Search

Engineering vehicles play a vital role in supporting construction projects. However, due to their substantial size, heavy tonnage, and significant blind spots while in motion, they present a potential threat to road maintenance, pedestrian safety, and the well-being of other vehicles. Hence, monitoring engineering vehicles holds considerable importance. This paper introduces an engineering vehicle detection model based on improved YOLOv6. First, a Swin Transformer is employed for feature extraction, capturing comprehensive image features to improve the detection capability of incomplete objects. Subsequently, the SimMIM self-supervised training paradigm is implemented to address challenges related to insufficient data and high labeling costs. Experimental results demonstrate the model's superior performance, with a m A P 50 : 95 value of 88.5% and m A P 50 value of 95.9% on the dataset of four types of engineering vehicles, surpassing existing mainstream models and proving its effectiveness in engineering vehicle detection. [ABSTRACT FROM AUTHOR]

Accurate tracing of crude oil origins is essential for thwarting deceptive trade practices, including origin falsification to evade taxes, thereby preventing economic losses and security threats for importing nations. Traditional crude oil origin determination methods require complex sample preparation, expensive instrumentation, and stable testing environments, rendering them impractical for real-time analysis at locations such as ports. This paper introduces a novel approach utilizing near-infrared spectroscopy (NIRS) combined with deep learning algorithms to expedite and enhance the precision of crude oil source identification. To effectively eliminate outliers, an improved Mahalanobis distance is introduced, incorporating regularization principles and global-local concepts. This approach addresses the challenges of inverting covariance matrices in high-dimensional spectra and excludes samples with localized aberrations. Furthermore, the integration of multi-receptive fields perception, Transformer-based global information interaction, and the scSE attention mechanism has led to the development of an MG-Unet model, designed to resolve spectral peak overlap issues and capture long-range feature dependencies. The proposed method achieves state-of-the-art accuracy of 96.92%, demonstrating significant potential for reliable crude oil source tracing. [ABSTRACT FROM AUTHOR]

Magnesium metal batteries (MMBs) currently face challenges suffering from severe Mg metal passivation and extremely high overpotential in conventional electrolytes. Herein, a strategy of using a low‐cost deep eutectic solution (DES) is proposed to modify Mg anode with the monolithic and compact coating of a MgCl2‐Al‐MgCl2 sandwich structure, enabling the stable and reversible Mg plating–stripping behavior. An organic/nanocrystal hybrid interphase is in‐situ built through a facile Mg‐Al displacement reaction between aluminum‐chloro clusters and Mg in AlCl3/Et3NHCl solution, and it can effectively minimize the adverse interfacial passivation reaction and surface diffusion barrier, affording the high ion‐conduction and electronic insulation. This DES‐assisted method guarantees a highly reversible cycling of Mg metal anode (over 5000 h at 0.1 mA cm−2 and 400 h at 2.0 mAh cm−2) in Mg(TFSI)2/DME electrolyte with the improved interfacial kinetics and low overpotential. Even at a much higher current density of 1 mA cm−2, the overpotential only undergoes a slight increase from 0.2 V (at 0.1 mA cm−2) to 0.23 V. The corresponding full cells with CuS and phenanthraquinone cathodes deliver satisfactory cyclic performance. The DES modification strategy provides a new solution to the design of robust and conductive solid electrolyte interphase for achieving high‐voltage and durable MMBs. [ABSTRACT FROM AUTHOR]

Graph Neural Networks (GNNs) have demonstrated significant potential as powerful tools for handling graph data in various fields. However, traditional GNNs often encounter limitations in information capture and generalization when dealing with complex and high-order graph structures. Concurrently, the sparse labeling phenomenon in graph data poses challenges in practical applications. To address these issues, we propose a novel graph contrastive learning method, TP-GCL, based on a tensor perspective. The objective is to overcome the limitations of traditional GNNs in modeling complex structures and addressing the issue of sparse labels. Firstly, we transform ordinary graphs into hypergraphs through clique expansion and employ high-order adjacency tensors to represent hypergraphs, aiming to comprehensively capture their complex structural information. Secondly, we introduce a contrastive learning framework, using the original graph as the anchor, to further explore the differences and similarities between the anchor graph and the tensorized hypergraph. This process effectively extracts crucial structural features from graph data. Experimental results demonstrate that TP-GCL achieves significant performance improvements compared to baseline methods across multiple public datasets, particularly showcasing enhanced generalization capabilities and effectiveness in handling complex graph structures and sparse labeled data. [ABSTRACT FROM AUTHOR]

Purpose: To enhance the predictive risk model for all-cause mortality in individuals with Type 2 Diabetes (T2DM) and prolonged Atherosclerotic Cardiovascular Disease (ASCVD) risk factors. Despite the utility of the Coronary Artery Calcium (CAC) score in assessing cardiovascular risk, its capacity to predict all-cause mortality remains limited. Methods: A retrospective cohort study included 1929 asymptomatic T2DM patients with ASCVD risk factors, aged 40–80. Variables encompassed demographic attributes, clinical parameters, CAC scores, comorbidities, and medication usage. Factors predicting all-cause mortality were selected to create a predictive scoring system. By using stepwise selection in a multivariate Cox proportional hazards model, we divided the patients into three risk groups. Results: In our analysis of all-cause mortality in T2DM patients with extended ASCVD risk factors over 5 years, we identified significant risk factors, their adjusted hazard ratios (aHR), and scores: e.g., CAC score > 1000 (aHR: 1.57, score: 2), CAC score 401–1000 (aHR: 2.05, score: 2), and more. These factors strongly predict all-cause mortality, with varying risk groups (e.g., very low-risk: 2.0%, very high-risk: 24.0%). Significant differences in 5-year overall survival rates were observed among these groups (log-rank test < 0.001). Conclusion: The Poh-Ai Predictive Scoring System excels in forecasting mortality and cardiovascular events in individuals with Type 2 Diabetes Mellitus and extended ASCVD risk factors. [ABSTRACT FROM AUTHOR]

Conversion‐reaction metal fluoride cathodes have the advantages of low cost, environmental friendliness, and high energy density. However, their tailored synthesis and structure design under safe, facile, and scalable conditions have always been a puzzle, which limits the popularization of conversion‐type cathodes in lithium metal batteries. To address these challenges, here an iron fluoride heterostructure with FeF2 and FeF3 binary phases is proposed and prepared by deep eutectic solvent method under the assistance of cobalt cation as an oxidization promoter. The compact heterogeneous contact between tetragonal FeF2 and hexagonal tungsten bronze FeF3 phases enables the promotion and stabilization of interface charge transfer and topotactic conversion reaction. The narrower band gap of FeF2, higher theoretical capacity and thermodynamic potential of FeF3 synergistically contribute to the balance between cycling reversibility and capacity. The heterostructure cathode with an optimized molar ratio of FeF2/FeF3 can realize a highly reversible capacity of ≈520 mAh g−1 in the first tens of cycles and 305 mAh g−1 after 200 cycles. The typical two‐stage reaction plateaus are well preserved even under the high current density of 1000 mA g−1. The green synthesis strategy and heterostructure fluoride design open a new horizon for the development of high‐energy‐density metal fluoride batteries. [ABSTRACT FROM AUTHOR]

