Integrated chemical characterization, metabolite profiling, and pharmacokinetics analysis of Zhijun Tangshen Decoction by UPLC-Q/TOF-MS.

Diabetic nephropathy (DN) is the main cause of end-stage renal disease worldwide and a major public issue affecting the health of people. Therefore, it is essential to explore effective drugs for the treatment of DN. In this study, the traditional Chinese medicine (TCM) formula, Zhijun Tangshen Decoction (ZJTSD), a prescription modified from the classical formula Didang Decoction, has been used in the clinical treatment of DN. However, the chemical basis underlying the therapeutic effects of ZJTSD in treating DN remains unknown. In this study, compounds of ZJTSD and serum after oral administration in rats were identified and analyzed using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS). Meanwhile, a semi-quantitative approach was used to analyze the dynamic changes in the compounds of ZJTSD in vivo. UPLC-Q/TOF-MS analysis identified 190 compounds from ZJTSD, including flavonoids, anthraquinones, terpenoids, phenylpropanoids, alkaloids, and other categories. A total of 156 xenobiotics and metabolites, i.e., 51 prototype compounds and 105 metabolites, were identified from the compounds absorbed into the blood of rats treated with ZJTSD. The results further showed that 23 substances with high relative content, long retention time, and favorable pharmacokinetic characteristics in vivo deserved further investigations and validations of bioactivities. In conclusion, this study revealed the chemical basis underlying the complexity of ZJTSD and investigated the metabolite profiling and pharmacokinetics of ZJTSD-related xenobiotics in rats, thus providing a foundation for further investigation into the pharmacodynamic substance basis and metabolic regulations of ZJTSD.

Serum Cystatin C is Associated with Depression After Intracerebral Hemorrhage.

Purpose: Cystatins are associated with neuronal degeneration and nervous system healing. Cystatin C (Cys C) has recently been linked to brain injury and immunological inflammation. This study aimed to determine the relationship between serum Cys C levels and depression following intracranial hemorrhage (ICH). Patients and Methods: Between September 2020 and December 2022, 337 patients with ICH were sequentially recruited and followed up for three months. The post-stroke depression (PSD) and non-PSD groups were separated based on the 17-item Hamilton Depression Rating Scale (HAMD). The PSD diagnosis was established based on the DSM-IV criteria. Cys-C levels were documented within twenty-four hours of admission. Results: Three months after ICH, 93 (27.6%) of 337 enrolled patients were diagnosed with depression. The Cys C levels were significantly higher in depressed patients than in nondepressed patients after ICH (1.32 vs 1.01; p<0.001). After adjusting for potential confounding variables, depression after ICH was associated with the highest quartile of Cys C levels (odds ratio (OR) = 3.195, 95% CI: 1.562-6.536; p=0.001). The receiver operating characteristic curve (ROC) curve predicted that the ideal cut-off for CysC levels as a predictor of depression after ICH would be 0.730, resulting in 84.5% sensitivity and 88.4% specificity, with an area under curve (AUC) of 0.880 (95% CI: 0.843-0.917; p< 0.0001). Conclusion: Increased CysC concentrations were independently related to depression three months after ICH, highlighting that CysC levels at admission may be a potential biomarker for predicting the onset of depression following ICH.

Front-face excitation-emission matrix fluorescence spectroscopy combined with interpretable deep learning for the rapid identification of the storage year of Ningxia wolfberry.

Ningxia wolfberry stored for many years may be disguised as fresh wolfberry by unscrupulous traders and sold for huge profits. In this work, the front-face excitation-emission matrix (FF-EEM) fluorescence spectroscopy coupled with interpretable deep learning was proposed to identify the storage year of Ningxia wolfberry in a lossless, fast and accurate way. Alternating trilinear decomposition (ATLD) algorithm was used to decompose the three-way data array obtained by Ningxia wolfberry samples, extracting the chemically meaningful information. Meanwhile, a convolutional neural network (CNN) model for the identification of the storage year of Ningxia wolfberry, called EEMnet, was proposed. The model successfully classified wolfberry samples from different storage years by extracting the subtle feature differences of the spectra, and the correct classification rate of the training set, test set and prediction set was more than 98%. In addition, a series of interpretability analyses were implemented to break the "black box" of the deep learning model. These results indicated that the method based on FF-EEM fluorescence spectroscopy combined with EEMnet could quickly and accurately identify the year of Ningxia wolfberry in a green way, providing a new idea for the identification of the storage years of Chinese medicinal materials.

