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Abstract Dislocations in ceramics are increasingly recognized for their promising potential in applications such as toughening intrinsically brittle ceramics and tailoring functional properties. However, the atomistic simulation of dislocation plasticity in ceramics remains challenging due to the complex interatomic interactions characteristic of ceramics, which include a mix of ionic and covalent bonds, and highly distorted and extensive dislocation core structures within complex crystal structures. These complexities exceed the capabilities of empirical interatomic potentials. Therefore, constructing neural network potentials (NNPs) emerges as the optimal solution. Yet, creating a training dataset that includes dislocation structures proves difficult due to the complexity of their core configurations in ceramics and the computational demands of density functional theory for large atomic models containing dislocation cores. In this work, we propose a training dataset from properties that are easier to compute via high-throughput calculation. Using this dataset, we have successfully developed NNPs for dislocation plasticity in ceramics, specifically for three typical functional ceramics: ZnO, GaN, and SrTiO3. These NNPs effectively capture the nonstoichiometric and charged core structures and slip barriers of dislocations, as well as the long-range electrostatic interactions between charged dislocations. The effectiveness of this dataset was further validated by measuring the similarity and uncertainty across snapshots derived from large-scale simulations, alongside extensive validation across various properties. Utilizing the constructed NNPs, we examined dislocation plasticity in ceramics through nanopillar compression and nanoindentation, which demonstrated excellent agreement with experimental observations. This study provides an effective framework for constructing NNPs that enable the detailed atomistic modeling of dislocation plasticity, opening new avenues for exploring the plastic behavior of ceramics.

Abstract Background Despite significant strides in lung cancer immunotherapy, the response rates for Kirsten rat sarcoma viral oncogene homolog (KRAS)‐driven lung adenocarcinoma (LUAD) patients remain limited. Fibrinogen‐like protein 1 (FGL1) is a newly identified immune checkpoint target, and the study of related resistance mechanisms is crucial for improving the treatment outcomes of LUAD patients. This study aimed to elucidate the potential mechanism by which FGL1 regulates the tumor microenvironment in KRAS‐mutated cancer. Methods The expression levels of FGL1 and SET1 histone methyltransferase (SET1A) in lung cancer were assessed using public databases and clinical samples. Lentiviruses were constructed for transduction to overexpress or silence FGL1 in lung cancer cells and mouse models. The effects of FGL1 and Yes‐associated protein (Yap) on the immunoreactivity of cytotoxic T cells in tumor tissues were evaluated using immunofluorescence staining and flow cytometry. Chromatin immunoprecipitation and dual luciferase reporter assays were used to study the SET1A‐directed transcriptional program. Results Upregulation of FGL1 expression in KRAS‐mutated cancer was inversely correlated with the infiltration of CD8+ T cells. Mechanistically, KRAS activated extracellular signal‐regulated kinase 1/2 (ERK1/2), which subsequently phosphorylated SET1A and increased its stability and nuclear localization. SET1A‐mediated methylation of Yap led to Yap sequestration in the nucleus, thereby promoting Yap‐induced transcription of FGL1 and immune evasion in KRAS‐driven LUAD. Notably, dual blockade of programmed cell death‐1 (PD‐1) and FGL1 further increased the therapeutic efficacy of anti‐PD‐1 immunotherapy in LUAD patients. Conclusion FGL1 could be used as a diagnostic biomarker of KRAS‐mutated lung cancer, and targeting the Yap‐FGL1 axis could increase the efficacy of anti‐PD‐1 immunotherapy.

Abstract The interaction between lattice vibrations and electrons plays a key role in various aspects of condensed matter physics — including electron hydrodynamics, strange metal behavior, and high-temperature superconductivity. In this study, we present systematic investigations using Raman scattering and angle-resolved photoemission spectroscopy (ARPES) to examine the phononic and electronic subsystems of the topological superconductor candidate 2M-WS2. Raman scattering exhibits an anomalous nonmonotonic temperature dependence of phonon linewidths, indicative of strong phonon–electron scattering over phonon–phonon scattering. The ARPES results demonstrate pronounced dispersion anomalies (kinks) at multiple binding energies within both bulk and topological surface states, indicating a robust and mode-selective coupling between the electronic states and various phonon modes. These experimental findings align with previous calculations of the Eliashberg function, providing a deeper understanding of the highest superconducting transition temperature observed in 2M-WS2 (8.8 K) among all transition metal dichalcogenides as induced by electron–phonon coupling. Furthermore, our results may offer valuable insights into other properties of 2M-WS2 and guide the search for high-temperature topological superconductors.

