Investigation of factors affecting sodium alginate fouling mechanisms in a microfiltration process under non-constant-flux and non-constant-pressure conditions.

Variations in transmembrane pressure and permeate flux are closely related to membrane fouling. In this study, a laboratory-scale submerged microfiltration system was used to investigate the influence of sodium alginate (SA) concentration and peristaltic pump rotation speed on the fouling under the conditions of (1) the same driving force and non-aerated-PAC, (2) different driving forces and non-aerated-PAC, and (3) different driving forces and aerated-PAC. The results showed that the normalized transmembrane pressure (TMP') increased linearly with decreasing normalized permeate flux (J') during the early microfiltration stage regardless of the operating conditions, indicating that the SA microfiltration process controlled by the peristaltic pump was non-constant-flux and non-constant-pressure. The latter filtration stage was considered constant-pressure filtration when 200-1,200 mg/L of SA was filtrated at the same rotation speed. During filtration of 800 mg/L of SA under the non-aerated-PAC condition, the later filtration stage was considered constant-pressure filtration when the peristaltic pump rotated at slower speeds of 15 and 30 rpm. This approached constant-flux filtration when the peristaltic pump rotated at faster speeds of 60 and 90 rpm, and PAC-aeration scouring was an effective measure for mitigating membrane fouling by SA.

CTHRC1, a novel gene with multiple functions in physiology, disease and solid tumors (Review).

Collagen triple helix repeat containing 1 (CTHRC1) is a gene discovered in 2005; it is highly conserved, and no homologous proteins have been disclosed thus far. A number of studies have shown that CTHRC1 is present in normal tissues and organs, and it has vital functions in physiological processes, including participating in the regulation of metabolism, arterial remodeling, bone formation and myelination of the peripheral nervous system. It has been reported that abnormal expression of CTHRC1 is involved in the carcinogenesis of various human organs, such as the breast, colon, pancreas, lung, stomach and liver. Therefore, the present review aims to collate all known findings and results on the regulation of CTHRC1 expression and related signaling pathways. To conclude, this review also provides a hypothesis of the functional mechanism of this gene.

A review of the regulatory mechanisms of extracellular vesicles-mediated intercellular communication.

Extracellular vesicles (EVs) are small, membrane-bound structures that are released from cells into the surrounding environment. These structures can be categorized as exosomes, microvesicles, or apoptotic vesicles, and they play an essential role in intercellular communication. These vesicles are attracting significant clinical interest as they offer the potential for drug delivery, disease diagnosis, and therapeutic intervention. To fully understand the regulation of intercellular communication through EVs, it is essential to investigate the underlying mechanisms. This review aims to provide a summary of the current knowledge on the intercellular communications involved in EV targeting, binding, and uptake, as well as the factors that influence these interactions. These factors include the properties of the EVs, the cellular environment, and the recipient cell. As the field of EV-related intercellular communication continues to expand and techniques improve, we can expect to uncover more information about this complex area, despite the current limitations in our knowledge.

Tumor Cell-Intrinsic BTLA Receptor Inhibits the Proliferation of Tumor Cells via ERK1/2.

B and T lymphocyte attenuator (BTLA) is an immune checkpoint molecule that mediates the escape of tumor cells from immunosurveillance. Consequently, BTLA and its ligand herpesvirus entry mediator (HVEM) are potentially immunotherapeutic targets. However, the potential effects of BTLA on tumor cells remain incompletely unknown. Here, we show that BTLA is expressed across a broad range of tumor cells. The depletion of BTLA or HVEM promotes cell proliferation and colony formation, which is reversed by the overexpression of BTLA in BTLA knockout cells. In contrast, overexpression of BTLA or HVEM inhibits tumor cell proliferation and colony formation. Furthermore, the proliferation of a subpopulation with high BTLA was also significantly slower than that of the low BTLA subpopulation. Mechanistically, the coordination of BTLA and HVEM inhibits its major downstream extracellular regulated protein kinase (ERK1/2) signaling pathway, thus preventing tumor cell growth. This study demonstrates that tumor cell-intrinsic BTLA/HVEM is a potential tumor suppressor and is likely to have a potential antagonist for immunotherapy, thus representing a potential biomarker for the optimal cancer immunotherapeutic treatment.

