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Abstract Ionogels are promising material candidates for ionotronics due to their excellent ionic conductivity, stretchability, and thermal stability. However, it is challenging to develop 3D printable ionogels with both excellent electrical and mechanical properties. Here, we report a highly conductive and stretchable nanostructured (CSN) ionogel for 3D printing ionotronic sensors. We propose the photopolymerization-induced microphase separation strategy to prepare the CSN ionogels comprising continuous conducting nanochannels intertwined with cross-linked polymeric framework. The resultant CSN ionogels simultaneously achieves high ionic conductivity (over 3 S m−1), high stretchability (over 1500%), low degree of hysteresis (0.4% at 50% strain), wide-temperature-range thermostability (−72 to 250 °C). Moreover, its high compatible with DLP 3D printing enables the fabrication of complex ionogel micro-architectures with high resolution (up to 5 μm), which allows us to manufacture capacitive sensors with superior sensing performances. The proposed CSN ionogel paves an efficient way to manufacture the next-generation capacitive sensors with enhanced performance.

Abstract Great yield-enhancing prospects of autotetraploid rice was restricted by various polyploidy-induced reproductive dysfunction. To surmount these challenges, our group has generated a series of valuable fertile tetraploid lines (denoted as neo-tetraploid rice) through 20-year efforts. With this context, a G-type lectin receptor-like kinase, OsNRFG6, was identified as a pivotal factor associated with reproductive regulation in neo-tetraploid rice. Nevertheless, it is still elusive about a comprehensive understanding of its precise functional roles and underlying molecular mechanisms during reproduction of neo-tetraploid rice. Here, we demonstrated that OsNRFG6 executed a constitutive expression pattern and encoded proteins localizing in perinucleus and endoplasmic reticulum. Subsequently, four independent mutant lines of OsNRFG6 within neo-tetraploid rice background were further identified, all displaying low seed-setting rate due to abortive embryo sacs and defective double fertilization. RNA-seq and RT-qPCR revealed a significant down-regulation of OsNRFG6 and female reproductive genes such as OsMEL1 and LOG in ovaries prior to and post-fertilization, attributing this effect to OsNRFG6 mutation. Furthermore, through yeast-two hybrids, bimolecular fluorescence complementation assays, and luciferase complementation imaging assays, it was determined that OsNRFG6 could interact with itself and two female reproductive proteins (LOG and OsDES1) to form protein complexes. These results elucidate the reproductive functions and molecular pathway governed by OsNRFG6 in regulating fertility of neo-tetraploid rice, offering insights into molecular understanding of fertility improvement in polyploid rice.

Abstract Neonatal pulmonary hemorrhage is a late manifestation of various diseases. Premature delivery and low body weight are frequently observed as high-risk factors, characterized by acute onset, rapid progression, and high mortality rates. Pulmonary hemorrhage caused by cytomegalovirus infection in newborns with normal immune function is a rare occurrence. This case report focuses on a term neonate with normal birth weight who presented solely with nasal obstruction shortly after birth. However, 4 days after birth, the newborn experienced a sudden onset of blood gushing from both the mouth and nasal cavity. The patient was diagnosed with gastrointestinal bleeding, neonatal pneumonia and neonatal lung consolidation. And he was discharged after ten days of symptomatic treatment. However, upon returning home, the patient experienced a sudden onset of bleeding from the mouth and nose, leading to his untimely demise. Subsequent autopsy revealed the presence of pulmonary hemorrhage in newborn, which presented as interstitial pneumonia. The cause of pulmonary hemorrhage is cytomegalovirus infection. This case emphasizes the importance of pediatricians enhancing their skills in differentiating pulmonary hemorrhage, especially from cytomegalovirus pneumonia.

Abstract In this paper, we study the existence and uniqueness of positive solutions for a class of a fractional differential equation system of Riemann–Liouville type on infinite intervals with infinite-point boundary conditions. First, the higher-order equation is reduced to the lower-order equation, and then it is transformed into the equivalent integral equation. Secondly, we obtain the existence and uniqueness of positive solutions for each fixed parameter λ > 0 $\lambda >0$ by using the mixed monotone operators fixed-point theorem. The results obtained in this paper show that the unique positive solution has good properties: continuity, monotonicity, iteration, and approximation. Finally, an example is given to demonstrate the application of our main results.

Abstract Active origami capable of precise deployment control, enabling on-demand modulation of its properties, is highly desirable in multi-scenario and multi-task applications. While 4D printing with shape memory composites holds great promise to realize such active origami, it still faces challenges such as low load-bearing capacity and limited transformable states. Here, we report a fabrication-design-actuation method of precisely controlled electrothermal origami with excellent mechanical performance and spatiotemporal controllability, utilizing 4D printing of continuous fiber-reinforced composites. The incorporation of continuous carbon fibers empowers electrothermal origami with a controllable actuation process via Joule heating, increased actuation force through improved heat conduction, and enhanced mechanical properties as a result of reinforcement. By modeling the multi-physical and highly nonlinear deploying process, we attain precise control over the active origami, allowing it to be reconfigured and locked into any desired configuration by manipulating activation parameters. Furthermore, we showcase the versatility of electrothermal origami by constructing reconfigurable robots, customizable architected materials, and programmable wings, which broadens the practical engineering applications of origami.

