An exposomic approach with 138 chemical and non-chemical exposures to predict 32 biomarkers of male reproductive damages: A case study of college students in Chongqing, China.

Male reproductive damage in the general population comprises different disorders in various biomarkers, which could be respectively caused by a number of exposure factors. However, researchers considering the environmental/behavioral/psychological exposures together to evaluate their contribution to male reproductive damage are still lacking. The present study investigated the comprehensive association between 138 environmental/behavioral/psychological exposures and 32 male reproductive biomarkers in 796 young Chinese men using graph-guided fused lasso (GFLASSO) and hierarchical clustering methods. All biomarkers were found to be associated with various exposures. A combination of these exposures not only predicted the levels of single biomarkers in another test dataset, but also identified the comprehensive reproductive features by clustering the men into five subgroups with distinct damages representing disrupted spermatogenesis with abnormal sperm morphology, low sperm motility with DNA fragmentation, chromatin immaturity, aberrant endocrine, or DNA strand breakage. The findings can be used to suggest a novel way to identify the males with a high risk of reproductive damage and develop personalized preventive strategies.

Synthesis, Anti-inflammatory Activities and Mechanisms of 3,5- dihydroxycinnamic Acid Derivatives.

BACKGROUND: 3,4-dihydroxycinnamic acid and its derivatives exhibit numerous biologic activities. Such activities have not previously been reported for 3,5-dihydroxycinnamic acid derivatives. In this study, ten derivatives of 3,5- dihydroxycinnamic acid were synthesized and their anti-inflammatory activities were tested in 12-O-tetradecanoylphorbol 13-acetate-induced mouse ear edema. Molecular biological studies have shed lights on their anti-inflammatory mechanism. METHODS: Anti-inflammatory activities of ten new synthesized derivatives of 3,5-dihydroxycinnamic acid were tested in 12-O-tetradecanoylphorbol 13-acetate-induced mouse ear edema, and their anti-inflammatory mechanism was studied by ELISA, real-time RT-PCR, MPO assay and AA-induced mouse ear edema. RESULTS: Compound 7 showed a pronounced anti-inflammatory effect and the inhibition rate was 65.6% at a dose of 1.6mg/ear. This compound acted by reducing mRNA and protein synthesis of tumor necrosis factor-α, interleukins 1ß and 6, and also by decreasing the levels of activated neutrophil infiltrates. Furthermore, compound 7 significantly suppressed arachidonic acid-induced edema as well. Cell-based assays showed that compound 7 inhibited the production of cyclooxygenase- 2-catalyzed prostaglandin E2 from lipopolysaccharide-treated RAW 264.7 cells, and also inhibited 5-lipoxygenase production from A23187-treated RBL-1 cells, and consequently reduced leukotriene B4 production. CONCLUSION: This investigation revealed that some of the derivatives of 3,5-dihydroxycinnamic acid exhibit a more pronounced anti-inflammatory effect than 3,4-dihydroxycinnamic acid. Therefore, 3,5-dihydroxycinnamic acid derivatives, especially compound 7, represent potential value for antiinflammatory drug development.

Caffeic acid reduces cutaneous tumor necrosis factor alpha (TNF-α), IL-6 and IL-1ß levels and ameliorates skin edema in acute and chronic model of cutaneous inflammation in mice.

Caffeic acid (3,4-dihydroxycinnamic acid, CA) has been reported to have anti-inflammatory activity in animal models. However, the mechanisms underlying the anti-inflammatory effects of CA in skin inflammation are only partially understood. The present study was designed to investigate the effects and mechanisms of CA on acute and chronic skin inflammation in mice and the effect of CA in keratinocytes in vitro. The results showed that topical treatment with CA inhibited 12-O-tetradecanoyl-phorbol-13-acetate (TPA)-induced skin edema in a dose-dependent manner, leading to substantial reductions in skin thickness and tissue weight, neutrophil-mediated myeloperoxidase activity, and various histopathological indicators. The CA treatment also significantly reduced the mRNA and protein levels of tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6) and IL-1ß at the application site, and the TNF-α production, the TNF-α-induced IL-6 and IL-1ß production, and TNF-α-induced nuclear factor-kappa B (NF-κB) activation in human keratinocytes in vitro. Furthermore, CA was effective at reducing inflammatory damage induced by chronic TPA exposure. These results demonstrate that CA has anti-inflammatory activities in both acute and chronic contact dermatitis models via blockade of the mRNA and protein synthesis of these cytokines and neutrophil-mediated myeloperoxidase activity, and can target inflammatory mediators specifically in the keratinocytes. Taken together, the present results suggest that CA might be a therapeutic agent against inflammatory skin diseases.

