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A spectral transformation strategy based on the dynamic time warping algorithm is proposed to eliminate systematic errors between primary and secondary instruments.

In a smart urban environment, providing accurate information about human activities is an important task. It is a trend to implement human activity recognition (HAR) algorithms and applications on smart phones, including health monitoring, self-management system, health tracking and so on. However, human activity recognition(HAR) is very complex, and it is important to use the best technology and machine learning to understand human activities. One of the main problems of the existing HAR strategies is that the classification accuracy is relatively low, and in order to improve the accuracy, it needs high computational overhead. The purpose of this paper is to use an exploratory data analysis method to deal with HAR, after the implementation of different data mining techniques, the results of dimensionality reduction and visualization are obtained. The HAR method based on smart phone and EDA proposed in this paper is a high precision method. Compared with other classifiers, its accuracy is 96.56%. This article will discuss computational prediction activities and the computational limitations of using exploratory data to analyze (EDA) on 564 feature data frames. The experimental results show that HAR-based exploratory data analysis is a common sensory signal processing technology. The GridSearchCV and LinearSVC algorithm can provide accurate automatic human activity recognition (HAR), for elderly and disabled patients in need of continuous care, and it is a decision-making tool to support sports coaches to make plans.

DNA-templated silver nanoclusters (DNA/AgNCs) serve as a useful electrochemical sensing nanomaterial characterized by excellent electroactivity and good stability, while the effect of surrounding nucleotides on their electroactivity has not been studied. Herein, we validated a nucleotide-assisted enhancement mechanism of the DNA/AgNCs electroactivity caused by T-rich nucleic acid sequences in the vicinity of AgNCs. Based on the T-rich nucleic acid-enhanced AgNCs (NAE-AgNCs) combined with hybrid chain reaction (HCR), a novel signal-enhanced electrochemical biosensing platform was established for the ultrasensitive detection of miRNA. In the presence of target miRNA-155, HCR could be triggered to generate duplex strands containing both numerous AgNC synthesis sites and T-rich overhang strands upon the electrode. With the electrodeposition of adjacent AgNCs on the electrode, the larger oxidation potential of T-rich nucleic acid leaded to stronger electron-accepting capacity, which could contribute to increased current responses. The T-rich NAE HCR electrochemical strategy resulted in a detection limit of 0.39 fM for miRNA-155 detection, one order of magnitude lower than conventional HCR-based electrochemical sensors. This T-rich nucleic acid-assisted enhancement mechanism provided a new direction to construct highly sensitive, label-free, low-cost, and simple sensing platforms for applications in biomarker assays and clinic diagnosis.

Enzyme inhibition based drug screening strategy has been widely employed for new drug discovery. But this strategy faces some challenges in practical application especially for the trace active compound screening from natural products such as the stability of enzyme and the sensitivity of screening approach. Inspired by the above, we for the first time demonstrate the self-assembly of α-glucosidase (GAA) and glucose oxidase (GOx) into one multi-enzymes-inorganic nanoreactor with hierarchical structure (flower shape). The hybrid enzyme nanoreactor enjoys the merits including the character of assembly line, the enhanced enzymatic activity and robust stability. The flower shape of enzyme nanoreactor possessed a bigger specific surface area, facilitating the trace GAA inhibitor detection. Based on the above, we proposed an enzyme nanoreactor mediated plasmonic sensing strategy for anti-diabetic drug screening. First, maltose was chosen as the substrate for GAA and the generated glucose were immediately utilized by GOx to generate H2O2, and finally, H2O2 etched the Ag nanoprism to round nanodiscs, resulting in the blue shift of surface plasmon resonance (SPR) absorption band. With the aid of hybrid enzyme nanoreactor guided SPR, the ultrasensitive screening of GAA inhibitor (i.e. anti-diabetic drug) can be realized with the detection limit of 5nM for acarbose. The proposed approach was successfully utilized for GAA inhibitor screening from natural products. We anticipate that the proposed sensing method may provide new insights and inspirations in the enzyme inhibition based drug discovery and clinical diagnosis.

