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Plasmonics enables the manipulation of light beyond the optical diffraction limit 1 – 4 and may therefore confer advantages in applications such as photonic devices 5 – 7 , optical cloaking 8 , 9 , biochemical sensing 10 , 11 and super-resolution imaging 12 , 13 . However, the essential field-confinement capability of plasmonic devices is always accompanied by a parasitic Ohmic loss, which severely reduces their performance. Therefore, plasmonic materials (those with collective oscillations of electrons) with a lower loss than noble metals have long been sought 14 – 16 . Here we present stable sodium-based plasmonic devices with state-of-the-art performance at near-infrared wavelengths. We fabricated high-quality sodium films with electron relaxation times as long as 0.42 picoseconds using a thermo-assisted spin-coating process. A direct-waveguide experiment shows that the propagation length of surface plasmon polaritons supported at the sodium–quartz interface can reach 200 micrometres at near-infrared wavelengths. We further demonstrate a room-temperature sodium-based plasmonic nanolaser with a lasing threshold of 140 kilowatts per square centimetre, lower than values previously reported for plasmonic nanolasers at near-infrared wavelengths. These sodium-based plasmonic devices show stable performance under ambient conditions over a period of several months after packaging with epoxy. These results indicate that the performance of plasmonic devices can be greatly improved beyond that of devices using noble metals, with implications for applications in plasmonics, nanophotonics and metamaterials. A thermo-assisted spin-coating process followed by packaging is used to fabricate sodium films that are stable for several months, enabling the realization of plasmonic devices with state-of-the-art performance at near-infrared wavelengths.

Electrocoagulation (EC) has gained increasing attention as an effective and environmentally friendly technique for purifying water and wastewater. This review provides a comprehensive analysis of the recent literature on EC and identifies new trends and potentials for further research. Initially, the nature of EC and its operating parameters are discussed, while the research trends are analyzed using the Scopus database and VOSviewer software. From 1977 to 2022, 2691 research articles and review papers on EC for water/wastewater treatment were published, with the number of publications increasing from 2 in 1977 to 293 in 2022. In the past five years, most studies focused on treatment performance and the mechanism of EC systems. However, recent emphasis has been placed on combining EC with other treatment processes and addressing emerging pollutants. The innovative applications of EC are highlighted, including the removal of microplastics and per/polyfluoroalkyl substances, the power supply of EC via microbial fuel cells (MFCs) and electro-wetlands (EWs), and the application of power management systems in EC. The review concludes with suggestions for further research to enhance the technology and expand its scope of applications.

With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and significant role in situation awareness. While, in addition to different passive transducer localization modes and solutions of target’s location, the reasonable planning and optimal layout of passive transducers’ location are other major factors affecting the precision of localization. Planning an optimal airspace for passive transducers is the key problem to improve the monitoring efficiency. This paper proposes the optimal layout algorithm for the cooperative platform in the space based on the geometrical relationship of cooperative localization. For example, the principle of direction location in traditional methods is simple: only two passive sensors can work, but the location accuracy of long-distance targets is low. At the same time, TDOA (Time Difference Of Arrival) location has high accuracy and good stability, but it needs at least three passive sensors to work together, which requires the most resources. In this paper, a platform optimization layout algorithm based on direction and TDOA hybrid positioning is proposed. Compared with direction positioning, it improves the long-distance positioning accuracy, reduces the number of sensors required for TDOA positioning, and reduces the resource occupancy rate. However, the TDOA positioning data mixed with direction positioning data inevitably leads to the decline of overall accuracy. In order to solve these difficulties, the weighted least square method is used to optimize the accuracy. The simulation shows that, within the designated target airspace, the optimal action airspace can be generated automatically based on the platforms’ cooperation mode. If there is no resource limitation, the airspace planning based on TDOA positioning has the highest accuracy for the target. However, in practical application, considering the resource limitation, the hybrid positioning of direction and TDOA can also meet the requirements of high accuracy and high stability. The average error is reduced by more than 45% compared with direction positioning, and the airspace occupancy is reduced by more than 30% compared with TDOA positioning. The goal of minimizing the scope of platform airspace planning is realized.

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion.

