Search

In order to investigate the inhibitory effect of β-carotene on lipid oxidation in Pickering emulsion, the Pickering emulsions embedded with β-carotene were prepared using cellulose nanocrystal (CNC) as an emulsifier. The DPPH and ABTS+ radical scavenging rates were used as evaluation indices to examine the antioxidant properties of β-carotene, both before and after embedding. The oxidative and coloring stability of the embedded β-carotene emulsions was investigated by measuring the β-carotene embedding and retention rate, peroxide value (POV), thiobarbituric acid (TBA) value, and color difference. The results showed that the β-carotene embedded in the emulsions had a good scavenging effect on DPPH and ABTS+ free radicals. The retention of β-carotene in the emulsions significantly decreased (P

Photorespiration begins with the oxygenation reaction catalyzed by 1,5-bisphosphate carboxylase/oxygenase (Rubisco) and serves as a repair pathway for carbon retrieval by converting 2-phosphoglycolate to 3-phosphogly-cerate allowing plants to thrive in an oxygen-rich environment. Photorespiration metabolism is intimately linked to plant primary metabolism, particularly carbon and nitrogen assimilation, and cellular redox equilibrium, and such interactions are dynamically regulated by environmental changes. Although the basic genetics and biochemistry of photorespiration have been well characterized, it is still essential to further improve our understanding of the regulatory mechanisms of photorespiration and the roles in responding to changing environments, which are required for the future genetic manipulation of photorespiration. Here, we summarize recent progress regarding the evolutionary aspects of photorespiration and its multifaceted regulation, highlighting its intricate interactions with environmental CO2, light, and nitrogen nutrition. This review provides a comprehensive perspective on the functional implications of photorespiration for plants to adapt to the environment and opens new avenues for our in-depth exploration of photorespiration to develop better strategies to enhance plant productivity and adaptability in the face of changing environmental conditions.

Seven new species of the subgenus Homoneura are described, Homoneura (Homoneura) biconica Chen & Li, sp. nov., Homoneura (Homoneura) dilatata Chen & Li, sp. nov., Homoneura (Homoneura) jiangjinensis Chen & Li, sp. nov., Homoneura (Homoneura) microtricha Chen & Li, sp. nov., Homoneura (Homoneura) multiseta Chen & Li, sp. nov., Homoneura (Homoneura) serrulata Chen & Li, sp. nov., Homoneura (Homoneura) simianshana Chen & Li, sp. nov., which were collected from Jiangjin District, southwestern Chongqing, China and are assigned to the henanensis group. A key to all of the 53 species of this species group in China is presented.

Ischnothyreus Simon, 1893 is a large genus of oonopid spiders that currently contains 126 species, amongst which, 28 have been recorded in China.Two new Ischnothyreus species, Ischnothyreus daheling Tong & Zhang, sp. nov. and Ischnothyreus longyang Tong & Zhang, sp. nov., are described, based on specimens collected from Yunnan Province and Ischnothyreus velox Jackson, 1908 is recorded in China for the first time, based on material collected from Guangxi Province. All three species are illustrated.

Objective To explore the clinical efficacy of a programmed death receptor 1(PD-1) inhibitor in combination with amilorotinib in the treatment of elderly advanced non-small cell lung cancer(NSCLC) that has failed second-line chemotherapy. Methods A total of 106 elderly advanced NSCLC patients who failed second-line chemotherapy admitted to Taizhou Second People's Hospital from January 2019 to April 2021 were selected as the study subjects, they were divided into the single-agent group and the combination group according to the method of randomized numerical table, each had 53 cases.The single-agent group was treated with Anlotinib, and the combination group was treated with PD-1 inhibitor combined with Anlotinib.The indicators of disease control rate, incidence of toxic side reactions, survival rate, tumor markers [cytokeratin 19 fragment antigen 21-1(CYFRA21-1), carcinoembryonic antigen(CEA), carbohydrate antigen 125(CA125)] , angiogenesis indicators [vascular endothelial growth factor(VEGF-A), VEGF receptor 2(VEGFR2)] , serum kinesin superfamily protein(KIF) C1, N-cadherin and the Quality of Life Core Scale(QLQ-C30) scores were compared. Results The disease control rate in the combination group was higher than that in the monotherapy group(P0.05);Kaplan Meier survival analysis showed that the combined group had a higher cumulative survival rate than the monotherapy group(P

Five species of the genus Opopaea Simon, 1892 from southern China are recognised, including four new species: Opopaea mangun Tong & Li, sp. nov., Opopaea taibao Tong & Yang, sp. nov., Opopaea wenshan Tong & Zhang, sp. nov. and Opopaea yuhuang Tong & Li, sp. nov. from Yunnan and one newly-recorded species: Opopaea foveolata Roewer, 1963 from Hainan. Detailed diagnoses, descriptions and photomicroscopy images of new species are provided, based on specimens of both sexes. A key to species of the genus Opopaea from China is provided.

There was an error in the original publication [...]

Preventing the occurrence of secondary caries serves as one of the significant issues in dental clinic, thus make it indispensable to improving the properties of conventional composite resin (CR) by developing a novel CR. In present study, two groups of experimental CRs loaded with different contents of fluoride-doped nano-zirconia fillers (25 wt% and 50 wt%) were fabricated. The surface topography, mechanical performance, fluoride release, antibacterial effect, aging property and cytotoxicity of the experimental CRs were evaluated subsequently. A uniform distribution of the F-zirconia fillers over the whole surface of resin matrix could be observed. The experimental CRs showed continuous fluoride release within 28 days, which was positively correlated with the content of F-zirconia fillers. Moreover, the amount of fluoride release increased in the acidic buffer. Addition of F-zirconia fillers could improve the color stability, wear resistance and microhardness of the experimental CRs, without reducing the flexure strength. Furtherly, the fluoride ions released continuously from the experimental CRs resulted in effective contact and antibacterial properties, while they showed no cytotoxicity. As a consequence, considerations can be made to employ this new kind of composite resin loaded with fluoride-doped nano-zirconia fillers to meet clinical requirements when the antimicrobial benefits are desired.

Direct seeding ratoon rice (DSRR) system is a planting method that can significantly increase grain yield, improving light and temperature utilization efficiency and reducing labor input. However, the current nitrogen fertilizer management method which does not aim at the seedling emergence and development characteristics of DSRR just is only based on the traditional method of transplanting ratoon rice, and which is not conducive to the population development and yield improvement. To determine the suitable nitrogen fertilizer application optimization, we set four nitrogen fertilizer application treatments (N0, no nitrogen fertilizer; N1, traditional nitrogen fertilizer; N2, transferring 20% of total nitrogen from basal fertilizer to tillering stage; N3, reducing total nitrogen by 10% from N2 tillering fertilizer) on a hybrid rice “Fengliangyouxiang1 (FLYX1)” and an inbred rice “Huanghuazhan (HHZ)” under DSRR. The effects of treatments on dry matter accumulation, root growth and vigor, leaf area index, leaf senescence rate and yield were investigated. Our results demonstrated that the yield of main crop in N2 treatment was the highest, which was 63.3%, 6.6% and 8.8% higher than that of N0, N1 and N3 treatment, respectively, mainly due to the difference of effective panicle and spikelets number per m2. The average of two years and varieties, the annual yield of N2 was significant higher than that of N1 and N3 by 4.94% and 8.55%, respectively. However, there was no significant difference between the annual yields of N1 and N3. N2 treatment had significant effects on the accumulation of aboveground dry matter mass which was no significant difference in 20 days after sowing(DAS), but significant difference in 50 DAS. Meanwhile, the root activity and the leaf senescence rate of N2 treatment was significant lower than that of other treatments. In summary, “20% of total nitrogen was transferred from basal fertilizer to tillering stage” can improve the annual yield and main crop development of DSRR system. Further reducing the use of nitrogen fertilizer may significantly improve the production efficiency of nitrogen fertilizer and improve the planting income in DSRR system.

