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PurposeThe 3D U-Net deep neural network structure is widely employed for dose prediction in radiotherapy. However, the attention to the network depth and its impact on the accuracy and robustness of dose prediction remains inadequate.Methods92 cervical cancer patients who underwent Volumetric Modulated Arc Therapy (VMAT) are geometrically augmented to investigate the effects of network depth on dose prediction by training and testing three different 3D U-Net structures with depths of 3, 4, and 5.ResultsFor planning target volume (PTV), the differences between predicted and true values of D98, D99, and Homogeneity were statistically 1.00 ± 0.23, 0.32 ± 0.72, and -0.02 ± 0.02 for the model with a depth of 5, respectively. Compared to the other two models, these parameters were also better. For most of the organs at risk, the mean and maximum differences between the predicted values and the true values for the model with a depth of 5 were better than for the other two models.ConclusionsThe results reveal that the network model with a depth of 5 exhibits superior performance, albeit at the expense of the longest training time and maximum computational memory in the three models. A small server with two NVIDIA GeForce RTX 3090 GPUs with 24 G of memory was employed for this training. For the 3D U-Net model with a depth of more than 5 cannot be supported due to insufficient training memory, the 3D U-Net neural network with a depth of 5 is the commonly used and optimal choice for small servers.

In order to achieve high power conversion efficiency, interface engineering of the charge transport layers in perovskite solar cells (PSCs) has significantly reduced the energy band mismatching and charge accumulation. This simulation study investigated the effect of cadmium telluride (CdTe) buffer layer (BL) on the performance of PSC through SCAPS-1D modeling program. The device configuration with BL consisted of metal electrode/CuI/CdTe/CH3NH3SnI3/TiO2/TCO/glass substrate. The insertion of BL between absorber and HTM improved the energy band alignment by increasing the power conversion efficiency (PCE) from 11.09 % to 14.76 %. The important parameters including thicknesses of the buffer and absorber layers, the doping concentrations of absorber, electron transport material (ETM), and hole transport material (HTM) were investigated. Moreover, the effect of the electron affinity of the ETM, HTM and the hole mobility of HTM were optimized to further enhance the performance of the proposed structure. The optimized results showed the noticeable increase in efficiency of 23.56 %.

Diabetic nephropathy (DN), a leading cause of end-stage renal disease, remains a formidable challenge in diabetes management due to the complex nature of its pathogenesis, particularly the epithelial-mesenchymal transition (EMT) process. Our innovative study leverages network pharmacology to explore the therapeutic potentials of Myricetin, a natural flavonoid, focusing on its effects against NOX4, a critical mediator in DN progression. This investigation marks a pioneering approach by integrating network pharmacology to predict and elucidate the inhibitory relationship between Myricetin and NOX4. Utilizing a high-fat diet/streptozotocin (HFD/STZ) induced DN mouse model, we delved into the effects of Myricetin on renal EMT processes. Through network pharmacology analyses coupled with molecular docking studies, we identified and confirmed Myricetin's binding efficacy to NOX4. Extensive in vitro and in vivo experiments further established Myricetin's significant impact on mitigating EMT by modulating the NOX4-NF-κB-Snail signaling pathway. Results from our research demonstrated notable improvements in renal function and reductions in tissue fibrosis among treated HFD/STZ mice. By curtailing NOX4 expression, Myricetin effectively reduced reactive oxygen species (ROS) production, thereby inhibiting NF-κB activation and subsequent Snail expression, crucial steps in the EMT pathway. Supported by both theoretical predictions and empirical validations, this study unveils the mechanism underlying Myricetin's modulation of EMT in DN through disrupting the NOX4-NF-κB-Snail axis. These findings not only contribute a new therapeutic avenue for DN treatment but also underscore the utility of network pharmacology in advancing drug discovery processes.

Abstract Background Diabetic kidney disease (DKD) represents a microvascular complication of diabetes mellitus. Shenkang Pills (SKP), a traditional Chinese medicine formula, has been widely used in the treatment of DKD and has obvious antioxidant effect. Ferroptosis, a novel mode of cell death due to iron overload, has been shown to be associated with DKD. Nevertheless, the precise effects and underlying mechanisms of SKP on ferroptosis in diabetic kidney disease remain unclear. Methods The active components of SKP were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Protein–protein interaction (PPI) network and Herb-ingredient-targets gene network were constructed using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted utilizing the Metascape system database. Additionally, an in vivo model of DKD induced by Streptozotocin (STZ) was established to further investigate and validate the possible mechanisms underlying the effectiveness of SKP. Results We retrieved 56 compounds and identified 223 targets of SKP through the TCMSP database. Key targets were ascertained using PPI network analysis. By constructing a Herb-Ingredient-Targets gene network, we isolated the primary active components in SKP that potentially counteract ferroptosis in diabetic kidney disease. KEGG pathway enrichment analysis suggested that SKP has the potential to alleviate ferroptosis through HIF signaling pathway, thereby mitigating renal injury in DKD. In animal experiments, fasting blood glucose, 24 h urine protein, urea nitrogen and serum creatine were measured. The results showed that SKP could improve DKD. Results from animal experiments were also confirmed the efficacy of SKP in alleviating renal fibrosis, oxidative stress and ferroptosis in DKD mice. These effects were accompanied by the significant reductions in renal tissue expression of HIF-1α and HO-1 proteins. The mRNA and immunohistochemistry results were the same as above. Conclusions SKP potentially mitigating renal injury in DKD by subduing ferroptosis through the intricacies of the HIF-1α/HO-1 signaling pathway.

