Occurrence and removal of psychiatric pharmaceuticals in the Tehran South Municipal Wastewater Treatment Plant.

Psychiatric drugs released by humans in wastewater have received more attention because of their potential risks for aquatic organisms. In this study, the occurrence of the two most common groups of psychiatric drugs (sedatives-hypnotics-anxiolytics and antidepressants) were evaluated in the Tehran South Municipal Wastewater Treatment Plant. All the target sedatives-hypnotics-anxiolytics (alprazolam, phenobarbital, and thioridazine) and antidepressants (fluoxetine, citalopram, sertraline, and venlafaxine) were observed in influent and secondary clarification (SC) effluent. Thioridazine (164.25 ± 218.74 ng/L) and citalopram (672.53 ± 938.56 ng/L) had the highest mean concentrations in the influent, while alprazolam (5.09 ± 2.33 ng/L) and citalopram (776.97 ± 1088.01 ng/L) had the highest concentrations in the SC effluent. The higher concentrations of the psychiatric drugs, except thioridazine, were detected in the SC effluent compared to the concentrations in the influent. The increased drugs concentrations, with negative removal efficiencies, were more distinctive in the cold season samples. Psychiatric drugs processed in the chlorination unit followed a completely different pattern compared to the drugs in the biological treatment unit. All the drugs' concentrations, except thioridazine, decreased in the chlorination unit, ranging between 27 ± 14% for alprazolam and 75 ± 10% for citalopram. However, the mean concentrations of the detected drugs were as follows: sertraline (11.96 ± 11.62 ng/L) and venlafaxine (184.94 ± 219.74 ng/L) which could cause environmental and ecological concerns.

Metabolomic study of serum in patients with invasive ductal breast carcinoma with LC-MS/MS approach.

BACKGROUND: Invasive ductal carcinoma (IDC) is the most common type of breast cancer so its early detection can lead to a significant decrease in mortality rate. However, prognostic factors for IDC are not adequate and we need novel markers for the treatment of different individuals. Although positron emission tomography and magnetic resonance imaging techniques are available, they are based on morphological features that do not provide any clue for molecular events accompanying cancer progression. In recent years, "omics" approaches have been extensively developed to propose novel molecular signatures of cancers as putative biomarkers, especially in biofluids. Therefore, a mass spectrometry-based metabolomics investigation was performed to find some putative metabolite markers of IDC and potential metabolites with prognostic value related to the estrogen receptor, progesterone receptor, lymphovascular invasion, and human epidermal growth factor receptor 2. METHODS: An untargeted metabolomics study of IDC patients was performed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The multivariate principal component analysis by XCMS online built a model that could separate the study groups and define the significantly altered m/z parameters. The most important biological pathways were also identified by pathway enrichment analysis. RESULTS: The results showed that the significantly altered metabolites in IDC serum samples mostly belonged to amino acids and lipids. The most important involved pathways included arginine and proline metabolism, glycerophospholipid metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. CONCLUSIONS: Significantly altered metabolites in IDC serum samples compared to healthy controls could lead to the development of metabolite-based potential biomarkers after confirmation with other methods and in large cohorts.

Direct analysis of six antibiotics in wastewater samples using rapid high-performance liquid chromatography coupled with diode array detector: a chemometric study towards green analytical chemistry.

In this work, a rapid HPLC-DAD method has been developed for the analysis of six antibiotics (amoxicillin, metronidazole, sulfamethoxazole, ofloxacine, sulfadiazine and sulfamerazine) in the sewage treatment plant influent and effluent samples. Decreasing the chromatographic run time to less than 4 min as well as lowering the cost per analysis, were achieved through direct injection of the samples into the HPLC system followed by chemometric analysis. The problem of the complete separation of the analytes from each other and/or from the matrix ingredients was resolved as a posteriori. The performance of MCR/ALS and U-PLS/RBL, as second-order algorithms, was studied and comparable results were obtained from implication of these modeling methods. It was demonstrated that the proposed methods could be used promisingly as green analytical strategies for detection and quantification of the targeted pollutants in wastewater samples while avoiding the more complicated high cost instrumentations.

Fast HPLC-DAD quantification procedure for selected sulfonamids, metronidazole and chloramphenicol in wastewaters using second-order calibration based on MCR-ALS.

The present work focuses on the application of multivariate curve resolution-alternating least squares (MCR-ALS) for analysis of five important antibiotics (sulfamethoxazole, metronidazole, chloramphenicol, sulfadizine and sulfamerazine) in highly complex wastewater samples, using solid phase extraction (SPE)-high performance liquid chromatography with diode-array detection (HPLC-DAD) on a short column, regarding the fast elution methodology. The samples were pre-concentrated on Bond Elut-ENV cartridges and separated on an ODS column (7 cm) in less than 4 min using an isocratic mode of elution with methanol-water (55:45, v/v) at pH=3.2. Due to the matrix interferences and the resulting sensitivity changes, a strategy implementing standard addition calibration in combination with MCR/ALS algorithm was applied. In this paper, the signal corresponding to background contribution was considered as a systematic part of the model during MCR/ALS data processing, so the background correction step was not necessary. The qualitative and quantitative results showed that the application of MCR/ALS algorithm in the traditional chromatographic method was appropriately able to resolve highly drifted background constituents as well as heavily overlapped peaks among the analytes and also between the analytes and the matrix interferences. Recoveries were ranged from 69.6% to 120.3% with relative standard deviations of less than or equal to 11.0% and showed the acceptable performance of the method. Additionally, statistical t-test as well as computed elliptical joint confidence region (EJCR) confirmed the accuracy of the proposed method and indicated the absence of both constant and proportional errors in the predicted concentrations. The results well explained that the second-order advantage for analytes was achieved in samples containing one or more uncalibrated components, which strongly related to wastewater samples.