IntroductionAutotetraploid rice holds high resistance to abiotic stress and substantial promise for yield increase, but it could not be commercially used because of low fertility. Thus, our team developed neo-tetraploid rice with high fertility and hybrid vigor when crossed with indica autotetraploid rice. Despite these advances, the molecular mechanisms underlying this heterosis remain poorly understood.MethodsAn elite indica autotetraploid rice line (HD11) was used to cross with neo-tetraploid rice, and 34 hybrids were obtained to evaluate agronomic traits related to yield. WE-CLSM, RNA-seq, and CRISPR/Cas9 were employed to observe endosperm structure and identify candidate genes from two represent hybrids. Results and discussionThese hybrids showed high seed setting and an approximately 55% increase in 1000-grain weight, some of which achieved grain yields comparable to those of the diploid rice variety. The endosperm observations indicated that the starch grains in the hybrids were more compact than those in paternal lines. A total of 119 seed heterosis related genes (SHRGs) with different expressions were identified, which might contribute to high 1000-grain weight heterosis in neo-tetraploid hybrids. Among them, 12 genes had been found to regulate grain weight formation, including OsFl3, ONAC023, OsNAC024, ONAC025, ONAC026, RAG2, FLO4, FLO11, OsISA1, OsNF-YB1, NF-YC12, and OsYUC9. Haplotype analyses of these 12 genes revealed the various effects on grain weight among different haplotypes. The hybrids could polymerize more dominant haplotypes of above grain weight regulators than any homozygous cultivar. Moreover, two SHRGs (OsFl3 and SHRG2) mutants displayed a significant reduction in 1000-grain weight and an increase in grain chalkiness, indicating that OsFl3 and SHRG2 positively regulate grain weight. Our research has identified a valuable indica autotetraploid germplasm for generating strong yield heterosis in combination with neo-tetraploid lines and gaining molecular insights into the regulatory processes of heterosis in tetraploid rice.

Abstract Aims The present study aimed to phenotype the cerebral structural and glucose metabolic alterations in patients with heart failure (HF) using simultaneous positron emission tomography (PET)/magnetic resonance (MR) and to investigate their relationship to cardiac biomarkers and cognitive performance. Methods and results Forty‐two HF patients caused by ischaemic heart disease (mean age 67.2 ± 10.4, 32 males) and 32 age‐ and sex‐matched healthy volunteers (mean age 61.3 ± 4.8, 18 males) were included in this study. Participants underwent simultaneous cerebral fluorine‐18 (18F) fluorodeoxyglucose PET/MR followed by cardiac MR scan, and neuropsychological scores were obtained to assess cognitive performance. The grey matter volume (GMV) and standardized uptake value ratio (SUVR) were calculated to examine cerebral structural and metabolic alterations. Cardiac biomarkers included cardiac MR parameters and cardiac serum laboratory tests. Mediation analysis was performed to explore the associations among cerebral alterations, cardiac biomarkers, and cognitive performance. HF patients demonstrated notable cognitive impairment compared with normal controls (P

Abstract 4D printing technology combines 3D printing and stimulus-responsive materials, enabling construction of complex 3D objects efficiently. However, unlike smart soft materials, 4D printing of ceramics is a great challenge due to the extremely weak deformability of ceramics. Here, we report a feasible and efficient manufacturing and design approach to realize direct 4D printing of ceramics. Photocurable ceramic elastomer slurry and hydrogel precursor are developed for the fabrication of hydrogel-ceramic laminates via multimaterial digital light processing 3D printing. Flat patterned laminates evolve into complex 3D structures driven by hydrogel dehydration, and then turn into pure ceramics after sintering. Considering the dehydration-induced deformation and sintering-induced shape retraction, we develop a theoretical model to calculate the curvatures of bent laminate and sintered ceramic part. Then, we build a design flow for direct 4D printing of various complex ceramic objects. This approach opens a new avenue for the development of ceramic 4D printing technology.

Abstract Post-surgical treatments of the human throat often require continuous monitoring of diverse vital and muscle activities. However, wireless, continuous monitoring and analysis of these activities directly from the throat skin have not been developed. Here, we report the design and validation of a fully integrated standalone stretchable device platform that provides wireless measurements and machine learning-based analysis of diverse vibrations and muscle electrical activities from the throat. We demonstrate that the modified composite hydrogel with low contact impedance and reduced adhesion provides high-quality long-term monitoring of local muscle electrical signals. We show that the integrated triaxial broad-band accelerometer also measures large body movements and subtle physiological activities/vibrations. We find that the combined data processed by a 2D-like sequential feature extractor with fully connected neurons facilitates the classification of various motion/speech features at a high accuracy of over 90%, which adapts to the data with noise from motion artifacts or the data from new human subjects. The resulting standalone stretchable device with wireless monitoring and machine learning-based processing capabilities paves the way to design and apply wearable skin-interfaced systems for the remote monitoring and treatment evaluation of various diseases.

