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In this work, a high-performance liquid chromatography-diode array detection (HPLC-DAD) method combined with chemometrics was developed for differentiating geographical origins of Chinese red wines. Phenolic compounds were firstly detected and quantified by direct injection HPLC-DAD method in thirty red wines originated from two famous wine-growing regions in China. Given the high complexity of the wine samples and the co-elution problems during chromatographic separation, multivariate curve resolution-alternating least squares (MCR-ALS) was utilized to extract pure chromatographic and spectral profiles of each co-eluted compound. Quantification of phenolic compounds was thus achieved even in the presence of overlapping peaks and uncalibrated interferents. The quantitative data of the phenolic compounds in wines provided by the MCR-ALS algorithm were afterwards analyzed by unsupervised principal component analysis (PCA) and hierarchical cluster analysis (HCA) methods and supervised orthogonal partial least squares-discrimination analysis (OPLS-DA) method. Both PCA and HCA results showed that the thirty red wines from different geographical origins could be obviously distinguished, and the OPLS-DA could successfully predict the geographical origins of red wines. This study demonstrated that the HPLC-DAD method combined with chemometrics can be used as an effective tool for differentiating geographical origins of Chinese red wines on the basis of phenolic compounds.

Chrysanthemum morifolium Ramat cv. "Hangbaiju" (HBJ), known as one of the "eight flavors of Zhejiang", is commonly used as a classical tea material for both food and medicine over three thousand years in China. The quality of HBJ is closely related to its geographical origins. However, the mechanism underlying the geographical differences of HBJ remains to be elucidated. In this study, an untargeted metabolomic strategy based on UHPLC-QTOF-MS was established to discover the differential metabolites in HBJ samples from four different origins and explore the possible relationship with mineral elements in planting soils by chemometric analysis. Eight compounds were screened and identified as the key differential metabolites in HBJ samples from different origins. Among them, four important pharmacodynamic compounds including L-arginine, rutin, chlorogenic acid and apigenin-7-O-glucoside are the most abundant in HBJ samples from Tongxiang region, which suggests that HBJ planted in Tongxiang has higher medicinal values. Pearson correlation analysis revealed that the contents of soil mineral elements are positively correlated with those of chlorogenic acid, rutin, apigenin-7-O-glucoside in HBJ samples. Furthermore, an interrelationship model based on random forest algorithm was established to successfully predict the contents of differential metabolites in HBJ samples by soil mineral elements. All these results indicated that the contents of differential metabolites in HBJ samples seemed to be affected by soil mineral elements and therefore resulted in the geographical differences of HBJ.

Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.

In this paper, an excitation-emission matrix (EEM) fluorescence spectroscopy method coupled with two kinds of multi-way classification algorithms was developed for the identification of the adulteration of Shanxi aged vinegars. The first classification model was built from selective information provided by parallel factor analysis (PARAFAC) based on partial least squares-discriminant analysis (PLS-DA) algorithm and the other one was modeled based on strictly multi-way classification algorithm multi-way partial least squares-discriminant analysis (N-PLS-DA). Both classification models showed good clustering tendency for authentic and adulterated Shanxi aged vinegars. Compared with the PARAFAC-PLS-DA method, more accurate and reliable classification results were provided by the N-PLS-DA method because it is a strictly multi-way classification method and can make the utmost use of the EEM fluorescence information of the vinegar samples. The N-PLS-DA model constructed from the EEM spectra enabled the recognition of adulterated samples with accurate rate of 100% both in training and prediction sets and obtained maximum sensitivity and specificity. This study showed that EEM fluorescence spectroscopy combined with multi-way classification algorithm N-PLS-DA could be used as a good method for the identification of the adulteration of Shanxi aged vinegar samples.

In this work, nitrogen doped carbon dots (NCDs) were synthesized through one step hydrothermal reaction using citric acid and ethylenediamine as precursors. The prepared NCDs exhibit high quantum yield of 67.4%, good stability, excellent selectivity and sensitivity. It was found that the NCDs have potential as a fluorescence sensor for the detection of Hg

BACKGROUND Patients with schizophrenia have an increased prevalence of type 2 diabetes mellitus that has shown a significant association with the rs7754840 polymorphism in the gene encoding the cyclin-dependent kinase 5 (CDK5) regulatory subunit-associated protein 1-like 1 (CDKAL1). OBJECTIVE To examine whether this polymorphism was involved in the susceptibility in first-episode drug-naive schizophrenic patients (FDSP), and further influenced their clinical symptoms. METHODS This polymorphism was genotyped in 239 FDSP and 368 healthy controls. The clinical symptoms in FDSP were assessed using the Positive and Negative Syndrome Scale (PANSS) five-factor models. RESULTS There was no significant difference in the allelic and genotypic frequencies of this polymorphism between two groups (both p > 0.05) after adjusting for covariates. However, the PANSS depressive score significantly differed by genotype in FDSP after adjusting for covariates (F = 5.25, p = 0.006). This significant difference also persisted after Bonferroni correction (p

