Bio-based and cost effective method for phenolic compounds removal using cross-linked enzyme aggregates.

This work aimed at presenting a green method using a new source of peroxidase isolated from Raphanus sativus var. niger (RSVNP) in immobilized form, for the treatment of wastewater. To ensure stability and enzymatic activity in the biodegradation process, RSVNP was immobilized as a cross-linked enzyme aggregate (CLEAs). With more than 29% of recovered activity and 85% aggregation yield, acetone was selected as the best precipitating agent. The formed protein aggregates required 2% (v/v) of glutaraldehyde (GA) concentration and a ratio of 9:1 (v/v) enzyme (E) amount to cross-linker (E/GA). Compared to the free enzyme, RSVNP-CLEAs were found more chemically and thermally stable and exhibited good storage stability for more than 8 weeks. In addition, RSVNP-CLEAs were evaluated for their ability to remove phenol and p-cresol from aqueous solution by varying several operating conditions. A maximal yield (98%) of p-cresol conversion was recorded after 40 min; while 92% of phenol was degraded after 1 h duration time. The reusability of RSVNP-CLEAs was tested, displaying 71% degradation of phenol in the third batch carried out and more than 54% was achieved for p-cresol after four successive reuses in the presence of hydrogen peroxide at 2 mM concentration.

QSAR modeling in ecotoxicological risk assessment: application to the prediction of acute contact toxicity of pesticides on bees (Apis mellifera L.).

Despite their indisputable importance around the world, the pesticides can be dangerous for a range of species of ecological importance such as honeybees (Apis mellifera L.). Thus, a particular attention should be paid to their protection, not only for their ecological importance by contributing to the maintenance of wild plant diversity, but also for their economic value as honey producers and crop-pollinating agents. For all these reasons, the environmental protection requires the resort of risk assessment of pesticides. The goal of this work was therefore to develop a validated QSAR model to predict contact acute toxicity (LD50) of 111 pesticides to bees because the QSAR models devoted to this species are very scarce. The analysis of the statistical parameters of this model and those published in the literature shows that our model is more efficient. The QSAR model was assessed according to the OECD principles for the validation of QSAR models. The calculated values for the internal and external validation statistic parameters (Q 2 and [Formula: see text] are greater than 0.85. In addition to this validation, a mathematical equation derived from the ANN model was used to predict the LD50 of 20 other pesticides. A good correlation between predicted and experimental values was found (R 2 = 0.97 and RMSE = 0.14). As a result, this equation could be a means of predicting the toxicity of new pesticides.

Health risk assessment of heavy metal intake due to fish consumption in the Sistan region, Iran.

The heavy metal (Pb, Cd, Cr, and Ni) content of a fish species consumed by the Sistan population and its associated health risk factors were investigated. The mean concentrations of Pb, Cd, and Cr were slightly higher than the standard levels. The Ni content of fish was below the maximum guideline proposed by the US Food and Drug Administration (USFDA). The average estimated weekly intake was significantly below the provisional tolerable intake based on the FAO and WHO standards for all studied metals. The target hazard quotients (THQ) of all metals were below 1, showing an absence of health hazard for the population of Sistan. The combined target hazard quotient for the considered metals was 26.94 × 10-3. The cancer risk factor for Pb (1.57 × 10-7) was below the acceptable lifetime carcinogenic risk (10-5). The results of this study reveal an almost safe level of Pb, Cd, Cr, and Ni contents in the fish consumed by the Sistan population. Graphical abstract ᅟ.