Peptide‐based materials are one of the most important biomaterials, with diverse structures and functionalities. Over the past few decades, a self‐assembly strategy is introduced to construct ...peptide‐based nanomaterials, which can form well‐controlled superstructures with high stability and multivalent effect. More recently, peptide‐based functional biomaterials are widely utilized in clinical applications. However, there is no comprehensive review article that summarizes this growing area, from fundamental research to clinic translation. In this review, the recent progress of peptide‐based materials, from molecular building block peptides and self‐assembly driving forces, to biomedical and clinical applications is systematically summarized. Ex situ and in situ constructed nanomaterials based on functional peptides are presented. The advantages of intelligent in situ construction of peptide‐based nanomaterials in vivo are emphasized, including construction strategy, nanostructure modulation, and biomedical effects. This review highlights the importance of self‐assembled peptide nanostructures for nanomedicine and can facilitate further knowledge and understanding of these nanosystems toward clinical translation.
The recent progress in peptide‐based nanomaterials from building block peptides and self‐assembly driving forces to application‐directed ex situ and in situ construction of nanomaterials is systematically summarized. The advantages of intelligent in situ construction of peptide‐based nanomaterials in vivo are emphasized. The importance of self‐assembled peptide nanostructures for nanomedicine is highlighted.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
A pathology‐adaptive nanosystem, in which nest‐like hosts are built based on nanofibers that are transformed from i.v. injected nanoparticles under the acidic tumor microenvironment. The solid tumor ...is artificially modified by nest‐like hosts readily and firmly, resulting in highly efficient accumulation and stabilization of guest theranostics. This strategy shows great potential for the theranostics delivery to tumors.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Recently, deep convolution neural networks (CNNs) steered face super-resolution methods have achieved great progress in restoring degraded facial details by joint training with facial priors. ...However, these methods have some obvious limitations. On the one hand, multi-task joint learning requires additional marking on the dataset, and the introduced prior network will significantly increase the computational cost of the model. On the other hand, the limited receptive field of CNN will reduce the fidelity and naturalness of the reconstructed facial images, resulting in suboptimal reconstructed images. In this work, we propose an efficient CNN-Transformer Cooperation Network (CTCNet) for face super-resolution tasks, which uses the multi-scale connected encoder-decoder architecture as the backbone. Specifically, we first devise a novel Local-Global Feature Cooperation Module (LGCM), which is composed of a Facial Structure Attention Unit (FSAU) and a Transformer block, to promote the consistency of local facial detail and global facial structure restoration simultaneously. Then, we design an efficient Feature Refinement Module (FRM) to enhance the encoded features. Finally, to further improve the restoration of fine facial details, we present a Multi-scale Feature Fusion Unit (MFFU) to adaptively fuse the features from different stages in the encoder procedure. Extensive evaluations on various datasets have assessed that the proposed CTCNet can outperform other state-of-the-art methods significantly. Source code will be available at https://github.com/IVIPLab/CTCNet.
Cross-resolution face recognition (CRFR), which is important in intelligent surveillance and biometric forensics, refers to the problem of matching a low-resolution (LR) probe face image against ...high-resolution (HR) gallery face images. Existing shallow learning-based and deep learning-based methods focus on mapping the HR-LR face pairs into a joint feature space where the resolution discrepancy is mitigated. However, little works consider how to extract and utilize the intermediate discriminative features from the noisy LR query faces to further mitigate the resolution discrepancy due to the resolution limitations. In this study, we desire to fully exploit the multi-level deep convolutional neural network (CNN) feature set for robust CRFR. In particular, our contributions are threefold. (i) To learn more robust and discriminative features, we desire to adaptively fuse the contextual features from different layers. (ii) To fully exploit these contextual features, we design a feature set-based representation learning (FSRL) scheme to collaboratively represent the hierarchical features for more accurate recognition. Moreover, FSRL utilizes the primitive form of feature maps to keep the latent structural information, especially in noisy cases. (iii) To further promote the recognition performance, we desire to fuse the hierarchical recognition outputs from different stages. Meanwhile, the discriminability from different scales can also be fully integrated. By exploiting these advantages, the efficiency of the proposed method can be delivered. Experimental results on several face datasets have verified the superiority of the presented algorithm to the other competitive CRFR approaches.
