Determination of valsartan and pitavastatin using synchronous spectrofluorimetry and augmented least squares chemometric models: A comparative study with greenness and blueness assessment

Hypertension and hyperlipidemia are two common conditions that require effective management to reduce the risk of cardiovascular diseases. Among the medications commonly used for the treatment of these conditions, valsartan and pitavastatin have shown significant efficacy in lowering blood pressure and cholesterol levels, respectively. In this study, synchronous spectrofluorimetry coupled to chemometric analysis tools, specifically concentration residual augmented classical least squares (CRACLS) and spectral residual augmented classical least squares (SRACLS), was employed for the determination of valsartan and pitavastatin simultaneously. The developed models exhibited excellent predictive performance with relative root mean square error of prediction (RRMSEP) of 2.253 and 2.1381 for valsartan and pitavastatin, respectively. Hence, these models were successfully applied to the analysis of synthetic samples and commercial formulations as well as plasma samples with high accuracy and precision. Besides, the greenness and blueness profiles of the determined samples were also evaluated to assess their environmental impact and analytical practicability. The results demonstrated excellent greenness and blueness scores with AGREE score of 0.7 and BAGI score of 75 posing the proposed method as reliable and sensitive approach for the determination of valsartan and pitavastatin with potential applications in pharmaceutical quality control, bioanalytical studies, and therapeutic drug monitoring.

A novel derivative synchronous fluorescence method for the rapid, non-destructive and intuitive differentiation of denitrifying bacteria

It is challenging to differentiate bacteria residing in the same habitat by direct observation. This difficulty impedes the harvest, application and manipulation of functional bacteria in environmental engineering. In this study, we developed a novel method for rapid differentiation of living denitrifying bacteria based on derivative synchronous fluorescence spectroscopy, as exemplified by three heterotrophic nitrification-aerobic denitrification bacteria having the maximum nitrogen removal efficiencies greater than 90%. The intact bacteria and their living surroundings can be analyzed as an integrated target, which eliminates the need for the complex pre-processing of samples. Under the optimal synchronous scanning parameter (Δλ = 40 nm), each bacterium possesses a unique fluorescence spectral structure and the derivative synchronous fluorescence technique can significantly improve the spectral resolution compared to other conventional fluorescence methods, which enables the rapid differentiation of different bacteria through derivative synchronous fluorescence spectra as fast as 2 min per spectrum. Additionally, the derivative synchronous fluorescence technique can extract the spectral signals contributed by bacterial extracellular substances produced in the biological nitrogen removal process. Moreover, the results obtained from our method can reflect the real-time denitrification properties of bacteria in the biological nitrogen removal process of wastewater. All these merits highlight derivative synchronous fluorescence spectroscopy as a promising analytic method in the environmental field.