Background The abnormal expression of leucine-rich-alpha-2-glycoprotein 1 (LRG-1) is reported to be associated with multiple malignancies, but its role in the progression of pancreatic ductal adenocarcinoma (PDAC) remains to be determined. Methods The expression of LRG-1 was assessed in PDAC tissues by RT-PCR, Western blot and immunohistochemistry. LRG-1-silenced or overexpressed cell lines were constructed using shRNA or LRG-1-overexpressing plasmids. EdU incorporation assay, Transwell invasion and wound-healing assays were performed to evaluate the proliferation, invasion and migration of PDAC cells. In addition, protein expression of the mitogen-activated protein kinase (MAPK) pathway was detected using Western blot. Finally, Co-immunoprecipitation assay was conducted in search of the potential interaction between LRG-1 and epidermal growth factor receptor (EGFR). Results The expression of LRG-1 in PDAC tissue was significantly higher than that in adjacent normal tissue, and high LRG-1 expression predicted poor survival and a late tumor stage. In addition, LRG-1 markedly promoted the viability, proliferation, migration and invasion of PDAC cells in vitro and facilitated tumor growth in vivo. More importantly, we revealed that these bioactivities of LRG-1 might result from its selective interaction with EGFR, which might further activate the p38/MAPK signaling pathways. Conclusion LRG-1 may prove to be a promising biomarker for predicting prognosis of PDAC patients. Inhibition of LRG-1 or its downstream pathway could be a potential therapeutic target for the treatment of PDAC.

Summary P/TGMS (Photo/thermo‐sensitive genic male sterile) lines are crucial resources for two‐line hybrid rice breeding. Previous studies revealed that slow development is a general mechanism for sterility–fertility conversion of P/TGMS in Arabidopsis. However, the difference in P/TGMS genes between rice and Arabidopsis suggests the presence of a distinct P/TGMS mechanism in rice. In this study, we isolated a novel P/TGMS line, ostms19, which shows sterility under high‐temperature conditions and fertility under low‐temperature conditions. OsTMS19 encodes a novel pentatricopeptide repeat (PPR) protein essential for pollen formation, in which a point mutation GTA(Val) to GCA(Ala) leads to ostms19 P/TGMS phenotype. It is highly expressed in the tapetum and localized to mitochondria. Under high temperature or long‐day photoperiod conditions, excessive ROS accumulation in ostms19 anthers during pollen mitosis disrupts gene expression and intine formation, causing male sterility. Conversely, under low temperature or short‐day photoperiod conditions, ROS can be effectively scavenged in anthers, resulting in fertility restoration. This indicates that ROS homeostasis is critical for fertility conversion. This relationship between ROS homeostasis and fertility conversion has also been observed in other tested rice P/TGMS lines. Therefore, we propose that ROS homeostasis is a general mechanism for the sterility–fertility conversion of rice P/TGMS lines.

To ensure the safety of buildings, accurate and robust prediction of a reinforced concrete deep beam’s shear capacity is necessary to avoid unpredictable accidents caused by brittle failure. However, the failure mechanism of reinforced concrete deep beams is very complicated, has not been fully elucidated, and cannot be accurately described by simple equations. To solve this issue, machine learning techniques have been utilized and corresponding prediction models have been developed. Nevertheless, these models can only provide deterministic prediction results of the scalar type, and the confidence level is uncertain. Thus, these prediction results cannot be used for the design and assessment of deep beams. Therefore, in this paper, a probabilistic prediction approach of the shear strength of reinforced concrete deep beams is proposed based on the natural gradient boosting algorithm trained on a collected database. A database of 267 deep beam experiments was utilized, with 14 key parameters identified as the inputs related to the beam geometry, material properties, and reinforcement details. The proposed NGBoost model was compared to empirical formulas from design codes and other machine learning methods. The results showed that the NGBoost model achieved higher accuracy in mean shear strength prediction, with an R2 of 0.9045 and an RMSE of 38.8 kN, outperforming existing formulas by over 50%. Additionally, the NGBoost model provided probabilistic predictions of shear strength as probability density functions, enabling reliable confidence intervals. This demonstrated the capability of the data-driven NGBoost approach for robust shear strength evaluation of RC deep beams. Overall, the results illustrated that the proposed probabilistic prediction approach dramatically surpassed the current formulas adopted in design codes and machine learning models in both prediction accuracy and robustness.

