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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., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Structure optimization based on natural products has become an effective way to develop new green fungicides. In this project, thirty-two novel NPs-derived hydrazide compounds were designed and synthesized by introducing the bioactive hydrazide substructure into sinapic acid and mycophenolic acid. The fungicidal bioassays indicated that the obtained hydrazide compounds showed excellent and selective fungicidal activity against specific pathogens, especially compounds C8 , D7 , and D8 with EC 50 values of 0.63, 0.56, and 0.43 μg mL -1 against M. oryzae , respectively. SAR indicated that the introduction of 4-fluoro, 4-chloro, and 2,4-difluoro groups was conducive to improving the fungicidal activity, while the extension of the hydrazide bridge would affect the selectivity for inhibitory activity. Subsequently, the effects of hydrazide compounds on rice seedling and zebrafish growth were also investigated. The fungicidal mechanism implied that treatment with compound B4 would cause significant changes in metabolites of plasma membrane-related linolenic acid metabolism, arachidonic acid metabolism, and α-linolenic acid metabolism pathways, which further led to the wrinkled hyphae and the blurred plasma membrane and cytoplasm. Finally, the frontier molecular orbitals and charge distribution were calculated to analyze the differences in bioactivity from a structural perspective. These results provide important guidance for the development and practical application of novel fungicides.

As a widely consumed spice and traditional Chinese medicine, Zingiber officinale Roscoe (ginger) has been used in the treatment of nausea, coughs, and colds. In this article, 18 new glycosides ( 1 - 18 ) and six known analogues ( 19 - 24 ) were isolated from the peel of ginger. The planar structures of these compounds were determined by using HR-ESI-MS and extensive spectroscopic techniques (UV, IR, 1D-NMR, and 2D-NMR). Their relative and absolute configurations of the stereogenic centers in the new natural products were determined by analysis of NMR data, using a quantum mechanical NMR approach and time-dependent density functional theory based electronic circular dichroism calculations. The renal fibrosis activities of the isolated natural products together with those of 6-gingerol (6-Gi), 8-gingerol (8-Gi), and 10-gingerol (10-Gi) were evaluated in TGF-β1 induced NRK-52E cells. Compounds 9 , 10 , 15 , 22 - 24 , 6-Gi, 8-Gi, and 10-Gi were found to be active toward extracellular matrix, indicating that they have potential renal fibrosis activities.

In this project, quinoline and quinolone-containing hydrazide compounds were designed and synthesized by introducing a bioactive hydrazide group into the skeleton of waltherione F. The fungicidal activity revealed that some hydrazide compounds exhibited excellent and broad-spectrum fungicidal activity; especially, compounds E8 , E12 , and E16 showed more than 90% or even 100% inhibition rates against most pathogens at 50 μg·mL -1 . The fungicidal mechanism indicated that compound E8 may affect the normal function of the plasma membrane, further generating changes in the morphology and subcellular structure of mycelia. Simultaneously, Fusarium graminearum may resist the E8 -treated stress through the metabolic pathways related to l-glutamate, l-glutamine, and glutathione. Finally, the effect of compound E8 on wheat seedling's growth and the toxicity to zebrafish were accomplished. These results will provide important guidance to discover novel fungicidal lead compounds and explore new targets, which are effective ways to alleviate the increasingly severe drug resistance.

Hydrazides are present in many bioactive molecules and exhibit a variety of biological activities, such as insecticidal, herbicidal, antifungal, antitumor, and antiviral effects. In this Review, we review the application of hydrazide and its derived structures in the agricultural fungicidal field, including monohydrazides, diacylhydrazines, hydrazide-hydrazones, and sulfonyl hydrazides. In addition, the antifungal mechanism of action of the hydrazide derivatives was analyzed and summarized, mainly involving succinate dehydrogenase inhibitors, laccase inhibitors, and targeting plasma membranes. Finally, based on the structural analysis of the novel fungicidal lead compounds, the structure-activity relationship of the hydrazide derivatives was constructed and the development trend of hydrazide structures in fungicidal applications was prospected. It is hoped that this Review can provide some significant guidance for the development of new hydrazide fungicides in the future.