The genera Kachinia Tong & Li, 2018 and Promolotra Tong & Li, 2020 are recorded from China for the first time. Two new species, Kachinia longling sp. nov. (♂♀) and Promolotra lushui sp. nov. (♂♀) are described. Descriptions, diagnoses, photographs and keys to Kachinia and Promolotra species are provided.

Soft open point (SOP) realizes the normal and flexible interconnection between distribution network feeders, leading to the improvement of the flexibility and rapidity of the distribution network control. However, drawbacks such as high cost and low utilization rate limit its application. A novel medium voltage photovoltaic power generation device with the SOP function is proposed in this paper. There are two grid-connected interfaces, and both of them adopt the cascaded H-bridge topology. A common DC-link is used for both H-bridge inverters belonging to the two grid-connected interfaces respectively. The proposed device eliminates the step-up transformers, and can be connected directly to the medium voltage distribution network. Therefore, advantages such as simple structure, low cost, low power loss and fault-tolerant operation capability are able to be obtained. The stability and flexibility of the distribution network operation are improved. The topology and power flow mode of the proposed medium voltage photovoltaic power generation device with the SOP function are analyzed, and the distribution network multi-objective optimal operation model with the proposed device is established. The proposed medium voltage photovoltaic power generation device with the SOP function is connected to the modified IEEE 33-node distribution network, and the network optimal operation with the device in terms of the power flow optimization and voltage improvement is analyzed.

Representing and rendering dynamic underwater scenes present significant challenges due to the medium’s inherent properties, which result in image blurring and information ambiguity. To overcome these challenges and accomplish real-time rendering of dynamic underwater environments while maintaining efficient training and storage, we propose Underwater Dynamic Scene Reconstruction Gaussian Splatting (UDR-GS), a method based on Gaussian Splatting. By leveraging prior information from a pre-trained depth estimation model and smoothness constraints between adjacent images, our approach uses the estimated depth as a geometric prior to aid in color-based optimization, significantly reducing artifacts and improving geometric accuracy. By integrating depth guidance into the Gaussian Splatting (GS) optimization process, we achieve more precise geometric estimations. To ensure higher stability, smoothness constraints are applied between adjacent images, maintaining consistent depth for neighboring 3D points in the absence of boundary conditions. The symmetry concept is inherently applied in our method by maintaining uniform depth and color information across multiple viewpoints, which enhances the reconstruction quality and visual coherence. Using 4D Gaussian Splatting (4DGS) as a baseline, our strategy demonstrates superior performance in both RGB novel view synthesis and 3D geometric reconstruction. On average, across multiple datasets, our method shows an improvement of approximately 1.41% in PSNR and a 0.75% increase in SSIM compared with the baseline 4DGS method, significantly enhancing the visual quality and geometric fidelity of dynamic underwater scenes.

This study investigated the dietary effect of curcumin (CUR) on amino acid, 5′-nucleotides, fatty acid, and volatile compound profiles of chicken meat. A total of 400 healthy 1-day-old broiler male chicks were divided into 4 groups (n = 10) and fed either a basal diet or a diet with the addition of CUR with concentrations of 100 mg/kg, 150 mg/kg, and 200 mg/kg for 43 days. The results show that the addition of CUR in chicken diets is conducive to promoting the deposition of amino acids and increasing the content of 5′-nucleotides in chicken meat, reducing the contents of saturated fatty acid (SFA) and C20:4 n6 but increasing the ratio between polyunsaturated fatty acid (PUFA) and SFA. In addition, the volatile compound profile shows that the main volatile compounds in chicken meat are aldehydes (including hexanal, heptanal, octanal, and nonanal), with significant increases in their contents observed among chickens in the CUR-intake group. Moreover, it has been found that (E, E)-2,4-nonadienal, trans-2-decenal, benzaldehyde, and trans-2-octenal in chicken meat can significantly increase its overall aroma, and the addition of CUR with 150 mg/kg had the best effect on improving nutritional quality and flavor of chicken meat. This study provides a basis for the comprehensive utilization of CUR as a feed additive with the potential to substitute antibiotics.

Three new species of the genus Trilacuna Tong & Li, 2007, T. cangshan Tong, Yang & Zhang, sp. nov. (♂), T. wumanshan Tong, Yang & Zhang, sp. nov. (♂), and T. xiaoheishan Tong, Yang & Zhang, sp. nov. (♂♀) are described from Yunnan, China. Descriptions, diagnoses, and photographs are provided.

ABSTRACT: This study purposed to investigate the alleviating effect of dietary curcumin supplementation on oxidative stress in the liver of broilers induced by diquat. One-day-old Cobb broilers (400) were selected and randomly divided into 5 groups, with 8 replicates and 10 broilers per replicate. The control group and the diquat group were fed the basal diet, while the curcumin supplementation groups were fed the basal diet supplemented with different amounts of curcumin (50, 100, and 150 mg/kg). On d 21 of the test, 1 broiler was randomly selected from each replicate and intraperitoneally injected with 20 mg/mL of diquat solution at a dose of 1 mL/kg BW or equivalent physiological saline (for the control group). After 48 h of feeding, the selected broilers were slaughtered for analysis. The results show that diquat treatment reduced the antioxidant capacity of the liver, caused oxidative stress, and affected its lipid metabolism. However, diet supplementation using curcumin completely or partially reversed the effect of diquat on the liver of broilers. The blood alanine aminotransferase activity, total bilirubin and total protein levels, and liver Caspase-3 mRNA abundance in broilers were lower or significantly lower in the curcumin supplementation group than in the diquat group (P < 0.05). The curcumin supplementation groups had significantly higher total antioxidant capacity activity but significantly lower malondialdehyde in the liver of broilers than the diquat group (P < 0.05). The blood triglyceride level of broilers was lower or significantly lower in the curcumin supplementation groups than in the diquat group (P < 0.05). The activities of cetyl coenzyme A carboxylase in the liver were significantly lower in the 150 mg/kg curcumin supplementation groups than in the DQ group (P < 0.05). In conclusion, dietary curcumin supplementation could ameliorate the effects of diquat-induced oxidative stress on the antioxidant capacity, tissue morphology, and lipid metabolism of the liver of broilers, thus protecting the liver. The recommended dosage for broiler diets is 100 to 150 mg/kg curcumin.

