Endophytic Enterobacter sp. YG-14 mediated arsenic mobilization through siderophore and its role in enhancing phytostabilization.

Soil arsenic (As) phytoremediation has long faced the challenge of efficiently absorbing As by plant accumulators while maintaining their health and fast growth. Even at low doses, arsenic is highly toxic to plants. Therefore, plant growth-promoting microorganisms that can mediate As accumulation in plants are of great interest. In this study, the endophyte Enterobacter sp. YG-14 (YG-14) was found to have soil mobilization activity. By constructing a siderophore synthesis gene deletion mutant (ΔentD) of YG-14, the endophyte was confirmed to effectively mobilize Fe-As complexes in mining soil by secreting enterobactin, releasing bioavailable Fe and As to the rhizosphere. YG-14 also enhances As accumulation in host plants via extracellular polymer adsorption and specific phosphatase transfer protein (PitA) absorption. The root accumulation of As was positively correlated with YG-14 root colonization. In addition, YG-14 promoted plant growth and alleviated oxidative damage in R. pseudoacacia L. under arsenic stress. This is the first study, from phenotype, physiology, and molecular perspectives, to determine the role of endophyte in promoting As phytostabilization and maintaining the growth of the host plant. This demonstrated the feasibility of using endophytes with high siderophore production to assist host plants in As phytoremediation.

Role of hierarchy structure on the mechanical adaptation of self-healing hydrogels under cyclic stretching.

Soft materials with mechanical adaptability have substantial potential for various applications in tissue engineering. Gaining a deep understanding of the structural evolution and adaptation dynamics of soft materials subjected to cyclic stretching gives insight into developing mechanically adaptive materials. Here, we investigate the effect of hierarchy structure on the mechanical adaptation of self-healing hydrogels under cyclic stretching training. A polyampholyte hydrogel, composed of hierarchical structures including ionic bonds, transient and permanent polymer networks, and bicontinuous hard/soft-phase networks, is adopted as a model. Conditions for effective training, mild overtraining, and fatal overtraining are demonstrated in soft materials. We further reveal that mesoscale hard/soft-phase networks dominate the long-term memory effect of training and play a crucial role in the asymmetric dynamics of compliance changes and the symmetric dynamics of hydrogel shape evolution. Our findings provide insights into the design of hierarchical structures for adaptive soft materials.

Tuning 3D refractive indices via constrained uniaxial stretch in cellulose triacetate films plasticized with triethyl citrate.

Tuning 3D refractive indices of polymers is urgently needed for optical films, but it is quite challenging. Here, we proposed a simple constrained uniaxial stretch method that successfully tuned the 3D refractive indices in cellulose triacetate (TAC) films plasticized with triethyl citrate (TEC). Our results suggest that, under constrained uniaxial stretch, the main chains and side groups prefer to orientate in the stretch direction and the constrained direction, respectively. Such a unique chain arrangement differentiates the refractive indices in three directions of the film. The branched small molecule TEC is also crucial for tuning refractive indices, which promotes chain activity and enhances the chain orientation under stretching, leading to a considerable change in refractive indices before samples fracture. The polymer film we fabricated possesses a direction-dependent optical performance, where the refractive index in the film thickness direction is between that of the stretch direction and constrained direction. This work provides a fundamental understanding on the chain structure and optical performance of polymer films. The constrained uniaxial stretch method, in general, should also be applicable to tuning other 3D physical properties through tuning the direction-dependent orientation of polymers.

Bond Orientation-Determined Enthalpic Stress in Polymer Glasses upon Deformation.

The mechanical properties of polymer glass are determined by both intermolecular local packing structures and aligned intrachain configurations. These configurations involve multiple space scales, and the underlying mechanism is not well understood yet. By applying mechanical stimulation to cold-drawn polymer glasses, the present simulation work shows a one-to-one correspondence between arising retractive stress and the segment orientation parameter on the length scale of the intrachain connecting bond. Such retractive stress is a newly produced enthalpic stress when segment orientation on the length scale of bonds and particle mobility coexist. This reveals a potential mechanism of how the intrachain orientation on the length scale of bonds influences the mechanical behaviors of polymer glasses.

Multiscale Relaxation Behavior of Amorphous Plasticized Poly(vinyl butyral).

