Search

Fourier-transform infrared spectroscopy (FTIR) serves as a rapid analytical technique to characterize food specimens chemically. The purpose of this study was to investigate the potential of FTIR combined with multivariate statistics to detect Alpha-glucosidase (Alpha-glu) inhibitory activities of a non-cereal flour-like coconut testa flour (CTF). CTF of five distinct local cultivars was sequentially extracted with hexane, ethyl acetate (EtOAc), and methanol (MeOH) to assay the Alpha-glu inhibitory activity. FTIR spectra of CTF extracts were obtained within the range of 4000–500 cm−1 and the prominent spectral peaks obtained for both hexane and EtOAc extracts were roughly similar but some additional peaks were observed in EtOAc extracts representing phenolic constituents. The major absorbance peaks found in MeOH extracts were primarily indicative of the occurrence of the hydroxyl group associated with carbohydrates and phenolic compounds. The multivariate predictive models developed using partial least squares (PLS) and orthogonal partial least squares (OPLS) regression analyses indicated a strong correlation between Alpha-glu inhibitory activity and spectral data. Models developed for the spectral regions 3700–2800 cm−1 and 1800–500 cm−1 exerted the highest regression coefficients with the lowest root mean square errors. In OPLS regression analysis, the model obtained with third-derivative spectral data was identified as the best, exhibiting the highest regression coefficients and the lowest root mean square errors. Both PLS and OPLS regression analyses indicated a potential correlation of Alpha-glu inhibitory activity with FTIR spectral regions. Notably, OPLS models offered enhanced interpretability of the model parameters. This study suggests that the application of multivariate regression analysis of FTIR spectral data on coconut-based products could help to detect Alpha-glu inhibitory activities. [ABSTRACT FROM AUTHOR]

Fourier-transform infrared spectroscopy (FTIR) serves as a rapid analytical technique to characterize food specimens chemically. The purpose of this study was to investigate the potential of FTIR combined with multivariate statistics to detect Alpha-glucosidase (Alpha-glu) inhibitory activities of a non-cereal flour-like coconut testa flour (CTF). CTF of five distinct local cultivars was sequentially extracted with hexane, ethyl acetate (EtOAc), and methanol (MeOH) to assay the Alpha-glu inhibitory activity. FTIR spectra of CTF extracts were obtained within the range of 4000–500 cm−1 and the prominent spectral peaks obtained for both hexane and EtOAc extracts were roughly similar but some additional peaks were observed in EtOAc extracts representing phenolic constituents. The major absorbance peaks found in MeOH extracts were primarily indicative of the occurrence of the hydroxyl group associated with carbohydrates and phenolic compounds. The multivariate predictive models developed using partial least squares (PLS) and orthogonal partial least squares (OPLS) regression analyses indicated a strong correlation between Alpha-glu inhibitory activity and spectral data. Models developed for the spectral regions 3700–2800 cm−1 and 1800–500 cm−1 exerted the highest regression coefficients with the lowest root mean square errors. In OPLS regression analysis, the model obtained with third-derivative spectral data was identified as the best, exhibiting the highest regression coefficients and the lowest root mean square errors. Both PLS and OPLS regression analyses indicated a potential correlation of Alpha-glu inhibitory activity with FTIR spectral regions. Notably, OPLS models offered enhanced interpretability of the model parameters. This study suggests that the application of multivariate regression analysis of FTIR spectral data on coconut-based products could help to detect Alpha-glu inhibitory activities.

• The quality consistency of BZYMP was evaluated using a Comprehensive linear quantitative fingerprint method (CLQFM). • Establishment of three-wavelength fusion fingerprint (TWFP) for comprehensive evaluation of BZYMP. • Establishment of Electrochemical fingerprint. • Constructed OPLS model to predict the antioxidant capacity of BZYMP. • Constructed spectral-effect relationship models for TWFP-ECFP and TWFP- IC 50. Bazhen Yimu Pill (BZYMP) is a concoction of 9 Chinese herbs with pharmacological effects such as vasodilatation, inhibition of platelet aggregation and uterine stimulation. Due to its complex composition and the interaction of multiple chemical components, it presents challenges in quality control. The aim of this study was to construct a fingerprint profile of BAYMP and to conduct a study on the relationship between the fingerprint profile and therapeutic effects. Firstly, 2 fingerprint profiles of BZYMP were established using high performance liquid chromatography (HPLC) and electrochemical analysis. In addition, in order to avoid the incomplete chemical information extracted from a single wavelength, a three-wavelength fusion fingerprint (TWFP) was established and a clear and easy-to-understand electrochemical fingerprint (ECFP) was innovatively established by using electrochemical analysis, and 9 characteristic parameters were recorded. Subsequently, the quality consistency of BZYMP was qualitatively and quantitatively evaluated by the comprehensive linear quantitative fingerprint method (CLQFM) method, while the fingerprint efficacy relationship between the fingerprint peaks of BZYMP and the IC 50 value of the DPPH assay was constructed by the OPLS model, and the relationship between the fingerprint peaks and the electrochemical analyses was explored by using the Pearson correlation coefficient. This study examined BZYMP from two dimensions, quality consistency and efficacy, and provided a new idea for other traditional Chinese medicines and their preparations to realize the dual control of quality and efficacy. [ABSTRACT FROM AUTHOR]

