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DNA origami-based nanorobot presents thrombin to cause tumor infarction after specific recognition of a tumor vessel marker. Nanoscale robots have potential as intelligent drug delivery systems that respond to molecular triggers 1 , 2 , 3 , 4 . Using DNA origami we constructed an autonomous DNA robot programmed to transport payloads and present them specifically in tumors. Our nanorobot is functionalized on the outside with a DNA aptamer that binds nucleolin, a protein specifically expressed on tumor-associated endothelial cells 5 , and the blood coagulation protease thrombin within its inner cavity. The nucleolin-targeting aptamer serves both as a targeting domain and as a molecular trigger for the mechanical opening of the DNA nanorobot. The thrombin inside is thus exposed and activates coagulation at the tumor site. Using tumor-bearing mouse models, we demonstrate that intravenously injected DNA nanorobots deliver thrombin specifically to tumor-associated blood vessels and induce intravascular thrombosis, resulting in tumor necrosis and inhibition of tumor growth. The nanorobot proved safe and immunologically inert in mice and Bama miniature pigs. Our data show that DNA nanorobots represent a promising strategy for precise drug delivery in cancer therapy.

Effective and safe hemodialysis is essential for patients with acute kidney injury and chronic renal failures. However, the development of effective anticoagulant agents with safe antidotes for use during hemodialysis has proven challenging. Here, we describe DNA origami-based assemblies that enable the inhibition of thrombin activity and thrombus formation. Two different thrombin-binding aptamers decorated DNA origami initiates protein recognition and inhibition, exhibiting enhanced anticoagulation in human plasma, fresh whole blood and a murine model. In a dialyzer-containing extracorporeal circuit that mimicked clinical hemodialysis, the origami-based aptamer nanoarray effectively prevented thrombosis formation. Oligonucleotides containing sequences complementary to the thrombin-binding aptamers can efficiently neutralize the anticoagulant effects. The nanoarray is safe and immunologically inert in healthy mice, eliciting no detectable changes in liver and kidney functions or serum cytokine concentration. This DNA origami-based nanoagent represents a promising anticoagulant platform for the hemodialysis treatment of renal diseases. Safe haemodialysis is essential for patients with acute kidney injury and renal failure. Here the authors present a DNA origami-based approach with high affinity and specificity to thrombin, inhibiting coagulation.

Water level is decreased during foundation pit excavation to avoid water inrush under confined water pressure. Cut-off wall is often used as waterproof curtain to partially cut off the dewatered aquifer. When a foundation pit is located in a built-up area and the underlying confined aquifer is not cut off, the drawdown must be minimized outside the pit to avoid land subsidence in buildings and pipelines. The coupling effect of the cut-off wall and pumping well is used to control the drawdown outside the foundation pit. However, the coupling mechanism is not intuitively well understood because of the limitations of existing experimental methods. In this study, transparent soil was introduced to model the coupling mechanism in the physical model test. High-purity fused silica and mixed paraffin oil were used as skeleton and fluid to simulate the confined aquifer and groundwater. Industrial solid dye and paraffin oil were used as tracers. A camera was used to collect flow information. Tests were performed for the combinations of cut-off wall and partially penetrating pumping wells. The insertion depth ratio of the cut-off wall most effectively influenced the drawdown. The layout of the pumping wells in horizontal direction influenced water level distribution and flow rate. The optimal depth of the pumping wells was 1–5 m above the bottom of the cut-off wall, and the optimal horizontal distance between the cut-off wall and the pumping wells was 25% of the pit width. Non-Darcy flow was observed within the range of 0–10 m around the bottom of the cut-off wall. These results were significant in understanding the cut-off wall and pumping well coupling effect on foundation pit dewatering.

Heavy metals are a growing threat to human health due to the resulting damage to the ecology; the removal of heavy metals by lactic acid bacteria (LAB) has been a focus of many studies. In this study, 10 LAB strains were evaluated for their ability to absorb and tolerate lead. Lactobacillus plantarum YW11 was found to possess the strongest ability of lead absorbing and tolerance, with the rate of absorption as high as 99.9% and the minimum inhibitory concentration of lead on YW11 higher than 1000 mg/L. Based on the isobaric tags for relative and absolute quantitation (iTRAQ) proteomics analysis of YW11, a total of 2009 proteins were identified both in the lead-treated strain and the control without the lead treatment. Among these proteins, 44 different proteins were identified. The abundance of 25 proteins increased significantly, and 19 proteins decreased significantly in the treatment group. These significantly differential abundant proteins are involved in the biological processes of amino acid and lipid metabolism, energy metabolism, cell wall biosynthesis, and substance transport. This study contributed further understanding of the molecular mechanism of L. plantarum in the binding and removal of lead to explore its potential application in counteracting heavy metal pollution of environment, food, and other fields.