The oriental fruit fly, Bactrocera dorsalis (Hendel), is a devastating pest of citrus fruits. After successful mating, adult females insert their eggs into the ripened fruit, resulting in moldy and rotten fruit and causing great economic losses for the citrus industry. In the field, flies initiate copulatory behaviors as twilight approaches, and decreasing light intensity in this period is the normal stimulus for copulation. In this study, ten light intensities ranging from 0–30 000 lux were set to identify the typical intensity that strongly regulates the copulation behavior of B. dorsalis. Three light intensities found to regulate the copulation behavior were then selected to verify their effects on adult male wing fanning and female chemotaxis towards 2,3,5-trimethylpyrazine (TMP). At last, strong light and complete darkness were artificially combined in the lab to verify whether they could prevent copulation to inform behavioral manipulation of oriental flies in the future. The results indicated that adult flies generally initiated copulatory behaviors at low light intensity (

Accurate prediction of reservoir landslide displacements is crucial for early warning and hazard prevention. Current machine learning (ML) paradigms for predicting landslide displacement demonstrate superior performance, while often relying on various feature engineering techniques, such as decomposing into different temporal lags and feature selection. This study investigates the impact of various feature selection techniques on the performance of ML algorithms for landslide displacement prediction. The Shuping and Baishuihe landslides in China’s Three Gorges Reservoir Area are used to comprehensively benchmark four prevalent ML algorithms. Both static ML models, including backpropagation neural network (BPNN), support vector machine (SVM), and dynamic models, such as long short-term memory (LSTM), and gated recurrent unit (GRU), are included. Each ML model is evaluated under three feature engineering techniques: raw multivariate time series, and feature selection under maximal information coefficient-partial autocorrelation function (MIC-PACF), or grey relational analysis-PACF (GRA-PACF). The results demonstrate that appropriate feature selection methods could significantly improve the performance of static ML models. In contrast, dynamic models effectively leverage inherent capabilities in capturing temporal dynamics within raw multivariate time series, seeing marginal gains with extensive feature engineering compared to no feature selection strategy. The optimal feature selection approach varies based on the ML model and specific landslide, highlighting the importance of case-specific assessments. The findings in this study offer guidance on integrating feature selection techniques with different machine learning models to maximize the robustness and generalizability of data-driven landslide displacement prediction frameworks.

This paper established a numerical model for the structure system in a soil–structure interaction using MATLAB 23.2 and ANSYS 24.1 software and validated the effectiveness and accuracy of a simplified nonlinear calculation model for soil–structure interaction through the numerical simulation results. Meanwhile, a list of key parameters was identified according to their influence on the simplified model, including the free field area, site soil parameters, equivalent soil area, superstructure size and number of stories, and input seismic waves. On this basis, a series of parametric investigations were carried out with the validated simplified model, by varying the selected key parameters. The research findings demonstrated that the simplified calculation model exhibited excellent accuracy and efficiency, and was capable of reflecting the nonlinear response of the structural system. It is applicable to the field of dynamic response analysis of the superstructure, considering soil–structure interaction.

Objectives: This study aimed to explore the potential of full dynamic PET kinetic analysis in assessing amyloid binding and perfusion in the cardiac region using 18F-Florbetapir PET, establishing a quantitative approach in the clinical assessment of cardiac amyloidosis disease. Materials & methods: The distribution volume ratios (DVRs) and the relative transport rate constant (R1), were estimated by a pseudo-simplified reference tissue model (pSRTM2) and pseudo-Logan plot (pLogan plot) with kidney reference for the region of interest-based and voxel-wise-based analyses. The parametric images generated using the pSRTM2 and linear regression with spatially constrained (LRSC) algorithm were then evaluated. Semi-quantitative analyses include standardized uptake value ratios at the early phase (SUVREP, 0.5–5 min) and late phase (SUVRLP, 50–60 min) were also calculated. Results: Ten participants [7 healthy controls (HC) and 3 cardiac amyloidosis (CA) subjects] underwent a 60-min dynamic 18F-Florbetapir PET scan. The DVRs estimated from pSRTM2 and Logan plot were significantly increased (HC vs CA; DVRpSRTM2: 0.95 ± 0.11 vs 2.77 ± 0.42, t’(2.13) = 7.39, P = 0.015; DVRLogan: 0.80 ± 0.12 vs 2.90 ± 0.55, t’(2.08) = 6.56, P = 0.020), and R1 were remarkably decreased in CA groups, as compared to HCs (HC vs CA; 1.08 ± 0.37 vs 0.56 ± 0.10, t’(7.63) = 3.38, P = 0.010). The SUVREP and SUVRLP were highly correlated to R1 (r = 0.97, P

With the large-scale application of composite materials in aircraft structures, the threat of visually invisible damage such as internal delamination of composite materials caused by impact from foreign objects is increasing,therefore, impact event monitoring and impact location identification of composite reinforced structures is essential.In order to verify the engineering validity of the impact localization algorithm, based on the piezoelectric sensing signal of the impact test on the composite large wall plate structure, the localization accuracy of the time-reversal focusing,error function and cross-correlation function impact monitoring algorithms is compared. The results show that, in the monitoring area of 2 360 mm×1 260 mm, the error of the cross-correlation function algorithm is smaller than that of the time-reversal focusing algorithm, and the error of the time-reversal focusing algorithm is larger at the truss, which is not suitable for impact positioning of reinforced structures.