As a key component in laminated glass, plasticized polyvinyl butyral (PVB) interlayer is a kind of impact-resistant polymer material with high toughness. Recently, by using ultrasmall angle X-ray scattering (USAXS) technique, Stretch-induced phase-separated structure on the scale of hundreds of nanometers formed in plasticized PVB for the first time is reported. In this work, the multiscale relaxation behavior of plasticized PVB is further investigated. The relaxation behavior of deformed plasticized PVB is studied from macroscopic stress, mesoscopic phase-separated structure, and microscopic chain segment by combining USAXS, and birefringence with in situ stretching device. The contributions of chain segments and hydrogen bonding clusters for the multiscale relaxation behavior are discussed.

The Rice Endophyte-Derived α-Mannosidase ShAM1 Degrades Host Cell Walls To Activate DAMP-Triggered Immunity against Disease.

Endophytes play an important role in shaping plant growth and immunity. However, the mechanisms for endophyte-induced disease resistance in host plants remain unclear. Here, we screened and isolated the immunity inducer ShAM1 from the endophyte Streptomyces hygroscopicus OsiSh-2, which strongly antagonizes the pathogen Magnaporthe oryzae. Recombinant ShAM1 can trigger rice immune responses and induce hypersensitive responses in various plant species. After infection with M. oryzae, blast resistance was dramatically improved in ShAM1-inoculated rice. In addition, the enhanced disease resistance by ShAM1 was found to occur through a priming strategy and was mainly regulated through the jasmonic acid-ethylene (JA/ET)-dependent signaling pathway. ShAM1 was identified as a novel α-mannosidase, and its induction of immunity is dependent on its enzyme activity. When we incubated ShAM1 with isolated rice cell walls, the release of oligosaccharides was observed. Notably, extracts from the ShAM1-digested cell wall can enhance the disease resistance of the host rice. These results indicated that ShAM1 triggered immune defense against pathogens by damage-associated molecular pattern (DAMP)-related mechanisms. Our work provides a representative example of endophyte-mediated modulation of disease resistance in host plants. The effects of ShAM1 indicate the promise of using active components from endophytes as plant defense elicitors for the management of plant disease. IMPORTANCE The specific biological niche inside host plants allows endophytes to regulate plant disease resistance effectively. However, there have been few reports on the role of active metabolites from endophytes in inducing host disease resistance. In this study, we demonstrated that an identified α-mannosidase protein, ShAM1, secreted by the endophyte S. hygroscopicus OsiSh-2 could activate typical plant immunity responses and induce a timely and cost-efficient priming defense against the pathogen M. oryzae in rice. Importantly, we revealed that ShAM1 enhanced plant disease resistance through its hydrolytic enzyme (HE) activity to digest the rice cell wall and release damage-associated molecular patterns. Taken together, these findings provide an example of the interaction mode of endophyte-plant symbionts and suggest that HEs derived from endophytes can be used as environmentally friendly and safe prevention agent for plant disease control.

Multi-omics joint analysis reveals how Streptomyces albidoflavus OsiLf-2 assists Camellia oleifera to resist drought stress and improve fruit quality.

Camellia oleifera (C. oleifera) is a unique edible oil crop in China cultivated in the hilly southern mountains. Although C. oleifera is classified as a drought-tolerant tree species, drought remains the main factor limiting the growth of C. oleifera in summer and autumn. Using endophytes to improve crop drought tolerance is one effective strategy to meet our growing food crop demand. In this study, we showed that endophyte Streptomyces albidoflavus OsiLf-2 could mitigate the negative impact of drought stress on C. oleifera, thus improving seed, oil, and fruit quality. Microbiome analysis revealed that OsiLf-2 treatment significantly affected the microbial community structure in the rhizosphere soil of C. oleifera, decreasing both the diversity and abundance of the soil microbe. Likewise, transcriptome and metabolome analyses found that OsiLf-2 protected plant cells from drought stress by reducing root cell water loss and synthesizing osmoregulatory substances, polysaccharides, and sugar alcohols in roots. Moreover, we observed that OsiLf-2 could induce the host to resist drought stress by increasing its peroxidase activity and synthesizing antioxidants such as cysteine. A multi-omics joint analysis of microbiomes, transcriptomes, and metabolomes revealed OsiLf-2 assists C. oleifera in resisting drought stress. This study provides theoretical and technical support for future research on endophytes application to enhance the drought resistance, yield, and quality of C. oleifera.

A versatile biaxial stretching device for in situ synchrotron radiation small- and wide-angle x-ray scattering measurements of polymer films.

