Search Results (7,627)

Background/Objectives: The development of polymer–lipid hybrid nanoparticles (PLNs) is a promising area of research, as it can help increase the stability of cationic lipid carriers. Hybrid PLNs are core–shell nanoparticle structures that combine the advantages of both polymer nanoparticles and liposomes, especially in terms of their physical stability and biocompatibility. Natural polymers such as polyhydroxyalkanoate (PHA) can be used as a matrix for the PLNs’ preparation. Methods: In this study, we first obtained stable cationic hybrid PLNs using a cationic liposome (CL) composed of a polycationic lipid 2X3 (1,26-bis(cholest-5-en-3β-yloxycarbonylamino)-7,11,16,20-tetraazahexacosane tetrahydrochloride), helper lipid DOPE (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine), and the hydrophobic polymer mcl-PHA, which was produced by the soil bacterium Pseudomonas helmantisensis P1. Results: The new polymer-lipid carriers effectively encapsulated and delivered model mRNA-eGFP (enhanced green fluorescent protein mRNA) to BHK-21 cells. We then evaluated the role of mcl-PHA in increasing the stability of cationic PLNs in ionic solutions using dynamic light scattering data, electrophoretic mobility, and transmission electron microscopy techniques. Conclusions: The results showed that increasing the concentration of PBS (phosphate buffered saline) led to a decrease in the stability of the CLs. At high concentrations of PBS, the CLs aggregate. In contrast, the presence of isotonic PBS did not result in the aggregation of PLNs, and the particles remained stable for 120 h when stored at +4 °C. The obtained results show that PLNs hold promise for further in vivo studies on nucleic acid delivery. Full article

The increased intensity and frequency of extreme climate events (ECEs) have significantly impacted vegetation phenology, further profoundly affecting the structure and functioning of terrestrial ecosystems. However, the mechanisms by which ECEs affect the end of the growing season (EOS), a crucial phenological phase, remain unclear. In this study, we first evaluated the temporal variations in the EOS anomalies in Northern China (NC) based on the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from 2001 to 2018. We then used event coincidence analysis (ECA) to assess the susceptibility of EOS to four ECEs (i.e., extreme heat, extreme cold, extreme wet and extreme dry events). Finally, we examined the dependence of the response of EOS to ECEs on background climate conditions. Our results indicated a slight decrease in the proportion of areas experiencing extreme heat and dry events (1.10% and 0.66% per year, respectively) and a slight increase in the proportion of areas experiencing extreme wet events (0.77% per year) during the preseason period. Additionally, EOS exhibited a delaying trend at a rate of 0.25 days/a during the study period. The susceptibility of EOS to ECEs was closely related to local hydrothermal conditions, with higher susceptibility to extreme dry and extreme hot events in drier and warmer areas and higher susceptibility to extreme cold and extreme wet events in wetter regions. Grasslands, in contrast to forests, were more sensitive to extreme dry, hot and cold events due to their weaker resistance to water deficits and cold stress. This study sheds light on how phenology responds to ECEs across various ecosystems and hydrothermal conditions. Our results could also provide a valuable guide for ecosystem management in arid regions. Full article

Background/Objectives: The usefulness of dual-energy computed tomography (DECT) for low absorption in the parenchymal phase and contrast effects in the delayed phase for pancreatic cancer is not clear. Therefore, the diagnostic capability of low-KeV images obtained using DECT for pancreatic cancer in the pancreatic parenchymal and delayed phases was evaluated quantitatively and qualitatively. Methods: Twenty-five patients with pancreatic cancer who underwent contrast-enhanced DECT were included. A total of 50 and 70 KeV CT images, classified as low-keV and conventional CT-equivalent images, were produced, respectively. The tumor-to-pancreas contrast (Hounsfield units [HU]) in the pancreatic parenchymal and delayed phases was calculated by subtracting the CT value of the pancreatic tumor from that of normal parenchyma. Results: The median tumor-to-pancreas contrast on 50 KeV CT in the pancreatic parenchymal phase (133 HU) was higher than that on conventional CT (68 HU) (p < 0.001). The median tumor-to-pancreas contrast in the delayed phase was −28 HU for 50 KeV CT and −9 HU for conventional CT (p = 0.545). For tumors < 20 mm, the tumor-to-pancreas contrast of 50 KeV CT (−39 HU) had a significantly clearer contrast effect than that of conventional CT (−16.5 HU), even in the delayed phase (p = 0.034). Conclusions: These 50 KeV CT images may clarify the low-absorption areas of pancreatic cancer in the pancreatic parenchymal phase. A good contrast effect was observed in small pancreatic cancers on 50 KeV delayed-phase images, suggesting that DECT is useful for the visualization of early pancreatic cancer with a small tumor diameter. Full article

