Aims:The aim of this study was to investigate the effectiveness of freshwater green microalgae in remediating swine manure wastewater. Two different species of freshwater green microalgae (Scenedesmus quadricaudaand Stigeocloniumsp.) were used in this study.Methodology and results:Laboratory experiments were performed to compare the growth rate and nutrients (total phosphorus, ammonia nitrogen, nitrate nitrogen and nitrite nitrogen) uptake by these two species of microalgae in swine manure wastewater. Experimental work was carried out for 14 days at room temperature of 30±1 °C with about 1520 Lux of light intensity. The results showed that both microalgae grew well in swine manure wastewater. S.quadricaudaperformed better in remediating swine manure wastewater, by reducing 83.99% of COD, 80.39% of BOD5, 84.78% of total phosphorus (TP), 91.79% of ammonia nitrogen (NH3-N), 89.79% of nitrate nitrogen (NO3-N) and 87.14% of nitrite nitrogen (NO2-N) compared to Stigeocloniumsp. which was only able to remove 79.26% of COD, 76.27% of BOD5,75.17% of TP, 86.42% of NH3-N, 84.38% of NO3-N and 82.38 NO2-N.Conclusion, significance and impact of study:The results of this study indicate that these two species of microalgae have potential to be used in the remediation of swine manure wastewate

INTRODUCTIONWaiting times for kidney transplant are long in Singapore. Healthrelated quality of life (HRQoL) of patients might be affected as a result of the stress of the long wait and the uncertainty of being called to undergo a surgical operation. This study aimed to measure the HRQoL of patients on the kidney transplant waiting list and to identify factors which could impact on the HRQoL scores in this group of patients.

MATERIALS AND METHODSThis was a cross-sectional study of kidney transplant waiting list patients managed at a tertiary renal unit using the SF-36. A SF-36 normative calculator was used to generate HRQoL scores for the Singapore general population matched with the study cohort's age, gender and ethnicity.

RESULTSThere were 265 respondents with a response rate was 81%. Our study shows that HRQoL scores for the kidney transplant waiting list patients were lower than the population norms across all subscales and were clinically significant for General Health, Role Physical, Bodily Pain, Social Functioning and Mental Component Summary scores. Factors such as being Chinese, married, employed and undergoing haemodialysis predicted better HRQoL scores after adjusting for possible confounders. Age, gender, educational level, household income, history of kidney transplant, duration on the transplant waiting list and years on dialysis did not significantly influence SF-36 across all subscales scores.

CONCLUSIONKidney transplant waiting list patients had worse HRQoL compared to the general population. Factors such as ethnicity, marital status, employment status, and type of dialysis treatment significantly influenced patients' perception of their HRQoL.

Cross-Sectional Studies ; Female ; Health Status ; Humans ; Kidney Transplantation ; Male ; Quality of Life ; Surveys and Questionnaires ; Waiting Lists