Embedded Physical Intelligence in Liquid Crystalline Polymer Actuators and Robots.

Responsive materials possess the inherent capacity to autonomously sense and respond to various external stimuli, demonstrating physical intelligence. Among the diverse array of responsive materials, liquid crystalline polymers (LCPs) stand out for their remarkable reversible stimuli-responsive shape-morphing properties and their potential for creating soft robots. While numerous reviews have extensively detailed the progress in developing LCP-based actuators and robots, there exists a need for comprehensive summaries that elucidate the underlying principles governing actuation and how physical intelligence is embedded within these systems. This review provides a comprehensive overview of recent advancements in developing actuators and robots endowed with physical intelligence using LCPs. This review is structured around the stimulus conditions and categorizes the studies involving responsive LCPs based on the fundamental control and stimulation logic and approach. Specifically, three main categories are examined: systems that respond to changing stimuli, those operating under constant stimuli, and those equip with learning and logic control capabilities. Furthermore, the persisting challenges that need to be addressed are outlined and discuss the future avenues of research in this dynamic field.

Integrated physiology, transcriptome and proteome analyses highlight the potential roles of multiple hormone-mediated signaling pathways involved in tapping panel dryness in rubber tree.

Currently, one of the most serious threats to rubber tree is the tapping panel dryness (TPD) that greatly restricts natural rubber production. Over-tapping or excessive ethephon stimulation is regarded as the main cause of TPD occurrence. Although extensive studies have been carried out, the molecular mechanism underlying TPD remains puzzled. An attempt was made to compare the levels of endogenous hormones and the profiles of transcriptome and proteome between healthy and TPD trees. Results showed that most of endogenous hormones such as jasmonic acid (JA), 1-aminocyclopropanecarboxylic acid (ACC), indole-3-acetic acid (IAA), trans-zeatin (tZ) and salicylic acid (SA) in the barks were significantly altered in TPD-affected rubber trees. Accordingly, multiple hormone-mediated signaling pathways were changed. In total, 731 differentially expressed genes (DEGs) and 671 differentially expressed proteins (DEPs) were identified, of which 80 DEGs were identified as putative transcription factors (TFs). Further analysis revealed that 12 DEGs and five DEPs regulated plant hormone synthesis, and that 16 DEGs and six DEPs were involved in plant hormone signal transduction pathway. Nine DEGs and four DEPs participated in rubber biosynthesis and most DEGs and all the four DEPs were repressed in TPD trees. All these results highlight the potential roles of endogenous hormones, signaling pathways mediated by these hormones and rubber biosynthesis pathway in the defense response of rubber trees to TPD. The present study extends our understanding of the nature and mechanism underlying TPD and provides some candidate genes and proteins related to TPD for further research in the future.

Construction and analysis of the tapping panel dryness-related lncRNA/circRNA-miRNA-mRNA ceRNA network in latex of Hevea brasiliensis.

Tapping panel dryness (TPD) results in a severe reduction in latex yield in Hevea brasiliensis. However, the molecular regulatory mechanisms of TPD occurrence are still largely unclear. In this study, whole-transcriptome sequencing was carried out on latex from TPD and healthy trees. In total, 7078 long noncoding RNAs (lncRNAs), 3077 circular RNAs (circRNAs), 4956 miRNAs, and 25041 mRNAs were identified in latex, among which 435 lncRNAs, 68 circRNAs, 320 miRNAs, and 1574 mRNAs were differentially expressed in the latex of TPD trees. GO and KEGG analyses indicated that plant hormone signal transduction, MAPK signaling pathway, and ubiquitin-mediated proteolysis were the key pathways associated with TPD onset. Phytohormone profiling revealed significant changes in the contents of 28 hormonal compounds, among which ACC, ABA, IAA, GA, and JA contents were increased, while SA content was reduced in TPD latex, suggesting that hormone homeostasis is disrupted in TPD trees. Furthermore, we constructed a TPD-related competitive endogenous RNA (ceRNA) regulatory network of lncRNA/circRNA-miRNA-mRNA with 561 edges and 434 nodes (188 lncRNAs, 5 circRNAs, 191 miRNAs, and 50 mRNAs) and identified two hub lncRNAs (MSTRG.11908.1 and MSTRG.8791.1) and four hub miRNAs (hbr-miR156, miR156-x, miRf10477-y, and novel-m0452-3p). Notably, the lncRNA-miR156/157-SPL module containing three hubs probably plays a crucial role in TPD onset. The expression of network hubs and the lncRNA-miR156/157-SPL module were further validated by qRT-PCR. Our results reveal the TPD-associated ceRNA regulatory network of lncRNA/circRNA-miRNA-mRNA in latex and lay a foundation for further investigation of molecular regulatory mechanisms for TPD onset in H. brasiliensis.