Septic arthritis (SA) represents an orthopedics urgency and mainly affects the knee joint. Due to its devastating effects on cartilage, immediate management is crucial. SA is characterized by an annual incidence of 2 to 10 cases per 100,000 individuals, with mortality rates fluctuating between 0.5% and 15%, with a substantially higher mortality rate observed in older people (15%) in contrast to younger cohorts (4%). The etiology of septic arthritis is multifactorial: a spectrum of Gram-positive and Gram-negative bacteria can contribute to the development of this condition, especially Staphylococcus aureus. The treatment involves urgent (arthroscopic or arthrotomic) debridement associated with adequate antibiotic therapy. Intra-articular antibiotic carriers can also be used to increase their local concentration and effectiveness. The case of a 67-year-old woman affected by knee SA from methicillin-susceptible S. aureus is presented. She was treated with an arthroscopic debridement enhanced by intra-articular antibiotic-loaded calcium sulphate beads, together with antibiotic therapy. At 2-year follow up, the infection had been eradicated and the patient fully recovered. This is the first description, to our knowledge, in the English literature, of the use of antibiotic-loaded calcium sulphate beads as an adjuvant in the surgical treatment of SA of a native knee joint. Full article

Although deep learning techniques have potential in vehicle behavior prediction, it is difficult to integrate traffic rules and environmental information. Moreover, its black-box nature leads to an opaque and difficult-to-interpret prediction process, limiting its acceptance in practical applications. In contrast, ontology reasoning, which can utilize human domain knowledge and mimic human reasoning, can provide reliable explanations for the speculative results. To address the limitations of the above deep learning methods in the field of vehicle behavior prediction, this paper proposes a front vehicle behavior prediction method that combines deep learning techniques with ontology reasoning. Specifically, YOLOv5s is first selected as the base model for recognizing the brake light status of vehicles. In order to further enhance the performance of the model in complex scenes and small target recognition, the Convolutional Block Attention Module (CBAM) is introduced. In addition, so as to balance the feature information of different scales more efficiently, a weighted bi-directional feature pyramid network (BIFPN) is introduced to replace the original PANet structure in YOLOv5s. Next, using a four-lane intersection as an application scenario, multiple factors affecting vehicle behavior are analyzed. Based on these factors, an ontology model for predicting front vehicle behavior is constructed. Finally, for the purpose of validating the effectiveness of the proposed method, we make our own brake light detection dataset. The accuracy and [email protected] of the improved model on the self-made dataset are 3.9% and 2.5% higher than that of the original model, respectively. Afterwards, representative validation scenarios were selected for inference experiments. The ontology model created in this paper accurately reasoned out the behavior that the target vehicle would slow down until stopping and turning left. The reasonableness and practicality of the front vehicle behavior prediction method constructed in this paper are verified. Full article

This study introduces a novel multi-criteria group evaluation approach grounded in the theory of basic uncertain information (BUI) to facilitate the selection of green recycling suppliers for shared electric bikes. Firstly, a comprehensive index system of green recycling suppliers is established, encompassing recycling capacity, environmental sustainability, financial strength, maintenance capabilities, and policy support, to provide a solid foundation for the scientific selection process. Secondly, the basic uncertain information generalized power weighted average (BUIGPWA) operator is proposed to aggregate group evaluation information with BUI pairs, and some related properties are investigated. Furthermore, the basic uncertain information-based best–middle–worst TOPSIS (BUI-BMW-TOPSIS) model incorporating the best, middle, and worst reference points to enhance decision-making accuracy is proposed. Ultimately, by integrating the BUIGPWA operator for group information aggregation with the BUI-BMW-TOPSIS model to handle multi-criteria decision information, a novel multi-criteria group decision-making (MCGDM) method is constructed to evaluate green recycling suppliers for shared electric bikes. Case analyses and comparative analyses demonstrate that compared with the BUIWA operator, the BUIGPWA operator yields more reliable results because of its consideration of the degree of support among decision-makers. Furthermore, in contrast to the traditional TOPSIS method, the BUI-BMW-TOPSIS model incorporates the credibility of information provided by decision-makers, leading to more trustworthy outcomes. Notably, variations in attribute weights significantly impact the decision-making results. In summary, our methods excel in handling uncertain information and complex multi-criteria group decisions, boosting scientific rigor and reliability, and supporting optimization and sustainability of shared electric bike green recycling suppliers. Full article