Chitosan is a biocompatible, non-toxic and renewable natural basic polysaccharide that can be cross-linked and reacted with Ce(IV) to form a physiologically active chitosan-Ce(IV) complex. To investigate this novel complex and its potential to hydrolyze phosphate ester bonds, chitosan-cerium complex microspheres resin (CS-CCMR) was prepared from chitosan and ceric ammonium nitrate by reversed-phase suspension cross-linking polymerization. CS-CCMR was characterized, its ability to hydrolyze disodium p-nitrobenzene phosphate (PNPP2Na) and organophosphorus pesticides was investigated, and the hydrolytic mechanism was explored. CS-CCMR was composed of dark yellow microspheres with smooth surfaces and dense pores. It was found that CS-CCMR contained 4.507 mg/g Ce(IV), indicating that coordination polymerization between Ce(IV) and chitosan was successful. The presence of Ce(IV) in CS-CCMR was confirmed by multiple analytical methods and it was found that coordination of Ce(IV) by chitosan was mediated by the nitrogen atom of the amino group and the oxygen atom of the hydroxyl group of chitosan. It was shown that CS-CCMR efficiently hydrolyzed the phosphate ester bonds of PNPP2Na and five organophosphorus pesticides. Hydrolysis of PNPP2Na is potentially accomplished by charge neutralization and nucleophilic substitution. The mechanism of parathion degradation by CS-CCMR involves modification of the nitro group to give aminoparathion, followed by cleavage of the P–O bond to generate diazinphos. Consequently, the novel chitosan-Ce(IV) complex exhibits great efficiency for hydrolysis of phosphate ester bonds and CS-CCMR is expected to be developed as an agent to reduce the possibility of contamination of fruit and vegetable drinks by organophosphorus pesticides.

Skeletal muscle atrophy is a common complication of chronic kidney disease (CKD) that affects the quality of life and prognosis of patients. We aimed to investigate the effects and mechanisms of caffeic acid (CA), a natural phenolic compound, on skeletal muscle atrophy in CKD rats. Male Sprague–Dawley rats underwent 5/6 nephrectomy (NPM) and were treated with CA (20, 40, or 80 mg/kg/day) for 10 weeks. The body and muscle weights, renal function, hemoglobin, and albumin were measured. The histological, molecular, and biochemical changes in skeletal muscles were evaluated using hematoxylin-eosin staining, quantitative real-time PCR, malondialdehyde/catalase/superoxide dismutase/glutathione level detection, and enzyme-linked immunosorbent assay. Western blotting and network pharmacology were applied to identify the potential targets and pathways of CA, CKD, and muscle atrophy. The results showed that CA significantly improved NPM-induced muscle-catabolic effects, reduced the expression of muscle atrophy-related proteins (muscle atrophy F-box and muscle RING finger 1) and proinflammatory cytokines (interleukin [IL]-6, tumor necrosis factor-alpha, and IL-1β), and attenuated muscle oxidative stress. Network pharmacology revealed that CA modulated the response to oxidative stress and nuclear factor kappa B (NF-κB) signaling pathway and that Toll-like receptor 4 (TLR4) was a key target. In vivo experiment confirmed that CA inhibited the TLR4/myeloid differentiation primary response 88 (MYD88)/NF-kB signaling pathway, reduced muscle iron levels, and restored glutathione peroxidase 4 activity, thereby alleviating ferroptosis and inflammation in skeletal muscles. Thus, CA might be a promising therapeutic agent for preventing and treating skeletal muscle atrophy in CKD by modulating the TLR4/MYD88/NF-κB pathway and ferroptosis.

Objective: Shenshuai Yingyang Jiaonang (SSYYJN), a traditional Chinese medicine formula, can ameliorate muscle atrophy associated with chronic kidney disease (CKD). However, its mechanisms of action remain unclear. This study is to investigate the molecular mechanisms involved in the effects of SSYYJN in ameliorating muscle atrophy associated with CKD in rats. Methods: The chemical compounds of SSYYJN were identified by UPLC-Q-Orbitrap HRMS. Considering the dose-response relationship of the identified compounds, male SD rats were randomly divided into Sham, Model, SSYYJN, and α-Keto Acid (KA) groups. Subsequently, we assessed the therapeutic and anti-ferroptotic effects of SSYYJN. Network pharmacology studies were used to predict the molecular mechanism of SSYYJN on ferroptosis and were further verified for accuracy. Results: A total of 42 active compounds were identified from SSYYJN. SSYYJN alleviated muscle atrophy caused by CKD, as evidenced by changes in body weight, serum biochemical indices, mass and histopathology of the skeletal muscle, and the levels of MuRF1. SSYYJN reduced the levels of iron, MDA, and ROS, increased the levels of GSH, NAPDH, and Gpx4. Network pharmacology analysis indicated that SSYYJN exerted anti-ferroptotic effects that were closely related to the HIF-1α signaling pathway. Molecular protein and genetic test results showed that SSYYJN increased HIF-1α protein and increased SLC7A11. Conclusions: SSYYJN attenuates muscle atrophy in CKD by inhibiting ferroptosis through the activation of the HIF-1α/SLC7A11 pathway and might be a promising traditional Chinese medicine for muscle atrophy in CKD.

