Coupling Fault Diagnosis Based on Dynamic Vertex Interpretable Graph Neural Network.

Mechanical equipment is composed of several parts, and the interaction between parts exists throughout the whole life cycle, leading to the widespread phenomenon of fault coupling. The diagnosis of independent faults cannot meet the requirements of the health management of mechanical equipment under actual working conditions. In this paper, the dynamic vertex interpretable graph neural network (DIGNN) is proposed to solve the problem of coupling fault diagnosis, in which dynamic vertices are defined in the data topology. First, in the date preprocessing phase, wavelet transform is utilized to make input features interpretable and reduce the uncertainty of model training. In the fault topology, edge connections are made between nodes according to the fault coupling information, and edge connections are established between dynamic nodes and all other nodes. Second the data topology with dynamic vertices is used in the training phase and in the testing phase, the time series data are only fed into dynamic vertices for classification and analysis, which makes it possible to realize coupling fault diagnosis in an industrial production environment. The features extracted in different layers of DIGNN interpret how the model works. The method proposed in this paper can realize the accurate diagnosis of independent faults in the dataset with an accuracy of 100%, and can effectively judge the coupling mode of coupling faults with a comprehensive accuracy of 88.3%.

Inhibition of the p62-Nrf2-GPX4 Pathway Confers Sensitivity to Butachlor-Induced Splenic Macrophage Ferroptosis.

Butachlor is widely used in agriculture around the world and therefore poses environmental and public health hazards due to persistent and poor biodegradability. Ferroptosis is a type of iron-mediated cell death controlled by glutathione (GSH) and GPX4 inhibition. P62 is an essential autophagy adaptor that regulates Keap1 to activate nuclear factor erythroid 2-related factor 2 (Nrf2), which effectively suppresses lipid peroxidation, thereby relieving ferroptosis. Here, we found that butachlor caused changes in splenic macrophage structure, especially impaired mitochondrial morphology with disordered structure, which is suggestive of the occurrence of ferroptosis. This was further confirmed by the detection of iron metabolism, the GSH system, and lipid peroxidation. Mechanistically, butachlor suppressed the protein level of p62 and promoted Keap1-mediated degradation of Nrf2, which results in decreased GPX4 expression and accelerated splenic macrophage ferroptosis. These findings suggest that targeting the p62-Nrf2-GPX4 signaling axis may be a promising strategy for treating inflammatory diseases.

Defect by design: Harnessing the "petal effect" for advanced hydrophobic surface applications.

HYPOTHESIS: In the interfacial wetting boundary, the superhydrophobic surface is often damaged, and the anisotropic wettability of its surface has attracted many researchers' attention. The "petal effect" surface has typical anisotropic wettability. We predict that under the dual conditions of structural defects and high impact velocity, the "petal effect" becomes more adhesive on the surface. EXPERIMENTS: This study refers to the droplet state on rose petals, structural defects were constructed on the superhydrophobic surface. This paper studies the influence of macro-structural defects on the wettability change from natural to bionic "lotus effect" to "petal effect" in both static and dynamic angles. FINDINGS: Macro defects significantly change the static contact angle of the superhydrophobic surface. The higher the impact velocity of the droplet, the higher the energy dissipation of the "petal effect" surface (DSHS), which improves the adhesion of the surface to the droplet and prolongs the contact time. It is found that the defect structure and high impact velocity will directly affect the deposition and desorption of droplets on the superhydrophobic surface, and they are both essential. This wetting dynamic law is very likely to be helpful in the quantitative design of defect structure scale for dynamic desorption of droplets on superhydrophobic surfaces.

AQP1 Deficiency Drives Phthalate-Induced Epithelial Barrier Disruption through Intestinal Inflammation.

Di-2-ethylhexyl phthalate (DEHP) is frequently used as a plasticizer to enhance the plasticity and durability of agricultural products, which pose adverse effects to human health and the environment. Aquaporin 1 (AQP1) is a main water transport channel protein and is involved in the maintenance of intestinal integrity. However, the impact of DEHP exposure on gut health and its potential mechanisms remain elusive. Here, we determined that DEHP exposure induced a compromised duodenum structure, which was concomitant with mitochondrial structural injury of epithelial cells. Importantly, DEHP exposure caused duodenum inflammatory epithelial cell damage and strong inflammatory response accompanied by activating the TLR4/MyD88/NF-κB signaling pathway. Mechanistically, DEHP exposure directly inhibits the expression of AQP1 and thus leads to an inflammatory response, ultimately disrupting duodenum integrity and barrier function. Collectively, our findings uncover the role of AQP1 in phthalate-induced intestinal disorders, and AQP1 could be a promising therapeutic approach for treating patients with intestinal disorders or inflammatory diseases.