Combining the least correlation design, wavelet packet transform and correlation coefficient test to reduce the size of calibration set for NIR quantitative analysis in multi-component systems.

The paper focuses on solving a common and important problem of NIR quantitative analysis in multi-component systems: how to significantly reduce the size of the calibration set while not impairing the predictive precision. To cope with the problem orthogonal discrete wavelet packet transform (WPT), the least correlation design and correlation coefficient test (r-test) have been combined together. As three examples, a two-component carbon tetrachloride system with 21 calibration samples, a two-component aqueous system with 21 calibration samples, and a two-component aqueous system with 41 calibration samples have been treated with the proposed strategy, respectively. In comparison with some previous methods based on much more calibration samples, the results out of the strategy showed that the predictive ability was not obviously decreased for the first system while being clearly strengthened for the second one, and the predictive precision out of the third one was even satisfactory enough for most cases of quantitative analysis. In addition, all important factors and parameters related to our strategy are discussed in detail.

The spatial effect of near-infrared spectroscopy and its application to the study of supramolecular chemistry.

An unlooked-for experimental observation that in near-infrared spectroscopy (NIR) the absorption peak of the second overtone of aniline adsorbed by 13X molecular sieve nearly disappeared led us investigate a fundamental question: the behavior of NIR when the outside space surrounding a molecule is too small to allow the molecule to vibrate freely. Through NIR of various organic compounds adsorbed by different porous inorganic materials like 13X molecular sieve, silica gel and active aluminium oxide, and NIR of supramolecular cyanuric acid-melamine, we can reasonably confirm a theoretical inference that in the micro-environment above, all intensities of NIR absorbance decrease, and the second overtone decreases more than the first overtone does. Furthermore, one distinct feature of NIR, higher sensitivity to the size of micro-environmental space as compared with mid-infrared (MIR), and its potential application to the study of supramolecular structure are outlined by our experiments.

Determination of psoralen in human plasma using excitation-emission matrix fluorescence coupled to second-order calibration.

A new algorithm, an alternating normalization-weighted error (ANWE) method, and the parallel factor analysis (PARAFAC) have been used to directly determine psoralen (PSO) in human plasma. The two methods fully exploit the second-order advantage of the applied three-way fluorescence data. Interestingly, the calibration samples need only the components of interest, and the prediction samples allow containing not only the components of interest, but also unknown interferents. Consequently, the determination of PSO in plasma becomes no longer troublesome or time-consuming. The results are satisfying. Furthermore, compared with PARAFAC, the newly introduced ANWE method can obtain more satisfactory results.

Simultaneous determination of 6-methylcoumarin and 7-methoxycoumarin in cosmetics using three-dimensional excitation-emission matrix fluorescence coupled with second-order calibration methods.

This paper reports a simple, rapid, and effective method for quantitative analysis of 6-methylcoumarin (6-MC) and 7-methoxycoumarin (7-MOC) in cosmetics using excitation-emission matrix (EEM) fluorescence coupled with second-order calibration. After simple pretreatments, the adopted calibration algorithms exploiting the second-order advantage, i.e., parallel factor analysis (PARAFAC) and self-weighted alternating tri-linear decomposition (SWATLD), could allow the individual concentrations of the analytes of interest to be predicted even in the presence of uncalibrated interferences. In the analysis of facial spray, with the external calibration method, the average recoveries attained from PARAFAC and SWATLD with the factor number of 3 (N=3) were 101.4+/-5.5 and 97.5+/-4.1% for 6-MC, and 103.3+/-1.7 and 101.7+/-1.8% for 7-MOC, respectively. Moreover, in the analysis of oil control nourishing toner, the standard addition method (SAM) was suggested to overcome the partial fluorescence quenching of 6-MC induced by the analyte-background interaction, which also yielded satisfactory prediction results. In addition, the accuracy of the two algorithms was also evaluated through elliptical joint confidence region (EJCR) tests as well as figures of merit (FOM), including sensitivity (SEN), selectivity (SEL) and limit of detection (LOD). It was found that both algorithms could give accurate results, only the performance of SWATLD was slightly better than that of PARAFAC in the cases suffering from matrix effects. The method proposed lights a new avenue to determine quantitatively 6-MC and 7-MOC in cosmetics, and may hold great potential to be extended as a promising alternative for more practical applications in cosmetic quality control, due to its advantages of easy sample pretreatment, non-toxic and non-destructive analysis, and accurate spectral resolution and concentration prediction.

Using near-infrared spectroscopy and differential adsorption bed method to study adsorption kinetics of orthoxylene on silica gel.

