Development of stapled NONO-associated peptides reveals unexpected cell permeability and nuclear localisation.

The non-POU domain-containing octamer-binding protein (NONO) is a nucleic acid-binding protein with diverse functions that has been identified as a potential cancer target in cell biology studies. Little is known about structural motifs that mediate binding to NONO apart from its ability to form homodimers, as well as heterodimers and oligomers with related homologues. We report a stapling approach to macrocyclise helical peptides derived from the insulin-like growth factor binding protein (IGFBP-3) that NONO interacts with, and also from the dimerisation domain of NONO itself. Using a range of chemistries including Pd-catalysed cross-coupling, cysteine arylation and cysteine alkylation, we successfully improved the helicity and observed modest peptide binding to the NONO dimer, although binding could not be saturated at micromolar concentrations. Unexpectedly, we observed cell permeability and preferential nuclear localisation of various dye-labelled peptides in live confocal microscopy, indicating the potential for developing peptide-based tools to study NONO in a cellular context.

Ultracompact Energy Transfer in Anapole-based Metachains.

Realization of electromagnetic energy confinement beyond the diffraction limit is crucial for high-performance on-chip devices. Herein we construct an array of nonradiative anapoles that originate from the destructive far-field interference of electric and toroidal dipole modes to achieve ultracompact and high-efficiency electromagnetic energy transfer without the coupler. We experimentally investigate the proposed metachain at mid-infrared frequencies and give the first near-field experimental evidence of anapole-based energy transfer, in which the spatial profile of the anapole mode is also unambiguously identified on the nanoscale. We further demonstrate that the metachain is intrinsically lossless and scalable at infrared wavelengths, realizing a 90° bending loss down to 0.32 dB at the optical communication wavelength. The present scheme bridges the gap between the energy confinement and the transfer of anapoles and opens a new gate for more compactly integrated photonic and energy devices, which can operate in a broad spectral range.

Performance investigation of the polar coded FSO communication system over turbulence channel.

In this paper, for the first time, to the best of our knowledge, polar codes are introduced and experimentally implemented in a free space optical (FSO) communication system to combat atmospheric turbulence induced fading. By analyzing the characteristics of the turbulence channel, a method of evaluating the channel state information for polar decoding is proposed that can achieve good trade-off between the performance and the computational complexity of this polar coded system. To verify our scheme, an intensity modulation direct detection FSO communication experimental platform with a turbulence chamber is established. For the weak turbulence condition, comparing with the low-density parity check codes, the experimental results show that our proposed scheme has stronger error correcting capacity and lower computational complexity in combating the turbulence induced fading. Moreover, for moderate and strong turbulence conditions, the gamma-gamma turbulence model is adopted for constructing the Monte Carlo simulation. The results of the experiment and simulation both show that our proposed scheme can effectively combat atmospheric turbulence induced fading with a relatively low computational complexity in a wide range of turbulence conditions.

Intravenous injection of nattokinase-heparin electrostatic complex improves the therapeutic effect of advanced tumors by dissolving cancer-related thrombosis.

AIMS: Cancer-related thrombosis (CAT) is a common complication in cancer patients, significantly impacting their quality of life and survival prospects. Nattokinase (NK) has potent thrombolytic properties, however, its efficacy is limited by low oral bioavailability and the risk of severe allergic reactions with intravenous use. Heparin (HP) is a widely used anticoagulant in clinical settings. This study aimed to overcome the intravenous toxicity of NK and explore its effect on CAT in advanced tumors. MAIN METHODS: In this study, NK-HP electrostatic complexes were constructed, and their safety and thrombolytic efficacy were verified through guinea pig allergy tests, mouse tail vein tests, and both in vivo and in vitro thrombolysis experiments. Additionally, an S180 advanced tumor model was developed and combined with sialic acid-modified doxorubicin liposomes (DOX-SAL) to investigate the impact of NK-HP on CAT and its antitumor effects in advanced tumors. KEY FINDINGS: We observed that NK-HP can eliminate the intravenous injection toxicity of NK, has strong thrombolytic performance, and can prevent thrombosis formation. Intravenous injection of NK-HP can enhance the antitumor effect of DOX-SAL by reducing the fibrin content in advanced tumors and increasing the levels of the cross-linked protein degradation product D-dimer. SIGNIFICANCE: This study developed a method to eliminate the intravenous injection toxicity of NK, proposing a promising therapeutic strategy for CAT treatment, particularly for CAT in advanced tumors, and improving the efficacy of nano-formulations in anti-tumor therapy.

Re-examining the effect of carbon emission trading policy on improving the green innovation of China's enterprises.

