Mitochondrial pathway of programmed cell death in Paeonia lactiflora pollen cryopreservation.

Programmed cell death (PCD) is an important factor to reduces the viability of plant germplasm after cryopreservation. However, the pathways by which PCD occurs is not fully understood. To investigate whether there is a mitochondrial pathway for pollen PCD after cryopreservation, the pollen of Paeonia lactiflora two cultivars with different PCD levels after cryopreservation was used as test material and the changes of mitochondrial calcium ions (Ca2+), structure, function and their relationship with PCD were compared. The results showed that compared with fresh pollen, the PCD of 'Feng Huang Nie Pan' was significantly reduced after cryopreservation. Their mitochondrial Ca2+ content decreased by 74.27%, mitochondrial permeability transition pore (MPTP) opening reduced by 25.41%, mitochondrial membrane potential slightly decreased by 5.02%, cardiolipin oxidation decreased by 65.31%, and oxygen consumption remained stable, with a slightly ATP production increase. On the contrary, compared with fresh pollen, 'Zi Feng Chao Yang' showed severe PCD after cryopreservation. The decline in mitochondrial Ca2+-ATPase activity led to an accumulation of excessive Ca2+ within mitochondria, triggering widespread opening of MPTP, significantly affecting mitochondrial respiration and energy synthesis. These results suggest the mitochondrial pathway of PCD exists in pollen cryopreservation.

Underwater smart glasses: A visual-tactile fusion hazard detection system.

Marine activities typically face various risk factors such as marine animal attacks or unexpected collisions. In this paper, we develop underwater smart glasses (USGs) based on visual-tactile fusion for underwater hazard detection in real-time, ensuring operational safety. The proposed USG is composed of the vision module by artificial intelligence (AI)-enabled optical sensing and the tactile module by triboelectric metamaterials-enabled mechanical sensing. The vision module is obtained based on the underwater target detection algorithm you only look once-underwater hazard (YOLO-UH) developed by the dataset to detect toxic marine organisms in the visual field. The tactile module is designed with the kirigami tribo-materials (KTMs) to sensitively detect and warn of collisions outside the visual field. Through numerical simulations, laboratory tests, and real-world experiments, we validated the performance of both modules. The reported USG with its visual-tactile fusion concept enables near-far all-around hazard detection and reduces the danger for divers working underwater.

YOLOX-DG robotic detection systems for large-scale underwater concrete structures.

Large-scale complex underwater concrete structures have structural damage and the traditional damage detection method mostly uses manual identification, which is inaccurate and inefficient. Therefore, robotic detection systems have been proposed to replace manual identification for underwater concrete structures in ocean engineering. However, the highly corrosive and disruptive environment of the ocean poses great difficulties for the application. Here, we develop a manta ray-inspired underwater robot with well controllability to establish the damage datasets of underwater concrete structures, proposing the YOLOX-DG algorithm to improve the damage detection accuracy, and integrating the model into the robotic detection systems for underwater concrete damages. Eventually, the system is used for ocean testing in real applications (i.e., underwater marine harbors around the East China Sea), and satisfactory detection performance is obtained. The reported manta ray-inspired robotic detection system can be used to accurately monitor and analyze the underwater regions.

Cuproptosis-related genes score and its hub gene GCSH: A novel predictor for cholangiocarcinomas prognosis based on RNA seq and experimental analyses.

