Antibiotics are a category of chemical compounds used to treat bacterial infections and are widely applied in cultivation, animal husbandry, aquaculture, and pharmacy. Currently, residual antibiotics ...and their metabolites pose a potential risk of allergic reactions, bacterial resistance, and increased cancer incidence. Residual antibiotics and the resulting bacterial antibiotic resistance have been recognized as a global challenge that has attracted increasing attention. Therefore, monitoring antibiotics is a critical way to limit the ecological risks from antibiotic pollution. Accordingly, it is desirable to devise new analytical platforms to achieve efficient antibiotic detection with excellent sensitivity and specificity. Quantum dots (QDs) are regarded as an ideal material for use in the development of antibiotic detection biosensors. In this review, we characterize different types of QDs, such as silicon, chalcogenide, carbon, and other doped QDs, and summarize the trends in QD-based antibiotic detection. QD-based sensing applications are classified according to their recognition strategies, including molecularly imprinted polymers (MIPs), aptamers, and immunosensors. We discuss the advantages of QD-derived antibiotic sensors, including low cost, good sensitivity, excellent stability, and fast response, and illustrate the current challenges in this field.
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•The strategies of applying quantum dots (QDs) in antibiotic detection are described.•The QD-based sensors of antibiotics are first summarized.•Sensors are classified according to antibiotic-recognition strategy.•QD antibiotic detection abilities and advantages are described.
In this article, a fast direct solver based on strong admissibility skeletonization factorization (SASF) is proposed for electromagnetic scattering from conducting objects. Different from the ...conventional skeletonization scheme, the proposed skeletonization constructs the hierarchical matrix representation, in which only far-field interactions are compressed. As a result, the approximation rank is relatively small, and the computational efficiency will have significant improvement. Subsequently, the strong skeletonization factorization is applied to the compressed system matrix. The system matrix can be factorized into products of a series of block unit triangular matrices and a block diagonal matrix. The arising fill-in blocks corresponding to far-field interactions are compressed and eliminated by a novel and efficient method to maintain the high efficiency and accuracy of the factorization procedure. The computational complexity and storage requirement of the proposed factorization scale as <inline-formula> <tex-math notation="LaTeX">O(N^{1.5}) </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">O(N \log N) </tex-math></inline-formula>, respectively. Several numerical results are presented to demonstrate the accuracy and effectiveness of the proposed method.
In environmental modeling, the impact of fixed scatterers on the background environment can be effectively accounted for by using numerical Green's functions (NGF), which significantly reduces the ...number of unknowns in the problem. A recursive solution to acquire NGF using artificial neural networks (ANN) acceleration is presented for multibody scattering scenarios. The recursive method is employed to decompose the multibody problem, transforming the interaction between scatterers into a generalized incident field via NGF. This allows for the decomposition of the scattering characteristics of the multibody problem in the presence of intense oscillations into the effects of single bodies. This decomposition facilitates the accelerated calculation of neural networks. In addition, the scatterers' center positions as prior information can assist the network in extracting data features effectively, leading to an overall improvement in the learning performance of ANN. The implementation of the recursive method combined with ANN acceleration for solving the NGF of the multibody problem not only enhances the accuracy of the neural network acceleration approach but also significantly reduces the overall runtime when compared to the conventional calculation method. Numerical results demonstrate that the relative error of the proposed method accumulates with the recursions and is less than 8.5% after 11 recursions, and the computation time is reduced to about 6.5% of the method of moment.
Synthetic aperture radar (SAR) can perform observations at all times and has been widely used in the military field. Deep neural network (DNN)-based SAR target recognition models have achieved great ...success in recent years. Yet, the adversarial robustness of these models has received far less academic attention in the remote sensing community. In this article, we first present a comprehensive adversarial robustness evaluation framework for DNN-based SAR target recognition. Both data-oriented metrics and model-oriented metrics have been used to fully assess the recognition performance under adversarial scenarios. Adversarial training is currently one of the most successful methods to improve the adversarial robustness of DNN models. However, it requires class labels to generate adversarial attacks and suffers significant accuracy dropping on testing data. To address these problems, we introduced adversarial self-supervised learning into SAR target recognition for the first time and proposed a novel unsupervised adversarial contrastive learning-based defense method. Specifically, we utilize a contrastive learning framework to train a robust DNN with unlabeled data, which aims to maximize the similarity of representations between a random augmentation of a SAR image and its unsupervised adversarial example. Extensive experiments on two SAR image datasets demonstrate that defenses based on adversarial self-supervised learning can obtain comparable robust accuracy over state-of-the-art supervised adversarial learning methods.