This paper has demonstrated the study on the adsorption kinetics of orthoxylene on silica gel with a novel experimental methodology. In the method, there was a differential adsorption bed (DAB) where the solid adsorbent always contacted with the same bulk concentration of the adsorbate vapor, and the DAB was monitored with near-infrared diffuse reflectance spectroscopy (NIRDRS) continuously as well as non-invasively. Local partial least squares (PLS) algorithm was suggested to replace normal global PLS method in multivariate calibration models for processing NIRDRS data, because the concentration of the adsorbate on the adsorbent varied greatly as the adsorption process was going on. In this way, we, conveniently as well as promptly, obtained instantaneous adsorption rates of several orthoxylene/silica gel adsorption processes under different conditions like partial pressure of orthoxylene vapor and velocity of gas, and discovered that the adsorption process was physical adsorption, and mainly controlled by external diffusion.

Determination of pesticides in honey using excitation-emission matrix fluorescence coupled with second-order calibration and second-order standard addition methods.

The present paper presents a novel method for simultaneous determination of the three pesticides, carbaryl, carbendazim and 1-naphthol in honey. The excitation-emission matrix fluorescence data from calibration and prediction samples composed a three-way data array and then were analyzed using the second-order calibration method based on the self-weighted alternating trilinear decomposition (SWATLD). The second-order advantage of the SWATLD-based second-order calibration method was exploited, which makes it possible that calibration can be performed even in the presence of unknown interferences. The method was applied to determine the pesticides in the complex matrix of the honey sample. After the calibration step the recoveries of carbendazim and 1-naphthol were satisfactory. The quantification of carbaryl using the second-order standard addition method (SOSAM) based on SWATLD and the high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS) were performed to validate the concentration of carbaryl in honey samples.

Quantitative analysis of hydrolysis of carbaryl in tap water and river by excitation-emission matrix fluorescence coupled with second-order calibration.

A novel method was proposed to determine simultaneously carbaryl and its degradation product 1-naphthol in river and tap water in this paper. The parallel factor analysis (PARAFAC) algorithm was adopted to analyze the excitation-emission matrix (EEM) fluorescence data. The second-order advantage of the PARAFAC-based second-order calibration algorithm was exploited, which make it possible that calibration can be performed even in the presence of unknown interferences. Good recoveries were obtained although the excitation and emission spectral profiles of the analytes were overlapped with background in the river water. It was also applied to investigate the hydrolysis kinetics of carbaryl in river water and tap water. The rate equation, the rate constant and the half life were calculated.

An ensemble of Monte Carlo uninformative variable elimination for wavelength selection.

An improved method based on an ensemble of Monte Carlo uninformative variable elimination (EMCUVE) is presented for wavelength selection in multivariate calibration of spectral data. The proposed algorithm introduces Monte Carlo (MC) strategy to uninformative variable elimination-PLS (UVE-PLS) instead of leave-one-out strategy for estimating the contributions of each wavelength variable in the PLS model. In EMCUVE wavelength variables are evaluated by different Monte Carlo uninformative variable elimination (MCUVE) models. Moreover, a fusion of MCUVE and the vote rule can obtain an improvement over the original uninformative variable elimination method. Results obtained from simulated data and real data sets demonstrate that EMCUVE can properly carry out wavelength selection in the course of data analysis and improve predictive ability for multivariate calibration model.

Determination of carbendazim in bananas by excitation-emission matrix fluorescence with three second-order calibration methods.

A novel method for determination of carbendazim in bananas is proposed in this study. After the bananas were simply extracted, the carbendazim was quantified under the interference of banana extract using the second-order calibration algorithms based on the parallel factor analysis (PARAFAC), the self-weighted alternating trilinear decomposition (SWATLD) and the alternating penalty trilinear decomposition algorithms (APTLD), respectively. For analysis of the complex samples, the so-called second-order advantage was adequately exploited and good results were obtained. Figures of merit, such as limit of detection, sensitivity and selectivity, were calculated to compare the performances of the three algorithms.

A novel efficient way to estimate the chemical rank of high-way data arrays.