Introduction: Statistical methods such as empirical orthogonal functions (EOFs) are often used to model the sound speed profile (SSP). However, their statistical nature often leads to the sample dependence and physical fuzziness. Method: This study proposes a technique for modeling the SSP from the perspective of ocean dynamics. It employs the ocean normal mode, which is the mode of fluid particles motion, to deduce perturbations in the SSP, which is called the ocean mode basis (OMB). Result: The results of SSP reconstruction of in-situ samples showed that a few leading orders of the OMB can provide a compact representation of the SSP. Oscillations of the contours and gradient of the sound speed in thermocline were analyzed by using the first two orders of the projection coefficients of the relationship between the OMB and the baroclinic mode. As a physical model, this technique can also be used to characterize the dynamics of internal solitary waves. Furthermore, the OMB derived from archival date was used for SSP inversion. The results showed that the OMB can reconstruct SSP of a reasonable resolution without requiring in-situ samples. Discussion: Compared with statistical models, the OMB can better explain the ocean dynamics underlying variations in the SSP while requiring fewer samples. [ABSTRACT FROM AUTHOR]

Introduction: Existing methods primarily focus on earth acoustic parameters inversion under specific layered structures. However, they face challenges with experimental data from unknown seabed stratification, hindering accurate parameter inversion. Methods: To address this, a novel algorithm combines Back Propagation Neural Network (BPNN) for distinguishing seabed stratification and inverting acoustic parameters. Simulated sound pressure data disturb seabed parameters as input, enabling feature recognition for training the neural network inversion model. Acoustic parameters are then estimated under identified stratification using the sound field model. Results: The inversion model is validated using simulation and pool shrinkage data. Results show the neural network model effectively stratifies simulation and experimental data, providing accurate inversion results for acoustic parameters corresponding to distinct layers. Discussion: The neural network model's accuracy and practicality are confirmed through hierarchical judgment of scale test data and acoustic parameter inversion. This approach introduces a new perspective for shallow sea acoustic parameter inversion, offering a promising application scenario. [ABSTRACT FROM AUTHOR]

Objective: To assess the cardiorenal protective effects of different doses of atorvastatin in patients with cardiorenal syndrome (CRS) Type-2. Methods: Medical records of 113 patients with CRS Type-2, admitted to First Affiliated Hospital of Hebei North University from August 2021 to August 2022 and treated with atorvastatin, were retrospectively analyzed. Patients were retrospectively grouped based on the dosage of atorvastatin. A total of 38 patients who received 10mg/day atorvastatin were selected as a Low-dose group, 36 patients who received 20mg/day atorvastatin comprised a Mediumdose group, and 39 patients who received 40mg/day atorvastatin comprised a High-dose group. Cardiac function indicators (Left ventricular end-diastolic dimension [LVEDD], left ventricular end-stage systole diameter [LVESD], and left ventricular ejection fraction [LVEF]), renal function indicators (creatinine [SCr], serum uric acid [SUA], heme oxygenase-1 [HO-1], urinary albumin [UALB]), and inflammatory factors (Serum interleukin-6 [IL-6], hypersensitive C-reactive protein [hs-CRP], and tumor necrosis factor -α [TNF-α]) were compared between the three groups. Results: After the treatment, levels of renal and cardiac function indicators, and inflammatory factor indicators of the three groups were significantly improved compared to the before-treatment levels. The degree of improvement in the Medium-dose and the High-dose groups was significantly higher than in the Low-dose group (p<0.05). There were no significant differences in all cardiorenal function indicators and inflammatory factors between the Medium-dose and the High-dose groups after the treatment. During the treatment process, no adverse events were reported in all three groups. Conclusions: In the treatment of patients with CRS Type-2, medium dose (20mg/day) atorvastatin can have the same therapeutic effect as the high dose (40mg/day) treatment. Medium dose has a good protective effect on the heart and kidneys of the patients, and helps to reduce inflammatory reactions and improve heart and kidney function. [ABSTRACT FROM AUTHOR]

Background: Previous studies show that using 12‐lead electrocardiogram (ECG) or 24‐h ECG monitor for the detection of cardiac arrhythmia events in patients with stroke or syncope is ineffective. Hypothesis: The 14‐day continuous ECG patch has higher detection rates of arrhythmias compared with conventional 24‐h ECG monitoring in patients with ischemic stroke or syncope. Methods: This cross‐sectional study of patients with newly diagnosed ischemic stroke or syncope received a 24‐h ECG monitoring and 14‐day continuous cardiac monitoring patch and the arrhythmia events were measured. Results: This study enrolled 83 patients with ischemic stroke or syncope. The detection rate of composite cardiac arrhythmias was significantly higher for the 14‐day ECG patch than 24‐h Holter monitor (69.9% vs. 21.7%, p =.006). In patients with ischemic stroke, the detection rates of cardiac arrhythmias were 63.4% for supraventricular tachycardia (SVT), 7% for ventricular tachycardia (VT), 5.6% for atrial fibrillation (AF), 4.2% for atrioventricular block (AVB), and 1.4% for pause by 14‐day ECG patch, respectively. The significant difference in arrhythmic detection rates were found for SVT (45.8%), AF (6%), pause (1.2%), AVB (2.4%), and VT (9.6%) by 14‐day ECG patch but not by 24‐h Holter monitor in patients with ischemic stroke or syncope. Conclusions: A 14‐day ECG patch can be used on patients with ischemic stroke or syncope for the early detection of AF or other cardiac arrhythmia events. The patch can be helpful for physicians in planning medical or mechanical interventions of patients with ischemic stroke and occult AF. [ABSTRACT FROM AUTHOR]

