Straight-chain alkanes (n-alkanes) have been proposed as biomarkers to assess petroleum pollution sources in marine environments. In this work, three sampling sites were selected along Iranian-protected mangrove forests in the Persian Gulf. Sample sites were chosen to represent different compositions and sources of n-alkanes in surface sediments (0–5 cm) from different locations in the Khamir Port, in the middle part of the Gulf, and in the Qeshm Island. Samples were analyzed by gas chromatography-mass spectrometry (GC–MS), and the obtained n-alkanes concentrations were analyzed by principal component analysis (PCA) and multivariate curve resolution alternating least squares (MCR-ALS) to deduce their possible sources and distribution patterns. Results revealed that n-alkanes have a dominant biogenic source in marginal Qeshm Island stations, which changed from biogenic to petrogenic sources in the Khamir Port areas. Sediment samples from the Khamir Port showed the significant presence of oil pollution due to transportation. These samples are being exposed to basic Persian Gulf currents entering from the Hormuz Strait causing oil pollution spread over the entire Gulf area. Sediment samples of the Middle Part stations located between two other sites show a combined condition of the two previous sections, with petrogenic and biogenic contributions. The present study demonstrates that the Hara Protected Area was already contaminated by background oil pollution as a result of continuous oil spills and war conflicts in the Persian Gulf.Additionally, the MCR-ALS method is shown to be a powerful chemometric tool for the investigation, resolution, identification, and description of pollution patterns distributed over a particular geographical area and environmental compartment. They can be used as well as parameters like unresolved to resolved ratio (U/R), pristane to phytane (Pr/Ph), n-C₁₇/Pr, n-C₁₈/Ph, and unresolved complex mixture (UCM) to assess petroleum pollution sources in the sediments.

Unfortunately, the original publication of this paper contains a mistake. The correct name of the 3rd Author is Sunny H. Patel. The original article has been corrected.

Guppy (Poecilia reticulata) is a promising model organism in toxicological studies, and vitellogenin (Vtg) is a commonly used biomarker for environmental estrogens. Although an ELISA for guppy Vtg has been developed previously, we found that guppy had two forms of Vtgs. In this study, two Vtgs were characterized and enzyme-linked immunosorbent assays (ELISAs) for each Vtg were developed. Two Vtgs purified from 17β-estradiol (E₂)-exposed guppy were characterized as phospholipoglycoproteins with molecular weights of ~ 520 and ~ 480 kDa, respectively. In SDS-PAGE, one purified Vtg appeared as three major bands of ~ 210, ~ 126, and ~ 102 kDa, and the other revealed a clear band of ~ 68 kDa. Matrix-assisted laser desorption/ionization–time of flight/time of flight mass spectrometry analysis showed that they were VtgAb and VtgC. Using purified Vtgs and their corresponding antibodies, two sandwich ELISAs with working ranges of 7.8~1000 and 15.6~500 ng/mL were developed. Precision tests showed that intra- and inter-assay coefficients of variations of both ELISAs were below 10%. Parallelism between Vtg standard curves and serial dilutions of whole body homogenate from E₂-exposed guppy confirmed that two ELISAs could quantify guppy Vtgs. Furthermore, two ELISAs were used to measure Vtg inductions in liver, caudal fin and whole body of male guppy exposed to 17a-ethinylestradiol to validate their use for detecting estrogenic effects of exogenous chemicals. These homologous Vtg ELISAs will promote the use of guppy as a model organism to study estrogenic chemicals.

Recombinant α-carbonic anhydrase of the polyextremophilic bacterium Bacillus halodurans TSLV1 (rBhCA) has been produced extracellularly in active form in Pichia pastoris under methanol inducible (AOX1) as well as constitutive (GAP) promoters. A marked improvement in rBhCA production was achieved by developing a P. pastoris recombinant that produces rBhCA constitutively as compared to that under inducible promoter. The purified rBhCA from P. pastoris is a glycosylated protein that displays a higher molecular mass (79.5 kDa) than that produced from E. coli recombinant (75 kDa); the former has a Tm of 75 °C, which is slightly higher than that of the latter (72 °C). The former rBhCA exhibits higher thermostability than the latter. The former sequestered CO₂ efficiently similar to that of the native BhCA and the latter. This is the first report on the production of recombinant carbonic anhydrase extracellularly in P. pastoris.

Pharmaceuticals in the aquatic environment may be decomposed by abiotic and biotic factors. Photodegradation is the most investigated abiotic process, as it occurs in the natural environment and may be applied in wastewater treatment technology. Although pharmaceuticals are detected in effluents and surface water in a mixture, the photodegradation process is mainly evaluated with single compounds. The photodegradation of fluoxetine (FLU) and fluvoxamine (FLX) in the presence of diclofenac (DCF) and triclosan (TCS) was investigated with HPLC and bioassay. FLU did not degrade under UV-Vis irradiation in SunTest CPS+ either with or without the tested additives, although small amounts of desmethyl fluoxetine and 4-(trifluoromethyl)phenol were formed. In contrast, during irradiation, FLX isomerized to cis-FLX. This process was enhanced by DCF and TCS, but to a lesser degree than by humic acids. Thus, the presence and composition of the matrix should be considered in the environmental risk assessment of pharmaceuticals. As the toxicity of the tested solutions depended only on the concentration of the tested drugs, it was suggested that the biological activity of the photodegradation products was lower than that of the parent compounds.

