Publications by authors named "Jinxing Li"

104 Publications

Development of ferroelectric nematic fluids with giant-ε dielectricity and nonlinear optical properties.

Sci Adv 2021 Apr 21;7(17). Epub 2021 Apr 21.

South China Advanced Institute for Soft Matter Science and Technology (AISMST), School of Molecular Science and Engineering, South China University of Technology, Guangzhou 510640, China.

Superhigh-ε materials that exhibit exceptionally high dielectric permittivity are recognized as potential candidates for a wide range of next-generation photonic and electronic devices. In general, achieving a high-ε state requires low material symmetry, as most known high-ε materials are symmetry-broken crystals. There are few reports on fluidic high-ε dielectrics. Here, we demonstrate how small molecules with high polarity, enabled by rational molecular design and machine learning analyses, enable the development of superhigh-ε fluid materials (dielectric permittivity, ε > 10) with strong second harmonic generation and macroscopic spontaneous polar ordering. The polar structures are confirmed to be identical for all the synthesized materials. Furthermore, adapting this strategy to high-molecular weight systems allows us to generalize this approach to polar polymeric materials, creating polar soft matters with spontaneous symmetry breaking.
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http://dx.doi.org/10.1126/sciadv.abf5047DOI Listing
April 2021

IL‑33/ST2 promotes the malignant progression of gastric cancer via the MAPK pathway.

Mol Med Rep 2021 May 24;23(5). Epub 2021 Mar 24.

Department of Clinical Laboratory, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250012, P.R. China.

Gastric cancer (GC) remains one of the commonest malignant tumors and the second leading cause of cancer‑related deaths worldwide. IL‑33 is highly expressed in tumor tissues and serum of patients with GC. However, the function of the IL‑33 and IL‑33 receptor ST2 in the malignant progression of GC is yet to be elucidated. The present study aimed to explore the effect of the IL‑33/ST2 axis on the biological functions of GC cells. The expression of ST2 in GC tissues was measured by immunohistochemistry. GC cell lines (AGS and MKN45) were treated with IL‑33, and the expression of ST2 was downregulated by using specific siRNA. The effects of the IL‑33/ST2 axis on cell proliferation, migration, invasion, cell cycle and apoptosis was detected by CCK8, Transwell, wound healing, flow cytometry and western blotting assays. The present study found that ST2 was highly expressed in GC tissues compared with normal tissues. IL‑33 promoted the proliferation and cell cycle progression of GC cells, and upregulated the expression levels of CDK4, CDK6 and cyclin D1. Furthermore, IL‑33 inhibited the apoptosis of GC cells and regulated the expression of apoptosis‑associated proteins. In addition, IL‑33 stimulated the invasion and migration of GC cells. However, the transfection of ST2 small interfering (si)RNA attenuated the effects of IL‑33. Finally, IL‑33 stimulation increased the phosphorylation levels of ERK1/2, JNK and p38. The transfection of ST2 siRNA could significantly inhibit the IL‑33‑induced ERK1/2, JNK and p38 activation. In conclusion, it was found that ST2 was highly expressed in GC tissues. IL‑33/ST2 promoted the malignant progression of GC cells by inducing the activation of ERK1/2, JNK and p38.
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http://dx.doi.org/10.3892/mmr.2021.12000DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985998PMC
May 2021

The influence of elevated CO on bacterial community structure and its co-occurrence network in soils polluted with CrO nanoparticles.

Sci Total Environ 2021 Mar 13;779:146430. Epub 2021 Mar 13.

Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou 310058, China; National Demonstration Center for Experimental Environment and Resources Education, Zhejiang University, Hangzhou 310058, China. Electronic address:

Elevated CO (eCO) and nanoparticles release are considered among the most noteworthy global concerns as they may impose negative effects on human health and ecosystem functioning. A mechanistic understanding of their combined impacts on soil microbiota is essential due to the profound eCO effect on soil biogeochemical processes. In this study, the impacts of CrO nanoparticles (nano-CrO) on the activity, structure and co-occurrence networks of bacterial communities under ambient and eCO were compared between a clay loam and a sandy loam soil. We showed that eCO substantially mitigated nano-CrO toxicity, with microbial biomass, enzyme activity and bacterial alpha-diversity in clay loam soil were much higher than those in sandy loam soil. Nano-CrO addition caused an increase in alpha-diversity except for clay loam soil samples under eCO. 16S rRNA gene profiling data found eCO remarkably reduced community divergences induced by nano-CrO more efficiently in clay loam soil (P < 0.05). Network analyses revealed more complex co-occurrence network architectures in clay loam soil than in sandy loam soil, however, nano-CrO decreased but eCO increased modularity and network complexity. Rising CO favoured the growth of oligotrophic (Acidobacteriaceae, Bryobacteraceae) rather than the copiotrophic bacteria (Sphingomonadaceae, Caulobacteraceae, Bacteroidaceae), which may contribute to community recovery and increase available carbon utilization efficiency. Our results suggested that the degree to which eCO mitigates nano-CrO toxicity is soil dependent, which could be related to the variation in clay and organic matter content, resilience of the resistant bacterial taxa, and microbial network complexity in distinct soils.
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http://dx.doi.org/10.1016/j.scitotenv.2021.146430DOI Listing
March 2021

Addi-Reg: A Better Generalization-Optimization Tradeoff Regularization Method for Convolutional Neural Networks.

