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Herein, this study contributes significantly to the advancement of continuum manipulators in two main aspects. First, a modularization concept and a hybrid actuation scheme to create a novel origami continuum manipulator with exceptional deformability are introduced. Second, an accurate model and framework for the forward and inverse kinematic analysis of origami manipulators are proposed. Specifically, each origami manipulator module can achieve axial extension and bending deformation by coordinated actuation of shape memory alloy (SMA) and pneumatic muscles, and the manipulator's end is equipped with a deformable gripper based on waterbomb origami and actuated by SMA. Through careful consideration of the self‐weight and torque balance, an accurate kinematic model based on the Denavit–Hartenberg method is established, which enables one to effectively predict the reachable extreme positions and spatial poses of the manipulator and solve the inverse kinematics using a genetic algorithm. Comprehensive experiments are conducted to validate the design's rationality and model's accuracy. In these tests, the rich spatial configurations are not only demonstrated that can be achieved by integrating hybrid actuators with origami modules but also the accuracy and reliability of the kinematic model are confirmed, opening up possibilities for the advancement and application of origami‐inspired robotics in various fields. [ABSTRACT FROM AUTHOR]

Recent advances in multistable metamaterials reveal a link between structural configuration transition and Boolean logic, heralding a new generation of computationally capable intelligent materials. To enable higher‐level computation, existing computational frameworks require the integration of large‐scale networked logic gates, which places demanding requirements on the fabrication of materials counterparts and the propagation of signals. Inspired by cellular automata, a novel computational framework based on multistable origami metamaterials by incorporating reservoir computing is proposed, which can accomplish high‐level computation tasks without the need to construct a logic gate network. This approach thus eliminates the demanding requirements for the fabrication of materials and signal propagation when constructing large‐scale networks for high‐level computation in conventional mechanical logic. Using the multistable stacked Miura‐origami metamaterial as a validation platform, digit recognition is experimentally implemented by a single actuator. Moreover, complex tasks, such as handwriting recognition and 5‐bit memory tasks, are also shown to be feasible with the new computation framework. The research represents a significant advancement in developing a new generation of intelligent materials with advanced computational capabilities. With continued research and development, these materials can have a transformative impact on a wide range of fields, from computational science to material mechano‐intelligence technology and beyond. [ABSTRACT FROM AUTHOR]

Annelids such as earthworms are considered to have central pattern generators (CPGs) that generate rhythms in neural circuits to coordinate the deformation of body segments for effective locomotion. At present, the states of earthworm‐like robot segments are often assigned holistically and artificially by mimicking the earthworms' retrograde peristalsis wave, which is unable to adapt their gaits for variable environments and tasks. This motivates the authors to extend the bioinspired research from morphology to neurobiology by mimicking the CPG to build a versatile framework for spontaneous motion control. Here, the spatiotemporal dynamics is exploited from the coupled Hopf oscillators to not only unify the two existing gait generators for restoring temporal‐symmetric phase‐coordinated gaits and discrete gaits but also generate novel temporal‐asymmetric phase‐coordinated gaits. Theoretical and experimental tests consistently confirm that the introduction of temporal asymmetry improves the robot's locomotion performance. The CPG‐based controller also enables seamless online switching of locomotion gaits to avoid abrupt changes, sharp stops, and starts, thus improving the robot's adaptability in variable working scenarios. [ABSTRACT FROM AUTHOR]

The exploitation of new fungicides and the discovery of action targets are effective ways to solve the problem of resistance, and structural optimization of natural products has become an resultful method to discover lead compounds. In this work, in conjunction with the structures of the fungicidal lead compounds h‐I‐9, X‐I‐3, and X‐II‐5 found in our previous project, waltherione F‐derived diamide compounds were synthesized and characterized by 1H NMR, 13C NMR, and HRMS. The biological assays suggested that the target compounds exhibited weak to good fungicidal activity against the tested pathogens, while most of the target compounds displayed high cellular cytotoxicity against Hela cells. The investigation of accidentally discovered fluorescence characteristics revealed that the compound I‐1 exhibited the most vigorous fluorescence intensity at 350 nm, which was significantly higher than that of I‐3 at 225 nm and was further elucidated by density functional theory (DFT) calculations. Overall, the above results would provide theoretical guidance for the design of active target molecules and the development of fluorescent probes. [ABSTRACT FROM AUTHOR]