Arabidopsis membrane protein AMAR1 interaction with type III effector XopAM triggers a hypersensitive response.

The efficient infection of plants by the bacteria Xanthomonas campestris pv. campestris (Xcc) depends on its type III effectors (T3Es). Although the functions of AvrE family T3Es have been reported in some bacteria, the member XopAM in Xcc has not been studied. As XopAM has low sequence similarity to reported AvrE-T3Es and different reports have shown that these T3Es have different targets in hosts, we investigated the functions of XopAM in the Xcc-plant interaction. Deletion of xopAM from Xcc reduced its virulence in cruciferous crops but increased virulence in Arabidopsis (Arabidopsis thaliana) Col-0, indicating that XopAM may perform opposite functions depending on the host species. We further found that XopAM is a lipase that may target the cytomembrane and that this activity might be enhanced by its membrane-targeted protein XOPAM-ACTIVATED RESISTANCE 1 (AMAR1) in Arabidopsis Col-0. The binding of XopAM to AMAR1 induced an intense hypersensitive response that restricted Xcc proliferation. Our results showed that the roles of XopAM in Xcc infection are not the same as those of other AvrE-T3Es, indicating that the functions of this type of T3E have differentiated during long-term bacterium‒host interactions.

A deep learning framework for identifying Alzheimer's disease using fMRI-based brain network.

Background: The convolutional neural network (CNN) is a mainstream deep learning (DL) algorithm, and it has gained great fame in solving problems from clinical examination and diagnosis, such as Alzheimer's disease (AD). AD is a degenerative disease difficult to clinical diagnosis due to its unclear underlying pathological mechanism. Previous studies have primarily focused on investigating structural abnormalities in the brain's functional networks related to the AD or proposing different deep learning approaches for AD classification. Objective: The aim of this study is to leverage the advantages of combining brain topological features extracted from functional network exploration and deep features extracted by the CNN. We establish a novel fMRI-based classification framework that utilizes Resting-state functional magnetic resonance imaging (rs-fMRI) with the phase synchronization index (PSI) and 2D-CNN to detect abnormal brain functional connectivity in AD. Methods: First, PSI was applied to construct the brain network by region of interest (ROI) signals obtained from data preprocessing stage, and eight topological features were extracted. Subsequently, the 2D-CNN was applied to the PSI matrix to explore the local and global patterns of the network connectivity by extracting eight deep features from the 2D-CNN convolutional layer. Results: Finally, classification analysis was carried out on the combined PSI and 2D-CNN methods to recognize AD by using support vector machine (SVM) with 5-fold cross-validation strategy. It was found that the classification accuracy of combined method achieved 98.869%. Conclusion: These findings show that our framework can adaptively combine the best brain network features to explore network synchronization, functional connections, and characterize brain functional abnormalities, which could effectively detect AD anomalies by the extracted features that may provide new insights into exploring the underlying pathogenesis of AD.

A novel framework of MOPSO-GDM in recognition of Alzheimer's EEG-based functional network.

