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We report a modified two-dimensional Cherenkov radiation, which occurs on a high-index dielectric nano-film driven by uniformly moving electron-beam. It is essentially different from the ordinary Cherenkov radiation in that, in the nondispersive medium, it shows unique dispersion characteristics—the waves with higher frequencies radiate at larger Cherenkov angles. Its radiation frequency and direction are essentially determined by structure parameters as well as the beam-velocity. By means of fully electromagnetic simulations and theoretical analyses, we explored the mechanism and requirements of this radiation. This new Cherenkov radiation may lead to promising applications in a broad range of fields.

MYB transcription factors have been demonstrated to play key regulatory roles in plant growth, development and abiotic stress response. However, knowledge concerning the involvement of rice genes in salinity and drought stress resistance are largely unknown. In the present study, we cloned and characterized the gene, which was induced by drought and salinity stress. Subcellular localization of OsMYB6-YFP fusion protein in protoplast cells indicated that OsMYB6 was localized in the nucleus. Overexpression of in rice did not suggest a negative effect on the growth and development of transgenic plants, but -overexpressing plants showed increased tolerance to drought and salt stress compared with wild-type plants, as are evaluated by higher proline content, higher CAT and SOD activities, lower REL and MDA content in transgenic plants under drought and salt stress conditions. In addition, the expression of abiotic stress-responsive genes were significantly higher in transgenic plants than that in wild-type plants under drought and salt stress conditions. These results indicate that gene functions as a stress-responsive transcription factor which plays a positive regulatory role in response to drought and salt stress resistance, and may be used as a candidate gene for molecular breeding of salt-tolerant and drought-tolerant crop varieties.

Spinal ependymomas are the most common spinal cord tumors in adults, but their intratumoral cellular heterogeneity has been less studied, and how spinal microglia are involved in tumor progression is still unknown. Here, our single-cell RNA-sequencing analyses of three spinal ependymoma subtypes dissect the microenvironmental landscape of spinal ependymomas and reveal tumor-associated macrophage (TAM) subsets with distinct functional phenotypes. CCL2 + TAMs are related to the immune response and exhibit a high capacity for apoptosis, while CD44 + TAMs are associated with tumor angiogenesis. By combining these results with those of single-cell ATAC-sequencing data analysis, we reveal that TEAD1 and EGR3 play roles in regulating the functional diversity of TAMs. We further identify diverse characteristics of both malignant cells and TAMs that might underlie the different malignant degrees of each subtype. Finally, assessment of cell-cell interactions reveal that stromal cells act as extracellular factors that mediate TAM diversity. Overall, our results reveal dual functions of TAMs in tumor progression, providing valuable insights for TAM-targeting immunotherapy. The intratumoural heterogeneity of spinal ependymomas and the role of microglia in tumour progression remain underexplored. Here, the authors perform single-cell RNA- and ATAC-sequencing data analysis of three subtypes and reveal tumour-associated macrophage subsets with distinct functional phenotypes.

Background Identifying GPCR-compound interactions (GCI) plays a significant role in drug discovery and chemogenomics. Machine learning, particularly deep learning, has become increasingly influential in this domain. Large molecular models, due to their ability to capture detailed structural and functional information, have shown promise in enhancing the predictive accuracy of downstream tasks. Consequently, exploring the performance of these models in GCI prediction, as well as evaluating their effectiveness when integrated with other deep learning models, has emerged as a compelling research area. This paper aims to investigate these challenges. Results This study introduces EnGCI, a novel model comprising two distinct modules. The MSBM integrates a graph isomorphism network (GIN) and a convolutional neural network (CNN) to extract features from GPCRs and compounds, respectively. These features are then processed by a Kolmogorov-Arnold network (KAN) for decision-making. The LMMBM utilizes two large-scale pre-trained models to extract features from compounds and GPCRs, and subsequently, KAN is again employed for decision-making. Each module leverages different sources of multimodal information, and their fusion enhances the overall accuracy of GPCR-compound interaction (GCI) prediction. Evaluating the EnGCI model on a rigorously curated GCI dataset, we achieved an AUC of approximately 0.89, significantly outperforming current state-of-the-art benchmark models. Conclusions The EnGCI model integrates two complementary modules: one that learns molecular features from scratch for the GPCR-compound interaction (GCI) prediction task, and another that extracts molecular features using pre-trained large molecular models. After further processing and integration, these multimodal information sources enable a more profound exploration and understanding of the complex interaction relationships between GPCRs and compounds. The EnGCI model offers a robust and efficient framework that enhances GCI predictive capabilities and has the potential to significantly contribute to GPCR drug discovery.