In Li metal batteries, the rational construction of artificial solid electrolyte interphase (ASEI) can homogenize the Li‐ion flowing and Li‐mass plating/stripping, and reinforce the mechanical and electrochemical stabilities of electrode–electrolyte interface. Here, an ordered‐mesoporous powder zirconium oxophosphate (ZrOP) is proposed to construct a Li‐ion conductive ASEI by brushing ZrOP on metallic Li. The P‐induced amorphization in ZrOP is expected to accelerate the spontaneous lithiation reaction and promote the generation of P‐contained Li‐ion conductors and LiF domains in ASEI during Li anode cycling. The electrochemical activation of ASEI with promoted ionic conductivity and interconnected porous network is favorable for the homogeneous nucleation and growth of Li metal grains (with ≈10 µm in size), and the suppression of Li dendrites and volume expansion during long‐term Li plating and stripping. The ZrOP‐modified Li symmetric cell enables a long lifespan of over 1600 h at 1 mA cm−2, and the corresponding LiNi0.8Co0.1Mn0.1O2 (NCM811) based full cell displays a stable cycling for at least 300 cycles with a capacity retention of 80% at 1 C. The modified thin Li foil (40 µm in thickness) anode also enables a multilayered pouch cell based on a high‐loading NCM811 cathode with stable cycling and reversible capacity over 1 Ah. [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease (NAFLD) is associated with mutations in lipopolysaccharide-binding protein (LBP), but the underlying epigenetic mechanisms remain understudied. Herein, LBP-/- rats with NAFLD were established and used to conduct integrative targetingactive enhancer histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation coupled with high-throughput and transcriptomic sequencing analysis to explore the potential epigenetic pathomechanisms of active enhancers of NAFLD exacerbation upon LBP deficiency. Notably, LBP-/- reduced the inflammatory response but markedly aggravated high-fat diet (HFD)- induced NAFLD in rats, with pronounced alterations in the histone acetylome and regulatory transcriptome. In total, 1 128 differential enhancer-target genes significantly enriched in cholesterol and fatty acid metabolism were identified between wild-type (WT) and LBP-/- NAFLD rats. Based on integrative analysis, CCAAT/enhancer-binding protein β (C/EBPβ) was identified as a pivotal transcription factor (TF) and contributor to dysregulated histone acetylome H3K27ac, and the lipid metabolism gene SCD was identified as a downstream effector exacerbating NAFLD. This study not only broadens our understanding of the essential role of LBP in the pathogenesis of NAFLD from an epigenetics perspective but also identifies key TF C/EBPβ and functional gene SCD as potential regulators and therapeutic targets. [ABSTRACT FROM AUTHOR]

The endothelial cell (EC) outgrowth in both vasculogenesis and angiogenesis starts with remodeling surrounding matrix and proceeds with the crosstalk between cells for the multicellular vasculature formation. The mechanical plasticity of matrix, defined as the ability to permanently deform by external traction, is pivotal in modulating cell behaviors. Nevertheless, the implications of matrix plasticity on cell-to-cell interactions during EC outgrowth, along with the molecular pathways involved, remain elusive. Here we develop a collagen-hyaluronic acid based hydrogel platform with tunable plasticity by using compositing strategy of dynamic and covalent networks. We show that although the increasing plasticity of the hydrogel facilitates the matrix remodeling by ECs, the largest tubular lumens and the longest invading distance unexpectedly appear in hydrogels with medium plasticity instead of the highest ones. We unravel that the high plasticity of the hydrogels promotes stable integrin cluster of ECs and recruitment of focal adhesion kinase with an overenhanced contractility which downregulates the vascular endothelial cadherin expression and destabilizes the adherens junctions between individual ECs. Our results, further validated with mathematical simulations and in vivo angiogenic tests, demonstrate that a balance of matrix plasticity facilitates both cell-matrix binding and cell-to-cell adherens, for promoting vascular assembly and invasion. It is vital to unveil the effects of extracellular matrix cues on endothelial cell (EC) outgrowth for desirably governing vasculature formation, but the role of matrix plasticity on EC outgrowth is elusive. Here, the authors develop hydrogels with tunable mechanical plasticity independent of stiffness, and elucidate the plasticity-mediated responses of ECs during vasculogenesis and angiogenesis. [ABSTRACT FROM AUTHOR]

Lung segmentation is an essential step in a computer‐aided diagnosis system for chest radiographs. The lung parenchyma is first segmented in pulmonary computer‐aided diagnosis systems to remove the interference of non‐lung regions while increasing the effectiveness of the subsequent work. Nevertheless, most medical image segmentation methods nowadays use U‐Net and its variants. These variant networks perform poorly in segmentation to detect smaller structures and cannot accurately segment boundary regions. A multi‐interaction feature fusion network model based on Kiu‐Net is presented in this paper to address this problem. Specifically, U‐Net and Ki‐Net are first utilized to extract high‐level and detailed features of chest images, respectively. Then, cross‐residual fusion modules are employed in the network encoding stage to obtain complementary features from these two networks. Second, the global information module is introduced to guarantee the segmented region's integrity. Finally, in the network decoding stage, the multi‐interaction module is presented, which allows to interact with multiple kinds of information, such as global contextual information, branching features, and fused features, to obtain more practical information. The performance of the proposed model was assessed on both the Montgomery County (MC) and Shenzhen datasets, demonstrating its superiority over existing methods according to the experimental results. [ABSTRACT FROM AUTHOR]

Although cellular metabolic states have been shown to modulate bacterial susceptibility to antibiotics, the interaction between glutamate (Glu) and chloramphenicol (CAP) resistance remains unclear because of the specificity of antibiotics and bacteria. We found that the level of Glu was upregulated in the CAP-resistant strain of Edwardsiella tarda according to a comparative metabolomics approach based on LC-MS/MS. Furthermore, we verified that exogenous metabolites related to Glu, the tricarboxylic acid (TCA) cycle, and glutathione (GSH) metabolism could promote CAP resistance in survival assays. If GSH metabolism or the TCA cycle is inhibited by L-buthionine sulfoximine or propanedioic acid, the promotion of CAP resistance by Glu in the corresponding pathway disappears. According to metabolomic analysis, exogenous Glu could change pantothenate metabolism, affecting GSH biosynthesis and the TCA cycle. These results showed that the glutamate-pantothenate pathway could promote CAP resistance by being involved in the synthesis of GSH, entering the TCA cycle by direct deamination, or indirectly affecting the metabolism of the two pathways by pantothenate. These results extend our knowledge of the effect of Glu on antibiotic resistance and suggest that the potential effect, which may aggravate antibiotic resistance, should be considered before Glu and GSH administration in the clinic. [ABSTRACT FROM AUTHOR]

