The use of Daphnia magna neonates hatched from ephippia for toxicity testing

2000 ◽  
pp. 145-153 ◽  
Author(s):  
M. M. Moreira Dos Santos ◽  
G. Persoone
Keyword(s):  
Daphnia Magna ◽  
Toxicity Testing

Frozen algae as food for Daphnia magna straus in toxicity testing

1992 ◽  
Vol 24 (1) ◽  
pp. 58-62 ◽  
Author(s):  
Eileen J. Cox ◽  
Caroline Naylor ◽  
P. Calow
Keyword(s):  
Daphnia Magna ◽  
Toxicity Testing

Surfactants – standard determination methods in comparison with substance specific mass spectrometric methods and toxicity testing by Daphnia magna and Vibrio fischeri

2000 ◽  
Vol 42 (7-8) ◽  
pp. 391-398 ◽  
Author(s):  
H.-Q. Li ◽  
H. F. Schröder
Keyword(s):  
Daphnia Magna ◽  
Vibrio Fischeri ◽  
Atmospheric Pressure Chemical Ionization ◽  
Pure Water ◽  
Toxicity Testing ◽  
Mass Spectrometric ◽  
Mass Spectrometric Detection ◽  
Specific Mass ◽  
Pressure Chemical Ionization ◽  
Pressure Chemical

The recovery of different types of surfactants formerly applied and up-coming new ones from spiked wastewater and ultra-pure water was examined by sum parameter determinations (substance-group-specific Methylene Blue (MBAS), Bismuth Active (BiAS) and Disulfine Blue Active Substances (DSBAS)) and by substance-specific mass spectrometric detection (MS). For MS determination atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) was applied in the flow injection (FIA) and liquid chromatographic separation (LC) mode. Quantitation was performed in the multiple ion detection mode using mass and tandem (MS/MS) mass spectrometric detection. In parallel the ecotoxicological potential of these surfactants was determined by Daphnia magna and Vibrio fischeri toxicity testing. MS was found to provide more reliable data in surfactant analysis than the substance-group-specific methods. The toxicity of the up-coming new surfactants against water organisms should not be neglected.

Freeze-Dried Chlorella vulgaris as Food for Daphnia magna Straus in Toxicity Testing

1993 ◽  
Vol 25 (2) ◽  
pp. 166-172 ◽  
Author(s):  
C. Naylor ◽  
M.C. Bradley ◽  
P. Calow
Keyword(s):  
Daphnia Magna ◽  
Chlorella Vulgaris ◽  
Toxicity Testing ◽  
Freeze Dried

scholarly journals Effect of the Albumin Corona on the Toxicity of Combined Graphene Oxide and Cadmium to Daphnia magna and Integration of the Datasets into the NanoCommons Knowledge Base

Nanomaterials ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1936 ◽  
Author(s):  
Diego Stéfani T. Martinez ◽  
Gabriela H. Da Silva ◽  
Aline Maria Z. de Medeiros ◽  
Latif U. Khan ◽  
Anastasios G. Papadiamantis ◽  
...  
Keyword(s):  
Graphene Oxide ◽  
Acute Toxicity ◽  
Knowledge Base ◽  
Daphnia Magna ◽  
Colloidal Stability ◽  
Cadmium Toxicity ◽  
Toxicity Testing ◽  
Mixture Toxicity ◽  
Water Quality Monitoring ◽  
Corona Formation

In this work, we evaluated the effect of protein corona formation on graphene oxide (GO) mixture toxicity testing (i.e., co-exposure) using the Daphnia magna model and assessing acute toxicity determined as immobilisation. Cadmium (Cd2+) and bovine serum albumin (BSA) were selected as co-pollutant and protein model system, respectively. Albumin corona formation on GO dramatically increased its colloidal stability (ca. 60%) and Cd2+ adsorption capacity (ca. 4.5 times) in reconstituted water (Daphnia medium). The acute toxicity values (48 h-EC50) observed were 0.18 mg L−1 for Cd2+-only and 0.29 and 0.61 mg L−1 following co-exposure of Cd2+ with GO and BSA@GO materials, respectively, at a fixed non-toxic concentration of 1.0 mg L−1. After coronation of GO with BSA, a reduction in cadmium toxicity of 110 % and 238% was achieved when compared to bare GO and Cd2+-only, respectively. Integration of datasets associated with graphene-based materials, heavy metals and mixture toxicity is essential to enable re-use of the data and facilitate nanoinformatics approaches for design of safer nanomaterials for water quality monitoring and remediation technologies. Hence, all data from this work were annotated and integrated into the NanoCommons Knowledge Base, connecting the experimental data to nanoinformatics platforms under the FAIR data principles and making them interoperable with similar datasets.

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