An interesting new physical phenomenon is uncovered-an open resonator array excited by an electron beam and able to generate a special kind of Smith-Purcell radiation (SPR). Although the frequency and direction satisfy the SPR relation, this is a single frequency radiation in a specific direction that is essentially different from ordinary SPR. The spectral density of this special radiation is also much higher than that of ordinary SPR. By means of theoretical analysis and digital simulations, the radiation mechanism together with its requirements are explored. This radiation may have great influence in modern physics and optics as it offers new ways to carry out coherent radiation generation and beam diagnostics.

Introduction The prognostic value of multifocality in paediatric papillary thyroid carcinoma (PTC) patients remains a subject of debate. This study aimed to explore the clinical significance and prognostic value of multifocality in children and adolescents with PTC. Methods This study retrospectively analysed the clinicopathological characteristics and postoperative follow-up data of 338 PTC patients aged ≤ 20 years from May 2012 to July 2022. The clinical and pathological characteristics of 205 patients with unifocal lesions and 133 patients with multifocal lesions were compared. A logistic regression model evaluated the relationship between multifocal lesions and disease recurrence/persistence in children and adolescents with PTC. Based on the median follow-up time of children with multifocal PTC, 114 patients with multifocal PTC older than 20 years were added, and the clinicopathological characteristics were compared between the 133. paediatric/adolescent patients and 114 adult patients with multifocal PTC. Results Among the paediatric and adolescent patients, over a median follow-up time of 49 months, 133 had multifocal disease and 205 had unifocal disease. Multifocal PTC patients exhibited stronger invasiveness in the form of extrathyroidal extension, tumour diameter, lymph node metastasis, and distant metastasis. Multifocality (OR 2.68; p  = 0.017), lateral lymph node metastasis (OR 2.85; p  = 0.036), and distant metastasis (OR 4.28; p  = 0.010) were identified as independent predictive factors for the recurrence/persistence of disease. Comparing the paediatric/adolescent vs. adult multifocal patients, the former demonstrated greater tumour invasiveness. Lateral lymph node metastasis (OR 6.36; P  = 0.012) and distant metastasis (OR 3.70; P  = 0.027) were independent predictive factors for recurrence/persistence of disease in multifocal patients, while age was not (OR 0.95; P  = 0.455). Conclusion Tumour multifocality independently predicts persistent/recurrent disease in paediatric and adolescent PTC patients.

Thyroid cancer (THCA) is the most common endocrine tumor. Coagulation may be associated with the development of cancer, but its role in THCA patients is not yet clear. In this study, we determined the predictive value of coagulation biomarker D-dimer for THCA patient lateral lymph node metastasis (LLNM) through receiver operating characteristics (ROC) analysis and logistic regression analysis. Subsequently, this study used the TCGA database to identify coagulation-related molecular subtypes through consensus clustering analysis and compared their prognosis. We identified coagulation-related genes (CRGs) associated with prognosis in thyroid cancer through gene expression data and clinical information, and constructed a prognostic model by selecting the prognostic CRGs using LASSO regression. Patients were divided into high-risk and low-risk groups based on the median score. Subsequently, prognosis, clinical characteristics, gene mutation occurrence, immune infiltration, function, and drug sensitivity of the two groups were analyzed. We also constructed a nomogram combining the model and clinical features. Finally, the expression of the prognostic CRGs was validated by RT-qPCR. D-dimers had better performance in predicting LLNM(the area under the curve was 0.656 (95% CI 0.580-0.733), with a cut-off value of 0.065 mg/l), and D-dimer>0.065mg/l was an independent predictor of LLNM. Then, we selected 8 prognostic CRGs to construct a predictive model. The prognosis of low-risk group patients was significantly better than that of high-risk group (P<0.001). The results showed significant differences in clinical characteristics, gene mutation occurrence, immune infiltration, function, and drug sensitivity between the high-risk and low-risk groups. We validated by qPCR that these 8 prognostic CRGs were overexpressed in THCA cell lines. Overall, this study provided an in-depth exploration of the potential role of the coagulation in thyroid cancer and its clinical significance, offering a new theoretical basis and research direction for personalized therapy and prognostic evaluation.