Hydroxyl radicals (·OH) produced in subsurface sediments play an important role in biogeochemical cycles. One of the major sources of·OH in sediments is associated with reduced compounds (e.g., iron and organic matter) oxygenation. Moreover, the properties of iron forms and dissolved organic matter (DOM) components varied significantly across redox-fluctuation zones of estuaries. However, the influence of these variations on mechanisms of·OH production in estuaries remains unexplored. Herein, sediments from riparian zones, wetlands, and rice fields in the Yellow River Estuary were collected to systematically explore the diverse mechanisms of·OH generation. Rhythmic continuous·OH production (82–730 μmol/kg) occurred throughout the estuary, demonstrating notable spatial heterogeneity. The amorphous iron form and humic-like DOM components were the key contributors to·OH accumulation in estuary wetlands and freshwater restoration wetlands, respectively. The crystalline iron form and protein-like DOM components influenced the capabilities of iron reduction and continuous·OH production. Moreover, the orthogonal partial least squares models outperformed various multivariate models in screening crucial factors and predicting the spatiotemporal production of·OH. This study provides novel insights into varied mechanisms of·OH generation within distinct redox-fluctuation zones in estuaries and further elucidates elemental behavior and contaminant fate in estuarine environments. Given that estuaries serve as sinks for anthropogenic pollutants, various organic pollutants (e.g., emerging contaminants such as antibiotics) have been widely detected in estuarine environments. The production of·OH in sediments has been proven to affect the fate of contaminants. Therefore, the varied mechanisms of·OH in estuarine environments, dominated by diverse iron forms and DOM components, were explored in this study. MLR and OPLS models exhibited good performance in screening crucial factors and predicting·OH production. Our work highlights that in estuarine subsurface environments, the presence of·OH potentially leads to a natural degradation of pollutants. [Display omitted] • The generation and mechanism of·OH across varied esutarine redox-fluctuation zones were studied. • The production of·OH exhibited spatial heterogeneities from 82 to 730 μmol/kg. • Amorphous and crystalline iron phases were the key contributor and controller to·OH production. • DOM especially humic-like component was the main electron donor and shuttle in early oxygenation. • Predictive model based on OPLS for·OH production showed satisfactory performance. [ABSTRACT FROM AUTHOR]

Accurate electricity consumption (EC) forecasting is vital for ensuring efficient energy supply and underpinning long-term economic stability. Prior research has often overlooked the intricate interplay between the nuanced dynamics of economic growth and EC. In contrast, this study innovatively incorporates the economic cycle into the analytical framework of EC, providing a more comprehensive perspective. Firstly, we construct the MSAR-OPLS two-step model to discern the factors influencing EC across various cycles. We select the most fitting stabilization cycle as the foundation for forecasting. By integrating both dynamic and static scenario analyses, we offer a comprehensive and precise evaluation of future EC trends. This study ensures both the reliability and accuracy of our forecasts. Projections suggest that China's EC will escalate to 11,780 billion kWh by 2030, reflecting an average annual growth rate of 3.96% from 2023 to 2030. Furthermore, through rigorous robustness and sensitivity analyses, the study validates the forecast's accuracy. Beyond emphasizing the role of economic phases in ensuring energy security, this research furnishes policymakers with insights on embedding foresightful elements into strategic economic and energy planning. • Electricity consumption forecasting is a precondition for power planning. • Include economic cycles in electricity consumption forecasting. • Combine dynamic analysis to establish static forecasts for multiple scenarios. • Prevent power shortages or surpluses through influencing factors identification. [ABSTRACT FROM AUTHOR]