IEEE Trans Cybern 2021 Mar 22;PP. Epub 2021 Mar 22.

In convolutional neural networks (CNNs), generating noise for the intermediate feature is a hot research topic in improving generalization. The existing methods usually regularize the CNNs by producing multiplicative noise (regularization weights), called multiplicative regularization (Multi-Reg). However, Multi-Reg methods usually focus on improving generalization but fail to jointly consider optimization, leading to unstable learning with slow convergence. Moreover, Multi-Reg methods are not flexible enough since the regularization weights are generated from a definite manual-design distribution. Besides, most popular methods are not universal enough, because these methods are only designed for the residual networks. In this article, we, for the first time, experimentally and theoretically explore the nature of generating noise in the intermediate features for popular CNNs. We demonstrate that injecting noise in the feature space can be transformed to generating noise in the input space, and these methods regularize the networks in a Mini-batch in Mini-batch (MiM) sampling manner. Based on these observations, this article further discovers that generating multiplicative noise can easily degenerate the optimization due to its high dependence on the intermediate feature. Based on these studies, we propose a novel additional regularization (Addi-Reg) method, which can adaptively produce additional noise with low dependence on intermediate feature in CNNs by employing a series of mechanisms. Particularly, these well-designed mechanisms can stabilize the learning process in training, and our Addi-Reg method can pertinently learn the noise distributions for every layer in CNNs. Extensive experiments demonstrate that the proposed Addi-Reg method is more flexible and universal, and meanwhile achieves better generalization performance with faster convergence against the state-of-the-art Multi-Reg methods.
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http://dx.doi.org/10.1109/TCYB.2021.3062881DOI Listing
March 2021

Layer-Output Guided Complementary Attention Learning for Image Defocus Blur Detection.

IEEE Trans Image Process 2021 23;30:3748-3763. Epub 2021 Mar 23.

Defocus blur detection (DBD), which has been widely applied to various fields, aims to detect the out-of-focus or in-focus pixels from a single image. Despite the fact that the deep learning based methods applied to DBD have outperformed the hand-crafted feature based methods, the performance cannot still meet our requirement. In this paper, a novel network is established for DBD. Unlike existing methods which only learn the projection from the in-focus part to the ground-truth, both in-focus and out-of-focus pixels, which are completely and symmetrically complementary, are taken into account. Specifically, two symmetric branches are designed to jointly estimate the probability of focus and defocus pixels, respectively. Due to their complementary constraint, each layer in a branch is affected by an attention obtained from another branch, effectively learning the detailed information which may be ignored in one branch. The feature maps from these two branches are then passed through a unique fusion block to simultaneously get the two-channel output measured by a complementary loss. Additionally, instead of estimating only one binary map from a specific layer, each layer is encouraged to estimate the ground truth to guide the binary map estimation in its linked shallower layer followed by a top-to-bottom combination strategy, gradually exploiting the global and local information. Experimental results on released datasets demonstrate that our proposed method remarkably outperforms state-of-the-art algorithms.
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http://dx.doi.org/10.1109/TIP.2021.3065171DOI Listing
March 2021

Cigarette smoke extract amplifies NADPH oxidase-dependent ROS production to inactivate PTEN by oxidation in BEAS-2B cells.

Food Chem Toxicol 2021 Apr 10;150:112050. Epub 2021 Feb 10.

Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases Co-constructed by Henan Province & Education Ministry of P.R. China, Henan University of Chinese Medicine, Zhengzhou, China; Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou, China; Department of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450000, China. Electronic address:

Chronic obstructive pulmonary disease (COPD) is widely recognized as a global public health problem and the third leading cause of mortality worldwide by 2020. Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) is a dual-specificity protein and lipid phosphatase that plays an important role in COPD. However, the redox regulation of PTEN in the development of COPD was poorly studied. Our results showed that cigarette smoke extract (CSE) could oxidize PTEN in a time-dependent manner in BEAS-2B cells, whereas PTEN oxidation exposed to CSE was delayed compared to that of HO Additionally, we found that ROS derived from DUOX1 and 2 of NADPH oxidases were mainly responsible for oxidative inactivation PTEN, also simultaneously led to Trx-1 inactivation by dimerization. Oxidative mechanism of PTEN exposed to CSE was mediated by forming a disulfide bond between Cysand Cys, similar to HO. Inactivation of PTEN resulted in the increased phosphorylation of Akt. In conclusion, CSE exposure could elevate the intracellular ROS mainly from DUOX1 and 2 to oxidize PTEN and Trx-1 resulting in Akt activation, eventually cause the occurrence of COPD, suggesting that PTEN is a potential target for new therapies in COPD.
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http://dx.doi.org/10.1016/j.fct.2021.112050DOI Listing
April 2021

Intriguing hierarchical Co@NC microflowers in situ assembled by nanoneedles: Towards enhanced reduction of nitroaromatic compounds via interfacial synergistic catalysis.

J Hazard Mater 2021 Feb 16;403:123987. Epub 2020 Sep 16.

School of Medicine, Stanford University, Stanford, CA 94304, USA.