Quantifying road-deposited sediment (RDS) wash-off is critical in estimating pollutant load and for supporting the designs of urban storm water low-impact development (LID) best management practices (BMPs). The objective of this study was to identify a simple and effective small-scale wash-off load estimation and prediction method suitable for BMP engineering. The reliabilities, complexities, and applicabilities of four prediction methods (i.e., the event mean concentration (EMC) equation method, the exponential equation method, and the RDS mass difference before and after rainfall event method, and the RDS index model) were tested for three sites (i.e., a newly built area, and built-up area, and conservation area) during five natural rainfall events. Taking the calculations by the EMC method as standard results revealed the following. (1) The degree of agreement of the methods with the standard results in descending order was exponential equation method > RDS index model > RDS mass difference. (2) The degree of complexity of the studied methods in descending order was exponential equation method > the EMC equation method > the RDS index model > the RDS mass difference. (3) When considering the applicability of the models in terms of LID-BMP engineering, the RDS index model could be considered optimal for supporting the design of urban storm water BMPs.

Heavy metal distributions in water, sediments, and freshwater shellfish collected from Liuyang River in China have been investigated. The concentrations of heavy metals including Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, and Pb were determined by ICP-MS. The distribution pattern of heavy metals in sediments was different from that in water. Large coefficients of variation of heavy metal concentrations were observed in water due to the susceptibility to discharge fluctuation and seasonal variation. Multivariate statistical analysis such as Pearson’s correlation analysis, hierarchical cluster analysis (HCA), and principal component analysis (PCA) were employed to identify the possible sources of heavy metals in sediments. These heavy metals were categorized into three distinct groups, one was derived from natural existence and two were associated with anthropogenic activities. Five shellfish species including three species of gastropod mollusks (Parafossarulus eximius, Semisulcospira cancellata, and Pomacea canaliculata) and two species of bivalve mollusks (Corbicula fluminea and Anodonta woodiana) were collected and investigated. The distribution pattern of heavy metals in shellfish species was visualized by the nonmetric multidimensional scaling (NMDS) plot. The metal pollution index (MPI) values for the shellfish species were in the descending order of C. fluminea > A. woodiana > S. cancellata > P. eximius > P. canaliculata.

In the context of non-point source pollution management and algal blooms control, the reliable nutrient forecasting is of critical importance. Considering the highly stochastic, non-linear, and non-stationary natures involved in riverine total nitrogen (TN) load time series data, some traditional statistical and artificial intelligence models are inherently unable to give accurate nutrient forecasts due to their mechanism and structure characteristics. In this study, based on the wavelet analysis (WA) and support vector regression (SVR), a promising combined WA-SVR model was proposed for forecasting riverine TN loads. The data pro-processing tool WA was employed to decompose the time series data of riverine TN load for revealing its dominator. Subsequently, all wavelet components were used as inputs to SVR for WA-SVR model. The continuous riverine TN loads during 2004–2012 in the ChangLe River watershed of eastern China were estimated by using a calibrated Load Estimator model. Performance criteria, namely, determination coefficient (R²), Nash-Sutcliffe model efficiency (NS), and mean square error (MSE) were applied to assess the performance of the developed models. The effects of different mother wavelets on the efficiency of the conjunction model were investigated. The results demonstrated that the mother wavelet played a crucial role for the successful implementation of the WA-SVR model. Among the 23 selected mother wavelet functions, dmey wavelet performed best in forecasting the daily and monthly TN loads. Furthermore, the performance of the optimal WA-SVR model was compared with that of single SVR model without wavelet decomposition. The comparison indicated that the hybrid model provided better accuracy than that of single SVR model. For daily riverine TN loads, the R², NS, and MSE values of WA-SVR model during the test stage were 0.9699, 0.9658, and 0.4885 × 10⁷ kg/day, respectively. For monthly riverine TN loads, the R², NS, and MSE values of the model during the test stage were 0.9163, 0.9159, and 0.3237 × 10¹⁰ kg/month, respectively. The overall results strongly suggested that the combined WA-SVR method can successfully forecast riverine TN loads in agricultural watersheds.

Oil meal is a by-product of the oil industry (peanut meal, sesame meal, and camellia meal). Oil is extracted from seeds, and the leftover meal is then pelletized, and this process generates a large amount of waste oil meal in Taiwan. In this study, peanut meal, sesame meal, and camellia meal derived fuels were prepared from the waste oil meal with waste cooking oil. The combustion behaviors of the oil meal derived fuels were also investigated. The characteristics of the derived fuel made from oil meal with waste cooking oil showed that the ash content is less than 10% and its calorific value reached 5000 kcal/kg. Additionally, the activation energy of the oil meal and waste cooking oil was analyzed by the Kissinger method. The results show that the fuel prepared in this work from the oil meal mixed with waste cooking oil is suitable for use as an alternative fuel and also avoids food safety issues.

2,4-Dichlorophenoxyacetic acid is one of the most widely used herbicides. Its impact on health is increasingly attracting great attentions. This study aimed to investigate the effect of 2,4-dichlorophenoxyacetic acid on glucose metabolism in HepG2 cells and the underlying mechanism. After 24 h exposure to 2,4-dichlorophenoxyacetic acid, glycogen was measured by PAS staining and glucose by ELISA in HepG2 cells. The expression of genes involved in glucose metabolism was measured by real-time PCR, Western blotting, and immunofluorescence. HepG2 cells presented more extracellular glucose consumption and glycogen content after exposed to 2,4-dichlorophenoxyacetic acid. Expression of gluconeogenesis-related genes, FoxO1, and CREB is significantly elevated. Moreover, PPARβ was up-regulated dose-dependently. SiRNA knockdown of PPARβ completely rescued the increase of glycogen accumulation and glucose uptake, and the up-regulation of FOXO1 and CREB expression. Our findings propose novel mechanisms that 2,4-dichlorophenoxyacetic acid causes glucose metabolism dysfunction through PPARβ in HepG2 cells.