Lipid profile (total cholesterol and lipoprotein fractions) has been found to correlate with depression and cognitive impairment across the lifespan. However, the role of lipid levels in self-rated depressive state and cognitive impairment remains unclear. In this study, we examined the relationship between lipid profile (total cholesterol, triglycerides, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol) and cognition in adults with and without self-rated depression. Four hundred and thirty-eight healthy participants completed the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), the Self-Rating Depression Scale (SDS), and a serum lipoprotein test. Using multivariate ANOVA, partial correlation and network analysis, a network linking lipoprotein profile, depressive state and cognition was constructed. A significant difference in serum lipid profile between the high and low depressive groups was detected. Depressive state had a strong negative correlation with cognitive performance. Of the lipid profile, only high-density lipoprotein was positively correlated with depressive symptom severity, whereas the other three indices showed negative correlation with both depressive state and cognitive performance. Our results suggest that serum lipid profile may be directly linked to self-rated depression and cognitive performance. Further studies recruiting larger clinical samples are needed to elucidate the specific effect of lipoprotein on cognitive impairment in mood disorder.

Cognitive and sensory deficits were considered a core feature of major depressive disorder (MDD). However, few studies investigated stereopsis integrity in patients with MDD. Thus, the objectives of this study investigated stereopsis integrity and its correlations with cognitive function and depressive symptom in patients with MDD. 90 patients with MDD and 116 healthy controls (HCs) were enrolled in this study. Their stereoacuity was evaluated using the Titmus Stereopsis Test as well as assessing their cognitive function and depressive symptom by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and Hamilton Depression Scale (HAMD). Log seconds of arc was significantly higher in patients than HCs (1.92 ± 0.41 versus 1.67 ± 0.16, t = 5.35, p 0.0001). The percentage of patients with correct stereopsis detection was markedly declined in 400 (z = 3.06, p = 0.002), 200 (z = 3.84, p 0.001), 140 (z = 4.73, p 0.001), 100 (z = 4.58, p 0.001), 80 (z = 5.06, p 0.001), 60 (z = 4.72, p 0.001), 50 (z = 4.24, p 0.001), and 40 (z = 4.85, p 0.001) seconds of arc compared with HCs. Log seconds of arc was significantly correlated with the RBANS total score (r = -0.38, p 0.0001), subscores of attention (r = -0.49, p 0.0001) and language (r = -0.33, p = 0.001) rather than HAMD score (r = 0.03, p = 0.78) in MDD patients. In addition, log seconds of arc was significantly related to the RBANS total score (r = -0.58, p 0.0001) and language score (r = -0.45, p = 0.006) rather than attention score (r = -0.30, p = 0.07) in HCs. Further stepwise multivariate regression analyses showed the negative correlation of log seconds of arc with attention score (β = -0.80, t = -3.95, p 0.0001) rather than HAMD score (β = -0.008, t = -0.09, p = 0.93) in MDD patients. However, there was no relationship between log seconds of arc and attention score in HCs (β = 1.52, t = 1.19, p = 0.24). Our results identified the marked deficits of stereopsis in MDD patients that were tightly correlated with their attention functioning rather than depressive symptom.

The quantification of preservatives in cosmetics has attracted great attentions for their controversial and widespread use. HPLC is a prevailing method for preservatives determination among various analytical methods. However, it takes long time to fully separate these compounds because of the complexity of cosmetic matrices. In this study, a fast and green HPLC-DAD strategy assisted with second-order multivariate calibration methods based on alternating trilinear decomposition (ATLD) and multivariate curve resolution-alternating least squares (MCR-ALS) was developed for the simultaneous determination of eight selected preservatives in complex facial mask samples. This appealing strategy proved to be a useful tool for eliminating unknown interferences in complex matrices without complete separation, which benefited from the “second-order advantages” and thus made the determination of the eight analytes in facial mask samples shorten to 8.2 min under a fast elution program. In particular, for the first time, we focused on the applicability of ATLD method for modeling of HPLC-DAD data with severe signal overlapping and slight time shifts. The spiked recovery values were in the range of 71.4–124.6%, and the RMSEP and REP values ranged from 0.07 to 2.4 μg mL−1 and 1.3–14.5%, respectively, indicating that the ATLD method could provide satisfactory prediction. The resolved spectral profiles and concentration values were compared with those obtained by the MCR-ALS method, an excellent tool for modeling of data deviating from trilinearity. Both qualitative and quantitative results from the two methods were consistent with each other, which evidenced the competence of ATLD method in handling HPLC-DAD data with severe signal overlapping and slight time shifts.