Human serum lipidomics analysis revealed glyphosate may lead to lipid metabolism disorders and health risks.

Glyphosate-based herbicides (GBH) are one of the most widely used pesticides worldwide. Industrial workers in glyphosate-based herbicides manufacture are the populations who experience long-term exposure to high glyphosate levels. The impacts of glyphosate on human health are the important public health problem of great concern. Up to date, the potential adverse effects of glyphosate on humans or other mammals have been reported in multiple studies. However, limited research is available on lipid alternations related to human exposure to glyphosate. In fact, the perturbations in some lipid metabolisms have been found in industrial workers in previous work. This study aims to explore the serum lipidomic characterization and to understand the underlying mechanisms of health risks associated with glyphosate exposure. A nontargeted lipidomics study was conducted to investigate the 391 serum samples from the general population and chemical factory workers. It was demonstrated that glyphosate caused significant perturbations of 115 differentially expressed lipids. The main manifestations were the elevation of circulating diacylglycerols (DG), cholesteryl esters (CE), ceramides (Cer), sphingomyelins (SM), lysophosphatidylethanolamines (LPE) and phosphatidylcholines (PC), and the decrease of ysophosphatidylcholines (LPC), triacylglycerols (TG), fatty acids (FA) and phosphatidylethanolamines (PE). A total of 88 lipids were further screened as potential lipid biomarkers associated closely with glyphosate using partial correlation analysis, and five of which (including PC 16:0/18:2; O, PC 18:0/18:2; O, PC 18:0/20:4; O, PC O-40:9 and CE 18:3) showed excellent superior performance (AUC = 1) to evaluate and monitor health risks due to glyphosate exposure. The present work discovered glyphosate-induced potential health risks, including chronic hepatic and renal dysfunction, atherosclerosis, cardiovascular disease and neurodegenerative diseases from a lipidomic perspective, and could inform the identification of early indicators and interpretation of biological mechanisms to detect health risks of the glyphosate-exposed populations as early as possible.

Progressive ataxia of cerebrotendinous xanthomatosis with a rare c.255+1G>T splice site mutation: A case report.

BACKGROUND: Cerebrotendinous xanthomatosis is an autosomal recessive disorder of lipid metabolism caused by the mutation of the CYP27A1 gene encoding sterol 27-hydroxylase, an essential enzyme for the conversion of cholesterol to chenodeoxycholic and cholic acids. Cerebrotendinous xanthomatosis is a rare neurological disease with a wide range of clinical symptoms that are easily misdiagnosed. CASE SUMMARY: Here we report the clinical, biochemical, and molecular characterization of a 33-year-old female patient with cerebrotendinous xanthomatosis. The patient developed ataxia and had the typical symptoms of juvenile cataracts, tendon xanthomata, and progressive nervous system dysfunction. Magnetic resonance imaging of the brain revealed bilateral dentate nucleus lesions and white matter abnormalities. This patient was misdiagnosed for 2 years resulting in severe neurological complications. After 2 years of chenodeoxycholic acid treatment, she still presented with ataxia and dysarthria. The pathogenic sites of CYP27A1 were identified as c.255+1G>T and c.1263+1G>T, which were both caused by shear denaturation. CONCLUSION: Cerebrotendinous xanthomatosis requires a multidisciplinary diagnosis that must be made early to avoid progressive neurological degeneration. c.1263+1G>T is a known mutation, but c.255+1G>T is a rare mutation site.

Discovery of potential active ingredients of Er-Zhi-Wan, a famous traditional Chinese formulation, in model rat serum for treating osteoporosis with kidney-yin deficiency by UPLC-Q/TOF-MS and molecular docking.