Background: Most patients with Alzheimer's disease (AD) have an insidious onset and frequently atypical clinical symptoms, which are considered a normal consequence of aging, making it difficult to diagnose AD medically. But then again, accurate diagnosis is critical to prevent degeneration and provide early treatment for AD patients. Objective: This study aims to establish a novel EEG-based classification framework with deep learning methods for AD recognition. Methods: First, considering the network interactions in different frequency bands (δ, θ, α, ß, and γ), multiplex networks are reconstructed by the phase synchronization index (PSI) method, and fourteen topology features are extracted subsequently, forming a high-dimensional feature vector. However, in feature combination, not all features can provide effective information for recognition. Moreover, combining features by manual selection is time-consuming and laborious. Thus, a feature selection optimization algorithm called MOPSO-GDM was proposed by combining multi-objective particle swarm optimization (MOPSO) algorithm with Gaussian differential mutation (GDM) algorithm. In addition to considering the classification error rates of support vector machine, naive bayes, and discriminant analysis classifiers, our algorithm also considers distance measure as an optimization objective. Results: Finally, this method proposed achieves an excellent classification error rate of 0.0531 (5.31%) with the feature vector size of 8, by a ten-fold cross-validation strategy. Conclusion: These findings show that our framework can adaptively combine the best brain network features to explore network synchronization, functional interactions, and characterize brain functional abnormalities, which can improve the recognition efficiency of diseases. While improving the classification accuracy of application algorithms, we aim to expand our understanding of the brain function of patients with neurological disorders through the analysis of brain networks.

A modular strategy for distributed, embodied control of electronics-free soft robots.

Robots typically interact with their environments via feedback loops consisting of electronic sensors, microcontrollers, and actuators, which can be bulky and complex. Researchers have sought new strategies for achieving autonomous sensing and control in next-generation soft robots. We describe here an electronics-free approach for autonomous control of soft robots, whose compositional and structural features embody the sensing, control, and actuation feedback loop of their soft bodies. Specifically, we design multiple modular control units that are regulated by responsive materials such as liquid crystal elastomers. These modules enable the robot to sense and respond to different external stimuli (light, heat, and solvents), causing autonomous changes to the robot's trajectory. By combining multiple types of control modules, complex responses can be achieved, such as logical evaluations that require multiple events to occur in the environment before an action is performed. This framework for embodied control offers a new strategy toward autonomous soft robots that operate in uncertain or dynamic environments.

Liquid Crystal Elastomer Based Dexterous Artificial Motor Unit.

Despite the great advancement in designing diverse soft robots, they are not yet as dexterous as animals in many aspects. One challenge is that they still lack the compact design of an artificial motor unit with a great comprehensive performance that can be conveniently fabricated, although many recently developed artificial muscles have shown excellent properties in one or two aspects. Herein, an artificial motor unit is developed based on gold-coated ultrathin liquid crystal elastomer (LCE) film. Subject to a voltage, Joule heating generated by the gold film increases the temperature of the LCE film underneath and causes it to contract. Due to the small thermal inertial and electrically controlling method of the ultrathin LCE structure, its cyclic actuation speed is fast and controllable. It is shown that under electrical stimulation, the actuation strain of the LCE-based motor unit reaches 45%, the strain rate reaches 750%/s, and the output power density is as high as 1360 W kg-1 . It is further demonstrated that the LCE-based motor unit behaves like an actuator, a brake, or a nonlinear spring on demand, analogous to most animal muscles. Finally, as a proof-of-concept, multiple highly dexterous artificial neuromuscular systems are demonstrated using the LCE-based motor unit.

Ectopic Expression of HbRPW8-a from Hevea brasiliensis Improves Arabidopsis thaliana Resistance to Powdery Mildew Fungi (Erysiphe cichoracearum UCSC1).