Abstract Electron-electron correlations can lift the high degeneracies in strong correlated systems, resulting in various symmetry-broken states. Twisted monolayer-bilayer graphene (tMBG) is an especially rich system due to its low crystalline symmetry. Here, we report abundant electric-field tunable symmetry-broken states in tMBG. The ground state at half filling of the conduction flat band is spin- and valley-polarization dominated under positive and negative electric field, respectively, consistent with our theoretical calculations. In addition, we find a symmetry-broken Chern insulator emanating from 1.5 electrons per moiré unit with C = 3 emerges at high magnetic field in a negative electric field range. The C = 3 suggests that one and a half flavor-polarized Chern 2 bands within the same valley are filled, consistent with the valley-polarization-dominated half-filling state under negative electric field, while the fractional filling stems from a density-wave state held by enlarged unit cells containing two moiré units.

BackgroundCombining epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) with chemotherapy (ETC) offers more advantages for patients with EGFR-positive non-small cell lung cancer (NSCLC) than using EGFR TKIs alone (ET). However, whether this conclusion applies to patients with brain metastases (BM) remains controversial. This meta-analysis was performed to evaluate the benefits and risks of the two groups.MethodsSix databases were systematically searched for relevant literatures comparing ETC versus ET in treating EGFR-positive NSCLC patients with BM. The primary outcome assessed was overall survival (OS), while secondary outcomes included progression-free survival (PFS), and central nervous system (CNS)-PFS, responses, progression status and safety.ResultsSeven studies based on five randomized clinical trials with 550 patients were included. The ETC group exhibited better OS (hazard ratio [HR]: 0.64 [0.48, 0.87]), PFS (HR: 0.42 [0.34, 0.52]), and CNS-PFS (HR: 0.42 [0.31, 0.57]). The benefits in survival for OS, PFS, and CNS-PFS were validated in nearly all subgroups. Meanwhile, the overall objective response rate (ORR) (risk ratio [RR]: 1.25 [1.02, 1.52]) and CNS-ORR (RR: 1.19 [0.93, 1.51]) also tended to favor the ETC group. However, the addition of chemotherapy also brought about more grade 3-5/serious adverse events (AEs). The top five grade 3-5 AEs in the ETC group were alanine aminotransferase increase (11.25%), neutropenia (7.5%), nausea (7.5%), anorexia (5%), and diarrhea (5%).ConclusionsETC appears to be better than ET in treating EGFR-positive NSCLC patients with BM, with better OS, PFS, CNS-PFS, and responses. However, its poorer safety profile also needs to be taken into consideration.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024551073.

Unmanned aerial vehicle (UAV) mainly uses GPS (Global Positioning System) for positioning, but it is difficult to locate in areas where GPS signal is missing or being disturbed. Therefore, the relative positioning technology based on visual method is also widely used in UAV landing, but due to the influence of cross wind and the motion of the landing plane, the traditional visual landing sign and positioning method is prone to lose the positioning target at the end stage of the landing. Therefore, this article proposes a landing sign based on double-layer unique coding, which can realize continuous positioning in the horizontal direction and accurate positioning of large-scale changes in the vertical direction. Firstly, real-time image acquisition and image processing are carried out through the airborne camera. Based on the flight altitude and encoding extraction effect of the UAV, the red or blue channel component is extracted, and then the image is preprocessed, edge detection, line detection, coding grid extraction, etc. As long as any 5 × 5 small squares of the whole pattern can be extracted, the perspective-n-point algorithm is used to obtain the relative pose estimation between the UAV and the landing sign. Experiments show that the landing sign and recognition algorithm effectively improve the UAV landing reliability.