Diabetic kidney disease (DKD) stands as a pressing health challenge, with mesangial cell fibrosis identified as a pivotal hallmark leading to glomerular sclerosis. Gaining a deeper grasp on the molecular dynamics behind this can potentially introduce groundbreaking therapeutic avenues. Recent revelations from studies on ROCK1-deficient mice, which displayed resilience against high-fat diet (HFD)-induced glomerulosclerosis and mitochondrial fragmentation, spurred our hypothesis regarding ROCK1's potential role in mesangial cell fibrosis. Subsequent rigorous experiments corroborated our theory, highlighting the critical role of ROCK1 in orchestrating mesangial cell proliferation and fibrosis, especially in high-glucose settings. Mechanistically, ROCK1 inhibition led to a notable hindrance in the high-glucose-triggered MAPK signaling pathway, particularly emphasizing the ROCK1/ERK/P38 axis. To translate this understanding into potential therapeutic interventions, we embarked on a comprehensive drug screening journey. Leveraging molecular modeling techniques, Myricetin surfaced as an efficacious inhibitor of ROCK1. Dose-dependent in vitro assays substantiated Myricetin's prowess in curtailing mesangial cell proliferation and fibrosis via ROCK1/ERK/P38 pathway. In vivo verifications paralleled these findings, with Myricetin treatment resulting in significant renal function enhancements and diminished DKD pathological markers, all pivoted around the ROCK1/ERK/P38 nexus. These findings not only deepen our comprehension of DKD molecular underpinnings but also elevate ROCK1 to the pedestal of a promising therapeutic beacon. Concurrently, Myricetin is spotlighted as a potent natural contender, heralding a new era in DKD therapeutic design.

Biomass-derived materials have traditionally been used to generate electrical energy through the combustion of their organic components. However, within the past few years, certain common biomass compounds, especially plant-based products such as cellulose and lignin, have drawn attention in the energy field due to their wide availability, low cost, and chemical versatility. In the case of cellulose, the combination of crystalline and amorphous domains, along with the high surface area and abundance of hydroxyl groups, has allowed for its application in multiple devices to harvest energy from the environment. However, to date, there are no reviews focusing on the different approaches that have been developed to implement these sustainable materials in the generation of renewable energies and the desirable material properties for these applications. This manuscript reviews alternative ways that have been developed to exploit biomass compounds in power generation, especially cellulose and lignin. Three different types of energy harvesting are discussed: mechanical, osmotic, and thermal energy. In the case of mechanical energy, the application of plant-derived materials in piezoelectric and triboelectric generators is described. In both cases, approaches where the biomass material has an active role in power generation instead of acting as a mechanical support are reported. For osmotic energy, the performance of inverse electrodialysis systems and the use of plant-derived materials, including the chemical modifications carried out to allow for their use for energy generation, was reviewed. Finally, for thermal energy generation, the reported work on biopolymer-based devices that work using thermoelectricity has been summarised. In each case, the latest advances in the field from the materials science perspective and the reported performance were described. Hybrid approaches involving the combination of biomass materials with other components have also been considered and compared with the performance obtained using biopolymers alone. Current limitations and opportunities are, finally, discussed to offer an overview of the current landscape and indicate future directions of the field.

Purpose: To develop an algorithm using a residual base network guided by the confidence map and transfer learning for limited dataset size and imbalanced bladder wall segmentation.Methods: The geometric transformation was made to the training data for data augmentation, and a pre-trained Resnet50 model on ImageNet was also adopted for transfer learning. Three loss functions were put into the pre-trained Resnet50 network, they are the cross-entropy loss function (CELF), the generalized Dice loss function (GDLF) and the Tversky loss function (TLF). Three models were obtained through training, and three corresponding confidence maps were output after entering a new image. By selecting the point with the maximum confidence values at the corresponding position, we merged the three images into one figure, performed threshold filtering to avoid external anomalies, and finally obtained the segmentation result.Results: The average Jaccard similarity coefficient of model training based on the CELF, GDLF and TLF is 0.9173, 0.8355, 0.8757, respectively, and the average Jaccard similarity coefficient of our algorithm can be achieved at 0.9282. In contrast, the classical 2D U-Net algorithm can only achieve 0.518. We also qualitatively give the reasons for the improvement of model performance.Conclusion: Our study demonstrates that a confidence map-assisted residual base network can accurately segment bladder walls on a limited-size data set. Compared with the segmentation results of each model alone, our method originally improves the accuracy of the segmentation results by combining confidence map guidance with threshold filtering.