A modified hierarchically off-diagonal low-rank (HODLR) fast direct solver is presented to analyze the scattering by electrically large and complex perfect electric conducting objects. The overall ...idea of HODLR solver is that the impedance matrix can be decomposed into the multiplication of several diagonal block matrices and the inverse is obtained easily with Sherman-Morrison-Woodbury formula. In this paper, a novel modified matrix compression method is utilized for the low-rank approximation of the off-diagonal submatrices. The proposed method only compresses the far-group subblocks judged by extended admissibility condition. The low-rank representations of the off-diagonal submatrices are then reconstructed and recompressed with the help of adaptive tolerance strategy. Consequently, the computation time and storage requirements will reduce significantly compared with the conventional solver. Several numerical results are presented to demonstrate the effectiveness and accuracy of the proposed method.
Due to the unexpected side effects of the iodinated contrast agents, novel contrast agents for X-ray computed tomography (CT) imaging are urgently needed. Nanoparticles made by heavy metal elements ...are often employed, such as gold and bismuth. These nanoparticles have the advantages of long in vivo circulation time and tumor targeted ability. However, due to the long residence time in vivo, these nanoparticles may bring unexpected toxicity and, the preparation methods of these nanoparticles are complicated and time-consuming.
In this investigation, a small molecular bismuth chelate using diethylenetriaminepentaacetic acid (DPTA) as the chelating agent was proposed to be an ideal CT contrast agent.
The preparation method is easy and cost-effective. Moreover, the bismuth agent show better CT imaging for kidney than iohexol in the aspect of improved CT values. Up to 500 µM, the bismuth agent show negligible toxicity to L02 cells and negligible hemolysis. And, the bismuth agent did not induce detectable morphology changes to the main organs of the mice after intravenously repeated administration at a high dose of 250 mg/kg. The pharmacokinetics of the bismuth agent follows the first-order elimination kinetics and, it has a short half-life time of 0.602 h. The rapid clearance from the body promised its excellent biocompatibility.
This bismuth agent may serve as a potential candidate for developing novel contrast agent for CT imaging in clinical applications.
The Maillard reaction (MR) has been known to modify proteins and optimize their physicochemical properties by conjugating with reducing sugars. The structure and physicochemical properties of wheat ...gliadin and maize amylopectin conjugates induced by MR were investigated under different gliadin–amylopectin ratios (2:1, 1:1, 1:2, 1:4, and 1:8). The formation of conjugates was indicated by sodium dodecyl sulfate‐polyacrylamide gel electrophoresis, degree of conjugation, and browning development analyses. The Fourier transform infrared and fluorescence spectroscopy analyses suggested changes in the structures of conjugates and the microenvironment of amino acids. A remarkable decrease in the β‐turn structure content and an increase in the free sulfhydryl group content were observed at a ratio of 1:8, leading to decreased allergenicity. The reaction process was commendably controlled at a ratio of 1:1 with a 59.7% degree of conjugation in this group, contributing to the amelioration of solubility and foaming properties. Meanwhile, improvements in the oil holding capacity, surface hydrophobicity, and emulsifying properties were observed at a ratio of 1:4.
Practical Application
The study revealed that the conjugates produced by MR might have various degrees of improved functional properties and reduced allergenicity at different ratios of substrates. Our study might be helpful for conjugates to assist in improving the texture of products and its potential in expanding the industrial application of products with gliadin.
The emergence of new immune-evasive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and subvariants outpaces the development of vaccines specific against the dominant ...circulating strains. In terms of the only accepted immune correlate of protection, the inactivated whole-virion vaccine using wild-type SARS-CoV-2 spike induces a much lower serum neutralizing antibody titre against the Omicron subvariants. Since the inactivated vaccine given intramuscularly is one of the most commonly used coronavirus disease 2019 (COVID-19) vaccines in developing regions, we tested the hypothesis that intranasal boosting after intramuscular priming would provide a broader level of protection. Here, we showed that one or two intranasal boosts with the Fc-linked trimeric spike receptor-binding domain from wild-type SARS-CoV-2 can induce significantly higher serum neutralizing antibodies against wild-type SARS-CoV-2 and the Omicron subvariants, including BA.5.2 and XBB.1, with a lower titre in the bronchoalveolar lavage of vaccinated Balb/c mice than vaccination with four intramuscular doses of inactivated whole virion vaccine. The intranasally vaccinated K18-hACE2-transgenic mice also had a significantly lower nasal turbinate viral load, suggesting a better protection of the upper airway, which is the predilected site of infection by Omicron subvariants. This intramuscular priming and intranasal boosting approach that achieves broader cross-protection against Omicron variants and subvariants may lengthen the interval required for changing the vaccine immunogen from months to years.
