In this research, an electrochemical sensor based on molecularly imprinted polymer (MIP) nanoparticles for selective and sensitive determination of diazinon (DZN) pesticides was developed. The nanoparticles of diazinon imprinted polymer were synthesized by suspension polymerization and then used for modification of carbon paste electrode (CPE) composition in order to prepare the sensor. Cyclic voltammetry (CV) and square wave voltammetry (SWV) methods were applied for electrochemical measurements. The obtained results showed that the carbon paste electrode modified by MIP nanoparticles (nano-MIP-CP) has much higher adsorption ability for diazinon than the CPE based non-imprinted polymer nanoparticles (nano-NIP-CP). Under optimized extraction and analysis conditions, the proposed sensor exhibited excellent sensitivity (95.08 μA L μmol(-1)) for diazinon with two linear ranges of 2.5 × 10(-9) to 1.0 × 10(-7) mol L(-1) (R (2) = 0.9971) and 1.0 × 10(-7) to 2.0 × 10(-6) mol L(-1) (R (2) = 0.9832) and also a detection limit of 7.9 × 10(-10) mol.L(-1). The sensor was successfully applied for determination of diaznon in well water and apple fruit samples with recovery values in the range of 92.53-100.86 %. Graphical abstract Procedure for preparation of electrochemical sensor based on MIP nanoparticles for determination of diazinon.

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The aims of this study were to determine the relationship between saliva and plasma methadone concentrations and the influence of variability in saliva pH. Saliva and plasma samples were taken before the daily dose of methadone in 60 patients undergoing methadone maintenance treatment (MMT). Saliva pH was measured immediately after sampling, and concentrations of (RS)-, (R)-, and (S)-methadone in saliva and plasma were assayed by LC/MS. In addition, unbound (R)- and (S)-methadone concentrations were measured in plasma samples by ultrafiltration. Plasma binding and pH differences between plasma and saliva were then used to estimate methadone saliva/plasma ratios and to compare them with observed values. Saliva pH ranged from 5.1 to 7.6 (mean +/- SD, 6.7 +/- 0.5). Plasma and saliva concentrations correlated weakly [(RS)-, r = 0.14, P = 0.007, n = 44; (R)-, r = 0.10, P = 0.04, n = 43; (S)-, r = 0.22, P = 0.002, n = 43], and the mean saliva-to-plasma methadone concentration ratios were 1.1 (+/-1.3 SD), 1.5 (+/-1.5), and 0.8 (+/-0.8), for (RS)-, (R)-, and (S)-methadone, respectively. Corresponding values based on unbound concentrations of methadone in plasma were 21 (+/-20.6, n = 31), 21 (+/-19, n = 34), and 17 (+/-15, n = 36). The salivary concentration-to-dose ratios showed statistically significant but weak inverse correlations with saliva pH [(RS)-, r = 0.27, P < 0.001; (R)-, r = 0.25, P < 0.001; (S)-, r = 0.29, P < 0.001, respectively]. There were significant correlations between predicted and observed saliva/plasma ratios [(RS)-, r = 0.44, P < 0.001, n = 31; (R)-, r = 0.58, P < 0.001, n = 32; (S)-, r = 0.10, P = 0.04, n = 34], but the mean predicted saliva concentrations were about 5 times lower than the mean observed values. The poor correlations between salivary and plasma methadone concentrations observed in this study are partly related to the effect of variable saliva pH. However, saliva pH explained only 10%-36% of the total variation. As a conclusion, monitoring methadone concentrations in saliva may not be a useful alternative to plasma concentration measurements. Correction for saliva pH measured immediately after collection improves the relationship between saliva and plasma methadone concentration, but most of the variation remains unexplained.

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