Search Results (16)

Skin aging is commonly characterized by increased wrinkles, loss of elasticity, and hyperpigmentation, significantly affecting personal appearance and quality of life. Although botulinum toxin type A (BTX-A) has been widely applied in cosmetic anti-wrinkle treatments, its intrinsic cytotoxicity limits broader clinical applications. In this study, we developed a novel exosome-based BTX-A composite delivery system designed to synergize the anti-aging properties of exosomes with the wrinkle-reducing effects of BTX-A while reducing toxicity. Human adipose-derived mesenchymal stem cells were genetically modified via lentiviral transduction to overexpress Synaptic Vesicle Glycoprotein 2C (SV2C), the receptor of BTX-A, thereby producing SV2C-enriched functionalized exosomes (EXO^SV2C). These exosomes (2.0 × 10⁷ particles/mL) were incubated with BTX-A (3 U/mL) to generate the EXO^SV2C-BTX-A complex. In vitro, EXO^SV2C-BTX-A significantly promoted the proliferation and migration of human dermal fibroblasts and effectively alleviated D-galactose (D-gal)-induced cellular senescence and collagen type I loss. These effects were superior to those observed with either BTX-A or exosomes alone. In vivo, intradermal injection of EXO^SV2C-BTX-A for 28 days markedly suppressed D-gal-induced skin aging in 8-week-old male KM mice, as evidenced by reduced malondialdehyde levels in dermal tissue, enhanced collagen type I expression, and preserved skin structure. Notably, the composite exhibited significantly lower toxicity compared to free BTX-A. Collectively, these findings highlight EXO^SV2C-BTX-A as a promising exosome-mediated BTX-A delivery platform with enhanced anti-aging efficacy and improved biocompatibility, offering a potential therapeutic strategy for skin rejuvenation. Full article

Autonomous Unmanned Surface Vehicle (USV) operations in complex ocean engineering scenarios necessitate robust navigation, guidance, and control technologies. These systems require reliable sensor-based object detection and efficient, safe, and energy-aware path planning. To address these multifaceted challenges, this paper proposes a novel synergistic AI framework. The framework integrates (1) a novel adaptation of the Swin-Transformer to generate a dense, semantic risk map from raw visual data, enabling the system to interpret ambiguous marine conditions like sun glare and choppy water, enabling real-time environmental understanding crucial for guidance; (2) a Transformer-enhanced A-star (T-ASTAR) algorithm with spatio-temporal attentional guidance to generate globally near-optimal and energy-aware static paths; (3) a domain-adapted TD3 agent featuring a novel energy-aware reward function that optimizes for USV hydrodynamic constraints, making it suitable for long-endurance missions tailored for USVs to perform dynamic local path optimization and real-time obstacle avoidance, forming a key control element; and (4) CUDA acceleration to meet the computational demands of real-time ocean engineering applications. Simulations and real-world data verify the framework’s superiority over benchmarks like A* and RRT, achieving 30% shorter routes, 70% fewer turns, 64.7% fewer dynamic collisions, and a 215-fold speed improvement in map generation via CUDA acceleration. This research underscores the importance of integrating powerful AI components within a hierarchical synergy, encompassing AI-based perception, hierarchical decision planning for guidance, and multi-stage optimal search algorithms for control. The proposed solution significantly advances USV autonomy, addressing critical ocean engineering challenges such as navigation in dynamic environments, object avoidance, and energy-constrained operations for unmanned maritime systems. Full article

Members of the B-Box (BBX) family of proteins play crucial roles in the growth and development of rice. Here, we identified a rice BBX protein, Oryza sativa BBX2 (OsBBX2), which exhibits the highest expression in the root. The transcription of OsBBX2 follows a diurnal rhythm under photoperiodic conditions, peaking at dawn. Functional analysis revealed that OsBBX2 possesses transcriptional repression activity. The BBX2 was overexpressed in the rice japonica cultivar Longjing 11 (LJ11), in which Ghd7 and PRR37 were non-functional or exhibited weak functionality. The overexpression of OsBBX2 (OsBBX2 OE) resulted in a delayed heading date under a long-day (LD) condition, whereas the bbx2 mutant exhibited flowering patterns similar to the wild type (WT). Additionally, transcripts of Ehd1, Hd3a, and RFT1 were downregulated in the OsBBX2 OE lines under the LD condition. OsBBX2 interacted with Hd1 (BBX18), and the bbx2 hd1 double mutant displayed a late flowering phenotype comparable to that of hd1. Furthermore, OsBBX2 enhanced the transcriptional repression of Hd3a through its interaction with Hd1, as demonstrated in the protoplast-based assay. Taken together, these findings suggest that the OsBBX2 delays flowering by interacting with Hd1 and co-repressing Hd3a transcription. Full article

