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Introduction: For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed to further improve the accuracy and efficiency of HER2 amplification status detection with a deep learning model, and apply the model to predict the efficacy of neoadjuvant therapy. Methods: We combined Next-Generation Sequencing (NGS) data and IHC staining images of 606 breast cancer patients and developed a Vision Transformer (ViT) deep learning model to identify the amplification of HER2 through these IHC staining images. This model was then applied to predict the efficacy of neoadjuvant therapy in 399 HER2-positive breast cancer patients. Results: The NGS data of 606 patients were split into training (N = 404), validation (N = 101), and testing (N = 101) sets. The top 3 genes with highest mutation frequency were TP53, ERBB2 and PIK3CA. With the NGS results as deep learning model labels, the accuracy of our ViT model was 93.1% for HER2 amplification recognition. The misidentifications was likely due to the heterogeneity of HER2 expression in cancer tissues. For predicting the efficacy of neoadjuvant therapy, receiver operating characteristic (ROC) curves were plotted, and the combination of image recognition result and clinical pathological features yielded an area under the curve (AUC) value of 0.855 in the training set and 0.841 in the testing set. Conclusions: Our study provided a method of HER2 status recognition based on IHC images, improving the efficiency and accuracy of HER2 status assessment, and can be used for predicting the efficacy of anti-HER2 targeted neoadjuvant therapy. We intend our deep learning model to assist pathologists in HER2 amplification recognition. [ABSTRACT FROM AUTHOR]

The current artificial intelligence (AI) infrastructure widely employs remote direct memory access (RDMA) protocol for high-performance communication in networks, utilizing Reliable Connection (RC)-based Queue Pairs (QP) to ensure end-to-end correct and ordered data transmission. However, as the scale of AI infrastructure continues to expand, this RC-based QP communication mechanism faces deficiencies in scalability and is prone to congestion, resulting in degraded network transfer performance. In this paper, we propose an optimized RDMA QP communication mechanism to address scalability and congestion issues in hyper-scale AI infrastructure networks. Firstly, we replace RC-based QPs with Reliable Datagram (RD)-based QPs and propose a new reliable mechanism to address scalability problems, eliminating the need for repetitive QP establishment by AI processes during external communication. Additionally, to mitigate congestion caused by a single path, we implement multipath data transmission by introducing a new unordered reception method in the network software stack. Through experiments and simulation tests, the optimized RDMA QP communication in large-scale AI infrastructure exhibits exceptional scalability and significantly reduces the occurrence of congestion, resulting in an overall network performance improvement of over 15%. [ABSTRACT FROM AUTHOR]

Background: Obesity increases the risk of papillary thyroid carcinoma (PTC) and lymph node metastasis (LNM), possibly via modulation of the tumor immunological microenvironment. Materials and Methods: The STROCSS guideline was followed to conduct a retrospective cohort study. Binary logistic regression analysis with odds ratios (OR) was performed to assess the association between tumor-infiltrating lymphocytes (TILs), obesity, and LNM. Using The Cancer Genome Atlas (TCGA) data, we examined the relationship between immune cell subsets and obesity-regulating molecules in thyroid cancer tissues. The Cox regression risk model was used to analyze the prognosis of thyroid cancer. Results: After adjusting for confounding factors, our findings revealed that overweight and obesity were associated with a decrease in TIL infiltration (OR 0.876, p = 0.005 and OR 0.795, p = 0.001, respectively). Furthermore, these conditions were observed to be correlated with increased likelihood of LNM (OR 1.134, p = 0.005 and OR 1.307, p < 0.001, respectively). On the contrary, TIL infiltration was inversely associated with LNM (OR 0.868, p < 0.001). When controlling for TIL infiltration as the sole variable, the combination of obesity and TIL infiltration did not independently predict LNM (adjusted OR 1.442, p = 0.113). However, obesity alone was found to elevate the likelihood of LNM (adjusted OR 1.539, p = 0.02). Additionally, adiponectin (a crucial adipokine) was reduced in obesity and demonstrated a negative correlation with the abundance of infiltrated dendritic cells and regulatory T cells, as evidenced by TCGA data analysis. Furthermore, ADIPOR2 expression negatively correlated with LNM and positively associated with unfavorable prognosis in PTC, with a hazard ratio of 0.480 (p = 0.007). Conclusions: TIL infiltration may affect obesity-associated PTC LNM. Obesity may affect LNM and result in poor prognosis through ADIPOR2 regulation of antitumor immune cells. [ABSTRACT FROM AUTHOR]

Purpose: To develop a contrastive language-image pretraining (CLIP) model based on transfer learning and combined with self-attention mechanism to predict the tumor-stroma ratio (TSR) in pancreatic ductal adenocarcinoma on preoperative enhanced CT images, in order to understand the biological characteristics of tumors for risk stratification and guiding feature fusion during artificial intelligence-based model representation. Material and methods: This retrospective study collected a total of 207 PDAC patients from three hospitals. TSR assessments were performed on surgical specimens by pathologists and divided into high TSR and low TSR groups. This study developed one novel CLIP-adapter model that integrates the CLIP paradigm with a self-attention mechanism for better utilizing features from multi-phase imaging, thereby enhancing the accuracy and reliability of tumor-stroma ratio predictions. Additionally, clinical variables, traditional radiomics model and deep learning models (ResNet50, ResNet101, ViT_Base_32, ViT_Base_16) were constructed for comparison. Results: The models showed significant efficacy in predicting TSR in PDAC. The performance of the CLIP-adapter model based on multi-phase feature fusion was superior to that based on any single phase (arterial or venous phase). The CLIP-adapter model outperformed traditional radiomics models and deep learning models, with CLIP-adapter_ViT_Base_32 performing the best, achieving the highest AUC (0.978) and accuracy (0.921) in the test set. Kaplan–Meier survival analysis showed longer overall survival in patients with low TSR compared to those with high TSR. Conclusion: The CLIP-adapter model designed in this study provides a safe and accurate method for predicting the TSR in PDAC. The feature fusion module based on multi-modal (image and text) and multi-phase (arterial and venous phase) significantly improves model performance. [ABSTRACT FROM AUTHOR]