A new method of numerical simulating prediction and decontamination effect evaluation for abrasive jet decontamination to radioactively contaminated metal is proposed. Based on the Computational ...Fluid Dynamics and Discrete Element Model (CFD-DEM) coupled simulation model, the motion patterns and distribution of abrasives can be predicted, and the decontamination effect can be evaluated by image processing and recognition technology. The impact of three key parameters (impact distance, inlet pressure, abrasive mass flow rate) on the decontamination effect is revealed. Moreover, here are experiments of reliability verification to decontamination effect and numerical simulation methods that has been conducted. The results show that: 60Co and other homogeneous solid solution radioactive pollutants can be removed by abrasive jet, and the average removal rate of Co exceeds 80%. It is reliable for the proposed numerical simulation and evaluation method because of the well goodness of fit between predicted value and actual values: The predicted values and actual values of the abrasive distribution diameter are Ф57 and Ф55; the total coverage rate is 26.42% and 23.50%; the average impact velocity is 81.73 m/s and 78.00 m/s. Further analysis shows that the impact distance has a significant impact on the distribution of abrasive particles on the target surface, the coverage rate of the core area increases at first, and then decreases with the increase of the impact distance of the nozzle, which reach a maximum of 14.44% at 300 mm. It is recommended to set the impact distance around 300 mm, because at this time the core area coverage of the abrasive is the largest and the impact velocity is stable at the highest speed of 81.94 m/s. The impact of the nozzle inlet pressure on the decontamination effect mainly affects the impact kinetic energy of the abrasive and has little impact on the distribution. The greater the inlet pressure, the greater the impact kinetic energy, and the stronger the decontamination ability of the abrasive. But in return, the energy consumption is higher, too. For the decontamination of radioactively contaminated metals, it is recommended to set the inlet pressure of the nozzle at around 0.6 MPa. Because most of the Co elements can be removed under this pressure. Increasing the mass and flow of abrasives appropriately can enhance the decontamination effectiveness. The total mass of abrasives per unit decontamination area is suggested to be 50 g because the core area coverage rate of the abrasive is relatively large under this condition; and the nozzle wear extent is acceptable.
Huang-Lian-Jie-Du-Decoction (HLJDD), a prescription of traditional Chinese medicine, has been clinically used to treat diabetes for thousands of years and its mechanism was reported to be related to ...gut microbiota. However, no study has explored the effect of HLJDD on the gut microbiota in type 2 diabetes mellitus (T2DM) yet. Therefore, in this study, we investigated the modulation of gut microbiota induced by HLJDD treatment in T2DM in order to unveil the underlying mechanism.
A combination of high-fat diet (HFD) and streptozotocin (STZ) was used to induce T2DM in rats. Bacterial communities in the fecal samples from the control group, the T2DM model group, and the HLJDD-treated T2DM group were analyzed by 16S gene sequencing, followed with a subset sample analyzed by shotgun sequencing.
The HLJDD treatment significantly ameliorated hyperglycemia and inflammation in T2DM rats. Additionally, our results indicated that HLJDD treatment could not only restore the gut dysbiosis in T2DM rats, which was proved by an increasing amount of short chain fatty acids (SCFAs)-producing and anti-inflammatory bacteria such as
,
, and
as well as a decreasing amount of conditioned pathogenic bacteria (e.g.,
,
, and
), but also modulate the dysregulated function of gut microbiome in T2DM rats, including an up-regulation in bile acid biosynthesis as well as a reduction in glycolysis/gluconeogenesis and nucleotide metabolism.
HLJDD treatment could ameliorate hyperglycemia and restore the dysregulated microbiota structure and function to a normal condition mainly by increasing SCFAs-producing bacteria and reducing conditioned pathogenic bacteria in T2DM rats, which provides insights into the mechanism of HLJDD treatment for T2DM from the view of gut microbiota.
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