The RPW8s (Resistance to Powdery Mildew 8) are atypical broad-spectrum resistance genes that provide resistance to the powdery mildew fungi. Powdery mildew of rubber tree is one of the serious fungal diseases that affect tree growth and latex production. However, the RPW8 homologs in rubber tree and their role of resistance to powdery mildew remain unclear. In this study, four RPW8 genes, HbRPW8-a, b, c, d, were identified in rubber tree, and phylogenetic analysis showed that HbRPW8-a was clustered with AtRPW8.1 and AtRPW8.2 of Arabidopsis. The HbRPW8-a protein was localized on the plasma membrane and its expression in rubber tree was significantly induced upon powdery mildew infection. Transient expression of HbRPW8-a in tobacco leaves induced plant immune responses, including the accumulation of reactive oxygen species and the deposition of callose in plant cells, which was similar to that induced by AtRPW8.2. Consistently, overexpression of HbRPW8-a in Arabidopsis thaliana enhanced plant resistance to Erysiphe cichoracearum UCSC1 and Pseudomonas syringae pv. tomato DC30000 (PstDC3000). Moreover, such HbRPW8-a mediated resistance to powdery mildew was in a salicylic acid (SA) dependent manner. Taken together, we demonstrated a new RPW8 member in rubber tree, HbRPW8-a, which could potentially contribute the resistance to powdery mildew.

Magnetic vitrimer-based soft robotics.

Magnetically responsive elastomers, consisting of elastomer embedded with magnetic particles, can produce fast and reversible actuation when subjected to a magnetic field. They have been extensively explored to construct versatile remotely controllable soft robots. Nevertheless, the magnetically induced actuation strain in elastomers is typically small, which limits its broad applications. Recently, magnetic particles have been mixed with viscous fluids to enable giant magnetically induced deformations. However, their response speed is slow and the actuation is usually irreversible. In this work, we have developed a magnetic vitrimer (MV), with magnetic particles mixed with the polymer network containing abundant dynamic covalent bonds. At room temperature, the MV behaves like a regular magnetically responsive elastomer. When the temperature is elevated to the exchange reaction temperature of the dynamic covalent bonds, the material behaves like a viscous magnetically responsive fluid, which can produce large deformations. The embedded magnetic particles and the vitrimer matrix also make the material self-healable without requiring any direct touch. We have demonstrated that with the guidance of an externally applied magnetic field, a MV-based soft robot can pass through a confined space, dramatically change its configuration, self-heal without any contact, catch, secure and release a fast-moving object, and move along a planned path.

Highly robust and soft biohybrid mechanoluminescence for optical signaling and illumination.

Biohybrid is a newly emerging and promising approach to construct soft robotics and soft machines with novel functions, high energy efficiency, great adaptivity and intelligence. Despite many unique advantages of biohybrid systems, it is well known that most biohybrid systems have a relatively short lifetime, require complex fabrication process, and only remain functional with careful maintenance. Herein, we introduce a simple method to create a highly robust and power-free soft biohybrid mechanoluminescence, by encapsulating dinoflagellates, bioluminescent unicellular marine algae, into soft elastomeric chambers. The dinoflagellates retain their intrinsic bioluminescence, which is a near-instantaneous light response to mechanical forces. We demonstrate the robustness of various geometries of biohybrid mechanoluminescent devices, as well as potential applications such as visualizing external mechanical perturbations, deformation-induced illumination, and optical signaling in a dark environment. Our biohybrid mechanoluminescent devices are ultra-sensitive with fast response time and can maintain their light emission capability for weeks without special maintenance.

Genome-wide identification of lncRNAs, miRNAs, mRNAs and their regulatory networks involved in tapping panel dryness in rubber tree (Hevea brasiliensis).

Noncoding RNAs (ncRNAs) play pivotal roles in various biological processes in plants. However, the role of ncRNAs in tapping panel dryness (TPD) of rubber tree (Hevea brasiliensis Muell. Arg.) is largely unknown. Here, the whole transcriptome analyses of bark tissues from healthy and TPD trees were performed to identify differentially expressed long ncRNAs (DELs), microRNAs/miRNAs (DEMs), genes (DEGs) and their regulatory networks involved in TPD. A total of 263 DELs, 174 DEMs and 1574 DEGs were identified in the bark of TPD tree compared with that of healthy tree. Kyoto Encyclopedia of Genes and Genomes analysis revealed that most of the DEGs and targets of DELs and DEMs were mainly enriched in metabolic pathways, biosynthesis of secondary metabolites and plant hormone signal transduction. Additionally, the majority of DEGs and DELs related to rubber biosynthesis were downregulated in TPD trees. Furthermore, 98 DEGs and 44 DELs were targeted by 54 DEMs, 190 DEGs were identified as putative targets of 56 DELs, and 2 and 44 DELs were predicted as precursors and endogenous target mimics of 2 and 6 DEMs, respectively. Based on these, the DEL-DEM-DEG regulatory network involved in TPD was constructed, and 13 hub DELs, 3 hub DEMs and 2 hub DEGs were identified. The results provide novel insights into the regulatory roles of ncRNAs underlying TPD and lay a foundation for future functional characterization of long ncRNAs, miRNAs and genes involved in TPD in rubber tree.