The production of peanut oil in the industrial sector necessitates the utilization of diverse raw materials to generate consistent batches with stable flavor profiles, thereby leading to an increased focus on understanding the correlation between raw materials and flavor characteristics. In this study, sensory evaluations, headspace solid-phase micro-extraction gas chromatography mass spectrometry (HS-SPME-GC-MS), odor activity value (OAV) calculations, and correlation analysis were employed to investigate the flavors and main contributing amino acids of hot-pressed oils derived from different peanut varieties. The results confirmed that the levels of alcohols, aldehydes, and heterocyclic compounds in peanut oil varied among nine different peanut varieties under identical processing conditions. The OAVs of 25 key aroma compounds, such as methylthiol, 3-ethyl-2,5-dimethylpyrazine, and 2,3-glutarone, exceeded a value of 1. The sensory evaluations and flavor content analysis demonstrated that pyrazines significantly influenced the flavor profile of the peanut oil. The concentrations of 11 amino acids showed a strong correlation with the levels of pyrazines. Notably, phenylalanine, lysine, glutamic acid, arginine, and isoleucine demonstrated significant associations with both pyrazine and nut flavors. These findings will provide valuable insights for enhancing the sensory attributes of peanut oil and selecting optimal raw peanuts for its production.

Abstract Background Testa color is an important trait of peanut (Arachis hypogaea L.) which is closely related with the nutritional and commercial value. Pink and red are main color of peanut testa. However, the genetic mechanism of testa color regulation in peanut is not fully understood. To elucidate a clear picture of peanut testa regulatory model, samples of pink cultivar (Y9102), red cultivar (ZH12), and two RNA pools (bulk red and bulk pink) constructed from F4 lines of Y9102 x ZH12 were compared through a bulk RNA-seq approach. Results A total of 2992 differential expressed genes (DEGs) were identified among which 317 and 1334 were up-regulated and 225 and 1116 were down-regulated in the bulk red-vs-bulk pink RNA pools and Y9102-vs-ZH12, respectively. KEGG analysis indicates that these genes were divided into significantly enriched metabolic pathways including phenylpropanoid, flavonoid/anthocyanin, isoflavonoid and lignin biosynthetic pathways. Notably, the expression of the anthocyanin upstream regulatory genes PAL, CHS, and CHI was upregulated in pink and red testa peanuts, indicating that their regulation may occur before to the advent of testa pigmentation. However, the differential expression of down-stream regulatory genes including F3H, DFR, and ANS revealed that deepening of testa color not only depends on their gene expression bias, but also linked with FLS inhibition. In addition, the down-regulation of HCT, IFS, HID, 7-IOMT, and I2’H genes provided an alternative mechanism for promoting anthocyanin accumulation via perturbation of lignin and isoflavone pathways. Furthermore, the co-expression module of MYB, bHLH, and WRKY transcription factors also suggested a fascinating transcriptional activation complex, where MYB-bHLH could utilize WRKY as a co-option during the testa color regulation by augmenting anthocyanin biosynthesis in peanut. Conclusions These findings reveal candidate functional genes and potential strategies for the manipulation of anthocyanin biosynthesis to improve peanut varieties with desirable testa color.

Purpose: To develop a deep learning framework based on a hybrid dataset to enhance the quality of CBCT images and obtain accurate HU values. Materials and Methods: A total of 228 cervical cancer patients treated in different LINACs were enrolled. We developed an encoder–decoder architecture with residual learning and skip connections. The model was hierarchically trained and validated on 5279 paired CBCT/planning CT images and tested on 1302 paired images. The mean absolute error (MAE), peak signal to noise ratio (PSNR), and structural similarity index (SSIM) were utilized to access the quality of the synthetic CT images generated by our model. Results: The MAE between synthetic CT images generated by our model and planning CT was 10.93 HU, compared to 50.02 HU for the CBCT images. The PSNR increased from 27.79 dB to 33.91 dB, and the SSIM increased from 0.76 to 0.90. Compared with synthetic CT images generated by the convolution neural networks with residual blocks, our model had superior performance both in qualitative and quantitative aspects. Conclusions: Our model could synthesize CT images with enhanced image quality and accurate HU values. The synthetic CT images preserved the edges of tissues well, which is important for downstream tasks in adaptive radiotherapy.

For investigating ocean activities and comprehending the role of the oceans in global climate change, it is essential to gather high-quality ocean data. However, existing ocean observation data have deficiencies such as inconsistent spatial and temporal distribution, severe fragmentation, and restricted observation depth layers. Data assimilation is computationally intensive, and other conventional data fusion techniques offer poor fusion precision. This research proposes a novel multi-source ocean data fusion network (ODF-Net) based on deep learning as a solution for these issues. The ODF-Net comprises a number of one-dimensional residual blocks that can rapidly fuse conventional observations, satellite observations, and three-dimensional model output and reanalysis data. The model utilizes vertical ocean profile data as target constraints, integrating physics-based prior knowledge to improve the precision of the fusion. The network structure contains channel and spatial attention mechanisms that guide the network model’s attention to the most crucial features, hence enhancing model performance and interpretability. Comparing multiple global sea temperature datasets reveals that the ODF-Net achieves the highest accuracy and correlation with observations. To evaluate the feasibility of the proposed method, a global monthly three-dimensional sea temperature dataset with a spatial resolution of 0.25°×0.25° is produced by fusing ocean data from multiple sources from 1994 to 2017. The rationality tests on the fusion dataset show that ODF-Net is reliable for integrating ocean data from various sources.