Abstract Isopropyl alcohol molecules, as a biomarker for anti-virus diagnosis, play a significant role in the area of environmental safety and healthcare relating volatile organic compounds. However, conventional gas molecule detection exhibits dramatic drawbacks, like the strict working conditions of ion mobility methodology and weak light-matter interaction of mid-infrared spectroscopy, yielding limited response of targeted molecules. We propose a synergistic methodology of artificial intelligence-enhanced ion mobility and mid-infrared spectroscopy, leveraging the complementary features from the sensing signal in different dimensions to reach superior accuracy for isopropyl alcohol identification. We pull in “cold” plasma discharge from triboelectric generator which improves the mid-infrared spectroscopic response of isopropyl alcohol with good regression prediction. Moreover, this synergistic methodology achieves ~99.08% accuracy for a precise gas concentration prediction, even with interferences of different carbon-based gases. The synergistic methodology of artificial intelligence-enhanced system creates mechanism of accurate gas sensing for mixture and regression prediction in healthcare.

Plastic straws are well-known tools to assist human beings in drinking fluid, but most of them have micro-defects including black spot defects, head problems, pressure tube defects, and sealing wrinkles. The manual detection of these defects has drawbacks such as low efficiency, a high false detection rate, and excessive labor. This paper proposed machine vision-based detection with self-adaption and high-accuracy characteristics. A serial synthesis of algorithms including homomorphic filtering, Nobuyuki Otsu, and morphological opening operations is proposed to obtain plastic straws with binary images with good performance, and it was further found that the convolutional neural network can be designed to realize the real-time recognition of black spot defects, where the corner detection algorithm demonstrates the linear fitting of the edge point of the straw with the effective detection of sealing wrinkle defects. We also demonstrated that the multi-threshold classification algorithm is used to detect defects effectively for head problems and pressure tube defects. The detection system based on machine vision successfully overcomes shortcomings of manual inspection, which has high inspection efficiency and adaptively detects multiple defects with 96.85% accuracy. This research can effectively help straw companies achieve high-quality automated production and promotes the application of machine vision in plastic straw defects with the aid of machine learning.

During 14–16 March 2021, a large-scale dust storm event occurred in the northern region of China, and it was considered the most intense event in the past decade. This study employs observation data for PM2.5 and PM10 from the air quality monitoring station, the HYSPLIT model, ground-based polarized Lidar networks, AGRI payload data from Fengyun satellites and CALIPSO satellite Lidar data to jointly explore and scrutinize the three-dimensional spatial and temporal characteristics of aerosol transport. Firstly, by integrating meteorological data for PM2.5 and PM10, the air quality is assessed across six stations within the Lidar network during the dust storm. Secondly, employing a backward trajectory tracking model, the study elucidates sources of dust at the Lidar network sites. Thirdly, deploying a newly devised portable infrared 1064 nm Lidar and a pulsed 532 nm Lidar, a ground-based Lidar observation network is established for vertical probing of transboundary dust transport within the observed region. Finally, by incorporating cloud imagery from Fengyun satellites and CALIPSO satellite Lidar data, this study revealed the classification of dust and the height distribution of dust layers at pertinent sites within the Lidar observation network. The findings affirm that the eastward movement and southward compression of the intensifying Mongolian cyclone led to severe dust storm weather in western and southern Mongolia, as well as Inner Mongolia, further transporting dust into northern, northwestern, and northeastern parts of China. This dust event wielded a substantial impact on a broad expanse in northern China, manifesting in localized dust storms in Inner Mongolia, Beijing, Gansu, and surrounding areas. In essence, the dust emanated from the deserts in Mongolia and northwest China, encompassing both deserts and the Gobi region. The amalgamation of ground-based and spaceborne Lidar observations conclusively establishes that the distribution height of dust in the source region ranged from 3 to 5 km. Influenced by high-pressure systems, the protracted transport of dust over extensive distances prompted a gradual reduction in its distribution height owing to sedimentation. The comprehensive analysis of pertinent research data and information collectively affirms the precision and efficacy of the three-dimensional aerosol monitoring conducted by the ground-based Lidar network within the region.

Nuclear Factor Y (NF-Y) is a class of heterotrimeric transcription factors composed of three subunits: NF-A, NF-YB, and NF-YC. NF-YC family members play crucial roles in various developmental processes, particularly in the regulation of flowering time. However, their functions in petunia remain poorly understood. In this study, we isolated four PhNF-YC genes from petunia and confirmed their subcellular localization in both the nucleus and cytoplasm. We analyzed the transcript abundance of all four PhNF-YC genes and found that PhNF-YC2 and PhNF-YC4 were highly expressed in apical buds and leaves, with their transcript levels decreasing before flower bud differentiation. Silencing PhNF-YC2 using VIGS resulted in a delayed flowering time and reduced chlorophyll content, while PhNF-YC4-silenced plants only exhibited a delayed flowering time. Furthermore, we detected the transcript abundance of flowering-related genes involved in different signaling pathways and found that PhCO, PhGI, PhFBP21, PhGA20ox4, and PhSPL9b were regulated by both PhNF-YC2 and PhNF-YC4. Additionally, the transcript abundance of PhSPL2, PhSPL3, and PhSPL4 increased only in PhNF-YC2-silenced plants. Overall, these results provide evidence that PhNF-YC2 and PhNF-YC4 negatively regulate flowering time in petunia by modulating a series of flowering-related genes.

Implant restoration is currently the most mainstream method for repairing missing teeth. With the increasing number of plantings, various planting complications begin to be paid attention to. Among them, there are many reports of disability phenomena such as loose and broken abutment screws and broken top screws, which cause the implant to fail or fail to function. In recent years, with the development of computer-aided software and its application in the field of oral treatment, digital guide plates based on 3D printing of oral CBCT scanning data are widely used in oral implants. Therefore, we explore the application prospect of post-core crown restoration after removing broken screws from the implant abutment with a digital guide plate. We reported a case of upper right first molar implant abutment screws broken, which were removed by a digital guide plate and customized turning bur. The resin-matrix ceramics crown post core was prepared, and then the occlusal force was tested by the T-ScanIII system. It provides a reference for the application of digital guide plates in special cases such as broken screws of implant abutment.