Abstract Active metamaterials with shapes or mechanical properties that can be controlled remotely are promising candidates for soft robots, flexible electronics, and medical applications. However, current active metamaterials often have long response times and short ranges of linear working strains. Here, we demonstrate magnetoactive microlattice metamaterials constructed from 3D-printed, ultra-flexible polymer shells filled with magnetorheological (MR) fluid. Under compressive stress, the magnetorheological fluid develops hydrostatic pressure, allowing for a linear compression strain of more than 30% without buckling. We further show that under a relatively low magnetic field strength (approximately 60 mT), the microlattices can become approximately 200% stiffer than those in a relaxed state, and the energy absorption increases ~16 times. Furthermore, our microlattices showed an ultra-low response time with “field on” and “field off” times of ~200 ms and ~50 ms, respectively. The ability to continuously tune the mechanical properties of these materials in real time make it possible to modulate stress‒strain behavior on demand. Our study provides a new route toward large-scale, highly tunable, and remotely controllable metamaterials with potential applications in wearable exoskeletons, tactile sensors, and medical supports.

Abstract Stretchable ionotronics have drawn increasing attention during the past decade, enabling myriad applications in engineering and biomedicine. However, existing ionotronic sensors suffer from limited sensing capabilities due to simple device structures and poor stability due to the leakage of ingredients. In this study, we rationally design and fabricate a plethora of architected leakage-free ionotronic sensors with multi-mode sensing capabilities, using DLP-based 3D printing and a polyelectrolyte elastomer. We synthesize a photo-polymerizable ionic monomer for the polyelectrolyte elastomer, which is stretchable, transparent, ionically conductive, thermally stable, and leakage-resistant. The printed sensors possess robust interfaces and extraordinary long-term stability. The multi-material 3D printing allows high flexibility in structural design, enabling the sensing of tension, compression, shear, and torsion, with on-demand tailorable sensitivities through elaborate programming of device architectures. Furthermore, we fabricate integrated ionotronic sensors that can perceive different mechanical stimuli simultaneously without mutual signal interferences. We demonstrate a sensing kit consisting of four shear sensors and one compressive sensor, and connect it to a remote-control system that is programmed to wirelessly control the flight of a drone. Multi-material 3D printing of leakage-free polyelectrolyte elastomers paves new avenues for manufacturing stretchable ionotronics by resolving the deficiencies of stability and functionalities simultaneously.

Abstract The spatial correlation pattern of economic resilience is an important proposition for China’s sustainable economic development. This paper measures the economic resilience of 31 provinces in China from 2012 to 2020, and explores the spatial correlation of economic resilience from the overall, group and individual perspectives and its influencing factors. The results show that first, a tightly ordered hierarchy of economic resilience formed in each province of China after 2016. Among them, Jiangsu, Shandong, Guangdong, Hubei, and Shaanxi are the most important clustering points and radiation centers in the spatial correlation framework of economic resilience. Second, being adjacent to marginal and core provinces will maintain the province’s centrality index category to the greatest extent, while being adjacent to sub-core and general provinces leads the province to gain more opportunities for upward transfer. Third, the essence of the interprovincial economic resilience subordination linkage in China is manifested in the aggregation of city clusters or economic circles. The northern economic resilience linkage system with the Bohai Rim as the core contains more provinces but is less stable. Provinces located in the Yangtze River Delta region are the opposite. Fourth, the proximity of geographical location and the difference in human capital level drive the formation of spatial association networks, while the difference in external openness and the difference in physical capital inhibit the formation of networks.

Thick panel origami holds great potential in engineering structures, but conventional fabrication processes limit their design and applications. Here the authors report a multimaterial 3D printing-based design and fabrication strategy for thick-panel origami structures with push-to-pull deformation.

Traditional thermosetting epoxy resins are widely applied in many fields due to their excellent performance. However, stable internal crosslinked networks hinder the repair of epoxy resins damaged during the operation and the recycling of decommissioned epoxy resins. Since vitrimers are epoxy resins that exhibit dynamic covalent bonding, reversible repair properties, and recyclability, they offer a potential solution to this problem. Therefore, by introducing an ester-exchange catalyst, we further introduced disulfide (S–S) bonds to the crosslinked network to construct a vitrimer resin exhibiting double-dynamic bonds, systematically investigated the basic thermodynamic and electrical properties of resins containing different S–S bond contents, and studied the self-healing properties of the possible multispecies and multiscale physical and electrical damages during device operation. Moreover, we investigated the self-healing properties of resins containing different S–S bonding contents. Results showed that the resin exhibited excellent electrical insulation, and the dynamic properties of the resin increased with the increasing number of S–S bonds in the crosslinked network, which considerably increased the repair efficiency and damage repair scale. In addition, the excellent dynamic properties rendered the resin degradable, enabling the non-destructive recycling of valuable materials from the resin matrix and specific processable remodelling and endowed the resin with thermally elastic shape memory properties. This work helps expand the class of vitrimer resins and promotes the application of vitrimers for manufacturing environmentally friendly electrical equipment.

