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In recent years, the integration of graphene and related two-dimensional (2D) materials in optical fibers have stimulated significant advances in all-fiber photonics and optoelectronics. The conventional passive silica fiber devices with 2D materials are empowered for enhancing light-matter interactions and are applied for manipulating light beams in respect of their polarization, phase, intensity and frequency, and even realizing the active photo-electric conversion and electro-optic modulation, which paves a new route to the integrated multifunctional all-fiber optoelectronic system. This article reviews the fast-progress field of hybrid 2D-materials-optical-fiber for the opto-electro-mechanical devices. The challenges and opportunities in this field for future development are discussed.

Active origami capable of precise deployment control, enabling on-demand modulation of its properties, is highly desirable in multi-scenario and multi-task applications. While 4D printing with shape memory composites holds great promise to realize such active origami, it still faces challenges such as low load-bearing capacity and limited transformable states. Here, we report a fabrication-design-actuation method of precisely controlled electrothermal origami with excellent mechanical performance and spatiotemporal controllability, utilizing 4D printing of continuous fiber-reinforced composites. The incorporation of continuous carbon fibers empowers electrothermal origami with a controllable actuation process via Joule heating, increased actuation force through improved heat conduction, and enhanced mechanical properties as a result of reinforcement. By modeling the multi-physical and highly nonlinear deploying process, we attain precise control over the active origami, allowing it to be reconfigured and locked into any desired configuration by manipulating activation parameters. Furthermore, we showcase the versatility of electrothermal origami by constructing reconfigurable robots, customizable architected materials, and programmable wings, which broadens the practical engineering applications of origami. Effective active origami capable of on-demand modulation are limited by challenges such as limited load-bearing capacity and transformable states. Here, authors report fiber-reinforced composites for controlled electrothermal origami with excellent mechanical performance and spatiotemporal controllability.

Background Influenza is a severe respiratory illness that continually threatens global health. It has been widely known that gut microbiota modulates the host response to protect against influenza infection, but mechanistic details remain largely unknown. Here, we took advantage of the phenomenon of lethal dose 50 (LD 50 ) and metagenomic sequencing analysis to identify specific anti-influenza gut microbes and analyze the underlying mechanism. Results Transferring fecal microbes from mice that survive virulent influenza H7N9 infection into antibiotic-treated mice confers resistance to infection. Some gut microbes exhibit differential features to lethal influenza infection depending on the infection outcome. Bifidobacterium pseudolongum and Bifidobacterium animalis levels are significantly elevated in surviving mice when compared to dead or mock-infected mice. Oral administration of B. animalis alone or the combination of both significantly reduces the severity of H7N9 infection in both antibiotic-treated and germ-free mice. Functional metagenomic analysis suggests that B. animalis mediates the anti-influenza effect via several specific metabolic molecules. In vivo tests confirm valine and coenzyme A produce an anti-influenza effect. Conclusions These findings show that the severity of influenza infection is closely related to the heterogeneous responses of the gut microbiota. We demonstrate the anti-influenza effect of B. animalis , and also find that the gut population of endogenous B. animalis can expand to enhance host influenza resistance when lethal influenza infection occurs, representing a novel interaction between host and gut microbiota. Further, our data suggest the potential utility of Bifidobacterium in the prevention and as a prognostic predictor of influenza.

MYB proteins comprise a large family of plant transcription factors, members of which perform a variety of functions in plant biological processes. To date, no genome-wide characterization of this gene family has been conducted in maize (Zea mays). In the present study, we performed a comprehensive computational analysis, to yield a complete overview of the R2R3-MYB gene family in maize, including the phylogeny, expression patterns, and also its structural and functional characteristics. The MYB gene structure in maize and Arabidopsis were highly conserved, indicating that they were originally compact in size. Subgroup-specific conserved motifs outside the MYB domain may reflect functional conservation. The genome distribution strongly supports the hypothesis that segmental and tandem duplication contribute to the expansion of maize MYB genes. We also performed an updated and comprehensive classification of the R2R3-MYB gene families in maize and other plant species. The result revealed that the functions were conserved between maize MYB genes and their putative orthologs, demonstrating the origin and evolutionary diversification of plant MYB genes. Species-specific groups/subgroups may evolve or be lost during evolution, resulting in functional divergence. Expression profile study indicated that maize R2R3-MYB genes exhibit a variety of expression patterns, suggesting diverse functions. Furthermore, computational prediction potential targets of maize microRNAs (miRNAs) revealed that miR159, miR319, and miR160 may be implicated in regulating maize R2R3-MYB genes, suggesting roles of these miRNAs in post-transcriptional regulation and transcription networks. Our comparative analysis of R2R3-MYB genes in maize confirm and extend the sequence and functional characteristics of this gene family, and will facilitate future functional analysis of the MYB gene family in maize.