Antioxidant capacity is an important indicator for evaluating the growth and developmental quality of rice. This study has guiding significance for the cultivation of high-nutrient-value varieties. To investigate the molecular mechanisms underlying the antioxidant characteristics of rice grains after the filling stage, Yangzinuo 1 (YZN1) was used as the experimental material, and grains collected at five different time points (7 days apart) after the filling stage were used for transcriptome sequencing. Through weighted gene coexpression network analysis (WGCNA), a coexpression network of gene weights related to antioxidant characteristics was constructed. LOC_Os10g39140, LOC_Os10g38276, and LOC_Os05g45740 were identified from the 2 modules showing the highest correlations with the target traits. GO functional annotation showed that target modules were enriched in pathways related to phenylalanine, flavonoids, and other related pathways, such as GO:0006558, GO:0006559, GO:0009812, and GO:0009813. Correlation analysis with metabolites revealed that differentially expressed genes were significantly enriched in pathways related to antioxidant characteristics and energy metabolism processes, such as glycolysis/gluconeogenesis and flavonoid biosynthesis. The core genes identified in this study were found to be highly correlated with antioxidant characteristics and enriched in pathways related to metabolic and energy pathways and molecular activities. These results provide an effective dataset supporting breeding targeting functional rice characteristics. [ABSTRACT FROM AUTHOR]

Water permeability of reinforced concrete is essential for transportation of ingress ions inside concrete structures. The coupling effect of permeability and loading presents a challenge for the experimental simulation of water-permeate reinforced concrete subjected to tension. This renders the development of the model based on dimensionless analysis, using a series of experimental tests from an innovative experimental system that allows simultaneous measurement of permeability and crack width. The experiments focused on both ordinary concrete and high strength concrete under tension. The relationship between permeability and variables such as deformation, diameter of rebars, tensile load, and crack width under tension was formulated through multiple regression analysis using the testing data. The load to deformation characteristics determines the permeability of the concrete under tension. The proposed model accounts for the influence of continuous loading on permeability, as demonstrated by the robust analysis and proposed yield effective point. The robust analysis demonstrates that the diameter of the rebar, load, and crack width exert minimal influence on the permeability of concrete at lower significance levels. However, permeability variations become pronounced from 0.5 threshold, with significant changes observed between 0.5 and 0.9 thresholds. The findings indicate a differential impact of the variables on the permeability of concrete under tension. The yield-effective points delineate the relationship between the rebar diameter, load, and crack-width on the permeability of concrete with a threshold of 0.5, 0.5, and 0.58, respectively. At a threshold of 0.78, higher permeability will occur in the concrete, attributed to the prevalence of deformation. This deformation highlights the parameters with the most significant influence on the permeability of concrete under tension. The robust analysis and yield effective point derivative are useful parameters to measure concrete permeability and evaluate the behavior of the permeability model under tension. [ABSTRACT FROM AUTHOR]

This paper details with a color image encryption algorithm based on bit-plane permutation and dynamic Deoxyribonucleic acid (DNA) technology (CIEA-BPD) is proposed by using Logistic map. The proposed scheme is using Logistic map for generating permutation sequence to shuffle the color bit planes of three components and masking matrices combined with DNA technology to diffuse the pixel value of the color image. Through classical security analysis, CIEA-BPD can withstand different attacks. Experimental results verify that CIEA-BPD can efficiently encrypt a random-like cipher-image with a high degree of security. [ABSTRACT FROM AUTHOR]

The development of non-platinum group metal (non-PGM) and efficient multifunctional electrocatalysts for oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER) with high activity and stability remains a great challenge. Herein, by in-situ transforming silver manganese composite oxide heterointerface into boosted Mott-Schottky heterointerface through a facile carbon reduction strategy, a nanorod-like silver/manganese oxide with superior multifunctional catalytic activities for ORR, OER and HER and stability was obtained. The nanorod-like silver/manganese oxide with Mott-Schottky heterointerface (designated as Ag/Mn3O4) exhibits an ORR half-wave potential of 0.831 V (vs. RHE) in 0.1 M KOH, an OER overpotential of 338 mV and a HER overpotential of 177 mV at the current density of 10 mA·cm−2 in 1 M KOH, contributing to its noble-metal benchmarks comparable performance in aqueous aluminum-air (Al-air) battery and laboratorial overall water splitting electrolytic cell. Moreover, in-situ electrochemical Raman and synchrotron radiation spectroscopic measurements were conducted to further illustrate the catalytic mechanism of Ag/Mn3O4 Mott-Schottky heterointerface towards various electrocatalytic reactions. At the heterointerface, the Ag phase serves as the electron donor and the active phase for ORR and HER, while the Mn3O4 phase serves as the electron acceptor and the active phase for OER, respectively. This work deepens the understanding of the Mott-Schottky effect on electrocatalysis and fills in the gap in fundamental physical principles that are behind measured electrocatalytic activity, which offers substantial implications for the rational design of cost-effective multifunctional electrocatalysts with Mott-Schottky effect. [ABSTRACT FROM AUTHOR]

Background: The approval of selumetinib in patients with neurofibromatosis type 1(NF1) and inoperable plexiform neurofibromas (PN) has reshaped the landscape of clinical management of the disease, and further comprehensive evaluation of the drug's efficacy and safety is needed. Methods: Original articles reporting on the efficacy and safety of elumetinib in patients with NF1 were comprehensively searched in the Pubmed database, Embase database, Cochrane Library, and Web of Science database and screened for inclusion of studies that met the criteria. We pooled the objective response rate (ORR), disease control rate (DCR), disease progression rate (DPR), and the rate of improvement in PN-related complications using meta-analysis. The incidence of drug-related adverse events was also statistically analyzed. Results: This study included 10 clinical trials involving 268 patients. The pooled ORR was 68.0% (95% CI 58.0–77.3%), the DCR was 96.8% (95% CI 90.8–99.7%) and the DPR was only 1.4% (95% CI 0–4.3%). The pooled improvement rate was 75.3% (95% CI 56.2–90.9%) for pain and 77.8% (95% CI 63.1–92.5%) for motor disorders. Most adverse events were mild, with the most common being gastrointestinal reactions (diarrhea: 62.5%; vomiting: 54.5%). Conclusion: Our study demonstrates that selumetinib is effective in patients with NF1 and PN, significantly improving the serious complications associated with PN as well as having tolerable toxicities. Our findings help to increase clinicians' confidence in applying selumetinib and promote the clinical adoption and benefit of the new drug. [ABSTRACT FROM AUTHOR]