Background Colorectal cancer (CRC) is one of the most common malignant tumors of the digestive system, ranking third for morbidity and mortality worldwide. At present, no effective control method is available for this cancer type. In tumor cells, especially iron metabolization, is necessary for its growth and proliferation. High levels of iron are an important feature to maintain tumor growth; however, the overall mechanism remains unclear. Methods We used western blotting, immunohistochemistry (IHC) and real-time quantitative PCR to analyze the expression of IGF2BP2 in cell lines and tissues. Further, RNA-sequencing, RNA immunoprecipitation and methylated RNA immunoprecipitation experiments explored the specific binding of target genes. Moreover, the RNA stability assay was performed to determine the half-life of genes downstream of IGF2BP2. In addition, the Cell Counting Kit-8, colony formation assay, 5-ethynyl-2’-deoxyuridine assay and flow cytometry were used to evaluate the effects of IGF2BP2 on proliferation and iron metabolism. Lastly, the role of IGF2BP2 in promoting CRC growth was demonstrated in animal models. Results We observed that IGF2BP2 is associated with iron homeostasis and that TFRC is a downstream target of IGF2BP2. Further, overexpression of TFRC can rescue the growth of IGF2BP2-knockdown CRC cells. Mechanistically, we determined that IGF2BP2 regulates TFRC methylation via METTL4, thereby regulating iron metabolism and promoting CRC growth. Furthermore, using animal models, we observed that IGF2BP2 promotes CRC growth. Conclusion IGF2BP2 regulates TFRC mRNA methylation via METTL4, thereby regulating iron metabolism and promoting CRC growth. Our study highlights the key roles of IGF2BP2 in CRC carcinogenesis and the iron transport pathways.

Purpose To explore the association between waist circumference (WC), estimated cardiopulmonary function (eCRF), and cardiovascular disease (CVD) risk in southern Xinjiang. Update the Framingham model to make it more suitable for the southern Xinjiang population. Methods Data were collected from 7705 subjects aged 30–74 years old in Tumushuke City, the 51st Regiment of Xinjiang Production and Construction Corps. CVD was defined as an individual's first diagnosis of non-fatal acute myocardial infarction, death from coronary heart disease, and fatal or non-fatal stroke. The Cox proportional hazards regression analysis was used to analyze the association between WC, eCRF and CVD risk. Restricted cubic spline plots were drawn to describe the association of the two indicators with CVD risk. We update the model by incorporating the new variables into the Framingham model and re-estimating the coefficients. The discrimination of the model is evaluated using AUC, NRI, and IDI metrics. Model calibration is evaluated using pseudo R 2 values. Results WC was an independent risk factor for CVD (multivariate HR: 1.603 (1.323, 1.942)), eCRF was an independent protective factor for CVD (multivariate HR: 0.499 (0.369, 0.674)). There was a nonlinear relationship between WC and CVD risk (nonlinear χ2 = 12.43, P  = 0.002). There was a linear association between eCRF and CVD risk (non-linear χ2 = 0.27, P  = 0.6027). In the male, the best risk prediction effect was obtained when WC and eCRF were added to the model (AUC = 0.763((0.734,0.792)); pseudo R 2  = 0.069). In the female, the best risk prediction effect was obtained by adding eCRF to the model (AUC = 0.757 (0.734,0.779); pseudo R 2  = 0.107). Conclusion In southern Xinjiang, WC is an independent risk factor for CVD. eCRF is an independent protective factor for CVD. We recommended adding WC and eCRF in the male model and only eCRF in the female model for better risk prediction.

Ferroptosis is an iron-dependent programmed cell death associated with severe kidney diseases, linked to decreased glutathione peroxidase 4 (GPX4). However, the spatial distribution of renal GPX4-mediated ferroptosis and the molecular events causing GPX4 reduction during ischemia-reperfusion (I/R) remain largely unknown. Using spatial transcriptomics, we identify that GPX4 is situated at the interface of the inner cortex and outer medulla, a hyperactive ferroptosis site post-I/R injury. We further discover OTU deubiquitinase 5 (OTUD5) as a GPX4-binding protein that confers ferroptosis resistance by stabilizing GPX4. During I/R, ferroptosis is induced by mTORC1-mediated autophagy, causing OTUD5 degradation and subsequent GPX4 decay. Functionally, OTUD5 deletion intensifies renal tubular cell ferroptosis and exacerbates acute kidney injury, while AAV-mediated OTUD5 delivery mitigates ferroptosis and promotes renal function recovery from I/R injury. Overall, this study highlights a new autophagy-dependent ferroptosis module: hypoxia/ischemia-induced OTUD5 autophagy triggers GPX4 degradation, offering a potential therapeutic avenue for I/R-related kidney diseases. Understanding the role of GPX4 in cell ferroptosis at the interface of the inner cortex and medulla is crucial in the context of renal injury. Here, the authors demonstrate that the OTUD5 interaction with GPX4 is key in resisting ischemia/reperfusion-induced ferroptosis in renal cells, offering a new strategy for treating acute kidney injury.