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Adipocyte differentiation of bone marrow mesenchymal stem/stromal cells (BMSCs) instead of osteoblast formation contributes to age- and menopause-related marrow adiposity and osteoporosis. Vascular calcification often occurs with osteoporosis, a contradictory association called “calcification paradox”. Here we show that extracellular vesicles derived from aged bone matrix (AB-EVs) during bone resorption favor BMSC adipogenesis rather than osteogenesis and augment calcification of vascular smooth muscle cells. Intravenous or intramedullary injection of AB-EVs promotes bone-fat imbalance and exacerbates Vitamin D3 (VD3)-induced vascular calcification in young or old mice. Alendronate (ALE), a bone resorption inhibitor, down-regulates AB-EVs release and attenuates aging- and ovariectomy-induced bone-fat imbalance. In the VD3-treated aged mice, ALE suppresses the ovariectomy-induced aggravation of vascular calcification. MiR-483-5p and miR-2861 are enriched in AB-EVs and essential for the AB-EVs-induced bone-fat imbalance and exacerbation of vascular calcification. Our study uncovers the role of AB-EVs as a messenger for calcification paradox by transferring miR-483-5p and miR-2861. This study uncovers the role of extracellular vesicles from bone matrix as a messenger in the development of osteoporosis and vascular calcification (calcification paradox) during skeletal aging and menopause by transferring miR-483-5p and miR-2861.

Premature ovarian failure (POF) is one of the common disorders found in women leading to 1% female infertility. Clinical features of POF are hypoestrogenism or estrogen deficiency, increased gonadotropin level, and, most importantly, amenorrhea. With the development of regenerative medicine, human mesenchymal stem cell (hMSC) therapy brings new prospects for POF. This study aimed to describe the types of MSCs currently available for POF therapy, their biological characteristics, and their mechanism of action. It reviewed the latest findings on POF to provide the theoretical basis for further investigation and clinical therapy.

Spatial mode (de)multiplexing of orbital angular momentum (OAM) beams is a promising solution to address future bandwidth issues, but the rapidly increasing divergence with the mode order severely limits the practically addressable number of OAM modes. Here we present a set of multi-vortex geometric beams (MVGBs) as high-dimensional information carriers for free-space optical communication, by virtue of three independent degrees of freedom (DoFs) including central OAM, sub-beam OAM, and coherent-state phase. The novel modal basis set has high divergence degeneracy, and highly consistent propagation behaviors among all spatial modes, capable of increasing the addressable spatial channels by two orders of magnitude than OAM basis as predicted. We experimentally realize the tri-DoF MVGB mode (de)multiplexing and data transmission by the conjugated modulation method, demonstrating lower error rates caused by center offset and coherent background noise, compared with OAM basis. Our work provides a potentially useful basis for the next generation of large-scale dense data communication.

Geminiviruses are plant viruses with limited coding capacity. Geminivirus-encoded proteins are traditionally identified by applying a 10-kDa arbitrary threshold; however, it is increasingly clear that small proteins play relevant roles in biological systems, which calls for the reconsideration of this criterion. Here, we show that geminiviral genomes contain additional ORFs. Using tomato yellow leaf curl virus, we demonstrate that some of these small ORFs are expressed during the infection, and that the encoded proteins display specific subcellular localizations. We prove that the largest of these additional ORFs, which we name V3, is required for full viral infection, and that the V3 protein localizes in the Golgi apparatus and functions as an RNA silencing suppressor. These results imply that the repertoire of geminiviral proteins can be expanded, and that getting a comprehensive overview of the molecular plant-geminivirus interactions will require the detailed study of small ORFs so far neglected. Geminiviruses are small plant-infecting viruses. Here the authors screen the geminivirus genome for small open reading frames that may have been previously overlooked and show that one encodes a protein named V3 that localizes to the Golgi and acts as an RNA silencing suppressor.

Computer-generated holograms are crucial for a wide range of applications such as 3D displays, information encryption, data storage, and opto-electronic computing. Orbital angular momentum (OAM), as a new degree of freedom with infinite orthogonal states, has been employed to expand the hologram bandwidth. However, in order to reduce strong multiplexing crosstalk, OAM holography suffers from a fundamental sampling criterion that the image sampling distance should be no less than the diameter of largest addressable OAM mode, which severely hinders the increase in resolution and capacity. Here we establish a comprehensive model on multiplexing crosstalk in OAM holography, propose a pseudo incoherent approach that is almost crosstalk-free, and demonstrate an analogous coherent solution by temporal multiplexing, which dramatically eliminates the crosstalk and largely relaxes the constraint upon sampling condition of OAM holography, exhibiting a remarkable resolution enhancement by several times, far beyond the conventional resolution limit of OAM holography, as well as a large scaling of OAM multiplexing capacity at fixed resolution. Our method enables OAM-multiplexed holographic reconstruction with high quality, high resolution, and high capacity, offering an efficient and practical route towards the future high-performance holographic systems. The resolution of orbital angular momentum holography is limited by a fundamental sampling criterion. Here, the authors break the resolution barrier by temporal multiplexing of binary holograms and enhance the resolution and capacity by several times.

Photonic computing, with potentials of high parallelism, low latency and high energy efficiency, have gained progressive interest at the forefront of neural network (NN) accelerators. However, most existing photonic computing accelerators concentrate on discriminative NNs. Large-scale generative photonic computing machines remain largely unexplored, partly due to poor data accessibility, accuracy and hardware feasibility. Here, we harness random light scattering in disordered media as a native noise source and leverage large-scale diffractive optical computing to generate images from above noise, thereby achieving hardware consistency by solely pursuing the spatial parallelism of light. To realize experimental data accessibility, we design two encoding strategies between images and optical noise latent space that effectively solves the training problem. Furthermore, we utilize advanced photonic NN architectures including cascaded and parallel configurations of diffraction layers to enhance the image generation performance. Our results show that the photonic generator is capable of producing clear and meaningful synthesized images across several standard public datasets. As a photonic generative machine, this work makes an important contribution to photonic computing and paves the way for more sophisticated applications such as real world data augmentation and multi modal generation. Large-scale generative photonic computing suffers from poor data accessibility, accuracy and hardware feasibility. Here, authors harness random light scattering in disordered media as a native noise source and leverage large-scale diffractive optical computing to generate images from above noise.

With the advent of the Internet of Things (IoT) era, a wide array of wireless sensors supporting the IoT have proliferated. As key elements for enabling the IoT, wireless sensor nodes require minimal energy consumption and low device complexity. In particular, energy-efficient resource scheduling is critical in maintaining a network of wireless sensor nodes, since the energy-intensive processing of wireless sensor nodes and their interactions is too complicated to control. In this study, we present a practical deep Q-network (DQN)-based packet scheduling algorithm that coordinates the transmissions of multiple IoT devices. The scheduling algorithm dynamically adjusts the connection interval (CI) and the number of packets transmitted by each node within the interval. Through various experiments, we verify how effectively the proposed scheduler improves energy efficiency and handles the time-varying nature of the network environment. Moreover, we attempt to gain insight into the optimized packet scheduler by analyzing the policy of the DQN scheduler. The experimental results show that the proposed scheduling algorithm can further prolong a network’s lifetime in a dynamic network environment in comparison with that in other alternative schemes while ensuring the quality of service (QoS).

Cultural heritage continues to be endangered by environmental, social, and political issues requiring new digital preservation methods. This paper proposes a deep learning framework consisting of an Feature Pyramid Network (FPN) and an Modified Builder Optimization Algorithm (MBOA) whose purpose is to classify, restore, and synthesize culturally significant artwork. Using the WikiArt dataset, the model represents the cultural styles of many artistic traditions by fully utilizing FPN’s multi-scale architecture and identifying both fine scale textures as well as global stylistic semantics. The MBOA optimizes hyperparameters through an innovative bio-inspired search strategy, which improves convergence and model performance and improves training efficiency. The framework achieves style classification accuracy of 96.7% in terms of preference, a PSNR of 32.41 dB and SSIM of 0.937 for restoration, and an Fréchet Inception Distance (FID) score of 14.3 for generation, therefore outperforming state-of-the-art CNNs and generative models. The results illustrated the framework’s powerful reconstruction capabilities in restoring degraded works of art, or generating new works inspired by cultural aesthetics. By combining a Feature Pyramid Network, Modified Builder Optimization Algorithm, and Neural Style Transfer, this work further expands the capabilities and role of Generative AI for use in digital preservation. This approach supports not only archival fidelity and quality but forms a creative interaction, enhancing the capabilities of networks and reinterpreting global heritage assets in the digital age as a scalable tool for museums, teachers, and cultural institutions.

Thirty years ago, Coullet et al. proposed that a special optical field exists in laser cavities bearing some analogy with the superfluid vortex. Since then, optical vortices have been widely studied, inspired by the hydrodynamics sharing similar mathematics. Akin to a fluid vortex with a central flow singularity, an optical vortex beam has a phase singularity with a certain topological charge, giving rise to a hollow intensity distribution. Such a beam with helical phase fronts and orbital angular momentum reveals a subtle connection between macroscopic physical optics and microscopic quantum optics. These amazing properties provide a new understanding of a wide range of optical and physical phenomena, including twisting photons, spin–orbital interactions, Bose–Einstein condensates, etc., while the associated technologies for manipulating optical vortices have become increasingly tunable and flexible. Hitherto, owing to these salient properties and optical manipulation technologies, tunable vortex beams have engendered tremendous advanced applications such as optical tweezers, high-order quantum entanglement, and nonlinear optics. This article reviews the recent progress in tunable vortex technologies along with their advanced applications.

Drought stress is a major threat to crop production, but effective methods to mitigate the adverse effects of drought are not available. Here, we report that adding fluorine atoms in the benzyl ring of the abscisic acid (ABA) receptor agonist AM1 optimizes its binding to ABA receptors by increasing the number of hydrogen bonds between the compound and the surrounding amino acid residues in the receptor ligand-binding pocket. The new chemicals, known as AMFs, have long-lasting effects in promoting stomatal closure and inducing the expression of stress-responsive genes. Application of AMFs or transgenic overexpression of the receptor PYL2 in Arabidopsis and soybean plants confers increased drought resistance. The greatest increase in drought resistance is achieved when AMFs are applied to the PYL2-overexpression transgenic plants. Our results demonstrate that the combining of potent chemicals with transgenic overexpression of an ABA receptor is very effective in helping plants combat drought stress. Plants respond to abiotic stress via the phytohormone ABA. Here, Cao et al. report a series of new ABA receptor agonists, named AMFs, which have higher receptor-binding affinities and show that, when employed in tandem with ABA receptor overexpression, can significantly increase drought resistance