Background: Diabetic osteoporosis exhibits heterogeneity at the molecular level. Ferroptosis, a controlled form of cell death brought on by a buildup of lipid peroxidation, contributes to the onset and development of several illnesses. The aim was to explore the molecular subtypes associated with ferroptosis in diabetic osteoporosis at the molecular level and to further elucidate the potential molecular mechanisms. Methods: Integrating the CTD, GeneCards, FerrDb databases, and the microarray data of GSE35958, we identified ferroptosis-related genes (FRGs) associated with diabetic osteoporosis. We applied unsupervised cluster analysis to divide the 42 osteoporosis samples from the GSE56814 microarray data into different subclusters based on FRGs. Subsequently, FRGs associated with two ferroptosis subclusters were obtained by combining database genes, module-related genes of WGCNA, and differentially expressed genes (DEGs). Eventually, the key genes from FRGs associated with diabetic osteoporosis were identified using the least absolute shrinkage and selection operator (LASSO), Boruta, support vector machine recursive feature elimination (SVM RFE), and extreme gradient boosting (XGBoost) machine learning algorithms. Based on ROC curves of external datasets (GSE56815), the model's efficiency was examined. Results: We identified 15 differentially expressed FRGs associated with diabetic osteoporosis. In osteoporosis, two distinct molecular clusters related to ferroptosis were found. The expression results and GSVA analysis indicated that 15 FRGs exhibited significantly different biological functions and pathway activities in the two ferroptosis subclusters. Therefore, we further identified 17 FRGs associated with diabetic osteoporosis between the two subclusters. The results of the comprehensive analysis of 17 FRGs demonstrated that these genes were heterogeneous and had a specific interaction between the two subclusters. Ultimately, the prediction model had a strong foundation and excellent AUC values (0.84 for LASSO, 0.84 for SVM RFE, 0.82 for Boruta, and 0.81 for XGBoost). IDH1 is a common gene to all four algorithms thus being identified as a key gene with a high AUC value (AUC = 0.698). Conclusions: As a ferroptosis regulator, IDH1 is able to distinguish between distinct molecular subtypes of diabetic osteoporosis, which may offer fresh perspectives on the pathogenesis of the disease's clinical symptoms and prognostic heterogeneity. [ABSTRACT FROM AUTHOR]

As a probiotic, enterococcus faecium (E. faecium) has the characteristics of high temperature resistance, gastric acid resistance, bile salt resistance, etc. It can also effectively improve animal performance and immunity and improve the animal's intestinal environment, so in recent years it has been more widely used in the livestock industry. However, due to the improper use of antibiotics and the growing environmental stress of strains, the drug resistance of enterococcus faecium has become more and more serious, and because some enterococcus faecium carry virulence genes, leading to the emergence of pathogenic strains, its safety issues have been widely concerned. This paper focuses on the biological characteristics of enterococcus faecium, the application of this bacterium in animal husbandry and the safety issues in its use, with a view to providing a reference for the application of enterococcus faecium in the development of animal husbandry. [ABSTRACT FROM AUTHOR]

Drawing upon the conservation of resources (COR) theory, this paper discusses the effect of platform economic dependence on working time and the mediating role of work pressure, as well as the boundary role of platform human resource management practices, with a survey of 9576 takeaway riders. The results suggest that the greater the economic dependence of takeaway riders on the platform organization, the longer they work; work pressure plays a mediating role between platform economic dependence and working time; the amount of platform rewards has no effect on the positive relationship between platform economic dependence and working time, whereas the difficulty of obtaining platform rewards strengthens the positive relationship between platform economic dependence and working time. This paper contributes to the literature on gig work by providing a micro-individual perspective and to the literature on COR theory by enriching the studies of resource caravan passageways. [ABSTRACT FROM AUTHOR]

Chest X-ray (CXR) images can be used to diagnose a variety of lung diseases, such as tuberculosis, pneumonia, and lung cancer. However, the variation in lung morphology due to differences in age, gender, and the severity of pathology makes high-precision lung segmentation a challenging task. Traditional segmentation networks, such as U-Net, have become the standard architecture and have achieved remarkable results in lung field image segmentation tasks. However, because traditional convolutional operations can only explicitly capture local semantic information, it is difficult to obtain global semantic information, resulting in difficult performance in terms of accuracy requirements in medical practical applications. In recent years, the introduction of Transformer technology to natural language processing has achieved great success in the field of computer vision. In this paper, a new network architecture called TransCotANet is proposed. The network architecture is based on the U-Net architecture with convolutional neural networks (CNNs) as the backbone and extracts global semantic information through symmetric cross-layer connections in the encoder structure, where the encoder stage includes an upsampling module to improve the resolution of the feature map, and uses the dynamic aggregation module CotA to dynamically aggregate multi-scale feature maps and finally obtain more accurate segmentation results. The experimental results show that the method outperformed other methods for lung field image segmentation datasets. [ABSTRACT FROM AUTHOR]

In this work, a novel flower-shaped NV-g-C3N5@VS2 heterojunction was prepared by hydrothermal in situ synthesis using NV-g-C3N5 as the matrix and thioacetamide as the precursor. The prepared heterojunction showed a flower-like and layered structure, which widened the visible light absorption range and facilitated the usage of visible light. Under visible light irradiation, the NV-g-C3N5@VS2 heterojunction exhibited excellent photoelectrocatalytic nitrogen reduction activity with an ammonia yield of 49.26 μg h−1 mg−1 in an electrolyte solution saturated with N2. Moreover, the NV-g-C3N5@VS2 heterojunction achieved outstanding photocatalytic degradation activity. The photocatalytic degradation rate of Rhodamine (RhB) reached 95% in 35 min under visible light irradiation. More importantly, the catalyst displayed good reusability and stability after four cycling runs for the photodegradation of MB. The prepared catalyst showed excellent photocatalytic universality and was also applied to efficiently degrade organic pollutants such as methyl orange (MO) and methylene blue (MB). Therefore, solar light-driven photocatalytic and photoelectrocatalytic applications based on the NV-g-C3N5@VS2 heterojunction are expected to pave a new way for fertilizers, energy utilization, and environmental remediation. [ABSTRACT FROM AUTHOR]

The polyethylene oxide (PEO) based solid-state batteries are considered as promising candidates for the next-generation Li metal batteries with high energy density and safety. However, the low Li-ion conductivity and high-voltage endurability hinder the further applications of PEO-based electrolytes. To overcome these issues, herein two-dimensional (2D) CeF3 nanoplates with maximally exposed [001] crystal faces are introduced into the PEO matrix to expand the electrochemical window and improve Li-ion conduction and transport. The optimized crystal shape and crystal face anisotropy of CeF3 nanoplate filler reduce the crystallinity of composite solid polymer electrolyte (CSPE) via its Lewis acid-base interaction with ether oxygen of PEO. The Li-affinity [100] and Li-repellent [001] crystal faces of CeF3 nanoplates synergistically realize the dissociation of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), fast Li-adsorption/desorption, and Li+ migration. The optimized CSPE-0.1CeF3 membrane enables the achievement of Li metal batteries with high endurability and stability, from the kinetically favorable Li/Li symmetric cells with long-term cycling over 8000 h. The highly reversible Li/LiFePO4 cells exhibit a capacity retention of 109.2 mAh·g−1 after 1000 cycles at 1 C, corresponding to a low capacity fading rate of 0.026% per cycle. The conversion-type all-solid-state Li/CSPE-0.1CeF3/FeF3 cells show a high reversible capacity of 201.9 mAh·g−1 after long-term 600 cycles and of 231.1 mAh·g−1 at an ultra-high rate of 5 C. [ABSTRACT FROM AUTHOR]