Mental disorders affect many different groups around the world, and disadvantaged groups are often more severely affected. Neighbourhood green spaces (GS) can improve mental health, especially in disadvantaged groups. Many countries address social inequality and inequity through GS interventions. However, current evidence shows inconsistencies, which may result from the study site, research design, socio-demographically diverse samples, inclusivity considerations, and the different metrics used to quantify GS exposure and mental health benefits. Few conceptual models explain how neighbourhood greenery can act as a structural intervention. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method and retrieved 5559 documents from eight databases to examine whether neighbourhood GS can modify mental health associations in disadvantaged groups. We found that neighbourhood GS had substantial protective effects on the mental health of disadvantaged groups. However, disadvantaged people are more influenced by GS quality than by other GS exposures, such as GS usage, distance, and accessibility. Improvements in subjective well-being were most pronounced in terms of mental health outcomes. Mechanistically, neighbourhood GS improves mental health mainly through increased social cohesion and, green visibility, and young people receive further benefits from physical activity (PA). These findings offer a comprehensive understanding of the associations and mechanisms between neighbourhood GS and the mental health of disadvantaged groups, addressing health equities that are induced by the unfair distribution of GS, and thus promoting health-oriented environmental planning and policies. [ABSTRACT FROM AUTHOR]

Background: The clinical manifestations of nonclassical 11beta-hydroxylase deficiency are very similar to those of non-classical 21-hydroxylase deficiency. For this study, we investigated the relationship between the clinical and molecular features of congenital adrenal hyperplasia caused by 11beta-hydroxylase deficiency and reviewed the related literature, which are expected to provide assistance for the clinical diagnosis and analysis of congenital adrenal hyperplasia. Methods: Clinical data for 10 Chinese patients diagnosed with congenital adrenal hyperplasia in our hospital from 2018 to 2022 were retrospectively analyzed. We examined the effects of gene mutations on protease activity and constructed three-dimensional structure prediction models of proteins. Results: We describe 10 patients with 11beta-hydroxylase gene mutations (n = 5, 46,XY; n = 5, 46,XX), with 10 novel mutations were reported. Female patients received treatment at an early stage, with an average age of 2.08 ± 1.66 years, whereas male patients received treatment significantly later, at an average age of 9.77 ± 3.62 years. The most common CYP11B1 pathogenic variant in the Chinese population was found to be c.1360C > T. All mutations lead to spatial conformational changes that affect protein stability. Conclusions: Our study found that there was no significant correlation between each specific mutation and the severity of clinical manifestations. Different patients with the same gene pathogenic variant may have mild or severe clinical manifestations. The correlation between genotype and phenotype needs further study. Three-dimensional protein simulations may provide additional support for the physiopathological mechanism of genetic mutations. [ABSTRACT FROM AUTHOR]

Propylene carbonate (PC)-based electrolytes have exhibited significant advantages in boosting the low-temperature discharging of graphite-based Li-ion batteries. However, it is still unclear whether they can improve the charging property and suppress lithium plating. Studying this topic is challenging due to the problem of electrochemical compatibility. To overcome this issue, we introduced graphite with phase defects. The results show that the pouch-type full batteries using PC-based electrolyte exhibit steady performance over 500 cycles and can be reversibly charged over 30 times at −20 °C with an average Coulombic efficiency of 99.95%, while the corresponding value for the conventional ethylene carbonate (EC)-based electrolyte sample is only 31.20%. This indicates that the use of PC-based electrolyte significantly suppresses lithium plating during low-temperature charging. We further demonstrate that the improved performance is mainly attributed to the unique solvation structure, where more PF 6 − anions participate in solvation, leading to the formation of a stable F-rich solid state electrolyte interface on the graphite surface and a lower reduction tendency of Li+ ions. This work inspires new ideas for the design of PC-based electrolytes for low-temperature charging and fast-charging batteries. [ABSTRACT FROM AUTHOR]

Background: Aberrant DNA methylation is one of the major epigenetic alterations in neuroblastoma. Objective: Exploring the prognostic significance of methylation driver genes in neuroblastoma could help to comprehensively assess patient prognosis. Methods: After identifying methylation driver genes (MDGs), we used the LASSO algorithm and stepwise Cox regression to construct methylation driver gene-related risk score (MDGRS), and evaluated its predictive performance by multiple methods. By combining risk grouping and MDGRS grouping, we developed a new prognostic stratification strategy and explored the intrinsic differences between the different groupings. Results: We identified 44 stably expressed MDGs in neuroblastoma. MDGRS showed superior predictive performance in both internal and external cohorts and was strongly correlated with immune-related scores. MDGRS can be an independent prognostic factor for neuroblastoma, and we constructed the nomogram to facilitate clinical application. Based on the new prognostic stratification strategy, we divided the patients into three groups and found significant differences in overall prognosis, clinical characteristics, and immune infiltration between the different subgroups. Conclusion: MDGRS was an accurate and promising tool to facilitate comprehensive pre-treatment assessment. And the new prognostic stratification strategy could be helpful for clinical decision making. [ABSTRACT FROM AUTHOR]

To express the opinions of decision-makers, q-rung orthopair hesitant fuzzy sets (q-ROHFSs) have been employed extensively. Therefore, it is necessary to construct q-rung orthopair hesitant fuzzy preference relations (q-ROHFPRs) as a crucial decision-making tool for decision-makers. The goal of this paper aims to define a new consistency and consensus approach for solving q-ROHFPR group decision-making (GDM) problems. To do this, we first state the definitions of q-ROHFPRs and additive consistent q-ROHFPRs based on q-ROHFSs, an additive consistency index and acceptable additive consistent q-ROHFPRs. Second, based on minimizing the deviation, we establish an acceptable goal programming model for unacceptable additive consistent q-ROHFPRs. Third, an iterative algorithm is created for achieving acceptable consistency and reaching a rational consensus. The degree of rational consensus among individual q-ROHFPRs is quantified by a distance-based consensus index. Afterward, a non-linear programming model is formulated to derive the priority vector of alternatives, which are q-rung orthopair hesitant fuzzy numbers (q-ROHFNs). Based on this model, a GDM model for q-ROHFPRs is then developed. To demonstrate the validity and utility of the proposed GDM model, a case study on the risk assessment of hypertension is provided. The finding of sensitivity and comparison analyses supports the feasibility and efficacy of the suggested approach. [ABSTRACT FROM AUTHOR]