Background: Recent researches have demonstrated that cuproptosis, a copper-dependent cell death mechanism, is related to tumorigenesis, progression, clinical prognosis, tumor microenvironment, and drug sensitivity. Nevertheless, the function and impact of cuproptosis in cholangiocarcinoma (CCA), remain elusive. Methods: Utilizing data obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA-CHOL) datasets, we conducted subgroup typing of CCA according to cuproptosis-related genes (CRGs) and explored functional differences and prognostic value between groups. A CRG score was established considering clinical prognosis and gene expression. Furthermore, differences in the immune microenvironment, response to immunotherapy, metabolic patterns, and cancer progression characteristics between high- and low-risk groups were examined on the basis of these scores. In vitro experiments validated the function of the key gene glycine cleavage system protein H (GCSH) in cellular and tissues, respectively. Results: Prognostic models established on the basis of subgroup genetic differences achieved satisfactory results in validation. Metabolic-related gene expression levels and tumor microenvironment distribution were significantly different between the high and low CRG groups. GCSH was revealed as the singular prognostic CRG in CCA (HR =6.04; 95% CI: 1.15-31.80). Moreover, inhibition of the cupcoptosis key gene GCSH attenuated the malignant ability of CCA cell lines in vitro, including cell proliferation, migration and invasion, and this function of GCSH may be achieved via JAK-STAT signaling in CCA. Conclusion: The CRG scoring system accurately predicts prognosis and opens up new possibilities for cuproptosis-related therapy for CCA. The cuproptosis key gene GCSH has been preliminarily confirmed as a reliable therapeutic target or prognostic marker for CCA patients.

Lightweight Pneumatically Elastic Backbone Structure with Modular Construction and Nonlinear Interaction for Soft Actuators.

There has been a growing need for soft robots operating various force-sensitive tasks due to their environmental adaptability, satisfactory controllability, and nonlinear mobility unique from rigid robots. It is of desire to further study the system instability and strongly nonlinear interaction phenomenon that are the main influence factors to the actuations of lightweight soft actuators. In this study, we present a design principle on lightweight pneumatically elastic backbone structure (PEBS) with the modular construction for soft actuators, which contains a backbone printed as one piece and a common strip balloon. We build a prototype of a lightweight (<80 g) soft actuator, which can perform bending motions with satisfactory output forces (∼20 times self-weight). Experiments are conducted on the bending effects generated by interactions between the hyperelastic inner balloon and the elastic backbone. We investigated the nonlinear interaction and system instability experimentally, numerically, and parametrically. To overcome them, we further derived a theoretical nonlinear model and a numerical model. Satisfactory agreements are obtained between the numerical, theoretical, and experimental results. The accuracy of the numerical model is fully validated. Parametric studies are conducted on the backbone geometry and stiffness, balloon stiffness, thickness, and diameter. The accurate controllability, operation safety, modularization ability, and collaborative ability of the PEBS are validated by designing PEBS into a soft laryngoscope, a modularized PEBS library for a robotic arm, and a PEBS system that can operate remote surgery. The reported work provides a further applicability potential of soft robotics studies.

Maximizing Triboelectric Nanogenerators by Physics-Informed AI Inverse Design.

Triboelectric nanogenerators offer an environmentally friendly approach to harvesting energy from mechanical excitations. This capability has made them widely sought-after as an efficient, renewable, and sustainable energy source, with the potential to decrease reliance on traditional fossil fuels. However, developing triboelectric nanogenerators with specific output remains a challenge mainly due to the uncertainties associated with their complex designs for real-life applications. Artificial intelligence-enabled inverse design is a powerful tool to realize performance-oriented triboelectric nanogenerators. This is an emerging scientific direction that can address the concerns about the design and optimization of triboelectric nanogenerators leading to a next generation nanogenerator systems. This perspective paper aims at reviewing the principal analysis of triboelectricity, summarizing the current challenges of designing and optimizing triboelectric nanogenerators, and highlighting the physics-informed inverse design strategies to develop triboelectric nanogenerators. Strategic inverse design is particularly discussed in the contexts of expanding the four-mode analytical models by physics-informed artificial intelligence, discovering new conductive and dielectric materials, and optimizing contact interfaces. Various potential development levels of artificial intelligence-enhanced triboelectric nanogenerators are delineated. Finally, the potential of physics-informed artificial intelligence inverse design to propel triboelectric nanogenerators from prototypes to multifunctional intelligent systems for real-life applications is discussed.

Ultra-Stretchable Kirigami Piezo-Metamaterials for Sensing Coupled Large Deformations.