Background: Forkhead box M1 (FOXM1) is a member of the Forkhead box (Fox) transcription factor family. It regulates cell mitosis, cell proliferation, and genome stability. However, the relationship between the expression of FOXM1 and the levels of m6a modification, immune infiltration, glycolysis, and ketone body metabolism in HCC has yet to be fully elucidated. Methods: Transcriptome and somatic mutation profiles of HCC were downloaded from the TCGA database. Somatic mutations were analyzed by maftools R package and visualized in oncoplots. GO, KEGG and GSEA function enrichment was performed on FOXM1 co-expression using R. We used Cox regression and machine learning algorithms (CIBERSORT, LASSO, random forest, and SVM-RFE) to study the prognostic value of FOXM1 and immune infiltrating characteristic immune cells in HCC. The relationship between FOXM1 and m6A modification, glycolysis, and ketone body metabolism were analyzed by RNA-seq and CHIP-seq. The competing endogenous RNA (ceRNA) network construction relies on the multiMiR R package, ENCORI, and miRNET platforms. Results: FOXM1 is highly expressed in HCC and is associated with a poorer prognosis. At the same time, the expression level of FOXM1 is significantly related to the T, N, and stage. Subsequently, based on the machine learning strategies, we found that the infiltration level of T follicular helper cells (Tfh) was a risk factor affecting the prognosis of HCC patients. The high infiltration of Tfh was significantly related to the poor overall survival rate of HCC. Besides, the CHIP-seq demonstrated that FOXM1 regulates m6a modification by binding to the promoter of IGF2BP3 and affects the glycolytic process by initiating the transcription of HK2 and PKM in HCC. A ceRNA network was successfully obtained, including FOXM1 - has-miR-125-5p – DANCR/MIR4435-2HG ceRNA network related to the prognosis of HCC. Conclusion: Our study implicates that the aberrant infiltration of Tfh associated with FOXM1 is a crucial prognostic factor for HCC patients. FOXM1 regulates genes related to m6a modification and glycolysis at the transcriptional level. Furthermore, the specific ceRNA network can be used as a potential therapeutic target for HCC. [ABSTRACT FROM AUTHOR]

Triple‐negative breast cancer (TNBC) is an aggressive breast cancer subtype, which has poor prognosis due to the lack of effective targeted drugs. KPT‐330, an inhibitor of the nuclear export protein CRM‐1, has been widely used in clinical medicine. Y219, a novel proteasome inhibitor designed by our group, shows superior efficacy, reduced toxicity, and reduced off‐target effects as compared to the proteasome inhibitor bortezomib. In this study, we investigated the synergistic effect of KPT‐330 and Y219 against TNBC cells, as well as the underlying mechanisms. We report that combination treatment with KPT‐330 and Y219 synergistically inhibited the viability of TNBC cells in vitro and in vivo. Further analysis revealed that the combined use of KPT‐330 and Y219 induced G2‐M phase arrest and apoptosis in TNBC cells, and attenuated nuclear factor kappa B (NF‐κB) signaling by facilitating nuclear localization of IκB‐α. Collectively, these results suggest that the combined use of KPT‐330 and Y219 may be an effective therapeutic strategy for the treatment of TNBC. [ABSTRACT FROM AUTHOR]

Solid‐state fluoride ion batteries (SSFIBs) are anion‐shuttle‐driven and alkali‐metal‐free emerging energy storage systems, and have the advantages of low cost, high safety, and energy density. However, the current major challenges of SSFIBs or quasi‐SSFIBs are the lack of high‐conductivity fluoride electrolytes and the difficulty of mild‐temperature operation of full cells. Here, a 2D fluoride conductor (KSn2F5) synthesized by mechanochemical method is employed as the compatible solid electrolyte with a high F‐ion conductivity of 10−4 S cm−1 at 60 °C. The high concentration and frequent hopping of charge carriers in F‐vacancy‐rich KSn2F5 contribute to the higher ionic conductivity compared to most reported fluoride structures. Integrating this layered electrolyte with high‐voltage CuF2 cathode and Sn/SnF2 anode, a highly reversible cycling of conversion‐type quasi‐SSFIBs with a discharge capacity of 150 mAh g−1 for at least 70 cycles at 60 °C is achieved. The interface engineering aided by tetra‐n‐butylammonium fluoride salt facilitates the F‐ion transfer between cathode and electrolyte and fluorination/defluorination conversion mechanism of CuF2 cathode with optimized multiphase and nanodomain distributions. [ABSTRACT FROM AUTHOR]

Introduction: Brachiaria humidicola, a tropical grass, could release root exudates with biological nitrification inhibition (BNI) capacity and reduce soil nitrous oxide (N2O) emissions from grasslands. However, evidence of the reduction effect in situ in tropical grasslands in China is lacking. Methods: To evaluate the potential effects of B. humidicola on soil N2O emissions, a 2-year (2015-2017) field experiment was established in a Latosol and included eight treatments, consisting of two pastures, non-native B. humidicola and a native grass, Eremochloa ophiuroide, with four nitrogen (N) application rates. The annual urea application rates were 0, 150, 300, and 450 kg N ha-1. Results: The average 2-year E. ophiuroides biomass with and without N fertilization were 9.07-11.45 and 7.34 t ha-1, respectively, and corresponding values for B. humidicola increased to 31.97-39.07 and 29.54 t ha-1, respectively. The N-use efficiencies under E. ophiuroide and B. humidicola cultivation were 9.3-12.0 and 35.5-39.4%, respectively. Annual N2O emissions in the E. ophiuroides and B. humidicola fields were 1.37 and 2.83 kg N2O-N ha-1, respectively, under no N fertilization, and 1.54-3.46 and 4.30-7.19 kg N2O-N ha-1, respectively, under N fertilization. Discussions: According to the results, B. humidicola cultivation increased soil N2O emissions, especially under N fertilization. This is because B. humidicola exhibited the more effective stimulation effect on N2O production via denitrification primarily due to increased soil organic carbon and exudates than the inhibition effect on N2O production via autotrophic nitrification. Annual yield-scaled N2O emissions in the B. humidicola treatment were 93.02-183.12 mg N2O-N kg-1 biomass, which were significantly lower than those in the E. ophiuroides treatment. Overall, our results suggest that cultivation of the non-native grass, B. humidicola with BNI capacity, increased soil N2O emissions, while decreasing yield-scaled N2O emissions, when compared with native grass cultivation. [ABSTRACT FROM AUTHOR]