A novel method, a subspace projection of pseudo high-way data array (SPPH), was developed for estimating the chemical rank of high-way data arrays. The proposed method determines the chemical rank through performing singular value decomposition (SVD) on the slice matrices of original high-way data array to produce a pseudo high-way data array and employing the idea of the difference of the original truncated data set and the pseudo one. Compared with traditional methods, it uses the information from eigenvectors combined with the projection residual to estimate the rank of the three-way data arrays instead of using the eigenvalue. In order to demonstrate the excellent performance of the new method, simulated and real three-way data arrays were carried out by the proposed method. The results showed that the proposed method could accurately and quickly determine the chemical rank to fit the trilinear model. Moreover, the newly proposed method was compared with the other four factor-determining methods, i.e. factor indicator function (IND), ADD-ONE-UP, core consistency diagnostic (CORCONDIA) and two-mode subspace comparison (TMSC) approaches. It was found that the proposed method can deal with more complex situations with existence of severe collinearity and trace concentration than many other methods can and performs well in practical applications.

Estimating the chemical rank of three-way data arrays by a simple linear transform incorporating Monte Carlo simulation.

Estimating an appropriate chemical rank of a three-way data array is very important to second-order calibration. In this paper, a simple linear transform incorporating Monte Carlo simulation approach (LTMC) to estimate the chemical rank of a three-way data array was suggested. The new method determines the chemical rank through performing a simple linear transform procedure on the original cube matrix to produce two subspaces by singular value decomposition. One of two subspaces is derived from the original three-way data array itself and the other is derived from a new three-way data array produced by the linear transformation of the original one. Projection technique incorporating the Monte Carlo approach acts as distinguishing criterion to choose the appropriate component number of the system. Simulated three-way trilinear data arrays with different noise types (homoscedastic and heteroscedastic), various noise level as well as high collinearity are used to illustrate the feasibility of the new method. The results have shown that the new method could yield accurate results with different conditions appended. The feasibility of the new method is also confirmed by two real arrays, HPLC-DAD data and excitation-emission fluorescent data. All the results are compared with the other three factor-determining methods: factor indicator function (IND), core consistency diagnostic (CORCONDIA) and two-mode subspace comparison (TMSC) approach. It shows that the newly proposed algorithm can objectively and quickly determine the chemical rank to fit the trilinear model.

Interference-free determination of Sudan dyes in chilli foods using second-order calibration algorithms coupled with HPLC-DAD.

This paper presents a new method for the determination of Sudan dyes contained in hot chilli samples. The method employs second-order calibration algorithms to handle the recorded data. The second-order calibration algorithms are based on the popular parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD) and self-weighted alternating trilinear decomposition (SWATLD), respectively. These chemometric methodologies have the second-order advantage, which is the ability to get accurate concentration estimates of interested analytes even in the presence of uncalibrated interfering components. The results on a set of spiked chilli test shows that low contents of Sudan I and Sudan II in complex chilli mixtures can be accurately determined using the new method. The sample preparation was based on solvent extraction, and internal standard was not required. Quantification was carried out with simple mobile phase.

Study of the interactions of berberine and daunorubicin with DNA using alternating penalty trilinear decomposition algorithm combined with excitation-emission matrix fluorescence data.

Studies of interactions between drugs and DNA are very interesting and significant not only in understanding the mechanism of interaction, but also for guiding the design of new drugs. However, until recently, mechanisms of interactions between drug molecules and DNA were still relatively little known. It is necessary to introduce more simple methods to investigate the mechanism of interaction. In this study, the interactions of daunorubicin (DNR) or berberine (BER) with DNA and the competitive interactions of DNR and BER with DNA have been studied by alternating penalty trilinear decomposition algorithm (APTLD) combined with excitation-emission matrix fluorescence data. The excitation and emission spectra as well as the relative concentrations of co-existing species in different reaction and equilibrium mixtures can be directly and conveniently obtained by the APTLD treatment. The results obtained are valuable for providing a deeper insight into the interaction mechanism of DNR and BER with DNA. It is proved that the fluorescence spectrum of complex DNR-DNA is different from that of DNR. Furthermore, the present method provides a new way to search for a new non-toxic, highly efficient fluorescent probe. For controversial interaction mechanism of the drugs and DNA, it can provide a helpful verification.

Fluorescence determination of metoprolol in human plasma by trilinear decomposition-based calibration techniques.

In this study a new spectrofluorimetric method for the direct determination of metoprolol in human plasma is presented and discussed. It is based on the use of fluorescence excitation-emission matrices (EEMs) and second-order calibration performed with parallel factor analysis (PARAFAC) or alternating trilinear decomposition (ATLD). This methodology enables accurate and reliable discrimination of the analyte signal, even in the presence of unknown and uncalibrated fluorescent component(s), which is often referred to as the second-order advantage. No separation or sample pretreatment steps were required. Satisfactory results were obtained. Metoprolol recoveries in plasma were determined as 87+/-2% and 90+/-4% with PARAFAC and ATLD, respectively. All RSD values of intra- and interday assays were below 5%.