Er-Zhi-Wan (EZW), a classical traditional Chinese formulation, has attracted more and more attention. This study was carried out to analyze the constituents of EZW absorbed into blood and find out the potential active ingredients for treating osteoporosis (OP) with kidney-yin deficiency (KYD). The rat model of OP with KYD was achieved by ovariectomies and using the mixture of thyroxine and reserpine. Then ultra-high performance liquid chromatography coupled with a quadrupole time-of-flight mass spectrometer (UPLC-Q/TOF-MS) combined with statistical analysis was used to analyze the constituents of EZW absorbed into blood and differential components between the normal and OP with KYD rats. Finally, the components identified in OP with KYD rats were docked with targets of OP with KYD found in online databases. The results of molecular docking were adopted to find the potential active ingredients and further verified in vitro experiment. A total of 21 prototype compounds and 69 metabolites were identified in serum. Among them, 63 components in model rats and 50 components in normal rats were summarized, respectively. Most of the identified metabolites in serum of model rats were produced by hydrolysis, oxidation or glucuronidation, while in serum of normal rats were produced by hydrolysis, oxidation and methylation. According to the results of molecular docking, specnuezhenide, salidroside, tyrosol, echinacoside and verbascoside could be classified as potential active ingredients. The activity of salidroside and a metabolite was verified by pharmacodynamics analysis. In summary, UPLC-Q/TOF-MS system was combined with molecular docking to search the potential active ingredients from model rats of OP with KYD, which provided a new idea for the research on the pharmacodynamic material basis of other traditional medicine. Moreover, the result of this study lays the foundation for further study regarding the mechanism of EZW in treating OP with KYD.

Analysis of active compounds and geographical origin discrimination of Atractylodes macrocephala Koidz. by using high performance liquid chromatography-diode array detection fingerprints combined with chemometrics.

In this work, a simple and effective strategy for the determination of 12 active compounds of Atractylodes macrocephala Koidz. (AM) was proposed by using high performance liquid chromatography-diode array detection (HPLC-DAD) combined with alternating trilinear decomposition (ATLD) algorithm. Utilizing the "second-order advantage", three common problems in HPLC could be resolved, namely baseline drifts, peak overlaps, and unknown interferences. 12 compounds were rapidly eluted within 12.5 min, and the average spiked recoveries were 80.8-109.9%. The figures of merit reflected the feasibility of the proposed method. Compared with the results of the traditional univariate calibration method based on HPLC-UV technique, the proposed strategy further verified the reliability and simplicity of the mathematical separation. On this basis, partial least squares-discriminant analysis (PLS-DA) was applied to discriminate 113 AM samples from different geographical origins, and variable importance in projection (VIP) was used to further screen the main differential components that affect the regional division of AM. A series of results show that the AM samples from the three regions have obviously different clustering trends. Overall, the strategy is expected to provide a scientific basis for the modern research of medicinal materials, and it is also conducive to the clinical use and market supervision of AM.

Salidroside protects against osteoporosis in ovariectomized rats by inhibiting oxidative stress and promoting osteogenesis via Nrf2 activation.

BACKGROUND: Osteoporosis (OP) is characterized as low bone mass, bone microarchitecture breakdown and bone fragility. The increase of oxidative stress could lead to breakdown in the balance of bone formation and resorption which gives rise to OP. Nrf2 is a transcription factor which takes part in oxidative stress and recently was reported that it can regulate the occurrence of OP. Salidroside (SAL) with the efficacies of anti-oxidation, anti-aging and bone-protection is one of the active ingredients in Ligustri Lucidi Fructus, a traditional Chinese medicinal herb. Nevertheless, few studies have explored the potential mechanism of SAL preventing OP development from the perspective of oxidative stress intervention. PURPOSE: This study aimed to investigate the pharmacological effect and molecular mechanisms of SAL on OP. STUDY DESIGNS AND METHODS: A tert-butyl hydroperoxide (t-BHP)-induced oxidative stress model was applied for investigating the effects of SAL in vitro, and an ovariectomized (OVX) model was used for in vivo study on the effect of SAL for OP. Related pharmacodynamic actions and molecular mechanisms of SAL were explored in both rat osteoblasts (ROBs) and OVX rats. Network biology and cell metabolomics were performed for further investigating the correlation and association among potential biomarkers, targets and pathways. RESULTS: SAL reduced levels of ROS and lipid peroxidation (LPO), increased activities of antioxidant enzymes like GPx and SOD, and enhanced osteogenic differentiation in t-BHP-induced ROBs and OVX rats. Mechanistic studies showed SAL prevented OP development and reduced oxidative damage in ROBs and OVX rats through up-regulating Nrf2 expression and facilitating its nuclear translocation. The joint analysis of network biology and cell metabolomics revealed that galactose metabolism and fatty acid metabolism could be the major influenced pathways following treatment with SAL. CONCLUSION: SAL could protect against OP by inhibiting oxidative stress, promoting osteogenesis through the up-regulation of Nrf2 and intervening galactose metabolism and fatty acid metabolism. Our study implied that SAL may be a potential drug to treat OP.

