ABSTRACT
Current gene delivery methods for maize are limited to specific genotypes and depend on time‐consuming and labor‐intensive tissue culture techniques. Here, we report a new method to ...transfect maize that is culture‐free and genotype independent. To enhance efficiency of DNA entry and maintain high pollen viability of 32%‐55%, transfection was performed at cool temperature using pollen pretreated to open the germination aperture (40%–55%). Magnetic nanoparticles (MNPs) coated with DNA encoding either red fluorescent protein (RFP), β‐glucuronidase gene (GUS), enhanced green fluorescent protein (EGFP) or bialaphos resistance (bar) was delivered into pollen grains, and female florets of maize inbred lines were pollinated. Red fluorescence was detected in 22% transfected pollen grains, and GUS stained 55% embryos at 18 d after pollination. Green fluorescence was detected in both silk filaments and immature kernels. The T1 generation of six inbred lines showed considerable EGFP or GUS transcripts (29%–74%) quantitated by polymerase chain reaction, and 5%–16% of the T1 seedlings showed immunologically active EGFP or GUS protein. Moreover, 1.41% of the bar transfected T1 plants were glufosinate resistant, and heritable bar gene was integrated into the maize genome effectively as verified by DNA hybridization. These results demonstrate that exogenous DNA could be delivered efficiently into elite maize inbred lines recalcitrant to tissue culture‐mediated transformation and expressed normally through our genotype‐independent pollen transfection system.
The success, stability, and repeatability of transfection of maize pollen with magnetic nanoparticles was improved by using low temperature during transfection to maintain pollen viability and pretreatment to open the pollen aperture.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge during the global pandemic and may facilitate escape from current antibody therapies and vaccine protection. ...Here we showed that the South African variant B.1.351 was the most resistant to current monoclonal antibodies and convalescent plasma from coronavirus disease 2019 (COVID-19)-infected individuals, followed by the Brazilian variant P.1 and the United Kingdom variant B.1.1.7. This resistance hierarchy corresponded with Y144del and 242–244del mutations in the N-terminal domain and K417N/T, E484K, and N501Y mutations in the receptor-binding domain (RBD) of SARS-CoV-2. Crystal structure analysis of the B.1.351 triple mutant (417N-484K-501Y) RBD complexed with the monoclonal antibody P2C-1F11 revealed the molecular basis for antibody neutralization and escape. B.1.351 and P.1 also acquired the ability to use mouse and mink ACE2 receptors for entry. Our results demonstrate major antigenic shifts and potential broadening of the host range for B.1.351 and P.1 variants, which poses serious challenges to current antibody therapies and vaccine protection.
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•SARS-CoV-2 variants of concern are resistant to antibody neutralization•B.1.351 variant is the most resistant, followed by P.1 and B.1.1.7•The resistance hierarchy corresponds to mutations in NTD and RBD•B.1.351 and P.1 acquire the ability to use mouse and mink ACE2 for entry
SARS-CoV-2 variants continue to emerge and spread around the world. Wang et al. conduct comprehensive mutational and crystal structure analyses of the variants and show that variants of concern, and the South African variant B.1.351 in particular, are resistant to many monoclonal antibodies and COVID-19 convalescent plasma and acquire the ability to use mouse and mink ACE2 receptors for infection.
Cardiovascular disease (CVD) and environmental degradation are leading global health problems of our time. Recent studies have linked exposure to heavy metals to the risks of CVD and diabetes, ...particularly in populations from low- and middle-income countries, where concomitant rapid development occurs. In this review, we 1) assessed the totality, quantity, and consistency of the available epidemiological studies, linking heavy metal exposures to the risk of CVD (including stroke and coronary heart disease); 2) discussed the potential biological mechanisms underlying some tantalizing observations in humans; and 3) identified gaps in our knowledge base that must be investigated in future work. An accumulating body of evidence from both experimental and observational studies implicates exposure to heavy metals, in a dose-response manner, in the increased risk of CVD. The limitations of most existing studies include insufficient statistical power, lack of comprehensive assessment of exposure, and cross-sectional design. Given the widespread exposure to heavy metals, an urgent need has emerged to investigate these putative associations of environmental exposures, either independently or jointly, with incident CVD outcomes prospectively in well-characterized cohorts of diverse populations, and to determine potential strategies to prevent and control the impacts of heavy metal exposure on the cardiometabolic health outcomes of individuals and populations.
