Molecular Mechanism and Agricultural Application of the NifA-NifL System for Nitrogen Fixation.

Nitrogen-fixing bacteria execute biological nitrogen fixation through nitrogenase, converting inert dinitrogen (N2) in the atmosphere into bioavailable nitrogen. Elaborating the molecular mechanisms of orderly and efficient biological nitrogen fixation and applying them to agricultural production can alleviate the "nitrogen problem". Azotobacter vinelandii is a well-established model bacterium for studying nitrogen fixation, utilizing nitrogenase encoded by the nif gene cluster to fix nitrogen. In Azotobacter vinelandii, the NifA-NifL system fine-tunes the nif gene cluster transcription by sensing the redox signals and energy status, then modulating nitrogen fixation. In this manuscript, we investigate the transcriptional regulation mechanism of the nif gene in autogenous nitrogen-fixing bacteria. We discuss how autogenous nitrogen fixation can better be integrated into agriculture, providing preliminary comprehensive data for the study of autogenous nitrogen-fixing regulation.

Hierarchical neural network with efficient selection inference.

The image classification precision is vastly enhanced with the growing complexity of convolutional neural network (CNN) structures. However, the uneven visual separability between categories leads to various difficulties in classification. The hierarchical structure of categories can be leveraged to deal with it, but a few CNNs pay attention to the character of data. Besides, a network model with a hierarchical structure is promising to extract more specific features from the data than current CNNs, since, for the latter, all categories have the same fixed number of layers for feed-forward computation. In this paper, we propose to use category hierarchies to integrate ResNet-style modules to form a hierarchical network model in a top-down manner. To extract abundant discriminative features and improve the computation efficiency, we adopt residual block selection based on coarse categories to allocate different computation paths. Each residual block works as a switch to determine the JUMP or JOIN mode for an individual coarse category. Interestingly, since some categories need less feed-forward computation than others by jumping layers, the average inference time cost is reduced. Extensive experiments show that our hierarchical network achieves higher prediction accuracy with similar FLOPs on CIFAR-10 and CIFAR-100, SVHM, and Tiny-ImageNet datasets compared to original residual networks and other existing selection inference methods.

Gold nanoparticles with asymmetric polymerase chain reaction for colorimetric detection of DNA sequence.

We developed a novel strategy for rapid colorimetric analysis of a specific DNA sequence by combining gold nanoparticles (AuNPs) with an asymmetric polymerase chain reaction (As-PCR). In the presence of the correct DNA template, the bound oligonucleotides on the surface of AuNPs selectively hybridized to form complementary sequences of single-stranded DNA (ssDNA) target generated from As-PCR. DNA hybridization resulted in self-assembly and aggregation of AuNPs, and a concomitant color change from ruby red to blue-purple occurred. This approach is simpler than previous methods, as it requires a simple mixture of the asymmetric PCR product with gold colloid conjugates. Thus, it is a convenient colorimetric method for specific nucleic acid sequence analysis with high specificity and sensitivity. Most importantly, the marked color change occurs at a picogram detection level after standing for several minutes at room temperature. Linear amplification minimizes the potential risk of PCR product cross-contamination. The efficiency to detect Bacillus anthracis in clinical samples clearly indicates the practical applicability of this approach.

Superior penetration and retention behavior of 50 nm gold nanoparticles in tumors.

Nanoparticles offer potential as drug delivery systems for chemotherapeutics based on certain advantages of molecular drugs. In this study, we report that particle size exerts great influence on the penetration and retention behavior of nanoparticles entering tumors. On comparing gold-coated Au@tiopronin nanoparticles that were prepared with identical coating and surface properties, we found that 50 nanoparticles were more effective in all in vitro, ex vivo, and in vivo assays conducted using MCF-7 breast cells as a model system. Beyond superior penetration in cultured cell monolayers, 50 nm Au@tiopronin nanoparticles also penetrated more deeply into tumor spheroids ex vivo and accumulated more effectively in tumor xenografts in vivo after a single intravenous dose. In contrast, larger gold-coated nanoparticles were primarily localized in the periphery of the tumor spheroid and around blood vessels, hindering deep penetration into tumors. We found multicellular spheroids to offer a simple ex vivo tumor model to simulate tumor tissue for screening the nanoparticle penetration behavior. Taken together, our findings define an optimal smaller size for nanoparticles that maximizes their effective accumulation in tumor tissue.

Gold nanoparticles functionalized with therapeutic and targeted peptides for cancer treatment.

Functionalization of nanostructures such as gold nanoparticles (AuNPs) with different biological molecules has many applications in biomedical imaging, clinical diagnosis and therapy. Researchers mostly employed AuNPs larger than 10 nm for different biological and medicinal applications in previous studies. Herein, we synthesized a novel small (2 nm) AuNPs, which were functionalized with the therapeutic peptide, PMI (p12), and a targeted peptide, CRGDK for selective binding to neuropilin-1(Nrp-1) receptors which overexpressed on the cancer cells and regulated the process of membrane receptor-mediated internalization. It was found that CRGDK peptides increased intracellular uptake of AuNPs compared to other surface conjugations quantified by ICP-MS. Interestingly, CRGDK functionalized AuNPs resulted in maximal binding interaction between the CRGDK peptide and targeted Nrp-1 receptor overexpressed on MDA-MB-321 cell surface, which improved the delivery of therapeutic P12 peptide inside targeted cells. Au@p12 + CRGDK nanoparticles indicated with highly effective cancer treatment by increasing p53 expression upregulated with intracellular enhanced p12 therapeutic peptide. These results have implications to design and functionalize different molecules onto AuNPs surfaces to make hybrid model system for selective target binding as well as therapeutic effects for cancer treatment.

Size-dependent localization and penetration of ultrasmall gold nanoparticles in cancer cells, multicellular spheroids, and tumors in vivo.

This work demonstrated that ultrasmall gold nanoparticles (AuNPs) smaller than 10 nm display unique advantages over nanoparticles larger than 10 nm in terms of localization to, and penetration of, breast cancer cells, multicellular tumor spheroids, and tumors in mice. Au@tiopronin nanoparticles that have tunable sizes from 2 to 15 nm with identical surface coatings of tiopronin and charge were successfully prepared. For monolayer cells, the smaller the Au@tiopronin NPs, the more AuNPs found in each cell. In addition, the accumulation of Au NPs in the ex vivo tumor model was size-dependent: smaller AuNPs were able to penetrate deeply into tumor spheroids, whereas 15 nm nanoparticles were not. Owing to their ultrasmall nanostructure, 2 and 6 nm nanoparticles showed high levels of accumulation in tumor tissue in mice after a single intravenous injection. Surprisingly, both 2 and 6 nm Au@tiopronin nanoparticles were distributed throughout the cytoplasm and nucleus of cancer cells in vitro and in vivo, whereas 15 nm Au@tiopronin nanoparticles were found only in the cytoplasm, where they formed aggregates. The ex vivo multicellular spheroid proved to be a good model to simulate in vivo tumor tissue and evaluate nanoparticle penetration behavior. This work gives important insights into the design and functionalization of nanoparticles to achieve high levels of accumulation in tumors.