Xinhui Chenpi (XHCP) is a well-known type of Chenpi (CP) widely used as both a Chinese herb and a food ingredient. While previous studies have explored how the quality of CP changes over time, there has been limited research specifically on XHCP. This study aims to assess the chemical components and quality of XHCP based on total flavonoid content (TF), antioxidant activity (AA), and color value (CV) at two stages: freshly harvested (XHCP-0Y) and after 3 years of storage (XHCP-3Y). Thirty-eight common volatile compounds were identified, and the content of 17 compounds among them, nine nonvolatile compounds, which included one alkaloid (synephrine), three phenolic acids (PA, protocatechuic acid, vanillic acid, and ferulic acid), and five flavonoids (narirutin, hesperidin, sinensetin, nobiletin, and tangeretin), were firstly detected by the newly developed gas chromatograph-mass spectrometer (GC-MS) and ultra-performance liquid chromatography (UPLC) methods. Compared to XHCP-0Y, the content of 17 volatile compounds and synephrine decreased in XHCP-3Y to varying degrees, while the content of PA, five flavonoids, TF, AA, and CV increased. The reduction of dryness caused by volatile compounds and the enhancement of efficacy related to PA, flavonoids, and AA suggested improved quality of XHCP after 3 years of storage. The methods developed in this study show promise for evaluating the quality of XHCP during the aging process.

The real-time, precise qualitative and quantitative sensing of food flavor compounds is crucial for ensuring food safety, quality, and consumer acceptance. As indicators for food flavor labeling, it is vital to delve deep into the specific ingredient and content of food flavor compounds to assess the food flavor quality, but still facing huge challenges. Photoluminescent fluorescent probe technology, with fast detection and high sensitivity, has shown immense potentials in detecting food flavor compounds. In this review, the classification and optical sensing mechanism of photoluminescent fluorescent probe technology are described in detail. Besides, challenges in applying photoluminescent fluorescent probe technology to analyze food flavor compounds are outlined to indicate future research directions. We hope this review can provide an insight for the applications of photoluminescent fluorescent probe technology in the evaluation of food flavor quality in future.

BACKGROUND: In the fields of environmental monitoring and nuclear emergency, in order to obtain the relevant information of uranyl-induced environmental pollution and nuclear accident, it is necessary to establish a rapid quantitative analytical technique for uranyl ions. As a new promising technique, surface-enhanced Raman scattering (SERS) is hopeful to achieve this goal. However, uranyl ions are easily desorbed from SERS substrates under acidic conditions, and the structures of SERS substrates will be destroyed in the strong acidic aqueous solutions. Besides, the quantitative detection ability of SERS for uranyl ions needs to be promoted. Hence, it is necessary to develop new SERS substrates for accurate quantitative detection of trace uranyl in environmental water samples, especially in acidic solutions.
RESULTS: In this work, we prepared silver ions/sodium alginate supramolecular hydrogel membrane (Ag+/SA SMH membrane), and the Ag+ ions from the membrane were transformed into Ag/Ag2O complex nanoparticles under laser irradiation. The Raman signal of uranyl was strongly enhanced under the synergistic interaction of electromagnetic enhancement derived from the Ag nanoparticles and charge transfer enhancement between uranyl and Ag2O. Utilizing the peak of SA (550 cm-1) as an internal standard, a quantitative detection with a LOD of 6.7 × 10-9 mol L-1 was achieved due to a good linear relation of uranyl concentrations from 1.0 × 10-8 mol L-1 to 2 × 10-6 mol L-1. Furthermore, foreign metal ions hardly affected the SERS detection of uranyl, and the substrate could determine trace uranyl in natural water samples. Particularly, the acidity had no obvious effect on SERS signals of uranyl ions. Therefore, in addition to the detection of uranyl ions in natural water samples, the proposed strategy could also detect uranyl ions in strong acidic solutions.
UNASSIGNED: A simple one-step method was used to prepare an Ag+/SA SMH membrane for rapid quantitative detection of uranyl ions for the first time. The proposed substrate successfully detected uranyl ions under acidic conditions by immobilizing uranyl ion in hydrogel structure. In comparison with the previous studies, a more accurate quantitative analysis for uranyl ions was achieved by using an internal standard, and the proposed strategy could determine trace uranyl in either natural water samples or strong acidic solutions.

