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1.
Bull Environ Contam Toxicol ; 87(6): 633-7, 2011 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-21979137

RESUMO

Two kraft pulp mill effluents were compared in terms of their chronic toxicity to Daphnia magna. One resulted from pulping Pinus radiata and the other came from a parallel processing of Pinus radiata and Eucalyptus globulus (mixed kraft pulp mill effluent). The concentration of phytosterols found in the mixed kraft pulp mill effluent was higher than in the effluent from Pinus radiata, with values of 0.1082 and 0.02 µg/L, respectively. The phytosterols per se are responsible for 12.9% and 8.1% of the deviation from the natural shape, while the kraft pulp mill effluents account for 25.6%-27.8% of shape deviation. The role of ß-sitosterol and stigmasterol is discussed in relation to endocrine disruption.


Assuntos
Daphnia/efeitos dos fármacos , Eucalyptus/química , Resíduos Industriais/análise , Pinus/química , Poluentes Químicos da Água/toxicidade , Animais , Disruptores Endócrinos/análise , Disruptores Endócrinos/toxicidade , Sitosteroides/análise , Sitosteroides/toxicidade , Estigmasterol/análise , Estigmasterol/toxicidade , Poluentes Químicos da Água/análise
2.
Bull Environ Contam Toxicol ; 83(1): 23-8, 2009 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-19333532

RESUMO

A series of six 96-h static bioassays were performed to validate the use of anchoveta (Engraulis ringens) embryos as test organisms for ecotoxicological studies. The standardization protocol utilized potassium dichromate (K(2)Cr(2)O(7)) as a reference toxicant and egg mortality as the endpoint. The results indicated that the mean sensitivity of anchoveta embryos to potassium dichromate was 156.1 mg L(-1) (range: 131-185 mg L(-1)). The statistical data analysis showed high homogeneity in LC50 values among bioassays (variation coefficient = 11.02%). These results demonstrated that the protocol and handling procedures implemented for the anchoveta embryo bioassays comply with international standards for intra-laboratory precision. After secondary treatment, an effluent from a modern Kraft pulp mill was tested for E. ringens embryo toxicity, finding no significant differences from the controls.


Assuntos
Peixes/embriologia , Testes de Toxicidade/métodos , Poluentes Químicos da Água/toxicidade , Animais , Bioensaio/métodos , Bioensaio/normas , Embrião não Mamífero/anatomia & histologia , Embrião não Mamífero/efeitos dos fármacos , Monitoramento Ambiental/métodos , Peixes/anatomia & histologia , Resíduos Industriais , Oceanos e Mares , Dicromato de Potássio/toxicidade , Água do Mar
11.
Arch Environ Contam Toxicol ; 33(4): 407-14, 1997 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-9419259

RESUMO

Sensitivity to toxicants is a major criterion for selecting organisms for bioassay testing. If a sensitive species is also abundant and occupies a role as prey for many other species within a community, then the species become a valuable tool in environmental monitoring. These features apply to larval midge Chironomus petiolatus in freshwater environments of central Chile. The youngest larval instar is the most sensitive and presents the additional feature of lower survival within control arenas, making it more difficult to discern toxicant-related mortality from background mortality. In this work, we perform acute bioassays with the three larval stages of C. petiolatus and K2Cr2O7 as reference toxicant, with the goal of selecting a particular instar as the best bioassay tool using two criteria: sensitivity and background mortality. Sensitivity is evaluated through Monte Carlo estimation of LC50 and background mortality through bootstrap resampling, and a final Bioassay Performance Index as the product of LC50 and background mortality. For this task we developed a new computationally intensive statistical algorithm. Results show that the best bioassay tool is not the youngest and most sensitive instar but an intermediate one.


Assuntos
Algoritmos , Bioensaio/métodos , Chironomidae/crescimento & desenvolvimento , Animais , Estudos de Avaliação como Assunto , Larva , Método de Monte Carlo
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