Lipid nanoparticles (LNPs) are the most clinically relevant vehicles for mRNA vaccines. Despite the great successes, the toxicity caused by the high dose of lipid components still represents a great challenge. The suboptimal loading capacity of mRNA in LNPs not only compromises the vaccine’s efficacy but also heightens the risk of non-specific immune responses, accelerates clearance caused by anti-PEG IgG/IgM. These problems underscore the urgent need for improving mRNA loading capacity in LNPs to provide dose-sparing effects. Herein, we develop a metal ion mediated mRNA enrichment strategy to efficiently form a high-density mRNA core, and manganese ion (Mn 2+ ) exhibits a unique capability to match the need. The prepared Mn-mRNA nanoparticle is subsequently coated with lipids to form the resulting nanosystem, L@Mn-mRNA, which achieved nearly twice the mRNA loading capacity compared to conventional mRNA vaccine formulations (LNP-mRNA). Remarkably, L@Mn-mRNA also demonstrates a 2-fold increase in cellular uptake efficiency compared to LNP-mRNA, attributed to the enhanced stiffness provided by the Mn-mRNA core. By combining improved mRNA loading with superior cellular uptake, L@Mn-mRNA achieves significantly enhanced antigen-specific immune responses and therapeutic efficacy as vaccines. We elucidate the mechanism behind Mn-mRNA construction and optimize the L@Mn-mRNA formulations, and this method is suitable for types of lipids and mRNAs. Moreover, L@Mn-mRNA also reduces the risk of anti-PEG IgG/IgM generation. Thus, this strategy holds significant potential as a platform for the next generation of lipid-based mRNA vaccines. Lipid nanoparticles are the gold standard for mRNA delivery but suffer from low loading capacity. Here, the authors report on the use of manganese ions to form mRNA rich cores within lipid nanoparticles which increased mRNA loading, reducing the lipid needed and increasing transfection and immune response in vivo.

T-cell engager (TCE)-based immunotherapy is clinically validated in hematological cancers. However, application in solid tumors faces hurdles including T cell penetration, the immunosuppressive tumor microenvironment, and toxicity. We develop an mRNA-encoded TCE (MTS105) targeting Glypican-3, the hepatocellular carcinoma antigen, delivered via lipid nanoparticles directly to liver tissue. In mice, rats, and cynomolgus monkeys, MTS105 exhibits higher liver exposure versus plasma. Liver-orthotopic tumor-bearing mice achieve complete, dose-dependent regression, with fast intratumoral T cell activation owing to sustained higher liver and tumor functional TCE exposure versus conventional antibody-based TCE. In vivo, MTS105 induces intratumoral CD8 cell precursor and terminally differentiated memory subsets with high activation scores. In cynomolgus monkeys, MTS105 displays favorable, linear plasma pharmacokinetics including mRNA, ionizable lipid, and translated TCE following single and repeated-four-weekly dosing (up to 45 μg/kg). No severe adverse effects or gross pathology were observed. Our results thus support the advancement of MTS105 into clinical trials, with a first-in-human study currently underway. T-cell engager (TCE)-based immunotherapy requires further development in solid tumors due to limited T cell penetration, immunosuppressive tumor microenvironment and toxicity. The authors here develop a glypican-3 targeting mRNA TCE (MTS105) which manifests superior T cell activation and tumor regression hepatocellular carcinoma mice model comparing to conventional TCE, and safety with cynomolgus monkey studies.