Mechanical metamaterials are known for their prominent mechanical characteristics such as programmable deformation that are due to periodic microstructures. Recent research trends have shifted to utilizing mechanical metamaterials as structural substrates to integrate with functional materials for advanced functionalities beyond mechanical, such as active sensing. This study reports on the ultra-stretchable kirigami piezo-metamaterials (KPM) for sensing coupled large deformations caused by in- and out-of-plane displacements using the lead zirconate titanate (PZT) and barium titanate (BaTiO3 ) composite films. The KPM are fabricated by uniformly compounding and polarizing piezoelectric particles (i.e., PZT and BaTiO3 ) in silicon rubber and structured by cutting the piezoelectric rubbery films into ligaments. Characterizes the electrical properties of the KPM and investigates the bistable mechanical response under the coupled large deformations with the stretching ratio up to 200% strains. Finally, the PZT KPM sensors are integrated into wireless sensing systems for the detection of vehicle tire bulge, and the non-toxic BaTiO3 KPM are applied for human posture monitoring. The reported kirigami piezo-metamaterials open an exciting venue for the control and manipulation of mechanically functional metamaterials for active sensing under complex deformation scenarios in many applications.

Piezo-Wormbots for Continuous Crawling.

Biomimetic soft robots are typically made of soft materials with bioinspired configurations. However, their locomotion is activated and manipulated by externally controlled soft actuators. In this study, piezo-wormbots were developed by automatically triggering the mechanical metamaterial-inspired soft actuator to mimic the continuous crawling of inchworms without manipulation, where crawling was controlled by the deformation of the piezo-wormbots themselves. We designed the flexible piezo-wormbots with an actuator to generate bending deformation under continuous inflation, piezoelectric rubber to automatically create internal excitation voltage to trigger deflation, as well as true legs and prolegs to convert the bending-recovering sequence into continuous crawling. We tailored the actuator to enhance the crawling performance and found that the response was critically affected by the leg pattern, inflation-to-deflation time duration ratio, air pressure, and ground environment. We observed satisfactory locomotion performance for the following tasks (pushing boxes and approaching a predefined target) through accurate self-actuated crawling under up to 51 continuous bending cycles. The maximum crawling velocity of the piezo-wormbots was found to be 16.6 mm/s, resulting in a maximum body length per second (BL/s) of 0.13, which is comparable to those of most natural inchworms (0.1-0.3 BL/s). This study offers new insight into bioinspired soft robotics and expands its biomimetic performance to continuously autonomous locomotion.

The Role of Caspase-11 and Pyroptosis in the Regulation of Inflammation in Peri-Implantitis.

Peri-implantitis is an important cause of oral implant failure. In the past, TLR4 and TLR2 in the Toll-like family were generally considered as the key immune recognition receptors regulating peri-implantitis. However, under the guidance of this theory, there are still some unexplainable peri-implantitis symptoms. With the discovery of novel intracellular LPS receptor Caspase-11, a new understanding of inflammatory signaling and immune regulation in the development of peri-implantitis has been gained. However, the regulatory role of Caspase-11 in peri-implantitis and its crosstalk with the TLR4 pathway remain unclear. The therapeutic effect of drugs targeting Caspase-11 on peri-implantitis is still in its early stages. In view of this situation, this paper reviews the possible role of Caspase-11 in peri-implant inflammation, elaborated the entry process of LPS and the activation mechanism of Caspase-11, and analyzes the differences in Caspase-11 between commonly studied animals, mice and humans. The current research hotspots and challenges are also analyzed to provide new insights and ideas for researchers.

The role of hydrodynamics for the spatial distribution of high-temperature hydrothermal vent-endemic fauna in the deep ocean environment.