In this work, the changes of microstructure and strength of Al–7Si alloys after introducing trace multicomponent AlCrNiTi alloy were studied. The addition contents of AlCrNiTi alloys to the Al–7Si-based alloy were 0.3, 0.6, 0.9 and 1.2 wt% (marked as S1, S2, S3, S4, S5 alloy), respectively. According to the results, the microstructure of Al–7Si alloy was obviously refined with the increase of adding AlCrNiTi concentration. When the introduction concentration of AlCrNiTi alloy was 0.9 wt%, the α-Al was significantly refined from coarse dendrites to equiaxed crystals, and its grain size and secondary dendrite arm spacing (SDAS) were reduced by 72.4% and 33.8%, respectively. Additionally, the size of Si phases was also decreased sharply and the roundness was increased from 0.29 to 0.45. Moreover, it was observed that the nano-sized Si phases with the size of 370 nm, bulk Al3Ni phase and AlCrNiTi particles precipitated during solidification. With the addition of AlCrNiTi modifier, the nucleation undercooling of Si and α-Al phases of Al–7Si alloys was decreased by 2.5 °C and 5.3 °C, respectively. With the modification and refinement of the microstructure in Al–7Si alloy, the mechanical properties have been significantly improved. Compared with the modifier-free S1 alloy, the elongation value (El) of S4 alloy enhanced by 36.7% from ~ 7.9 to ~ 10.8%, and the ultimate tensile strength (UTS) is increased by 12.1% from ~ 173 to ~ 194 MPa. [ABSTRACT FROM AUTHOR]

Introduction: LUAD (Lung adenocarcinoma), the most common subtype of lung carcinoma and one of the highest incidences and mortality cancers in the world remains still a substantial treatment challenge. Ivermectin, an avermectin derivative, has been traditionally used as an antiparasitic agent in human and veterinary medicine practice during the last few decades. Though ivermectin has been shown to be effective against a variety of cancers, however, there is few available data reporting the antitumor effects of ivermectin in LUAD. Methods: The effect of ivermectin on cell viability and proliferative ability of LUAD cells was evaluated using CCK-8 and colony formation assay. Apoptosis rate and autophagy flux were detected using flow cytometry based on PI/Annexin V staining and confocal laser scanning microscope based on LC3-GFP/RFP puncta, respectively. Western blotting experiment was conducted to verify the results of changes in apoptosis and autophagy. LUAD-TCGA and GEO databases were used to analyse the expression and predictive value of PAK1 in LUAD patients. Xenograft model and immumohistochemical staining were used for verification of the inhibitor effect of ivermectin in vivo. Results: Ivermectin treatment strikingly impeded the colony formation, and the viability of the cell, along with cell proliferation, and caused the apoptosis and enhanced autophagy flux in LUAD cells. In addition, ivermectin-induced nonprotective autophagy was confirmed by treating LUAD cells with 3-MA, an autophagy inhibitor. Mechanistically, we found that ivermectin inhibited PAK1 protein expression in LUAD cells and we confirmed that overexpression of PAK1 substantially inhibited ivermectin-induced autophagy in LUAD cells. Based on TCGA and GEO databases, PAK1 was highly expressed in LUAD tissues as compared with normal tissues. Furthermore, LUAD patients with high PAK1 level have poor overall survival. Finally, in vivo experiments revealed that ivermectin efficiently suppressed the cellular growth of LUAD among nude mice. Conclusion: This study not only revealed the mechanism of ivermectin inhibited the growth of LUAD but also supported an important theoretical basis for the development of ivermectin during the therapy for LUAD. [ABSTRACT FROM AUTHOR]

3D concrete printing has the potential to replace shotcrete for construction of linings of tunnels in hard rock. The shear strength of the interface between rock and printed concrete is vital, especially at super-early ages. However, traditional methods for testing the shear strength of the interface, e.g., the direct shear test, are time-consuming and result in a high variability for fast-hardening printed concrete. In this paper, a new fast bond shear test is proposed. Each test can be completed in 1 min, with another 2 min for preparing the next test. The influence of the matrix composition, the age of the printed matrices, and the interface roughness of the artificial rock substrate on the shear strength of the interface was experimentally studied. The tests were conducted at the age of the matrices at the 1st, the 4th, the 8th, the 16th, the 32nd, and the 64th min after its final setting. A dimensionless formula was established to calculate the shear strength, accounting for the age of the printed matrices, the interface roughness, and the shear failure modes. It was validated by comparing the calculated results and the experimental results of one group of samples. [ABSTRACT FROM AUTHOR]

Objective: This study aims to compare the feasibility and effectiveness of automatic deep learning network and radiomics models in differentiating low tumor stroma ratio (TSR) from high TSR in pancreatic ductal adenocarcinoma (PDAC). Methods: A retrospective analysis was conducted on a total of 207 PDAC patients from three centers (training cohort: n = 160; test cohort: n = 47). TSR was assessed on hematoxylin and eosin-stained specimens by experienced pathologists and divided as low TSR and high TSR. Deep learning and radiomics models were developed including ShuffulNetV2, Xception, MobileNetV3, ResNet18, support vector machine (SVM), k-nearest neighbor (KNN), random forest (RF), and logistic regression (LR). Additionally, the clinical models were constructed through univariate and multivariate logistic regression. Kaplan–Meier survival analysis and log-rank tests were conducted to compare the overall survival time between different TSR groups. Results: To differentiate low TSR from high TSR, the deep learning models based on ShuffulNetV2, Xception, MobileNetV3, and ResNet18 achieved AUCs of 0.846, 0.924, 0.930, and 0.941, respectively, outperforming the radiomics models based on SVM, KNN, RF, and LR with AUCs of 0.739, 0.717, 0.763, and 0.756, respectively. Resnet 18 achieved the best predictive performance. The clinical model based on T stage alone performed worse than deep learning models and radiomics models. The survival analysis based on 142 of the 207 patients demonstrated that patients with low TSR had longer overall survival. Conclusions: Deep learning models demonstrate feasibility and superiority over radiomics in differentiating TSR in PDAC. The tumor stroma ratio in the PDAC microenvironment plays a significant role in determining prognosis. Critical relevance statement: The objective was to compare the feasibility and effectiveness of automatic deep learning networks and radiomics models in identifying the tumor-stroma ratio in pancreatic ductal adenocarcinoma. Our findings demonstrate deep learning models exhibited superior performance compared to traditional radiomics models. Key points: • Deep learning demonstrates better performance than radiomics in differentiating tumor-stroma ratio in pancreatic ductal adenocarcinoma. • The tumor-stroma ratio in the pancreatic ductal adenocarcinoma microenvironment plays a protective role in prognosis. • Preoperative prediction of tumor-stroma ratio contributes to clinical decision-making and guiding precise medicine. [ABSTRACT FROM AUTHOR]