This paper proposes a flexible and novel strategy that alternating trilinear decomposition (ATLD) method combines with two-dimensional linear discriminant analysis (2D-LDA). The developed strategy was applied to three-way chemical data for the characterization and classification of samples. In order to confirm the methodology performances of characterization and classification, a series of simulated three-way data arrays and a real-life EEMs data set involving the characterization and classification of tea samples according to the tea varieties were subjected to ATLD-2DLDA analysis. Further, the obtained results were compared with those obtained by using LDA based on relative concentrations of ATLD (ATLD-LDA), discriminant analysis by N-way partial least square (N-PLS-DA) and 2D-LDA method. For the simulated data sets with respect to different levels of noise and class overlap as well as number of groups, the ATLD-2DLDA always obtains superior classification performances than the ATLD-LDA, 2D-LDA and N-PLS-DA methods. Regarding the real EEMs data set of tea samples, the proposed methodology not only could provide a chemically meaningful model of the data for characterizing the different tea varieties, but also achieved the best correct classification rate (100%) for the test samples, compared with the results of ATLD-LDA (83.9%), 2D-LDA (90.3%) and N-PLS-DA (90.3%). These results demonstrated that the proposed methodology was indeed a feasible and reliable tool for characterization and classification of three-way chemical data arrays in a flexible and accurate manner.

The aim of the present work was to develop a rapid and interference-free method based on liquid chromatography-mass spectrometry (LC-MS) for the simultaneous determination of nine B-group vitamins in various energy drinks. A smart and green strategy that modeled the three-way data array of LC-MS with second-order calibration methods based on alternating trilinear decomposition (ATLD) and alternating penalty trilinear decomposition (APTLD) algorithms was developed. By virtue of "mathematical separation" and "second-order advantage", the proposed strategy successfully solved the co-eluted peaks and unknown interferents in LC-MS analysis with the elution time less than 4.5min and simple sample preparation. Satisfactory quantitative results were obtained by the ATLD-LC-MS and APTLD-LC-MS methods for the spiked recovery assays, with the average spiked recoveries ranging from 87.2-113.9% to 92.0-111.7%, respectively. These results acquired from the proposed methods were confirmed by the LC-MS/MS method, which shows a quite good consistency with each other. All these results demonstrated that the developed chemometrics-assisted LC-MS strategy had advantages of being rapid, green, accurate and low-cost, and it could be an attractive alternative for the determination of multiple vitamins in complex food matrices, which required no laborious sample preparation, tedious condition optimization or more sophisticated instrumentations.

Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems.

Alternating trilinear decomposition (ATLD) method enables the qualitative and quantitative analysis of excitation-emission matrix fluorescence (EEMF) data acquired from complex samples. However, the impact of diverse background interferences from different sample sources on the performances of ATLD method has never been lucubrated. In this work, simulated and real EEMF data sets from different sample sources with diverse background interferences were collected and subjected to ATLD analysis. The performances of ATLD modeling individual and global EEMF data sets were comprehensively compared in terms of the resolved spectral profiles and quantitative results. It was found that ATLD method can use the same set of calibration samples to resolve and quantify multiple components of interest in multiple complex systems with diverse background interferences, regardless of individual or global modeling. The results revealed that the qualitative and quantitative results provided by ATLD method were affected neither by diversity of background interferences nor by data merging as long as the acquired EEMF data sets conform to the trilinear component model. This property of ATLD method can enrich the “second-order advantage”, i.e. the term “unknown interferences” in the concept of “second-order advantage” refers to not only constant background interferences but also diverse background interferences, which will be certain to further expand the practicality of ATLD method in complex sample analysis, especially in the field of fluorescence spectroscopy.

The unconstrained optimization method (UOM) plays an important role in the field of physics, mathematics, statistics, etc. Rosenbrock function is a 4-degree function with a curved canyon. It is most suitable for testing UOM. However, the test hasn't done. We have written 14 UOM computer programs, 12 of which contain our new algorithm. From the optimal result, the 2-order approximation direction is the best, followed by the conjugate direction, followed by the negative gradient direction. For quadratic fitting function method, linear fitting gradient method and unbounded polyhedron deformation method, a new algorithm for moving points was proposed. When the new point is better than all of the other points, the other points should close up to it. And when the new point is worse than all of the other points, it should close up to the best point or center point. The improvement of moving points makes these optimization directions be effective for complex objective functions.