Automatic ship detection is a crucial task within the domain of maritime transportation management. With the progressive success of convolutional neural networks (CNNs), a number of advanced CNN models have been presented in order to detect ships. Although these detection models have achieved marked performance, several undesired results may occur under complex maritime conditions, such as missed detections, false positives, and low detection accuracy. Moreover, the existing detection models endure large number of parameters and heavy computation cost. To deal with these problems, we suggest a lightweight ship model of detection called DSSM–LightNet based upon the improved YOLOv8n. First, we introduce a lightweight Dual Convolutional (DualConv) into the model to lower both the number of parameters and the computational complexity. The principle is that DualConv combines two types of convolution kernels, 3x3 and 1x1, and utilizes group convolution techniques to effectively reduce computational costs while processing the same input feature map channels. Second, we propose a Slim-neck structure in the neck network, which introduces GSConv and VoVGSCSP modules to construct an efficient feature-fusion layer. This fusion strategy helps the model better capture the features of targets of different sizes. Meanwhile, a spatially enhanced attention module (SEAM) is leveraged to integrate with a Feature Pyramid Network (FPN) and the Slim-neck to achieve simple yet effective feature extraction, minimizing information loss during feature fusion. CIoU may not accurately reflect the relative positional relationship between bounding boxes in some complex scenarios. In contrast, MPDIoU can provide more accurate positional information in bounding-box regression by directly minimizing point distance and considering comprehensive loss. Therefore, we utilize the minimum point distance IoU (MPDIoU) rather than the Complete Intersection over Union (CIoU) Loss to further enhance the detection precision of the suggested model. Comprehensive tests carried out on the publicly accessible SeaShips dataset have demonstrated that our model greatly exceeds other algorithms in relation to their detection accuracy and efficiency, while reserving its lightweight nature. Full article

Objectives: To evaluate the value of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) for discriminability of severe lung injury and atelectasis in polytraumatized patients. Materials & Methods: Contrast-enhanced PCD-CT examinations of 20 polytraumatized patients with severe thoracic trauma were included in this retrospective study. Spectral PCD-CT data were reconstructed using a noise-optimized virtual monoenergetic imaging (VMI) algorithm with calculated VMIs ranging from 40 to 120 keV at 10 keV increments. Injury-to-atelectasis contrast-to-noise ratio (CNR) was calculated and compared at each energy level based on CT number measurements in severely injured as well as atelectatic lung areas. Three radiologists assessed subjective discriminability, noise perception, and overall image quality. Results: CT values for atelectasis decreased as photon energy increased from 40 keV to 120 keV (mean Hounsfield units (HU): 69 at 40 keV; 342 at 120 keV), whereas CT values for severe lung injury remained near-constant from 40 keV to 120 keV (mean HU: 42 at 40 keV; 44 at 120 keV) with significant differences at each keV level (p < 0.001). The optimal injury-to-atelectasis CNR was observed at 40 keV in comparison with the remaining energy levels (p < 0.001) except for 50 keV (p > 0.05). In line with this, VMIs at 40 keV were rated best regarding subjective discriminability. VMIs at 60–70 keV, however, provided the highest subjective observer parameters regarding subjective image noise as well as image quality. Conclusions: Discriminability between severely injured and atelectatic lung areas after thoracic trauma can be substantially improved by virtual monoenergetic imaging from PCD-CT with superior contrast and visual discriminability at 40–50 keV. Full article

The use of SGLT2 inhibitors (SGLT2is) has been found in large clinical studies to slow the progression of chronic kidney disease (CKD) and to lower the risk of acute kidney injury (AKI). Recent reports suggest that SGLT2is may also reduce the likelihood of developing radiocontrast-associated nephropathy (CAN) following contrast-enhanced imaging and intravascular interventions. This review underscores potential pitfalls and confounders in these studies and calls for caution in adopting their conclusions regarding the safety and renoprotective potency of SGLT2is, in particular in patients at high risk, with advanced CKD and hemodynamic instability undergoing coronary intervention. This caution is particularly warranted since both SGLT2is and contrast media intensify medullary hypoxia in the already hypoxic diabetic kidney and their combination may lead to medullary hypoxic damage, a principal component of CAN. Further studies are needed to evaluate this dispute, particularly in patients at high risk, and to reveal whether SGLT2is indeed provide renal protection or are hazardous during contrast-enhanced imaging and vascular interventions. Full article