9- -epoxycarotenoid dioxygenase (NCED) is a key enzyme involved in the biosynthesis of abscisic acid (ABA), which is associated with drought tolerance in plants. An osmotic-inducible gene was isolated from a drought-resistant cultivar of and constitutively overexpressed in a drought-sensitive cultivar of . Transgenic plants showed significantly improved drought tolerance, including a higher growth rate and better drought resistant under drought conditions, compared to those of wild-type (WT) plants. After water was withheld for 50 days, the upper leaves of transgenic plants remained green, whereas most leaves of WT plants turned yellow and fell. Besides the increase in ABA content, overexpression of induced the production of jasmonic acid (JA) and accumulation of JA biosynthesis-related genes, including ( ) and ( ). Moreover, transgenic plants possessed advantageous physiological indices, including lower leaf stomatal density, lower photosynthesis rate, and lower accumulation of proline and superoxide dismutase (SOD), compared to those of WT plants, indicating increased resistance to drought stress. Quantitative real time polymerase chain reaction (RT-qPCR) analysis revealed that overexpression of enhanced the expression of drought-responsive genes, such as ( ) ( ), ( ), ( ) and ( ). Although the development of transgenic plants was delayed by 4 months than WT plants, because of seed dormancy and abnormal seedlings, the surviving transgenic plants provided a solid method for protection of woody plants from drought stress.

Winograd’s minimal filtering algorithm has been widely used in 2-D Convolutional Neural Networks (CNNs) to reduce the number of multiplications for faster processing. However, it is only effective on convolutions with kernel size as 3 and stride as 1, because it suffers from significantly increased FLOPs and numerical accuracy problems for kernel size larger than 3 and fails on convolution with stride larger than 1. Worse, the extension to N–D convolution will intensify the numerical accuracy problem. These problems severely obstruct Winograd’s minimal filtering algorithm’s application to video analysis. In this paper, we propose a novel Decomposable Winograd Method (DWM) for the N–D convolution acceleration, which breaks through the limitation of original Winograd’s minimal filtering algorithm to more general convolutions. DWM decomposes kernels with large size or stride>1 to several small kernels with stride as 1 for further applying Winograd algorithm, so that DWM can reduce the number of multiplications while keeping the numerical accuracy. It enables the fast exploration of larger kernel size, larger stride value, and higher dimensions in CNNs for high performance and accuracy and even the potential for new CNNs. Comparing against the original Winograd algorithm, the proposed DWM is able to support all kinds of N–D convolutions with a speedup of 1.44×–3.38×, without affecting the numerical accuracy.

Fringe projection profilometry (FPP) has been widely applied to non-contact three-dimensional measurement in industries owing to its high accuracy and speed. The point cloud, which is a measurement result of the FPP system, typically contains a large number of invalid points caused by the background, ambient light, shadows, and object edge regions. Research on noisy point detection and elimination has been conducted over the past two decades. However, existing invalid point removal methods are based on image intensity analysis and are only applicable to simple measurement backgrounds that are purely dark. In this paper, we propose a novel invalid point removal framework that consists of two aspects: (1) A convolutional neural network (CNN) is designed to segment the foreground from the background of different intensity conditions in FPP measurement circumstances to remove background points and the most discrete points in background regions. (2) A two-step method based on the fringe image intensity threshold and a bilateral filter is proposed to eliminate the small number of discrete points remaining after background segmentation caused by shadows and edge areas on objects. Experimental results verify that the proposed framework (1) can remove background points intelligently and accurately in different types of complex circumstances, and (2) performs excellently in discrete point detection from object regions.

Largemouth bass (Micropterus salmoides) is an important commercial fish farmed in China. Challenges related to diseases caused by pathogens, such as iridovirus, have become increasingly serious. In 2017, we detected iridovirus-infected diseased largemouth bass in Zunyi, Guizhou Province. The isolated virus was identified as an infectious spleen and kidney necrosis virus (ISKNV)-like virus (ISKNV-ZY). ISKNV-ZY induces a cytopathic effect after infecting mandarin fish brain (MFB) cells. Abundant hexagonal virus particles were observed in the cytoplasm of ISKNV-ZY-infected MFB cells, using electron microscopy. The whole genome of ISKNV-ZY contained 112,248 bp and 122 open reading frames. Phylogenetic tree analysis showed that ISKNV-ZY was most closely related to BCIV, indicating that it is an ISKNV-like megalocytivirus. ISKNV-ZY-infected largemouth bass started to die on day six and reached a death peak on days 7–8. Cumulative mortality reached 100% on day 10. Using RNA sequencing-based transcriptome analysis after ISKNV-ZY infection, 6254 differentially expressed unigenes (DEGs) were identified, of which 3518 were upregulated and 2673 downregulated. The DEGs were associated with endocytosis, thermogenesis, oxidative phosphorylation, the JAK-STAT signaling pathway, the MAPK signaling pathway, etc. These results contribute to understanding the molecular regulation mechanism of ISKNV infection and provide a basis for ISKNV prevention.