A User-Friendly Platform for Single-Cell Raman Spectroscopy Analysis.

The optimization of Raman instruments greatly expands our understanding of single-cell Raman spectroscopy. The improvement in the speed and sensitivity of the instrument and the implementation of advanced data mining methods help to reveal the complex chemical and biological information within the Raman spectral data. Here we introduce a new Matlab Graphical User-Friendly Interface (GUI), named "CELL IMAGE" for the analysis of cellular Raman spectroscopy data. The three main steps of data analysis embedded in the GUI include spectral processing, pattern recognition and model validation. Various well-known methods are available to the user of the GUI at each step of the analysis. Herein, a new subsampling optimization method is integrated into the GUI to estimate the minimum number of spectral collection points. The introduction of the signal-to-noise ratio (SNR) of the analyte in the binomial statistical model means the new subsampling model is more sophisticated and suitable for complicated Raman cell data. These embedded methods allow "CELL IMAGE" to transform spectral information into biological information, including single-cell visualization, cell classification and biomolecular/ drug quantification.

Mitigation of membrane fouling of alginate with combined actions of aeration and powdered activated carbon: Fouling behaviors and mechanisms.

A laboratory-scale flat-sheet ceramic microfiltration membrane system was developed to investigate the membrane fouling behaviors and mechanisms of sodium alginate (SA) in the presence of aeration and powdered activated carbon (PAC). When the SA concentration increased from 20 to 500 mg/L, the permeate flux decreased by 81.7%, and the transmembrane pressure (TMP) and resistance increased 1.7 and 24.5 times, respectively. At an SA concentration of 500 mg/L, it was found that the membrane fouling tended to decrease with the increase in the aeration rate, indicating high control of the fouling by air scouring, while PAC-aeration scouring produced a significant improvement in the permeate flux with substantially reduced fouling. In the microfiltration of 500 mg/L SA at an air flow rate of 2.2 L/min and PAC concentrations of 40, 100, and 250 mg/L, the flux increased by 179.3%, 238.0%, and 302.7%, the TMP decreased by 32.6%, 34.8%, and 45.7%, and the cake and pore blocking resistance decreased by 78.0%, 85.1%, and 87.9%, respectively, compared to the corresponding values without PAC-aeration scouring. Intermediate blocking and complete blocking models were confirmed to elucidate the effect of aeration scouring and PAC-aeration scouring on the mitigation of membrane fouling by SA. PRACTITIONER POINTS: Air scouring was effective at mitigating membrane fouling of sodium alginate. The addition of PAC could alleviate membrane fouling of SA. Synergistic scouring by aeration and PAC offers a promising means for more-efficient and cost-effective control of membrane fouling. The fouling mechanisms in various scenarios were elucidated.

[Application of two noninvasive scores in predicting the risk of respiratory failure in full-term neonates: a comparative analysis]. / ä¸¤ç§æ— åˆ›è¯„åˆ†æ³•åœ¨è¶³æœˆæ–°ç”Ÿå„¿å‘¼å¸è¡°ç«­é£Žé™©é¢„æµ‹ä¸­çš„åº”ç”¨æ¯”è¾ƒ.

