Escherichia coli's water load affects zebrafish (Danio rerio) behavior

Ecotoxicological Effects of Potassium Dichromate on the Tadpole Shrimp Triops longicaudatus

The tadpole shrimp Triops longicaudatus is a freshwater crustacean with fast embryonic and larval development, short life cycle, and high fecundity. They are very active swimmers of a reasonable size, easy to spot and record. Such characteristics make it a promising candidate as an experimental model in ecotoxicology to evaluate the effects of aquatic pollutants, particularly using its locomotor behavior as an endpoint. To evaluate the sensitivity of T. longicaudatus and develop endpoints of interest, we conducted exposure experiments with lethal and sub-lethal concentrations of potassium dichromate, a compound known for its ecotoxicological importance and as a hexavalent chromium source. The endpoints evaluated were mortality, growth, sexual maturation, reproductive output, cholinesterase activity and locomotor/swimming behavior. The 96 h median lethal concentration was found to be 65 µg/L. Furthermore, exposure to potassium dichromate at higher concentrations had a significant negative impact on the growth rate of T. longicaudatus in terms of both body mass and length. The time for maturation was also delayed at higher concentrations. In addition, locomotor behavior allowed for the discrimination of all tested chromium concentrations and the control group and from each other, proving to be the most sensitive endpoint. Overall, the data support the potential of T. longicaudatus as a model for ecotoxicity testing, using apical endpoints with impact at the population level; in particular, results suggest that behavior assessments in this species might be useful for detecting hazardous compounds in environmental monitoring of freshwater ecosystems.

Environmental diagnosis with Raman Spectroscopy applied to diatoms

Freshwater quality has been changing due to the ever greater use of water resources and the contamination load resulting from human activities. Management of these systems, thus, requires constant diagnose of water quality with fast and efficient methodologies. The conventional methods adopted are, however, time-consuming, often very expensive, and require specialised expertise. Raman spectroscopy (RS) is a simple, fast and label-free technique that can be applied to environmental diagnosis using diatoms. Here, we developed a diagnostic method based on Raman spectroscopy applied to freshwater diatoms. For this, Raman spectra were recorded from diatoms of three lakes of a natural city park. The data acquired was analysed by chemometrics methods to describe the data (Partial Least Squares Regression), infer relationships in the dataset (Cluster Analysis) and produce classification models (Artificial Neural Network). The classification models developed diagnosed the lakes with excellent accuracy (89%) without requiring taxonomic information about the diatom species recorded. This study provides a proof-of-concept for the application of diatom Raman spectroscopy to diagnosing water quality, laying an important foundation for future environmental studies aiming at assessing freshwater systems, to be replicated at larger scales and to varied geographic settings.

Early detection of cyanide, organophosphate and rodenticide pollution based on locomotor activity of zebrafish larvae

Cyanide, organophosphate and rodenticides are highly toxic substances widely used in agriculture and industry. These toxicants are neuro- and organotoxic to mammals at low concentrations, thus early detection of these chemicals in the aqueous environment is of utmost importance. Here, we employed the behavioral toxicity test with wildtype zebrafish larvae to determine sublethal concentrations of the above mentioned common environmental pollutants. After optimizing the test with cyanide, nine rodenticides and an organophosphate were successfully tested. The compounds dose-dependently initially (0-60-min exposure) stimulated locomotor activity of larvae but induced toxicity and reduced swimming during 60-120-min exposure. IC₅₀ values calculated based on swimming distance after 2-h exposure, were between 0.1 and 10 mg/L for both first-generation and second-generation anticoagulant rodenticides. Three behavioral characteristics, including total distance travelled, sinuosity and burst count, were quantitatively analyzed and compared by hierarchical clustering of the effects measured by each three parameters. The toxicity results for all three behavioral endpoints were consistent, suggesting that the directly measured parameter of cumulative swimming distance could be used as a promising biomarker for the aquatic contamination. The optimized method herein showed the potential for utilization as part of a monitoring system and an ideal tool for the risk assessment of drinking water in the military and public safety.

Chinese Language Feature Analysis Based on Multilayer Self-Organizing Neural Network and Data Mining Techniques

As one of the oldest languages in the world, Chinese has a long cultural history and unique language charm. The multilayer self-organizing neural network and data mining techniques have been widely used and can achieve high-precision prediction in different fields. However, they are hardly applied to Chinese language feature analysis. In order to accurately analyze the characteristics of Chinese language, this paper uses the multilayer self-organizing neural network and the corresponding data mining technology for feature recognition and then compared it with other different types of neural network algorithms. The results show that the multilayer self-organizing neural network can make the accuracy, recall, and F1 score of feature recognition reach 68.69%, 80.21%, and 70.19%, respectively, when there are many samples. Under the influence of strong noise, it keeps high efficiency of feature analysis. This shows that the multilayer self-organizing neural network has superior performance and can provide strong support for Chinese language feature analysis.