Hyperuricemia (HUA), recognized as the fourth “high” condition following hypertension, hyperlipidemia, and hyperglycemia, is a metabolic disorder that severely impairs renal function. Spike lavender essential oil (SLEO) exhibits substantial anti-inflammatory and antioxidant activities and can inhibit xanthine oxidase (XOD), suggesting its potential therapeutic potential against HUA. This of this study aimed to analyze the chemical constituents of SLEO with potential efficacy in treating HUA and to explore their mechanisms of action. Gas chromatography-mass spectrometry (GC–MS) combined with a greedy algorithm identified linalool, β-pinene, and β-caryophyllene as key active components of SLEO. Through network pharmacology “weight coefficient” method, the NOD-like signaling pathway emerged as a significant mechanism for SLEO in treating HUA. Investigating an in vitro uric acid (UA)-induced HK-2 cell model revealed that SLEO effectively inhibited the production of IL-1β and IL-18 in the supernatant of HK-2 cells compared to the NLRP3 (antagonist MCC950). Additionally, a HUA rat model demonstrated that SLEO administration significantly reduced hyperuricemia pathological indicators, such as UA, XOD, and blood urea nitrogen (BUN) levels, with renal histopathological sections showing a marked reduction in following SLEO treatment. Metabolomics and transcriptomics analyses further highlighted significant changes in differential metabolites such as arachidonic acid and glycine, as well as the regulation of differential genes such as pycard and PTGS2 in rats.Immunohistochemistry, Western blotting, molecular docking and in vitro XOD activity inhibition assays elucidated the active components mechanisms of SLEO in treating HUA and associated renal inflammation. The findings concluded that SLEO mitigates HUA and renal inflammation by modulating the arachidonic acid metabolic pathway and the NF-κB signaling pathway. Moreover, linalool, β-pinene and β-caryophyllene in SLEO were shown to reduce UA production and lower UA levels in vivo by inhibiting the TLR4/NF-κB/NLRP3 pathway, thereby alleviating HUA-induced renal injury.

Abstract In higher plants, mature male gametophytes have distinct apertures. After pollination, pollen grains germinate, and a pollen tube grows from the aperture to deliver sperm cells to the embryo sac, completing fertilization. In rice, the pollen aperture has a single-pore structure with a collar-like annulus and a plug-like operculum. A crucial step in aperture development is the formation of aperture plasma membrane protrusion (APMP) at the distal polar region of the microspore during the late tetrad stage. Previous studies identified OsINP1 and OsDAF1 as essential regulators of APMP and pollen aperture formation in rice, but their precise molecular mechanisms remain unclear. We demonstrate that the Poaceae-specific OsSRF8 gene, encoding a STRUBBELIG-receptor family 8 protein, is essential for pollen aperture formation in Oryza sativa. Mutants lacking functional OsSRF8 exhibit defects in APMP and pollen aperture formation, like loss-of-function OsINP1 mutants. OsSRF8 is specifically expressed during early anther development and initially diffusely distributed in the microsporocytes. At the tetrad stage, OsSRF8 is recruited by OsINP1 to the pre-aperture region through direct protein-protein interaction, promoting APMP formation. The OsSRF8-OsINP1 complex then recruits OsDAF1 to the APMP site to co-regulate annulus formation. Our findings provide insights into the mechanisms controlling pollen aperture formation in cereal species.

Abstract To address the issues of low accuracy and slow response speed in tea disease classification and identification, an improved YOLOv7 lightweight model was proposed in this study. The lightweight MobileNeXt was used as the backbone network to reduce computational load and enhance efficiency. Additionally, a dual-layer routing attention mechanism was introduced to enhance the model’s ability to capture crucial details and textures in disease images, thereby improving accuracy. The SIoU loss function was employed to mitigate missed and erroneous judgments, resulting in improved recognition amidst complex image backgrounds.The revised model achieved precision, recall, and average precision of 93.5%, 89.9%, and 92.1%, respectively, representing increases of 4.5%, 1.9%, and 2.6% over the original model. Furthermore, the model’s volum was reduced by 24.69M, the total param was reduced by 12.88M, while detection speed was increased by 24.41 frames per second. This enhanced model efficiently and accurately identifies tea disease types, offering the benefits of lower parameter count and faster detection, thereby establishing a robust foundation for tea disease monitoring and prevention efforts.