Developing highly efficient and cost-effective catalyst with tuned microstructure holds great promise in the reduction of nitroaromatic compounds under mild reaction conditions. Herein, we report a new Co@NC-MF catalyst with a fascinating hierarchical flower-like architecture in situ assembled from uniform Co@NC nanoneedles, which can function as a favorable platform for the efficient reduction of nitroaromatic compounds in the presence of NaBH. In addition with the structural advantage, the characterization and experimental results demonstrate the enormous advantage of interfacial synergistic catalysis in enhancing the catalytic performance. The outside electron-rich N-doped carbon layer as Lewis basic sites and the inside Co nanoparticles are responsible for the adsorption of 4-nitrophenol (4-NP) and generation of active hydrogen species, respectively. This work contributes to the construction of well-integrated composites with well-balanced interface synergy to boost the catalytic performance in various heterogeneous reactions.
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http://dx.doi.org/10.1016/j.jhazmat.2020.123987DOI Listing
February 2021

Ethylene-mediated apoplastic barriers development involved in cadmium accumulation in root of hyperaccumulator Sedum alfredii.

J Hazard Mater 2021 02 19;403:123729. Epub 2020 Aug 19.

Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmentaland Resource Sciences, Zhejiang University, Hangzhou, 310058, China; Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou, 310058, China; National Demonstration Center for Experimental Environment and Resources Education, Zhejiang University, Hangzhou, 310058, China. Electronic address:

Ethylene is an important phytohormone for plant adaptation to heavy metal stress. However, the effects of ethylene on radial apoplastic transport of Cd remain elusive. This study investigated the role of ethylene on apoplastic barriers development and consequences for Cd uptake in Sedum alfredii. In response to Cd, endogenous ethylene production in hyperaccumulating ecotype (HE) roots was decreased due to the down-regulated expressions of ethylene biosynthesis genes, while the opposite result was observed in non-hyperaccumulating ecotype (NHE). Interestingly, the ethylene emission in HE was always higher than that in NHE, regardless of Cd concentrations. Results of exogenous application of ethylene biosynthesis precursor/inhibitor indicate that ethylene with high level would delay the formation of apoplastic barriers in HE through restraining phenylalanine ammonia lyase activity and gene expressions related to lignin/suberin biosynthesis. Simultaneously, correlation analyses suggest that Cd-induced apoplastic barriers formation may be also regulated by ethylene signaling. By using an apoplastic bypass tracer and scanning ion-selected electrode, we observed that the delayed deposition of apoplastic barriers significantly promoted Cd influx in roots. Taken together, high endogenous ethylene in HE postponed the formation of apoplastic barriers and thus promoted the Cd accumulation in the apoplast of roots.
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http://dx.doi.org/10.1016/j.jhazmat.2020.123729DOI Listing
February 2021

Consensus guided incomplete multi-view spectral clustering.

Neural Netw 2021 Jan 11;133:207-219. Epub 2020 Nov 11.

PAMI Research Group, Department of Computer and Information Science, University of Macau, Taipa, Macau. Electronic address:

Incomplete multi-view clustering which aims to solve the difficult clustering challenge on incomplete multi-view data collected from diverse domains with missing views has drawn considerable attention in recent years. In this paper, we propose a novel method, called consensus guided incomplete multi-view spectral clustering (CGIMVSC), to address the incomplete clustering problem. Specifically, CGIMVSC seeks to explore the local information within every single-view and the semantic consistent information shared by all views in a unified framework simultaneously, where the local structure is adaptively obtained from the incomplete data rather than pre-constructed via a k-nearest neighbor approach in the existing methods. Considering the semantic consistency of multiple views, CGIMVSC introduces a co-regularization constraint to minimize the disagreement between the common representation and the individual representations with respect to different views, such that all views will obtain a consensus clustering result. Experimental comparisons with some state-of-the-art methods on seven datasets validate the effectiveness of the proposed method on incomplete multi-view clustering.
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http://dx.doi.org/10.1016/j.neunet.2020.10.014DOI Listing
January 2021

Harmonization Shared Autoencoder Gaussian Process Latent Variable Model With Relaxed Hamming Distance.

IEEE Trans Neural Netw Learn Syst 2020 Oct 7;PP. Epub 2020 Oct 7.

Multiview learning has shown its superiority in visual classification compared with the single-view-based methods. Especially, due to the powerful representation capacity, the Gaussian process latent variable model (GPLVM)-based multiview approaches have achieved outstanding performances. However, most of them only follow the assumption that the shared latent variables can be generated from or projected to the multiple observations but fail to exploit the harmonization in the back constraint and adaptively learn a classifier according to these learned variables, which would result in performance degradation. To tackle these two issues, in this article, we propose a novel harmonization shared autoencoder GPLVM with a relaxed Hamming distance (HSAGP-RHD). Particularly, an autoencoder structure with the Gaussian process (GP) prior is first constructed to learn the shared latent variable for multiple views. To enforce the agreement among various views in the encoder, a harmonization constraint is embedded into the model by making consistency for the view-specific similarity. Furthermore, we also propose a novel discriminative prior, which is directly imposed on the latent variable to simultaneously learn the fused features and adaptive classifier in a unit model. In detail, the centroid matrix corresponding to the centroids of different categories is first obtained. A relaxed Hamming distance (RHD)-based measurement is subsequently presented to measure the similarity and dissimilarity between the latent variable and centroids, not only allowing us to get the closed-form solutions but also encouraging the points belonging to the same class to be close, while those belonging to different classes to be far. Due to this novel prior, the category of the out-of-sample is also allowed to be simply assigned in the testing phase. Experimental results conducted on three real-world data sets demonstrate the effectiveness of the proposed method compared with state-of-the-art approaches.
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http://dx.doi.org/10.1109/TNNLS.2020.3026876DOI Listing
October 2020

Electronic skins and machine learning for intelligent soft robots.

