The Petroleum-Inducible Mixed-Function Oxidase of Cunner (Tautogolabrus adspersus Walbaum 1792): Some Characteristics Relevant to Hydrocarbon Monitoring

1978 ◽  
Vol 35 (12) ◽  
pp. 1547-1552 ◽  
Author(s):  
D. G. Walton ◽  
W. R. Penrose ◽  
J. M. Green

The hepatic aryl hydrocarbon hydroxylase of the cunner (Tautogolabrus adspersus) is a sensitive indicator of petroleum contamination. This fish is a particularly favorable species because of its limited home range and ease of capture. Oil concentrations of 1–2 mg/L in water caused two- to sixfold induction of the enzyme above uninduced levels; induction decayed in < 7 d after exposure ceased. Feeding of crude oil or mussel tissue contaminated with oil at a concentration of 500 mg/kg caused up to fivefold induction. Males maintained a constant specific activity of aryl hydroxylase through the season, but females had a decreased activity before spawning. Starvation may also have reduced AHH activity. Correlations with liver and body weight were not observed. 2,5-Diphenyloxazole was found to be a safe substitute for benzo[a]pyrene in the assay. Key words: cunner, mixed function oxidase, aryl hydrocarbon hydroxylase, oil pollution, monitoring, biochemistry

1978 ◽  
Vol 35 (5) ◽  
pp. 643-647 ◽  
Author(s):  
J. H. Vandermeulen ◽  
W. R. Penrose

Bivalves exposed to short-term (4 d) and long-term (6 yr) oil pollution were assayed for aryl hydrocarbon hydroxylase (AHH) and N-demethylase activity. Short-term induction studies were carried out on Mya arenaria, Mytilus edulis, and Ostrea edulis incubated in aqueous extracts of Kuwait crude oil or Bunker C (fuel) oil. For the chronic-induction studies Mya arenaria and Mytilus edulis were collected from oiled clam beds (Arrow Bunker C) in Chedabucto Bay, Nova Scotia. None of the bivalves showed any basal or petroleum-hydrocarbon-induced aryl hydrocarbon hydroxylase or N-demethylase activity, as shown by their inability to metabolize benzopyrene or imipramine. In contrast, oil-free control trout and trout taken from a polluted lake readily metabolized both these compounds. The inability of these bivalves to degrade petroleum aromatic hydrocarbons and the tendency of these compounds to accumulate in their tissues present an opportunity for transfer of unaltered hydrocarbons into the food chain. Key words: aryl hydrocarbon hydroxylase, aromatic hydrocarbon, bivalve, Mya arenaria, Mytilus edulis, Ostrea edulis, petroleum, pollution


1977 ◽  
Vol 145 (6) ◽  
pp. 1607-1611 ◽  
Author(s):  
J A Cohn ◽  
A P Alvares ◽  
A Kappas

The difference spectra of the carbon monoxide-complex of dithionite-reduced rat brain microsomes, compared with both reduced microsomes, alone, and the carbon monoxide-complex of oxidized microsomes, indicate the presence of small amounts of cytochrome P-450 in brain. As in liver, cytochrome P-450 in brain is degraded in vitro to its inactive form, cytochrome P-420 by methylmercury chloride. Aryl hydrocarbon hydroxylase activity is also present in rat brain microsomes and, at lower specific activity, in brain homogenates. This carcinogen metabolizing activity is increased four-fold in rats pretreated with 3-methylcholanthrene.


2021 ◽  
Vol 11 (8) ◽  
pp. 3642
Author(s):  
Oleg Bukin ◽  
Dmitry Proschenko ◽  
Denis Korovetskiy ◽  
Alexey Chekhlenok ◽  
Viktoria Yurchik ◽  
...  

The oil pollution of seas is increasing, especially in local areas, such as ports, roadsteads of the vessels, and bunkering zones. Today, methods of monitoring seawater are costly and applicable only in the case of big ecology disasters. The development of an operative and reasonable project for monitoring the sea surface for oil slick detection is described in this article using drones equipped with optical sensing and artificial intelligence. The monitoring system is implemented in the form of separate hard and soft frameworks (HSFWs) that combine monitoring methods, hardware, and software. Three frameworks are combined to fulfill the entire monitoring mission. HSFW1 performs the function of autonomous monitoring of thin oil slicks on the sea surface, using computer vision with AI elements for detection, segmentation, and classification of thin slicks. HSFW2 is based on the use of laser-induced fluorescence (LIF) to identify types of oil products that form a slick or that are in a dissolved state, as well as measure their concentration in solution. HSFW3 is designed for autonomous navigation and drone movement control. This article describes AI elements and hardware complexes of the three separate frameworks designed to solve the problems with monitoring slicks of oil products on the sea surface and oil products dissolved in seawater. The results of testing the HSFWs for the detection of pollution caused by marine fuel slicks are described.


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