@article{(Open Science Index):https://publications.waset.org/pdf/10001853,
	  title     = {Assessment of Diagnostic Enzymes as Indices of Heavy Metal Pollution in Tilapia Fish},
	  author    = {Justina I. R. Udotong},
	  country	= {},
	  institution	= {},
	  abstract     = {Diagnostic enzymes like aspartate aminotransferase
(AST), alanine aminotransferase (ALT) and alkaline phosphatase
(ALP) were determined as indices of heavy metal pollution in Tilapia
guinensis. Three different sets of fishes treated with lead (Pb), iron
(Fe) and copper (Cu) were used for the study while a fourth group
with no heavy metal served as a control. Fishes in each of the groups
were exposed to 2.65mg/l of Pb, 0.85mg/l of Fe and 0.35 mg/l of Cu
in aerated aquaria for 96 hours. Tissue fractionation of the liver
tissues was carried out and the three diagnostic enzymes (AST, ALT,
and ALP) were estimated. Serum levels of the same diagnostic
enzymes were also measured. The mean values of the serum enzyme
activity for ALP in each experimental group were 19.5±1.62,
29.67±2.17 and 1.15±0.27 IU/L for Pb, Fe and Cu groups compared
with 9.99±1.34 IU/L enzyme activity in the control. This result
showed that Pb and Fe caused increased release of the enzyme into
the blood circulation indicating increased tissue damage while Cu
caused a reduction in the serum level as compared with the level in
the control group. The mean values of enzyme activity obtained in
the liver were 102.14±6.12, 140.17±2.06 and 168.23±3.52 IU/L for
Pb, Fe and Cu groups, respectively compared to 91.20±9.42 IU/L
enzyme activity for the control group. The serum and liver AST and
ALT activities obtained in Pb, Fe, Cu and control groups are
reported. It was generally noted that the presence of the heavy metal
caused liver tissues damage and consequent increased level of the
diagnostic enzymes in the serum.},
	    journal   = {International Journal of Biotechnology and Bioengineering},
	  volume    = {9},
	  number    = {6},
	  year      = {2015},
	  pages     = {670 - 674},
	  ee        = {https://publications.waset.org/pdf/10001853},
	  url   	= {https://publications.waset.org/vol/102},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 102, 2015},