A biaxial stretching device is designed and developed for the real-time structural measurements of polymer films. This device adopts a vertical layout to perform real-time x-ray scattering measurements. It has a maximum stretching ratio of 8 × 8 in two perpendicular directions. Its maximum experimental temperature and stretching rate are 250 °C and 100 mm/s, respectively. The control accuracies of the experimental temperature and stretching rate are ±1 °C and 0.01 mm, respectively. All the parameters related to film biaxial processing, such as stretching speed, stretching ratio, and temperature, can be independently set. The device feasibility is demonstrated via a real-time experiment in a synchrotron radiation beamline. Wide-angle x-ray diffraction, small-angle x-ray scattering, and stress-strain data can be simultaneously obtained during various stretching modes. The proposed device fills the gap between the synchrotron radiation x-ray scattering technique and the biaxial stretching processing of polymer films. This device will play an important role in improving the understanding of the physics behind biaxial polymer processing.

Force-triggered rapid microstructure growth on hydrogel surface for on-demand functions.

Living organisms share the ability to grow various microstructures on their surface to achieve functions. Here we present a force stamp method to grow microstructures on the surface of hydrogels based on a force-triggered polymerisation mechanism of double-network hydrogels. This method allows fast spatial modulation of the morphology and chemistry of the hydrogel surface within seconds for on-demand functions. We demonstrate the oriented growth of cells and directional transportation of water droplets on the engineered hydrogel surfaces. This force-triggered method to chemically engineer the hydrogel surfaces provides a new tool in addition to the conventional methods using light or heat, and will promote the wide application of hydrogels in various fields.

Mechanism of temperature-induced asymmetric swelling and shrinking kinetics in self-healing hydrogels.

Understanding the physical principle that governs the stimuli-induced swelling and shrinking kinetics of hydrogels is indispensable for their applications. Here, we show that the shrinking and swelling kinetics of self-healing hydrogels could be intrinsically asymmetric. The structure frustration, formed by the large difference in the heat and solvent diffusions, remarkably slows down the shrinking kinetics. The plateau modulus of viscoelastic gels is found to be a key parameter governing the formation of structure frustration and, in turn, the asymmetric swelling and shrinking kinetics. This work provides fundamental understandings on the temperature-triggered transient structure formation in self-healing hydrogels. Our findings will find broad use in diverse applications of self-healing hydrogels, where cooperative diffusion of water and gel network is involved. Our findings should also give insight into the molecular diffusion in biological systems that possess macromolecular crowding environments similar to self-healing hydrogels.

Deep residual-SVD network for brain image registration.

Objective.Medical image registration aims to find the deformation field that can align two images in a spatial position. A medical image registration method based on U-Net architecture has been proposed currently. However, U-Net architecture has few training parameters, which leads to weak learning ability, and it ignores the adverse effects of image noise on the registration accuracy. The article aims at addressing the problem of weak network learning ability and the adverse effects of noisy images on registration.Approach.Here we propose a novel unsupervised 3D brain image registration framework, which introduces the residual unit and singular value decomposition (SVD) denoising layer on the U-Net architecture. Residual unit solves the problem of network degradation, that is, registration accuracy becomes saturated and then degrades rapidly with the increase in network depth. SVD denoising layer uses the estimated model order for SVD-based low-rank image reconstruction. we use Akaike information criterion to estimate the appropriate model order, which is used to remove noise components. We use the exponential linear unit (ELU) as the activation function, which is more robust to noise than other peers.Main results.The proposed method is evaluated on the publicly available brain MRI datasets: Mindboggle101 and LPBA40. Experimental results demonstrate our method outperforms several state-of-the-art methods for the metric of Dice Score. The mean number of folding voxels and registration time are comparable to state-of-the-art methods.Significance.This study shows that Deep Residual-SVD Network can improve registration accuracy. This study also demonstrate that the residual unit can enhance the learning ability of the network, the SVD denoising layer can denoise effectively, and the ELU is more robust to noise.

Polymer crystallization under external flow.