The global navigation satellite system reflectometry (GNSS-R) technique has shown promise in retrieving sea levels using signal-to-noise ratio (SNR) data. However, its accuracy and performance are often limited compared to conventional tide gauges, particularly due to constraints in satellite elevation angles. To address these limitations, we propose a methodology integrating Long Short-Term Memory Deep Neural Networks (LSTM-DNN) models, utilising SNR residual sequences as key feature inputs. Our study focuses on the SC02 station, examining elevation angles ranging from 5° to 10°, 5° to 15°, and 5° to 20°. Results reveal notable reductions in root mean square errors (RMSE) of 2.855%, 17.519%, and 15.756%, respectively, showcasing improvements in accuracy across varying elevation angles. Of particular significance is the enhancement in precision observed at higher elevation angles. This underscores the valuable contribution of our approach to nearshore sea level wave height retrieval, promising advancements in the GNSS-R technique. Full article

Cold stress at the booting stage leads to a lower seed setting rate and seriously threatens the production of rice (Oryza sativa L.), which has become a major yield-limiting factor in higher-altitude and -latitude regions. Because cold tolerance at the booting stage (CTB) is a complex trait and is controlled by multiple loci, only a few genes have been reported so far. In this study, a function of OsMKKK70 (Mitogen Activated Protein Kinase Kinase Kinase 70) in response to CTB was characterized. OsMKKK70 expression was rapidly induced by cold stress at the booting stage. OsMKKK70 overexpression (OsMKKK70-OE) plants were more sensitive to cold stress at the booting stage with a lower seed setting and pollen fertility, but there was no significant difference between the osmkkk70 mutant and WT. Considering the effect of functional redundancy, we further tested the CTB response of osmkkk62/70 and osmkkk55/62/70, the double and triple mutants of OsMKKK70 with its closest homologs OsMKKK62 and OsMKKK55, and found that osmkkk62/70 and osmkkk55/62/70 displayed significantly increased CTB with a higher seed setting and pollen fertility, indicating that OsMKKK70 negatively regulates rice CTB. Moreover, under the low-temperature (LT) condition, the osmkkk62/70 mutant had slightly higher Gibberellin (GA) contents, increased expression of GA biosynthesis genes, and lower protein level of OsSLR1 in anthers than those in WT. By contrast, OsMKKK70-OE anther had a lower GA biosynthesis than that of WT. Together, these findings suggest that OsMKKK70 negatively regulates rice CTB by fine-tuning GA levels in anthers. Full article

Photocatalysis is an effective technology for NO removal even at low concentrations in the ambient atmosphere. However, the low efficiency of this advanced process and the tendency of producing toxic byproducts hinder the practical application of photocatalysis. To overcome these problems, the Bi@Ba₂TiO₄/BaBi₄Ti₄O₁₅ photocatalytic composites were successfully prepared by a one-step hydrothermal method. The as-synthesized photocatalysts exhibited an efficient photocatalytic performance and generated low amounts of toxic byproducts. X-ray diffraction studies show that Bi³⁺ is successfully reduced on the surface of Ba₂TiO₄/BaBi₄Ti₄O₁₅ (BT/BBT). After L-Ascorbic acid (AA) modification, the photocatalytic NO removal efficiency of Bi@Ba₂TiO₄/BaBi₄Ti₄O₁₅ is increased from 25.55% to 67.88%, while the production of the toxic byproduct ${\mathrm{NO}}_2$ is reduced by 92.02%, where the initial concentration of NO is diluted to ca. 800 ppb by the gas stream and the flow rate is controlled at 301.98 mL·min⁻¹ in a 150 mL cylindrical reactor. Furthermore, ambient humidity has little effect on the photocatalytic performance of theBi@Ba₂TiO₄/BaBi₄Ti₄O₁₅, and the photocatalyst exhibits excellent reusability after repeated cleaning with deionized water. The improved photocatalytic effect is attributed to the addition of AA in BT/BBT being able to reduce Bi³⁺ ions to form Bi nanoparticles giving surface plasmon effect (SPR) and generate oxygen vacancies (OVs) at the same time, thereby improving the separation efficiency of photogenerated carriers, enhancing the light absorption, and increasing the specific surface areas. The present work could provide new insights into the design of high-performance photocatalysts and their potential applications in air purification, especially for NO removal. Full article