Active hydrothermal vents provide the surrounding submarine environment with substantial amounts of matter and energy, thus serving as important habitats for diverse megabenthic communities in the deep ocean and constituting a unique, highly productive chemosynthetic ecosystem on Earth. Vent-endemic biological communities gather near the venting site and are usually not found beyond a distance of the order of 100 m from the vent. This is surprising because one would actually expect matter ejected from high-temperature vents, which generate highly turbulent buoyancy plumes, to be suspended and carried far away by the plume flows and deep-sea currents. Here, we study this problem from a fluid dynamics perspective by simulating the vent hydrodynamics using a numerical model that couples the plume flow with induced matter and energy transport. We find that both low- and high-temperature vents deposit most vent matter relatively close to the plume. In particular, the tendency of turbulent buoyancy plumes to carry matter far away is strongly counteracted by generated entrainment flows back into the plume stem. The deposition ranges of organic and inorganic hydrothermal particles obtained from the simulations for various natural high-temperature vents are consistent with the observed maximum spatial extent of biological communities, evidencing that plume hydrodynamics exercises strong control over the spatial distribution of vent-endemic fauna. While other factors affecting the spatial distribution of vent-endemic fauna, such as geology and geochemistry, are site-specific, the main physical features of plume hydrodynamics unraveled in this study are largely site-unspecific and therefore universal across vent sites on Earth.

Mechanical metamaterials and beyond.

Mechanical metamaterials enable the creation of structural materials with unprecedented mechanical properties. However, thus far, research on mechanical metamaterials has focused on passive mechanical metamaterials and the tunability of their mechanical properties. Deep integration of multifunctionality, sensing, electrical actuation, information processing, and advancing data-driven designs are grand challenges in the mechanical metamaterials community that could lead to truly intelligent mechanical metamaterials. In this perspective, we provide an overview of mechanical metamaterials within and beyond their classical mechanical functionalities. We discuss various aspects of data-driven approaches for inverse design and optimization of multifunctional mechanical metamaterials. Our aim is to provide new roadmaps for design and discovery of next-generation active and responsive mechanical metamaterials that can interact with the surrounding environment and adapt to various conditions while inheriting all outstanding mechanical features of classical mechanical metamaterials. Next, we deliberate the emerging mechanical metamaterials with specific functionalities to design informative and scientific intelligent devices. We highlight open challenges ahead of mechanical metamaterial systems at the component and integration levels and their transition into the domain of application beyond their mechanical capabilities.

Skin-Contact Triboelectric Nanogenerator for Energy Harvesting and Motion Sensing: Principles, Challenges, and Perspectives.

Energy harvesting has become an increasingly important field of research as the demand for portable and wearable devices continues to grow. Skin-contact triboelectric nanogenerator (TENG) technology has emerged as a promising solution for energy harvesting and motion sensing. This review paper provides a detailed overview of skin-contact TENG technology, covering its principles, challenges, and perspectives. The introduction begins by defining skin-contact TENG and explaining the importance of energy harvesting and motion sensing. The principles of skin-contact TENG are explored, including the triboelectric effect and the materials used for energy harvesting. The working mechanism of skin-contact TENG is also discussed. This study then moves onto the applications of skin-contact TENG, focusing on energy harvesting for wearable devices and motion sensing for healthcare monitoring. Furthermore, the integration of skin-contact TENG technology with other technologies is discussed to highlight its versatility. The challenges in skin-contact TENG technology are then highlighted, which include sensitivity to environmental factors, such as humidity and temperature, biocompatibility and safety concerns, and durability and reliability issues. This section of the paper provides a comprehensive evaluation of the technological limitations that must be considered when designing skin-contact TENGs. In the Perspectives and Future Directions section, this review paper highlights various advancements in materials and design, as well as the potential for commercialization. Additionally, the potential impact of skin-contact TENG technology on the energy and healthcare industries is discussed.

Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course.

As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI prediction models focus on the development and optimization of the accuracy of AI algorithms rather than applying AI models to provide student with in-time and continuous feedback and improve the students' learning quality. To fill this gap, this research integrated an AI performance prediction model with learning analytics approaches with a goal to improve student learning effects in a collaborative learning context. Quasi-experimental research was conducted in an online engineering course to examine the differences of students' collaborative learning effect with and without the support of the integrated approach. Results showed that the integrated approach increased student engagement, improved collaborative learning performances, and strengthen student satisfactions about learning. This research made contributions to proposing an integrated approach of AI models and learning analytics (LA) feedback and providing paradigmatic implications for future development of AI-driven learning analytics.

Origami Tribo-Metamaterials with Mechanoelectrical Multistability.