Remote sensing images acquired by the FY4 satellite are crucial for regional cloud monitoring and meteorological services. Inspired by the success of deep learning networks in image super-resolution, we applied image super-resolution to FY4 visible spectrum (VIS) images. However, training a robust network directly for FY4 VIS image super-resolution remains challenging due to the limited provision of high resolution FY4 sample data. Here, we propose a super-resolution and transfer learning model, FY4-SR-Net. It is composed of pretraining and fine-tuning models. The pretraining model was developed using a deep residual network and a large number of FY4 A 4 and 1 km resolution VIS images as the training data. The knowledge derived from 4 km to 1 km resolution images was incorporated into FY4 B 1 km to 0.25 km resolution VIS images. The FY4-SR-Net is fine-tuned by incorporating limited 1 km and 0.25 km resolution panchromatic images, and then producing 1km super-resolution VIS images of the FY4 satellite. Using the one-day FY4 test dataset for qualitative and quantitative evaluations, the FY4-SR-Net outperformed the classic bicubic interpolation approach with a 16.12% reduction in root-mean-square error and a 2.97% rise in peak signal-to-noise ratio averages. The structural similarity value average increased by 0.0026. This article provides a new precedent for improving the spatial resolution of FY4 series meteorological satellites, which has important scientific significance and application properties.

The shipping industry is increasingly threatened by global climate change. Reliable trajectory prediction can be used to perceive potential risks and ensure navigation efficiency. However, many existing studies have not fully considered the impact of complex ocean environmental factors and have only focused on local regions, which are difficult to extend to a global scale. To this end, we propose a deep learning vessel trajectory prediction method fusing discretized meteorological data (TripleConvTransformer). First, we clean the automatic identification system data to form a high-quality spatiotemporal trajectory dataset. Then, we fuse the trajectory data with the meteorological data after feature discretization to deeply mine the motion information of ocean-going ships. Finally, we design three modules, the global convolution, local convolution, and trend convolution modules, based on the simplified transformer model to capture multiscale features. We compare TripleConvTransformer with state-of-the-art prediction models. The experimental results show that in the prediction of the trajectory points in the next 90 min, the smallest root mean square error in terms of longitude and latitude and the highest overall prediction accuracy are achieved using TripleConvTransformer. Our method not only fully considers the influence of meteorological factors in the ocean-going process but also effectively extracts the important information hidden in the data, thus achieving accurate trajectory prediction on a global scale.

Radiotherapy is an effective treatment for certain patients with muscle-invasive bladder cancer and radio-sensitivity detection plays a vital role during bladder cancer radio treatment because radiotherapy responses have profound influences on a patient’s prognosis. Although several potential biomarkers were investigated to assess the radio-response of bladder cancer, studies on detecting radio-sensitivity based on morphological characteristics of cancer cells at the single-cell level are rare. In fact, morphological parameters are vital characteristics of cells that could provide direct information to infer the physiological statuses of cells and evaluate the response of cells to the external stimulations. In this study, digital holographic microscopy was applied to quantify morphological parameters of bladder cancer cells (HT-1376) at the single-cell level and their alterations after exposure to four different radiation doses, i.e., 0 Gy (control), 4, 8, and 12 Gy. Based on the reconstructed phase images, four morphological parameters of cells, namely, cell phase volume (CPV), cell projected area (CPA), cell average phase height (CAPH), and cell maximum phase height (CMPH), were quantitatively calculated. The results show that the change rates of CPV, CAPH, and CMPH were increased with the radiation dose rising, while the change rate of CPA was decreased with the radiation dose increasing. Moreover, the change rates of CPV, CPA, CAPH, and CMPH were different between control group and 12 Gy treated group. The results demonstrate that morphological characteristics have the potential to be utilized to estimate the radio-sensitivity of bladder cancer cells, and it may provide new perspectives to establishing label-free methods to detect radio-sensitivity and guide radiotherapy in bladder cancer.

Accumulated ice has brought much damage to engineering and people’s lives. The accumulation of ice can affect the flight safety of aircraft and lead to the failure of cables and power generation blades; it can even cause damage to human life. Traditional anti-icing and de-icing strategies have many disadvantages such as high energy consumption, low efficiency, or pollution of the environment. Therefore, inspired by animal communities, researchers have developed new passive anti-icing materials such as superhydrophobic material. In this paper, the solid surface wetting phenomenon and superhydrophobic anti-icing and de-icing mechanism were introduced. The methods of fabrication of superhydrophobic surfaces were summarized. The research progress of wear-resistant superhydrophobic coatings, self-healing/self-repairing superhydrophobic coatings, photothermal superhydrophobic coatings, and electrothermal superhydrophobic coatings in the field of anti-icing and de-icing was reviewed. The current problems and challenges were analyzed, and the development trend of superhydrophobic materials was also prospected in the field of anti-icing and de-icing. The practicality of current superhydrophobic materials should continue to be explored in depth.