Transitions of multistability in materials are exploited for various functions and applications, such as spectral gap tuning, impact energy trapping, and wave steering. However, a fundamental and comprehensive understanding of the transitions, either quasistatic or dynamic transitions, has not yet been acquired, especially in terms of the sequence predictability and tailoring mechanisms. This research, utilizing the stacked Miura‐ori‐variant (SMOV) structure that has multistable shape reconfigurability as a platform, uncovers the deep knowledge of quasistatic and dynamic transitions and proposes the corresponding versatile formation and tuning of mechanical logic gates. Through theoretical, numerical, and experimental means, discriminative and deterministic quasistatic transition sequences, including reversible and irreversible ones, are uncovered, where they constitute a transition map that is editable upon adjusting the design parameters. Via applying dynamic excitations and tailoring the excitation conditions, reversible transitions between all stable configurations become attainable, generating a fully connected transition map. Benefiting from the nonlinearity of the quasistatic and dynamic transitions, basic and compound mechanical logic gates are achieved. The versatility of the scheme is demonstrated using a single SMOV to realize different complex logic operations without increasing structural complexity, showing its unique computing power and inspiring the avenue for efficient physical intelligence. [ABSTRACT FROM AUTHOR]

Structural optimization based on natural products is an important and effective way to discover new green pesticides. Here, two series of amide derivatives based on sinapic acid and mycophenolic acid were designed in combination with the fungicidal natural product piperlongumine and synthesized by preparing the carboxylic acid into acyl chloride and then reacting with the corresponding aromatic amines, respectively. The resulting structures were successively characterized by 1H NMR, 13 C NMR, and HRMS. The crystal structures of molecules I-4 and II-5 were analyzed for structure validation. The in vitro inhibitory activity indicated that most of the target products exhibited fungicidal activity equivalent to or even better than fluopyram against Physalospora piricola. The in vivo fungicidal activity demonstrated that the compounds I-5 and II-4 displayed almost the same preventative activity as carbendazim and fluopyram at 200 μg mL−1. The TEM observation revealed that the fungicidal activity of the target molecules against Physalospora piricola may be due to the influence on the mitochondria in the cell structure. These results will provide valuable theoretical guidance for developing the new green fungicides. [ABSTRACT FROM AUTHOR]

Lung cancer is primarily caused by cigarette smoking and the leading cancer killer in the USA and across the world. Early detection of lung cancer by low-dose CT (LDCT) can reduce the mortality. However, LDCT dramatically increases the number of indeterminate pulmonary nodules (PNs), leading to overdiagnosis. Having a definitive preoperative diagnosis of malignant PNs is clinically important. Using microarray and droplet digital PCR to directly profile plasma miRNA expressions of 135 patients with PNs, we identified 11 plasma miRNAs that displayed a significant difference between patients with malignant versus benign PNs. Using multivariate logistic regression analysis of the molecular results and clinical/radiological characteristics, we developed an integrated classifier comprising two miRNA biomarkers and one radiological characteristic for distinguishing malignant from benign PNs. The classifier had 89.9% sensitivity and 90.9% specificity, being significantly higher compared with the biomarkers or clinical/radiological characteristics alone (all p < 0.05). The classifier was validated in two independent sets of patients. We have for the first time shown that the integration of plasma biomarkers and radiological characteristics could more accurately identify lung cancer among indeterminate PNs. Future use of the classifier could spare individuals with benign growths from the harmful diagnostic procedures, while allowing effective treatments to be immediately initiated for lung cancer, thereby reduces the mortality and cost. Nevertheless, further prospective validation of this classifier is warranted. [ABSTRACT FROM AUTHOR]

Adenocarcinoma is the most common type of lung cancer, the leading cause of cancer deaths in the world. Early detection is the key to improve the survival of lung adenocarcinoma patients. We have previously shown that microRNAs (miRNAs) were stably present in sputum and could be applied to diagnosis of lung cancer. The aim of our study was to develop a panel of miRNAs that can be used as highly sensitive and specific sputum markers for early detection of lung adenocarcinoma. Our study contained 3 phases: ( i) marker discovery using miRNA profiling on paired normal and tumor lung tissues from 20 patients with lung adenocarcinoma; ( ii) marker optimization by real-time reverse transcription-quantitative polymerase chain reaction on sputum of a case-control cohort consisting of 36 cancer patients and 36 health individuals and ( iii) validation on an independent set of 64 lung cancer patients and 58 cancer-free subjects. From the surgical tissues, 7 miRNAs with significantly altered expression were identified, of which '4' were overexpressed and '3' were underexpressed in all 20 tumors. On the sputum samples of the case-control cohort, 4 ( miR-21, miR-486, miR-375 and miR-200b) of the 7 miRNAs were selected, which in combination produced the best prediction in distinguishing lung adenocarcinoma patients from normal subjects with 80.6% sensitivity and 91.7% specificity. Validation of the marker panel in the independent populations confirmed the sensitivity and specificity that provided a significant improvement over any single one alone. The sputum markers demonstrated the potential of translation to laboratory settings for improving the early detection of lung adenocarcinoma. [ABSTRACT FROM AUTHOR]