The general aspects of polymer crystallization under external flow, i.e., flow-induced crystallization (FIC) from fundamental theoretical background to multi-scale characterization and modeling results are presented. FIC is crucial for modern polymer processing, such as blowing, casting, and injection modeling, as two-third of daily-used polymers is crystalline, and nearly all of them need to be processed before final applications. For academics, the FIC is intrinsically far from equilibrium, where the polymer crystallization behavior is different from that in quiescent conditions. The continuous investigation of crystallization contributes to a better understanding on the general non-equilibrium ordering in condensed physics. In the current review, the general theories related to polymer nucleation under flow (FIN) were summarized first as a preliminary knowledge. Various theories and models, i.e., coil-stretch transition and entropy reduction model, are briefly presented together with the modified versions. Subsequently, the multi-step ordering process of FIC is discussed in detail, including chain extension, conformational ordering, density fluctuation, and final perfection of the polymer crystalline. These achievements for a thorough understanding of the fundamental basis of FIC benefit from the development of various hyphenated rheometer, i.e., rheo-optical spectroscopy, rheo-IR, and rheo-x-ray scattering. The selected experimental results are introduced to present efforts on elucidating the multi-step and hierarchical structure transition during FIC. Then, the multi-scale modeling methods are summarized, including micro/meso scale simulation and macroscopic continuum modeling. At last, we briefly describe our personal opinions related to the future directions of this field, aiming to ultimately establish the unified theory of FIC and promote building of the more applicable models in the polymer processing.

Bayesian Fully Convolutional Networks for Brain Image Registration.

The purpose of medical image registration is to find geometric transformations that align two medical images so that the corresponding voxels on two images are spatially consistent. Nonrigid medical image registration is a key step in medical image processing, such as image comparison, data fusion, target recognition, and pathological change analysis. Existing registration methods only consider registration accuracy but largely neglect the uncertainty of registration results. In this work, a method based on the Bayesian fully convolutional neural network is proposed for nonrigid medical image registration. The proposed method can generate a geometric uncertainty map to calculate the uncertainty of registration results. This uncertainty can be interpreted as a confidence interval, which is essential for judging whether the source data are abnormal. Moreover, the proposed method introduces group normalization, which is conducive to the network convergence of the Bayesian neural network. Some representative learning-based image registration methods are compared with the proposed method on different image datasets. Experimental results show that the registration accuracy of the proposed method is better than that of the methods, and its antifolding performance is comparable to that of fast image registration and VoxelMorph. Furthermore, the proposed method can evaluate the uncertainty of registration results.

Effect of mesoscale phase contrast on fatigue-delaying behavior of self-healing hydrogels.

We investigate the fatigue resistance of chemically cross-linked polyampholyte hydrogels with a hierarchical structure due to phase separation and find that the details of the structure, as characterized by SAXS, control the mechanisms of crack propagation. When gels exhibit a strong phase contrast and a low cross-linking level, the stress singularity around the crack tip is gradually eliminated with increasing fatigue cycles and this suppresses crack growth, beneficial for high fatigue resistance. On the contrary, the stress concentration persists in weakly phase-separated gels, resulting in low fatigue resistance. A material parameter, λtran, is identified, correlated to the onset of non-affine deformation of the mesophase structure in a hydrogel without crack, which governs the slow-to-fast transition in fatigue crack growth. The detailed role played by the mesoscale structure on fatigue resistance provides design principles for developing self-healing, tough, and fatigue-resistant soft materials.

Constitutive modeling of strain-dependent bond breaking and healing kinetics of chemical polyampholyte (PA) gel.

A finite strain nonlinear viscoelastic constitutive model is used to study the uniaxial tension behaviour of chemical polyampholyte (PA) gel. This PA gel is cross-linked by chemical and physical bonds. Our constitutive model attempts to capture the time and strain dependent breaking and healing kinetics of physical bonds. We compare model prediction by uniaxial tension, cyclic and relaxation tests. Material parameters in our model are obtained by least squares optimization. These parameters gave fits that are in good agreement with the experiments.

Molecular mechanism of abnormally large nonsoftening deformation in a tough hydrogel.

Tough soft materials usually show strain softening and inelastic deformation. Here, we study the molecular mechanism of abnormally large nonsoftening, quasi-linear but inelastic deformation in tough hydrogels made of hyperconnective physical network and linear polymers as molecular glues to the network. The interplay of hyperconnectivity of network and effective load transfer by molecular glues prevents stress concentration, which is revealed by an affine deformation of the network to the bulk deformation up to sample failure. The suppression of local stress concentration and strain amplification plays a key role in avoiding necking or strain softening and endows the gels with a unique large nonsoftening, quasi-linear but inelastic deformation.

Supertough Lignin Hydrogels with Multienergy Dissipative Structures and Ultrahigh Antioxidative Activities.

