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In this work, a sensitive and quantitative immunochromatographic assay (ICA) detection method for avian influenza viruses (AIVs) of the H7 hemagglutinin (HA) antigen was established based on highly chromatic red silica nanoparticles (SiNPs). It can detect two H7 subtypes of influenza viruses, H7N2 and H7N9. The highly chromatic red SiNPs were prepared by adsorbing C.I. Direct Red 224 on the surface of the SiNPs for multiple times using the layer by layer (LbL) self-assembly method under the electrostatic action of ethylene imine polymer (PEI) and poly(sodium-p-styrenesulfonate) (PSS). The highly chromatic red silica nanoparticles modified with anti-H7 HA mAb1 were used as immunodetection probes. The accumulated highly chromatic red SiNPs on the T-line can be observed by the naked eye to qualitatively detect the H7 HA antigen. The quantitative analysis is carried out by using a camera and Image J software. Within the range of 0.1-10 ng mL-1, the linear equation between the H7 HA antigen concentration and the peak area of the T-line gray value was y = 868.9722 + 435.4836X (R2 = 0.9716), and the limit of detection (LOD) of this method was 0.08 pg mL-1 (S/N = 3). The highly chromatic red SiNP based ICA for the detection of H7 HA has no cross activity with other subtypes of influenza viruses. This method of combining highly chromatic colored markers with ICA has great potential in practical applications for the rapid and quantitative detection of other types of AIVs.

In this paper, monodisperse high chroma colored silica nanoparticles (SiNPs) were efficiently prepared by layer-by-layer (LbL) self-assembled technique. Poly(sodium-p-styrenesulfonate) (PSS) and Poly(ethyleneterephthalate) (PEI) were respectively used as polyanion and polycationic electrolytes. The monodisperse SiNPs with negative charge on the surface were used as the matrix. Direct dye (C.I Direct Red 224) was deposited on the SiNPs surface by means of LbL electrostatic adsorption. PEI and C.I. Direct Red 224 were electrostatically adsorbed on the surface of SiNPs. Then PSS and PEI were adsorbed on SiNPs surface to make the red SiNPs positive negative, respectively. And multilayer film-coated high chroma red SiNPs were prepared by repeating the above steps 4 times. The effects of concentration of polyelectrolyte, supporting salt (NaCl), amount of C.I Direct Red 224 and deposition time on dye coupling rate were studied. The multilayer film-coated high chroma red SiNPs were characterized using Scanning Electron Microscopy (SEM), Nano ZS potential laser particle analyzer and UV–vis spectrophotometer. The nanoparticles show good dispersibility due to the mutual repulsion of the same charge, and deep color. In addition, dense nano-film formed prevents the detachment of the dye and prevent the dye from falling off. This high chroma red SiNPs is expected to become a probe of visual marker and amplify the signal in immunoassay.

Dehydration-responsive element binding proteins (DREBs) are an important class of transcription factors related to plant stress tolerance. Ammopiptanthus mongolicus is an evergreen broadleaf shrub endemic to desert areas of northwest China, and it has a very high tolerance to harsh environments. In order to reveal the functions and mechanisms of the AmDREB1F gene from this species in enduring abiotic stresses, we performed subcellular localization test, expression pattern analysis, and stress tolerance evaluation of transgenic Arabidopsis harboring this gene. The protein encoded by AmDREB1F was localized in the nucleus. In laboratory-cultured A. mongolicus seedlings, the expression of AmDREB1F was induced significantly by cold and drought but very slightly by salt and heat stresses, and undetectable upon ABA treatment. In leaves of naturally growing shrubs in the wild, the expression levels of the AmDREB1F gene were much higher during the late autumn, winter and early spring than in other seasons. Moreover, the expression was abundant in roots and immature pods rather than other organs of the shrubs. Constitutive expression of AmDREB1F in Arabidopsis induced the expression of several DREB-regulated stress-responsive genes and improved the tolerance of transgenic lines to drought, high salinity and low temperature as well as oxidative stress. The constitutive expression also caused growth retardation of the transgenics, which could be eliminated by the application of gibberellin 3. Stress-inducible expression of AmDREB1F also enhanced the tolerance of transgenic Arabidopsis to all of the four stresses mentioned above, without affecting its growth and development. These results suggest that AmDREB1F gene may play positive regulatory roles in response to abiotic stresses through the ABA-independent signaling pathways.

Cadmium (Cd) and arsenic (As), two common heavy metals that are toxic to living bodies, are often commonly coadsorbed onto minerals in the soil environment and influenced by many surrounding factors. Among them, pH is the critical factor in determining the As(V)–Cd(II) interaction during coadsorption processes; hence, this study aimed to elucidate the regulatory mechanisms in determining the As(V)–Cd(II) interactions on γ-Al2O3 interface after excluding pH interference. At pH 6.0, Cd(II) adsorption sharply increased at first and then decreased with increasing As(V) concentrations, and the turning point of As(V)/Cd(II) molar ratios was approximately 5. For comparison, As(V) adsorption remained stable at the beginning and then sharply increased with increasing Cd(II) concentrations, with the turning point at Cd(II)/As(V) molar ratios = 1. Through analysis by zeta potential, X-ray diffraction and high resolution transmission electron microscope, electrostatic adsorption and formation of ternary complexes were proven to be the critical mechanisms in deciding the reactivity of Cd(II), whereas formation of ternary complexes and surface precipitation were the dominant mechanisms controlling the stability of As(V). The results in this study allowed us to infer that the mechanism for the coadsorption of Cd(II) and As(V) at stable pH conditions included both competitive and synergistic effects.