Abstract Background Surgery combined with radiotherapy substantially escalates the likelihood of encountering complications in early-stage cervical squamous cell carcinoma(ESCSCC). We aimed to investigate the feasibility of Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in ESCSCC and minimize the occurrence of adverse events associated with the treatment. Methods A dataset comprising MR images was obtained from 289 patients who underwent radical hysterectomy and pelvic lymph node dissection between January 2019 and April 2022. The dataset was randomly divided into two cohorts in a 4:1 ratio.The postoperative radiotherapy options were evaluated according to the Peter/Sedlis standard. We extracted clinical features, as well as intratumoral and peritumoral radiomic features, using the least absolute shrinkage and selection operator (LASSO) regression. We constructed the Clinical Signature (Clinic_Sig), Radiomics Signature (Rad_Sig) and the Deep Transformer Learning Signature (DTL_Sig). Additionally, we fused the Rad_Sig with the DTL_Sig to create the Deep Learning Radiomic Signature (DLR_Sig). We evaluated the prediction performance of the models using the Area Under the Curve (AUC), calibration curve, and Decision Curve Analysis (DCA). Results The DLR_Sig showed a high level of accuracy and predictive capability, as demonstrated by the area under the curve (AUC) of 0.98(95% CI: 0.97–0.99) for the training cohort and 0.79(95% CI: 0.67–0.90) for the test cohort. In addition, the Hosmer-Lemeshow test, which provided p-values of 0.87 for the training cohort and 0.15 for the test cohort, respectively, indicated a good fit. DeLong test showed that the predictive effectiveness of DLR_Sig was significantly better than that of the Clinic_Sig(P

The corrosion resistance of laser powder bed fusion (LPBF) 304L stainless steel (SS) in 3.5 wt% NaCl solution was evaluated at room temperature through potentiodynamic polarization and electrochemical impedance spectroscopy tests. For electropolished samples, annealing at 1200 °C slightly enhanced the corrosion resistance due to changes in crystal orientation and inclusion composition, and reduced residual strain. In contrast, annealing at 1050 °C significantly reduced the corrosion resistance mainly due to the disappearance of dislocation cells and the remained residual dislocations. Residual stress/strain and martensitic transformation induced by sandpaper grinding can also deteriorate the corrosion resistance. Only the as-received sample shows stable passivation regardless of the surface conditions.

Hyperplasia and migration of fibroblast-like synoviocytes (FLSs) are the key drivers in the pathogenesis of rheumatoid arthritis (RA) and joint destruction. Abundant Yes-associated protein (YAP), which is a powerful transcription co-activator for proliferative genes, was observed in the nucleus of inflammatory FLSs with unknown upstream mechanisms. Using Gene Expression Omnibus database analysis, it was found that Salvador homolog-1 (SAV1), the pivotal negative regulator of the Hippo-YAP pathway, was slightly downregulated in RA synovium. However, SAV1 protein expression is extremely reduced. Subsequently, it was revealed that SAV1 is phosphorylated, ubiquitinated, and degraded by interacting with an important serine-threonine kinase, G protein-coupled receptor (GPCR) kinase 2 (GRK2), which was predominately upregulated by GPCR activation induced by ligands such as prostaglandin E2 (PGE2) in RA. This process further contributes to the decreased phosphorylation, nuclear translocation, and transcriptional potency of YAP, and leads to aberrant FLSs proliferation. Genetic depletion of GRK2 or inhibition of GRK2 by paroxetine rescued SAV1 expression and restored YAP phosphorylation and finally inhibited RA FLSs proliferation and migration. Similarly, paroxetine treatment effectively reduced the abnormal proliferation of FLSs in a rat model of collagen-induced arthritis which was accompanied by a significant improvement in clinical manifestations. Collectively, these results elucidate the significance of GRK2 regulation of Hippo-YAP signaling in FLSs proliferation and migration and the potential application of GRK2 inhibition in the treatment of FLSs-driven joint destruction in RA.