Hydrogels derived from lignin are typically weak and contain only a small amount of lignin, which limits their broad application prospects. In the present work, a novel lignin/poly(N,N-dimethylacrylamide) (PDMA) hydrogel with a high lignin content, superb toughness, and ultrahigh antioxidative performance is constructed by employing a facile dissolve-dry-swell solvent exchange method. Through this process, lignin and PDMA are self-assembled into a multienergy dissipative structure containing rigid lignin-rich domains. Precisely, the PDMA chains both interpenetrated inside and adhered on the surface of these domains through hydrophobic associations. This structure enables the lignin hydrogels to dissipate energy efficiently during the fracture process. At an optimized ultrahigh lignin content of 58% (dry weight basis), the prepared lignin hydrogel exhibited remarkable mechanical properties, such as a high elastic modulus (2.5 MPa), tensile strength (2.5 MPa), and super tensile strain (11.3), and an extremely high fracture energy above 16 000 J m-2. In addition, the tough lignin hydrogel exhibited a commendable antioxidant property and nontoxicity. All these advantageous properties provide the lignin/PDMA hydrogels with the potential for use in biomedical materials applications.

High-Fidelity Hydrogel Thin Films Processed from Deep Eutectic Solvents.

Polyampholyte (PA) hydrogels are a fascinating class of soft materials that can exhibit high toughness while retaining self-healing characteristics. This behavior results from the random distribution of oppositely charged monomers along the polymer chains that form transient bonds with a range of bond strengths. PAs can be dissolved in aqueous salt solutions and then recast via immersion precipitation, making them particularly useful as surface coatings in biomedical applications. Moreover, this immersion precipitation technique allows these PA hydrogels to be fabricated into films less than 100 nm. One critical challenge to this aqueous processing method is the recrystallization of the salt upon water evaporation. Such recrystallization can disrupt the hydrogel morphology especially in thin films. In this study, a deep eutectic solvent (DES) formed from urea and choline chloride was used to dissolve PAs made from p-styrenesulfonic acid sodium salt and 3-(methacryloylamino)propyl trimethylammonium chloride. This DES has a freezing point of 12 °C, allowing it to remain stable and liquid-like at room temperatures. Thus, these PAs can be processed in DES solutions, without this issue of recrystallization and with simple methods such as spin coating and dip coating. These methods allow these hydrogels to be used in thin (<100 nm)-film coating applications. Finally, the complete miscibility of DES in water allows a wider range of one-phase compositions and expands the processing window of these polyampholyte materials.

Hydrogels as dynamic memory with forgetting ability.

The memory of our brain, stored in soft matter, is dynamic, and it forgets spontaneously to filter unimportant information. By contrast, the existing manmade memory, made from hard materials, is static, and it does not forget without external stimuli. Here we propose a principle for developing dynamic memory from soft hydrogels with temperature-sensitive dynamic bonds. The memorizing-forgetting behavior is achieved based on fast water uptake and slow water release upon thermal stimulus, as well as thermal-history-dependent transparency change of these gels. The forgetting time is proportional to the thermal learning time, in analogy to the behavior of brain. The memory is stable against temperature fluctuation and large stretching; moreover, the forgetting process is programmable. This principle may inspire future research on dynamic memory based on the nonequilibrium process of soft matter.

Robust Multiscale-Oriented Thermoresponsive Fibrous Hydrogels with Rapid Self-Recovery and Ultrafast Response Underwater.

Hydrogels with ultrafast response to environmental stimuli, possessing robust structural integrity and rapid self-recovery, have been considered as promising platforms for numerous applications, for example, in biomimetic materials and nanomedicine. Inspired by the bundled fibrous structure of actin, we developed a robust and ultrafast thermoresponsive fibrous hydrogel (TFH) by fully utilizing the weak noncovalent bonds and strong covalently cross-linked semiflexible electrospun fibrous nets. The TFH exhibits an ultrafast response (within 10 s), rapid self-recovery rate (74% within 10 s), tunable tensile strength (3-380 kPa), and high toughness (∼1560 J/m2) toward temperature. A multiscale orientation is considered to play a key role in the excellent mechanical properties at the fibrous mesh, fiber, and molecular scales. Furthermore, to take advantage of this TFH adequately, a novel kind of noodle-like hydrogel for thermo-controlled protein sorption based on the TFH is prepared, which exhibits high stability and ultrafast sorption properties. The bioinspired platforms hold promise as artificial skins and "smart" sorption membrane carriers, which provide a unique bioactive environment for tissue engineering and nanomedicine.