China's carbon emission trading (CET) policy guides enterprises to carry out green innovation and address the growing environmental challenges through market-based instruments. However, can CET policy effectively promote enterprises' green innovation? It has become a hot issue. Whether it can play the "Porter effect" is also controversial. We have little research on the effectiveness and heterogeneity of CET policy in China. We obtained the following conclusions from the empirical results: (1) CET policy has clearly promoted green innovation in enterprises, the proportion of green innovation of enterprises increased by 13.43%, and the "weak Porter hypothesis" was tenable. And the results of the research have been tested to be robust and reliable. (2) CET policy plays an obvious role in enhancing the enterprises' green innovation with high-stock enterprise, large-scale enterprise, and state-owned enterprises. (3) Carbon quota auction does not motivate enterprises to improve green innovation; the CET policy under the ex-post allowance allocation of government can better inspire enterprises to undertake green innovation events. (4) The pilot policy of carbon emission trading can increase the introduction of scientific research talents, increase the expenditure of scientific research and development, and improve the net profit margin of enterprise assets, thus directly or indirectly promoting the development of green innovation of enterprises. Overall, the research in this article provides theoretical policy and empirical research for implementing carbon emission trading policy in developing countries and provides theoretical support for how to realize the "double dividend" of environmental protection and enterprises' green innovation competitiveness. Meanwhile, it also provides reference for the national CET to be officially run, and it is instructive to establish a flexible market-based instruments.

Graph Few-Shot Learning via Restructuring Task Graph.

Existing graph few-shot learning (FSL) methods usually train a model on many task graphs and transfer the learned model to a new task graph. However, the task graphs often contain a great number of isolated nodes, which results in the severe deficiency of learned node embeddings. Furthermore, in the training process, the neglect of task information also constrains the model's expressive ability. In this brief, we propose a novel metric-based graph few-shot learning approach via restructuring task graph (GFL-RTG). To solve the problems above, we innovatively restructure the task graph by adding class nodes and a task node to the original individual task graph. We first add class nodes and determine the connectivity between class nodes and others via their similarity. Then, we utilize a graph pooling network to learn a task embedding, which is regarded as a task node. Finally, the new task graph is restructured by combining class nodes, task node, and original nodes, which is then used as input to the metric-based graph neural network (GNN) to conduct few-shot learning. Our extensive experiments on three graph-structured datasets demonstrate that our proposed method generally outperforms the state-of-the-art baselines in few-shot learning.

Cyclisation strategies for stabilising peptides with irregular conformations.

Cyclisation is a common synthetic strategy for enhancing the therapeutic potential of peptide-based molecules. While there are extensive studies on peptide cyclisation for reinforcing regular secondary structures such as α-helices and ß-sheets, there are remarkably few reports of cyclising peptides which adopt irregular conformations in their bioactive target-bound state. In this review, we highlight examples where cyclisation techniques have been successful in stabilising irregular conformations, then discuss how the design of cyclic constraints for irregularly structured peptides can be informed by existing ß-strand stabilisation approaches, new computational design techniques, and structural principles extracted from cyclic peptide library screening hits. Through this analysis, we demonstrate how existing peptide cyclisation techniques can be adapted to address the synthetic design challenge of stabilising irregularly structured binding motifs.

Water and nitrogen in-situ imaging detection in live corn leaves using near-infrared camera and interference filter.

BACKGROUND: Realizing imaging detection of water and nitrogen content in different regions of plant leaves in-site and real-time can provide an efficient new technology for determining crop drought resistance and nutrient regulation mechanisms, or for use in precision agriculture. Near-infrared imaging is the preferred technology for in-situ real-time detection owing to its non-destructive nature; moreover, it provides rich information. However, the use of hyperspectral imaging technology is limited as it is difficult to use it in field because of its high weight and power. RESULTS: We developed a smart imaging device using a near-infrared camera and an interference filter; it has a low weight, requires low power, and has a multi-wavelength resolution. The characteristic wavelengths of the filter that realize leaf moisture measurement are 1150 and 1400 nm, respectively, the characteristic wavelength of the filter that realizes nitrogen measurement is 1500 nm, and all filter bandwidths are 25 nm. The prediction result of the average leaf water content model obtained with the device was R2 = 0.930, RMSE = 1.030%; the prediction result of the average nitrogen content model was R2 = 0.750, RMSE = 0.263 g. CONCLUSIONS: Using the average water and nitrogen content model, an image of distribution of water and nitrogen in different areas of corn leaf was obtained, and its distribution characteristics were consistent with the actual leaf conditions. The experimental materials used in this research were fresh leaves in the field, and the test was completed indoors. Further verification of applying the device and model to the field is underway.

An Improved Multi-Relaxation Time Lattice Boltzmann Method for the Non-Newtonian Influence of the Yielding Fluid Flow in Cement-3D Printing.

The multi-relaxation time lattice Boltzmann method (MRT-LBM) has an excellent performance in dealing with the complex flow in many different areas. According to the specific behavior of the fluids, it also has some shortcomings when applied to some special flow like as the non-Newtonian flow. In Cement-3D printing, the fluids always exhibit according to the yielding behavior. When using the standard MRT-LBM, the simulation maybe divergent. In order to solve the problem, this work presents an improved MRT-LBM considering the non-Newtonian effect as a special forcing term to ensure the stable and accurate simulation. Finally, the Poiseuille flow was used to validate the feasibility of the proposed method.