Abstract Tissue engineering has demonstrated its efficacy in promoting tissue regeneration, and extensive research has explored its application in rotator cuff (RC) tears. However, there remains a paucity of research translating from bench to clinic. A key challenge in RC repair is the healing of tendon–bone interface (TBI), for which bioactive materials suitable for interface repair are still lacking. The umbilical cord (UC), which serves as a vital repository of bioactive components in nature, is emerging as an important source of tissue engineering materials. A minimally manipulated approach is used to fabricate UC scaffolds that retain a wealth of bioactive components and cytokines. The scaffold demonstrates the ability to modulate the TBI healing microenvironment by facilitating cell proliferation, migration, suppressing inflammation, and inducing chondrogenic differentiation. This foundation sets the stage for in vivo validation and clinical translation. Following implantation of UC scaffolds in the canine model, comprehensive assessments, including MRI and histological analysis confirm their efficacy in inducing TBI reconstruction. Encouraging short‐term clinical results further suggest the ability of UC scaffolds to effectively enhance RC repair. This investigation explores the mechanisms underlying the promotion of TBI repair by UC scaffolds, providing key insights for clinical application and translational research.

Indoor semivolatile organic compounds (SVOCs) pose a substantial threat to human health. However, identifying the sources of these emissions has been challenging owing to the scarcity of convenient and practical on-site methodologies. Herein, a novel method for source screening was proposed using aluminum silicate sampling strips to adsorb SVOCs from the surface air of indoor materials. The adsorbed SVOC levels indicate the emission intensity of these materials into indoor environments. Additionally, compact sampling strips can be readily fixed to any vertical surface using a static sticker, facilitating the characterization of various materials in practical settings. Laboratory-simulated experiments demonstrated the capability of the proposed method to differentiate between source and non-source materials within a 10-cm distance in the same space. In practical scenarios, the primary emission sources identified via this method exhibited a consistent correlation with the contents of the corresponding materials obtained from the traditional solvent-extraction method. As the adsorbed SVOCs were directly transferred to a GC–MS through thermal desorption instead of the solvent-extraction procedure, the proposed method demonstrated several-fold improvements in analytical sensitivity and efficiency. Using this versatile screening technique, some emerging and important SVOC species were identified within specific indoor materials. Eliminating these sources has been demonstrated as an effective approach to mitigate SVOC pollution. Overall, the proposed method offers a powerful tool for managing indoor pollutants and safeguarding human health.

Abstract Objective This work endeavored to examine the correlation between dietary choline intake and the odds of asthma, utilizing data from the National Health and Nutrition Examination Survey (NHANES). Methods Aggregated data from seven cycles (2005–2018) in the NHANES database were utilized. The independent variable was dietary choline intake, and the dependent variable was asthma. The weighted logistic regression method was used to construct a model reflecting the relationship between these two factors. This work employed stratified analysis without adjusting for confounding factors and subgroup analysis with adjusted confounding factors to mine the association between dietary choline intake and asthma. Additionally, restricted cubic spline analysis examined nonlinear associations of the two in age subgroups. Results Forty five thousand and seven hundreds ninety seven samples were included here. The model indicating the relationship between dietary choline intake and asthma was constructed (OR: 0.86, 95% CI: 0.79–0.93, p 30 kg/m2 (OR: 0.73, 95% CI: 0.60–0.89, p = 0.002). Conclusion Dietary choline intake was significantly inversely correlated with asthma prevalence, especially in adults and overweight/obese individuals, suggesting that increasing choline intake may reduce asthma risk. Further research is needed to explore this relationship and provide tailored dietary recommendations for different age and BMI groups to enhance asthma prevention and management.