The emerging mechanical functional metamaterials reported with promising mechanoelectrical characteristics bring increasing attention to structurally functional materials. It is essential to deploy mechanical metamaterials in energy materials for effective triggering and controllable mechanoelectrical response. This study reports origami tribo-metamaterials (OTMs) that design triboelectric materials in the origami-enabled, tubular metamaterials. The octagonal, hexagonal, and conical origami units are deployed as the metamaterial substrates to trigger the triboelectric pairs for mechanoelectrical multistability. For the octagonal OTM configuration with the triboelectric pair of fluorinated ethylene propylene-paper, the peak open-circuit voltage, short-circuit current, and transferred charge are obtained as 206.4 V, 4.66 µA, and 0.38 µC, respectively, and the maximum instantaneous output power density is 0.96 µW/cm2 with the load resistance of 20 MΩ. The OTM takes advantage of the origami metamaterials to obtain the multistable force-displacement response as effective stimuli for the triboelectric materials, which leads to tunable mechanoelectrical performance for speed and weight sensing and energy harvesting. The proposed OTM not only offers a strategy to structurally design energy materials to achieve desirable mechanoelectrical response, but also provides a guideline for the applications of mechanical functional metamaterials in practice.

Copebot: Underwater Soft Robot with Copepod-Like Locomotion.

It has been a great challenge to develop robots that are able to perform complex movement patterns with high speed and, simultaneously, high accuracy. Copepods are animals found in freshwater and saltwater habitats that can have extremely fast escape responses when a predator is sensed by performing explosive curved jumps. In this study, we present a design and build prototypes of a combustion-driven underwater soft robot, the "copebot," which, similar to copepods, is able to accurately reach nearby predefined locations in space within a single curved jump. Because of an improved thrust force transmission unit, causing a large initial acceleration peak (850 body length·s-2), the copebot is eight times faster than previous combustion-driven underwater soft robots, while able to perform a complete 360° rotation during the jump. Thrusts generated by the copebot are tested to quantitatively determine the actuation performance, and parametric studies are conducted to investigate the sensitivity of the kinematic performance of the copebot to the input parameters. We demonstrate the utility of our design by building a prototype that rapidly jumps out of the water, accurately lands on its feet on a small platform, wirelessly transmits data, and jumps back into the water. Our copebot design opens the way toward high-performance biomimetic robots for multifunctional applications.

The value of urinary interleukin-18 in predicting acute kidney injury: a systematic review and meta-analysis.

AIMS: The aim of this study was to systematically review relevant studies to evaluate the value of urinary interleukin-18 (uIL-18) in predicting acute kidney injury (AKI). METHODS: A comprehensive search of PubMed, Medline, Embase, and Cochrane Library was conducted for literature published up to 1 August 2022. Quality Assessment Tool for Diagnostic Accuracy Studies-2 (QUADAS-2) was applied to assess the literature quality. Then, relevant data were extracted from each eligible study and a random-effects regression model was utilized to pool sensitivity, specificity, and construct summary receiver operating characteristic (SROC) and area under curve (AUC). RESULTS: Twenty-six studies with 7183 patients were enrolled and relevant information was extracted. The estimated sensitivity and specificity of uIL-18 in the diagnosis of AKI were 0.64 (95% confidence interval (CI): 0.54-0.73) and 0.77 (95%CI: 0.71-0.83), respectively. The pooled diagnostic odds ratio (DOR) was 6.08 (95%CI: 3.63-10.18), and the AUC of uIL-18 in predicting AKI was 0.78 (95%CI: 0.74-0.81). Subgroup analysis showed that uIL-18 in pediatric patients was more effective in predicting AKI than in adults (DOR: 7.33 versus 5.75; AUC: 0.81 versus 0.77). CONCLUSIONS: Urinary IL-18 could be a relatively good biomarker with moderate predictive value for AKI, especially in pediatric patients. However, further research and clinical settings are still needed to validate our findings.

Bioinspired Soft Robotics: How Do We Learn From Creatures?