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., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Background and Aim: Acute-on-chronic liver failure (ACLF) has a high mortality rate. The role of granulocyte colony-stimulating factor (G-CSF) in ACLF remains controversial. Monocytes/macrophages are core immune cells, which are involved in the initiation and progression of liver failure; however, the effect of G-CSF on monocytes/macrophages is unclear. The study aimed to verify the clinical efficacy of G-CSF and explore the effect of it on monocytes in hepatitis B virus (HBV)-related ACLF (HBV-ACLF) paitents., Methods: We performed a large randomized controlled clinical trial for the treatment of HBV-ACLF using G-CSF. A total of 111 patients with HBV-ACLF were prospectively randomized into the G-CSF group (5 μg/kg G-CSF every day for 6 days, then every other day until day 18) or the control group (standard therapy). All participants were followed up for at least 180 days. The relationship between monocyte count and mortality risk was analyzed. The effect of G-CSF on the phenotype and function of monocytes from patients with HBV-ACLF was evaluated using flow cytometry in vivo and in vitro experiments., Results: The survival probability of the G-CSF group at 180 days was higher than that of the control group (72.2% vs. 53.8%, P = 0.0142). In the G-CSF-treated group, the monocyte counts on days 0 and 7 were independently associated with an evaluated mortality risk in the fully adjusted model (Model 3) [at day 0: hazard ratio (HR) 95% confidence interval (CI): 15.48 (3.60, 66.66), P = 0.0002; at day 7: HR (95% CI): 1.10 (0.50, 2.43), P =0.8080]. Further analysis showed that after treatment with G-CSF in HBV-ACLF patients, the expression of M1-like markers (HLA-DR and CD86) in monocytes decreased (HLA-DR: P = 0.0148; CD86: P = 0.0764). The expression of MerTK (M2-like marker) increased ( P = 0.0002). The secretion of TNF-α, IL-6, and IL-10 from monocytes decreased without lipopolysaccharide (LPS) stimulation (TNF-α: P < 0.0001; IL-6: P = 0.0025; IL-10: P = 0.0004) or with LPS stimulation (TNF-α: P = 0.0439; P = 0.0611; IL-10: P = 0.0099). Similar effects were observed in vitro experiments., Conclusion: G-CSF therapy confers a survival benefit to patients with HBV-ACLF. G-CSF can promote the anti-inflammatory/pro-restorative phenotype (M2-like) transition of monocytes, which may contribute to the recovery of ACLF. Clinical Trial Registration Number: ClinicalTrials.gov, identifier (NCT02331745)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tong, Wang, Xu, Wan, Fang, Chen, Mu, Liu, Chen, Su, Liu, Li, Huang and Hu.)

Self-locking origami structures are characterized by their piecewise linear constitutive relations between force and deformation, which, in practice, are always completely opaque and unmeasurable: the number of piecewise segments, the positions of non-smooth points, and the linear parameters of each segment are unknown a priori. However, acquiring this information is of fundamental importance for understanding the origami structure's dynamic folding process and predicting its dynamic behaviors. This, therefore, arouses our interest in adopting a dynamical identification process to determine the model and to estimate the parameters. In this research, based on the piecewise linear assumption, a physically-interpretable neural-fuzzy network is built to correlate the measured input and output data. Unlike the conventional approaches, the constructed neural network possesses specific physical meaning of its components: the number of neurons relates to the number of piecewise segments, the coefficients of the local linear models relate to the parameters of the constitutive relations, and the validity functions relate to the positions of non-smooth points. By addressing several examples with different backgrounds, the network's underlying data training methods are illustrated, including the local linear optimization for linear parameters, nested optimization for nonlinear partitions, and Local Linear Model Tree optimization for model selection. Noting that the tackled origami problem holds strong universality in terms of the unknown piecewise characteristics, the proposed approach would thus provide an effective, generic, and physically significant means for handling piecewise linear dynamical systems and meanwhile bring fresh vitality to the artificial neural network research., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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., (© 2017 UICC.)

