers, including hepatitis B surface antigen (HBsAg), anti-hepatitis B core (anti-HBc), anti-hepatitis C virus (anti-HCV), anti-human immunodeficiency viruses 1 and 2 (anti-HIV1&2), anti-human T-lymphotropic virus types 1 and 2 (anti-HTLV-1&2), and syphilis antigen.
RESULTS: Positive TTI markers were detected in 10.9% of the donors. The most detected TTI marker was anti-HBc (8.9%), followed by HBsAg (0.7%). Other markers were individually detected in <1% of the donors. Anti-HBc-positive was significantly elevated among non-Saudi blood donors. There was an association between age groups and anti-HCV (p=0.002), anti-HTLV (p=0.004) and syphilis antigen (p=0.02) markers positivity. The AB positive blood group exhibited the most positivity for TTI markers, followed by O positive blood group. Similarly, association was found between ABO group and HBsAg (p=0.01), anti-HBc (p=0.001), and anti-HCV (p<0.001) markers positivity.
CONCLUSION: Emphasis on implementing robust screening measures for donated blood is underscored by this study. There is the need for future study to extensively evaluate TTI status to enhance our understanding of the trend in TTI.
METHODS: The current study was conducted at the Hospital University Sains Malaysia, Kelantan. A total of 300 elderly Malay participants ≥ 65 years, with CKD, were taken in study. Demographic data, blood pressure, weight, and height were documented. Serum creatinine was assayed by Chemistry Analyzer Model Architect-C8000 (Jaffe Method), while serum cystatin C was examined by Human cystatin C ELISA kit (Sigma-Aldrich) using Thermo Scientific Varioskan Flash ELISA reader.
RESULTS: The study participants were divided into three groups on the basis of age. There was a statistically significant difference at the p value
METHODS: A clinically validated insulin/glucose model was used to calculate SI with the standard fasting assumption (SFA) G0 = GTARGET. Then GTARGET was treated as a variable in a second analysis (VGT). The outcomes were contrasted across twelve participants with established type 2 diabetes mellitus that were recruited to take part in a 24-week dietary intervention. Participants underwent three insulin-modified intravenous glucose tolerance tests (IM-IVGTT) at 0, 12, and 24 weeks.
RESULTS: SIVGT had a median value of 3.36×10-4 L·mU-1·min-1 (IQR: 2.30 - 4.95×10-4) and were significantly lower ( P < .05) than the median SISFA (6.38×10-4 L·mU-1·min-1, IQR: 4.87 - 9.39×10-4). The VGT approach generally yielded lower SI values in line with expected participant physiology and more effectively tracked changes in participant state over the 24-week trial. Calculated GTARGET values were significantly lower than G0 values (median GTARGET = 5.48 vs G0 = 7.16 mmol·L-1 P < .001) and were notably higher in individuals with longer term diabetes.
CONCLUSIONS: Typical modeling approaches can overestimate SI when GTARGET does not equal G0. Hence, calculating GTARGET may enable more precise SI measurements in individuals with type 2 diabetes, and could imply a dysfunction in diabetic metabolism.
METHODS: Data of 328 eligible housewives who participated in the MyBFF@Home study was used. Intervention group of 169 subjects were provided with an intervention package which includes physical activity (brisk walking, dumbbell exercise, physical activity diary, group exercise) and 159 subjects in control group received various health seminars. Physical activity level was assessed using short-International Physical Activity Questionnaire. The physical activity level was then re-categorized into 4 categories (active intervention, inactive intervention, active control and inactive control). Physical activity, blood glucose and lipid profile were measured at baseline, 3rd month and 6th month of the study. General Linear Model was used to determine the effect of physical activity on glucose and lipid profile.
RESULTS: At the 6th month, there were 99 subjects in the intervention and 79 control group who had complete data for physical activity. There was no difference on the effect of physical activity on the glucose level and lipid profile except for the Triglycerides level. Both intervention and control groups showed reduction of physical activity level over time.
CONCLUSION: The effect of physical activity on blood glucose and lipid profile could not be demonstrated possibly due to physical activity in both intervention and control groups showed decreasing trend over time.