Severe haze in China has been a global concern in recent years. Most studies about the mechanism of haze formation mare only focused on the heterogeneous reactions of SO 2 and NO 2 on mineral aerosols. However, little is known about the role of molecular chlorine (Cl 2 ) in those reactions. Here, we investigated the heterogeneous uptake of Cl 2 , SO 2 and NO 2 on γ-Al 2 O 3 particles under different conditions using a quartz-based flow reactor. We found that the existence of γ-Al 2 O 3 seed aerosols significantly promotes the formation of secondary chloride, sulfate and nitrate aerosols, and Cl 2 , NO 2 and SO 2 have synergistic effects when they react on γ-Al 2 O 3 surface under humid condition. The results also shows that Cl 2 can promote the formation of secondary sulfate and nitrate aerosols on γ-Al 2 O 3 surface. Moreover, Cl 2 is much easier to react with the surface of γ-Al 2 O 3 and form secondary Cl − aerosol when comparing with NO 2 and SO 2 , suggesting that Cl 2 is of great importance in atmospheric chemistry, it has the potential to alter the surface properties (e.g., chemical composition and fraction) of mineral aerosol, enhance the production of secondary inorganic aerosols in the troposphere, and thus cause adverse effects on the climate and human health.

Recently, α-glucosidase inhibitor has been widely used in clinic for diabetic therapy. In the present study, a facile and sensitive fluorescent assay based on enzyme activated inner filter effect (IFE) on nitrogen-doped carbon dots (CDs) was first developed for the detection of α-glucosidase. The N-doped CDs with green emission were prepared by a one-step hydrothermal synthesis and gave the fluorescence quantum yield of 30%, which were used as the signal output. Through α-glucosidase catalysis, 4-nitrophenol was released from 4-nitrophenyl-α-d-glucopyranoside (NGP). Interestingly, the absorption of 4-nitrophenol and the excitation of CDs were completely overlapping. Due to its great molar absorptivity, 4-nitrophenol was capable of acting as a powerful absorber to affect the fluorescent signal of CDs (i.e. IFE). By converting the absorption signals into fluorescence signals, the facile fluorescence assay strategy could be realized for α-glucosidase activity sensing, which effectively avoided the complex modification of the surface of CDs or construction of the nanoprobes. The established IFE-based sensing platform offered a low detection limit of 0.01 U/mL (S/N = 3). This proposed sensing approach has also been expanded to the inhibitor screening and showed excellent applicability. As a typical α-glucosidase inhibitor, acarbose was investigated with a low detection limit of 10-8 M. This developed method enjoyed many merits including simplicity, lost cost, high sensitivity, good reproducibility and excellent selectivity, which also provided a new insight on the application of CDs to develop the facile and sensitive biosensor.

A rapid, facile and ultrasensitive fluorescence sensing system based on nitrogen-doped carbon dots (N-doped CDs) for the detection of ascorbic acid (AA) was developed. The highly photoluminescent N-doped CDs with excellent solubility in water and good biocompatibility were prepared by a one-step hydrothermal synthesis and gave the fluorescence quantum yield of 47%. The addition of AA can intensively suppress the fluorescence of the N-doped CDs through the synergistic effect of the inner filter effect (IFE) and the static quenching effect (SQE). Benefited from the remarkable synergistic effect of IFE and SQE, a facile and ultrasensitive sensor was constructed successfully for AA sensing. The detection procedure was achieved within 2min. The linear response range of AA was obtained from 10-3 to 10-8 M with a detection limit of 5nM. This developed method enjoyed many merits including more simplicity, lost cost, high sensitivity, good selectivity, rapid response and excellent biocompatibility. Notably, the proposed fluorescent sensor exhibits excellent performance and applicability for AA determination in human serum and rat brain microdialysate, and may provide a fast yet facile route for AA detection in physiological and pathological fields.