We report on a novel colorimetric sensor system for highly sensitive detection of formaldehyde (FA) in the gas phase. The sensor is constructed with paper towel as a substrate coated with the sulfuric acid salt of hydroxylamine ((NH₂OH)₂·H₂SO₄) together with two pH indicators, bromophenol blue and thymol blue. Upon exposure to FA, the hydroxylamine will react with the absorbed FA to form a Schiff base (H₂C=N-OH), thus releasing a stoichiometric amount of sulfuric acid, which in turn induces a color change of the pH indicator. Such a color change was significantly enriched by incorporating two pH indicators in the system. With the optimized molar ratio of the two pH indicators, the color change (from brown to yellow, and to red) could become so dramatic as to be visible to the eye depending on the concentration of FA. In particular, under 80 ppb of FA (the air quality threshold set by WHO) the color of the sensor substrate changes from brown to yellow, which can even be envisioned clearly by the naked eyes. By using a color reader, the observed color change can be measured quantitatively as a function of the vapor concentration of FA, which produces a linear relationship as fitted with the data points. This helps estimate the limit of detection (LOD), to be 10 ppb under an exposure time of 10 min, which is much lower than the air quality threshold set by WHO. The reported sensor also demonstrates high selectivity towards FA with no color change observed when exposed to other common chemicals, including solvents and volatile organic compounds. With its high sensitivity and selectivity, the proposed paper-based colorimetric sensor thus developed can potentially be employed as a low-cost and disposable detection kit that may find broad application in detecting FA in indoor air and many other environments. Full article

Poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) is a highly important and attractive conducting polymer as well as commercially available in organic electronics, including electrochemical and electronic chemosensors, due to its unique features such as excellent solution-fabrication capability and miscibility, high and controllable conductivity, excellent chemical and electrochemical stability, good optical transparency and biocompatibility. In this review, we present a comprehensive overview of the recent research progress of PEDOT:PSS and its composites, and the application in electrochemical and electronic sensors for detecting liquid-phase or gaseous chemical analytes, including inorganic or organic ions, pH, humidity, hydrogen peroxide (H₂O₂), ammonia (NH₃), CO, CO₂, NO₂, and organic solvent vapors like methanol, acetone, etc. We will discuss in detail the structural, architectural and morphological optimization of PEDOT:PSS and its composites with other additives, as well as the fabrication technology of diverse sensor systems in response to a wide range of analytes in varying environments. At the end of the review will be given a perspective summary covering both the key challenges and potential solutions in the future research of PEDOT:PSS-based chemosensors, especially those in a flexible or wearable format. Full article

Perylene imide (PI) molecules and materials have been extensively studied for optical chemical sensors, particularly those based on fluorescence and colorimetric mode, taking advantage of the unique features of PIs such as structure tunability, good thermal, optical and chemical stability, strong electron affinity, strong visible light absorption and high fluorescence quantum yield. PI-based optical chemosensors have now found broad applications in gas phase detection of chemicals, including explosives, biomarkers of some food and diseases (such as organic amines (alkylamines and aromatic amines)), benzene homologs, organic peroxides, phenols and nitroaromatics, etc. In this review, the recent research on PI-based fluorometric and colorimetric sensors, as well as array technology incorporating multiple sensors, is reviewed along with the discussion of potential applications in environment, health and public safety areas. Specifically, we discuss the molecular design and aggregate architecture of PIs in correlation with the corresponding sensor performances (including sensitivity, selectivity, response time, recovery time, reversibility, etc.). We also provide a perspective summary highlighting the great potential for future development of PIs optical chemosensors, especially in the sensor array format that will largely enhance the detection specificity in complexed environments. Full article