The study of human serum metabolome on the health effects of glyphosate and early warning of potential damage.

Glyphosate is one of the most widely used herbicide with high efficiency, low toxicity and broad-spectrum. In recent decades, increasing evidence suggests that glyphosate may cause adverse health effects on human beings. However, until now, there is little data on the human metabolic changes. Since occupational workers are under greater health risks than ordinary people, the understanding regarding the health effects of glyphosate on occupational workers is very important for the early warning of potential damage. In this study, serum metabolic alterations in workers from three chemical factories were analyzed by gas chromatography-mass spectrometry (GC-MS) to assess the potential health risks caused by glyphosate at the molecular level. It was found that the levels of 27 metabolites changed significantly in the exposed group compared to the controls. The altered metabolic pathways, including amino acid metabolism, energy metabolism (glycolysis and TCA cycle) and glutathione metabolism (oxidative stress), etc., indicated a series of changes occur in health profile of the human body after glyphosate exposure, and the suboptimal health status of human may further evolve into various diseases, such as Parkinson's disease, renal and liver dysfunction, hepatocellular carcinoma, and colorectal cancer. Subsequently, 4 biomarkers (i.e., benzoic acid, 2-ketoisocaproic acid, alpha-ketoglutarate, and monoolein) were identified as potential biomarkers related to glyphosate exposure based on the partial correlation analyses, linear regression analyses, and FDR correction. Receiver-operating curve (ROC) analyses manifested that these potential biomarkers and their combinational pattern had good performance and potential clinical value to assess the potential health risk associated with glyphosate exposure while retaining high accuracy. Our findings provided new insights on mechanisms of health effects probably induced by glyphosate, and may be valuable for the health risk assessment of glyphosate exposure.

Geographical origin traceability of traditional Chinese medicine Atractylodes macrocephala Koidz. by using multi-way fluorescence fingerprint and chemometric methods.

Atractylodes macrocephala Koidz. (AM) is an important plant of traditional Chinese medicine (TCM), and its status can be comparable with ginseng in China. The efficacy and quality of AM are closely related to the place of origin. Hence, we proposed a simple and fast strategy to classify AM from different geographical origins by using multi-way fluorescence fingerprint combined with chemometric methods. AM samples with different dilution levels have different fluorescence characteristics, resulting from different content of fluorescence components and chemical microenvironment. Therefore, AM samples were diluted 5-fold, 10-fold, and 20-fold with 40% ethanol aqueous solution to obtain excitation-emission matrix data, and multi-way (three-way and four-way) data arrays were constructed. And then, the fluorescence fingerprints of AM samples were characterized by three-way and four-way parallel factor analysis (PARAFAC). In addition, four pattern recognition methods were used to classify AM from different provinces. The results show that the four-way data array can provide more abundant information than three-way data arrays, so it is more conducive to sample classification. According to the results obtained from the analysis of four-way data array, the correct classification rate (CCR) of the cross-validation and prediction set obtained by partial least squares-discrimination analysis (PLS-DA) were 90.5% and 100%, respectively. To sum up, the proposed method can be regarded as a powerful, feasible, convenient, reliable, and universal classification tool for the classification of AM samples from different provinces and can be used as a promising method to realize the geographical origin traceability of other TCMs.