Electrospun liquid crystal elastomer microfiber actuator.

Fibers capable of generating axial contraction are commonly seen in nature and engineering applications. Despite the broad applications of fiber actuators, it is still very challenging to fabricate fiber actuators with combined large actuation strain, fast response speed, and high power density. Here, we report the fabrication of a liquid crystal elastomer (LCE) microfiber actuators using a facile electrospinning technique. Owing to the extremely small size of the LCE microfibers, they can generate large actuation strain (~60 percent) with a fast response speed (<0.2 second) and a high power density (400 watts per kilogram), resulting from the nematic-isotropic phase transition of liquid crystal mesogens. Moreover, no performance degradation is detected in the LCE microfibers after 106 cycles of loading and unloading with the maximum strain of 20 percent at high temperature (90 degree Celsius). The small diameter of the LCE microfiber also results in a self-oscillatory behavior in a steady temperature field. In addition, with a polydopamine coating layer, the actuation of the electrospun LCE microfiber can be precisely and remotely controlled by a near-infrared laser through photothermal effect. Using the electrospun LCE microfiber actuator, we have successfully constructed a microtweezer, a microrobot, and a light-powered microfluidic pump.

HbLFG1, a Rubber Tree (Hevea brasiliensis) Lifeguard Protein, Can Facilitate Powdery Mildew Infection by Suppressing Plant Immunity.

Powdery mildew causes substantial losses in crop and economic plant yields worldwide. Although powdery mildew infection of rubber trees (Hevea brasiliensis), caused by the biotrophic fungus Erysiphe quercicola, severely threatens natural rubber production, little is known about the mechanism by which E. quercicola adapts to H. brasiliensis to invade the host plant. In barley and Arabidopsis thaliana, lifeguard (LFG) proteins, which have topological similarity to BAX INHIBITOR-1, are involved in host plant susceptibility to powdery mildew infection. In this study, we characterized an H. brasiliensis LFG protein (HbLFG1) with a focus on its function in regulating defense against powdery mildew. HbLFG1 gene expression was found to be upregulated during E. quercicola infection. HbLFG1 showed conserved functions in cell death inhibition and membrane localization. Expression of HbLFG1 in Nicotiana benthamiana leaves and A. thaliana Col-0 was demonstrated to significantly suppress callose deposition induced by conserved pathogen-associated molecular patterns chitin and flg22. Furthermore, we found that overexpression of HbLFG1 in H. brasiliensis mesophyll protoplasts significantly suppressed the chitin-induced burst of reactive oxygen species. Although A. thaliana Col-0 and E. quercicola displayed an incompatible interaction, Col-0 transformants overexpressing HbLFG1 were shown to be susceptible to E. quercicola. Collectively, the findings of this study provide evidence that HbLFG1 acts as a negative regulator of plant immunity that facilitates E. quercicola infection in H. brasiliensis.

Soft pumps for soft robots.

A light and portable soft electro-pneumatic pump could power future soft robots.

3D Printing of Electrically Responsive PVC Gel Actuators.