•The largest publicly dataset of breast cancer pathological images is released.•Dataset diversity alleviates relatively low accuracy of benign images classification.•Richer multilevel features make ...the image-wise feature fusion more sufficient.•The short-term and long-term correlations between patches are both preserved.•Our hybrid network outperformed other methods in pathological image classification.
Even with the rapid advances in medical sciences, histopathological diagnosis is still considered the gold standard in diagnosing cancer. However, the complexity of histopathological images and the dramatic increase in workload make this task time consuming, and the results may be subject to pathologist subjectivity. Therefore, the development of automatic and precise histopathological image analysis methods is essential for the field. In this paper, we propose a new hybrid convolutional and recurrent deep neural network for breast cancer histopathological image classification. Based on the richer multilevel feature representation of the histopathological image patches, our method integrates the advantages of convolutional and recurrent neural networks, and the short-term and long-term spatial correlations between patches are preserved. The experimental results show that our method outperforms the state-of-the-art method with an obtained average accuracy of 91.3% for the 4-class classification task. We also release a dataset with 3771 breast cancer histopathological images to the scientific community that is now publicly available at http://ear.ict.ac.cn/?page_id=1616. Our dataset is not only the largest publicly released dataset for breast cancer histopathological image classification, but it covers as many different subclasses spanning different age groups as possible, thus providing enough data diversity to alleviate the problem of relatively low classification accuracy of benign images.
Revealing the photoluminescence (PL) origin and mechanism is a most vital but challenging topic of carbon dots. Herein, confined-domain crosslink-enhanced emission (CEE) effect was first studied by a ...well-designed model system of carbonized polymer dots (CPDs), serving as an important supplement to CEE in the aspect of spatial interactions. The "addition-condensation polymerization" strategy was adopted to construct CPDs with substituents exerting different degrees of steric hindrance. The effect of confined-domain CEE on the structure and luminescence properties of CPDs have been systematically investigated by combining characterizations and theoretical calculations. Such tunable spatial interactions dominated the coupling strength of the luminophores in one particle, and eventually resulted in the modulated PL properties of CPDs. These findings provide insights into the structural advantages and the PL mechanism of CPDs, which are of general significance to the further development of CPDs with tailored properties.
New Au@SnO2 yolk-shell nanospheres have been successfully synthesized by using Au@SiO2 nanospheres as sacrificial templates. This process is environmentally friendly and is based on hydrothermal ...shell-by-shell deposition of polycrystalline SnO2 on spheriform Au@SiO2 nanotemplates. Au nanoparticles can be impregnated into the SnO2 nanospheres and the nanospheres show outer diameters of 110 nm and thicknesses of 15 nm. The possible growth model of the nanospheres is proposed. The gas sensing properties of the Au@SnO2 yolk-shell nanospheres were researched and compared with that of the hollow SnO2 nanospheres. The former shows lower operating temperature (210 °C), lower detection limit (5 ppm), faster response (0.3 s) and better selectivity. These improved sensing properties were attributed to the catalytic effect of Au, and enhanced electron depletion at the surface of the Au@SnO2 yolk-shell nanospheres.
Tongue cancer remains a massive threat to public health due to the high rate of metastasis. Tumor cell epithelial‐mesenchymal transition (EMT), which can be induced by transforming growth factor β1 ...(TGFβ1), has been regarded as a significant contributor to cancer invasion and migration. In our previous study, long noncoding RNA (lncRNA) MALAT1/miR‐124/JAG1 axis modulates the growth of tongue cancer. In addition to metastasis‐associated lung adenocarcinoma transcript 1 (MALAT1), another lncRNA, urothelial cancer associated 1 (UCA1), can promote EMT and cancer metastasis. In the present study, UCA1 was overexpressed in tongue cancer tissues and cell lines. UCA1 overexpression was correlated to the poorer prognosis of patients with tongue cancer. UCA1 knockdown significantly suppressed TGFβ1‐induced tongue cancer cell invasion and EMT by decreasing vimentin and increasing E‐cadherin. Regarding the molecular mechanism, UCA1 could directly bind to microRNA‐124 (miR‐124) and negatively regulate each other. UCA1 knockdown ameliorated, whereas miR‐124 inhibition exacerbated TGFβ1‐induced EMT and invasion in tongue cancer cells through miR‐124 downstream jagged 1 (JAG1) and Notch signaling. Moreover, miR‐124 inhibition partially impaired the effect of UCA1 knockdown. In tongue cancer tissues, miR‐124 expression was remarkably decreased, whereas JAG1 mRNA expression was increased. miR‐124 was negatively correlated with UCA1 and JAG1. UCA1 and JAG1 were positively correlated. In summary, we provided a novel mechanism by which the EMT process and cancer cell invasion in tongue cancer could be modulated from the perspective of lncRNA‐miRNA‐mRNA regulation.