A simple and sensitive method using in vivo microdialysis coupled with UPLC–MS/MS was established to evaluate the pharmacokinetics of Shuang Hu tincture (SHZTN). Xevo TQ‐S was used to analyze the active ingredients of mesaconitine, hypaconitine, 4‐hydroxycinnamic acid, ferulic acid and N‐(2, 3‐dimethyl phenyl)‐2‐ aminobenzoic acid of SHZTN. Samples were prepared using a methanol precipitation method and the internal standards lannaconitine and p‐hydroxybenzoic acid were added. The method validation was conducted according to the guidelines of the Pharmacopoeia of China. A good linear range was obtained in the range of 1–2,000 ng/ml. The intra‐day and inter‐day precisions were less than 14.7%, and the accuracy range of all the analytes was −10.5–9.3%. The recovery of each analyte was over 95.5%, and matrix effects can be neglected. After a single dose of 20 mg/kg SHZTN, the area under the curve and peak concentration of the five active ingredients were significantly increased by transdermal compared with oral administration, which indicated the high bioavailability of SHZTN. The time to peak concentration of all compounds was <3.4 h, and the half‐life was <15.4 h, which indicated that the five compounds have the best absorption and rapid elimination. The method was successfully developed and applied to the pharmacokinetic study of SHZTN. [ABSTRACT FROM AUTHOR]

Background This study investigated the effect of nucleos(t)ide analogue (NUC) treatment on hepatitis B virus (HBV) DNA integration and hepatocyte clonal expansion, both of which are implicated in hepatocellular carcinoma (HCC) in chronic hepatitis B. Methods Twenty-eight patients receiving NUCs (11 lamivudine, 7 telbivudine, 10 entecavir) were included. All had liver biopsies at baseline and year 1, and 7 had a third biopsy at year 10. HBV DNA integration and hepatocyte clone size were assessed by inverse polymerase chain reaction. Results All patients had detectable HBV integration at baseline, with a median integration frequency of 1.01 × 109 per liver and hepatocyte clone size of 2.41 × 105. Neither integration frequency nor hepatocyte clone size correlated with age and HBV virologic parameters. After 1 year of treatment, HBV integration was still detectable in all patients, with a median of 5.74 × 108 integration per liver (0.22 log reduction; P =.008) and hepatocyte clone size of 1.22 × 105 (0.40 log reduction; P =.002). HBV integration remained detectable at year 10 of treatment, with a median integration frequency of 4.84 × 107 integration per liver (0.93 log reduction from baseline) and hepatocyte clone size of 2.55 × 104 (1.02 log reduction from baseline). From baseline through year 1 to year 10, there was a decreasing trend in both integration frequency and hepatocyte clone size (P =.066 and.018, respectively). Conclusions NUCs reduced both HBV DNA integration and hepatocyte clonal expansion, suggesting another alternative pathway besides direct viral suppression to reduce HCC risk. Our findings supported the notion for a long-term NUC treatment to prevent HCC. [ABSTRACT FROM AUTHOR]

The garnet‐type solid‐state Li‐metal batteries are promising to develop into the high‐energy‐density system when coupled with the high‐capacity conversion reaction cathodes. However, the high interfacial resistance and poor contact between garnet electrolyte and Li anode are still a challenge. Here, an alloyable viscous fluid strategy is proposed for Li/garnet interface welding to enable highly reversible fluoride conversion solid‐state batteries. The super‐assembled phenide polymer with liquid metal property can serve as "oily" interlayer to in situ construct an ionic/electronic mixed conduction network by thermal and electrochemical lithiation. The resultant healing effect of contact voids between garnet and Li enables a dramatic reduction of interfacial resistance to 6 Ω cm2. The confinement and compaction of conversion products by garnet electrolyte endow the FeF3 based batteries with long‐cycling and high‐rate performance (520 and 330 mAh g−1 at 0.2 and 2 C respectively). This ceramic configuration also endows the CuF2 conversion battery with much better rechargeability (instead as widely known primary battery). [ABSTRACT FROM AUTHOR]

The RNA‐dependent RNA polymerase (RdRp) of influenza virus, consisting of subunits of PA, PB1, and PB2 proteins, is responsible for viral mRNA transcription and vRNA replication. Cap‐dependent endonuclease (CEN) exists in PA subunit of RdRp and mediates the critical "cap‐snatching" step of viral RNA transcription, which is considered as a promising anti‐influenza target. In this manuscript, a series of novel compounds were designed, synthesized, and biologically investigated as CEN inhibitors. The cellular activities of the target compounds against influenza A/H1N1 virus were investigated and the structure–activity relationship (SAR) was summarized. The results showed that some compounds were active against influenza A/H1N1 virus with IC50 values of less than 100 μM. The microsomal metabolic stabilities were carried out in human, monkey, and rat species, and the results showed that the active ingredients of compounds 32 and 40 were stable enough to be in vivo investigated. The in vivo pharmacokinetic results showed that compound 32 had acceptable biological parameters for both ig and iv administrations. Then the in vivo toxicity study of compound 32 with the doses of 100 and 50 mg/kg BID was performed in BALB/C mice. No obvious toxicity of compound 32 was observed during the experiment. Finally, the in vivo efficacy study of compound 32 in BALB/C mice showed that it was effective in alleviating influenza symptoms and showed a significant pharmacodynamic dose dependence. These results indicated that compound 32 was a promising candidate for further development. [ABSTRACT FROM AUTHOR]

Previous studies have indicated that influenza vaccination reduces the development of lung cancer. However, the protective effects of influenza vaccination on primary liver cancer in patients with chronic kidney disease (CKD) are unclear. This cohort study identified 12,985 patients aged at least 55 years who had received a diagnosis of CKD between 1 January 2001 and 31 December 2012 from the National Health Insurance Research Database of Taiwan. The patients were classified according to vaccination status. Propensity score matching was used to reduce selection bias. Cox proportional hazards regression analysis was used to evaluate the correlation between influenza vaccination and primary liver cancer in patients with CKD. The prevalence of primary liver cancer was lower in patients with CKD who had received an influenza vaccine (adjusted hazard ratio: 0.45, 95% confidence interval [CI]: 0.35–0.58, p < 0.001). The protective effects were observed regardless of sex, age, and comorbidities. Moreover, dose-dependent protective effects were observed. In the subgroup analysis, where the patients were classified by the number of vaccinations received, the adjusted hazard ratios for 1, 2–3, and ≥4 vaccinations were 0.86 (95% CI: 0.63–1.17), 0.45 (95% CI: 0.31–0.63), and 0.21 (95% CI: 0.14–0.33), respectively. In conclusion, influenza vaccination was associated with a lower incidence of liver cancer in patients with CKD. [ABSTRACT FROM AUTHOR]