Tumor metastasis is one of the big challenges in cancer treatment and is often associated with high patient mortality. Until now, there is an agreement that tumor invasion and metastasis are related ...to degradation of extracellular matrix (ECM) by enzymes. Inspired by the formation of natural ECM and the in situ self-assembly strategy developed in our group, herein, we in situ constructed an artificial extracellular matrix (AECM) based on transformable Laminin (LN)-mimic peptide 1 (BP-KLVFFK-GGDGR-YIGSR) for inhibition of tumor invasion and metastasis. The peptide 1 was composed of three modules including (i) the hydrophobic bis-pyrene (BP) unit for forming and tracing nanoparticles; (ii) the KLVFF peptide motif that was inclined to form and stabilize fibrous structures through intermolecular hydrogen bonds; and (iii) the Y-type RGD-YIGSR motif, derived from LN conserved sequence, served as ligands to bind cancer cell surfaces. The peptide 1 formed nanoparticles (1-NPs) by the rapid precipitation method, owing to strong hydrophobic interactions of BP. Upon intravenous injection, 1-NPs effectively accumulated in the tumor site due to the enhanced permeability and retention (EPR) effect and/or targeting capability of RGD-YIGSR. The accumulated 1-NPs simultaneously transformed into nanofibers (1-NFs) around the solid tumor and further entwined to form AECM upon binding to receptors on the tumor cell surfaces. The AECM stably existed in the primary tumor site over 72 h, which consequently resulted in efficiently inhibiting the lung metastasis in breast and melanoma tumor models. The inhibition rates in two tumor models were 82.3% and 50.0%, respectively. This in vivo self-assembly strategy could be widely utilized to design effective drug-free biomaterials for inhibiting the tumor invasion and metastasis.
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IJS, KILJ, NUK, PNG, UL, UM
We present the Topology Transformation Equivariant Representation learning, a general paradigm of self-supervised learning for node representations of graph data to enable the wide applicability of ...Graph Convolutional Neural Networks (GCNNs). We formalize the proposed model from an information-theoretic perspective, by maximizing the mutual information between topology transformations and node representations before and after the transformations. We derive that maximizing such mutual information can be relaxed to minimizing the cross entropy between the applied topology transformation and its estimation from node representations. In particular, we seek to sample a subset of node pairs from the original graph and flip the edge connectivity between each pair to transform the graph topology. Then, we self-train a representation encoder to learn node representations by reconstructing the topology transformations from the feature representations of the original and transformed graphs. In experiments, we apply the proposed model to the downstream node classification, graph classification and link prediction tasks, and results show that the proposed method outperforms the state-of-the-art unsupervised approaches.
Abstract
Marine mussels achieve strong underwater adhesion by depositing mussel foot proteins (Mfps) that form coacervates during the protein secretion. However, the molecular mechanisms that govern ...the phase separation behaviors of the Mfps are still not fully understood. Here, we report that GK-16*, a peptide derived from the primary adhesive protein Mfp-5, forms coacervate in seawater conditions. Molecular dynamics simulations combined with point mutation experiments demonstrate that Dopa- and Gly- mediated hydrogen-bonding interactions are essential in the coacervation process. The properties of GK-16* coacervates could be controlled by tuning the strength of the electrostatic and Dopa-mediated hydrogen bond interactions via controlling the pH and salt concentration of the solution. The GK-16* coacervate undergoes a pH induced liquid-to-gel transition, which can be utilized for the underwater delivery and curing of the adhesives. Our study provides useful molecular design principles for the development of mussel-inspired peptidyl coacervate adhesives with tunable properties.
Key message
We developed and validated a robust marker toolkit for high-throughput and cost-effective screening of a large number of functional genes in wheat.