Selenium Status Associates with Thyroid Hormone and Thyroid Dysfunction in Older Chinese Adults.

Selenium (Se) is physiologically essential for thyroid function. However, epidemiological studies on the association between Se status and thyroid function are limited and the results are inconsistent. Therefore, we explored this association in an elderly Chinese population sample. Participants in the cross-sectional study were people aged 65 years or older who provided fingernail and whole blood samples. Hyperthyroidism and hypothyroidism were defined by serum thyroid hormones concentrations, including thyroid stimulating hormone (TSH), total triiodothyronine (TT3), total thyroxine (TT4), free thyroxine (FT3), and free thyrotropin (FT4). Significant positive association was observed between whole blood and fingernail Se concentrations (r = 0.672, P < 0.001). Compared with the lowest Se quartile (Q1), the other fingernail Se quartile groups had lower TSH, higher FT3 and FT4 levels, and Q2 had higher TT3 levels after adjusting for covariates; the other whole blood Se quartile groups had lower TSH levels, Q2 had higher FT3, FT4 and TT3 levels, Q3 had higher FT3 levels, and Q4 had higher FT4 levels after adjusting for covariates. Compared with Q1, the adjusted odds ratios (OR) and 95% confidence intervals (95%CIs) of hypothyroidism for Q4 of whole blood Se was 0.141 (0.029,0.675), and the adjusted OR (95%CIs) of hyperthyroidism for Q2 and Q3 of fingernail Se were 4.121 (1.233,13.733) and 3.614 (1.095,11.926). Higher Se levels were significantly associated with lower TSH levels and higher levels of TT3, FT3 and FT4. Meanwhile, higher Se levels were associated with lower risk of hypothyroidism and higher risk of hyperthyroidism.

Real-world impact of chemotherapy on overall survival in craniomaxillofacial osteosarcoma.

OBJECTIVES: The goal of this study was to identify the survival benefit of chemotherapy in craniomaxillofacial osteosarcoma (CMFO) patients based on a US population. MATERIALS AND METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was used to select patients with CMFO from 1988 to 2016. Age and tumor size were grouped by X-tail. Cox analysis were used to estimate hazards ratios (HR) among patients. All of patients were divided into two cohorts by using Propensity Score Matching (PSM) method to evaluate the effect of chemotherapy. All prognostic factors were included in the nomograms which predict the median survival time. RESULTS: 410 patients were included in our study. The results of survival rate, Kaplan-Meier and Cox regression were showed no significant difference between the group of chemotherapy performed and the group without chemotherapy. PSM analysis also demonstrated the limited survival advantage of chemotherapy. Moreover, all factors were further incorporated to construct the novel nomograms and its concordance indices (C-index) for internal validation of OS prediction were 0.749 (95 %CI:0.731-0.767). CONCLUSIONS: Our study did not show the advantage of chemotherapy on the overall survival outcome of CMFO. Although neoadjuvant chemotherapy was currently recommended in clinical treatment, more rigorous randomized controlled trials are still needed. Nomograms would assist clinicians in making more accurate survival evaluation and choosing the optimal medical treatment.

Phthalate drives splenic inflammatory response via activating HSP60/TLR4/NLRP3 signaling axis-dependent pyroptosis.

As the most produced phthalate, di-(2-ethylhexyl) phthalate (DEHP) is a widely environmental pollutant primarily used as a plasticizer, which cause the harmful effects on human health. However, the impact of DEHP on spleen and its underlying mechanisms are still unclear. Pyroptosis is a novel form of cell death induced by activating NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasomes and implicated in pathogenesis of numerous inflammatory diseases. The current study aimed to explore the impact of DEHP on immune inflammatory response in mouse spleen. In this study, the male ICR mice were treated with DEHP (200 mg/kg) for 28 days. Here, DEHP exposure caused abnormal pathohistological and ultrastructural changes, accompanied by inflammatory cells infiltration in mouse spleen. DEHP exposure arouse heat shock response that involves increase of heat shock proteins 60 (HSP60) expression. DEHP also elevated the expressions of toll-like receptor 4 (TLR4) and myeloid differentiation protein 88 (MyD88) proteins, as well as the activation of NF-κB pathway. Moreover, DEHP promoted NLRP3 inflammasome activation and triggered NLRP3 inflammasome-induced pyroptosis. Mechanistically, DEHP drives splenic inflammatory response via activating HSP60/TLR4/NLRP3 signaling axis-dependent pyroptosis. Our findings reveal that targeting HSP60-mediated TLR4/NLRP3 signaling axis may be a promising strategy for inflammatory diseases treatment.