Track irregularities directly affect the quality and safety of railway vehicle operations. Quantitative detection and real-time monitoring of track irregularities are of great importance. However, due to the frequent variable vehicle speed, vehicle operation is a typical non-stationary process. The traditional signal analysis methods are unsuitable for non-stationary processes, making the quantitative detection of the wavelength and amplitude of track irregularities difficult. To solve the above problems, this paper proposes a quantitative detection method of track irregularities under non-stationary conditions with variable vehicle speed by order tracking analysis for the first time. Firstly, a simplified wheel-rail dynamic model is established to derive the quantitative relationship between the axle-box vertical vibration and the track vertical irregularities. Secondly, the Simpson double integration method is proposed to calculate the axle-box vertical displacement based on the axle-box vertical acceleration, and the process error is optimized. Thirdly, based on the order tracking analysis theory, the angular domain resampling is performed on the axle-box vertical displacement time-domain signal in combination with the wheel rotation speed signals, and the quantitative detection of the track irregularities is achieved. Finally, the proposed method is validated based on simulation and field test analysis cases. We provide theoretical support and method reference for the quantitative detection method of track irregularities.

Flexible and transparent surface-enhanced Raman scattering (SERS) substrates have attracted considerable attention for their ability to enable the direct in situ detection of analytes on curved surfaces. However, the curvature of an object can impact the signal enhancement of SERS during the measurement process. Herein, we propose a simple approach for fabricating a curvature-insensitive transparent SERS substrate by depositing silver nanoparticles (Ag NPs) onto a large-area wrinkled polystyrene/polydimethylsiloxane (Ag NP@W-PS/PDMS) bilayer film. Using rhodamine 6G (R6G) as a probe molecule, the optimized Ag NP@W-PS/PDMS film demonstrates a high analytical enhancement factor (AEF) of 4.83 × 105, excellent uniformity (RSD = 7.85%) and reproducibility (RSD = 3.09%), as well as superior mechanical flexibility. Additionally, in situ measurements of malachite green (MG) on objects with diverse curvatures, including fish, apple, and blueberry, are conducted using a portable Raman system, revealing a consistent SERS enhancement. Furthermore, a robust linear relationship (R2 ≥ 0.990) between Raman intensity and the logarithmic concentration of MG detected from these objects is achieved. These results demonstrate the tremendous potential of the developed curvature-insensitive SERS substrate as a point-of-care testing (POCT) platform for identifying analytes on irregular objects.

Most previously studies had considered that plant fungal disease spread widely and quickly by airborne fungi spore. However, little is known about the release dynamics, aerodynamic diameter, and pathogenicity threshold of fungi spore in air of the greenhouse environment. Grape gray mold is caused by Botrytis cinerea; the disease spreads in greenhouses by spores in the air and the spore attaches to the leaf and infects plant through the orifice. In this study, 120 μmol/L propidium monoazide (PMA) were suitable for treatment and quantitation viable spore by quantitative real-time PCR, with a limit detection of 8 spores/mL in spore suspension. In total, 93 strains of B. cinerea with high pathogenicity were isolated and identified from the air samples of grapevines greenhouses by a portable sampler. The particle size of B. cinerea aerosol ranged predominately from 0.65-3.3 μm, accounting for 71.77% of the total amount. The B. cinerea spore aerosols were infective to healthy grape plants, with the lowest concentration that could cause disease being 42 spores/m3. Botrytis cinerea spores collected form six greenhouse in Shandong Province were quantified by PMA-qPCR, with a higher concentration (1182.89 spores/m3) in May and June and a lower concentration in July and August (6.30 spores/m3). This study suggested that spore dispersal in aerosol is an important route for the epidemiology of plant fungal disease, and these data will contribute to the development of new strategies for the effective alleviation and control of plant diseases.