Introduction: This study aimed to assess the alleviative effect of quercetagetin (QG) on zearalenone (ZEN)-induced liver injury in rabbits.Methods: Ninety 41-day-old healthy Hyla rabbits were randomly assigned into three groups, including a control (fed with basic diet), ZEN addition group (fed with basic diet + 600 μg/kg ZEN), and ZEN + QG addition group (fed with basic diet + 600 μg/kg ZEN + 100 mg/kg QG), with 30 rabbits per group. The duration of the experiment was 28 days.Results: The results revealed no significant differences in the average daily gain, average daily feed intake, the gain to feed ratio and the liver, kidney and spleen organ indexes (p > 0.05) between the rabbits across the three groups. However, the sacculus rotundus index of the rabbits in the control group was significantly higher than that in the ZEN + QG group (p < 0.05). The intake of ZEN-contaminated diet also significantly increased the activities or levels of alanine transaminase, alkaline phosphatase, total bile acid (TBA), total bilirubin, malondialdehyde, and interleukin-4 (IL-4) and enhanced the abundance of kelch-like ECH-associated protein 1 (Keap1), heat shock protein 70 (HSP70) and cysteine-aspartic acid protease-3 (Caspase-3) mRNA in the blood or liver tissue in ZEN group, compared to the control group (p < 0.05). On the contrary, the activities or levels of immunoglobulin A, complement 3, total antioxidant capacity, glutathione peroxidase (GSH-Px), superoxide dismutase, interleukin-10, and the abundance of nuclear factor E2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) mRNA were significantly decreased (p < 0.05). Supplementing the diet with QG still maintained significantly higher levels of TBA and IL-4, and the abundance of GSH-Px, HSP70, IL-4, and Caspase-3 mRNA in the blood and liver of rabbits in the ZEN + QG group than in the control group (p < 0.05). At the same time, the other indicators were restored to levels in the control group (p > 0.05).Discussion: In conclusion, QG alleviated the ZEN-induced oxidative damage and liver injury caused by inflammatory reaction through the Keap1-Nrf2-antioxidant response element (ARE) signal pathway, which protected the liver. This study revealed the alleviative effect of QG on the hepatotoxicity of ZEN in rabbits for the first time, providing a new perspective for applying QG and developing a ZEN antidote.

Objectives: Previous studies showed that the central nervous system (CNS) controls movements by recruiting a low-dimensional set of modules, usually referred to as muscle synergies. Stroke alters the structure and recruitment patterns of muscle synergies, leading to abnormal motor performances. Some studies have shown that muscle synergies can be used as biomarkers for assessing motor function. However, coordination patterns of muscle synergies in post-stroke patients need more investigation to characterize how they are modified in functional movements.Methods: Thirteen mild-to-moderate stroke patients and twenty age-matched healthy subjects were recruited to perform two upper-limb movements, hand-to-mouth movement and reaching movement. Muscle synergies were extracted with nonnegative matrix factorization. We identified a set of reference synergies (i.e., averaged across healthy subjects) and typical synergies (i.e., averaged across stroke subjects) from the healthy group and stroke group respectively, and extracted affected synergies from each patient. Synergy similarity between groups was computed and analyzed. Synergy reconstruction analysis was performed to verify synergy coordination patterns in post-stroke patients.Results: On average, three synergies were extracted from both the healthy and stroke groups, while the mild impairment group had a significantly higher number of synergies than the healthy group. The similarity analysis showed that synergy structure was more consistent in the healthy group, and stroke instead altered synergy structure and induced more variability. Synergy reconstruction analysis at group and individual levels showed that muscle synergies of patients often showed a combination of healthy reference synergies in the analyzed movements. Finally, this study associated four synergy coordination patterns with patients: merging (equilibrium and disequilibrium), sharing (equilibrium and disequilibrium), losing, and preservation. The preservation was mainly represented in the mild impairment group, and the moderate impairment group showed more merging and sharing.Conclusion: This study concludes that stroke shows more synergy variability compared to the healthy group and the alterations of muscle synergies can be described as a combination of reference synergies by four synergy coordination patterns. These findings deepen the understanding of the underlying neurophysiological mechanisms and possible motor control strategies adopted by the CNS in post-stroke patients.

The genetic basis of spider major ampullate (Ma) gland silk production remains unknown. Hu et al. unveil a molecular atlas of this gland for the golden orb-weaving spider combining genome assembly and multiomics, revealing the single-cell spatial architecture of silk production in the Ma gland.

【Objective】To carry out cross breeding of high-quality Hybrid Cymbidium by using Hybrid Cymbidium germplasm resources, observe the performance of main target traits of offspring, and obtain new Hybrid Cymbidium varieties that meet the requirements of target traits.【Method】With Cymbidium sinense Yunv and C. lancifolium Wen Yin-1 as parents, conventional hybridization and seed culture of Hybrid Cymbidium were carried out. The characters of hybrid offspring were investigated and analyzed, and compared with their parents and control varieties Moye Amethyst.【Result】A new excellent Hybrid Cymbidium variety Yuqinglan was bred through the mixed selection breeding program. The collective hybrid was registered in the British Royal Horticultural Society under the name of Cymbidium SCAU Love Song. The results of variety comparison and many years of multi-point experiments show that Yuqinglan has compact plant type, erect leaves, erect inflorescences, 9.5 flowers on average, yellow white flowers with light fragrance, 5.6 cm in horizontal diameter and 5.9 cm in vertical diameter. It is cultivated in simple greenhouses in Guangzhou, and starts to flower in late December. Its single flower life is 30 days, and its ornamental period is 50 days. It is different from its parents in plant type, leaf type, and flower type, and its ornamental period is better than their parents, and it is more ornamental and disease resistant than the control Moye Amethyst, and it also has the characteristics of continuous flowering and forming flower lateral branches, which is the first report on orchids.【Conclusion】The new excellent Hybrid Cymbidium variety Yuqinglan, which has been bred through cross breeding and innovative improvement methods, has good characters and strong ornamental ability, and has broad prospects for popularization and application.

Purpose: Insufficient osseointegration and implant-associated infection are major factors in the failure of Ti-based implants, thus spurring scientists to develop multifunctional coatings that are better suited for clinical requirements. Here, a new biomimetic micro/nanoscale topography coating combined with antibacterial copper was simultaneously designed for Ti-based implant surfaces by adopting a hybrid approach combining plasma electrolytic oxidation and hydrothermal treatment.Results: The biological interactions between this biofunctionalized material interface and stem cells promoted cellular adhesion and spreading during initial attachment and supported cellular proliferation for favorable biocompatibility. Bone marrow mesenchymal stem cells (BMMSCs) on the coating displayed enhanced cellular mineral deposition ability, higher alkaline phosphatase activity, and upregulated expression of osteogenic-related markers without the addition of osteoinductive chemical factors, which improved osseointegration. More interestingly, this new coating reduced the viability of oral pathogens (Fusobacterium nucleatum and Porphyromonas gingivalis)—the primary causes of implant-associated infections as indicated by damage of cellular structures and decreased population. This is the first study investigating the antibacterial property of dental implants modified by a hybrid approach against oral pathogens to better mimic the oral environment.Conclusion: These findings suggest that biofunctionalization of the implant coating by surface modification methods and the incorporation of antibacterial copper (Cu) offer superior osteogenesis capability and effective antibacterial activity, respectively. These strategies have great value in orthopedic and dental implant applications.