N‑Acetyl‑d‑neuraminic acid (Neu5Ac) is the crucial compound for the chemical synthesis of antiflu medicine Zanamivir. Chemoenzymatic synthesis of Neu5Ac involves N-acetyl-d-glucosamine 2-epimerase (AGE)-catalyzed epimerization of N-acetyl-d-glucosamine (GlcNAc) to N-acetyl-d-mannosamine (ManNAc), and aldolase-catalyzed condensation between ManNAc and pyruvate. Host optimization plays an important role in the whole-cell biotransformation of value-added compounds. In this study, via single-plasmid biotransformation system, we showed that the AGE gene BT0453, cloned from human gut microorganism Bacteroides thetaiotaomicron VPI-5482, showed the highest biotransformation yield among the AGE genes tested; and there is no clear Neu5Ac yield difference between the BT0453 coupled with one aldolase coding nanA gene and two nanA genes. Next, Escherichia coli chromosomal genes involved in substrate degradation, product exportation and pH change were deleted via recombineering and CRISPR/Cas9. With the final E. coli BL21(DE3) ΔnanA Δnag ΔpoxB as host, a significant 16.5% yield improvement was obtained. Furthermore, precursor (pyruvate) feeding resulted in 3.2% yield improvement, reaching 66.8% molar biotransformation. The result highlights the importance of host optimization, and set the stage for further metabolic engineering of whole-cell biotransformation of Neu5Ac. [ABSTRACT FROM AUTHOR]

Spinal ultrasonography has increasingly been used to image axial structures from the cervical to sacral region in recent years. In this work, we propose a comprehensive, systematic cervical scanning protocol that we refined as a route map, especially for beginners, to facilitate teaching, learning, diagnosis, and treatment in clinical pain practice. As a simple and clear tool to demonstrate the scanning protocol, the route map is delineated with rectangles, lines, and arrows. The rectangles represent the positions of the transducer, the arrows indicate route directions, and the lines show the routes of transducer movement. In this article, we describe cervical spinal ultrasonography to illustrate the route map interpretation, scanning protocol and target anatomical structures in detail. We believe that this comprehensive, clear, systematic, and portable route map will be beneficial for inexperienced pain clinicians and ultrasound beginners. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the low-threshold optical bistable absorption in an asymmetrical one-dimensional photonic crystal structure (1D-PhC) containing a Weyl semimetal (WSM) defect layer. Dirven by the strong third-order nonlinear effect of the WSM and the field enhancement of the defect mode, low-threshold bistable absorption is achieved in the terahertz band. After optimizing the parameters, the rising threshold intensity is 83.7817 MW/m2 and the falling threshold intensity is 49.39 MW/m2, which are lower than the threshold intensities of bistable absorption in the reported works. Meanwhile, we discuss the effects of Fermi level of WSM, incident angle, and the numbers of periods of the left and right 1D-PhCs on the bistable absorption. Our work would facilitate the design of high-performance all-optical switches, all-optical logics, and optical absorbers. [ABSTRACT FROM AUTHOR]

Leaves are the primary photosynthetic organs, providing essential substances for tree growth. It is important to obtain an anatomical understanding and regulatory network analysis of leaf development. Here, we studied leaf development in Populus Nanlin895 along a development gradient from the newly emerged leaf from the shoot apex to the sixth leaf (L1 to L6) using anatomical observations and RNA-seq analysis. It indicated that mesophyll cells possess obvious vascular, palisade, and spongy tissue with distinct intercellular spaces after L3. Additionally, vacuoles fuse while epidermal cells expand to form pavement cells. RNA-seq analysis indicated that genes highly expressed in L1 and L2 were related to cell division and differentiation, while those highly expressed in L3 were enriched in photosynthesis. Therefore, we selected L1 and L3 to integrate ATAC-seq and RNA-seq and identified 735 differentially expressed genes (DEGs) with changes in chromatin accessibility regions within their promoters, of which 87 were transcription factors (TFs), such as ABI3VP1, AP-EREBP, MYB, NAC, and GRF. Motif enrichment analysis revealed potential regulatory functions for the DEGs through upstream TFs including TCP, bZIP, HD-ZIP, Dof, BBR-BPC, and MYB. Overall, our research provides a potential molecular foundation for regulatory network exploration in leaf development during photosynthesis establishment. Key message: Anatomy and RNA-seq of Populus leaves revealed the crucial stage for establishing photosynthesis. Integrating ATAC-seq and RNA-seq identified differentially expressed genes and their potential upstream transcription factors in this stage. [ABSTRACT FROM AUTHOR]

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Understanding the genetic basis of rubber tree (Hevea brasiliensis) domestication is crucial for further improving natural rubber production to meet its increasing demand worldwide. Here we provide a high-quality H. brasiliensis genome assembly (1.58 Gb, contig N50 of 11.21 megabases), present a map of genome variations by resequencing 335 accessions and reveal domestication-related molecular signals and a major domestication trait, the higher number of laticifer rings. We further show that HbPSK5, encoding the small-peptide hormone phytosulfokine (PSK), is a key domestication gene and closely correlated with the major domestication trait. The transcriptional activation of HbPSK5 by myelocytomatosis (MYC) members links PSK signaling to jasmonates in regulating the laticifer differentiation in rubber tree. Heterologous overexpression of HbPSK5 in Russian dandelion (Taraxacum kok-saghyz) can increase rubber content by promoting laticifer formation. Our results provide an insight into target genes for improving rubber tree and accelerating the domestication of other rubber-producing plants. Understanding the genetic basis of rubber tree domestication is critical for improving natural rubber production. Here, the authors assemble the genome of the rubber tree clone CATAS8-79 and conduct population and genetic association analyses to reveal the function of phytosulfokine in regulating number of laticifer rings. [ABSTRACT FROM AUTHOR]