OBJECTIVES: To study the value of Silverman-Anderson score versus Downes score in predicting respiratory failure in full-term neonates. METHODS: The convenience sampling method was used to select the full-term neonates with lung diseases who were hospitalized in the neonatal intensive care unit from July 2020 to July 2021. According to the diagnostic criteria for neonatal respiratory failure, they were divided into a respiratory failure group (65 neonates) and a non-respiratory failure group (363 neonates). Silverman-Anderson score and Downes score were used for evaluation. The receiver operating characteristic analysis was used to compare the value of the two noninvasive scores in predicting respiratory failure in full-term neonates. RESULTS: Among the 428 full-term neonates, 65 (15.2%) had respiratory failure. The Silverman-Anderson score had a significantly shorter average time spent on evaluation than the Downes score [(90±8) seconds vs (150±13) seconds; P<0.001]. The respiratory failure group had significantly higher points in both the Silverman-Anderson and Downes scores than the non-respiratory failure group (P<0.001). The Silverman-Anderson score had an AUC of 0.876 for predicting respiratory failure, with a sensitivity of 0.908, a specificity of 0.694, and a Youden index of 0.602 at the optimal cut-off value of 4.50 points. The Downes score had an AUC of 0.918 for predicting respiratory failure, with a sensitivity of 0.723, a specificity of 0.953, and a Youden index of 0.676 at the optimal cut-off value of 6.00 points. The Downes score had significantly higher AUC for predicting respiratory failure than the Silverman-Anderson score (P=0.026). CONCLUSIONS: Both Silverman-Anderson and Downes scores can predict the risk of respiratory failure in full-term neonates. The Silverman-Anderson score requires a shorter time for evaluation, while the Downes score has higher prediction efficiency. It is recommended to use Downes score with higher prediction efficiency in general evaluation, and the Silverman-Anderson score requiring a shorter time for evaluation can be used in emergency.

Ultra performance liquid chromatography-tandem mass spectrometry assay for the quantification of RNA and DNA methylation.

Previous studies have reported that nucleic acid methylation is a critical element in cardiovascular disease, and most studies mainly focused on sequencing and biochemical research. Here we developed an Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/ MS) method for the quantification analysis of the dissociative epigenetic modified nucleosides (5mdC, 5mrC, m6A) in Myocardial Infarction (MI) SD rats from different periods (1 week, 4 weeks, 8 weeks) after the surgery. The samples for analysis were obtained from heart tissue and blood of the rats. All the quantification results are compared with the sham-operated group. Total RNA and DNA were isolated by enzymatic hydrolytic methods before the UPLC-MS/MS analysis. The statistical analysis demonstrates the dynamic changes of modified nucleosides in MI rats, and it showed good specificity, accuracy, stability and less samples were needed in the method. In this paper, we discovered that the concentration of 5mdC, 5mrC, m6A from heart tissue significantly increased at 8 weeks after the surgery. Furthermore, UPLC-MS/MS helps us observe the similar change of the concentration of those 3 methylated biomarkers in peripheral blood after 8 weeks. The result shows that the dynamic process of those 3 methylated biomarkers in peripheral blood is related to the content of methylated biomarkers from the heart tissue. Based on the scientific evidence available, we proved that the methylation of genetic materials in peripheral blood is similar to myocardial infarction tissue. The relation between them indicates that peripheral blood could be a promising alternative to the heart tissue which monitor the level of methylation and MI diagnosis-aided.

Neural Network Adaptive Tracking Control of Uncertain MIMO Nonlinear Systems With Output Constraints and Event-Triggered Inputs.

This article is concerned with a neural adaptive tracking control scheme for a class of multiinput and multioutput (MIMO) nonaffine nonlinear systems with event-triggered mechanisms, which include the fixed thresholds, triggering control inputs, and decreasing functions of tracking errors. Unlike the existing results of nonaffine nonlinear controller decoupling, a novel nonlinear multiple control inputs separated design method is proposed based on the mean-value theorem and the Taylor expansion technique. By this way, a weaker condition of nonlinear decoupling is provided to instead of the previous ones. Then, introducing a prescribed performance barrier Lyapunov function (PPBLF) and using neural networks (NNs), the presented event-triggered controller can maintain better tracking performance and effectively alleviate the computation burden of the communication procedure. Furthermore, it is proved that all the closed-loop signals are bounded and the system output tracking errors are confined within the prescribed bounds. Finally, the simulation results are given to demonstrate the validity of the developed control scheme.

Data mining in Raman imaging in a cellular biological system.