GHA-DenseNet prediction and diagnosis of malignancy in femoral bone tumors using magnetic resonance imaging.

Background and objective: Due to their aggressive nature and poor prognosis, malignant femoral bone tumors present considerable hurdles. Early treatment commencement is essential for enhancing vital and practical outcomes. In this investigation, deep learning algorithms will be used to analyze magnetic resonance imaging (MRI) data to identify bone tumors that are malignant. Methodology: The study cohort included 44 patients, with ages ranging from 17 to 78 (22 women and 22 males). To categorize T1 and T2 weighted MRI data, this paper presents an improved DenseNet network model for the classification of bone tumor MRI, which is named GHA-DenseNet. Based on the original DenseNet model, the attention module is added to solve the problem that the deep convolutional model can reduce the loss of key features when capturing the location and content information of femoral bone tumor tissue due to the limitation of local receptive field. In addition, the sparse connection mode is used to prune the connection mode of the original model, so as to remove unnecessary and retain more useful fast connection mode, and alleviate the overfitting problem caused by small dataset size and image characteristics. In a clinical model designed to anticipate tumor malignancy, the utilization of T1 and T2 classifier output values, in combination with patient-specific clinical information, was a crucial component. Results: The T1 classifier's accuracy during the training phase was 92.88% whereas the T2 classifier's accuracy was 87.03%. Both classifiers demonstrated accuracy of 95.24% throughout the validation phase. During training and validation, the clinical model's accuracy was 82.17% and 81.51%, respectively. The clinical model's receiver operating characteristic (ROC) curve demonstrated its capacity to separate classes. Conclusions: The proposed method does not require manual segmentation of MRI scans because it makes use of pretrained deep learning classifiers. These algorithms have the ability to predict tumor malignancy and shorten the diagnostic and therapeutic turnaround times. Although the procedure only needs a little amount of radiologists' involvement, more testing on a larger patient cohort is required to confirm its efficacy.

Plasma Treatment for Achieving Oxygen Substitution in Layered MoS2 and the Room-Temperature Mid-Infrared (10 µm) Photoresponse.

Highly sensitive photodetectors in the mid-infrared (MIR, 3-15 µm) are highly desired in a growing number of applications. However, only a handful of narrow-band-gap semiconductors are suitable for this purpose, most of which require cryogenic cooling to increase the signal-to-noise ratio. The realization of high-performance MIR photodetectors operating at room temperature remains a challenge. Herein, we report on plasma-treated few-layer MoS2 for room-temperature MIR (10 µm) photodetection. Oxygen plasma treatment, which is a mature microfabrication process, is employed. The ion kinetic energy of oxygen plasma is adjusted to 70-130 eV. A photoresponsivity of 0.042 mA/W and a detectivity of 1.57 × 107 Jones are obtained under MIR light (10 µm) illumination with an average power density of 114.6 mW/cm2. The photoresponse is attributed to the introduction of electronic states in the band gap of MoS2 through oxygen substitution. A graphene/plasma-treated MoS2/graphene device is further demonstrated to shorten the active channel while maintaining the illumination area. The photoresponsivity and detectivity are largely boosted to 1.8 A/W and 2.64 × 109 Jones, respectively. The excellent detective performance of the graphene/plasma-treated MoS2/graphene device is further demonstrated in single-detector MIR (10 µm) scanning imaging. This work offers a facile approach to constructing integrated MoS2-based MIR photodetectors.

The anti-photoaging effect of C-phycocyanin on ultraviolet B-irradiated BALB/c-nu mouse skin.