Purpose: Cell death plays an important role in tumourigenesis and progression; nevertheless, the clinical significance of cell death-related genes in neuroblastoma remains incompletely understood. Methods: We separately constructed the corresponding risk scores for each of the eight cell death pathways separately and assessed their predictive performance. Through Cox regression analysis, these eight risk scores were integrated to obtain final cell death risk scores (CDRS). We evaluated the predictive performance of CDRS in multiple datasets and compared its accuracy with the clinical characteristics of patients and some existing prognostic models for neuroblastoma. We then explored the differences in immune infiltration between the high and low CDRS groups, and the significance of CDRS on EFS and disease progression. Results: All eight risk scores have high predictive accuracy, with the Immunogenic-RS being the most accurate and the cuproptosis-RS the least accurate. Model genes are mainly enriched in a variety of cancer-related pathways and are closely related to the clinical characteristics. CDRS showed superior and robust predictive performance in multiple datasets and was more accurate than the clinical characteristics of patients and some existing prognostic models for neuroblastoma. High CDRS group featured distinct immune cold tumor profiles and may have poorer immune checkpoint inhibitor efficacy. CDRS had significance in predicting EFS and disease progression. Conclusion: We integrated risk scores associated with multiple cell death pathways to develop a high-performing and robust neuroblastoma signature. CDRS was a promising tool that may help with risk assessment and prediction of overall prognosis, and thus improve clinical outcomes. [ABSTRACT FROM AUTHOR]

Highlights: A non-corrosive and air-stable hydrated eutectic electrolyte is developed. The electrolyte is composed of aluminum perchlorate nonahydrate and methylurea. The unique solvation structure enables reversible deposition/stripping of Al. The Al-ion battery in this electrolyte shows good charge/discharge performance. Aluminum-ion batteries (AIBs) have been highlighted as a potential alternative to lithium-ion batteries for large-scale energy storage due to the abundant reserve, light weight, low cost, and good safety of Al. However, the development of AIBs faces challenges due to the usage of AlCl3-based ionic liquid electrolytes, which are expensive, corrosive, and sensitive to humidity. Here, we develop a low-cost, non-corrosive, and air-stable hydrated eutectic electrolyte composed of aluminum perchlorate nonahydrate and methylurea (MU) ligand. Through optimizing the molar ratio to achieve the unique solvation structure, the formed Al(ClO4)3·9H2O/MU hydrated deep eutectic electrolyte (AMHEE) with an average coordination number of 2.4 can facilely realize stable and reversible deposition/stripping of Al. When combining with vanadium oxide nanorods positive electrode, the Al-ion full battery delivers a high discharge capacity of 320 mAh g−1 with good capacity retention. The unique solvation structure with a low desolvation energy of the AMHEE enables Al3+ insertion/extraction during charge/discharge processes, which is evidenced by in situ synchrotron radiation X-ray diffraction. This work opens a new pathway of developing low-cost, safe, environmentally friendly and high-performance electrolytes for practical and sustainable AIBs. [ABSTRACT FROM AUTHOR]

Depression is a common cause of increased suicides worldwide, and studies have shown that the number of patients suffering from major depressive disorder (MDD) increased several-fold during the COVID-19 pandemic, highlighting the importance of disease detection and depression management, while increasing the need for effective diagnostic tools. In recent years, machine learning and deep learning methods based on electroencephalography (EEG) have achieved significant results in the field of automatic depression detection. However, most current studies have focused on a small number of EEG signal channels, and experimental data require special processing by professionals. In this study, 128 channels of EEG signals were simply filtered and 24-fold leave-one-out cross-validation experiments were performed using 2DCNN-LSTM classifier, support vector machine, K-nearest neighbor and decision tree. The current results show that the proposed 2DCNN-LSTM model has an average classification accuracy of 95.1% with an AUC of 0.98 for depression detection of 6-second participant EEG signals, and the model is much better than 72.05%, 79.7% and 79.49% for support vector machine, K nearest neighbor and decision tree. In addition, we found that the model achieved a 100% probability of correctly classifying the EEG signals of 300-second participants. [ABSTRACT FROM AUTHOR]

Ferroptosis is distinct from classic apoptotic cell death characterized by the accumulation of reactive oxygen species (ROS) and lipid peroxides on the cell membrane. Increasing findings have demonstrated that ferroptosis plays an important role in cancer development, but the exploration of ferroptosis in breast cancer is limited. In our study, we aimed to establish a ferroptosis activation-related model based on the differentially expressed genes between a group exhibiting high ferroptosis activation and a group exhibiting low ferroptosis activation. By using machine learning to establish the model, we verified the accuracy and efficiency of our model in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) set and gene expression omnibus (GEO) dataset. Additionally, our research innovatively utilized single-cell RNA sequencing data to systematically reveal the microenvironment in the high and low FeAS groups, which demonstrated differences between the two groups from comprehensive aspects, including the activation condition of transcription factors, cell pseudotime features, cell communication, immune infiltration, chemotherapy efficiency, and potential drug resistance. In conclusion, different ferroptosis activation levels play a vital role in influencing the outcome of breast cancer patients and altering the tumor microenvironment in different molecular aspects. By analyzing differences in ferroptosis activation levels, our risk model is characterized by a good prognostic capacity in assessing the outcome of breast cancer patients, and the risk score can be used to prompt clinical treatment to prevent potential drug resistance. By identifying the different tumor microenvironment landscapes between the high- and low-risk groups, our risk model provides molecular insight into ferroptosis in breast cancer patients. [ABSTRACT FROM AUTHOR]

Polypyrrole (PPy) is widely available and has excellent potential for removing fluoride. Current research on PPy for fluoride removal mainly focuses on low-pollution neutral solution systems, such as drinking water and groundwater. However, there are fewer systematic studies on defluorination in acidic wastewater. In this work, a highly efficient hydrous CeO2 polypyrrole nanocomposite (HCeO2@PPy) was prepared by in situ oxidative polymerization. The composites were characterized using XRD, SEM–EDS, FTIR, XPS, and point-of-zero charge (pzc) determination. The material was tested for its ability to remove fluoride from both simulated and industrial wastewater. The results showed that the adsorption capacity of HCeO2@PPy increased by 3 times to 43.6 mg/g when compared to PPy. The adsorbent was particularly effective in removing F− under acidic conditions. The Langmuir model was used to describe the adsorption process, and the maximum adsorption capacity was 80.93 mg/g. In competitive anion adsorption experiments, other ions had negligible effects on fluoride ion removal and the adsorbent had a strong affinity for F−. In addition, the adsorbent was able to achieve a removal efficiency of 71.7% in acidic wastewater. The main adsorption mechanism is attributed to ion exchange and electrostatic attraction. This study provides new insights for the development of efficient and stable fluoride removal materials in acidic fluoride wastewater with complex compositions. [ABSTRACT FROM AUTHOR]