Multimaterial 3D printing using digital light processing (DLP) is challenging because multimaterial switching methods require direct contact onto the printed part to remove residual resin. Here, the authors report a DLP-based centrifugal multimaterial 3D printing method to generate large-volume heterogeneous 3D objects where composition, property and function are programmable at voxel scale.

Multimaterial (MM) 3D printing shows great potential for application in metamaterials, flexible electronics, biomedical devices and robots, since it can seamlessly integrate distinctive materials into one printed structure. Among numerous MM 3D printing technologies, digital light processing (DLP) MM 3D printing is compatible with a wide range of materials from hydrogels to ceramics, and can print MM 3D structures with high resolution, high complexity and fast speed. This paper introduces the fundamental mechanisms of DLP 3D printing, and reviews the recent advances of DLP MM 3D printing technologies with emphasis on material switching methods and material contamination issues. It also summarizes a number of typical examples of DLP MM 3D printing systems developed in the past decade, and introduces their system structures, working principles, material switching methods, residual resin removal methods, printing steps, as well as the representative structures and applications. Finally, we provide perspectives on the directions of the further development of DLP MM 3D printing technology.

Epoxy resins are widely used as insulation materials for power systems and are mainly prepared from petrochemical materials, which have the disadvantage of being non-recyclable and environmentally harmful. In this paper, the maleopimaric acid (MPAc) curing agent was prepared from a renewable resource, rosin, and blended with a petroleum-based curing agent (methylhexahydrophthalic anhydride) to cure bisphenol A epoxy resin. The effects of the blending ratio on the curing characteristics as well as on the thermal, mechanical, and electrical properties of the epoxy resins were examined. From the results obtained, as for thermal properties, the introduction of MPAc enhanced the rigidity, glass transition temperature, and thermal decomposition temperature. As for mechanical properties, the brittleness was increased while the tensile strength and bending strength were weakened. When the mass fraction of MPAc was 20–30 wt%, the electrical properties reached the optimum, meeting the application requirements of electrical equipment. This study shows that using rosin-based curing agent maleicpine acid (MPAc) as a partial replacement for petroleum-based curing agents can make electrical equipment environmentally friendly, demonstrating the potential application prospects of rosin-based epoxy resins.

Abstract Tumor immune microenvironment exerts a profound effect on the population of infiltrating immune cells. Tissue inhibitor of matrix metalloproteinase 1 (TIMP1) is frequently overexpressed in a variety of cells, particularly during inflammation and tissue injury. However, its function in cancer and immunity remains enigmatic. In this study, we find that TIMP1 is substantially up-regulated during tumorigenesis through analyzing cancer bioinformatics databases, which is further confirmed by IHC tissue microarrays of clinical samples. The TIMP1 level is significantly increased in lymphocytes infiltrating the tumors and correlated with cancer progression, particularly in GBM. Notably, we find that the transcriptional factor Sp1 binds to the promoter of TIMP1 and triggers its expression in GBM. Together, our findings suggest that the Sp1-TIMP1 axis can be a potent biomarker for evaluating immune cell infiltration at the tumor sites and therefore, the malignant progression of GBM.

ABSTRACTSmart structures have the advantages of high system integrity and diverse sensing capabilities. However, the labor-intensive and time-consuming fabrication process hinders the large-scale adoption of smart structures. Despite recent attempts to develop sensor-embedded structures using 3D printing technologies, the reported smart structures generally suffer from the complex fabrication process, constrained part size, and limited sensing modality. Herein, we propose a workflow to design and fabricate novel smart structures via multimaterial fused deposition modeling (FDM)-based 3D printing. More specifically, conductive filaments with tailorable mechanical and electrical properties, e.g. piezoresistive effects, were developed. Additionally, the printing process was optimized for processing soft filaments with Young’s modulus around 2 MPa, resolving the issue of filament buckling. Furthermore, the potential applications of the proposed workflow were showcased using three design cases, i.e. biaxial strain sensor, smart tire, and cable-driven soft finger with multiple sensing capabilities. This workflow provides a cost-effective and rapid solution for developing novel smart structures with soft materials.