Sci Robot 2020 04 22;5(41). Epub 2020 Apr 22.

Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA, USA.

Soft robots have garnered interest for real-world applications because of their intrinsic safety embedded at the material level. These robots use deformable materials capable of shape and behavioral changes and allow conformable physical contact for manipulation. Yet, with the introduction of soft and stretchable materials to robotic systems comes a myriad of challenges for sensor integration, including multimodal sensing capable of stretching, embedment of high-resolution but large-area sensor arrays, and sensor fusion with an increasing volume of data. This Review explores the emerging confluence of e-skins and machine learning, with a focus on how roboticists can combine recent developments from the two fields to build autonomous, deployable soft robots, integrated with capabilities for informative touch and proprioception to stand up to the challenges of real-world environments.
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http://dx.doi.org/10.1126/scirobotics.aaz9239DOI Listing
April 2020

Coordination between root cell wall thickening and pectin modification is involved in cadmium accumulation in Sedum alfredii.

Environ Pollut 2021 Jan 18;268(Pt A):115665. Epub 2020 Sep 18.

Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China; Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou, 310058, China; National Demonstration Center for Experimental Environment and Resources Education, Zhejiang University, Hangzhou, 310058, China. Electronic address:

Root cell wall (RCW) modification is a widespread important defense strategy of plant to cope with trace metals. However, mechanisms underlying its remolding in cadmium (Cd) accumulation are still lacking in hyperaccumulators. In this study, changes of RCW structures and components between nonhyperaccumulating ecotype (NHE) and hyperaccumulating ecotype (HE) of Sedum alfredii were investigated simultaneously. Under 25 μM Cd treatment, RCW thickness of NHE is nearly 2 folds than that of HE and the thickened cell wall of NHE was enriched in low-methylated pectin, leading to more Cd trapped in roots tightly. In the opposite, large amounts of high-methylated pectin were assembled around RCW of HE with Cd supply, in this way, HE S. alfredii decreased its root fixation of Cd and enhanced Cd migration into xylem. TEM and AFM results further confirmed that thickened cell wall was caused by the increased amounts of cellulose and lignin while root tip lignification was resulted from variations of sinapyl (S) and guaiacyl (G) monomers. Overall, thickened cell wall and methylated pectin have synchronicity in spatial location of roots, and their coordination contributed to Cd accumulation in S. alfredii.
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http://dx.doi.org/10.1016/j.envpol.2020.115665DOI Listing
January 2021

Improved FBAM and GO/PO Method for EM Scattering Analyses of Ship Targets in a Marine Environment.

Sensors (Basel) 2020 Aug 21;20(17). Epub 2020 Aug 21.

School of Physics and Optoelectronic Engineering, Xidian University, Xi'an 710071, China.

The combination of the fact-based asymptotic method (FBAM) and the geometrical optics and physical optics (GO/PO) hybrid method is an effective way to analyze the electromagnetic (EM) scattering from electrically large ship targets in a marine environment because it takes the multiple scattering of the ship targets into consideration as well as the coupling scattering field between the targets and the sea surface. However, regarding an electrically large marine scene that contains a large target, the occlusion judgement process for calculating the multiple scattering field and the coupling field makes it inefficient. To solve this problem, this paper proposes a physical mechanism-based improved method to reduce the invalid occlusion judgment between different patches on the composite ship-ocean scene, and this operation enhances the computational efficiency significantly. With the proposed method, radar cross section (RCS) results of different targets and composite ship-ocean scenes were calculated and compared with the original FBAM and GO/PO method. Numerical results showed that the proposed method had higher efficiency compared with the original method with the same good accuracy. In addition, synthetic aperture radar (SAR) images of a composite ship-ocean scene with different radar parameters and sea conditions were simulated with the proposed method for detection purpose. Finally, the proposed method was used to analyze the EM scattering characteristic of a marine environment with multiple ships.
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http://dx.doi.org/10.3390/s20174735DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506916PMC
August 2020

PEARL-seq: A Photoaffinity Platform for the Analysis of Small Molecule-RNA Interactions.

ACS Chem Biol 2020 09 17;15(9):2374-2381. Epub 2020 Aug 17.

Arrakis Therapeutics, 830 Winter Street, Waltham, Massachusetts, United States.

RNA is emerging as a valuable target for the development of novel therapeutic agents. The rational design of RNA-targeting small molecules, however, has been hampered by the relative lack of methods for the analysis of small molecule-RNA interactions. Here, we present our efforts to develop such a platform using photoaffinity labeling. This technique, termed hotoaffinity vluation of NA igation-uencing (PEARL-seq), enables the rapid identification of small molecule binding locations within their RNA targets and can provide information on ligand selectivity across multiple different RNAs. These data, when supplemented with small molecule SAR data and RNA probing data enable the construction of a computational model of the RNA-ligand structure, thereby enabling the rational design of novel RNA-targeted ligands.
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http://dx.doi.org/10.1021/acschembio.0c00357DOI Listing
September 2020

A comparative study of root cadmium radial transport in seedlings of two wheat (Triticum aestivum L.) genotypes differing in grain cadmium accumulation.