Androgenetic alopecia (AGA) is a genetic condition characterized by an excessive response to androgens, leading to hairline regression in men and hair thinning at the vertex in women, which can negatively impact self-esteem. Conventional synthetic treatments for AGA are often limited by their side effects. In contrast, Thai medicinal plants offer a promising alternative with fewer adverse effects. This study investigates the synergistic phytochemical and pharmacological effects of a novel Hair Rise^TM microemulsion, formulated with bioactive extracts from rice bran (Oryza sativa), shallot bulb (Allium ascalonicum), licorice root (Glycyrrhiza glabra), and corn kernels (Zea mays), for the treatment of hair loss. The microemulsion, in concentrations of 50%, 75%, and 100% (v/v), significantly enhanced the proliferation of human hair follicle dermal papilla cells (HFDPCs) compared to minoxidil. Additionally, it upregulated critical hair growth signaling pathways, including Wnt/β-catenin (CTNNB1), Sonic Hedgehog (SHH, SMO, GLI1), and vascular endothelial growth factor (VEGF), surpassing standard controls such as minoxidil and purmorphamine. The microemulsion also demonstrated potent anti-inflammatory and antioxidant properties by reducing nitric oxide production and oxidative stress, factors that contribute to inflammation and follicular damage in AGA. Furthermore, Hair Rise^TM inhibited 5α-reductase (types 1–3), a key enzyme involved in androgen metabolism, in both human prostate cancer cells (DU-145) and HFDPCs. These findings suggest that Hair Rise^TM microemulsion presents a promising natural therapy for promoting hair growth and reducing hair loss via multiple synergistic mechanisms, offering a potent, plant-based alternative to synthetic treatments. Full article

This study presents an air quality monitoring system that employs the Arduino Uno microcontroller. The system is augmented with a moving average filter and data fusion techniques from BME680 and CCS811 sensors, which are designed to process and combine data from these sensors. The system was tested and analyzed empirically across a range of residential environments in order to validate its efficacy. The findings indicated that the typical IAQ level in a bedroom was approximately 20 units. However, this level increased significantly, reaching 140 units, within minutes after the introduction of a 17% perfume spray. In contrast, the use of an aromatic diffuser resulted in a smaller increase in IAQ to 40 units, which returned to normal levels after ventilation. Moreover, the analysis demonstrated that the kitchen and bathroom exhibited inferior air quality in comparison to the bedroom. This was evidenced by elevated VOC and humidity levels, which were observed to be 10–20% higher due to the combined effects of household activities and inadequate ventilation. This study makes a significant contribution to the field of air quality monitoring by proposing a solution that employs sensor technology and data processing methods to enhance the quality of life within residential spaces. Full article

Objectives: This study aimed to identify radiologic features that differentiate lymphoma from metastasis manifesting as a solid enhancing mass lacking necrosis in the cerebellum. Methods: Pathologically confirmed 24 primary central nervous system lymphoma (PCNSL) and 32 metastasis patients with solid enhancing cerebellar masses without necrotic or hemorrhagic components were retrospectively analyzed. We evaluated the imaging characteristics using contrast-enhanced magnetic resonance imaging (MRI). The serrate sign was defined as a tumor spreading along white matter with branch-like enhancement or outward spikes. Results: The serrate sign was exclusively identified in the PCNSL group, showing a significant difference compared to the metastasis group (75.0% vs. 0%, p < 0.001). Homogeneous enhancement occurred more frequently in PCNSL than in metastasis (91.7% vs. 21.9%, p < 0.001). Conversely, bulging contour (62.5% vs. 4.2%, p < 0.001) and surface involvement (71.9% vs. 29.2%, p = 0.003) were more prevalent in metastasis than PCNSL. For predicting PCNSL, the serrate sign demonstrated 75.0% sensitivity, 100% specificity, 100% positive predictive value, 84.2% negative predictive value, and 89.3% accuracy. Conclusions: This study found that the serrate sign and homogeneous enhancement are reliable MRI features for differentiating cerebellar PCNSL from metastasis, whereas a bulging contour and surface involvement suggest metastasis. The serrate sign demonstrated diagnostic significance in differentiating PCNSL from metastasis. Full article