The distribution and dynamics of biomolecules in the cell is of critical interest in biological research. Raman imaging techniques have expanded our knowledge of cellular biological systems significantly. The technological developments that have led to the optimization of Raman instrumentation have helped to improve the speed of the measurement and the sensitivity. As well as instrumental developments, data mining plays a significant role in revealing the complicated chemical information contained within the spectral data. A number of data mining methods have been applied to extract the spectral information and translate them into biological information. Single-cell visualization, cell classification and biomolecular/drug quantification have all been achieved by the application of data mining to Raman imaging data. Herein we summarize the framework for Raman imaging data analysis, which involves preprocessing, pattern recognition and validation. There are multiple methods developed for each stage of analysis. The characteristics of these methods are described in relation to their application in Raman imaging of the cell. Furthermore, we summarize the software that can facilitate the implementation of these methods. Through its careful selection and application, data mining can act as an essential tool in the exploration of information-rich Raman spectral data.

Antioxidant Activity and Main Chemical Components of a Novel Fermented Tea.

In the present study, we aimed to develop a novel fermented tea (NFT) product and to evaluate their in vitro antioxidant potential and chemical composition. We found that NFT contained a high level of total phenolic compounds (102.98 mg gallic acid equivalents/g extract) and exhibited diverse antioxidant activities, such as scavenging of 1,1-diphenyl-2-picryl-hydrazyl (DPPH) and hydroxyl radicals, as well as reducing power. The total catechins in NFT were comparable to those of Lipton black tea (LBT), but lower than those of Boseong green tea (BGT) or Tieguanyin oolong tea (TOT). Among all catechins tested, epigallocatechin (EGC) and epigallocatechin-3-O-gallate (EGCG) were the predominant compounds in NFT. In particular, the contents of total theaflavins (TFs), theaflavin (TF), theaflavin-3-gallate (TF3G), and theaflavin-3'-gallate (TF3'G) in NFT were significantly higher than that of BGT, TOT, or LBT. NFT had the highest level of total essential amino acid and γ-aminobutyric acid (GABA) compared with BGT, TOT and LBT. Furthermore, the sensory evaluation results showed that NFT had satisfactory color, aroma, taste, and overall acceptability scores. Our results highlight the potential usefulness of this novel fermented tea as a nutraceutical food/ingredient with special functional activities.

Simultaneously quantifying intracellular FAD and FMN using a novel strategy of intrinsic fluorescence four-way calibration.

The simultaneous quantitative analysis of intracellular metabolic coenzymes flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN) is of interest because they participate in many electron-transfer reactions of metabolism. But, the simultaneous quantitative analysis of FAD and FMN is hard to be achieved by traditional analytical methods. This paper proposes a novel strategy of intrinsic fluorescence coupled with four-way calibration method for simultaneous quantitative analysis of intracellular metabolic coenzymes FAD and FMN. Through mathematical separation, this proposed analytical method efficiently achieved the simultaneous quantitative analysis of metabolic coenzymes FAD and FMN in the cell, despite the fact that uncalibrated spectral interferents coexist in the system. The predicted concentrations of FAD and FMN in the cell are 217.0 ±â€¯6.9 and 155.0 ±â€¯1.7 pmol/106 cells respectively, which were validated by the approved liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. This analytical method with second-order advantage simply requires the cell solution to be diluted by a buffer, it could introduce an interesting analytical strategy for multianalyte direct quantitative analysis in complex biological systems. In addition, we explore the third-order advantage of four-way calibration by a comparative study based on this real fluorescence data. The comparisons indicate that a four-way calibration method can provide higher sensitivity and more resolving power than a three-way calibration method.

Angle Distribution of Loading Subspace (ADLS) for estimating chemical rank in multivariate analysis: Applications in spectroscopy and chromatography.