Quantitative analysis of carbaryl and thiabendazole in complex matrices using excitation-emission fluorescence matrices with second-order calibration methods.

In this paper, a fast and efficient analytical strategy was proposed that chemometrics assisted with excitation-emission fluorescence matrices was used to quantify carbaryl (CAR) and thiabendazole (TBZ) in peach, soil and sewage. Even if there are serious overlapped peaks and unknown interferences in fluorescence analysis, the second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm can be used to analyze CAR and TBZ in peach, soil and sewage. The recoveries of CAR and TBZ in peach are 110.4% and 99.7% and their standard deviations are lower than 2.1% and 0.3%, respectively. In addition, the accuracy of the method was assessed with figures of merit as well as intra-day and inter-day precision. The limit of detection, the limit of quantitation of CAR and TBZ in peach are 1.2 ng mL-1 and 0.3 ng mL-1, 3.5 ng mL-1 and 0.8 ng mL-1, respectively. And their root-mean-square error of prediction are 17.0 ng mL-1 and 5.0 ng mL-1 and there are high sensitivity and selectivity in this method. Meanwhile, the results obtained by ATLD algorithm were compared with those obtained by the self-weighted alternate trilinear decomposition algorithm (SWATLD) and the parallel factor analysis (PARAFAC) algorithm, and statistical methods such as the t-test, F-test and the elliptic joint confidence region were used to evaluate for analysis. There were no significant differences among these methods. At last, high performance liquid chromatography-fluorescence detector (HPLC-FLD) was used to evaluate the accuracy and reliability of the proposed method. These results are satisfactory and indicate that the proposed method can be used for accurate and rapid determination of pesticides in complex systems.

Association of Versican Gene Polymorphisms with Intracranial Aneurysm Susceptibility in the Eastern Chinese Population.

OBJECTIVE: The proteoglycan versican (VCAN) plays an important role in extracellular matrix (ECM) assembly, and diminished maintenance of the ECM has been increasingly regarded as an important factor in the development of intracranial aneurysms (IAs). Previous studies have revealed that single-nucleotide polymorphisms (SNPs) of the VCAN gene are associated with susceptibility to IAs in European or Japanese populations. However, the association between IA susceptibility and VCAN SNPs in the Eastern Chinese population remains unclear. This study aimed to investigate the associations of the SNPs rs251124, rs2287926, and rs173686 with IA susceptibility in the Eastern Chinese population. METHODS: A total of 162 patients with IA and 182 controls were enrolled in this study. The study was conducted between January 2017 and December 2020. SNP genotyping for rs251124, rs2287926, and rs173686 was performed using Kompetitive Allele Specific PCR (KASP) after DNA extraction. The SNP data were analysed with CFX Manager Software version 3.1 (Bio-Rad). RESULTS: rs251124 and rs173686 were significantly associated with susceptibility to IA. The frequency of rs251124-TT in IA was higher than in controls (OR =1.26, 95% CI: 1.07-1.49; P<0.01), and its risk mainly came from the T allele. Furthermore, logistic regression analysis showed that the T/T genotype and T allele of rs251124 were independent risk factors for IA (OR=1.726, 95% CI: 1.136-2.263; P=0.011). Moreover, the G/G genotype and G allele of rs173686 were associated with increased IA susceptibility (OR=2.52, 95% CI: 1.261-5.037; P=0.009). CONCLUSION: The SNPs rs251124 and rs173686 were strongly associated with genetic susceptibility to IA in the Eastern Chinese population; however, no such association was found in the SNP rs2287926 of VCAN. Our findings suggest that the VCAN gene is an IA susceptible gene that should be further studied as a screening marker for IAs.

Simultaneous determination of nine tyrosine kinase inhibitors in three complex biological matrices by using high-performance liquid chromatography-diode array detection combined with a second-order calibration method.