Additive manufacturing of electrically responsive soft actuators is of great importance in designing and constructing novel soft robots and soft machines. However, there are very limited options for 3D-printable and electrically responsive soft materials. Herein, we report a strategy of 3D printing polyvinyl chloride (PVC) gel actuators that are electrically controllable. We print a jellyfish-like actuator from PVC ink, which can achieve 130° bending in less than 5 s. With the multi-material 3D printing technique, we have further printed a soft actuator with a stiffness gradient that can generate undulatory motion. As a proof-of-concept demonstration, we show that a 3D-printed PVC gel-based smart window can change its transparency upon the application of voltage. The 3D printing strategy developed in this article may expand the potential applications of electrically responsive soft materials in diverse engineering fields.

A novel chorismate mutase from Erysiphe quercicola performs dual functions of synthesizing amino acids and inhibiting plant salicylic acid synthesis.

Pathogens secrete effectors to establish a successful interaction with their host. It is well understood that plant pathogens recruit classically secreted chorismate mutase (Cmu) as an effector to disrupt plant salicylic acid (SA) synthesis. However, the identity and function of the Cmu effector from powdery mildew fungi remain unknown. Here, we identified a novel secreted Cmu effector, EqCmu, from rubber (Hevea brasiliensis Muell) powdery mildew fungus (Erysiphe quercicola). Unlike the classically secreted Cmu, EqCmu lack signal peptide, and exhibited characteristics of non-classically secreted proteins. EqCmu could fully complement a Saccharomyces cerevisiae ScAro7 mutant that was deficient in the synthesis of phenylalanine and tyrosine. In addition, transient expression of EqCmu could promote infection by Phytophthora capsici and reduce the levels of SA and the mRNA of PR1 gene in Nicotiana benthamiana in response to P. capsici infection, while confocal observations showed that EqCmu was localized within the cytoplasm and nucleus of transfected N. benthamiana leaf cells. These non-homologous systems assays provide evidences that EqCmu may serve as a "moonlighting" protein, which is not only a key enzyme in the synthesis of phenylalanine and tyrosine within fungal cells, but also has the function of regulating plant SA synthesis within plant cells. This is the first study to identify and functionally validate a candidate effector from E. quercicola. Overall, the non-classical secretion pathway is a novel mechanism for powdery mildew fungal effectors secretion and might play an important role in host-pathogen interactions.

A Candidate Secreted Effector Protein of Rubber Tree Powdery Mildew Fungus Contributes to Infection by Regulating Plant ABA Biosynthesis.

Powdery mildew infects a wide range of crops and economic plants, causing substantial losses. Rubber trees (Hevea brasiliensis) are the primary source of natural rubber, and powdery mildew infection causes significant losses to natural rubber yields. How the causal agent, Erysiphe quercicola, establishes successful infection in rubber trees is largely unknown. Previously, 133 candidate secreted effector proteins (CSEPs) were identified in powdery mildew fungus. In this study, we characterize a CSEP named EqCSEP01276 for its function in suppressing host plant defense responses. We show that EqCSEP01276 is a secreted protein and is able to disturb the localization of 9-cis-epoxycarotenoid dioxygenase 5 (HbNCED5), a key enzyme in abscisic acid (ABA) biosynthesis in plant cell chloroplasts of H. brasiliensis. We also show that this effector inhibits ABA biosynthesis, and that in H. brasiliensis ABA is a positive regulator of the plant immune response against powdery mildew. Our study reveals a strategy by which powdery mildew fungus manipulates plant ABA-mediated defense for a successful infection.

Three-dimensional printing of functionally graded liquid crystal elastomer.

As a promising actuating material, liquid crystal elastomer (LCE) has been intensively explored in building diverse active structures and devices. Recently, direct ink writing technique has been developed to print LCE structures with various geometries and actuation behaviors. Despite the advancement in printing LCE, it remains challenging to print three-dimensional (3D) LCE structures with graded properties. Here, we report a facile method to tailor both the actuation behavior and mechanical properties of printed LCE filaments by varying printing parameters. On the basis of the comprehensive processing-structure-property relationship, we propose a simple strategy to print functionally graded LCEs, which greatly increases the design space for creating active morphing structures. We further demonstrate mitigation of stress concentration near the interface between an actuatable LCE tube and a rigid glass plate through gradient printing. The strategy developed here will facilitate potential applications of LCEs in different fields.