Background The high prevalence of depression in general population was related to its social-demographics and cognitive performance. However, no studies investigated the prevalence of depression, its social-demographic and cognitive correlates in psychiatric medical staff. Thus, the aims of this study investigated the prevalence, social-demographic and cognitive correlates of depression in Chinese psychiatric medical staff. Methods 186 Chinese psychiatric medical staff were enrolled in Wenzhou Kangning Hospital. Depressive symptom score was assessed by the Self-rating Depression Scale (SDS). Cognition was assessed by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Results The prevalence of depression was 17.74% in these medical staff. The RBANS total score in participants with depressive symptom was significantly lower than that in participants with not depressive symptom after controlling for the confounding variables. The Person correlation analysis found that the normal SDS score in these medical staff was significantly related to age, education, occupations, RBANS total score and subscale scores. Stepwise multivariate regression analysis further identified that age and RBANS total score were significantly associated with the normal SDS score in these medical staff. Limitations The limitations included cross-sectional study design, the small sample size, and the self-rating scale of depression. Conclusions The prevalence of depression in Chinese psychiatric medical staff was higher in comparison with Chinese general population, but lower in comparison with Chinese medical staff. Cognitive deficits might be considered a core feather of depression that should be a valuable target for future interventions. Age influenced depressive symptom in these medical staff .

A multicolor enzyme-linked immunosorbent sensor was constructed to detect organophosphates pesticides (OPs) on base of TMB2+-mediated AuNRs etching. As the etching progresses, a rainbow-like color responses was generated. The naked eye limit of detection (LOD) of the sensing system is 0.25 ng mL−1. In particular, the longitudinal localized surface plasmon resonances (LSPR) peak shift of AuNRs is linearly correlated with the logarithm of OPs concentration in range of 104 to 5 × 106 pg mL−1 for parathion-methyl and fenitrothion, 5 × 104 to 107 pg mL−1 for fenthion, respectively. Compared with reported methods, this sensor displayed satisfactory linear ranges and detection limits. Average recoveries of this method ranged from 73.28% to 98.08% and relative standard deviations (RSDs) were below 8.0% as for food samples analysis without complicated pretreatments. Remarkably, the developed multicolor enzyme-linked immunosorbent sensor is capable of providing accurate and reliable assay for OPs in complex food samples.

A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method is presented for simultaneous determination of umbelliferone and scopoletin in Tibetan medicine Saussurea laniceps (SL) and traditional Chinese medicine Radix angelicae pubescentis (RAP). Using the strategy of combining EEM fluorescence data with second-order calibration method based on the alternating trilinear decomposition (ATLD) algorithm, the simultaneous quantification of umbelliferone and scopoletin in the two different complex systems was achieved successfully, even in the presence of potential interferents. The pretreatment is simple due to the "second-order advantage" and the use of "mathematical separation" instead of awkward "physical or chemical separation". Satisfactory results have been achieved with the limits of detection (LODs) of umbelliferone and scopoletin being 0.06ngmL(-1) and 0.16ngmL(-1), respectively. The average spike recoveries of umbelliferone and scopoletin are 98.8±4.3% and 102.5±3.3%, respectively. Besides, HPLC-DAD method was used to further validate the presented strategy, and t-test indicates that prediction results of the two methods have no significant differences. Satisfactory experimental results imply that our method is fast, low-cost and sensitive when compared with HPLC-DAD method.

In this work, a rapid chemometrics-enhanced liquid chromatography–single stage mass spectrometry (LC–MS) was developed for the simultaneous green determination of six co-eluted sulfonylurea-type oral antidiabetic agents (SOADs) in health teas and human plasma samples. Shortening the chromatographic separation time and reducing the cost per analysis were achieved via using full scan mode of LC–MS under simple isocratic elution condition followed by an environment-friendly “mathematical separation” strategy. The problem of the complete separation of target analytes from each other and/or from the uncalibrated interferences in complex matrices was resolved by alternating trilinear decomposition (ATLD) method as a posteriori . Satisfactory qualitative and quantitative results were obtained even in the existence of unknown interferences and the “second-order advantage” was fully exploited. The average spiked recoveries for all target analytes were between 81.6% and 110.1% with standard deviations less than 7.7%. It was demonstrated that the proposed strategy could be promisingly used for green resolution and determination of co-eluted multi-analytes of interest in complex samples while avoiding elaborate sample pretreatment steps and complicated experimental conditions as well as more sophisticated high-cost instrumentations.

In this paper, a new strategy of introducing an extra solvent mode in the three-way EEMs data to construct a four-way EX–EM-solvent-samples data set was used in order to investigate the ‘third-order advantage’ by comparing the performances of two four-way calibration algorithms with those of two three-way calibration algorithms. The results of the self-weighted alternating normalized residue fitting (SWANRF) and the parallel factor analysis (PARAFAC) algorithms were both disappointing in this work due to serious collinearity and high background interference. In contrast, the satisfactory results (average recovery, 100.0–107.4% and standard deviation, 1.0–3.0%) were obtained by the third-order calibration methods based on both four-way self-weighted alternating normalized residue fitting (four-way SWANRF) and four-way parallel factor analysis (four-way PARAFAC) algorithms. In addition, for prediction of Dulbecco's modified eagle medium (DMEM) samples, the root-mean-square error of prediction (RMSEP) values for schizandrol B obtained from two three-way calibration algorithms were 60.91 and 35.46 μg mL − 1 with 80% ethanol in the aqueous solvent, which were obviously much larger than these (0.0832 and 0.0825 μg mL − 1 ) obtained using two algorithms of the four-way calibration. The results demonstrated that third-order calibration can extract more inherent information from the data, and can easily solve the problems of serious collinearity and high background interference. In short, among the advantages of this method over the existing methods, low cost, non-toxic and non-destructive analysis can be cited.