Environ Pollut 2020 Nov 17;266(Pt 3):115235. Epub 2020 Jul 17.

Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China; National Demonstration Center for Experimental Environment and Resources Education, Zhejiang University, Hangzhou, 310058, China. Electronic address:

The radial transport of cadmium (Cd) is essential for Cd influx in roots. The role of radial transport pathway on the Cd translocation from root to shoot among wheat genotypes are still poorly understood. This study explored the role of apoplastic and symplastic pathway on root Cd uptake and root-to-shoot translocation in Zhenmai 10 (ZM10, high Cd in grains) and Aikang 58 (AK58, low Cd in grains). Under Cd treatment, the deposition of Casparian strips (CSs) and suberin lamellae (SL) initiated closer to the root apex in ZM10 than that in AK58, which resulted in the lower Cd concentration in apoplastic fluid of ZM10. Simultaneously, Cd-induced expression levels of genes related to Cd uptake in roots were significantly higher in AK58 by contrast with ZM10, contributing to the symplastic Cd accumulation in AK58 root. Moreover, the addition of metabolic inhibitor CCCP noticeably decreased the Cd accumulation in root of both genotypes. Intriguingly, compared to ZM10, greater amounts of Cd were sequestrated in the cell walls and vacuoles in roots of AK58, limiting the translocation of Cd from root to shoot. Furthermore, the elevated TaHMA2 expression in ZM10 indicates that ZM10 had a higher capacity of xylem loading Cd than AK58. All of these results herein suggest that the radial transport is significant for Cd accumulation in roots, but it cannot explain the difference in root-to-shoot translocation of Cd in wheat genotypes with contrast Cd accumulation in grains.
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http://dx.doi.org/10.1016/j.envpol.2020.115235DOI Listing
November 2020

Inhibition of transition metals dissolution in cobalt-free cathode with ultrathin robust interphase in concentrated electrolyte.

Nat Commun 2020 Jul 20;11(1):3629. Epub 2020 Jul 20.

Key Laboratory of Organic Optoelectronics and Molecular Engineering, Department of Chemistry, Tsinghua University, 100084, Beijing, China.

The low Coulombic efficiency during cycling hinders the application of Cobalt-free lithium-rich materials in lithium-ion batteries. Here we demonstrated that the dissolution of iron, rather than traditionally acknowledged manganese, is mainly responsible for the low Coulombic efficiency of the iron-substituted cobalt-free lithium-rich material. Besides, we presented an approach to inhibit the dissolution of transition metal ions by using concentrated electrolytes. We found that the cathode electrolyte interphase (CEI) layer formed in the concentrated electrolyte is a uniform and robust LiF-rich CEI, which is a sharp contrast with the uneven and fragile organic-rich CEI formed in the dilute electrolyte. The LiF-rich CEI not only effectively inhibits the dissolution of TMs but also stabilizes the cathode structure. The Coulombic efficiency, cycling stability, rate performance, and safety of the Fe-substituted cobalt-free lithium-rich cathode material in the concentrated electrolyte have been improved tremendously.
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http://dx.doi.org/10.1038/s41467-020-17396-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371675PMC
July 2020

Intrinsically stretchable electrode array enabled in vivo electrophysiological mapping of atrial fibrillation at cellular resolution.

Proc Natl Acad Sci U S A 2020 06 15;117(26):14769-14778. Epub 2020 Jun 15.

Department of Chemical Engineering, Stanford University, Stanford, CA 94305;

Electrophysiological mapping of chronic atrial fibrillation (AF) at high throughput and high resolution is critical for understanding its underlying mechanism and guiding definitive treatment such as cardiac ablation, but current electrophysiological tools are limited by either low spatial resolution or electromechanical uncoupling of the beating heart. To overcome this limitation, we herein introduce a scalable method for fabricating a tissue-like, high-density, fully elastic electrode (elastrode) array capable of achieving real-time, stable, cellular level-resolution electrophysiological mapping in vivo. Testing with acute rabbit and porcine models, the device is proven to have robust and intimate tissue coupling while maintaining its chemical, mechanical, and electrical properties during the cardiac cycle. The elastrode array records epicardial atrial signals with comparable efficacy to currently available endocardial-mapping techniques but with 2 times higher atrial-to-ventricular signal ratio and >100 times higher spatial resolution and can reliably identify electrical local heterogeneity within an area of simultaneously identified rotor-like electrical patterns in a porcine model of chronic AF.
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http://dx.doi.org/10.1073/pnas.2000207117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334471PMC
June 2020

Growth and Photosynthetic Inhibition of Cerium Oxide Nanoparticles on Soybean (Glycine max).

Bull Environ Contam Toxicol 2020 Jul 28;105(1):119-126. Epub 2020 May 28.

Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.