Lung cancer early detection by low-dose computed tomography (LDCT) can reduce the mortality. However, LDCT increases the number of indeterminate pulmonary nodules (PNs), whereas 95% of the PNs are ultimately false positives. Modalities for specifically distinguishing between malignant and benign PNs are urgently needed. We previously identified a panel of peripheral blood mononucleated cell (PBMC)-miRNA (miRs-19b-3p and -29b-3p) biomarkers for lung cancer. This study aimed to evaluate efficacy of integrating biomarkers and clinical and radiological characteristics of smokers for differentiating malignant from benign PNs. We analyzed expression of 2 miRNAs (miRs-19b-3p and -29b-3p) in PBMCs of a training set of 137 individuals with PNs. We used multivariate logistic regression analysis to develop a prediction model based on the biomarkers, radiographic features of PNs, and clinical characteristics of smokers for identifying malignant PNs. The performance of the prediction model was validated in a testing set of 111 subjects with PNs. A prediction model comprising the two biomarkers, spiculation of PNs and smoking pack-year, was developed that had 0.91 area under the curve of the receiver operating characteristic for distinguishing malignant from benign PNs. The prediction model yielded higher sensitivity (80.3% vs 72.6%) and specificity (89.4% vs 81.9%) compared with the biomarkers used alone (all P<.05). The performance of the prediction model for malignant PNs was confirmed in the validation set. We have for the first time demonstrated that the integration of biomarkers and clinical and radiological characteristics could efficiently identify lung cancer among indeterminate PNs., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

A generic degree-4 vertex (4-vertex) origami possesses one continuous degree-of-freedom for rigid folding, and this folding process can be stopped when two of its facets bind together. Such facet-binding will induce self-locking so that the overall structure stays at a pre-specified configuration without additional locking elements or actuators. Self-locking offers many promising properties, such as programmable deformation ranges and piecewise stiffness jumps, that could significantly advance many adaptive structural systems. However, despite its excellent potential, the origami self-locking features have not been well studied, understood, and used. To advance the state of the art, this research conducts a comprehensive investigation on the principles of achieving and harnessing self-locking in 4-vertex origami structures. Especially, for the first time, this study expands the 4-vertex structure construction from single-component to dual-component designs and investigates their self-locking behaviours. By exploiting various tessellation designs, this research discovers that the dual-component designs offer the origami structures with extraordinary attributes that the single-component structures do not have, which include the existence of flat-folded locking planes, programmable locking points and deformability. Finally, proof-of-concept experiments investigate how self-locking can effectively induce piecewise stiffness jumps. The results of this research provide new scientific knowledge and a systematic framework for the design, analysis and utilization of self-locking origami structures for many potential engineering applications.

Background: Surgeons are increasingly faced with the challenge of caring for obese patients. Advanced laparoscopic procedures have been shown to be safe in women with high BMI, but conversion rates remain high. Because robotics holds many potential advantages over traditional laparoscopic surgery, we sought to evaluate the outcome of robotic-assisted gynecologic surgery in obese patients., Methods: A retrospective chart review of obese female patients undergoing robotic gynecologic surgery between January 2008 and August 2010 was done. Patients were divided into three groups based on BMI (group I, BMI 30-34.9 kg/m 2 ; group II, BMI 35-39.9 kg/m 2 ; and group III, BMI >40 kg/m 2 ). Patients were assessed for baseline characteristics, comorbid conditions, and surgical outcomes and complications., Results: A total of 128 obese patients were identified with 43 in group I, 30 in group II, and 55 in group III. There was an increased prevalence of diabetes and asthma in group III and younger age in group I. Of the 128, 117 (91 %) underwent hysterectomy and/or staging with the majority of patients having surgery for either endometrial cancer or fibroids. Conversion to laparotomy was more common in groups 2 and 3 with a positive correlation between increasing BMI and conversion. There was no difference in complications between the groups and only 1 major postoperative complication in the entire cohort., Conclusions: Robotic-assisted gynecologic surgery can be safely performed in severely morbidly obese patients. Although conversion rates are higher with increasing obesity, a majority of procedures can still be completed minimally invasively.