Two nanoprobes based on gold nanoparticles (AuNPs) and magnetic nanoparticles (MNPs) were synthesized, respectively. A double- nanoprobe based immunoassay with sensitivity, rapidity, and reproducibility was developed for the determination of phenanthrene (Phe) and related low-mass polycyclic aromatic hydrocarbons (PAHs) in water samples. The AuNPs probe was used as signal amplification probe, which can improve the sensitivity of the immunoassay. The MNPs probe was used as immobilization of Phe, which can lead to speed up reaction of antigen-antibody by the suspension property and dispersed nature. The linear range and the limit of detection (LOD) were 0.14–6.55 ng/mL and 0.08 ng/mL, respectively. Compared with the traditional ELISA, the sensitivity of the double-probe based immunoassay was improved about 30 times and the time for determination was shorten 104 min. The recoveries of Phe and related low-mas PAHs from tap water, contaminated water and river water were 90.5–109.8%, 91.2–108.0% and 93.0–107.8%, respectively. The correlation coefficient of the results between the developed immunoassay and GC–MS/MS was 0.9977. The developed double- nanoprobe based immunoassay was sensitive, rapid and good reproducibility for the determination of Phe and related low-mas PAHs in environmental water.

A new chemometrics-assisted high performance liquid chromatography-diode array detection (HPLC-DAD) method was developed to rapidly quantify ten major components in nine Xihu Longjing tea samples. This new strategy proved to be a useful tool for handling the co-eluted problems during chromatographic analysis and enabled the quantification of ten major components in tea samples within only 10 min. The average recoveries of these analytes in tea samples ranged from 100.0% to 112.7% except (−)-epigallocatechin gallate (EGCG). The relative standard deviations of intra- and inter-day assays were in the range of 0.14%–5.09% for all the ten analytes. Furthermore, the quantitative results were used as input variables to perform principal component analysis (PCA) and hierarchical cluster analysis (HCA) for differentiating tea grades. Results demonstrated that the nine different grades of Xihu Longjing tea samples were successfully divided into three categories. This study showed that it is possible to perform tea grades differentiation according to the contents of major components using chemometric pattern recognition methods.

Cognitive impairment is a core feature of schizophrenia (SCH). In addition to the toxic effect of Bilirubin (BIL), it has antioxidant properties that were associated with the psychopathology and cognitive impairment of psychiatric disorders. The aim of this study was to examine the correlation of serum total BIL (TBIL) concentration with cognitive impairment in SCH patients. We recruited 34 SCH patients and 119 healthy controls (HCs) in this case-control design. Cognition was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Serum TBIL concentration was measured using the immunoturbidimetric method. Serum TBIL concentration was significantly decreased in SCH patients compared to HCs after adjusting for age, gender, and education. Serum TBIL concentration in SCH patients was also positively correlated with the RBANS immediate memory score. Further stepwise multiple regression analysis confirmed the positive association between serum TBIL concentration and immediate memory score in SCH patients. Our findings supported that the decline in serum TBIL concentration was associated with the immediate memory impairment and psychopathology of SCH.

In this work, high-performance liquid chromatography with diode array detection was applied for the simultaneous determination of andrographolide and dehydroandrographolide in Andrographis paniculata and its preparations. As a result of the incomplete baseline separation caused by complex backgrounds, the classical univariate calibration method failed to determine accurate contents of the analytes. On this occasion, chemometric second-order calibration based on the well-known alternating trilinear decomposition algorithm was then explored to serve as a post-experimental remedial tool to solve this problem. By using the intelligent "mathematical separation" of alternating trilinear decomposition, the peak areas of the analytes do not need to be directly measured and the predictive results become accurate. The contents of andrographolide and dehydroandrographolide were determined to be (7.95 ± 0.15) and (1.85 ± 0.02) μg/mL for Andrographis paniculata, (1.34 ± 0.01) and (5.53 ± 0.04) μg/mL for its preparations, which was in agreement with those obtained by a reference liquid chromatography with mass spectrometry method. This study showed the superiority of second-order calibration method over classical univariate calibration method for simultaneous determination of multi-analytes in complex samples. It also proved that second-order calibration may be a good choice for remedying incomplete baseline separation problem, with the accompanied reduction of experimental burden and toxic organic solvents as well as analysis time and cost.