Introduction: C-phycocyanin (C-PC), a photosynthetic protein obtained from Spirulina, is regarded a highly promising commercially available biochemical. Numerous in vitro and in vivo studies have provided evidence of C-PC's ability to mitigate the inflammatory response, alleviate oxidative stress, and facilitate wound healing. However, despite the existing knowledge regarding C-PC's protective mechanism against cellular apoptosis induced by ultraviolet B (UVB) radiation, further in vivo experiments are needed to explore its anti-photoaging mechanism. Methods: In this study, a UVB-induced skin photoaging model was established using BALB/c-nu mice, and the potential protective effects of topically administered c-PC were investigated by various molecular biology tools. In addition, a novel delivery system, C-PC nanodispersion, was developed to facilitate the transdermal delivery of C-PC. Results: C- PC demonstrated significant anti-photoaging activities in the UVB-induced skin. The application of C-PC to the dorsal skin of the mice resulted in improved macroscopic characteristics, such as reduced sagging and coarse wrinkling, under UVB irradiation Histological analyses showed that C-PC treatment significantly decreased the symptoms of epidermal thickening, prevented dermal collagen fiber loosening, increased the hydroxyproline (Hyp) content and activities of antioxidant enzymes (such as superoxide dismutase, catalase, and glutathione peroxidase) in mouse skin, decreased malondialdehyde levels and expressions of inflammatory factors (interleukin-1α [IL-1α], IL-1ß, IL-6, and tumor necrosis factor-α), reduced matrix metalloproteinase [MMP-3 and MMP-9] expressions, and inhibited the phosphorylation of c-Jun N-terminal kinase, extracellular signal-regulated kinase, and p38 proteins in the mitogen-activated protein kinase family. Discussion: By analyzing the results of the study, a new drug delivery system, C-PC nano-dispersion, was proposed, and the anti-photoaging effect of C-PC and its mechanism were investigated.

Dynamic monitoring of TGW6 by selective autophagy during grain development in rice.

Crop yield must increase to achieve food security in the face of a growing population and environmental deterioration. Grain size is a prime breeding target for improving grain yield and quality in crop. Here, we report that autophagy emerges as an important regulatory pathway contributing to grain size and quality in rice. Mutations of rice Autophagy-related 9b (OsATG9b) or OsATG13a causes smaller grains and increase of chalkiness, whereas overexpression of either promotes grain size and quality. We also demonstrate that THOUSAND-GRAIN WEIGHT 6 (TGW6), a superior allele that regulates grain size and quality in the rice variety Kasalath, interacts with OsATG8 via the canonical Atg8-interacting motif (AIM), and then is recruited to the autophagosome for selective degradation. In consistent, alteration of either OsATG9b or OsATG13a expression results in reciprocal modulation of TGW6 abundance during grain growth. Genetic analyses confirmed that knockout of TGW6 in either osatg9b or osatg13a mutants can partially rescue their grain size defects, indicating that TGW6 is one of the substrates for autophagy to regulate grain development. We therefore propose a potential framework for autophagy in contributing to grain size and quality in crops.

The DRD2 Antagonist Haloperidol Mediates Autophagy-Induced Ferroptosis to Increase Temozolomide Sensitivity by Promoting Endoplasmic Reticulum Stress in Glioblastoma.

PURPOSE: Temozolomide resistance remains a major obstacle in the treatment of glioblastoma (GBM). The combination of temozolomide with another agent could offer an improved treatment option if it could overcome chemoresistance and prevent side effects. Here, we determined the critical drug that cause ferroptosis in GBM cells and elucidated the possible mechanism by which drug combination overcomes chemoresistance. EXPERIMENTAL DESIGN: Haloperidol/temozolomide synergism was assessed in GBM cell lines with different dopamine D2 receptor (DRD2) expression in vitro and in vivo. Inhibitors of ferroptosis, autophagy, endoplasmic reticulum (ER) stress and cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) were used to validate the specific mechanisms by which haloperidol and temozolomide induce ferroptosis in GBM cells. RESULTS: In the present work, we demonstrate that the DRD2 level is increased by temozolomide in a time-dependent manner and is inversely correlated with temozolomide sensitivity in GBM. The DRD2 antagonist haloperidol, a butylbenzene antipsychotic, markedly induces ferroptosis and effectively enhances temozolomide efficacy in vivo and in vitro. Mechanistically, haloperidol suppressed the effect of temozolomide on cAMP by antagonizing DRD2 receptor activity, and the increases in cAMP/PKA triggered ER stress, which led to autophagy and ferroptosis. Furthermore, elevated autophagy mediates downregulation of FTH1 expression at the posttranslational level in an autophagy-dependent manner and ultimately leads to ferroptosis. CONCLUSIONS: Our results provide experimental evidence for repurposing haloperidol as an effective adjunct therapy to inhibit adaptive temozolomide resistance to enhance the efficacy of chemoradiotherapy in GBM, a strategy that may have broad prospects for clinical application.