Introduction: Muscle synergies have been proposed as a strategy employed by the central nervous system to control movements. Muscle synergy analysis is a well-established framework to examine the pathophysiological basis of neurological diseases and has been applied for analysis and assessment in clinical applications in the last decades, even if it has not yet been widely used in clinical diagnosis, rehabilitative treatment and interventions. Even if inconsistencies in the outputs among studies and lack of a normative pipeline including signal processing and synergy analysis limit the progress, common findings and results are identifiable as a basis for future research. Therefore, a literature review that summarizes methods and main findings of previous works on upper limb muscle synergies in clinical environment is needed to i) summarize the main findings so far, ii) highlight the barriers limiting their use in clinical applications, and iii) suggest future research directions needed for facilitating translation of experimental research to clinical scenarios. Methods: Articles in which muscle synergies were used to analyze and assess upper limb function in neurological impairments were reviewed. The literature research was conducted in Scopus, PubMed, and Web of Science. Experimental protocols (e.g., the aim of the study, number and type of participants, number and type of muscles, and tasks), methods (e.g., muscle synergy models and synergy extraction methods, signal processing methods), and the main findings of eligible studies were reported and discussed. Results: 383 articles were screened and 51 were selected, which involved a total of 13 diseases and 748 patients and 1155 participants. Each study investigated on average 15 ± 10 patients. Four to forty-one muscles were included in the muscle synergy analysis. Point-to-point reaching was the most used task. The preprocessing of EMG signals and algorithms for synergy extraction varied among studies, and non-negative matrix factorization was the most used method. Five EMG normalization methods and five methods for identifying the optimal number of synergies were used in the selected papers. Most of the studies report that analyses on synergy number, structure, and activations provide novel insights on the physiopathology of motor control that cannot be gained with standard clinical assessments, and suggest that muscle synergies may be useful to personalize therapies and to develop new therapeutic strategies. However, in the selected studies synergies were used only for assessment; different testing procedures were used and, in general, study-specific modifications of muscle synergies were observed; single session or longitudinal studies mainly aimed at assessing stroke (71% of the studies), even though other pathologies were also investigated. Synergy modifications were either study-specific or were not observed, with few analyses available for temporal coefficients. Thus, several barriers prevent wider adoption of muscle synergy analysis including a lack of standardized experimental protocols, signal processing procedures, and synergy extraction methods. A compromise in the design of the studies must be found to combine the systematicity of motor control studies and the feasibility of clinical studies. There are however several potential developments that might promote the use of muscle synergy analysis in clinical practice, including refined assessments based on synergistic approaches not allowed by other methods and the availability of novel models. Finally, neural substrates of muscle synergies are discussed, and possible future research directions are proposed. Conclusions: This review provides new perspectives about the challenges and open issues that need to be addressed in future work to achieve a better understanding of motor impairments and rehabilitative therapy using muscle synergies. These include the application of the methods on wider scales, standardization of procedures, inclusion of synergies in the clinical decisional process, assessment of temporal coefficients and temporal-based models, extensive work on the algorithms and understanding of the physio-pathological mechanisms of pathology, as well as the application and adaptation of synergy-based approaches to various rehabilitative scenarios for increasing the available evidence.

Essential oils, consisting of volatile compounds, are derived from various plant parts and possess antibacterial and antioxidant properties. Certain essential oils are utilized for medicinal purposes and can serve as natural preservatives in food products, replacing synthetic ones. This review describes how essential oils can promote the performance of bioactive films and preserve food through their antioxidant and antibacterial properties. Further, this article emphasizes the antibacterial efficacy of essential oil composite films for food preservation and analyzes their manufacturing processes. These films could be an attractive delivery strategy for improving phenolic stability in foods and the shelf-life of consumable food items. Moreover, this article presents an overview of current knowledge of the extraction of essential oils, their effects on bioactive films and food preservation, as well as the benefits and drawbacks of using them to preserve food products.

Recent progress has been made in defect detection using methods based on deep learning, but there are still formidable obstacles. Defect images have rich semantic levels and diverse morphological features, and the model is dynamically changing due to ongoing learning. In response to these issues, this article proposes a shunt feature fusion model (ST-YOLO) for steel-defect detection, which uses a split feature network structure and a self-correcting transmission allocation method for training. The network structure is designed to specialize the process of classification and localization tasks for different computing needs. By using the self-correction criteria of adaptive sampling and dynamic label allocation, more sufficiently high-quality samples are utilized to adjust data distribution and optimize the training process. Our model achieved better performance on the NEU-DET datasets and the GC10-DET datasets and was validated to exhibit excellent performance.

For Synthetic Aperture Radar (SAR) image registration, successive processes following feature extraction are required by both the traditional feature-based method and the deep learning method. Among these processes, the feature matching process—whose time and space complexity are related to the number of feature points extracted from sensed and reference images, as well as the dimension of feature descriptors—proves to be particularly time consuming. Additionally, the successive processes introduce data sharing and memory occupancy issues, requiring an elaborate design to prevent memory leaks. To address these challenges, this paper introduces the OptionEM-based reinforcement learning framework to achieve end-to-end SAR image registration. This framework outputs registered images directly without requiring feature matching and the calculation of the transformation matrix, leading to significant processing time savings. The Transformer architecture is employed to learn image features, while a correlation network is introduced to learn the correlation and transformation matrix between image pairs. Reinforcement learning, as a decision process, can dynamically correct errors, making it more-efficient and -robust compared to supervised learning mechanisms such as deep learning. We present a hierarchical reinforcement learning framework combined with Episodic Memory to mitigate the inherent problem of invalid exploration in generalized reinforcement learning algorithms. This approach effectively combines coarse and fine registration, further enhancing training efficiency. Experiments conducted on three sets of SAR images, acquired by TerraSAR-X and Sentinel-1A, demonstrated that the proposed method’s average runtime is sub-second, achieving subpixel registration accuracy.

Deep reinforcement learning is one of the research hotspots in artificial intelligence and has been successfully applied in many research areas; however, the low training efficiency and high demand for samples are problems that limit the application. Inspired by the rapid learning mechanisms of the hippocampus, to address these problems, a hierarchical episodic control model extending episodic memory to the domain of hierarchical reinforcement learning is proposed in this paper. The model is theoretically justified and employs a hierarchical implicit memory planning approach for counterfactual trajectory value estimation. Starting from the final step and recursively moving back along the trajectory, a hidden plan is formed within the episodic memory. Experience is aggregated both along trajectories and across trajectories, and the model is updated using a multi-headed backpropagation similar to bootstrapped neural networks. This model extends the parameterized episodic memory framework to the realm of hierarchical reinforcement learning and is theoretically analyzed to demonstrate its convergence and effectiveness. Experiments conducted in four-room games, Mujoco, and UE4-based active tracking highlight that the hierarchical episodic control model effectively enhances training efficiency. It demonstrates notable improvements in both low-dimensional and high-dimensional environments, even in cases of sparse rewards. This model can enhance the training efficiency of reinforcement learning and is suitable for application scenarios that do not rely heavily on exploration, such as unmanned aerial vehicles, robot control, computer vision applications, and so on.