This work reports a chemometrics-assisted high performance liquid chromatography-diode array detection (HPLC-DAD) strategy to solve varying interfering patterns from different chromatographic columns and sample matrices for the rapid simultaneous determination of six synthetic colorants in five kinds of beverages with little sample pretreatment. The investigation was performed using two types of LC columns under the same elution conditions. Although analytes using different columns have different co-elution patterns that appear more seriously in complex backgrounds, all colorants were properly resolved by alternating trilinear decomposition (ATLD) method and accurate chromatographic elution profiles, spectral profiles as well as relative concentrations were obtained. The results were confirmed by those obtained from traditional HPLC-UV method at a particular wavelength and the results of both methods were consistent with each other. All results demonstrated that the proposed chemometrics-assisted HPLC-DAD method is accurate, economical and universal, and can be promisingly applied to solve varying interfering patterns from different chromatographic columns and sample matrices for the analysis of complex food samples.

A novel ‘dilute-and-shoot’ analytical strategy coupling a self-weighted alternating normalized residue fitting (SWANRF) algorithm with two-dimensional fluorescence detection enhanced through photochemical derivatization (PD) was proposed in the present work for rapid, simultaneous and accurate quantitative analysis of aflatoxin B1 and G1 in various foodstuffs (including cereals, honey, and edible oil). By coupling the predominant second-order advantage of the SWANRF algorithm with the ultra-sensitivity of fluorescence detection enhanced through off-line photochemical derivatization, the specific quantitative information of both analytes could be successfully extracted from heavily interferential matrices without complicated multi-step purification and chromatographic separation procedures. Consequently, the whole analytical time and expense were significantly decreased, accurate recoveries (with relative standard deviations, RSDs) (93.5 ± 6.6–102.8 ± 4.0% for AFB1, and 96.4 ± 3.6–107.2 ± 6.0% for AFG1) and extremely low limits of detection (LODs) (0.12–0.21 ng mL−1 for AFB1, and 0.27–0.75 ng mL−1 for AFG1) were obtained for analytical foodstuff matrices. In addition, all quantitative results of this proposed strategy were carefully compared with the standard IAC-LC-ESI+-MS method for further confirmation, which proved that SWANRF-EEMs are promising as an alternative analytical strategy for the routine analysis of multiplex aflatoxins, and a theoretical basis for developing portable detecting devices.

A novel method is developed for the direct determination of naphazoline hydrochloride (NAP) and pyridoxine hydrochloride (VB6) in commercial eye drops. By using excitation–emission matrix (EEM) fluorescence coupled with second-order calibration method based on the alternating trilinear decomposition (ATLD) algorithm, the proposed approach can achieve quantitative analysis successfully even in the presence of unknown and uncalibrated interferences. The method shows good linearity for NAP and VB6 with correlation coefficients greater than 0.99. The results were in good agreement with the labeled contents. To further confirm the feasibility and reliability of the proposed method, the same batch samples were analyzed by multiple reaction monitoring (MRM) based on LC–MS/MS method. T -test demonstrated that there are no significant differences between the prediction results of the two methods. The satisfactory results obtained in this work indicate that the use of the second-order calibration method coupled with the EEM is a promising tool for industrial quality control and pharmaceutical analysis due to its advantages of high sensitivity, low-cost and simple implementation.

Methods to monitor the metabolic transformations of pharmaceuticals in a real-time and rapid fashion are required to develop safe and effective drugs. Lactone hydrolysis is one of the most important metabolic transformations; it occurs readily in pharmaceuticals containing lactones by both enzymatic and non-enzymatic processes. In this study, a novel strategy that combines three-way excitation–emission-kinetic (EEM-kinetic) fluorescence data with second-order calibration method based on alternating normalization-weighted error (ANWE) algorithm was developed to monitor the lactone hydrolysis of irinotecan (CPT-11). Accurate real-time concentrations together with reasonable resolutions of the excitation and emission profiles could be estimated for both the lactone form (CPT-11-L) and carboxylate form (CPT-11-C) of CPT-11 during its hydrolysis, even when the fluorescence spectra of CPT-11-L and CPT-11-C seriously overlapped with each other and unknown fluorescent components coexisted in the plasma. Satisfactory results were obtained for static validation samples, spiked plasma samples, and kinetic samples. The average recoveries of CPT-11-L and CPT-11-C in three types of samples mentioned above ranged from 83.7% to 116.7%. The lactone hydrolysis of CPT-11 follows 1st-order degradation kinetics with rate constants of 0.0318 ± 0.0031 min − 1 and 0.0323 ± 0.0008 min − 1 , and half-lives of 21.9 ± 2.0 min and 21.5 ± 0.5 min in PBS and plasma samples, respectively. The strategy described herein minimized or eliminated traditionally time-consuming sample pre-treatments and facilitated the quantification of the target drug in its native environment. This method was proved to be simple, real-time, fast, low-cost, high-efficiency and can be potentially applied to other types of dynamic systems.