Cerium oxide nanoparticles (CeO NPs) are widely used in industries and have caused environmental problems. However, the phytotoxicity induced by CeO NPs lacks detailed information on phytotoxicity. In this research, the effect of CeO NPs on soybean plants (Glycine max) was studied. Scanning electron microscopy with the energy dispersion spectroscopy was used to characterize the NPs form in soybean. The growth of the root was increased, whereas the growth of shoot was inhibited. Besides, Chlorophyll Fluorescence Imager (CF Imager) showed that chlorophyll synthesis was inhibited: the maximum quantum yield of Photosystem II complex (PSII) (Fv/Fm) and photochemical quenching (qP) decreased. Moreover, transmission electron microscopy revealed that the chloroplast thylakoid structure was changed, and thus reduced the energy conversion in the Calvin cycle from C5 to C3. Our work suggests that CeO NPs will cause growth changes as well as irreversible damage to soybean plants. Our findings will provide evidence for estimation of plant toxicity induced by CeO NPs.
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http://dx.doi.org/10.1007/s00128-020-02892-zDOI Listing
July 2020

Author Correction: Morphing electronics enable neuromodulation in growing tissue.

Nat Biotechnol 2020 Sep;38(9):1097

Department of Chemical Engineering, Stanford University, Stanford, CA, USA.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41587-020-0533-0DOI Listing
September 2020

Morphing electronics enable neuromodulation in growing tissue.

Nat Biotechnol 2020 09 20;38(9):1031-1036. Epub 2020 Apr 20.

Department of Chemical Engineering, Stanford University, Stanford, CA, USA.

Bioelectronics for modulating the nervous system have shown promise in treating neurological diseases. However, their fixed dimensions cannot accommodate rapid tissue growth and may impair development. For infants, children and adolescents, once implanted devices are outgrown, additional surgeries are often needed for device replacement, leading to repeated interventions and complications. Here, we address this limitation with morphing electronics, which adapt to in vivo nerve tissue growth with minimal mechanical constraint. We design and fabricate multilayered morphing electronics, consisting of viscoplastic electrodes and a strain sensor that eliminate the stress at the interface between the electronics and growing tissue. The ability of morphing electronics to self-heal during implantation surgery allows a reconfigurable and seamless neural interface. During the fastest growth period in rats, morphing electronics caused minimal damage to the rat nerve, which grows 2.4-fold in diameter, and allowed chronic electrical stimulation and monitoring for 2 months without disruption of functional behavior. Morphing electronics offers a path toward growth-adaptive pediatric electronic medicine.
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http://dx.doi.org/10.1038/s41587-020-0495-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805559PMC
September 2020

Multiscale Conditional Regularization for Convolutional Neural Networks.

IEEE Trans Cybern 2020 Apr 2. Epub 2020 Apr 2.

With the increased model size of convolutional neural networks (CNNs), overfitting has become the main bottleneck to further improve the performance of networks. Currently, the weighting regularization methods have been proposed to address the overfitting problem and they perform satisfactorily. Since these regularization methods cannot be used in all the networks and they are usually not flexible enough in different phases of the training and test processes, this article proposes a multiscale conditional (MSC) regularization method. MSC divides the intermediate features into different scales and then generates new data for each scale features, respectively. In addition, the new data are generated by employing the information from two conditions: 1) each sample feature and 2) each layer pattern. Finally, a self-identity structure is proposed to supplement the features with the generated data. Therefore, MSC can adaptively and efficiently generate much finer and individualized data to make the entire regularization more flexible. Furthermore, MSC is more general and can be applied to all kinds of networks through the proposed self-identity structure. The experimental results on all the benchmark datasets showed that the proposed MSC regularization method achieves the best performances in all the networks.
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http://dx.doi.org/10.1109/TCYB.2020.2979968DOI Listing
April 2020

Small-Scale Propellers Deliver Miniature Versions of Themselves.

Small 2020 04 3;16(17):e2000453. Epub 2020 Apr 3.

Department of Nanoengineering, University of California, La Jolla, San Diego, CA, 92093, USA.

Small-scale actuators and propellers have benefited from advances in materials and manufacturing to become more lifelike. Inspired by animal species, multi-generational chemically powered artificial propellers that carry small versions of themselves and deliver them "on-the-fly" are described. The released replicas are capable of autonomous propulsion and propelling immediately after detachment. Release occurs without human involvement and relies solely on sacrificial layers separating the carriers and replicas. These layers are composed of transient natural polymers, which dissolve under the swimming conditions to release the confined replicas. Judicious selection of the responsive transient materials, layer thickness, and solution conditions (e.g., pH), leads to programmable delivery of the replicas. Finally, the ability of the same carrier propellers to carry and transport multiple generations of propellers and deliver them at predetermined times is demonstrated.
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http://dx.doi.org/10.1002/smll.202000453DOI Listing
April 2020

Preparation and Characterization of Condensed Tannin Non-Isocyanate Polyurethane (NIPU) Rigid Foams by Ambient Temperature Blowing.

Polymers (Basel) 2020 Mar 30;12(4). Epub 2020 Mar 30.

Yunnan key laboratory of wood adhesives and glue products, Southwest Forestry University, Kunming 650224, China.