The alpha and theta frequency brainwave activity in electroencephalogram (EEG) signal is proven to correlate with attention, inhibitory processes, memory, perceptual abilities, and sleep. The decreasing of brainwaves is demonstrated to be the reason of aging and even Alzheimer's disease, so triggering alpha and theta brainwave activity may bring positive behavioral modifications such as promoting health care and a quick sleep. Herein, it is discovered that infrared radiation from multilayer graphene electrothermal film can obviously promote the appearance of alpha and theta brainwaves in the human brain. In particular, the occurrence frequency and duration time of the alpha and theta waves in EEG can be effectively enhanced up to 2.3/2.9 and 3.0/4.1 times, respectively. The comparative effect of different working temperatures and heating materials is systematically investigated, indicating efficient infrared radiation from the multilayer graphene electrothermal film, which coincides with the human‐body thermal‐radiation wavelength range from 7 to 14 μm, may be the main mechanism for this enhancement. The multilayer graphene film electrical heater represents a convenient and surprising way for triggering alpha and theta brainwaves, which has many potential applications in the area of enlarged healthcare requirements.

More and more discoveries have been made about the chronic toxic effects of aluminum, but the specific mechanism of action remains unclear. In this study, we explored the perturbation of aluminum on intestinal microflora and its effects on host and microbial metabolites through a more realistic nutrient absorption model. The microorganisms Turicibacter, Lactobacillus murinus, Lactobacillus_reuteri and Bifidobacterium pseudolongum may be the main targets of the aluminum affecting microbiota. Lysine, proline, putrescine, serotonin and cholesterol may be important metabolites affected by aluminum ions after the interference of intestinal flora composition, leading to abnormal metabolism pathways of amino acids and lipids in the body, and thus promoting inflammation and lesion. The possible mechanisms of aluminum action on the body: (1) Affecting immune cell response, ROS generation and production of a series of pro-inflammatory factors to promote inflammation; (2) Through the disturbance of intestinal microbiota composition structure, change the abundance of metabolites, and then affect amino acid metabolism, lipid metabolism pathways. The joint analysis of multiple omics showed significant difference in microbiome abundance and metabolomics expression between high dose group and the control group.

Abstract Background The COVID-19 pandemic has lasted for more than 1 year, causing far-reaching and unprecedented changes in almost all aspects of society. This study aimed to evaluate the long-term consequences of the COVID-19 pandemic on depression and anxiety, and explore the factors associated with it. Methods A cross-sectional study using an online survey was conducted to assess mental health problems from February 2 to February 9, 2021 by using patient health questionnaire-9 (PHQ-9) and generalized anxiety disorder-7 (GAD-7). The insomnia severity index (ISI), demographic data and COVID-19 related variables were measured by a self-designed questionnaire. The factors associated with depressive and anxiety symptoms were identified by Pearson chi-square test and binary logistic regression analysis. Results In the study that 1171 participants enrolled, the overall prevalence of depressive and anxiety symptoms among general people was 22.6 and 21.4% respectively in the present study. Living alone was a potential risk factor for depressive symptoms, while regular exercises was a potential protective factor. The prevalence of depressive and anxiety symptoms was significantly associated with the severity of insomnia symptoms and the negative feelings about pandemic. Conclusion COVID-19 pandemic- related chronic stress has brought about profound impacts on long-term mental health in the general population. The level of insomnia and a negative attitude towards the pandemic are significantly correlated with unfavorable mental health. However, we failed to found a significant association of age and gender with the mental health symptoms, although they were recognized as well-established risk factors during the outbreak by some other studies. This discrepancy may be because the acute and chronic effects of the pandemic are influenced by different factors, which reminds that more attention should be paid to the intrinsic psychological factors and physical reactions towards COVID-19.

Stretchable strain sensor detects a wide range of strain variation and is therefore a key component in various applications. Unlike traditional ones made of elastomers doped with conductive components or fabricated with liquid conductors, ionically conductive hydrogel-based strain sensors remain conductive under large deformations and are biocompatible. However, dehydration is a challenging issue for the latter. Researchers have developed hydrogel-elastomer-based strain sensors where an elastomer matrix encapsulates a hydrogel circuit to prevent its dehydration. However, the reported multi-step approaches are generally time-consuming. Our group recently reported a multimaterial 3D printing approach that enables fast fabrication of such sensors, yet requires a self-built digital-light-processing-based multimaterial 3D printer. Here, we report a simple projection lithography method to fabricate hydrogel-elastomer-based stretchable strain sensors within 5 minutes. This method only requires a UV projector/lamp with photomasks; the chemicals are commercially available; the protocols for preparing the polymer precursors are friendly to users without chemistry background. Moreover, the manufacturing flexibility allows users to readily pattern the sensor circuit and attach the sensor to a 3D printed soft pneumatic actuator to enable strain sensing on the latter. The proposed approach paves a simple and versatile way to fabricate hydrogel-elastomer-based stretchable strain sensors and flexible electronic devices.