Background: Necroptosis is a recently discovered form of cell death that plays an important role in the occurrence and development of colon adenocarcinoma (COAD). Our study aimed to construct a risk score model to predict the prognosis of patients with COAD based on necroptosis-related genes. Methods: The gene expression data of COAD and normal colon samples were obtained from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to calculate the risk score based on prognostic necroptosis-related differentially expressed genes (DEGs). Based on the risk score, patients were classified into high- and low-risk groups. Then, nomogram models were built based on the risk score and clinicopathological features. Otherwise, the model was verified in the Gene Expression Omnibus (GEO) database. Additionally, the tumor microenvironment (TME) and the level of immune infiltration were evaluated by “ESTIMATE” and single-sample gene set enrichment analysis (ssGSEA). Functional enrichment analysis was carried out to explore the potential mechanism of necroptosis in COAD. Finally, the effect of necroptosis on colon cancer cells was explored through CCK8 and transwell assays. The expression of necroptosis-related genes in colon tissues and cells treated with necroptotic inducers (TNFa) and inhibitors (NEC-1) was evaluated by quantitative real-time polymerase chain reaction (qRT-PCR). Results: The risk score was an independent prognostic risk factor in COAD. The predictive value of the nomogram based on the risk score and clinicopathological features was superior to TNM staging. The effectiveness of the model was well validated in GSE152430. Immune and stromal scores were significantly elevated in the high-risk group. Moreover, necroptosis may influence the prognosis of COAD via influencing the cancer immune response. In in-vitro experiments, the inhibition of necroptosis can promote proliferation and invasion ability. Finally, the differential expression of necroptosis-related genes in 16 paired colon tissues and colon cancer cells was found. Conclusion: A novel necroptosis-related gene signature for forecasting the prognosis of COAD has been constructed, which possesses favorable predictive ability and offers ideas for the necroptosis-associated development of COAD. [ABSTRACT FROM AUTHOR]

PANoptosis is a newly-discovered cell death pathway that involves crosstalk and co-ordination between pyroptosis, apoptosis, and necroptosis processes. However, the roles of PANoptosis-related genes (PRGs) in prognosis and immune landscape of colon cancer remain widely unknown. Here, we performed a bioinformatics analysis of expression data of nineteen PRGs identified from previous studies and clinical data of colon cancer patients obtained from TCGA and GEO databases. Colon cancer cases were divided into two PRG clusters, and prognosis-related differentially expressed genes (PRDEGs) were identified. The patient data were then separated into two corresponding distinct gene clusters, and the relationship between the risk score, patient prognosis, and immune landscape was analyzed. The identified PRGs and gene clusters correlated with patient survival and immune system and cancer-related biological processes and pathways. A prognosis signature based on seven genes was identified, and patients were divided into high-risk and lowrisk groups based on the calculated risk score. A nomogram model for prediction of patient survival was also developed based on the risk score and other clinical features. Accordingly, the high-risk group showed worse prognosis, and the risk score was related to immune cell abundance, cancer stem cell (CSC) index, checkpoint expression, and response to immunotherapy and chemotherapeutic drugs. Results of quantitative real-time polymerase chain reaction (qRT-PCR) showed that LGR5 and VSIG4 were differentially expressed between normal and colon cancer samples. In conclusion, we demonstrated the potential of PANoptosis-based molecular clustering and prognostic signatures for prediction of patient survival and tumor microenvironment (TME) in colon cancer. Our findings may improve our understanding of the role of PANoptosis in colon cancer, and enable the development of more effective treatment strategies. [ABSTRACT FROM AUTHOR]

Estimation of the amino acid content in maize leaves is helpful for improving maize yield estimation and nitrogen use efficiency. Hyperspectral imaging can be used to obtain the physiological and biochemical parameters of maize leaves with the advantages of being rapid, non-destructive, and high throughput. This study aims to estimate the multiple amino acid contents in maize leaves using hyperspectral imaging data. Two nitrogen (N) fertilizer experiments were carried out to obtain the hyperspectral images of fresh maize leaves. The partial least squares regression (PLSR) method was used to build the estimation models of various amino acid contents by using the reflectance of all bands, sensitive band range, and sensitive bands. The models were then validated with the independent dataset. The results showed that (1) the spectral reflectance of most amino acids was more sensitive in the range of 400–717.08 nm than other bands. The estimation accuracy was better by using the reflectance of the sensitive band range than that of all bands; (2) the sensitive bands of most amino acids were in the ranges of 505.39–605 nm and 651–714 nm; and (3) among the 24 amino acids, the estimation models of the b-aminobutyric acid, ornithine, citrulline, methionine, and histidine achieved higher accuracy than those of other amino acids, with the R2, relative root mean square error (RE), and relative percent deviation (RPD) of the measured and estimated value of testing samples in the range of 0.84– 0.96, 8.79%–19.77%, and 2.58–5.18, respectively. This study can provide a non-destructive and rapid diagnostic method for genetic sensitive analysis and variety improvement of maize. [ABSTRACT FROM AUTHOR]

Patients with type 2 diabetes mellitus (T2DM) have a higher risk of chronic kidney disease (CKD) due to vascular complications and chronic inflammation. T2DM contributes to a higher risk of mortality and morbidity related to influenza. In Taiwan, influenza vaccination is recommended for patients with T2DM. A previous meta-analysis reported the efficacy of influenza vaccination in reducing hospitalization and mortality in patients with diabetes; however, the renal protective effect of the vaccine remains unclear. This study evaluated whether influenza vaccination could reduce the incidence of CKD and dialysis in patients with T2DM. The study cohort included all patients aged ≥55 years who were diagnosed as having T2DM between 1 January 2000 and 31 December 2012, by using data from Taiwan's National Health Insurance Research Database. Each patient was followed up with to assess factors associated with CKD. A time-dependent Cox proportional hazard regression model after adjustment for potential confounders was used to calculate the hazard ratio (HR) of CKD in the vaccinated and unvaccinated patients. The study population comprised 48,017 eligible patients with DM; 23,839 (49.7%) received influenza vaccination and the remaining 24,178 (50.3%) did not. The adjusted HRs (aHRs) for CKD/dialysis decreased in the vaccinated patients compared with the unvaccinated patients (influenza season, noninfluenza season, and all seasons: aHRs: 0.47/0.47, 0.48/0.49, and 0.48/0.48, respectively, all p < 0.0001). We observed similar protective effects against CKD during the influenza and noninfluenza seasons. Regardless of comorbidities or drug use, influenza vaccination was an independent protective factor. Furthermore, aHRs for CKD/dialysis were 0.71 (0.65–0.77)/0.77 (0.68–0.87), 0.57 (0.52–0.61)/0.69 (0.56–0.70), and 0.30 (0.28–0.33)/0.28 (0.24–0.31) in the patients who received 1, 2–3, and ≥4 vaccinations during the follow-up period, respectively. This population-based cohort study demonstrated that influenza vaccination exerts a dose-dependent and synergistic protective effect against CKD in the patients with T2DM with associated risk factors. [ABSTRACT FROM AUTHOR]