Soft robotics has opened a unique path to flexibility and environmental adaptability, learning from nature and reproducing biological behaviors. Nature implies answers for how to apply robots to real life. To find out how we learn from creatures to design and apply soft robots, in this Review, we propose a classification method to summarize soft robots based on different functions of biological systems: self-growing, self-healing, self-responsive, and self-circulatory. The bio-function based classification logic is presented to explain why we learn from creatures. State-of-art technologies, characteristics, pros, cons, challenges, and potential applications of these categories are analyzed to illustrate what we learned from creatures. By intersecting these categories, the existing and potential bio-inspired applications are overviewed and outlooked to finally find the answer, that is, how we learn from creatures.

Emerging Deep-Sea Smart Composites: Advent, Performance, and Future Trends.

To solve the global shortage of land and offshore resources, the development of deep-sea resources has become a popular topic in recent decades. Deep-sea composites are widely used materials in abyssal resources extraction, and corresponding marine exploration vehicles and monitoring devices for deep-sea engineering. This article firstly reviews the existing research results and limitations of marine composites and equipment or devices used for resource extraction. By combining the research progress of smart composites, deep-sea smart composite materials with the three characteristics of self-diagnosis, self-healing, and self-powered are proposed and relevant studies are summarized. Finally, the review summarizes research challenges for the materials, and looks forward to the development of new composites and their practical application in conjunction with the progress of composites disciplines and AI techniques.

Higher Blood Cadmium Concentration Is Associated With Increased Likelihood of Abdominal Aortic Calcification.

Aims: This study aimed to evaluate the association between blood cadmium concentration (BCC) and abdominal aortic calcification (AAC) in adults aged ≥40 years in the United States. Methods: Data were obtained from the 2013-2014 National Health and Nutrition Examination Survey (NHANES). Participants without data about BCC and AAC scores were excluded. BCC was directly measured using inductively coupled plasma mass spectrometry (ICP-MS). AAC scores were quantified by the Kauppila scoring system, and severe AAC was defined as an AAC score >6. Weighted multivariable regression analysis and subgroup analysis were conducted to explore the independent relationship between cadmium exposure with AAC scores and severe AAC. Results: A total of 1,530 participants were included with an average BCC of 0.47 ± 0.02 µg/L and AAC score of 1.40 ± 0.10 [mean ± standard error (SE)]. The prevalence of severe AAC was 7.96% in the whole subjects and increased with the higher BCC tertiles (Tertile 1: 4.74%, Tertile 2: 9.83%, and Tertile 3: 10.17%; p = 0.0395). We observed a significant positive association between BCC and the AAC score (ß = 0.16, 95% CI: 0.01~0.30) and an increased risk of severe AAC [odds ratio (OR) = 1.45; 95% CI: 1.03~2.04]. Subgroup analysis and interaction tests revealed that there was no dependence for the association between BCC and AAC. Conclusion: Blood cadmium concentration was associated with a higher AAC score and an increased likelihood of severe AAC in adults in the United States. Cadmium exposure is a risk factor for AAC, and attention should be given to the management of blood cadmium.

Magnetic capsulate triboelectric nanogenerators.

Triboelectric nanogenerators have received significant research attention in recent years. Structural design plays a critical role in improving the energy harvesting performance of triboelectric nanogenerators. Here, we develop the magnetic capsulate triboelectric nanogenerators (MC-TENG) for energy harvesting under undesirable mechanical excitations. The capsulate TENG are designed to be driven by an oscillation-triggered magnetic force in a holding frame to generate electrical power due to the principle of the freestanding triboelectrification. Experimental and numerical studies are conducted to investigate the electrical performance of MC-TENG under cyclic loading in three energy harvesting modes. The results indicate that the energy harvesting performance of the MC-TENG is significantly affected by the structure of the capsulate TENG. The copper MC-TENG systems are found to be the most effective design that generates the maximum mode of the voltage range is 4 V in the closed-circuit with the resistance of 10 GΩ. The proposed MC-TENG concept provides an effective method to harvest electrical energy from low-frequency and low-amplitude oscillations such as ocean wave.