Recycling carbon fiber reinforced polymer (CFRP) waste is unavoidable for the sustainable manufacturing and cost reduction of CFRP products. Supercritical fluid technology is an emerging chemical method for recycling CFRP waste, but its energy intensity and environmental implication are limited understanding. In this paper, the energy intensity and environmental impact of supercritical fluid technology were quantitatively assessed in CFRP recycling process. Then, the life cycle assessment (LCA) method was used to analyse the life cycle environmental impact of CFRP in two scenarios, scenario (a) using conventional waste disposal method, while scenario (b) with CFRP waste recycling process. The results show that the energy consumption of CFRP waste recycling is 49.21 MJ/kg using the supercritical n-butanol method, which is far lower than that of virgin carbon fiber production (286 MJ/kg). Scenario (b) with CFRP waste recycling has a lower impact than scenario (a) at nine environmental impact categories, including a 26% reduction of global warming potential. Besides, the energy consumption of the supercritical n-butanol method is 31% lower than that of the steam thermolysis method (71.64 MJ/kg) in recycling 1 kg of CFRP waste, which validates that the supercritical n-butanol method is a potential strategy for recycling CFRP waste.

Potential deleterious health effects to astronauts induced by space radiation is one of the most important long-term risks for human space missions, especially future planetary missions to Mars which require a return-trip duration of about 3 years with current propulsion technology. In preparation for future human exploration, the Radiation Assessment Detector (RAD) was designed to detect and analyze the most biologically hazardous energetic particle radiation on the Martian surface as part of the Mars Science Laboratory (MSL) mission. RAD has measured the deep space radiation field within the spacecraft during the cruise to Mars and the cosmic ray induced energetic particle radiation on Mars since Curiosity’s landing in August 2012. These first-ever surface radiation data have been continuously providing a unique and direct assessment of the radiation environment on Mars. We analyze the temporal variation of the Galactic Cosmic Ray (GCR) radiation and the observed Solar Energetic Particle (SEP) events measured by RAD from the launch of MSL until December 2020, i.e., from the pre-maximum of solar cycle 24 throughout its solar minimum until the initial year of Cycle 25. Over the long term, the Mars’s surface GCR radiation increased by about 50% due to the declining solar activity and the weakening heliospheric magnetic field. At different time scales in a shorter term, RAD also detected dynamic variations in the radiation field on Mars. We present and quantify the temporal changes of the radiation field which are mainly caused by: (a) heliospheric influences which include both temporary impacts by solar transients and the long-term solar cycle evolution, (b) atmospheric changes which include the Martian daily thermal tide and seasonal CO2 cycle as well as the altitude change of the rover, (c) topographical changes along the rover path-way causing addition structural shielding and finally (d) solar particle events which occur sporadically and may significantly enhance the radiation within a short time period. Quantification of the variation allows the estimation of the accumulated radiation for a return trip to the surface of Mars under various conditions. The accumulated GCR dose equivalent, via a Hohmann transfer, is about 0.65±0.24 sievert and 1.59±0.12 sievert during solar maximum and minimum periods, respectively. The shielding of the GCR radiation by heliospheric magnetic fields during solar maximum periods is rather efficient in reducing the total GCR-induced radiation for a Mars mission, by more than 50%. However, further contributions by SEPs must also be taken into account. In the future, with advanced nuclear thrusters via a fast transfer, we estimate that the total GCR dose equivalent can be reduced to about 0.2 sievert and 0.5 sievert during solar maximum and minimum periods respectively. In addition, we also examined factors which may further reduce the radiation dose in space and on Mars and discuss the many uncertainties in the interpreting the biological effect based on the current measurement.

Particle accelerator on chip with high acceleration gradient has been an unremitting goal of researchers. Dielectric laser accelerator (DLA) is a possible candidate to achieve this goal. However, due to the limitation of dielectric breakdown, it is difficult for the available DLAs to reach an acceleration gradient as high as 1 GV m −1 since a long-duration multi-cycle laser pulse with high fluence have to be used. Here we propose to use a few-cycle laser pulse to drive a DLA based on the inverse Cherekov radiation effect. It significantly reduces the required pulse duration and the laser fluence, remarkably increasing the achievable acceleration gradient. Moreover, by using a cascade acceleration scheme, we realize a high energy-gain acceleration for low-energy electrons in a microscale device by simulation, which paves the way for the development of a fully on-chip particle accelerator.