Early detection and diagnosis have great practical significances for the effective prevention and treatment of cancer. In this study, we developed a novel, facile and ultra-sensitive fluorescence assay for the determination of tumor invasive biomarker β-glucuronidase (GLU) based on the inner-filter effect (IFE). The nitrogen-doped carbon quantum dots (N-CQDs) with green photoluminescence were employed as the fluorophore in IFE, and 4-nitrophenyl-β-D-glucuronide (PNPG) was used to act as GLU substrate, and GLU catalytic product (p-nitrophenol (PNP)) was capable of acting as the robust absorber in IFE to turn off the fluorescence of N-CQDs due to the complementary overlap between the absorption of PNP and the excitation of N-CQDs. Thus, signal of GLU activity could be recorded by the fluorescence intensity of N-CQDs. Unlike other fluorescence sensing mechanism such as fluorescence resonance energy transfer (FRET) or photoinduced electron transfer (PET), IFE has no requirement for electron or energy transfer process or any chemical modification of fluorophore, which makes our assay more flexible and simple. The proposed method exhibited a good linear relationship from 1UL(-1) to 60UL(-1) (R(2)=0.9967) with a low detection limit of 0.3UL(-1). This method was also successfully applied to the analysis of serum samples and the inhibitor screening from natural product. The developed sensor platform was proven to be reliable, facile, sensitive, and selective, making it promising as a candidate for GLU activity detection in clinic tumor diagnose and anti-tumor drug screening.

The medicines targeted at α-glucosidase played an important role in anti-diabetes and anti-HIV therapy. Unfortunately, the method based on fluorescent assay strategy for α-glucosidase inhibitor screening remains poorly investigated. In this study, a novel "Turn On" fluorescence sensor platform has been developed for trace α-glucosidase inhibitor screening from natural medicines. Firstly, carbon dots were prepared by one-pot synthesis and used as the signal output. Combining with the carbon dots, cobalt oxyhydroxide (CoOOH) nanoflakes were employed to build the fluorescence resonance energy transfer (FRET) based sensor platform. Secondly, L-ascorbic acid-2-O-α-D-glucopyranosyl (AAG) was innovatively introduced as α-glucosidase substrate. With hydrolysis of AAG by α-glucosidase, ascorbic acids (AA) were released that can rapidly reduce CoOOH nanoflakes to Co(2+), and then FRET was stopped accompanying with the fluorescence recovery of CDs. The sensor platform was ultrasensitive to AA with a detection limit of 5 nM, ensuring the sensitive monitoring of enzyme activity. Acarbose was used as the inhibitor model and its inhibition rate is proportional to the logarithm of concentration in range of 10(-9)-10(-3)M with the correlation coefficient of R(2)=0.996, and an ultralow limit of detection of ~1×10(-9)M was obtained. The inhibiting ability of seven compounds isolated from natural medicines was also evaluated. The constructed sensor platform was proven to be sensitive and selective as well as cost-effective, facile and reliable, making it promising as a candidate for trace α-glucosidase inhibitor screening.

The determination of trace nitrosamines (NAs) has received more and more attention due to NAs' strong carcinogenicity and wide existence in foodstuffs. But the convenient and sensitive method for simultaneously analyzing multiple NAs remains poorly investigated. In the present study, a new method was developed for the determination of four NAs in foodstuffs based on fluorescence labeling followed by high-performance liquid chromatography with fluorescence detection (HPLC-FLD), which did not require complex pretreatments and expensive equipment. NAs were firstly denitrosated using hydrobromic acid-acetic acid to obtain the secondary amines. Subsequently, a fluorescence labelling procedure was immediately carried out to label the secondary amines using 1,2-benzo-3,4-dihydrocarbazole-9-ethyl chloroformate (BCEOC). A response surface methodology (RSM) based on a Box-Behnken design (BBD) was used to optimize the main parameters affecting the denitrosation. Under the optimal HPLC conditions, the quantitative linear range of analytes was 0.05-200 nmol L-1, and the correlation coefficients were more than 0.9998. Detection limits for all NA derivatives were achieved within the range of 1.3-2.5 ng L-1. The proposed method was successfully applied for the determination of trace NAs in several foodstuffs. This method was proven to be simple, inexpensive, sensitive, accurate and reliable for trace NA determination in foodstuffs.