An improved Penzien model is proposed in this paper as a simplified model of soil–pile–structure interaction. The dynamic nonlinearity of soil under earthquake excitation is simulated by ANSYS in a free-field model and added to the original Penzien model. The improved Penzien model uses the finite element software ANSYS 2021 to simulate the dynamic nonlinearity of soil. The improved Penzien model is then used as a simplified calculation model of the numerical substructure. A substructure pseudo-dynamic test based on the improved Penzien model is carried out. The realization of the substructure pseudo-dynamic test verifies the feasibility and effectiveness of this method, which provides a convenient test method for the study of soil–pile–structure interaction in general laboratories. Soil and structure interaction reduces the acceleration of the structure, and the response exhibited a hysteresis phenomenon because of the nonlinear characteristics of the soil. The influences of soil–pile–structure interaction on velocity and displacement are very complex. The conclusions are reasonable, which proves that the substructure pseudo-dynamic test method of soil–pile–structure dynamic interaction using the improved Penzien model is feasible.

ObjectivePrevious studies have revealed that FAT atypical cadherin 1 (FAT1) plays a tumor-suppressive or oncogenic role in a context-dependent manner in various cancers. However, the functions of FAT1 are ambiguous in tumorigenesis owing to inconsistent research in oral squamous cell carcinoma (OSCC). The present study aimed at gaining an insight into the role of FAT1 in the tumor genesis and development.MethodsThe expression, mutant, and survival data analyses were done using data from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database, verified with clinical samples via real-time polymerase chain reaction (qRT-PCR), Western blot (WB), and immunohistochemical (IHC) staining. OSCC cells transfected with siRNA were employed for in vitro assessment in cell proliferation, apoptosis, and migration ability in appropriate ways. The underlying mechanism was explored by RNA sequencing after FAT1 silencing.ResultsOverall, FAT1 significantly increased in OSCC with a poor prognosis outcome. The in vitro experiment showed the promoting effect of FAT1 in the proliferation and migration of OSCC cells. FAT1 can also inhibit both the early and late apoptosis of OSCC cells. RNA-sequencing analysis of FAT1 silencing revealed that the cell cycle, DNA replication, and some core genes (MCM2, MCM5, CCNE1 SPC24, MYBL2, KIF2C) may be the potential mechanism in OSCC.ConclusionsFAT1 may act as an oncogene in OSCC with potential mechanism influencing the cell cycle and DNA repair.

Integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) could simultaneously obtain both functional MRI (fMRI) and 18F-fluorodeoxyglucose (FDG) PET and thus provide multiparametric information for the analysis of brain metabolism. In this study, we aimed to, for the first time, investigate the interplay of simultaneous fMRI and FDG PET scan using a randomized self-control protocol. In total, 24 healthy volunteers underwent PET/MRI scan for 30–40 min after the injection of FDG. A 22-min brain scan was separated into MRI-off mode (without fMRI pulsing) and MRI-on mode (with fMRI pulsing), with each one lasting for 11 min. We calculated the voxel-wise fMRI metrics (regional homogeneity, amplitude of low-frequency fluctuations, fractional amplitude of low-frequency fluctuations, and degree centrality), resting networks, relative standardized uptake value ratios (SUVr), SUVr slope, and regional cerebral metabolic rate of glucose (rCMRGlu) maps. Paired two-sample t-tests were applied to assess the statistical differences between SUVr, SUVr slope, correlation coefficients of fMRI metrics, and rCMRGlu between MRI-off and MRI-on modes, respectively. The voxel-wise whole-brain SUVr revealed no statistical difference (P > 0.05), while the SUVr slope was significantly elevated in sensorimotor, dorsal attention, ventral attention, control, default, and auditory networks (P < 0.05) during fMRI scan. The task-based group independent-component analysis revealed that the most active network components derived from the combined MRI-off and MRI-on static PET images were frontal pole, superior frontal gyrus, middle temporal gyrus, and occipital pole. High correlation coefficients were found among fMRI metrics with rCMRGlu in both MRI-off and MRI-on mode (P < 0.05). Our results systematically evaluated the impact of simultaneous fMRI scan on the quantification of human brain metabolism from an integrated PET/MRI system.

Waveguide problems are fundamental to elastic and acoustic wave propagation, where we are interested in finding the propagation constants and modal patterns of waveguide modes. As the waveguide is assumed uniform in one direction, the original 3-D problem can be converted into a so-called 2.5-D problem by using the Fourier transform in that direction. However, the introduction of elastic metamaterials (EMM) broadens the horizon of this subject, and new features are required in EMM waveguides that cannot be obtained by most traditional waveguide solvers. In this work, a spectral element method (SEM) is developed to simulate the elastic/acoustic waveguide problem in anisotropic media with anisotropic mass density and/or negative index parameters. We design an anisotropic density EMM waveguide with our SEM solver to demonstrate several intriguing phenomena. Comparisons with the traditional finite element method (FEM) for several examples show the significant advantages of the SEM in term of accuracy and efficiency.

Four-dimensional (4D) printing of shape memory polymer (SMP) imparts time responsive properties to 3D structures. Here, the authors explore 4D printing of a SMP in the submicron length scale, extending its applications to nanophononics.