Multivariate analyses are increasingly popular to explore the underlying structure of multivariate datasets, which are more and more prevalent in analytical chemistry. However, difficulties can be associated with estimating the number of components for the data with considerable coherence and noise. The method of Angle Distribution of Loading Subspace (ADLS) has been proposed to estimate the number of components for Principal Component Analysis (PCA) and PARAllel FACtor analysis (PARAFAC), which showed some advantages, in particular in the case of datasets with high coherence, over the commonly used methods (scree plot and cross-validation in PCA, and core consistency diagnostics (CORCONDIA) in PARAFAC). In this paper, we systematically improved and applied ADLS to estimate the number of components in different multivariate methods including, Multivariate Curve Resolution (MCR), PARAFAC and four-way PARAFAC. Firstly, we showed that ADLS performed better when estimating the chemical rank for MCR analysis, compared with scree plots. As well as this, we improved ADLS in multi-way analysis (three- and four-way PARAFAC) by calculating the loading subspace in advance using the Khatri-Rao product. The improved ADLS in multi-way analysis provided the correct result for the simulated three-way fluorescence datasets with unevenly distributed coherence at different dimensions, while the previous version of ADLS showed biased results and CORCONDIA / split-half analysis provided relatively unstable results. Moreover, ADLS was used to estimate the chemical rank for a four-way real-life fluorescence dataset analyzed by four-way PARAFAC. In this case the result of chemical rank results from ADLS was more precise and informative compared with CORCONDIA /split-half analysis in four-way analysis.

Dealing with overlapped and unaligned chromatographic peaks by second-order multivariate calibration for complex sample analysis: Fast and green quantification of eight selected preservatives in facial masks.

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.

Energy self-sufficient biological municipal wastewater reclamation: Present status, challenges and solutions forward.

Almost all present biological processes for treating municipal wastewater have been developed based on the philosophy of biological oxidation with high energy consumption and generation of waste sludge. Given such a situation, the fundamental question of what are the possible ways towards energy self-sufficient biological reclamation of municipal wastewater needs to be addressed urgently. Therefore, this review aims to offer a critical view and a holistic analysis of biological treatment processes with the focus on energy self-sufficiency which indeed is a game changer in the future technology development. The way towards energy self-sufficient operation of biological processes is to maximize energy recovery, while to minimize energy consumption. The examples of such process configurations known as A-B processes are thus discussed. Consequently, this review may offer in-depth insights into the possible directions towards the next-generation biological processes for municipal wastewater reclamation which should be designed as a water-energy-resource factory.

Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).

Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T2 and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry.

Towards a full understanding of the nature of Ni(II) species and hydroxyl groups over highly siliceous HZSM-5 zeolite supported nickel catalysts prepared by a deposition-precipitation method.

Highly siliceous HZSM-5 zeolite supported nickel catalysts prepared by a deposition-precipitation (D-P) method were characterized by Fourier transform infrared (FT-IR), hydrogen temperature programmed reduction (H2-TPR), X-ray diffraction (XRD), N2-absorption/desorption, field emission scanning electron microscopy (FE-SEM), X-ray photoelectron spectroscopy (XPS), and (27)Al magic-angle nuclear magnetic resonance (MAS NMR) techniques. The results showed that the D-P of nickel species occurred predominantly on the internal surface of highly siliceous HZSM-5 zeolite, in which the internal silanol groups located on the hydroxylated mesopores or nanocavities played a key role. During the D-P process, nickel hydroxide was first deposited-precipitated via olation/polymerization of neutral hydroxoaqua nickel species over the HZSM-5 zeolite. With the progress of the D-P process, 1 : 1 nickel phyllosilicate was formed over the HZSM-5 via the hetero-condensation/polymerization between charged hydroxoaqua nickel species and monomer silicic species generated due to the partial dissolution of the HZSM-5 framework. The 1 : 1 nickel phyllosilicate could also be generated via the hydrolytic adsorption of hydroxoaqua nickel species and their subsequent olation condensation. After calcination, the deposited-precipitated nickel hydroxide was decomposed into nickel oxide, while the 1 : 1 nickel phyllosilicate was transformed into 2 : 1 nickel phyllosilicate. According to the above mechanism, Ni(ii) species were present both in the form of nickel oxide and 2 : 1 nickel phyllosilicate, which were mutually separated from each other, being highly dispersed over HZSM-5 zeolite.

Solving signal instability to maintain the second-order advantage in the resolution and determination of multi-analytes in complex systems by modeling liquid chromatography-mass spectrometry data using alternating trilinear decomposition method assisted with piecewise direct standardization.