Thermal analysis technology to utilize waste biomass and waste heat to produce high-quality combustible gas through simulations and experiments.

To ensure the proper utilization of waste biomass (WB) and high-temperature waste heat, this study proposes a new method for obtaining gaseous fuels by pyrolyzing WB and using waste heat in the converter vaporization cooling flue (CVCF). This study is theoretically based on the simulation software Factsage 6.1 and the release patterns of the gaseous products including CO, H2, CH4 and CO2 obtained from waste biomass, were studied at different temperatures and pressures. Thermogravimetric-mass spectrometer (TG-MS) was used to investigate the pyrolysis of WB at heating rates of 5, 10, 15, and 20 °C/min from room temperature to 1400 °C. Kinetics parameters were calculated by using the Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) models. To investigate the effects of temperature, a settling furnace was also used to simulate CVCF. Thermal decomposition produced the primary gases namely CO, CH4, and H2. Pyrolysis had an average activation energy of 183.29 kJ/mol. As the temperature increased from 800 °C to 1200 °C, the CO content increased from 39.7 % to 48.9 % and the H2 content increased from 35 % to 45.1 %. As the temperature rose from 800 to 1200 °C, the lower heating value (LHV) increased from 11.38 to 12.05 MJ/Nm3. The findings primarily confirmed the feasibility of injecting biomass into the CVCF to generate gaseous fuels from waste heat.

Boosting the capacity and stability of a MoO3 cathode via valence regulation and polypyrrole coating for a rechargeable Zn ion battery.

Molybdenum trioxide (MoO3) is emerging as a hugely competitive cathode material for aqueous zinc ion batteries (ZIBs) for its high theoretical capacity and electrochemical activity. Nevertheless, owing to its undesirable electronic transport capability and poor structural stability, the practical capacity and cycling performance of MoO3 are yet unsatisfactory, which greatly blocks its commercial use. In this work, we report an effective approach to first synthesise nanosized MoO3-x materials to provide more active specific surface areas, while improving the capacity and cycle life of MoO3 by introducing low valence Mo and coated polypyrrole (PPy). MoO3 nanoparticles with low-valence-state Mo and PPy coating (denoted as MoO3-x@PPy) are synthesized via a solvothermal method and subsequent electrodeposition process. The as-prepared MoO3-x@PPy cathode delivers a high reversible capacity of 212.4 mA h g-1 at 1 A g-1 with good cycling life (more than 75% capacity retention after 500 cycles). In contrast, the original commercial MoO3 sample only obtains a capacity of 99.3 mA h g-1 at 1 A g-1, and a cycling stability of 10% capacity retention over 500 cycles. Additionally, the fabricated Zn//MoO3-x@PPy battery obtains a maximum energy density of 233.6 W h kg-1 and a power density of 11.2 kW kg-1. Our results provide an efficient and practical approach to enhance commercial MoO3 materials as high-performance cathodes for AZIBs.

Deep learning-based image segmentation model using an MRI-based convolutional neural network for physiological evaluation of the heart.

Background and Objective: Cardiovascular disease is a high-fatality health issue. Accurate measurement of cardiovascular function depends on precise segmentation of physiological structure and accurate evaluation of functional parameters. Structural segmentation of heart images and calculation of the volume of different ventricular activity cycles form the basis for quantitative analysis of physiological function and can provide the necessary support for clinical physiological diagnosis, as well as the analysis of various cardiac diseases. Therefore, it is important to develop an efficient heart segmentation algorithm. Methods: A total of 275 nuclear magnetic resonance imaging (MRI) heart scans were collected, analyzed, and preprocessed from Huaqiao University Affiliated Strait Hospital, and the data were used in our improved deep learning model, which was designed based on the U-net network. The training set included 80% of the images, and the remaining 20% was the test set. Based on five time phases from end-diastole (ED) to end-systole (ES), the segmentation findings showed that it is possible to achieve improved segmentation accuracy and computational complexity by segmenting the left ventricle (LV), right ventricle (RV), and myocardium (myo). Results: We improved the Dice index of the LV to 0.965 and 0.921, and the Hausdorff index decreased to 5.4 and 6.9 in the ED and ES phases, respectively; RV Dice increased to 0.938 and 0.860, and the Hausdorff index decreased to 11.7 and 12.6 in the ED and ES, respectively; myo Dice increased to 0.889 and 0.901, and the Hausdorff index decreased to 8.3 and 9.2 in the ED and ES, respectively. Conclusion: The model obtained in the final experiment provided more accurate segmentation of the left and right ventricles, as well as the myocardium, from cardiac MRI. The data from this model facilitate the prediction of cardiovascular disease in real-time, thereby providing potential clinical utility.