An intelligent chemometric second-order calibration method called alternating trilinear decomposition- assisted multivariate curve resolution combined with high-performance liquid chromatography-diode array detection was used for the simultaneous quantification of nine tyrosine kinase inhibitors in three complex biological systems. The method allows simultaneous quantification of the components in different biological matrices without the need for cumbersome pre-treatment steps, complex elution conditions, and complete peak separation. Even with the varying time shift, severe peak overlap, and various unknown interferences, the proposed method can extract pure chromatographic and spectroscopic information for each analyte, while providing accurate qualitative and quantitative results of nine common tyrosine kinase inhibitors in three different biological matrices. All the drugs were eluted in 7 min. The results showed that the nine drugs in each matrix showed good linearity (r > 0.984) in the calibration range with a root mean square error of calibration less than 0.9 µg/mL. The average spiked recoveries of the target analytes were all in the range of 83.4-110.0%, with standard deviations less than 9.0%. Finally, the classical method was used to validate the proposed method. In comparison to the traditional method, the proposed strategy is accuracy, simultaneous, and interference-free.

Three efficient chemometrics assisted fluorimetric detection methods for interference-free, rapid, and simultaneous determination of ibrutinib and pralatrexate in various complicated biological fluids.

In this study, a series of green, interference-free fluorimetric detection methods of the excitation-emission matrix coupled with the second-order calibration methods were proposed for the determination of ibrutinib and pralatrexate in various complicated biological fluids. The second-order advantage of the proposed method can overcome the problem of poor selectivity caused by the wide spectra of the fluorescence method. Even in the presence of uncalibrated interferences and severe peak overlap, the signal of pure substance and accurate quantitative results were still obtained. The average recoveries of the three methods were 94.5-104.9% for Alternating Trilinear Decomposition (ATLD) algorithm, 95.5-105.8% for Alternating Normalization Weighted Error (ANWE) algorithm and 94.4-105.7% for Parallel Factor Analysis (PARAFAC) algorithm, respectively. For ATLD, ANWE and PARAFAC, the relative standard deviations (RSD) were lower than 9.2%, 6.8% and 9.2%, and the RMSEPs were less than 8.1, 8.4 and 8.6 ng mL-1, respectively. In addition, the elliptic joint confidence region (EJCR) was adopted to further prove the accuracy of the three methods. The results showed that the three methods can accurately be quantified without significant difference. Good figures of merit parameters were also obtained. Among them, the limit of detection (LOD) and limit of quantification (LOQ) of ibrutinib and pralatrexate were in the range of 0.11-0.76 ng mL-1 and 0.21-1.12 ng mL-1, respectively, which were lower than the corresponding blood concentrations. These results indicate that the proposed method provides a promising, alternative and universal analysis strategy for clinical drug monitoring.

Comparison of three chemometric methods for processing HPLC-DAD data with time shifts: Simultaneous determination of ten molecular targeted anti-tumor drugs in different biological samples.

Three intelligent chemometric multi-way calibration methods including alternating trilinear decomposition (ATLD), alternating trilinear decomposition assisted multivariate curve resolution (ATLD-MCR) and multivariate curve resolution-alternating least squares (MCR-ALS) combined with high performance liquid chromatography-diode array detection (HPLC-DAD) were used to quantify ten molecular targeted anti-tumor drugs in three complex biological matrices (plasma, urine and cell culture media matrices). All analytes can be successfully eluted in 6.5 min. In this experiment, various degrees of time shifts occurred in different samples. While slight time shifts exist in the chromatographic analysis, satisfactory results can be obtained by the three proposed methods. When the time shift was large (5.6 s), the average spiked recoveries obtained by ATLD analysis were in the range of 58.9%-116.5%, which was less than satisfactory. However, the average recoveries obtained by MCR-ALS and ATLD-MCR analysis were 89.8%-114.8% and 84.5%-106.1% respectively, and more satisfactory results were obtained. For further research, ATLD-MCR and MCR-ALS methods were compared, and the results were evaluated by statistical tests. Accuracies of concentrations obtained by them were considered to be no significant difference. In addition, compared with other methods currently published, the proposed chemometric methods combined with the HPLC-DAD can rapidly, simultaneously and accurately determine varieties of molecular targeted anti-tumor drugs in different complex biological matrices even in the presence of severe peak overlaps, severe time shifts, slight baseline drifts and different unknown background interferences.