A sensitive and inexpensive method involving ultrasound-assisted dispersive liquid–liquid microextraction (UA-DLLME) and pre-column derivatization followed by high-performance liquid chromatography with fluorescence detection (HPLC-FLD) was developed for the analysis of glycyrrhetinic acid. In this work, glycyrrhetinic acid could be obtained by hydrolyzing glycyrrhizic acid to remove glucuronic acid and subsequently extracted by UA-DLLME using chloroform and acetone as the extraction and disperser solvents, respectively. The sample extraction was firstly concentrated to dry under nitrogen and then rapidly derivatized with 2-(12-oxobenzo[b]acridin-5(12H)-yl)-ethyl-4-toluenesulfonate (BAETS) after the UA-DLLME. The prime parameters influencing the UA-DLLME and derivatization procedure were optimized using response surface methodology. Under the optimum conditions, the proposed method has a better linearity in a wider range of 6–300 ng mL−1 and a high square of correlation coefficient (R 2) at 0.9994. Limit of detection and limit of quantification were found to be 1.7 ng mL−1 and 5.8 ng mL−1, respectively. The proposed method was applied to the analysis of glycyrrhetinic acid in liquorice, liquorice apricot and sugar plum samples. For the analysis of the spiked samples, the spiked recoveries were in the range of 90.4–103.0 % with RSD less than 5.18 %. All results demonstrated that the UA-DLLME-HPLC-FLD (ultrasound-assisted dispersive liquid–liquid microextraction-high-performance liquid chromatography with fluorescence detection) was a sensitive, accurate, efficient analytical method for the determination of glycyrrhetinic acid.

BACKGROUND: Currently, commercially prepared complementary foods have become an important part of the diet of many infants and toddlers. But the method for simultaneous analysis of different types of micronutrient remains poorly investigated, which hinders the rapid and comprehensive quality control of infant foods. In the presented study, we first tried to employ the fluorescence labeling strategy combined with high-performance liquid chromatography-fluorescence detection for simultaneous determination of some acidic micronutrients including biotin, nicotinic acid, linolenic acid, eicosapentaenoic acid, docosahexaenoic acid, arachidonic acid and linoleic acid in infant foods.

Semicarbazide (SEM) has been proven to extensively exist in foodstuffs due to anthropogenic factor in food processing and possesses various toxic effects on human health. Although many methods have been developed, they often require long analytical time, complex laboratory equipment, trained personnel, difficultly prepared antibodies, or relatively expensive equipment. The present study developed a new method for SEM determination by HPLC with fluorescence detection (FLD). The fluorescence reagent, 2-(11H-benzo[a]carbazol-11-yl) ethyl chloroformate (BCEC), was first used for SEM labeling. The fluorescent labeling conditions were optimized systematically. SEM can be labeled in only 10 min at 40 °C. The labeled SEM was analyzed on an eclipse XDB-C8 column in 8 min. The new method offered the low LOD of 0.4 μg/kg at a signal-to-noise ratio of 3 and also exhibited excellent reproducibility, precision, and accuracy. When applied to analyze several foodstuffs, it showed good applicability. The developed method has been proven to be simple, inexpensive, selective, sensitive, accurate, and reliable for SEM analysis in foodstuffs. Furthermore, this developed method should have a powerful potential in the analysis of SEM from many other food samples.

Plant hormone determination in food matrices has attracted more and more attention because of their potential risks to human health. However, analytical methods for the analysis of multiple plant hormones remain poorly investigated. In the present study, a convenient, selective, and ultrasensitive high-performance liquid chromatography method for the simultaneous determination of multiple classes of plant hormones has been developed successfully using dispersive liquid-liquid microextraction followed by precolumn fluorescent labeling. Eight plant hormones in fruits including jasmonic acid, 12-oxo-phytodienoic acid, indole-3-acetic acid, 3-indolybutyric acid, 3-indolepropionic acid, gibberellin A(3), 1-naphthylacetic acid, and 2-naphthaleneacetic acid were analyzed by this method. The conditions employed for dispersive liquid-liquid microextraction were optimized systematically. The linearity for all plant hormones was found to be >0.9993 (R-2 values). This method offered low detection limits of 0.19-0.44 ng/mL (at a signal-to-noise ratio of 3), and method accuracies were in the range of 92.32-103.10%. The proposed method was applied to determine plant hormones in five kinds of food samples, and this method can achieve a short analysis time, low threshold levels of detection, and a high specificity for the analysis of targeted plant hormones present at trace level concentrations in complex matrices.