In this paper we consider the Monge–Ampère type equations on compact almost Hermitian manifolds. We derive C∞ a priori estimates under the existence of an admissible C -subsolution. Finally, we obtain an existence result if there exists an admissible supersolution. [ABSTRACT FROM AUTHOR]

The flow structure in natural rivers may change due to the disturbance of vegetation, further affecting the transport of pollutants and sediment (Liu et al. 2020). In this paper, the random displacement model (RDM) is presented to study the material transport in the emergent vegetated flow by predicting the longitudinal dispersion coefficient (LDC), which plays an important role in the longitudinal transport of pollutants in natural rivers covered by emergent vegetation. RDM can be applied for the analysis of the vegetated flow provided that the velocity distribution and the turbulent diffusion coefficient distribution remain known. According to the experimental data on velocity and Reynolds stress, the flow field was divided into four sub-zones along the cross-sectional area where the transverse distribution of the longitudinal velocity and also transverse turbulent diffusion coefficient were determined. Moreover, the simulated results of the longitudinal dispersion coefficient were verified by using the previously measured data. In addition, the sensitivity analysis of RDM parameters was carried out. In comparison with the shear layer width and the velocity difference, the impact of vegetation zone width on the longitudinal dispersion coefficient was greater, but the model was fundamentally stable, further confirming that the analytical model can be reliable for predicting the longitudinal dispersion coefficient in the vegetated open-channel flow. Accurately estimating the longitudinal dispersion coefficient is useful for understanding the transport and fate of pollutants in river channels and, thereby, for exploring the sustainable development of the river ecological environment, as well as optimizing the planning and design of river course. [ABSTRACT FROM AUTHOR]

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Recombineering is a highly efficient DNA cloning and modification technique by using the recombinase-mediated homologous recombination. Selection/counterselection cassette is often used in chromosomal DNA or large episomal DNA manipulation, in which the selection marker is used for the first step cassette selection while deleting the target gene via allelic exchange, and the counterselection marker is used for the second step replacement of the cassette by the foreign DNA fragment. A variety of selection/counterselection cassettes are reported, however, the cassettes suffer from the shortcomings of the requirement of pre-engineered strain or specific culture medium. Herein, we report a novel S-tetR- PtetA-ccdB-aacC1-S selection/counterselection cassette that sidesteps the disadvantages. As a proof-of-concept, one-step gene cloning (0.7, 1.7, and 4.2 kb) and two-step Escherichia coli chromosomal gene knock-in (0.7 and 4.2 kb) were performed. The gene cloning and gene knock-in efficiencies are high up to 90%. The novel selection/counterselection cassette adds a powerful tool to the recombineering repertoire. [ABSTRACT FROM AUTHOR]

Floating vegetation occurs in various environments, such as artificial floating islands, wetlands, river courses, and lakes, which constitute an important part of the river landscape and ecological restoration. The vertical distribution of the streamwise velocity of the channel flow with floating vegetation is of the utmost importance, and therefore, it is the basis for research on bed erosion and pollutant transport. Laboratory experiments on an open-channel flow covered by floating vegetation with unanchored roots have shown a two-layer structure of the velocity profile and a rapid decrease in the Reynolds stress across the interface in the vegetation layer but gradual in the non-vegetation layer. The flow was divided into four subzones in a vertical direction according to the organized flow structure in the experiment as follows: (I) the uniform region deep within the non-vegetation layer, (II) the outer region in the non-vegetation layer, (III) the inner region in the vegetation layer, and (IV) the uniform region deep within the vegetation layer. An analytical model based on the momentum balance in each subzone was developed to predict the profiles of velocity and Reynolds stress. The predictions from analytical models agree well with those from laboratory studies of floating vegetation and lay the theoretical foundation for future studies on water eutrophication and the transport of pollutants, sediments, and algae. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communication is widely regarded as the key component of future 6G mobile communication systems. Through comparative analysis of some of the main existing technical routes of THz up-conversion and down-conversion in THz wireless communication systems, a novel ultra-wideband (UWB) fiber-THz-fiber seamlessly converged real-time architecture, which utilizes the commercially mature digital coherent optical module to realize ultrahigh-capacity THz real-time wireless communication, is proposed in this study. (1) The proposed architecture employs the dual-polarization photonic up-conversion technique for THz generation and hybrid optoelectronic down-conversion technique for THz reception to facilitate the seamless integration between optical fiber and THz communications. (2) Because of the limited bandwidth of optoelectronic devices, multidimensional modulation techniques are adopted for UWB THz signals to improve spectral efficiency and transmission capacity. (3) An intelligent nonlinear joint compensation technique based on the deep neural network, which can effectively improve the signal-to-noise ratio of the time-varying hybrid fiber-THz-fiber channel, is proposed. Based on the investigations of the aforementioned key techniques, we, for the first time, realize the photonics-assisted record-high 100/200 GbE real-time THz wireless transmission at 360–430 GHz band, the capacity of which is 10–20 times higher than that of 5G. The proposed fiber-THz-fiber architecture can realize the smooth conversion between high-speed THz and lightwave signals. Moreover, the architecture can significantly reduce the research difficulty and development cost, thereby considerably accelerating the commercialization of 6G THz technology by thoroughly reusing commercial digital coherent optical module (DCO) modules, which are compatible with the physical layer transmission protocols, such as IEEE 802.3 and ITU-T G.798. Finally, this study also introduces some potential directions of research and development for higher-capacity, longer-distance, and more-integrated fiber-THz-fiber seamless communication. [ABSTRACT FROM AUTHOR]

Boundary absorption intensity can affect the contaminant depletion capacity within rivers, and the process of spatial contaminant cloud expansion is complicated with the consideration of irreversible absorption boundaries at riverbanks. Nonuniformity of concentration distribution appears in spatial concentration distribution, especially in the transverse direction, which is caused by the absorption capacity difference between two riverbanks. A model for illustrating the performance of environmental dispersion with two irreversible absorption banks in 2D space is given in this work. Furthermore, the position of the maximum concentration distributions shifts within the transverse directions with the change of the absorption intensities at two boundaries. The overall absorption capacity would also be affected by the ratio of two absorption intensities at the left and right riverbanks. The residual mass is left with a greater variation in the two bank-absorption intensity ratios. A detailed analysis of the spatial concentration distribution and contaminant depletion capacity with two bank-absorption boundaries would contribute to the construction of a wetland for water treatment. With a certain absorption capacity in total, the transverse distribution of concentration gets more heterogeneous as the ratio deviates from 1gradually, and the transverse concentration distribution appears to be symmetric to the center (0.5W) when the ratios of absorption intensities at two stream-banks are in accord with β0 : β1 = β1 : β0. The novelty of this work is to provide the analytical solution of two-dimensional concentration distribution with the ratio of two stream-bank absorptions, furthermore, a linear fitting equation( P = 0.82 β 0 * β 0 * + β 1 * + 0.09 ) for crest position of transverse concentration distribution is given to show the shifting process of spatial contaminant cloud with the change of two stream-bank absorption ratios, and the correlation coefficients are all above 0.99, illustrating a good fit for the results. [ABSTRACT FROM AUTHOR]