Rapid and simultaneous determination of three fluoroquinolones in animal-derived foods using excitation-emission matrix fluorescence coupled with second-order calibration method.

The matter of fluoroquinolone residues in various foods still arouses wide public concern nowadays. In the present work, the strategy of excitation-emission matrix (EEM) fluorescence data coupled with second-order calibration method based on alternating normalization-weighted error (ANWE) algorithm was used to determine ofloxacin, lomefloxacin and ciprofloxacin in milk powder, milk and beef. Owning the unique "second-order advantage", the ANWE-assisted analytical method was proved to successfully and eco-friendly resolve the overlapped fluorescence spectra of multi-component in complex food matrixes without tedious pretreatment steps and sophisticated high-cost instrumentations. The feasibility of the proposed method was validated by experiments. The average spiked recoveries of three fluoroquinolones range from 82.6% to 110.5% with relative standard deviations lower than 7.4%, and the limits of detection range from 0.18 and 2.41 ng mL-1. For further evaluation, analytical figures of merit such as sensitivity and selectivity, as well as the RSDs of intra-day (≦10.6%) and inter-day (≦9.4%) were calculated. The satisfactory analytical results demonstrated that the proposed strategy could be a competitive alternative for simple, rapid and simultaneous determination of multiple fluoroquinolones in animal-derived food samples.

Simultaneous and fast determination of bisphenol A and diphenyl carbonate in polycarbonate plastics by using excitation-emission matrix fluorescence couples with second-order calibration method.

A new strategy for the determination of bisphenol A (BPA) and diphenyl carbonate (DPC) in polycarbonate plastics has been proposed, combing excitation-emission matrix fluorescence and second-order chemometrics methods. The studied compounds are two of the most frequently used chemical raw materials and intermediates, which is mainly used for bio-chemical products. The method is fast and sensitive as it can avoid tedious pretreatment steps and large amounts of organic solvents consumption. Chemometrics allowed accurate and precise quantification of two target analytes even in the presence of severe spectral overlap, unknown and background interferences, which benefit from "second-order advantages" provided by chemometrics multivariate calibration. Reasonable quantification results were obtained in real plastics samples, with limits of detection for two analytes were 0.04 and 1.18 × 103 ng mL-1 and limits of quantitation were 0.11 and 3.58 × 103 ng mL-1. In addition, the average recoveries for BPA and DPC were 99.35% and 83.50% with relative standard deviation <2.30%. It was proved that the proposed method can be a useful and sensitive tool to the determination of BPA and DPC in different polycarbonate plastics with a simple sample pretreatment at low cost.

Rapid, simultaneous and interference-free determination of three rhodamine dyes illegally added into chilli samples using excitation-emission matrix fluorescence coupled with second-order calibration method.

In this study, a smart and green analytical method based on the second-order calibration algorithm coupled with excitation-emission matrix (EEM) fluorescence was developed for the determination of rhodamine dyes illegally added into chilli samples. The proposed method not only has the advantage of high sensitivity over the traditional fluorescence method but also fully displays the "second-order advantage". Pure signals of analytes were successfully extracted from severely interferential EEMs profiles via using alternating trilinear decomposition (ATLD) algorithm even in the presence of common fluorescence problems such as scattering, peak overlaps and unknown interferences. It is worth noting that the unknown interferents can denote different kinds of backgrounds, not only refer to a constant background. In addition, the method using interpolation method could avoid the information loss of analytes of interest. The use of "mathematical separation" instead of complicated "chemical or physical separation" strategy can be more effective and environmentally friendly. A series of statistical parameters including figures of merit and RSDs of intra- (≤1.9%) and inter-day (≤6.6%) were calculated to validate the accuracy of the proposed method. Furthermore, the authoritative method of HPLC-FLD was adopted to verify the qualitative and quantitative results of the proposed method. Compared with the two methods, it also showed that the ATLD-EEMs method has the advantages of accuracy, rapidness, simplicity and green, which is expected to be developed as an attractive alternative method for simultaneous and interference-free determination of rhodamine dyes illegally added into complex matrices.