Stochastic dynamics mass spectrometric quantification and 3D molecular structural analysis of tricyclic antidepressant in marine dissolved organic matter.

Abstract

Antidepressants show widespread administration and higher market demand causing for their increasing concentrations in the environment; thus, highlighting the aquatic systems. This further leads to synergistic effects when antidepressants and metal ions interact simultaneously on free-living aquatic organisms. Therefore, the monitoring of the environmental pollution by antidepressants is imperative to develop proper management strategies for eco-toxicological human health risk assessment. The study applies innovative stochastic dynamics equations for exact processing of mass spectrometric variables to (i) identify and quantify carbamazepine, amitriptyline, and scandoside in marine dissolved organic matter in presence of their oxidized products and complex sample matrix effect; and (ii) determine them 3D molecular structurally; thus, increasing the selectivity and sensitivity of the mass spectrometric protocol. The development of novel methods for mass spectrometric quantitative and structural analysis is of significant importance. Available methods for database matching algorithms and standard spectral library show low cosine similarity values (0.8-0.88) due to the fact that marine organic matter is the most complex natural chemical mixture reducing the method performances of the available protocols. The routinely used selected reaction monitoring approach detecting only analytes of interest could not detect interfering antidepressants due to their environmental chemical transformation. Furthermore, there is difference in retention times ΔRTs = 0.05 min; thus, also presenting reliable co-chromatographic analysis. There are utilised ultra-high resolution electrospray ionization mass spectrometric and co-chromatographic methods, high accuracy computational quantum chemical approaches, and chemometrics. The provided empirical proof of the novel tool using the linear equation D^"_SD = f(conc.), which drastically assists capability and performances of the analytical mass spectrometry; furthermore, at very low concentration levels within 0.28 ng L^-1-1 ng.(mL^-1). The quantification of carbamazepine in wastewater waste water effluent via traditional methods show |r|= 0.99448, while the application to the novel formulas D^''_SD = f(conc.) cause for |r|= 0.99961 within linear dynamic range 5-200 ng mL^-1. The method is accurate showing parameters 237.1764; sd(yEr ±) = 0-0.01356, and se(yEr ±) = 0-0.00959 depending on the sample matrix effect. It is also precise, showing m/z 237.2₆₇ ± 0.088 and m/z 194.21₉₁₃ ± 0.03842 via single and tandem operation modes. The chromatographic performances show RT = 18.32₈, sd(yEr ±) = 0.013, and se(yEr ±) = 0.0075. The sample matrix effect is evaluated via pre- and post extraction spike data both using selected reaction monitoring and full scan operation modes. Two approaches assessing the matrix effect are discussed. The quantitative determining and 3D structural analysis of species within the innovative approach assessing the relation D^''_SD = f(D_QC) shows the following performances: |r|= 0.99797 (carbamazepine), |r|= 0.99962 (scandoside), and |r|= 0.99999 (amitriptyline) in marine organic matter, respectively. The study solves the most enduring problem of monitoring of pharmaceutics pollution causing for eco-toxicological and human health risk of antibiotic resistance and affect on microbial communities; thus, illustrating best performances reported, so far of |r|= 0.99999-0.99962 via innovative stochastic dynamics equations for exact processing of mass spectrometric variables and obtaining of highly reliable quantitative and 3D structural analyses of degradation and synthetic carbamazepines exhibiting diverse oxidized products at very low analyte concentrations within 0.28 ng L^-1-1 ng.(mL^-1) in marine organic matter which is the most complex natural chemical mixture.