The risk of stroke in patients with gout is high. The effect of vaccines in lowering the stroke risk in patients with gout remains unclear. We retrospectively analyzed 23,949 patients with gout (age ≥ 55 years) from the National Health Insurance Research Database over a 12-year period. The patients were divided into vaccinated (n = 11,649) and unvaccinated groups (n = 12,300). Overall, the vaccinated group had significantly lower risks of all stroke, hemorrhagic stroke, and ischemic stroke than the unvaccinated group (adjusted hazard ratio [aHR], 0.59 and 95% confidence interval [CI], 0.55–0.63; aHR, 0.60 and 95% CI, 0.49–0.73; and aHR, 0.60 and 95% CI, 0.55–0.65, respectively). The association appeared to be dose-dependent for both hemorrhagic and ischemic stroke (hemorrhagic stroke: aHR, 0.81 and 95% CI, 0.61–1.08; aHR, 0.80 and 95% CI, 0.62–1.02; and aHR, 0.37 and 95% CI, 0.28–0.48; ischemic stroke: aHR, 0.83 and 95% CI, 0.74–0.94; aHR, 0.73 and 95% CI, 0.65–0.81; and aHR, 0.42 and 95% CI, 0.38–0.47 for patients vaccinated 1, 2 or 3, and ≥4 times, respectively, during the follow-up period). Patients with a history of atrial fibrillation did not have a lower risk of hemorrhagic stroke even after receiving four vaccinations (aHR, 0.59; 95% CI, 0.25–1.38). Influenza vaccination was associated with a lower risk of all stroke in people with gout, and the association appeared to be dose-dependent. [ABSTRACT FROM AUTHOR]

In the latest video coding standard, namely Versatile Video Coding (VVC), more directional intra modes and reference lines have been utilized to improve prediction efficiency. However, complex content still cannot be predicted well with only the adjacent reference samples. Although nonlocal prediction has been proposed to further improve the prediction efficiency in existing algorithms, explicit signalling or matching error potentially limits the coding efficiency. To address these issues, we propose a joint local and nonlocal progressive prediction scheme, targeting at improving nonlocal prediction accuracy without additional signalling. Specifically, template matching based prediction (TMP) is conducted firstly to derive an initial nonlocal predictor. Based on the first prediction and previously decoded reconstruction information, a local template, including inner textures and neighboring reconstruction, is carefully designed. With the local template involved in nonlocal matching process, a more accurate nonlocal predictor can be found progressively in the second prediction. Finally, the coefficients from the two predictions are fused and transmitted in bitstreams. In this way, more accurate nonlocal predictor can be derived implicitly with local information instead of being explicitly signalled. Experimental results on the reference software VTM-9.0 of VVC show that the method achieves 1.02% BD-Rate reduction for natural sequences and 2.31% BD-Rate reduction for screen content videos under all intra (AI) configuration. [ABSTRACT FROM AUTHOR]

Realizing the rapid measurement of coal moisture content (MC) is of great significance. However, existing measurement methods are time-consuming and damage the original properties of the samples. To address these concerns, a coal MC intelligent measurement system is designed in this study that integrates microwave spectrum analysis and the distance-weighted k-nearest neighbor (DW-kNN) algorithm to realize rapid and non-destructive measurement of coal MC. Specifically, the measurement system is built using portable microwave analysis equipment, which can efficiently collect the microwave signals of coal. To improve the cleanliness of modeling data, an iterative clipping method based on Mahalanobis distance (MD-ICM) is used to detect and eliminate outliers. Based on multiple microwave frequency bands, various machine learning methods are evaluated, and it is found that coal MC measurement using broad frequency signals of 8.05–12.01 GHz yields the best results. Experiments are also carried out on coals from different regions to examine the regional robustness of the proposed method. The results of on-site testing with 27 additional samples show that the method based on the combination of microwave spectrum analysis and DW-kNN has a potential application prospect in the rapid measurement of coal MC. [ABSTRACT FROM AUTHOR]

Simple Summary: The risk of lung cancer occurrence among patients with chronic kidney disease (CKD) is significantly higher than patients with normal renal function. Moreover, the long-term outcomes of CKD patients with lung cancer are poor. We conducted the present nationwide population based study to assess the association between the risk of lung cancer and influenza vaccination. The results showed that among CKD patients, potentially risk reduction of lung cancer was observed after influenza vaccination. In addition, the potentially protective effect of influenza vaccination on lung cancer risk reduction appeared to be dose dependent. The findings of present study provided the additional effect of influenza vaccination among patients with CKD. Chronic kidney disease (CKD) is significantly associated with lung cancer incidence. The aim of this study was to elucidate whether influenza vaccination reduces the incidence of lung cancer in patients with CKD. This cohort study enrolled patients with a record of CKD diagnosis from 2000 to 2012 in Taiwan's National Health Insurance Research Database. Included patients were divided into vaccinated and unvaccinated groups. In total 12,985 patients with CKD were enrolled. Among these patients, 5495 were vaccinated and 7490 were unvaccinated. The risk of lung cancer was significantly lower in the influenza vaccination group after adjusting for age, sex, dialysis status, lung diseases, comorbidities, level of urbanization, and monthly income (adjusted hazard ratio (HR): 0.50, 95% confidence interval (CI; 0.38–0.65), p < 0.05). Lower risk of lung cancer was observed in both sexes, all age groups, dialysis status and co-existed lung diseases. The association between the risk of lung cancer and vaccination appeared to be dose-dependent (adjusted HRs: 0.91 (0.66–1.25), 0.49 (0.34–0.71), and 0.25 (0.17–0.38) for patients who received 1, 2 or 3, and ≥4 vaccinations during the follow-up period, respectively). In conclusion, Influenza vaccination decreased the risk of lung cancer in patients diagnosed with CKD. This potentially protective effect against lung cancer appeared to be dose dependent. [ABSTRACT FROM AUTHOR]

Radiotherapy has been widely applied for breast cancer treatment in the clinic, while improving the radiation sensitivity of tumors and protecting normal tissues from radiation damage has drawn considerable attention. In this study, we reported a biomimetic multifunctional nanozyme (BSA@CeO/Fe2+), which can be used as a radiosensitizer for breast cancer treatment. It was demonstrated that BSA@CeO/Fe2+ presented a pH dependent multiple enzyme like activity that enhances the hydroxyl radical level by cascade catalytic reactions in a tumor microenvironment to obtain a desirable tumor-suppression rate (83.07%). Moreover, BSA@CeO/Fe2+ was also proved to reduce reactive oxygen species levels in normal cells. Additionally, BSA@CeO/Fe2+ nanozymes showed no obvious toxicity by routine blood examination and blood biochemistry assays. Therefore, this work provided a promising strategy for nanocatalytic tumor therapy by rationally designing biomimetic nanozymes with multienzymatic activities for achieving high radiotherapy efficacy and excellent biosafety simultaneously. [ABSTRACT FROM AUTHOR]