Long-stranded non-coding RNAs (lncRNA) have important roles in disease as transcriptional regulators, mRNA processing regulators and protein synthesis factors. However, traditional methods for detecting lncRNA are time-consuming and labor-intensive, and the functions of lncRNA are still being explored. Here, we present a surface enhanced Raman spectroscopy (SERS) based biosensor for the detection of lncRNA associated with liver cancer (LC) as well as in situ cellular imaging. Using the dual SERS probes, quantitative detection of lncRNA (DAPK1-215) can be achieved with an ultra-low detection limit of 952 aM by the target-triggered assembly of core-satellite nanostructures. And the reliability of this assay can be further improved with the R2 value of 0.9923 by an internal standard probe that enables the signal dynamic calibration. Meanwhile, the high expression of DAPK1-215 mainly distributed in the cytoplasm was observed in LC cells compared with the normal ones using the SERS imaging method. Moreover, results of cellular function assays showed that DAPK1-215 promoted the migration and invasion of LC by significantly reducing the expression of the structural domain of death associated protein kinase. The development of this biosensor based on SERS can provide a sensitive and specific method for exploring the expression of lncRNA that would be a potential biomarker for the screening of LC.

Uranium is an essential nuclear material in civilian and military areas; however, its extensive application raises concerns about the potential safety issues in the fields of environmental protection and nuclear industry. In this study, we developed an Ag/Ag2O-COF (covalent-organic framework) composite SERS substrate to detect uranyl ions (UO22+) in environmental aqueous solutions. Herein, the strong SERS effect of uranyl adsorbed in Ag/Ag2O composite and the high adsorption efficiency of COF TpPa-1 were combined to realize the trace detection of uranyl ions. This method displayed a linear range of 10-8 mol L-1 to 10-6 mol L-1 with the detection limit of 8.9 × 10-10 mol L-1 for uranyl ions. Furthermore, common metal cations and oxo-ions hardly affected the SERS detection of uranyl, which is helpful for the trace analysis of uranyl in natural water samples. Although the proposed strategy is deployed for uranyl detection, the reusable and high-efficiency system may be expanded to trace detection of other substance with Raman activity.

In order to design organic small molecule fluorescent materials with multiple sensing, a bibranched -NH2 modified cyanostilbene derivative (AM) was synthesized. It exhibits solvent and aggregation-induced emission effects, with a solid-state quantum yield of 28%, which is seven times higher than that in THF. The synthesized sample AM demonstrated high sensitivity to trace water via a fluorescence \"turn-off\" response, achieving a low detection limit of 0.41 µM in THF and 0.80 µM in EtOH. AM also exhibits a \"turn-off\" response to picric acid, attributed to the photo-induced electron transfer effect it induces. The recognition of picric acid by AM demonstrates specificity and resistance to interference from nitro explosives, with a detection limit of 300 ppb and a linear relationship (R2 = 0.9981) at the range of 0-4 equivalents AM. Such acid recognition can facilitate the design of qualitative test papers and safety inks. Additionally, AM can function as a temperature sensor with a linear relationship (R2 = 0.9976) within the temperature range of 25-110 °C. Leveraging these unique characteristics, a series of methods were proposed for the direct quantitative determination of trace water in nonaqueous solvents, picric acid, and temperature.

Antibiotic mycelia residues (AMRs) contain antibiotic residues. If AMRs are ingested in excess by livestock, it may cause health problems. To address the current problem of unknown pixel-scale adulteration concentration in NIR-HSI, this paper innovatively proposes a new spectral simulation method for the evaluation of AMRs in protein feeds. Four common protein feeds (soybean meal (SM), distillers dried grains with solubles (DDGS), cottonseed meal (CM), and nucleotide residue (NR)) and oxytetracycline residue (OR) were selected as study materials. The first step of the method is to simulate the spectra of pixels with different adulteration concentrations using a linear mixing model (LMM). Then, a pixel-scale OR quantitative model was developed based on the simulated pixel spectra combined with local PLS based on global PLS scores (LPLS-S) (which solves the problem of nonlinear distribution of the prediction results due to the 0%-100% content of the correction set). Finally, the model was used to quantitatively predict the OR content of each pixel in hyperspectral image. The average value of each pixel was calculated as the OR content of that sample. The implementation of this method can effectively overcome the inability of PLS-DA to achieve qualitative identification of OR in 2%-20% adulterated samples. In compared to the PLS model built by averaging the spectra over the region of interest, this method utilizes the precise information of each pixel, thereby enhancing the accuracy of the detection of adulterated samples. The results demonstrate that the combination of the method of simulated spectroscopy and LPLS-S provides a novel method for the detection and analysis of illegal feed additives by NIR-HSI.