Functional markers (FMs) are the most ...valuable markers for crop breeding programs, and high-throughput genotyping for FMs could provide an excellent opportunity to effectively practice marker-assisted selection while breeding cultivars. Here we developed and validated kompetitive allele-specific PCR (KASP) assays for genes that underpin economically important traits in bread wheat including adaptability, grain yield, quality, and biotic and abiotic stress resistances. In total, 70 KASP assays either developed in this study or obtained from public databases were validated for reliability in application. The validation of KASP assays were conducted by (a) comparing the assays with available gel-based PCR markers on 23 diverse wheat accessions, (b) validation of the derived allelic information using phenotypes of a panel comprised of 300 diverse cultivars from China and 13 other countries, and (c) additional testing, where possible, of the assays in four segregating populations. All KASP assays being reported were significantly associated with the relevant phenotypes in the cultivars panel and bi-parental populations, thus revealing potential application in wheat breeding programs. The results revealed 45 times superiority of the KASP assays in speed than gel-based PCR markers. KASP has recently emerged as single-plex high-throughput genotyping technology; this is the first report on high-throughput screening of a large number of functional genes in a major crop. Such assays could greatly accelerate the characterization of crossing parents and advanced lines for marker-assisted selection and can complement the inflexible, high-density SNP arrays. Our results offer a robust and reliable molecular marker toolkit that can contribute towards maximizing genetic gains in wheat breeding programs.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), spread rapidly in Africa and Asia recently, causing huge economic losses in crop production. Fall armyworm caterpillars were first ...detected in South Korea and Japan in June 2019. Here, the migration timing and path for FAW into the countries were estimated by a trajectory simulation approach implementing the insect's flight behavior. The result showed that FAWs found in both South Korea and Japan were estimated to have come from eastern China by crossing the Yellow Sea or the East China Sea in 10–36 h in three series of migrations. In the first series, FAW moths that arrived on Jeju Island during 22–24 May were estimated to be from Zhejiang, Anhui and Fujian Provinces after 1–2 nights’ flights. In the second series, it was estimated that FAW moths landed in southern Korea and Kyushu region of Japan simultaneously or successively during 5–9 June, and these moths mostly came from Guangdong and Fujian Provinces. The FAW moths in the third series were estimated to have immigrated from Taiwan Province onto Okinawa Islands during 19–24 June. During these migrations, southwesterly low‐level jets extending from eastern China to southern Korea and/or Japan were observed in the northwestern periphery of the western Pacific Subtropical High. These results, for the first time, suggested that the overseas FAW immigrants invading Korea and Japan came from eastern and southern China. This study is helpful for future monitoring, early warning and the source control of this pest in the two countries.
Fall armyworm (FAW) would take a round‐trip migratory cycle in eastern Asia, where they will pose a serious threat to food security. Therefore, it is very important to understand the migration path and the source area for monitoring and controlling this pest. This study, for the first time, suggested that the overseas FAW immigrants invading Korea and Japan came from eastern and southern China. This study is helpful for future monitoring, early warning and the source control of this pest in the two countries.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Objective
Hepatitis B virus X protein (HBx) is a pivotal factor for HBV-induced hepatitis. Herein, we sought to investigate HBx-mediated NLR pyrin domain containing 3 (NLRP3) inflammasome activation ...and pyroptosis under oxidative stress.
Methods
The effect of HBx on the NLRP3 inflammasome was analyzed by enzyme-linked immunosorbent assays, quantitative reverse transcription-polymerase chain reaction, western blotting, and immunofluorescence in hepatic HL7702 cells. Pyroptosis was evaluated by western blotting, lactate dehydrogenase release, propidium iodide staining, and transmission electron microscopy. NLRP3 expression in the inflammasome from liver tissues was assessed by immunohistochemistry.
Results
In hydrogen peroxide (H
2
O
2
)-stimulated HL7702 cells, HBx triggered the release of pro-inflammatory mediators apoptosis-associated speck-like protein containing a CARD (ASC), interleukin (IL)-1β, IL-18, and high-mobility group box 1 (HMGB1); activated NLRP3; and initiated pro-inflammatory cell death (pyroptosis). HBx localized to the mitochondria, where it induced mitochondrial damage and production of mitochondrial reactive oxygen species (mitoROS). Treatment of HL7702 cells with a mitoROS scavenger attenuated HBx-induced NLRP3 activation and pyroptosis. Expression levels of NLRP3, ASC, and IL-1β in liver tissues from patients were positively correlated with HBV DNA concentration.
Conclusions
The NLRP3 inflammasome was activated by elevated mitoROS levels and mediated HBx-induced liver inflammation and hepatocellular pyroptosis under H
2
O
2
-stress conditions.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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