Ambient temperature self-blowing mimosa tannin-based non-isocyanate polyurethane (NIPU) rigid foam was produced, based on a formulation of tannin-based non-isocyanate polyurethane (NIPU) resin. A citric acid and glutaraldehyde mixture served as a blowing agent used to provide foaming energy and cross-link the tannin-derived products to synthesize the NIPU foams. Series of tannin-based NIPU foams containing a different amount of citric acid and glutaraldehyde were prepared. The reaction mechanism of tannin-based NIPU foams were investigated by Fourier Trasform InfraRed (FT-IR), Matrix Assisted Laser Desorption Ionization (MALDI-TOF) mass spectrometry, and C Nuclear Magnetic Resonance (C NMR). The results indicated that urethane linkages were formed. The Tannin-based NIPU foams morphology including physical and mechanical properties were characterized by mechanical compression, by scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). All the foams prepared showed a similar open-cell morphology. Nevertheless, the number of cell-wall pores decreased with increasing additions of glutaraldehyde, while bigger foam cells were obtained with increasing additions of citric acid. The compressive mechanical properties improved with the higher level of crosslinking at the higher amount of glutaraldehyde. Moreover, the TGA results showed that the tannin-based NIPU foams prepared had similar thermal stability, although one of them (T-Fs-7) presented the highest char production and residual matter, approaching 18.7% at 790 °C.
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http://dx.doi.org/10.3390/polym12040750DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7240429PMC
March 2020

Low calcium-induced delay in development of root apoplastic barriers enhances Cd uptake and accumulation in Sedum alfredii.

Sci Total Environ 2020 Jun 7;723:137810. Epub 2020 Mar 7.

Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; National Demonstration Center for Experimental Environment and Resources Education, Zhejiang University, Hangzhou 310058, China. Electronic address:

Mineral nutrients play an important role in heavy metal uptake and accumulation in plant. However, the effects of calcium (Ca) supply level on apoplastic transport in roots and consequences for uptake of cadmium (Cd) in hyperaccumulators are poorly understood. Here, we investigated how Ca regulated the development of apoplastic barriers in the roots of two ecotypes of Sedum alfredii and assessed its effects on Cd uptake. Results of correlation analysis indicated that Ca content was positively correlated with the development of Casparian strips (CSs) and suberin lamellae (SL) in the absence or presence of Cd. Simultaneously, low Ca supply was proven to delay the formation of endodermis CSs and suberin accumulation by decreasing the relative expressions of genes associated with CSs localization and lignin/suberin synthesis. Moreover, Cd in apoplastic fluid and cell walls (regarding the apoplastic transport) and symplastic fractions were elevated by low Ca supply. Contrary to high Ca supply, the expression levels of genes related to Cd influx and xylem loading were increased upon low Ca addition in roots of both ecotypes. All the results above suggested that low Ca supply promotes root Cd uptake via apoplastic pathway by delaying apoplastic barriers development and also regulating Cd transport to the xylem in S. alfredii.
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http://dx.doi.org/10.1016/j.scitotenv.2020.137810DOI Listing
June 2020

DRPL: Deep Regression Pair Learning For Multi-Focus Image Fusion.

IEEE Trans Image Process 2020 Mar 2. Epub 2020 Mar 2.

In this paper, a novel deep network is proposed for multi-focus image fusion, named Deep Regression Pair Learning (DRPL). In contrast to existing deep fusion methods which divide the input image into small patches and apply a classifier to judge whether the patch is in focus or not, DRPL directly converts the whole image into a binary mask without any patch operation, subsequently tackling the difficulty of the blur level estimation around the focused/defocused boundary. Simultaneously, a pair learning strategy, which takes a pair of complementary source images as inputs and generates two corresponding binary masks, is introduced into the model, greatly imposing the complementary constraint on each pair and making a large contribution to the performance improvement. Furthermore, as the edge or gradient does exist in the focus part while there is no similar property for the defocus part, we also embed a gradient loss to ensure the generated image to be all-in-focus. Then the structural similarity index (SSIM) is utilized to make a trade-off between the reference and fused images. Experimental results conducted on the synthetic and real-world datasets substantiate the effectiveness and superiority of DRPL compared with other state-of-the-art approaches. The testing code can be found in https://github.com/sasky1/DPRL.
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http://dx.doi.org/10.1109/TIP.2020.2976190DOI Listing
March 2020

Effective removal of inorganic and organic heavy metal pollutants with poly(amino acid)-based micromotors.

Nanoscale 2020 Feb;12(8):5227-5232

College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Institute of Molecular and Nano Science, Shandong Normal University, Jinan 250014, P. R. China.

The increasing extent of heavy metal pollution all over the world has resulted in many serious environmental and public health problems. To solve these problems, effective technologies for water treatment are urgently needed. Recent efforts have focused on the development of self-driven micro/nanomotors for eliminating inorganic and organic pollutants in an aqueous system. These synthetic micro/nanomotors can increase mass transfer through the transportation of reactive species, leading to higher decontamination rates. Here, we report a surface-tunable poly(amino acid) (PAA)-based micromotor. The property of the outer layer can be adjusted by changing the type and proportion of amino acids according to real requirements. Three kinds of micromotors are fabricated, which consist of a microtube composed of PAAs (i.e., polyaspartic acid (PAsp), polycysteine (PCys) or a copolymer of both (PAsp-Cys)), a thin Ni intermediate layer, and a Pt inner layer. Due to the presence of various side-chain functional groups (e.g., amino, carboxyl, and sulfhydryl) on the surface of the poly(amino acid)s, these micromotors can be used as effective scavengers for the removal of heavy metals (i.e., Cd2+, Pb2+ and methylmercury). Compared with PAsp and PCys micromotors, the PAsp-Cys micromotor shows good acid resistance and can simultaneously adsorb various kinds of heavy metals with high removal efficiency. The outer layer of the surface-tunable micromotor has good biocompatibility and adsorption efficiency, which holds considerable promise for environmental and biomedical applications.
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http://dx.doi.org/10.1039/c9nr09813eDOI Listing
February 2020

A slipped-CAG DNA-binding small molecule induces trinucleotide-repeat contractions in vivo.