Background: Amiloride (AMI) and triamterene (TRI) are both potassium-saving diuretics, which are ordinarily used as doping to enhance the performance of athletes in sports. For the similar structures and complex matrices existence, chromatography and extraction are commonly employed to realize the determination of AMI and TRI in biological fluids, which are very time-consuming and laborious. Results: A novel method is presented to simultaneous interference-free determination of AMI and TRI in complex biological fluids samples using excitation–emission matrix fluorescence coupled with second-order calibration method based on alternating normalization-weight error algorithm. Conclusion: The proposed method can obtain accurate qualitative and quantitative information of the analytes, even in the presence of the interference from complex biological fluids, which requires few prior purification and separation procedures.

Nowadays, Operational power forecasts are associated with the one-value deterministic Numerical Weather Forecasting (NWF) simulation in the anticipated wind speed. This article introduced a novel predicting methodology called SSOFC-Apriori-WRP, which presents one-day-ahead wind power and speed forecasting. This methodology relies highly on a Weather Research and Prediction (WRP) simulation, a shark smell optimization (SSO), enhanced fuzzy clustering (EFC), and an Apriori association procedure. The wind speed prediction with the help of shaped WRP model was produced. Then by dividing wind speed predictions series into different parts, definite conditions were met and were introduced. Next the suggested methodology by the combination of SSO-optimized fuzzy clustering and Apriori algorithm withdraws the association rules, which are dominated among the anticipating errors in the divided waves and the shape features. The suggested methodology could be implemented to the other compared models and decrease the unreliability of the WRP simulation, if the association rules are used in the ultimate optimization process.

Dynamic RWA algorithm which supports differentiating business service quality levels becomes a hot research in optical networks. This paper proposes a better ant colony algorithm for routing and wavelength assignment in ASON with supporting differentiating SLA of services and 10P bps network capacity. Firstly, the algorithm adds the concept of business interval period M to dynamically adjust the wavelength grouped in different periods So as to better meet the sercice requests of different levels; Secondly the algorithm adds a link selection control factor in the transition probability function ACA in order to achieve a better link load balancing. Simulation results show that after joining the cyclical and link selection control factor, blocking rate becomes lower and the load of network becomes more evenly.

With the explosive growth of optical network dimensioning [1] and the call of traffic, the network traffic is becoming more and more imbalanced. When some links are busy and have congestion, some others are idle for long time. This paper proposes a theory which simplifies a complex optical network into an equivalent easy one using the bandwidth of the optical link. and we call this theory TDBB. For the large capacity optical switching network node 1000×1000,divided in two level :the ms level 32×32 optical switching and ns level 32×32 using time division multiplexing in subcarrier wave. Every subcarrier [2] has 10G bandwidth. So we have 10T in single wave ,200T in single fiber. 10P capacity of total 50 ports. which is to say this theory can work for TE project in optical switching network which has more than 10pbs large capacity.

This paper studies a variable rate optical Orthogonal Frequency Division Multiplexing Passive Optical Network (OFDM-PON) real-time access system model, using the signal processing method of oversampling. The basic principle of the model is that the access system uses different oversampling rates according to the allocated bandwidth to different Optical Network Units (ONUs), ensuring that the entire system can utilize the existing hardware conditions to maximum effect. The proposed system uses Xilinx V5 FPGA to generate real-time OFDM signals. MATLAB software is used to recover the signals and calculate the bit error rate (BER). The simulation results are presented and analyzed to verify the performance of the system.

β-blockers are the first-line therapeutic agents for treating cardiovascular diseases and also a class of prohibited substances in athletic competitions. In this work, a smart strategy that combines three-way liquid chromatography-mass spectrometry (LC-MS) data with second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm was developed for simultaneous determination of ten β-blockers in human urine and plasma samples. This flexible strategy proved to be a useful tool to solve the problems of overlapped peaks and uncalibrated interferences encountered in quantitative LC-MS, and made the multi-targeted interference-free qualitative and quantitative analysis of β-blockers in complex matrices possible. The limits of detection were in the range of 2.0×10(-5)-6.2×10(-3) μg mL(-1), and the average recoveries were between 90 and 110% with standard deviations and average relative prediction errors less than 10%, indicating that the strategy could provide satisfactory prediction results for ten β-blockers in human urine and plasma samples only using liquid chromatography hyphenated single-quadrupole mass spectrometer in full scan mode. To further confirm the feasibility and reliability of the proposed method, the same batch samples were analyzed by multiple reaction monitoring (MRM) method. T-test demonstrated that there are no significant differences between the prediction results of the two methods. Considering the advantages of fast, low-cost, high sensitivity, and no need of complicated chromatographic and tandem mass spectrometric conditions optimization, the proposed strategy is expected to be extended as an attractive alternative method to quantify analyte(s) of interest in complex systems such as cells, biological fluids, food, environment, pharmaceuticals and other complex samples.

