This study explored fishmeal replacement with two freshwater microalgae: Spirulina Platensis and Chlorella vulgaris in African catfish (Clarias gariepinus) diet. The effect of inclusion of the two microalgae on biomarkers of oxidative stress, haematological parameters, enzyme activities and growth performance were investigated. The juvenile fish were given 3 distinct treatments with isonitrogenous (35.01-36.57%) and isoenergetic (417.24-422.27 Kcal 100 g-1) diets containing 50% S. platensis (50SP), 75% S. platensis (75SP), 50% C. vulgaris (50CL), 75% C. vulgaris (75CL) and 100% fishmeal (100% FM) was used as the control diet. The result shows that all the diets substituted with both S. platensis, and C. vulgaris boosted the growth performance based on specific growth rate (SGR) and body weight gain (BDWG) when compared with the control diet. The feed conversion ratio (FCR) and protein efficiency ratio (PER) was significantly influenced by all the supplementations. The haematological analysis of the fish shows a significant increase in the value of red and white blood cells upon supplementation with 50SP and 50CL but decrease slightly when increased to 75SP and 75CL. Furthermore, the value of haematocrit and haemoglobin also increased upon supplementation with 50SP and 50CL but decrease slightly when increased to 75SP and 75CL. The white blood cell (WBC), red blood cell (RBC) increased, while total cholesterol (TCL), and Plasma glucose levels decreased significantly upon supplementation of algae. This is a clear indication that S. platensis and C. vulgaris are a promising replacement for fishmeal, which is a source protein in the C. gariepinus diet.
Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients' actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3 cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: -1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged <40 years, and in those receiving neoadjuvant chemotherapy. PREDICT performed well in terms of discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74-0.81) and 0.73 (95% CI: 0.68-0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings.