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Aucubin slows the creation of osteoporosis through suppressing osteoclast difference through the fischer aspect erythroid 2-related issue 2-mediated antioxidation process.
Recent studies also suggest that inhibition of EZH2 enhances the response to tumor immunotherapy. Many small-molecule inhibitors have been developed to target EZH2 or the PRC2 complex, with some of these inhibitors now in early clinical trials reporting clinical responses with acceptable tolerability. In this review, we highlight the recent advances in targeting EZH2, its successes, and potential limitations, and we discuss the future directions of this therapeutic subclass.Lung squamous carcinoma (LUSC) is a highly metastatic disease with a poor prognosis. Using an integrated screening approach, we found that miR-671-5p reduces LUSC metastasis by inhibiting a circular RNA (circRNA), CDR1as. Although the putative function of circRNA is through miRNA sponging, we found that miR-671-5p more potently silenced an axis of CDR1as and its antisense transcript, cerebellar degeneration related protein 1 (CDR1). Silencing of CDR1as or CDR1 significantly inhibited LUSC metastases and CDR1 was sufficient to promote migration and metastases. #link# CDR1, which directly interacted with adaptor protein 1 (AP1) complex subunits and coatomer protein I (COPI) proteins, no longer promoted migration upon blockade of Golgi trafficking. Therapeutic inhibition of the CDR1as/CDR1 axis with miR-671-5p mimics reduced metastasis in vivo. This report demonstrates a novel role for CDR1 in promoting metastasis and Golgi trafficking. These findings reveal an miRNA/circRNA axis that regulates LUSC metastases through a previously unstudied protein, CDR1. SIGNIFICANCE This study shows that circRNA, CDR1as, promotes lung squamous migration, metastasis, and Golgi trafficking through its complimentary transcript, CDR1.Mussels can strongly adhere to hydrophilic minerals in sea habitats by secreting adhesive proteins. The adhesion ability of these proteins is often attributed to the presence of Dopa derived from posttranslational modification of Tyr, whereas the contribution of structural feature is overlooked. It remains largely unknown how adhesive proteins overcome the surface-bound water layer to establish underwater adhesion. Here, we use molecular dynamics simulations to probe the conformations of adhesive protein Pvfp-5β and its salt-tolerant underwater adhesion on superhydrophilic mica. Dopa and positively charged basic residues form pairs, in this intrinsically disordered protein, and these residue pairs can lead to firm surface binding. Our simulations further suggest that the unmodified Tyr shows similar functions on surface adhesion by forming pairing structure with a positively charged residue. We confirm the presence of these residue pairs and verify the strong binding ability of unmodified proteins using nuclear magnetic resonance spectroscopy and lap shear tests.Designing next-generation fuel cell and filtration devices requires the development of nanoporous materials that allow rapid and reversible uptake and directed transport of water molecules. Here, check details combine neutron spectroscopy and first-principles calculations to demonstrate rapid transport of molecular H2O through nanometer-sized voids ordered within the layers of crystalline carbon nitride with a polytriazine imide structure. The transport mechanism involves a sequence of molecular orientation reversals directed by hydrogen-bonding interactions as the neutral molecules traverse the interlayer gap and pass through the intralayer voids that show similarities with the transport of water through transmembrane aquaporin channels in biological systems. The results suggest that nanoporous layered carbon nitrides can be useful for developing high-performance membranes.There has been a great deal of interest in the development of technologies for actively manipulating neural networks in vitro, providing natural but simplified environments in a highly reproducible manner in which to study brain function and related diseases. Platforms for these in vitro neural networks require precise and selective neural connections at the target location, with minimal external influences, and measurement of neural activity to determine how neurons communicate. Here, we report a neuron-loaded microrobot for selective connection of neural networks via precise delivery to a gap between two neural clusters by an external magnetic field. In addition, the extracellular action potential was propagated from one cluster to the other through the neurons on the microrobot. link2 The proposed technique shows the potential for use in experiments to understand how neurons communicate in the neural network by actively connecting neural clusters.Cancer immunotherapy using cancer vaccines has shown great potential in the prevention and treatment of cancer. Here, we report an implantable autologous blood clot scaffold for enhanced cancer vaccination. It comprises a gel-like fibrin network formed by coagulation of blood to trap a large number of red blood cells. Upon implantation, the cross-linked RBCs in the blood clot can attract and recruit a great number of immune cells, leading to the formation of an "immune niche." Encapsulated with tumor-associated antigen and adjuvant, the blood clot vaccine (BCV) can induce a robust anticancer immune response. The BCV combined with immune checkpoint blockade effectively inhibits tumor growth in B16F10 and 4T1 tumor models. The proposed implantable blood clot cancer vaccine can be readily made by mixing the blood from patients with cancer with immunomodulating agents ex vivo, followed by reimplantation into the same patient for personalized cancer immunotherapy in future clinical translation.The topology of the cerebral cortex has been proposed to provide an important source of constraint for the organization of cognition. In a sample of twins (n = 1113), we determined structural covariance of thickness to be organized along both a posterior-to-anterior and an inferior-to-superior axis. Both organizational axes were present when investigating the genetic correlation of cortical thickness, suggesting a strong genetic component in humans, and had a comparable organization in macaques, demonstrating they are phylogenetically conserved in primates. In both species, the inferior-superior dimension of cortical organization aligned with the predictions of dual-origin theory, and in humans, we found that the posterior-to-anterior axis related to a functional topography describing a continuum of functions from basic processes involved in perception and action to more abstract features of human cognition. Together, our study provides important insights into how functional and evolutionary patterns converge at the level of macroscale cortical structural organization.Understanding spin textures in magnetic systems is extremely important to the spintronics and it is vital to extrapolate the magnetic Hamiltonian parameters through the experimentally determined spin. It can provide a better complementary link between theories and experimental results. We demonstrate deep learning can quantify the magnetic Hamiltonian from magnetic domain images. To train the deep neural network, we generated domain configurations with Monte Carlo method. The errors from the estimations was analyzed with statistical methods and confirmed the network was successfully trained to relate the Hamiltonian parameters with magnetic structure characteristics. The network was applied to estimate experimentally observed domain images. The results are consistent with the reported results, which verifies the effectiveness of our methods. On the basis of our study, we anticipate that the deep learning techniques make a bridge to connect the experimental and theoretical approaches not only in magnetism but also throughout any scientific research.Neurochemical dysregulation underlies many pathologies and can be monitored by measuring the composition of brain interstitial fluid (ISF). Existing in vivo tools for sampling ISF do not enable measuring large rare molecules, such as proteins and neuropeptides, and thus cannot generate a complete picture of the neurochemical connectome. Our micro-invasive platform, composed of a nanofluidic pump coupled to a membrane-free probe, enables sampling multiple neural biomarkers in parallel. This platform outperforms the state of the art in low-flow pumps by offering low volume control (single stroke volumes, less then 3 nl) and bidirectional fluid flow ( less then 100 nl/min) with negligible dead volume ( less then 30 nl) and has been validated in vitro, ex vivo, and in vivo in rodents. ISF samples ( less then 1.5 μL) can be processed via liquid chromatography-tandem mass spectrometry. These label-free liquid biopsies of the brain could yield a deeper understanding of the onset, mechanism, and progression of diverse neural pathologies.Cells respond to starvation by shutting down protein synthesis and by activating catabolic processes, including autophagy, to recycle nutrients. link3 This two-pronged response is mediated by the integrated stress response (ISR) through phosphorylation of eIF2α, which represses protein translation, and by inhibition of mTORC1 signaling, which promotes autophagy also through a stress-responsive transcriptional program. Implementation of such a program, however, requires protein synthesis, thus conflicting with general repression of translation. How is this mismatch resolved? We found that the main regulator of the starvation-induced transcriptional program, TFEB, counteracts protein synthesis inhibition by directly activating expression of GADD34, a component of the protein phosphatase 1 complex that dephosphorylates eIF2α. We discovered that GADD34 plays an essential role in autophagy by tuning translation during starvation, thus enabling lysosomal biogenesis and a sustained autophagic flux. Hence, the TFEB-GADD34 axis integrates the mTORC1 and ISR pathways in response to starvation.Drug resistance threatens the effective prevention and treatment of an ever-increasing range of human infections. This highlights an urgent need for new and improved drugs with novel mechanisms of action to avoid cross-resistance. Current cell-based drug screens are, however, restricted to binary live/dead readouts with no provision for mechanism of action prediction. Machine learning methods are increasingly being used to improve information extraction from imaging data. These methods, however, work poorly with heterogeneous cellular phenotypes and generally require time-consuming human-led training. We have developed a semi-supervised machine learning approach, combining human- and machine-labeled training data from mixed human malaria parasite cultures. Designed for high-throughput and high-resolution screening, our semi-supervised approach is robust to natural parasite morphological heterogeneity and correctly orders parasite developmental stages. Our approach also reproducibly detects and clusters drug-induced morphological outliers by mechanism of action, demonstrating the potential power of machine learning for accelerating cell-based drug discovery.With optical spectral marks equally spaced by a frequency in the microwave or the radio frequency domain, optical frequency combs have been used not only to synthesize optical frequencies from microwave references but also to generate ultralow-noise microwaves via optical frequency division. Here, we combine two compact frequency combs, namely, a soliton microcomb and a semiconductor gain-switched comb, to demonstrate low-noise microwave generation based on a novel frequency division technique. Using a semiconductor laser that is driven by a sinusoidal current and injection-locked to microresonator solitons, our scheme transfers the spectral purity of a dissipative soliton oscillator into the subharmonic frequencies of the microcomb repetition rate. In addition, the gain-switched comb provides dense optical spectral emissions that divide the line spacing of the soliton microcomb. With the potential to be fully integrated, the merger of the two chipscale devices may profoundly facilitate the wide application of frequency comb technology.
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