Some cancers such as human breast cancer, prostate cancer, and lung cancer easily metastasize to bone, leading to osteolysis and bone destruction accompanied by a complicated microenvironment. Systemic administration of bisphosphonates (BP) or denosumab is the routine therapy for osteolysis but with non-negligible side effects such as mandibular osteonecrosis and hypocalcemia. Thus, it is imperative to exploit optimized drug delivery systems, and some novel nanotechnology and nanomaterials have opened new horizons for scientists. Targeted and local drug delivery systems can optimize biodistribution depending on nanoparticles (NPs) or microspheres (MS) and implantable biomaterials with the controllable property. Drug delivery kinetics can be optimized by smart and sustained/local drug delivery systems for responsive delivery and sustained delivery. These delicately fabricated drug delivery systems with special matrix, structure, morphology, and modification can minimize unexpected toxicity caused by systemic delivery and achieve desired effects through integrating multiple drugs or multiple functions. This review summarized recent studies about optimized drug delivery systems for the treatment of cancer metastatic osteolysis, aimed at giving some inspiration in designing efficient multifunctional drug delivery systems.

Two-photon polymerization (TPP) is a cutting-edge micro/nanoscale three-dimensional (3D) printing technology based on the principle of two-photon absorption. TPP surpasses the diffraction limit in achieving feature sizes and excels in fabricating intricate 3D micro/nanostructures with exceptional resolution. The concept of 4D entails the fabrication of structures utilizing smart materials capable of undergoing shape, property, or functional changes in response to external stimuli over time. The integration of TPP and 4D printing introduces the possibility of producing responsive structures with micro/nanoscale accuracy, thereby enhancing the capabilities and potential applications of both technologies. This paper comprehensively reviews TPP-based 4D printing technology and its diverse applications. First, the working principles of TPP and its recent advancements are introduced. Second, the optional 4D printing materials suitable for fabrication with TPP are discussed. Finally, this review paper highlights several noteworthy applications of TPP-based 4D printing, including domains such as biomedical microrobots, bioinspired microactuators, autonomous mobile microrobots, transformable devices and robots, as well as anti-counterfeiting microdevices. In conclusion, this paper provides valuable insights into the current status and future prospects of TPP-based 4D printing technology, thereby serving as a guide for researchers and practitioners.

Synthetic aperture radar (SAR) multi‐target interactive motion recognition classifies the type of interactive motion and generates descriptions of the interactive motions at the semantic level by considering the relevance of multi‐target motions. A method for SAR multi‐target interactive motion recognition is proposed, which includes moving target detection, target type recognition, interactive motion feature extraction, and multi‐target interactive motion type recognition. Wavelet thresholding denoising combined with a convolutional neural network (CNN) is proposed for target type recognition. The method performs wavelet thresholding denoising on SAR target images and then uses an eight‐layer CNN named EilNet to achieve target recognition. After target type recognition, a multi‐target interactive motion type recognition method is proposed. A motion feature matrix is constructed for recognition and a four‐layer CNN named FolNet is designed to perform interactive motion type recognition. A motion simulation dataset based on the MSTAR dataset is built, which includes four kinds of interactive motions by two moving targets. The experimental results show that the recognition performance of the authors’ Wavelet + EilNet method for target type recognition and FolNet for multi‐target interactive motion type recognition are both better than other methods. Thus, the proposed method is an effective method for SAR multi‐target interactive motion recognition.

Soft materials exhibiting unique nonlinear mechanical behavior with large deformation are ubiquitous in nature. In addition, there is a type of soft active materials (SAMs) that can undergo large mechanical deformation. In recent years, soft materials have been developed for impactful applications in aerospace, biomedical devices, and soft robots. However, the traditional manufacturing approaches greatly limit the functionality and performance of structures and devices made of soft materials. 3D printing as an emerging advanced manufacturing technology is considered as an ideal tool to manufacture soft materials. Compared with other 3D printing technologies, digital light processing (DLP)-based 3D printing fabricates 3D objects by localized photopolymerization, and is capable of fabricating 3D objects with highly complex geometries and high resolution. Recently, DLP-based 3D printing has demonstrated its excellent compatibility with a variety of soft materials, and is capable of manufacturing these soft materials into 3D structures and devices with complex geometries, high resolution and unique performance. This reviewer article presents a brief but timely introduction to the most recent advances in DLP-based 3D printing of soft materials.

The excitation, rebound, and transport process of hot carriers (HCs) inside dynamic diode (DD) based on insulators has been rarely explored due to the original stereotyped in which it was thought that the insulators are nonconductive. However, the carrier dynamics of DD is totally different from the static diode, which may bring a subverting insight of insulators. Herein, we discovered insulators could be conductive under the framework of DD; the HC process inside the rebounding procedure caused by the disappearance and reestablishment of the built-in electric field at the interface of insulator/semiconductor heterostructure is the main generation mechanism. This type of DD can response fast up to 1 μs to mechanical excitation with an output of ~10 V, showing a wide band frequency response under different input frequencies from 0 to 40 kHz. It can work under extreme environments; various applications like underwater communication network, self-powered sensor/detector in the sea environment, and life health monitoring can be achieved.