Molecular analysis of sputum presents a noninvasive approach for diagnosis of lung cancer. We have shown that dysregulation of small nucleolar RNAs (snoRNAs) plays a vital role in lung tumorigenesis. We have also identified six snoRNAs whose changes are associated with lung cancer. Here we investigated if analysis of the snoRNAs in sputum could provide a potential tool for diagnosis of lung cancer. Using qRT-PCR, we determined expressions of the six snoRNAs in sputum of a training set of 59 lung cancer patients and 61 cancer-free smokers to develop a biomarker panel, which was validated in a testing set of 67 lung cancer patients and 69 cancer-free smokers for the diagnostic performance. The snoRNAs were robustly measurable in sputum. In the training set, a panel of two snoRNA biomarkers (snoRD66 and snoRD78) was developed, producing 74.58% sensitivity and 83.61% specificity for identifying lung cancer. The snoRNA biomarkers had a significantly higher sensitivity (74.58%) compared with sputum cytology (45.76%) (P < 0.05). The changes of the snoRNAs were not associated with stage and histology of lung cancer (All P >0.05). The performance of the biomarker panel was confirmed in the testing cohort. We report for the first time that sputum snoRNA biomarkers might be useful to improve diagnosis of lung cancer.

Introduction: Computed tomography (CT) plays a central role in lung cancer diagnosis. However, CT has relatively low specificity, presenting a challenge in clinical settings. We previously identified 12 microRNAs (miRNAs) whose expressions in tumor tissues were associated with lung cancer., Methods: Using quantitative reverse transcriptase polymerase chain reaction, we aimed to identify miRNA biomarkers in sputum that could complement CT for diagnosis of lung cancer., Results: In a training set consisting of 66 lung cancer patients and 68 cancer-free smokers, 10 of the 12 miRNAs were differentially expressed between the cases and controls (p ≤ 0.01). From the miRNAs, a logistic regression model was built on the basis of miR-31 and miR-210, both of which had the best prediction for lung cancer, producing an area under receiver operating characteristic curve of 0.83. Combined use of the two miRNAs yielded 65.2% sensitivity and 89.7% specificity, CT had 93.9% sensitivity and 83.8% specificity for lung cancer diagnosis. Notably, combined analysis of the miRNA biomarkers and CT produced a higher specificity than does CT used alone (91.2% versus 83.8%; p < 0.05). The diagnostic performance of the biomarkers was confirmed in a testing set comprising 64 lung cancer patients and 73 cancer-free smokers., Conclusion: The sputum miRNA biomarkers might be useful in improving CT for diagnosis of lung cancer, but further independent validation on an external and prospective cohort of patients is required.

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death. Developing minimally invasive techniques that can diagnose NSCLC, particularly at an early stage, may improve its outcome. Using microarray platforms, we previously identified 12 microRNAs (miRNAs) the aberrant expressions of which in primary lung tumors are associated with early-stage NSCLC. Here, we extend our previous research by investigating whether the miRNAs could be used as potential plasma biomarkers for NSCLC. We initially validated expressions of the miRNAs in paired lung tumor tissues and plasma specimens from 28 stage I NSCLC patients by real-time quantitative reverse transcription PCR, and then evaluated diagnostic value of the plasma miRNAs in a cohort of 58 NSCLC patients and 29 healthy individuals. The altered miRNA expressions were reproducibly confirmed in the tumor tissues. The miRNAs were stably present and reliably measurable in plasma. Of the 12 miRNAs, five displayed significant concordance of the expression levels in plasma and the corresponding tumor tissues (all r>0.850, all P<0.05). A logistic regression model with the best prediction was defined on the basis of the four genes (miRNA-21, -126, -210, and 486-5p), yielding 86.22% sensitivity and 96.55% specificity in distinguishing NSCLC patients from the healthy controls. Furthermore, the panel of miRNAs produced 73.33% sensitivity and 96.55% specificity in identifying stage I NSCLC patients. In addition, the genes have higher sensitivity (91.67%) in diagnosis of lung adenocarcinomas compared with squamous cell carcinomas (82.35%) (P<0.05). Altered expressions of the miRNAs in plasma would provide potential blood-based biomarkers for NSCLC.