METHODS: Male Wistar rats (200-250 g) were divided into 4 groups according to the diet given: control group (normal diet), ChV group with three different doses (50, 150 and 300 mg/kg body weight), liver cancer- induced group (choline deficient diet + 0.1% ethionine in drinking water or CDE group), and the treatment group (CDE group treated with three different doses of ChV). Rats were killed at 0, 4, 8 and 12 weeks of experiment and blood and tissue samples were taken from all groups for the determination of tumour markers expression alpha-fetoprotein (AFP), transforming growth factor-β (TGF-β), M2-pyruvate kinase (M2-PK) and specific antigen for oval cells (OV-6).
RESULTS: Serum level of TGF-β increased significantly (p < 0.05) in CDE rats. However, ChV at all doses managed to decrease (p < 0.05) its levels to control values. Expressions of liver tumour markers AFP, TGF-β, M2-PK and OV-6 were significantly higher (p < 0.05) in tissues of CDE rats when compared to control showing an increased number of cancer cells during hepatocarcinogenesis. ChV at all doses reduced their expressions significantly (p < 0.05).
CONCLUSIONS: Chlorella vulgaris has chemopreventive effect by downregulating the expression of tumour markers M2-PK, OV-6, AFP and TGF-β, in HCC-induced rats.
METHODS: This quantitative research was conducted by distributing survey questionnaires randomly to five coal-fired power plants in Peninsular Malaysia. A total of 340 respondents were involved in this research. Partial least squares structural equation modeling (PLS-SEM) analysis was performed using SmartPLS to validate and examine the relationship of the proposed model.
RESULTS: The results validate the construct of hazard control and prevention consisting of planning, action, managing, and verifying, while the safety outcomes construct consists of occupational accidents, fatal accidents, near misses, and lost time injuries. The results indicate that hazard control and prevention significantly relate to safety compliance, safety participation, safety motivation, and safety knowledge. Moreover, safety outcomes were influenced negatively by hazard control and prevention through safety compliance.
CONCLUSION: The model provides a better understanding of the influence of hazard control and prevention on safety behavior and outcomes.
PRACTICAL APPLICATIONS: The model can be used as guidance for practitioners and researchers in planning and implementing hazard control and prevention to improve health and safety in the workplace.
METHODS: Fifty-one adult patients with suspected bacterial sepsis on admission to the Emergency Department (ED) of a teaching hospital were included into the study. All relevant cultures and serology tests were performed. Serum levels for Group II Secretory Phospholipase A2 (sPLA2-IIA) and CD64 were subsequently analyzed.
RESULTS AND DISCUSSION: Sepsis was confirmed in 42 patients from a total of 51 recruited subjects. Twenty-one patients had culture-confirmed bacterial infections. Both biomarkers were shown to be good in distinguishing sepsis from non-sepsis groups. CD64 and sPLA2-IIA also demonstrated a strong correlation with early sepsis diagnosis in adults. The area under the curve (AUC) of both Receiver Operating Characteristic curves showed that sPLA2-IIA was better than CD64 (AUC = 0.93, 95% confidence interval (CI) = 0.83-0.97 and AUC = 0.88, 95% CI = 0.82-0.99, respectively). The optimum cutoff value was 2.13μg/l for sPLA2-IIA (sensitivity = 91%, specificity = 78%) and 45 antigen bound cell (abc) for CD64 (sensitivity = 81%, specificity = 89%). In diagnosing bacterial infections, sPLA2-IIA showed superiority over CD64 (AUC = 0.97, 95% CI = 0.85-0.96, and AUC = 0.95, 95% CI = 0.93-1.00, respectively). The optimum cutoff value for bacterial infection was 5.63μg/l for sPLA2-IIA (sensitivity = 94%, specificity = 94%) and 46abc for CD64 (sensitivity = 94%, specificity = 83%).
CONCLUSIONS: sPLA2-IIA showed superior performance in sepsis and bacterial infection diagnosis compared to CD64. sPLA2-IIA appears to be an excellent biomarker for sepsis screening and for diagnosing bacterial infections, whereas CD64 could be used for screening bacterial infections. Both biomarkers either alone or in combination with other markers may assist in decision making for early antimicrobial administration. We recommend incorporating sPLA2-IIA and CD64 into the diagnostic algorithm of sepsis in ED.