In large-scale image retrieval, the deep learning-based hashing methods have significantly progressed. However, most of the existing deep hashing methods still have the problems of low feature learning efficiency and weak ranking relationship discrimination. To remedy these problems, a novel Ranking-based Deep Hashing Network (RDHN) is proposed for image retrieval in this paper, which integrates the feature learning module and hash learning module into a unified deep hashing network framework to jointly learn a powerful hash function so that the raw images can be mapped to discrete hash codes with significant discrimination. Specifically, a novel difference convolution is designed based on edge detection operators, and then it is uniquely applied to the first convolutional layer of the convolutional neural network (CNN), which can take advantage of the sensitive characteristics of edge detection operators for edge information to extract richer image edge information. Meanwhile, in hash learning, the ranking metric Mean Average Precision (MAP) is optimized using the idea of scaling, and then a ranking loss function based on MAP is carefully designed to enhance the neighborhood ranking capabilities of the hash codes. Furthermore, to reduce the quantification error, a quantization loss function is also designed. Finally, the ranking loss function is combined with the quantization loss function to form the objective function. The proposed method can generate high-quality discrete hash codes while learning to preserve ranking information, effectively improving retrieval performance. Extensive experimental results on three widely used benchmark datasets demonstrate that the proposed method outperforms the state-of-the-art hashing approaches.

The impact of biomass burning (BB) emissions on concentrations and depositions of major aerosol components in the northern South China Sea (NSCS) region (105∼115°E and 15∼21°N) from December 2020 to April 2021 has been investigated using the WRF-chem model (weather research and forecasting model coupled with chemistry) in combination with aerosol composition measurement at a mountain site in the Hainan Island of China. Model comparisons with observations in Hainan demonstrated the effectiveness of WRF-chem in simulating aerosol components (PM2.5, black carbon (BC), organic matter (OM), sulfate, nitrate, and ammonium) in the NSCS region. The influences of BB emissions were significant on near-surface PM2.5, BC, and OM but nearly negligible on secondary inorganic components (i.e., sulfate, nitrate, and ammonium). The NSCS regional and period mean PM2.5, BC, and OM concentrations were 17.2 μg/m3, 0.65 μg/m3, and 6.7 μg/m3, in which 20%, 13%, and 35%, respectively, were from BB emissions. The mean PM2.5, BC, and OM deposition fluxes were 73.8 mg/m2/month, 2.9 mg/m2/month, and 29.3 mg/m2/month, respectively, and 22%, 15%, and 38% of these depositions were from BB emissions. Dry deposition dominated the removal of aerosols. For both aerosol concentrations and depositions, the influences of BB emissions exhibited evidently larger contributions in spring (March and April) than those in winter (December to February). Most of the BB emissions were from mainland Southeast Asia (MSEA), in terms of period mean, 79%, 72%, and 81% of the BB PM2.5, BB BC, and BB OM concentrations and 82%, 77%, and 83% of their depositions in the NSCS region were attributed to the MSEA region. The results of this study suggested that BB emissions have strong implications for air quality and biogeochemical cycle of the NSCS region.

Abstract Background Glycolate oxidase (GLO) is not only a key enzyme in photorespiration but also a major engine for H2O2 production in plants. Catalase (CAT)-dependent H2O2 decomposition has been previously reported to be involved in the regulation of IAA biosynthesis. However, it is still not known which mechanism contributed to the H2O2 production in IAA regulation. Results In this study, we found that in glo mutants of rice, as H2O2 levels decreased IAA contents significantly increased, whereas high CO2 abolished the difference in H2O2 and IAA contents between glo mutants and WT. Further analyses showed that tryptophan (Trp, the precursor for IAA biosynthesis in the Trp-dependent biosynthetic pathway) also accumulated due to increased tryptophan synthetase β (TSB) activity. Moreover, expression of the genes involved in Trp-dependent IAA biosynthesis and IBA to IAA conversion were correspondingly up-regulated, further implicating that both pathways contribute to IAA biosynthesis as mediated by the GLO-dependent production of H2O2. Conclusion We investigated the function of GLO in IAA signaling in different levels from transcription, enzyme activities to metabolic levels. The results suggest that GLO-dependent H2O2 signaling, essentially via photorespiration, confers regulation over IAA biosynthesis in rice plants.

Abstract Background BRE-AS1 is a recently identified tumor suppressor in non-small cell lung cancer. It role in other human diseases remains elusive. Methods Differential expression of BRE-AS1 in with triple-negative breast cancer (TNBC) patients (n = 74, patient group) and healthy volunteers (n = 58, control group) was studied with RT-qPCR. The direct interaction between BRE-AS1 and premature microRNA-21 (miR-21) was assessed by RNA pull-down assay. The interactions among BRE-AS1, miR-21 and PTEN were evaluated by overexpression assays. CCK-8 assay and Transwell assay were used to evaluate cell behaviors. Results BRE-AS1 was downregulated in TNBC, while miR-21 was highly expressed in TNBC. Low expression levels of lncRNA BRE-AS1 and high expression levels of miR-21 were significantly correlated with unfavorable survival outcomes. BRE-AS1 and miRNA-21 were inversely correlated across TNBC samples, not control samples. BRE-AS1 decreased miR-21 expression and increased PTEN expression while miR-21showed no role in BRE-AS1 expression. RNA pull-down assay illustrated that BRE-AS1 may sponge premature miR-21 to suppress it maturation. Overexpression of BRE-AS1 decreased cell behaviors, while overexpression of miR-21 promoted cell behaviors. MiR-21 suppressed the role of BRE-AS1 in cancer cell behaviors. Conclusion Therefore, BRE-AS1 may inhibit TNBC by downregulating miR-21.

Muscle synergies have been largely used in many application fields, including motor control studies, prosthesis control, movement classification, rehabilitation, and clinical studies. Due to the complexity of the motor control system, the full repertoire of the underlying synergies has been identified only for some classes of movements and scenarios. Several extraction methods have been used to extract muscle synergies. However, some of these methods may not effectively capture the nonlinear relationship between muscles and impose constraints on input signals or extracted synergies. Moreover, other approaches such as autoencoders (AEs), an unsupervised neural network, were recently introduced to study bioinspired control and movement classification. In this study, we evaluated the performance of five methods for the extraction of spatial muscle synergy, namely, principal component analysis (PCA), independent component analysis (ICA), factor analysis (FA), nonnegative matrix factorization (NMF), and AEs using simulated data and a publicly available database. To analyze the performance of the considered extraction methods with respect to several factors, we generated a comprehensive set of simulated data (ground truth), including spatial synergies and temporal coefficients. The signal-to-noise ratio (SNR) and the number of channels (NoC) varied when generating simulated data to evaluate their effects on ground truth reconstruction. This study also tested the efficacy of each synergy extraction method when coupled with standard classification methods, including K-nearest neighbors (KNN), linear discriminant analysis (LDA), support vector machines (SVM), and Random Forest (RF). The results showed that both SNR and NoC affected the outputs of the muscle synergy analysis. Although AEs showed better performance than FA in variance accounted for and PCA in synergy vector similarity and activation coefficient similarity, NMF and ICA outperformed the other three methods. Classification tasks showed that classification algorithms were sensitive to synergy extraction methods, while KNN and RF outperformed the other two methods for all extraction methods; in general, the classification accuracy of NMF and PCA was higher. Overall, the results suggest selecting suitable methods when performing muscle synergy-related analysis.