Nat Genet 2020 02 14;52(2):146-159. Epub 2020 Feb 14.

Department of Regulatory Bioorganic Chemistry, The Institute of Scientific and Industrial Research, Osaka University, Osaka, Japan.

In many repeat diseases, such as Huntington's disease (HD), ongoing repeat expansions in affected tissues contribute to disease onset, progression and severity. Inducing contractions of expanded repeats by exogenous agents is not yet possible. Traditional approaches would target proteins driving repeat mutations. Here we report a compound, naphthyridine-azaquinolone (NA), that specifically binds slipped-CAG DNA intermediates of expansion mutations, a previously unsuspected target. NA efficiently induces repeat contractions in HD patient cells as well as en masse contractions in medium spiny neurons of HD mouse striatum. Contractions are specific for the expanded allele, independently of DNA replication, require transcription across the coding CTG strand and arise by blocking repair of CAG slip-outs. NA-induced contractions depend on active expansions driven by MutSβ. NA injections in HD mouse striatum reduce mutant HTT protein aggregates, a biomarker of HD pathogenesis and severity. Repeat-structure-specific DNA ligands are a novel avenue to contract expanded repeats.
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http://dx.doi.org/10.1038/s41588-019-0575-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043212PMC
February 2020

The Brπ halogen bond assisted self-assembly of an asymmetric molecule regulated by concentration.

Chem Commun (Camb) 2020 Mar 5;56(18):2727-2730. Epub 2020 Feb 5.

College of Materials Science and Engineering, South China University of Technology, Guangzhou 510640, People's Republic of China.

The two-dimensional (2D) self-assembly behavior of an asymmetric thienophenanthrene derivative (M1) has been theoretically predicted and further probed via STM. The barely exploited Brπ halogen bonds play an assisting role in the structural formation, and a strong cooperative effect from the C-HBr bonds is shown. Such π-type halogen bond assisted self-assembly reveals self-adaption properties, which is of great interest for flexible light-emitting devices and self-healing materials.
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http://dx.doi.org/10.1039/c9cc08898aDOI Listing
March 2020

Label Co-Occurrence Learning With Graph Convolutional Networks for Multi-Label Chest X-Ray Image Classification.

IEEE J Biomed Health Inform 2020 08 16;24(8):2292-2302. Epub 2020 Jan 16.

Existing multi-label medical image learning tasks generally contain rich relationship information among pathologies such as label co-occurrence and interdependency, which is of great importance for assisting in clinical diagnosis and can be represented as the graph-structured data. However, most state-of-the-art works only focus on regression from the input to the binary labels, failing to make full use of such valuable graph-structured information due to the complexity of graph data. In this paper, we propose a novel label co-occurrence learning framework based on Graph Convolution Networks (GCNs) to explicitly explore the dependencies between pathologies for the multi-label chest X-ray (CXR) image classification task, which we term the "CheXGCN". Specifically, the proposed CheXGCN consists of two modules, i.e., the image feature embedding (IFE) module and label co-occurrence learning (LCL) module. Thanks to the LCL model, the relationship between pathologies is generalized into a set of classifier scores by introducing the word embedding of pathologies and multi-layer graph information propagation. During end-to-end training, it can be flexibly integrated into the IFE module and then adaptively recalibrate multi-label outputs with these scores. Extensive experiments on the ChestX-Ray14 and CheXpert datasets have demonstrated the effectiveness of CheXGCN as compared with the state-of-the-art baselines.
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http://dx.doi.org/10.1109/JBHI.2020.2967084DOI Listing
August 2020

Relaxed Asymmetric Deep Hashing Learning: Point-to-Angle Matching.

IEEE Trans Neural Netw Learn Syst 2020 Nov 29;31(11):4791-4805. Epub 2020 Oct 29.

Due to the powerful capability of the data representation, deep learning has achieved a remarkable performance in supervised hash function learning. However, most of the existing hashing methods focus on point-to-point matching that is too strict and unnecessary. In this article, we propose a novel deep supervised hashing method by relaxing the matching between each pair of instances to a point-to-angle way. Specifically, an inner product is introduced to asymmetrically measure the similarity and dissimilarity between the real-valued output and the binary code. Different from existing methods that strictly enforce each element in the real-valued output to be either +1 or -1, we only encourage the output to be close to its corresponding semantic-related binary code under the cross-angle. This asymmetric product not only projects both the real-valued output and the binary code into the same Hamming space but also relaxes the output with wider choices. To further exploit the semantic affinity, we propose a novel Hamming-distance-based triplet loss, efficiently making a ranking for the positive and negative pairs. An algorithm is then designed to alternatively achieve optimal deep features and binary codes. Experiments on four real-world data sets demonstrate the effectiveness and superiority of our approach to the state of the art.
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http://dx.doi.org/10.1109/TNNLS.2019.2958061DOI Listing
November 2020