Search

Herein, a novel visual method for detecting triazophos based on competitive bio-barcode immunoassay was described. The competitive immunoassay was established by gold nanoparticles (AuNPs), magnetic microparticle (MMPs) and triazophos, combined with biochip hybridization system to detect the residual of triazophos in water and apple. Because AuNPs carried many bio-barcodes, which hybridized with labeled DNA on the biochip, catalyzed signal amplification using silver staining was detected by grayscale values as well as the naked eye. Notably, the grayscale values decreases with increasing the concentrations of triazophos, and the color change weakened gradually. The detection range was in between 0.05 and 10 ng/mL and the minimum detection limit was set at 0.04 ng/mL. Percent recovery calculated from spiked water and apple samples ranged between 55.4 and 107.8% with relative standard deviations (RSDs) of 12.4-24.9%. It has therefore been shown that this protocol provides a new insight for rapid detection of small molecule pesticides in various matrices.

The existing coal mine equipment digital twin modeling method mainly focuses on single equipment modeling. It lacks three machine coupling collaborative relationship analysis. In order to solve the above problems, the paper puts forward three machine digital twin and collaborative modeling method for fully mechanized working face. By adopting an intelligent modeling method, the method constructs agent-based models of a coal mining machine, a hydraulic support and a scraper conveyor which comprise a sensing unit, a control unit and an execution unit. The method constructs corresponding visual models according to a three-dimensional modeling process. The method drives the three-dimensional models to move by the intelligent models. The combination of the two forms a digital twin model of three machines. A discrete event modeling method is used to construct a collaborative process model covering the interaction process of the three machine digital twin model. The three machine mining process is sorted out according to the time sequence to form a three machine collaborative process time sequence table. The digital twin model is used to describe the state and behavior of the three machines in fully mechanized mining and to simulate the calculation at the individual level. The collaborative process model is used to represent the sequential action transformation between digital twin models and realize the deduction of the whole three machine collaborative process. The simulation of rocker lifting and lowering for the digital twin model of the shearer is carried out. The simulation results show that compared with the measured data of real equipment, the model error is small, an average error of rocker arm dip angle is 2.3°. The simulation of continuous column lifting action for the digital twin model of hydraulic support is carried out. The simulation results show good consistency between the model and real equipment. Compared with the measured data of the real equipment, the average angle error is 0.14° and the average stroke error is 6.3 mm. Combined with the actual production log of the coal mine, the virtual and real simulation experiment of the three machine collaborative model is carried out. The results show that the three machine digital twin model of the fully mechanized working face and real equipment realize mutual mapping. The simulation results are close to the real records. The three machine collaborative model can accurately reflect the collaborative mining process. The method of three machine digital twin and collaborative modeling for fully mechanized working face provides a new idea for the digital twin modeling of fully mechanized coal mining equipment and its collaborative relationship.

Although the toxicity of triazophos is high and it has been pulled from the market in many countries; it is still widely used and frequently detected in agricultural products. While conventional analyses have been routinely used for the quantification and monitoring of triazophos residues, those for detecting low residual levels are deemed necessary. Therefore, we developed a novel and sensitive fluorometric signal amplification immunoassay employing bio-barcodes for the quantitative analysis of triazophos residues in foodstuffs and surface water. Herein, monoclonal antibodies (mAbs) attached to gold nanoparticles (AuNPs) were coated with DNA oligonucleotides (used as a signal generator), and a complementary fluorogenic RNA was used for signal amplification. The system generated detection signals through DNA-RNA hybridization and subsequent dissociation of fluorophores by Ribonuclease H (RNase H). It has to be noted that RNase H can only disintegrate the RNA in DNA-RNA duplex, but not cleave single or double-stranded DNA. Hence, with iterative cycles of DNA-RNA hybridization, sufficient strong signal was obtained for reliable detection of residues. Furthermore, this method enables quantitative detection of triazophos residues through fluorescence intensity measurements. The competitive immunoassay shows a wide linear range of 0.01-100 ng/mL with a limit of detection (LOD) of 0.0032 ng/mL. The assay substantially meets the demand for the low residue detection of triazophos residues in agricultural products and water samples. Accuracy (expressed as spiked recovery %) and coefficient of variation (CV) were ranged from 73.4% to 116% and 7.04% to 17.4%, respectively. The proposed bio-barcodes immunoassay has the advantages of being stable, reproducible, and reliable for residue detection. In sum, the present study provides a novel approach for detection of small molecules in various sample matrices.

A liquid chromatography–tandem mass spectrometry method with vonoprazan fumarate‐d4 as a stable isotope‐labeled internal standard was developed and validated aiming at quantification of vonoprazan fumarate in human plasma for a bioequivalence study. Chromatographic separation was achieved by acetonitrile one‐step protein precipitation using a gradient elution of 0.1% formic acid aqueous solution and acetonitrile with a run time of 3.65 min. Detection was carried out on a tandem mass spectrometer in multiple reaction monitoring mode via a positive electrospray ionization interface. The multiple reaction monitoring mode of precursor–product ion transitions for vonoprazan fumarate and vonoprazan fumarate‐d4 were m/z 346.0 → 315.1 and 350.0 → 316.0, respectively. The linear range was 0.150–60.000 ng/ml. This method was fully validated with acceptable results in terms of selectivity, carryover, lower limit of quantification, calibration curve, accuracy, precision, dilution effect, matrix effect, stability, recovery and incurred sample reanalysis. A successful application of this method was realized in the bioequivalence study of vonoprazan fumarate tablet (20 mg) among healthy Chinese volunteers. [ABSTRACT FROM AUTHOR]

Meat and meat products are highly susceptible to contamination by microorganisms and foodborne pathogens, which cause serious economic losses and health hazards. The large consumption and waste of meat and meat products means that there is a need for safe and effective preservation methods. Furthermore, toxicological aspects of chemical preservation techniques related to major health problems have sparked controversies and have prompted consumers and producers to turn to natural preservatives. Consequently, natural preservatives are being increasingly used to ensure the safety and quality of meat products as a result of customer preferences and biological efficacy. However, information on the current status of these preservatives is scattered and a comprehensive review is lacking. Here, we review current knowledge on the classification, mechanisms of natural preservatives and their applications in the preservation of meat and meat products, and also discuss the potential of natural preservatives to improve the safety of meat and meat products. The current status and the current research gaps in the extraction, application and controlled‐release of natural antibacterial agents for meat preservation are also discussed in detail. This review may be useful to the development of efficient food preservation techniques in the meat industry. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The Blasingame method is a valuable tool for analysing the diminishing production challenge in the presence of variable bottomhole pressure and diverse production conditions. It is essential to highlight that the Blasingame method views the closed reservoir as the outer boundary condition for its model. This paper introduces the concept of the equivalent well control radius and formulates the Blasingame method based on the fluid flow characteristics inherent in twin-well production, taking into account the influence of inter- well interference. This study provides an in-depth analysis of production variations in reservoirs with inter-well interference by examining Blasingame type-curve definitions of the dimensionless parameters. Additionally, it investigates key factors impacting production, including neighbouring wells' production, distance, and opening time: variations in all three parameters lead to different levels of interference between wells, which manifests itself in the regularised production integral derivative curve with different lengths and heights of convexity. Numerical simulations employing orthogonality are conducted to validate the reliability of this method. The results of these simulations offer theoretical support for the precise evaluation of reservoirs facing similar challenges. [ABSTRACT FROM AUTHOR]