Accurate and efficient short-term forecasting of multiple loads is of great significance to the operation control and scheduling of integrated energy distribution systems. In order to improve the effect of load forecasting, a mogrifier-quantum weighted memory enhancement long short-term memory (Mogrifier-QWMELSTM) neural network forecasting model is proposed. Compared with the conventional LSTM neural network model, the model proposed in this paper has three improvements in model structure and model composition. First, the mogrifier is added to make the data fully interact with each other. This addition can help enhance the correlation between the front and rear data and improve generalization, which is the main disadvantage of LSTM neural network. Second, the memory enhancement mechanism is added on the forget gate to realize the extraction and recovery of forgotten information. The addition can help improve the gradient transmission ability in the learning process of the neural network, make the neural network remain sensitive to distant data information, and enhance the memory ability. Third, the model is composed of quantum weighted neurons. Compared with conventional neurons, quantum weighted neurons have significant advantages in nonlinear data processing and parallel computing, which help to improve the accuracy of load forecasting. The simulation results show that the weighted mean accuracy of the proposed model can reach more than 97.5% in summer and winter. Moreover, the proposed model has good forecasting effect on seven typical days in winter, which shows that the model has good stability.

Abstract Background Vascular mimicry (VM) was associated with the prognosis of cancers. The aim of the study was to explore the association between VM and anticancer therapy response in patients with lung adenocarcinoma. Methods This was a single-center retrospective study of patients with lung adenocarcinoma between March 1st, 2013, to April 1st, 2019, at the Second People’s Hospital of Taizhou City. All included patients were divided into the VM and no-VM groups according to whether VM was observed or not in the specimen. Vessels with positive PAS and negative CD34 staining were confirmed as VM. The main outcome was progression-free survival (PFS). Results Sixty-six (50.4%) patients were male. Eighty-one patients received chemotherapy as the first-line treatment, and 50 patients received TKIs. Forty-five (34.4%) patients were confirmed with VM. There was no difference regarding the first-line treatment between the VM and no-VM groups (P = 0.285). The 86 patients without VM had a median PFS of 279 (range, 90–1095) days, and 45 patients with VM had a median PFS of 167 (range, 90–369) days (P

Gastric cancer is a leading cause of cancer death worldwide. Endoplasmic reticulum (ER) stress-induced apoptosis has been confirmed to be important in the treatment of gastric cancer. MiR-637 has recently been found to exert inhibitory effects on gastric cancer, and this study aimed to investigate whether miR-637 could regulate apoptosis through ER stress. The results showed that tunicamycin (TM) induced downregulation of miR-637 in gastric cancer cells (AGS) and increase of apoptosis and ER stress. Overexpression of miR-637 promoted TM-induced apoptosis and expression of ER stress associated proteins (GRP78 and CHOP), but inhibited expression of Calreticulin. MiR-637 could bind with the 3ʹ-UTR of CALR, and negatively regulated the expression of CALR. The co-transfection of miR-637 and CALR in AGS cells show that, CALR overexpression could reverse the pro-apoptosis effects of miR-637 in TM-treated cells. In conclusion, the present study suggests that miR-637 participates in ER stress-induced apoptosis in gastric cancer cells by suppressing CALR expression. miR-637 or CALR may be a future potential target for gastric cancer treatment.

Abstract Background The glyoxylate reductase (GR) multigene family has been described in various plant species, their isoforms show different biochemical features in plants. However, few studies have addressed the biological roles of GR isozymes, especially for rice. Results Here, we report a detailed analysis of the enzymatic properties and physiological roles of OsGR1 and OsGR2 in rice. The results showed that both enzymes prefer NADPH to NADH as cofactor, and the NADPH-dependent glyoxylate reducing activity represents the major GR activity in various tissues and at different growth stages; and OsGR1 proteins were more abundant than OsGR2, which is also a major contributor to total GR activities. By generating and characterizing various OsGR-genetically modified rice lines, including overexpression, single and double-knockout lines, we found that no phenotypic differences occur among the various transgenic lines under normal growth conditions, while a dwarfish growth phenotype was noticed under photorespiration-promoted conditions. Conclusion Our results suggest that OsGR1 and OsGR2, with distinct enzymatic characteristics, function redundantly in detoxifying glyoxylate in rice plants under normal growth conditions, whereas both are simultaneously required under high photorespiration conditions.

The complementary fusion of global and local features can effectively improve the performance of image retrieval. This article proposes a new local texture descriptor, combined with statistical modeling in transform domain for texture image retrieval. The proposed local descriptor calculates the eight directions of the central pixel by using the relationship between the central pixel and the neighboring pixels in six directions, which is called the local eight direction pattern (LEDP). In the texture image retrieval system of this article, the feature extraction part combines global statistical features and local pattern features. Among them, both the relative magnitude (RM) sub-band coefficients and relative phase (RP) sub-band coefficients are modeled as wrapped Cauchy (WC) distribution in the dual-tree complex wavelet transform (DTCWT) domain, and the global statistical features employ the parameters of this model; while the local pattern features respectively choose the local binary pattern (LBP) histogram features in the spatial domain and the LEDP histogram features of each direction sub-band in the DTCWT domain. On the other hand, the similarity measurement selects matching distances for different features and combines them in the form of convex linear optimization. Texture image retrieval experiments are conducted in the Corel-1k database (DB1), Brodatz texture database (DB2) and MIT VisTex texture database (DB3), respectively. Experimental results show that, compared with the best existing methods, the approach proposed in this article has achieved better retrieval performance.

Wolf spiders (Lycosidae) are crucial component of integrated pest management programs and the characteristics of their gut microbiota are known to play important roles in improving fitness and survival of the host. However, there are only few studies of the gut microbiota among closely related species of wolf spider. Whether wolf spiders gut microbiota vary with habitats remains unknown. Here, we used shotgun metagenomic sequencing to compare the gut microbiota of two wolf spider species, Pardosa agraria and P. laura from farmland and woodland ecosystems, respectively. The results show that the gut microbiota of Pardosa spiders is similar in richness and abundance. Approximately 27.3% of the gut microbiota of P. agraria comprises Proteobacteria, and approximately 34.4% of the gut microbiota of P. laura comprises Firmicutes. We assembled microbial genomes and found that the gut microbiota of P. laura are enriched in genes for carbohydrate metabolism. In contrast, those of P. agraria showed a higher proportion of genes encoding acetyltransferase, an enzyme involved in resistance to antibiotics. We reconstructed three high-quality and species-level microbial genomes: Vulcaniibacterium thermophilum, Anoxybacillus flavithermus and an unknown bacterium belonging to the family Simkaniaceae. Our results contribute to an understanding of the diversity and function of gut microbiota in closely related spiders.

The outbreak of a sudden infectious epidemic often causes serious casualties and property losses to the whole society. The COVID-19 epidemic that broke out in China at the end of December 2019, spread rapidly, resulting in large groups of confirmed diagnoses, and causing severe damage to China's society. This epidemic even now encompasses the globe. This paper takes the COVID-19 epidemic that has occurred in China as an example, the original data of this paper is derived from 20 Chinese media reports on COVID-19, and the grounded theory is used to analyze the original data to find the risk transmission rules of a sudden infectious epidemic. The results show that in the risk transmission of a sudden infectious epidemic, there are six basic elements: the risk source, the risk early warning, the risk transmission path, the risk transmission victims, the risk transmission inflection point, and the end of risk transmission. After a sudden infectious epidemic breaks out, there are three risk transmission paths, namely, a medical system risk transmission path, a social system risk transmission path, and a psychological risk transmission path, and these three paths present a coupling structure. These findings in this paper suggest that people should strengthen the emergency management of a sudden infectious epidemic by controlling of the risk source, establishing an efficient and scientific risk early warning mechanism and blocking of the risk transmission paths. The results of this study can provide corresponding policy implications for the emergency management of sudden public health events.