Rising food demands require new techniques to achieve higher genetic gains for crop production, especially in regions where climate can negatively affect agriculture. Wheat is a staple crop that often encounters this challenge, and ideotype breeding with optimized canopy traits for grain yield, such as determinate tillering, synchronized flowering, and stay-green (SG), can potentially improve yield under terminal drought conditions. Among these traits, SG has emerged as a key factor for improving grain quality and yield by prolonging photosynthetic activity during reproductive stages. This study aims to highlight the importance of growth dynamics in a wheat mapping population by using multispectral images obtained from uncrewed aerial vehicles as a high-throughput phenotyping technique to assess the effectiveness of using such images for determining correlations between vegetation indices and grain yield, particularly regarding the SG trait. Results show that the determinate group exhibited a positive correlation between NDVI and grain yield, indicating the effectiveness of these traits in yield improvement. In contrast, the indeterminate group, characterized by excessive vegetative growth, showed no significant NDVI–grain yield relationship, suggesting that NDVI values in this group were influenced by sterile tillers rather than contributing to yield. These findings provide valuable insights for crop breeders by offering a non-destructive approach to enhancing genetic gains through the improved selection of resilient wheat genotypes. Full article

At present, bamboo fiber is mainly prepared by rolling and carding after employing the alkali boiling softening method, which is not friendly to the environment. In order to obtain a green and environmentally friendly pretreatment method for preparing bamboo fiber, this paper starts with the current bamboo softening technology and explores the impact of various experimental factors on fiber extraction of Pleioblastus amarus (bitter bamboo) after application of the saturated steam softening method through studying the relationship between saturated steam temperature, holding time, moisture content of bamboo strips, fiber yield, fiber fineness, and the mechanical properties of Pleioblastus amarus fiber. Single-factor experiments revealed that optimal softening fiber extraction effects were achieved within a steam temperature range of 150–180 °C, a holding time of 10–30 min, and a moisture content of 12%–22%. Based on these findings, an orthogonal experiment was designed using a factorial-level table. Through the analysis of range, variance, and orthogonal experiment results, combined with the fibrillation effect and the practical application of fibers, the optimal process parameters of the saturated steam softening method for fiber extraction were determined: saturated steam temperature 170 °C, holding time 20 min, and moisture content 12%. In contrast to the method of conventional mechanical fiber extraction after alkali boiling softening treatment, bamboo fibers processed utilizing the optimized conditions of the saturated steam softening technique showcase a substantial 63% elevation in fiber yield, a notable 18% reduction in fiber fineness, a commendable 28% enhancement in fiber tensile strength, an equivalent tensile modulus, and a marked 53% decrease in elongation at break. The softening process can provide a green and environmentally friendly treatment method for bamboo fiber extraction and greatly promote the scope of application of Pleioblastus amarus. Full article

This experiment evaluated the function of chlorogenic acid (CGA) in the growth, health status, and inflammation of largemouth bass (Micropterus salmoides). Over eight weeks, CGA supplementation was designed at five levels: 0, 60, 120, 180, and 240 mg/kg. The 180 and 240 mg/kg CGA-supplemented groups showed significant improvements in the FBW, SGR, and WGR compared to the control group (0 mg/kg) (p < 0.05). All the CGA-supplemented groups exhibited a significant reduction in the FCR (p < 0.05), with the 180 mg/kg CGA group showing the lowest FCR. Nonetheless, there were no appreciable differences in the plasma concentrations of TP, ALT, or AST among the treatments (p > 0.05). Compared to the control group, the 180 mg/kg CGA group exhibited significantly lower TC and TG levels (p < 0.05). The ALP levels showed no significant differences from the control group (p > 0.05). In terms of antioxidant parameters, CGA supplementation considerably reduced the MDA content (p < 0.05) and increased the GSH levels, while decreasing the CAT, SOD, and GPx activity levels Meanwhile, CGA supplementation resulted in reduced mRNA levels of SOD, CAT, Nrf2, Keap1, and NF-κB compared to the control group. In contrast, the mRNA levels of GPx, IL-8, TLR2, and RelA were elevated in the liver. Our findings indicated that CGA supplementation improved the growth performance and antioxidant status and weakened the inflammatory response of largemouth bass. These findings suggest that CGA could be a valuable dietary supplement for enhancing the health and growth of this species. Full article