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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.

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

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.

4D printing enables 3D printed structures to change shape over "time" in response to environmental stimulus. Because of relatively high modulus, shape memory polymers (SMPs) have been widely used for 4D printing. However, most SMPs for 4D printing are thermosets, which only have one permanent shape. Despite the efforts that implement covalent adaptable networks (CANs) into SMPs to achieve shape reconfigurability, weak thermomechanical properties of the current CAN-SMPs exclude them from practical applications. Here, we report reconfigurable 4D printing via mechanically robust CAN-SMPs (MRC-SMPs), which have high deformability at both programming and reconfiguration temperatures (>1400%), high Tg (75°C), and high room temperature modulus (1.06 GPa). The high printability for DLP high-resolution 3D printing allows MRC-SMPs to create highly complex SMP 3D structures that can be reconfigured multiple times under large deformation. The demonstrations show that the reconfigurable 4D printing allows one printed SMP structure to fulfill multiple tasks.. [ABSTRACT FROM AUTHOR]