Urothelial cancer associated 1 (UCA1) could directly bind to microRNA‐124 (miR‐124) and negatively regulate each other. UCA1 knockdown ameliorated, whereas miR‐124 inhibition exacerbated transforming growth factor β1 (TGFβ1)‐induced epithelial‐mesenchymal transition (EMT) and invasion in tongue cancer cells through miR‐124 downstream jagged 1 (JAG1) and Notch signaling. Moreover, miR‐124 inhibition partially impaired the effect of UCA1 knockdown.
The evolutionary outcomes of high elevation adaptation have been extensively described. However, whether widely distributed high elevation endemic animals adopt uniform mechanisms during adaptation ...to different elevational environments remains unknown, especially with respect to extreme high elevation environments. To explore this, we analysed the phenotypic and genomic data of seven populations of plateau zokor (Myospalax baileyi) along elevations ranging from 2,700 to 4,300 m. Based on whole‐genome sequencing data and demographic reconstruction of the evolutionary history, we show that two populations of plateau zokor living at elevations exceeding 3,700 m diverged from other populations nearly 10,000 years ago. Further, phenotypic comparisons reveal stress‐dependent adaptation, as two populations living at elevations exceeding 3,700 m have elevated ratios of heart mass to body mass relative to other populations, and the highest population (4,300 m) displays alterations in erythrocytes. Correspondingly, genomic analysis of selective sweeps indicates that positive selection might contribute to the observed phenotypic alterations in these two extremely high elevation populations, with the adaptive cardiovascular phenotypes of both populations possibly evolving under the functional constrains of their common ancestral population. Taken together, phenotypic and genomic evidence demonstrates that heterogeneous stressors impact adaptations to extreme elevations and reveals stress‐dependent and genetically constrained adaptation to hypoxia, collectively providing new insights into the high elevation adaptation.
In this paper, a novel deep neural network (DNN)-driven feature learning method is proposed and applied to multi-view facial expression recognition (FER). In this method, scale invariant feature ...transform (SIFT) features corresponding to a set of landmark points are first extracted from each facial image. Then, a feature matrix consisting of the extracted SIFT feature vectors is used as input data and sent to a well-designed DNN model for learning optimal discriminative features for expression classification. The proposed DNN model employs several layers to characterize the corresponding relationship between the SIFT feature vectors and their corresponding high-level semantic information. By training the DNN model, we are able to learn a set of optimal features that are well suitable for classifying the facial expressions across different facial views. To evaluate the effectiveness of the proposed method, two nonfrontal facial expression databases, namely BU-3DFE and Multi-PIE, are respectively used to testify our method and the experimental results show that our algorithm outperforms the state-of-the-art methods.
A novel hierarchical heterostructure of α-Fe2O3 nanorods/TiO2 nanofibers with branch-like nanostructures was fabricated using a simple two-step process called the electrospinning technique and ...hydrothermal process. A high density of α-Fe2O3 nanorods (about 200 nm in diameter) was uniformly deposited on a TiO2 nanofibers backbone. The phase purity, morphology, and structure of hierarchical heterostructures are investigated by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and energy-dispersive X-ray (EDX) analysis. The highly branched α-Fe2O3/TiO2 heterostructures provided an extremely porous matrix and high specific surface area required for high-performance gas sensors. Different nanostructured α-Fe2O3/TiO2 heterostructures are also investigated by controlling the volume ratio of the reactants. The α-Fe2O3/TiO2 heterostructures with a proper mixture ratio of the reactants sensor exhibit obviously enhanced sensing characteristics, including higher sensing response, lower operating temperature, faster response speed, and better selectivity in comparison with other ones. Moreover, the α-Fe2O3/TiO2 heterostructures sensor also exhibits excellent sensing performances compared with α-Fe2O3 nanorods and TiO2 nanofibers sensors. Thus, the combination of TiO2 nanofibers backbone and α-Fe2O3 nanorods uniformly decorated endows a fascinating sensing performance as a novel sensing material with high response and rapid responding and recovering speed.