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases in wheat. Due to the large-scale and widely-distributed planting pattern of wheat, the directional selection pressure of the pathogen is very strong. Therefore, it is urgent to pyramid more stripe rust resistance genes in wheat cultivars to enhance resistance durability and ensure wheat production safety. In this study, two quantitative trait loci (QTL) for adult plant resistance (APR) to stripe rust, QYr.nafu-2BL and QYr.nafu-3BS, were validated and introgressed from wheat line P9897 into three Chinese elite wheat cultivars, Chuanmai 42, Xiangmai 25, and Zhengmai 9023, through marker validation. The three Chinese elite varieties were used as the female parent to cross with wheat line P9897, and they were selfed to the F₆ generation. A total of 114 lines were then selected based on field agronomic traits and stripe rust resistance. Four markers (Xcfd73, Xgwm120, Xbarc87 and Xbarc133) linked with the QTL’s regions were employed to screen the 114 F₆ lines. Subsequently, 27 lines combining two target QTL from P9897 were selected. The combination of agronomic traits and disease resistance results showed that 13 of these selected lines had favorable application prospects. The promising lines selected in this study could enrich the genetic resources of wheat stripe rust resistance genes, as well as provide material support and a theoretical basis for the prevention and control of wheat stripe rust in China. Full article

The Standardized Precipitation Evapotranspiration Index (SPEI) is widely used for climatological and hydrological studies, in which the estimation of potential evapotranspiration (PET) is of great importance. As many different models exist in estimating PET, the question that arises is in which way the selection of the PET model affects the calculated SPEI and the drought assessment. This study, on the basis of evaluating drought conditions over the Hexi Inland River Basin in China with long-term climate data of 18 stations by using SPEI, compared three types and eight kinds different PET models with respect to their sensitivity to the calculation of SPEI, and to drought events and drought characteristics. The results showed that the study area experienced a drying trend over the past 56 years, and the extreme drought events occurred more frequently after 2000 as a whole. All the investigated PET models were sensitive to the estimation of SPEI and to the drought assessment. When considering the alternatives of the Thornthwaite model in the calculation of SPEI for drought identification, the Blaney–Criddle equation among the temperature-based models and the Makkink equation among the radiation-based models are recommended due to the comparable results in determining the drought trends, drought events, and drought characteristics. Full article

Trauma is considered a “modern civilized sickness”, and its occurrence substantially affects all of society, as well as individuals. The implementation of trauma emergency systems in cities with young, prosperous, and highly mobile populations is necessary and significant. A complete trauma emergency system includes both low-level trauma centers that offer basic emergency services and high-level trauma centers that offer comprehensive services. GIS and operational research methods were used to solve the location problem associated with these centers. This study analyzed the spatial distribution characteristics of trauma demands and the candidate locations of trauma centers based on a spatial analysis and presented a hierarchical location-allocation model for low- and high-level trauma centers in Shenzhen. The response, coverage, treatment and cost capacities of the trauma center locations were considered, and an ant colony optimization was used to calculate the optimal solution. The objectives of this study were to optimize trauma center locations, improve the allocation of medical trauma resources and reduce the rate of deaths and disabilities due to trauma. Full article

With the coming era of big data and the rapid development and widespread applications of Geographical Information Systems (GISs), geocoding technology is playing an increasingly important role in bridging the gap between non-spatial data resources and spatial data in various fields. However, Chinese geocoding faces great challenges because of the complexity of the address string format in Chinese, which contains no delimiters between Chinese words, and the poor address management resulting from the existence of multiple address authorities spread among different governmental agencies. This paper presents a geocoding service based on an optimized Chinese address matching method, including address modeling, address standardization and address matching. The address model focuses on the spatial semantics of each address element, and the address standardization process is based on an address tree model. A geocoding service application is implemented in practice using a large quantity of data from Shenzhen Municipality. More than 1,460,000 data records were used to test the geocoding service, and good matching rates were achieved with good adaptability and intelligence. Full article

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. Full article

Research on spatial cluster detection of traffic crash (TC) at the city level plays an essential role in safety improvement and urban development. This study aimed to detect spatial cluster pattern and identify riskier road segments (RRSs) of TC constrained by network with a two-step integrated method, called NKDE-GLINCS combining density estimation and spatial autocorrelation. The first step is novel and involves in spreading TC count to a density surface using Network-constrained Kernel Density Estimation (NKDE). The second step is the process of calculating local indicators of spatial association (LISA) using Network-constrained Getis-Ord Gi* (GLINCS). GLINCS takes the smoothed TC density as input value to identify locations of road segments with high risk. This method was tested using the TC data in 2007 in Wuhan, China. The results demonstrated that the method was valid to delineate TC cluster and identify risk road segments. Besides, it was more effective compared with traditional GLINCS using TC counting as input. Moreover, the top 20 road segments with high-high TC density at the significance level of 0.1 were listed. These results can promote a better identification of RRS, which is valuable in the pursuit of improving transit safety and sustainability in urban road network. Further research should address spatial-temporal analysis and TC factors exploration. Full article