Ydethygesen9805

N-acylated homoserine lactones (AHLs), a class of auto-inducers produced by Gram-negative bacteria, are typical signaling molecules in quorum sensing (QS) systems. Importantly, AHLs play a key role in determining the virulence of foodborne pathogens and reflect the activity of spoilage bacteria. In this study, an eco-friendly fluorescence-sensing platform for the rapid and sensitive detection of AHLs was developed and characterized. Molecularly imprinted polymers embedded with yellow-emitting carbon quantum dots (CQDs) were obtained via the sol-gel process using furanone as an alternative template molecule, and long-wave-emitting CQDs with excellent optical properties were used as signal conversion materials. After template elution, the blotting cavities on the surface of the CQD@MIPs (molecularly imprinted polymers) were able to selectively recognize AHLs, demonstrating a stronger fluorescence response compared with the corresponding CQD@NIPs (non-imprinted polymers). Under optimal test conditions, a good linear relationship between the concentration of analyte and the relative fluorescence intensity of the CQD@MIPs was observed. The linear detection range was 0-2.0 μM, and the limit of detection (LOD) was 0.067 μM. Importantly, the proposed sensing platform functioned as an optical detection strategy that responded quickly (2 min) to AHLs. Additionally, this sensing platform was applied to the analysis of AHLs in bacterial supernatant samples with satisfactory results. More interestingly, the 3D-printing CQD@MIPs were tentative explored in this work, which was personalized and portable, has an advantage of point of care testing (POCT) detection in the future. Based on these results, this detection strategy has demonstrated substantial potential for application in and the field of food safety.The demand of simple, sensitive, selective and reliable assay for aflatoxin B1 (AFB1) detection is ubiquitous in food safety, due to its high toxic. Herein, a novel fluorescent aptasensor using metal-organic frameworks (UiO-66-NH2) and TAMRA label aptamer as sensing platform for AFB1 detection was developed. The TAMRA aptamer adsorbed on the surface of UiO-66-NH2 via van der Waals force and its fluorescence was quenched for the charge transfer from fluorescence dye TAMRA to metal ions of UiO-66-NH2. After introducing AFB1 to the system, the TAMRA aptamer binded to AFB1 and formed TAMRA aptamer/AFB1complex, making its conformation change and resulting in fluorescence recovery. Thus, the quantity of AFB1 could be analyzed according to the fluorescence signal change. Under optimize experimental conditions, the assay exhibited high sensitivity toward AFB1 in range of 0-180 ng mL-1 with low limit of detection of 0.35 ng mL-1 and good specificity against other toxins. Moreover, the aptamer/metal-organic frameworks sensing platform could be utilized to determine AFB1 content in food samples such as corn, rice and milk. It provided a reasonable method for other mycotoxin detection by changing the sequence of aptamer.Magnetic photocatalyst coupling with molecular imprinting technique is an efficient method for the specific photodegrade organic pollutants. Herein, this method is applied to fabricate a photoelectrochemical sensing platform for bisphenol A (BPA) detection based on electro-polymerization of molecularly imprinting pyrrole (MI-PPy) on the core-shell magnetic nanoparticles, Fe3O4@C@TiO2, which is magnetically adsorbed on magnetic glassy carbon electrode (MGCE). The MI-PPy layer not only provides molecular recognition capabilities for selective absorption of BPA, but also improves the photoelectrochemical behavior because of the heterostructure of TiO2/PPy that accelerated photoelectron transfer, which is a strategy to kill two birds with one stone. Therefore, the fabricated sensor shows a high sensitivity of 3.74 μA μM-1 cm-2 and excellent selectivity for BPA detection. Meanwhile, the electrode could be renewed by the UV irradiation and thus exhibits good recyclability and long-term stability. Under optimum conditions, the as-prepared electrode exhibited good photocurrent response for the detection of BPA, and allowed detection of BPA at a concentration as low as 0.03 μM. The favorable performance for BPA detection in real samples is able to extend more application of photoelectrochemical sensors for sensitive and long-term monitoring of environmental pollutants.Over the last decade, advances related to high-resolution mass spectrometry (HRMS) have led to improved capabilities for non-targeted chemical analyses. Important applications for these capabilities include identifying unknown xenobiotics and discovering emerging contaminants in human samples as exposure biomarkers. Despite technological advances, identifying unknown compounds by non-targeted analyses remains challenging due in part to the lack of MS spectral libraries and inherent sample complexity resulting in the generation of large amounts of MS data. While high resolution can separate nominally isobaric compounds in a mass spectrum, isomers cannot be distinguished. Much work also remains to develop models to predict both mass spectra and retention times for the unexplored regions of chemical space. In this review, we focus on recent advances and applications of non-targeted analyses using liquid chromatography - high-resolution mass spectrometry (LC-HRMS) in human biomonitoring, including sample preparation, molecular formula assignments, and prediction models for retention times and mass fragmentations, to enable and improve identifications of unknown chemicals. FM19G11 datasheet The purpose of this review is to improve our understanding of the applicability and limitations in both the analytical methods and data analysis aspects of non-targeted analysis in human exposure studies. We also discuss the challenges and prospects in this field for future research on sample preparation, identification confidence and accuracy, data processing tools, MS spectra comparability, liquid chromatographic retention time (RT) prediction algorithms, and quantitative capabilities.This study evaluates the use of Fourier transform infrared spectroscopy with attenuated total reflectance (ATR/FTIR) in tandem with data driven soft independent modeling of class analogy (DD-SIMCA) to check authenticity and monitor virgin coconut oil adulteration. By using infrared spectra of pure samples and samples adulterated with canola, corn, sunflower and soybean, one class models were developed to evaluate the authenticity and adulteration of virgin coconut oil. The proposed methodology was able to confirm the authenticity and to detect the adulteration with all tested oils in a concentration range of 10-40%. Also, it was possible to identify the four adulterants oils studied with 88-100% of sensitivity and 96-100% of specificity. The results indicated that ATR/FTIR spectroscopy in conjunction with a one-class strategy based on DD-SIMCA is a clean and fast methodology that can be easily implemented for virgin coconut oil purity control.