Nuclear Factor Y, Subunit C (NF-YC) transcription factors are conserved in most plants, and play essential roles in plant growth and development, especially in flowering regulation. Chrysanthemums are important commercial plants, and their market value is strongly impacted by flowering time. Until now, no details regarding the NF-YC family in the Chrysanthemum genus have been available. In this study, five NF-YC genes were cloned from Chrysanthemum indicum. Multiple alignments showed that CiNF-YCs had the highly conserved characteristic regions. Phylogenetic analyses identified a pair of paralogue NF-YC proteins in chrysanthemums. Gene structure and conserved motifs were also analyzed for functional understanding. According to the results of the expression experiments, CiNF-YC1 and CiNF-YC5 were mainly expressed in leaves or flowers, and their expression levels varied greatly from the seedling to flower bud differentiation stage. Arabidopsis overexpressing CiNF-YC1 and CiNF-YC3 showed significantly delayed flowering, accompanied by other morphological alterations. RT-qPCR analysis revealed that genes associated with photoperiod, vernalization, aging, and gibberellin pathways were downregulated in CiNF-YC1-OX lines, relative to the wild type, whereas in CiNF-YC3-OX lines, only SHORT VEGETATIVE PHASE (AtSVP), the key factor in the ambient temperature pathway, was upregulated. Taken together, these findings suggest that CiNF-YC1 and CiNF-YC3 negatively regulate flowering in Arabidopsis via different flowering pathways.

Based on the individual traits of the user’s construal level differences, this study examines the visual cognition differences of graphic–text combined icon concreteness in the interface between users with high and low construal levels. We classified four types of graphic–text combined icons, which are as follows: concrete graphic + concrete text (Ci + Ct), concrete graphic + abstract text (Ci + At), abstract graphic + concrete text (Ai + Ct), and abstract graphic + abstract text (Ai + At). According to the behavioral experiment results, there is no visual cognitive difference between the two types of traits users in Ci + Ct. In terms of Ci + At and Ai + Ct, the visual cognitive performance of high construal level users is slightly better than that of low construal level users. In Ai + At, there are obvious visual cognitive differences between the two types of users. Visual cognitive fluency plays a mediating role in response time and matching rates of the two types of users. Based on the construal level perspective, this study considers the visual cognitive differences based on the user’s stable traits. It provides a certain reference for the graphic–text combined icons’ design in the adaptive human–computer interaction interface.

In this study, an edible film based on funoran was developed. Moreover, the effects of plasticizers (glycerol, xylitol, and sorbitol) on the physicochemical properties of the funoran films were also investigated. The interactions between plasticizers and funoran molecules of the film-forming system were characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, and scanning electron microscopy. The results showed that the addition of plasticizers altered and broke the initial complex entangled structures of funoran molecular chains. Funoran films containing plasticizers were compatible, homogeneous, and dense, exhibiting good thermal stability below 100 °C. With the addition of plasticizers, the elongation at break, oxygen permeability, light transmittance, and water vapor permeability increased, but the tensile strength decreased. It was found that a glycerol addition of 40% was most suitable for commercial applications. All the results revealed the excellent film-forming properties of funoran, indicating that the prepared funoran films have tremendous potential for packaging applications.

Abstract Background NCA1 (NO CATALASE ACTIVITY 1) was recently identified in Arabidopsis as a chaperone protein to regulate catalase (CAT) activity through maintaining the folding of CAT. The gene exists mainly in higher plants; some plants, such as Arabidopsis, contain only one NCA1 gene, whereas some others such as rice harbor two copies. It is not yet understood whether and how both isoforms have functioned to regulate CAT activity in those two-copy-containing plant species. Results In this study, we first noticed that the spatiotemporal expression patterns of NCA1a and NCA1b were very similar in rice plants. Subsequent BiFC and yeast three-hybrid experiments demonstrated that both NCA1a and NCA1b show mutually exclusive, rather than simultaneous, interaction with CAT. For a further functional analysis, nca1a and nca1b single mutants or double mutants of rice were generated by CRISPR/Cas9. Analysis on these mutants under both normal and salinity stress conditions found that, as compared with WT, either nca1a or nca1b single mutant showed no difference at phenotypes and CAT activities, whereas the double mutants constantly displayed very low CAT activity (about 5%) and serious lesion phenotypes. Conclusions These results suggest that NCA1a and NCA1b show mutually exclusive interaction with CAT to regulate CAT activity in a functionally-redundant manner in rice.

Abstract The productivity evaluation of gas reservoirs is used to determine the optimal number of well pattern, which is an important part of the preparation of gas reservoir development plan. Using integral transformation and asymptotic analyses to solve the pseudo steady-state flow model in closed rectangular gas reservoir of constant thickness, analytic solution of pressure distribution of eccentric well can be obtained. This paper presents mathematical model of multiple wells producing from a closed gas reservoir by applying the principle of pressure superposition. The pseudo steady-state dimensionless production index is introduced to solve the multiple well mathematical models under the constant pressure, and the number of production wells and cumulative production in different production interval are obtained. The results of the calculation shows that the curve of the cumulative production and economic benefits have a maximum value when the producing time, gas price, and drilling costs are given, so it can determine the optimal number of wells and provide the basis for making gas reservoir development plan.

Seven new species of the genus Trilacuna Tong & Li, 2007: Trilacuna bawan Tong, Zhang & Li, sp. n. (male, female), T. datang Tong, Zhang & Li, sp. n. (male, female), T. fugong Tong, Zhang & Li, sp. n. (male, female), T. gongshan Tong, Zhang & Li, sp. n. (male, female), T. longling Tong, Zhang & Li, sp. n. (male, female), T. wuhe Tong, Zhang & Li, sp. n. (male, female), and T. xinping Tong, Zhang & Li, sp. n. (male, female) are described from Yunnan Province, China.

The evolution of mesoscale eddies is crucial for understanding the ocean energy cascade. In this study, using global reanalysis sea surface velocity data and a mesoscale eddy trajectory product tracked by satellite altimeters, we aimed to reveal the coherence of eddy kinetic energy (EKE) variation to low-frequency ageostrophic energy during the eddy life span. The variation in EKE throughout the eddy life span was highly coherent to that of the seven-day low-passed ageostrophic kinetic energy, with a correlation coefficient of −0.94. The low-frequency ageostrophic motions supplied 38% of the EKE variation in the growing stage of mesoscale eddies and absorbed 42% in the decaying stage. The evolution rate of the EKE during the eddy life span was consistent with the barotropic conversion rate of the low-frequency ageostrophic motions, further confirming the dominant role of low-frequency ageostrophic motions in eddy growth and decay.