In this work, an attractive chemometrics-enhanced high performance liquid chromatography-diode array detection (HPLC-DAD) strategy was proposed for simultaneous and fast determination of eight co-eluted compounds including gallic acid, caffeine and six catechins in ten kinds of Chinese teas by using second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm. This new strategy proved to be a useful tool for handling the co-eluted peaks, uncalibrated interferences and baseline drifts existing in the process of chromatographic separation, which benefited from the “second-order advantages”, making the determination of gallic acid, caffeine and six catechins in tea infusions within 8 min under a simple mobile phase condition. The average recoveries of the analytes on two selected tea samples ranged from 91.7 to 103.1% with standard deviations (SD) ranged from 1.9 to 11.9%. Figures of merit including sensitivity (SEN), selectivity (SEL), root-mean-square error of prediction (RMSEP) and limit of detection (LOD) have been calculated to validate the accuracy of the proposed method. To further confirm the reliability of the method, a multiple reaction monitoring (MRM) method based on LC–MS/MS was employed for comparison and the obtained results of both methods were consistent with each other. Furthermore, as a universal strategy, this new proposed analytical method was applied for the determination of gallic acid, caffeine and catechins in several other kinds of Chinese teas, including different levels and varieties. Finally, based on the quantitative results, principal component analysis (PCA) was used to conduct a cluster analysis for these Chinese teas. The green tea, Oolong tea and Pu-erh raw tea samples were classified successfully. All results demonstrated that the proposed method is accurate, sensitive, fast, universal and ideal for the rapid, routine analysis and discrimination of gallic acid, caffeine and catechins in Chinese tea samples.

Guava (Psidium guajava L.) leaf extracts have antiviral and antibacterial activity against shrimp pathogens such as yellow-head virus (YHV), white spot syndrome virus (WSSV), and Vibrio harveyi, which make it a potential water disinfectant for use in shrimp culture. In this study, the safety of guava leaf supplementation in shrimp was evaluated by studying its influence on growth and the non-specific immune response of Penaeus monodon. Six diets containing different levels of guava leaves (0% [basal diet], 0.025% [G1], 0.05% [G2], 0.1% [G3], 0.2% [G4], and 0.4% [G5]) were fed to groups of shrimp (1.576 ± 0.011 g body weight) in triplicate for 56 days. Growth performance (final body weight, WG, PWG, SGR) of shrimp fed guava leaf diets was significantly higher (P0.05) than that of shrimp fed on the basal diet. The G1 diet resulted in the highest body weight gain (308.44%), followed by the G2 (295.45%), G3 (283.05%), G5 (281.29%), G4 (276.11%), and finally the basal diet (214.58%). Survival of shrimp in the G1 diet group was higher than that of shrimp in the control and the other experimental groups; however, no statistical differences (P0.05) were found. Dietary supplementation with guava leaf improved the activities of prophenoloxidase (PO) and nitric oxide synthase (NOS) in serum, and of superoxide dismutase (SOD), acid phosphatase (ACP), alkaline phosphatase (AKP), and lysozyme (LSZ) both in serum and hepatopancreas of shrimp. In the experimental groups, the activities of these enzymes followed a similar pattern of change; they increased initially at low levels of dietary supplementation and then decreased with increasing concentrations of dietary guava leaf. Serum PO and SOD activities in shrimp fed the G1 diet reached 7.50 U ml(-1) and 178.33 U ml(-1), respectively, with PO activity being significantly higher than in controls. In shrimp fed the G1 diet, SOD, ACP, and AKP activities in hepatopancreas were significantly higher than in the controls, reaching 57.32 U g(-1), 23.28 U g(-1), and 19.35 U g(-1) protein, respectively. The highest activities of serum ACP, AKP, LSZ, and of hepatopancreas LSZ, were observed in the G3 diet group. Total nitric oxide synthase (TNOS) activity was highest (64.80 U ml(-1)) in the G4 diet group, which was significantly higher than that observed in the control group. These results suggest that dietary guava leaf supplementation could enhance the growth performance and non-specific immune response of P. monodon. Therefore, guava leaf is considered safe for use as a water disinfectant in shrimp culture.

Analysis the common gear fault signal, using continuous wavelet transform well time-frequency characteristics and failure mechanism gear features, combined with quasi-periodic signal rotary mechanical characteristics of the continuous wavelet transform fault signal. This method can reduce the noise source and other incentives interference, remove the specific needs of the signal to improve signal stripping effect, the use of a certain type of gear failures this step, to get a clear diagnosis results show that this method has proven a strong application space.

This paper analyzed the kinematical and mechanical feature of the trip operation for the 03A driller based on the dynamic brake theory of AC variable frequency motor. The moving pattern of the strip operation and the variable information of the load in winch roller were mastered. We checked the safety coefficient of the winch brake and put forward the suggestions on the safe operation for AC variable frequency controlled driller. This paper is very important for promoting the application of AC frequency technology in drillers.