Background The MYB superfamily constitutes one of the most abundant groups of transcription factors described in plants. Nevertheless, their functions appear to be highly diverse and remain rather unclear. To date, no genome-wide characterization of this gene family has been conducted in a legume species. Here we report the first genome-wide analysis of the whole MYB superfamily in a legume species, soybean ( Glycine max ), including the gene structures, phylogeny, chromosome locations, conserved motifs, and expression patterns, as well as a comparative genomic analysis with Arabidopsis . Results A total of 244 R2R3-MYB genes were identified and further classified into 48 subfamilies based on a phylogenetic comparative analysis with their putative orthologs, showed both gene loss and duplication events. The phylogenetic analysis showed that most characterized MYB genes with similar functions are clustered in the same subfamily, together with the identification of orthologs by synteny analysis, functional conservation among subgroups of MYB genes was strongly indicated. The phylogenetic relationships of each subgroup of MYB genes were well supported by the highly conserved intron/exon structures and motifs outside the MYB domain. Synonymous nucleotide substitution ( d N / d S ) analysis showed that the soybean MYB DNA-binding domain is under strong negative selection. The chromosome distribution pattern strongly indicated that genome-wide segmental and tandem duplication contribute to the expansion of soybean MYB genes. In addition, we found that ~ 4% of soybean R2R3-MYB genes had undergone alternative splicing events, producing a variety of transcripts from a single gene, which illustrated the extremely high complexity of transcriptome regulation. Comparative expression profile analysis of R2R3-MYB genes in soybean and Arabidopsis revealed that MYB genes play conserved and various roles in plants, which is indicative of a divergence in function. Conclusions In this study we identified the largest MYB gene family in plants known to date. Our findings indicate that members of this large gene family may be involved in different plant biological processes, some of which may be potentially involved in legume-specific nodulation. Our comparative genomics analysis provides a solid foundation for future functional dissection of this family gene.

The matching Wilson flow time for calculating the topological charge density correlator (TCDC) of the gluonic definition by the Wilson flow is analyzed using the matching procedure. The relationship has been established between the matching Wilson flow time for calculating TCDC and the matching Wilson flow time at which the topological charge defined by the gluon fields is closest to an integer. The properties of TCDC defined by the bosonic field are investigated, and the pseudoscalar glueball mass was extracted from the TCDC computed at the matching Wilson flow time. It is further demonstrated that the matching Wilson flow time determined by the matching procedure can be applied to compute the topological susceptibility in the gluonic definition.

For improving manufacturing efficiency and minimizing costs, design for additive manufacturing (AM) has been accordingly proposed. The existing design for AM methods are mainly surrogate model based. Due to the increasingly available data nowadays, machine learning (ML) has been applied to medical diagnosis, image processing, prediction, classification, learning association, etc. A variety of studies have also been carried out to use machine learning for optimizing the process parameters of AM with corresponding objectives. In this paper, a ML integrated design for AM framework is proposed, which takes advantage of ML that can learn the complex relationships between the design and performance spaces. Furthermore, the primary advantage of ML over other surrogate modelling methods is the capability to model input–output relationships in both directions. That is, a deep neural network can model property–structure relationships, given structure–property input–output data. A case study was carried out to demonstrate the effectiveness of using ML to design a customized ankle brace that has a tunable mechanical performance with tailored stiffness.

Sophisticated mechanically interlocked molecules (MIMs) with interesting structures, properties and applications have attracted great interest in the field of supramolecular chemistry. We herein report a highly efficient self-assembly of heterometallic triangular necklace 1 containing Cu and Pt metals with strong antibacterial activity. Single-crystal X-ray analysis shows that the finely arranged triangular necklace 1 has two racemic enantiomers in its solid state with intriguing packing motif. The superior antibacterial activity of necklace 1 against both standard and clinically drug-resistant pathogens implies that the presence of Cu(I) center and platinum(II) significantly enhance the bacterium-binding/damaging activity, which is mainly attributed to the highly positively charged nature, the possible synergistic effect of heterometals in the necklace, and the improved stability in culture media. This work clearly discloses the structure-property relationships that the existence of two different metal centers not only facilitates successful construction of heterometallic triangular necklace but also endows it with superior nuclease properties and antibacterial activities. Precise assembly of heterometallic complexes is a challenge. Here, the authors design a heterometallic triangular necklace through a highly efficient threading-and-ring-closing approach driven by metal-ligand coordination, which shows strong bacterium-binding and cell wall/plasma membrane-disrupting capacity for killing bacterial cells.

Recent advances in next-generation sequencing (NGS) technologies have triggered the rapid accumulation of publicly available multi-omics datasets. The application of integrated omics to explore robust signatures for clinical translation is increasingly emphasized, and this is attributed to the clinical success of immune checkpoint blockades in diverse malignancies. However, effective tools for comprehensively interpreting multi-omics data are still warranted to provide increased granularity into the intrinsic mechanism of oncogenesis and immunotherapeutic sensitivity. Therefore, we developed a computational tool for effective Immuno-Oncology Biological Research (IOBR), providing a comprehensive investigation of the estimation of reported or user-built signatures, TME deconvolution, and signature construction based on multi-omics data. Notably, IOBR offers batch analyses of these signatures and their correlations with clinical phenotypes, long non-coding RNA (lncRNA) profiling, genomic characteristics, and signatures generated from single-cell RNA sequencing (scRNA-seq) data in different cancer settings. Additionally, IOBR integrates multiple existing microenvironmental deconvolution methodologies and signature construction tools for convenient comparison and selection. Collectively, IOBR is a user-friendly tool for leveraging multi-omics data to facilitate immuno-oncology exploration and to unveil tumor-immune interactions and accelerating precision immunotherapy.

We address an interesting question in the present paper that whether the acoustic gravity can be applied as a tool to the study of regular black holes. For this purpose, we construct a general acoustic regular black hole in the spherically symmetric fluid, where its regularity is verified from the perspective of finiteness of curvature invariants and completeness of geodesics. In particular, we find that the acoustic interval not only looks like a line element of a conformally related black hole in which the fluid density can be regarded as a conformal factor, but also gives rise to a non-vanishing partition function which coincides with that of a conformally related black hole. As an application, we provide a specific acoustic regular black hole model, investigate its energy conditions and compute its quasinormal modes. We note that the strong energy condition of our model is violated completely outside the horizon of the model but remains valid in some regions inside the horizon, which may give a new insight into the relation between the regularity and strong energy condition. Moreover, we analyze the oscillating and damping features of our model when it is perturbed.