In heat-denatured peanut meal (HDPM), proteins are denatured and polysaccharides are degraded and browned. It can only be used as feed or fertilizer, and not using it as such is a waste of resources. To achieve high-value HDPM use, solid-state fermentation by Aspergillus oryzae and Saccharomyces cerevisiae was investigated. Conditions were optimized by response surface methodology and high-value antioxidant peptides (APs), nonstarch polysaccharides (NSPs), and fermentation products of heat-denatured peanut meal (FHDPM) were obtained. Optimal culture conditions were strain ratio 6:5, inoculation volume 2 mL, and fermentation for 42 h at 35 °C. Under optimal conditions, the theoretical soluble nitrogen concentration, 1,1-Diphenyl-2-picrylhydrazyl radical scavenging rate, hydroxyl free radical scavenging rate, and NSP yield reached 44.78 mg/mL, 62.44%, 94.95%, and 3.73%, respectively; however, their experimental values were 46.80 ± 1.23 mg/mL, 72.18 ± 0.78%, 96.79 ± 0.55%, and 4.42 ± 0.21%, respectively. NSPs, Aps, and FHDPM exhibited four higher classes and eight types of antioxidant activities. Moreover, levels of amino acids and trace elements, and physicochemical properties including emulsion activity index, emulsion stability index, foam capacity, foam stability, water holding capacity, and oil absorption capacity were enhanced by fermentation. The results indicate that APs and NSPs could serve as promising natural antioxidants in the food industry, and FHDPM could be used as a new type of high-value nutritional product in the feed industry. The findings provide new insight for comprehensive processing and utilization of HDPM.

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease, so there is an urgent need to suppress its development at early stage. Shenkang pills (SKP) are a hospital prescription selected and optimized from effective traditional Chinese medicinal formulas for clinical treatment of DN. In the present study, liquid chromatography-quadrupole-time of flight-mass spectrometry (LC-Q-TOF-MS) and total contents qualification were applied to generate a quality control standard of SKP. For verifying the therapeutic effects of SKP, db/db mice were administered intragastrically with SKP at a human-equivalent dose (1.82 g/kg) for 4 weeks. Moreover, the underlying mechanism of SKP were analyzed by the renal RNA sequencing and network pharmacology. LC-Q-TOF-MS identified 46 compounds in SKP. The total polysaccharide and organic acid content in SKP were 4.60 and 0.11 mg/ml, respectively, while the total flavonoid, saponin, and protein content were 0.25, 0.31, and 0.42 mg/ml, respectively. Treatment of SKP significantly reduced fasting blood glucose, improved renal function, and ameliorated glomerulosclerosis and focal foot processes effacement in db/db mice. In addition, SKP protected podocytes from injury by increasing nephrin and podocin expression. Furthermore, transcriptome analyses revealed that 430 and 288 genes were up and down-regulated in mice treated with SKP, relative to untreated controls. Gene ontology enrichment analysis revealed that the differentially expressed genes mainly involved in modulation of cell division and chromosome segregation. Weighted gene co-expression network analysis and network pharmacology analysis indicated that aurora kinase B (AURKB), Rac GTPase activating protein 1 (RacGAP1) and SHC binding, and spindle associated 1 (shcbp1) might be the core targets of SKP. This protein and Ras homolog family member A (RhoA) were found overexpression in db/db mice, but significantly decreased with SKP treatment. We conclude that SKP can effectively treat early-stage DN and improve renal podocyte dysfunction. The mechanism may involve down-regulation of the AURKB/RacGAP1/RhoA pathway.

With more demand for Sabin inactivated poliovirus vaccines (sIPVs) to support the global polio eradication effort worldwide, data regarding the potency characteristics of sIPV after exposure to freezing temperatures are urgently required. In the present study, the sIPVs were stored at −20°C for 24 h, 1 week, and 2 weeks in the freezer or in a vaccine carrier for 1 or 3 freeze-thaw cycle to evaluate the effect mediated by freezing temperatures that may be encountered during routine storage and transfer. The in vitro potency was then determined by a D-antigen enzyme-linked immunosorbent assay, and the in vivo potency was evaluated in Wistar rats. In the in vitro study for freezer storage groups, the D-antigen contents for all three types decreased and were lower than the release specifications after storing at −20°C for 2 weeks. After storing at −20°C for 1 week, the D-antigen contents for types I and III in combined group of a total of 45 vials, and for type II in the specific lot groups containing 15 vials decreased, but were within the release specifications. Moreover, no significant change in in vivo potency was observed. For vaccine carrier transfer groups, the D-antigen contents did not decrease after 1 freeze-thaw cycle; in contrast, it decreased, but no significant in vivo potency loss was observed after 3 freeze-thaw cycles. These results suggest that it may be possible to retain sufficient sIPV potency after short periods of freezing or freeze-thawing during transport.

Bilirubin oxidases (BODs), which catalyze the oxidation of bilirubin to biliverdin, are multi-copper oxidases that can be used in clinical diagnoses. Given their different reported enzymatic characterizations from laccases, BODs have gained considerable attention for their application in healthcare and environment management. In this study, a BOD gene from Myrothecium verrucaria was chemically synthesized and optimized to heterogeneous expression in Arabidopsis thaliana. The optimized DNA sequence showed 80.1% similarity to the original sequences. The gene was successfully transferred into A. thaliana, and the crude extracts of transgenic plants showed higher BOD activity compared with that of untransformed plants. BOD expressed in transgenic A. thaliana also exhibited an activity on the typical substrate (ABTS) of laccase and was able to decolorize the textile dyes crystal violet and malachite green. The results indicated that the M. verrucaria BOD gene could be transgenically exploited in plants for dye decolorization.