One-Pot Synthesis of NiSe2 with Layered Structure for Nickel-Zinc Battery.

Transition metal organic framework materials and their selenides are considered to be one of the most promising cathode materials for nickel-zinc (denoted as Ni-Zn) batteries due to their low cost, environmental friendliness, and controllable microstructure. Yet, their low capacity and poor cycling performance severely restricts their further development. Herein, we developed a simple one-pot hydrothermal process to directly synthesize NiSe2 (denotes as NiSe2-X based on the molar amount of SeO2 added) stacked layered sheets. Benefiting from the peculiar architectures, the fabricated NiSe2-1//Zn battery based on NiSe2 and the Zn plate exhibits a high specific capacity of 231.6 mAh g-1 at 1 A g-1, and excellent rate performance (162.8 mAh g-1 at 10 A g-1). In addition, the NiSe2//Zn battery also presents a satisfactory cycle life at the high current density of 8 A g-1 (almost no decay compared to the initial specific capacity after 1000 cycles). Additionally, the battery device also exhibits a satisfactory energy density of 343.2 Wh kg-1 and a peak power density of 11.7 kW kg-1. This work provides a simple attempt to design a high-performance layered cathode material for aqueous Ni-Zn batteries.

Fault Knowledge Graph Construction and Platform Development for Aircraft PHM.

To tackle the problems of over-reliance on traditional experience, poor troubleshooting robustness, and slow response by maintenance personnel to changes in faults in the current aircraft health management field, this paper proposes the use of a knowledge graph. The knowledge graph represents troubleshooting in a new way. The aim of the knowledge graph is to improve the correlation between fault data by representing experience. The data source for this study consists of the flight control system manual and typical fault cases of a specific aircraft type. A knowledge graph construction approach is proposed to construct a fault knowledge graph for aircraft health management. Firstly, the data are classified using the ERNIE model-based method. Then, a joint entity relationship extraction model based on ERNIE-BiLSTM-CRF-TreeBiLSTM is introduced to improve entity relationship extraction accuracy and reduce the semantic complexity of the text from a linguistic perspective. Additionally, a knowledge graph platform for aircraft health management is developed. The platform includes modules for text classification, knowledge extraction, knowledge auditing, a Q&A system, and graph visualization. These modules improve the management of aircraft health data and provide a foundation for rapid knowledge graph construction and knowledge graph-based fault diagnosis.

Design of CB-PDMS Flexible Sensing for Monitoring of Bridge Cracks.

This paper proposes a flexible sensor for detecting cracks on bridges. Strain and deflection sensing modules are integrated on the film that is made of composite conductive materials. By optimizing the preparation ratio and internal structure, the strain detection accuracy and sensitivity of the sensor have been improved. The bridge crack detection accuracy reached 91%, which is higher than current sensors. Experimental results show that the composite material containing 2.23 wt% carbon black (CB) mixed hybrid filler has good linearity, higher accuracy than sensors in use, excellent stretchability (>155%), high gauge factor (GF ~ 43.3), and excellent durability over 2000 stretching-releasing cycles under 10 N. The designed flexible sensor demonstrates the practicality and effectiveness of bridge crack detection and provides a feasible solution for accurate bridge health monitoring in the future.

Multifaceted roles of zinc finger proteins in regulating various agronomic traits in rice.

Rice is an important cereal crop, which provides staple food for more than half of the world's population. To meet the demand of the ever-growing population in the next few decades, an extra increase in rice yield is an urgent need. Given that various agronomic traits contribute to the yield of rice, deciphering the key regulators involved in multiple agronomic trait formation is particularly important. As a superfamily of transcription factors, zinc finger proteins participate in regulating multiple genes in almost every stage of rice growth and development. Therefore, understanding zinc finger proteins underlying regulatory network would provide insights into the regulation of agronomic traits in rice. To this end, we intend to summarize the current advances in zinc finger proteins, with emphasis on C2H2 and CCCH proteins, and then discuss their potential in improving rice yield.