Long-Term Copper Toxicity on Scenedesmus quadricauda and Complexing Polypeptides

1995 ◽  
Vol 30 (2) ◽  
pp. 265-276 ◽  
Author(s):  
Denis Bussières ◽  
Raynald Côté ◽  
Clément Richard ◽  
Édith St-Pierre
Keyword(s):  
Heavy Metal ◽  
Sharp Increase ◽  
Copper Ions ◽  
Copper Toxicity ◽  
Scenedesmus Quadricauda ◽  
Continuous Exposure ◽  
Exponential Curve ◽  
Negative Exponential

Abstract Long-term copper toxicity has been demonstrated in Scenedesmus quadricauda. Upon continuous exposure to copper ions at 250 μg/L, the algae responded by a sharp increase in the synthesis of complexing polypeptides to chelate Cu. Complexing polypeptides gradually decreased, as observed by six sampling tests over 732 h, resembling to a negative exponential curve. This gradual diminution is considered to be a prime mechanism of acclimation or of adaptation to a heavy metal contaminated environment.

Comparing the Genetic Detox Ability and Heavy Metal Burden in a Cohort of Samples of Egyptian Children and those with Autistic Spectrum Disorder

2019 ◽  
Author(s):  
Blaurock-Busch E
Keyword(s):  
Heavy Metal ◽  
Autism Spectrum ◽  
Control Group ◽  
Potentially Toxic Metals ◽  
Gstt1 Null Genotype ◽  
Egyptian Children ◽  
Glutathione S Transferases ◽  
Metal Burden ◽  
Detoxification Pathway

The heavy metal burden of patients with Autism spectrum disorders (ASD) has been widely discussed [1-5]. Present knowledge suggests that ASD patients, compared to ‘normal’s’ show a greater metal burden, which may be a cause of the ASD pathogenesis, possibly due to a limited detoxification potential. We thus aimed to evaluate if the metal burden of ASD children is due to comprised detoxification ability, and if missing of enzymes such as the glutathione-S-transferases provide an explanation, or if additional factors play a role. Genetically, we noticed a slight difference in the detoxification ability of the ASD group compared to the Control group. In the ASD group, carrier of the genotype GSTT1 null genotype (i.e. the homozygous loss) are 1.7 times more common as in the Control group and the GSTT1 allele is more frequent in the ASD patient collective. These findings are not statistically significant but indicate a trend. In addition, our data indicates that levels of potentially toxic metals in blood and hair of both groups demonstrate a similar immediate and long-term exposure. However, 36% of the ASD group showed signs of zinc deficiency compared to 11% of the Control group and this points towards inefficiency of the Phase I detoxification pathway. More research is needed to explore the role of other elements in the detoxification pathway.

scholarly journals Exercise during Short-Term and Long-Term Continuous Exposure to Hypoxia Exacerbates Sleep-Related Periodic Breathing

SLEEP ◽  
2016 ◽  
Vol 39 (4) ◽  
pp. 773-783 ◽  
Author(s):  
Helio Fernandez Tellez ◽  
Shawnda A. Morrison ◽  
Xavier Neyt ◽  
Olivier Mairesse ◽  
Maria Francesca Piacentini ◽  
...  
Keyword(s):  
Periodic Breathing ◽  
Continuous Exposure ◽  
Short Term

scholarly journals Atmospheric Heavy Metal Input to Forest Soils in Rural Areas of Denmark

2007 ◽  
Vol 7 ◽  
pp. 192-197 ◽  
Author(s):  
M. F. Hovmand ◽  
Kaare Kemp
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Rural Areas ◽  
Forest Floor ◽  
Ambient Atmosphere ◽  
Chronological Order ◽  
Forest Sites ◽  
Yearly Average ◽  
Atmospheric Inputs

Atmospheric bulk deposition of heavy metals (HM) was measured from 1972/73 to the present time at five to ten forest sites in rural areas of Denmark. From 1979, HM in aerosols were measured at one to four forest sites. On the basis of these long-term continuous measurements, the atmospheric inputs to the forest floor have been calculated. Yearly HM emission estimates to the European atmosphere seems to correlate well with yearly average values of HM deposition, as well as with HM concentrations in the ambient atmosphere. HM emissions have been estimated since the 1950s. Using the correlation between emission and deposition, HM deposition values maybe extrapolated in reverse chronological order. The accumulated atmospheric HM deposition has been estimated in this way over a period of 50 years.

Long-term cultivation impact on the heavy metal behavior in a reclaimed wetland, Northeast China

2013 ◽  
Vol 14 (3) ◽  
pp. 567-576 ◽  
Author(s):  
Wei Jiao ◽  
Wei Ouyang ◽  
Fanghua Hao ◽  
Fangli Wang ◽  
Bing Liu
Keyword(s):  
Heavy Metal ◽  
Northeast China

scholarly journals Long-Term River Water Quality Trends and Pollution Source Apportionment in Taiwan

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1394 ◽  
Author(s):  
Marsha Putri ◽  
Chao-Hsun Lou ◽  
Mat Syai’in ◽  
Shang-Hsin Ou ◽  
Yu-Chun Wang
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Heavy Metal ◽  
Cluster Analysis ◽  
River Water ◽  
Principal Component ◽  
Pollution Level ◽  
Metal Levels ◽  
Metal Monitoring

The application of multivariate statistical techniques including cluster analysis and principal component analysis-multiple linear regression (PCA-MLR) was successfully used to classify the river pollution level in Taiwan and identify possible pollution sources. Water quality and heavy metal monitoring data from the Taiwan Environmental Protection Administration (EPA) was evaluated for 14 major rivers in four regions of Taiwan with the Erren River classified as the most polluted river in the country. Biochemical oxygen demand (6.1 ± 2.38), ammonia (3.48 ± 3.23), and total phosphate (0.65 ± 0.38) mg/L concentration in this river was the highest of the 14 rivers evaluated. In addition, heavy metal levels in the following rivers exceeded the Taiwan EPA standard limit (lead: 0.01, copper: 0.03, and manganese: 0.03) mg/L concentration: lead-in the Dongshan (0.02 ± 0.09), Jhuoshuei (0.03 ± 0.03), and Xinhuwei Rivers (0.02 ± 0.02) mg/L; copper: in the Dahan (0.036 ± 0.097), Laojie (0.06 ± 1.77), and Erren Rivers are (0.05 ± 0.158) mg/L; manganese: in all rivers. A total 72% of the water pollution in the Erren River was estimated to originate from industrial sources, 16% from domestic black water, and 12% from natural sources and runoff from other tributaries. Our research demonstrated that applying PCA-MLR and cluster analysis on long-term monitoring water quality would provide integrated information for river water pollution management and future policy making.

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