Severe environmental pollution problems arising from toxic dyestuffs (e.g., methyl orange) are receiving increasing attention. Therefore, dyes’ safe removal has become a research hotspot. Among the many physical–chemical removal techniques, adsorption using renewable biological resources has proved to be more advantageous over others due to its effectiveness and economy. Chitosan is a natural, renewable biopolymer obtained by deactivated chitin. Thus, the magnetic resin of chitosan microspheres (MRCM), prepared by reversed-phase suspension cross-linking polymerization, was used to remove methyl orange from a solution in a batch adsorption system. The main results are as follows: (1) The results of physical and swelling properties of MRCM indicated that MRCM was a type of black spherical, porous, water-absorbing, and weak alkali exchange resin, and it had the ability to adsorb methyl orange when it was applied in solutions above pH 2.0. (2) In batch adsorption studies, the maximum adsorption capacity was obtained at pH 5; the adsorption equilibrium time was 140 min; and the maximum adsorption was reached at 450 mg/L initial concentration. (3) Among the three isotherm adsorption models, Langmuir achieved the best fit for the adsorption of methyl orange onto MRCM. (4) The adsorption thermodynamics indicated that the adsorption was spontaneous, with increasing enthalpy, and was driven by the entropy. (5) The pseudo-second-order kinetics equation was most suitable to describe the adsorption kinetics, and the adsorption kinetics was also controlled by the liquid–film diffusion dynamics. Consequently, MRCM with relatively higher methyl orange adsorption exhibited the great efficiency for methyl orange removal as an environment-friendly sorbent. Thus, the findings are useful for methyl orange pollution control in real-life wastewater treatment applications.

In this paper, a monopole UWB broadband antenna is designed, fabricated, and measured for wireless communication networks. The initial radiator model of the proposed antenna has a short-sleeve shape, and to expand the impedance bandwidth, the right and left angles are subtracted symmetrically from the lower half of the radiator. The impedance matching is improved by etching slots in the feed line and adding L-shaped patches symmetrically on both sides of the feed line. The results show that the proposed miniaturized antenna system can cover WiFi 7(2.4–2.484 GHz, 5.15–5.35 GHz, 5.725–5.825 GHz, 5.925–7.125 GHz), 4G LTE (2.3–2.39 GHz, 2.555–2.655 GHz), 5G (4.8–5.0 GHz), X-band (7–12.4 GHz), Ku-band (10.7–14.59 GHz), and C-band uplink bands (5.925–6.425 GHz). Moreover, the antenna is found to be omnidirectional at low frequencies, with a maximum peak gain of 5.43 dBi. The antenna can be used for multi-frequency wireless communication applications.

Pentacene is a well-known conjugated organic molecule with high mobility and a sensitive photo response. It is widely used in electronic devices, such as in organic thin-film transistors (OTFTs), organic light-emitting diodes (OLEDs), photodetectors, and smart sensors. With the development of flexible and wearable electronics, the deposition of good-quality pentacene films in large-scale organic electronics at the industrial level has drawn more research attention. Several methods are used to deposit pentacene thin films. The thermal evaporation technique is the most frequently used method for depositing thin films, as it has low contamination rates and a well-controlled deposition rate. Solution-processable methods such as spin coating, dip coating, and inkjet printing have also been widely studied because they enable large-scale deposition and low-cost fabrication of devices. This review summarizes the deposition principles and control parameters of each deposition method for pentacene and its derivatives. Each method is discussed in terms of experimentation and theory. Based on film quality and device performance, the review also provides a comparison of each method to provide recommendations for specific device applications.

Treatment planning plays an important role in the process of radiotherapy (RT). The quality of the treatment plan directly and significantly affects patient treatment outcomes. In the past decades, technological advances in computer and software have promoted the development of RT treatment planning systems with sophisticated dose calculation and optimization algorithms. Treatment planners now have greater flexibility in designing highly complex RT treatment plans in order to mitigate the damage to healthy tissues better while maximizing radiation dose to tumor targets. Nevertheless, treatment planning is still largely a time-inefficient and labor-intensive process in current clinical practice. Artificial intelligence, including machine learning (ML) and deep learning (DL), has been recently used to automate RT treatment planning and has gained enormous attention in the RT community due to its great promises in improving treatment planning quality and efficiency. In this article, we reviewed the historical advancement, strengths, and weaknesses of various DL-based automated RT treatment planning techniques. We have also discussed the challenges, issues, and potential research directions of DL-based automated RT treatment planning techniques.

Abstract In our work, eco-friendly, non-vacuum and low cost Electrostatic Spray Assisted Vapour Deposition (ESAVD) method has been used to produce Cu(In,Ga)(S,Se)2 (CIGS) solar cells. Copper (Cu) deficient (Cu/In + Ga = 0.76) CIGS films were designed to avoid the rather dangerous KCN treatment step for the removal of conductive minor phases of Cu2S/Cu2Se. A simple sodium (Na) treatment method was used to modify the morphology and electronic properties of the absorber and it clearly improved the solar cell performance. The SEM and XRD results testified a slightly increase of the grain size and (112) crystal orientation in the Na-incorporated CIGS thin films. From the Mott-schottky results, it can be seen that the functions of the Na treatment in our non-vacuum deposited CIGS are mainly used for defect passivation and reduction of charge recombination. Photovoltaic characteristics and j-V curve demonstrated that the dipping of CIGS films in 0.2 M NaCl solution for 20 minutes followed by selenization at 550 °C under selenium vapor resulted in the optimum photovoltaic performance, with j sc, V oc, FF and η of the optimized solar cell of 29.30 mA cm−2, 0.564 V, 65.59% and 10.83%, respectively.