The application of calibration transfer methods has been successful in combination with near-infrared spectroscopy or other tools for prediction of chemical composition. One of the developed methods that can provide accurate performances is the piecewise direct standardization (PDS) method, which in this paper is firstly applied to transfer from one day to another the second-order calibration model based on alternating trilinear decomposition (ATLD) method built for the interference-free resolution and determination of multi-analytes in complex systems by liquid chromatography-mass spectrometry (LC-MS) in full scan mode. This is an example of LC-MS analysis in which interferences have been found, making necessary the use of second-order calibration because of its capacity for modeling this phenomenon, which implies analytes of interest can be resolved and quantified even in the presence of overlapped peaks and unknown interferences. Once the second-order calibration model based on ATLD method was built, the calibration transfer was conducted to compensate for the signal instability of LC-MS instrument over time. This allows one to reduce the volume of the heavy works for complete recalibration which is necessary for later accurate determinations. The root-mean-square error of prediction (RMSEP) and average recovery were used to evaluate the performances of the proposed strategy. Results showed that the number of calibration samples used on the real LC-MS data was reduced by using the PDS method from 11 to 3 while producing comparable RMSEP values and recovery values that were statistically the same (F-test, 95% confidence level) to those obtained with 11 calibration samples. This methodology is in accordance with the highly recommended green analytical chemistry principles, since it can reduce the experimental efforts and cost with regard to the use of a new calibration model built in modified conditions.

A flexible trilinear decomposition algorithm for three-way calibration based on the trilinear component model and a theoretical extension of the algorithm to the multilinear component model.

There is a great deal of interest in decompositions of multilinear component models in the field of multi-way calibration, especially the three-way case. A flexible novel trilinear decomposition algorithm of the trilinear component model as a modification of an alternating least squares algorithm for three-way calibration is proposed. The proposed algorithm (constrained alternating trilinear decomposition, CATLD) is based on an alternating approximate least-squares scheme, in which two extra terms are added to each loss function, making it more efficient and flexible. The analysis of simulated three-way data arrays shows that it converges fast, is insensitive to initialization, and is insensitive to the overestimated number of components used in the decomposition. The analysis of real excitation-emission matrix (EEM) fluorescence and real high performance liquid chromatography-photodiode array detection (HPLC-DAD) data arrays confirms the results of the simulation studies, and shows that the proposed algorithm is favorable not only for EEMs but also for HPLC-DAD data. The three-way calibration method based on the CATLD algorithm is very efficient and flexible for direct quantitative analysis of multiple analytes of interest in complex systems, even in the presence of uncalibrated interferents and varying background interferents. Additionally, a theoretical extension of the proposed algorithm to the multilinear component model (constrained alternating multilinear decomposition, CAMLD) is developed.

A simple and convenient approach for preparing core-shell-like silica@nickel species nanoparticles: highly efficient and stable catalyst for the dehydrogenation of 1,2-cyclohexanediol to catechol.

A simple and convenient approach denoted as gel-deposition-precipitation (G-D-P) for the preparation of core-shell-like silica@nickel species nanoparticles was studied systematically. Core-shell-like silica@nickel species nanoparticles consisted of a Si-rich core and a Ni-rich shell. The G-D-P process included two steps: one was the deposition-precipitation of nickel over the gelled colloidal silica particle, generating core-shell-like silica@nickel species nanoparticles, and the other was the aging period. It was found that the nickel phyllosilicate layer was formed mainly during the aging period and served as the protective cover to resist against aggregation of the nanoparticles, which could be utilized for regulating the dispersion of nickel over the silica@nickel species nanoparticles. In the present paper, the silica@nickel species nanoparticles were used as the catalysts for preparing catechol via dehydrogenation of 1,2-cyclohexanediol. Their catalytic activity and long-term stability were compared to those of a catalyst prepared by a conventional deposition-precipitation (D-P) approach. The higher activity and better stability of the title reaction over the silica@nickel species nanoparticles catalyst prepared by G-D-P than those over the catalyst prepared by D-P could be due to the higher dispersion of metallic nickel stabilized by the layers of nickel phyllosilicates. Moreover, it was found that the dehydrogenation of 1,2-cyclohexanediol to catechol was a structurally sensitive reaction.