Silkworm diseases caused by fungi infection occur frequently in sericulture and brought huge economic loss to sericulture. However, on the other hand, some fungi such as Beauveria bassiana, as an important entomological fungus, play an important role in biological control of insect pests. Here, two fungal pathogens causing yellow muscardine were isolated from the silkworm and named as SZY1 and SZY2. These two strains showed almost the same conidial morphology which were smooth, near-spherical, spherical, or ovoid and 2.7 ± 0.6 µm × 2.5 ± 0.9 µm in size, and the hyphal growth rate was also similar. However, the conidia production of SZY2 was almost twice as many as that of SZY1. The complete ribosomal RNA gene was sequenced and analyzed. As a result, the gene sequences of internal transcript space 1 (ITS1)-5.8S rRNA-internal transcript space 2 (ITS2) of SZY1 and SZY2 were identical in sequence and size, and for 18S rRNA, 28S rRNA, and intergenic spacer (IGS), the gene identity of SZY1 to SZY2 was 99%, 99%, and 98%, respectively. Results of phylogenetic analysis based on either ITS1-5.8S rRNA-ITS2 or 18S rRNA showed that both SZY1 and SZY2 were closely related to Beauveria bassiana. These results revealed that the pathogens of yellow muscardine SZY1 and SZY2 were identified as two different strains of Beauveria bassiana, which could provide diagnostic evidence for silkworm muscardine and was helpful for the research and development of novel Bombyx batryticatus and fungal biological insecticide. [ABSTRACT FROM AUTHOR]

Neuroblastoma is a childhood malignancy with high morbidity and mortality. We identified key biomarkers associated with neuroblastoma risk and prognosis. The gene modules most associated with neuroblastoma risk were derived by WGCNA. Modular genes were intersected with differentially expressed genes between patients with high-risk (HR) and non-high-risk (NHR) to obtain risk genes, and enrichment analysis was performed. After incorporating risk genes into Cox regression analysis, LASSO algorithm, and K-M survival analysis, key genes were identified and introduced into four external datasets for validation. We performed short time-series expression miner analysis and single-sample genome enrichment analysis. Finally, we evaluated the difference in DNA methylation levels to identify meaningful methylation marks. We identified 5 key genes (ANO6, CPNE2, DST, PLXNC1, SCN3A) for neuroblastoma risk and prognosis, which correlated closely with known neuroblastoma biomarkers. All key genes showed a progressive downregulation trend with increasing risk levels of neuroblastoma. The immune infiltration of 14 immune cells was significantly different between HR-NB and NHR-NB, and most immune cells were negatively correlated with key genes. Furthermore, the expression of ANO6, CPNE2, DST, and PLXNC1 was modified by DNA methylation. This study identified 5 key genes for neuroblastoma risk and prognosis that were potential biomarkers. [ABSTRACT FROM AUTHOR]

Highlights: Fe single atoms supported on porous carbon nanofiber are prepared by spatial confinement. The iron single atoms supported on porous nitrogen-doped carbon nanofibers (FeSAs-NCF) can promote the reversible conversion between aluminum polysulfides. The FeSAs-NCF can chemically anchor the polysulfides to suppress shuttle effect. Rechargeable aluminum–sulfur (Al–S) batteries have been considered as a highly potential energy storage system owing to the high theoretical capacity, good safety, abundant natural reserves, and low cost of Al and S. However, the research progress of Al–S batteries is limited by the slow kinetics and shuttle effect of soluble polysulfides intermediates. Herein, an interconnected free-standing interlayer of iron single atoms supported on porous nitrogen-doped carbon nanofibers (FeSAs-NCF) on the separator is developed and used as both catalyst and chemical barrier for Al–S batteries. The atomically dispersed iron active sites (Fe–N4) are clearly identified by aberration-corrected high-angle annular dark-field scanning transmission electron microscopy and X-ray absorption near-edge structure. The Al–S battery with the FeSAs-NCF shows an improved specific capacity of 780 mAh g−1 and enhanced cycle stability. As evidenced by experimental and theoretical results, the atomically dispersed iron active centers on the separator can chemically adsorb the polysulfides and accelerate reaction kinetics to inhibit the shuttle effect and promote the reversible conversion between aluminum polysulfides, thus improving the electrochemical performance of the Al–S battery. This work provides a new way that can not only promote the conversion of aluminum sulfides but also suppress the shuttle effect in Al–S batteries. [ABSTRACT FROM AUTHOR]

The effects of eugenol emulsion (EUG) on the browning of fresh-cut yam during storage and its inhibition mechanism were studied. The EUG treatment group had a significant anti-browning ability, and the 1.5% EUG treatment group had the best effect. During the whole storage period, the activities of peroxidase (POD) and phenylalanine ammonia-lyase (PAL) decreased significantly after 1.5% EUG treatment, especially on day 4, when the activity of POD and PAL was 3.2% and 23% of that of the control group, respectively. Molecular docking experiments showed that EUG inhibited PAL activity by binding to the active center of PAL, a key browning enzyme. A decrease in total phenol content was also observed. In addition, after EUG treatment, catalase (CAT) activity was significantly increased, preventing the accumulation of reactive oxygen species (ROS)-H2O2. EUG inhibited membrane lipid metabolism, 1.5% EUG delayed the emergence of lipoxygenase activity peak, and malondialdehyde (MDA) content decreased by 75.67% compared with the control on 4 d. In comparison with control, EUG increased the scavenging capacity of DPPH, ABTS, and iron-reducing antioxidant capacity (FRAP). The mechanism may be that EUG enhances antioxidant capacity, thereby reducing ROS-induced membrane lipid metabolism, therefore, lowering the synthesis and oxidation of phenolic compounds, and ultimately inhibiting browning. [ABSTRACT FROM AUTHOR]