Perovskite solar cells (PSCs) have achieved tremendous success within just a decade. This success is critically dependent upon compositional engineering, morphology control of perovskite layer, or contingent upon high-temperature annealed mesoporous TiO2, but quantitative analysis of the role of facile TiCl4 treatment and thickness control of the compact TiO2 layer has not been satisfactorily undertaken. Herein, we report the facile thickness control and post-treatment of the electron transport TiO2 layer to produce highly efficient planar PSCs. TiCl4 treatment of TiO2 layer could remove the surface trap and decrease the charge recombination in the prepared solar cells. Introduction of ethanol into the TiCl4 aqueous solution led to further improved open-circuit voltage and short-circuit current density of the related devices, thus giving rise to enhanced power conversion efficiency (PCE). After the optimal TiCl4 treatment, PCE of 16.42% was achieved for PSCs with TiCl4 aqueous solution-treated TiO2 and 19.24% for PSCs with TiCl4 aqueous/ethanol solution-treated TiO2, respectively. This work sheds light on the promising potential of simple planar PSCs without complicated compositional engineering and avoiding the deposition and optimization of the mesoporous scaffold layer.

Human chemokine receptor CCR3 (hCCR3) belongs to the G protein-coupled receptors (GPCRs) superfamily of membrane proteins and plays major roles in allergic diseases and angiogenesis. In order to study the structural and functional mechanism of hCCR3, it is essential to produce pure protein with biological functions on a milligram scale. Here we report the expression of hCCR3 gene in a tetracycline-inducible stable mammalian cell line. A cell clone with high hCCR3 expression was selected from 46 stably transfected cell clones and from this cell line pure hCCR3 on a milligram scale was obtained after two-step purification. Circular dichroism spectrum with a characteristic shape and magnitude for α-helix indicated proper folding of hCCR3 after purification. The biological activity of purified hCCR3 was verified by its high binding affinity with its endogenous ligands CCL11 and CCL24, with K D in the range of 10(-8) M to 10(-6) M.

This paper presents a compact, highly isolated tri-band MIMO antenna for 5G and X-band communication applications. The overall dimensions of the antenna are 43 mm × 30 mm × 1.6 mm. It consists of two monopole radiating units and a metal base with branches and slit slots. The antenna achieves tri-band characteristics by improving the shape of the radiating patch. The isolation of the antenna is enhanced by slotting the floor and loading I- and T-shaped branches to absorb coupling currents. S12 > 15 dB is achieved in the frequency ranges of 3.3 GHz–4.06 GHz, 4.62 GHz–5.28 GHz, and 8.14 GHz–9.28 GHz. Measurement results show that the measured S-parameters do not change significantly compared with the simulation. It also has a low envelope correlation coefficient and good radiation performance. [ABSTRACT FROM AUTHOR]

This paper introduces a 12-element asymmetric mirror-coupled loop antenna for integration into 5G smartphones. The proposed antenna includes six identical asymmetrically mirrored (AM)-coupled building blocks, each consisting of two gap-coupled loop antennas, with each building block dimensioning a mere 12 × 7 mm2. The unique architecture of the proposed antenna yields an isolation performance exceeding 14 dB without the necessity for ancillary decoupling elements and effectively covers the dual-band 5G mobile frequency bands of 3.3-3.6 GHz and 4.8-5.0 GHz. The antenna was optimized using simulation software HFSS, and the results indicate an antenna's envelope correlation coefficient of less than 0.016 and an efficiency range of 72%-81%. Finally, the performance of single-hand and double-hand handset smartphone modes is discussed, which still exhibit good radiation and MIMO performance under both modes, demonstrating their stability in practical applications. Simulation and measurement results indicate that the proposed 12-element MIMO antenna holds great promise for 5G smartphone applications. [ABSTRACT FROM AUTHOR]

In this paper, a WiFi-UWB multiband monopole antenna is designed, fabricated, and tested based on the characteristic mode theory, which mainly consists of an L-shaped metal, an "ok"-shaped metal radiator, and a T-shaped metal patch. The substrate dimensions are 40 × 43 × 1.6 mm³, featuring a rectangular ground plate at the substrate's bottom. The "ok"-shaped metal on the upper surface is composed of a metal ring and a curved finger-shaped metal. To improve impedance matching and broaden the bandwidth, strategic modifications are implemented. Specifically, a rectangular slot is introduced at the top of the L-shaped metal, and the T-shaped metal is rotated 90° counterclockwise and positioned beneath the "ok"-shaped metal. The microstrip feed line, constructed from metal, incorporates a feed point. Simulation results indicate that the antenna effectively covers the frequency ranges of 2.30-2.50 GHz and 3.65-9.77 GHz. At the resonance point, the maximum return loss is below -40 dB, signifying superior directional radiation characteristics. The antenna design is characterized by a wide frequency band, simple structure, and holds significant practical value for multi-frequency communication. [ABSTRACT FROM AUTHOR]