Unsupervised domain adaptation (UDA) aims at transferring knowledge between a well-labelled ’source domain’ and an unlabelled ’target domain’ by decreasing distribution discrepancy. In real scenario, partial domain adaptation (PDA), where target domain only includes part of the classes of source domain, is adopted as fully-shared label space is often unavailable. Non-identical label spaces across domains lead to performance degradation due to source-unique classes being mis-matched to the target domain, i.e. negative transfer of the target domain. Although existing PDA approaches have produced promising results, they still confront with negative transfer problem without rigorous generalization bounds. In our work, a novel PDA model has been proposed based on margin disparity and maximum source intra-class density divergence (MDSD). It matches the feature distributions with shared labels and congregates source samples in the source with affirmative labels. Removing maximum target density with pseudo labels, it effectively avoids over-fitting and accelerates learning speed. In addition, we construct a new garbage classification dataset, which is comprised of source domain - Product (Pr) and target domain - Garbage (Ga) for PDA validation. Experiments show that our proposed unsupervised partial domain adaptation method has a good performance on Office-31, Office-Home and Pr-Ga datasets.

Aflatoxin M1 (AFM1) residues in milk pose a major threat to human health, so there is an urgent need for a simple, rapid, and sensitive method for the determination of trace AFM1 in milk. In this study, a competitive immunochromatographic assay (ICA), using visual (PEI/PSS)4 red silica nanoparticles (SiNPs) as signal amplification probes, was used for the highly sensitive detection of AFM1. The (PEI/PSS)4 red SiNPs were used to label AFM1 monoclonal antibody (mAb) to prepare ICA for the detection of AFM1. After exploring the optimal conditions of mAb and immunoprobe dosage conditions, the lowest visual detection limit (VDL) of AFM1 in phosphate-buffered saline with Tween 20 (PBST, 10 mM, pH 7.4, containing 1% BSA, 3% sucrose, 1% trehalose, and 0.5% Tween 20) can reach 0.1 pg/mL. The intuitive visually visible value of AFM1 in both PBST and milk was 10 pg/mL. The results showed that the immunochromatographic system based on high chroma color (PEI/PSS)4 red SiNPs has high sensitivity and broad application prospects for the detection of trace AFM1 residues in milk. The high chroma (PEI/PSS)4 red SiNPs are expected to be a convenient biomarker for improving the sensitivity of immune chromatography bands.

Aflatoxin M1 (AFM1) residues in milk pose a major threat to human health, so there is an urgent need for a simple, rapid, and sensitive method for the determination of trace AFM1 in milk. In this study, a competitive immunochromatographic assay (ICA), using visual (PEI/PSS)

We study the disorder-induced phase transition in two-dimensional non-Hermitian systems. First, the applicability of the noncommutative geometric method (NGM) in non-Hermitian systems is examined. By calculating the Chern number of two different systems (a square sample and a cylindrical one), the numerical results calculated by NGM are compared with the analytical one, and the phase boundary obtained by NGM is found to be in good agreement with the theoretical prediction. Then, we use NGM to investigate the evolution of the Chern number in non-Hermitian samples with the disorder effect. For the square sample, the stability of the non-Hermitian Chern insulator under disorder is confirmed. Significantly, we obtain a nontrivial topological phase induced by disorder. This phase is understood as the topological Anderson insulator in non-Hermitian systems. Finally, the disordered phase transition in the cylindrical sample is also investigated. The clean non-Hermitian cylindrical sample has three phases, and such samples show more phase transitions by varying the disorder strength: (1) the normal insulator phase to the gapless phase, (2) the normal insulator phase to the topological Anderson insulator phase, and (3) the gapless phase to the topological Anderson insulator phase.

We consider the problem of volumetric (3D) unsupervised domain adaptation (UDA) in cross-modality medical image segmentation, aiming to perform segmentation on the unannotated target domain (e.g. MRI) with the help of labeled source domain (e.g. CT). Previous UDA methods in medical image analysis usually suffer from two challenges: 1) they focus on processing and analyzing data at 2D level only, thus missing semantic information from the depth level; 2) one-to-one mapping is adopted during the style-transfer process, leading to insufficient alignment in the target domain. Different from the existing methods, in our work, we conduct a first of its kind investigation on multi-style image translation for complete image alignment to alleviate the domain shift problem, and also introduce 3D segmentation in domain adaptation tasks to maintain semantic consistency at the depth level. In particular, we develop an unsupervised domain adaptation framework incorporating a novel quartet self-attention module to efficiently enhance relationships between widely separated features in spatial regions on a higher dimension, leading to a substantial improvement in segmentation accuracy in the unlabeled target domain. In two challenging cross-modality tasks, specifically brain structures and multi-organ abdominal segmentation, our model is shown to outperform current state-of-the-art methods by a significant margin, demonstrating its potential as a benchmark resource for the biomedical and health informatics research community.