In this work, a new supplementary formula was introduced to modify the Kerner model. This supplementary formula enable the Kerner model to predict the thermal expansion coefficient of multi-phase reinforced composites by normalization of the thermal expansion coefficient, bulk modulus, and shear modulus of the reinforcements. For comparison, the modified Kerner model as well as modified Schapery, the rule of mixtures, and Turner models were used to predict the thermal expansion coefficient of multi-phase reinforced composites 6092 Aluminum Alloy/silicon carbide/β-eucryptite. The results confirm the robustness of the modified Kerner model for predicting the thermal expansion coefficient of composites with multi-phase near-spherical inclusions. It may provide a fine selection to predict the thermal expansion coefficient of multi-phase reinforced metal matrix composites which cannot predict efficiently before.

Waste copper-containing paint residue (WCPR) represents a typical hazardous waste containing both toxic organic substances and toxic heavy metals, but there are few reports on the recycling of heavy metals. The recovery of Cu from WCPR by H2SO4 leaching–extraction–stripping has the advantages of eco-friendliness, simplicity of operation, and high value-added product. The results show that under the optimal conditions, the leaching rate of Cu in WCPR is 94.31% (18.02 g/L), while the extraction and stripping rates of Cu in the leaching solution are 99.46 and 95.32%, respectively. Due to the high concentration of Cu2+ with fewer impurities in the stripping solution, the stripping solution is heated, evaporated, cooled, and crystallized to successfully produce high-purity dark blue CuSO4 crystal, accomplishing the high-value recycling of Cu in WCPR. In addition, the leach residue of WCPR contains acrylic resin and SiO2, which can be used in cement kilns for incineration, thus realizing the overall recycling and utilization of WCPR. HIGHLIGHTS The process of Cu recovery from waste copper-containing paint residue was first proposed to regenerate CuSO4.; Using leaching–extraction–stripping to recover Cu has the advantages of eco-friendliness and high value-added product.; The stripping solution without impurities can be used directly to regenerate CuSO4.; The resulting residue with no environmental risk can be cement kiln incineration.; The process can eliminate Cu pollution and recover Cu resource.;

Pest infestations in tea gardens are one of the common issues encountered during tea cultivation. This study introduces an improved YOLOv8 network model for the detection of tea pests to facilitate the rapid and accurate identification of early-stage micro-pests, addressing challenges such as small datasets and the difficulty of extracting phenotypic features of target pests in tea pest detection. Based on the original YOLOv8 network framework, this study adopts the SIoU optimized loss function to enhance the model’s learning ability for pest samples. AKConv is introduced to replace certain network structures, enhancing feature extraction capabilities and reducing the number of model parameters. Vision Transformer with Bi-Level Routing Attention is embedded to provide the model with a more flexible computation allocation and improve its ability to capture target position information. Experimental results show that the improved YOLOv8 network achieves a detection accuracy of 98.16% for tea pest detection, which is a 2.62% improvement over the original YOLOv8 network. Compared with the YOLOv10, YOLOv9, YOLOv7, Faster RCNN, and SSD models, the improved YOLOv8 network has increased the mAP value by 3.12%, 4.34%, 5.44%, 16.54%, and 11.29%, respectively, enabling fast and accurate identification of early-stage micro pests in tea gardens. This study proposes an improved YOLOv8 network model based on deep learning for the detection of micro-pests in tea, providing a viable research method and significant reference for addressing the identification of micro-pests in tea. It offers an effective pathway for the high-quality development of Yunnan’s ecological tea industry and ensures the healthy growth of the tea industry.

China’s Yunnan Province, known for its tea plantations, faces significant challenges in smart pest management due to its ecologically intricate environment. To enable the intelligent monitoring of pests within tea plantations, this study introduces a novel image recognition algorithm, designated as YOLOv8n-WSE-pest. Taking into account the pest image data collected from organic tea gardens in Yunnan, this study utilizes the YOLOv8n network as a foundation and optimizes the original loss function using WIoU-v3 to achieve dynamic gradient allocation and improve the prediction accuracy. The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model’s complexity. The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. The research results demonstrate that compared to the original YOLOv8n model, the improved YOLOv8n-WSE-pest model shows increases in the precision, recall, mAP50, and F1 score by 3.12%, 5.65%, 2.18%, and 4.43%, respectively. In external validation, the mAP of the model outperforms other deep learning networks such as Faster-RCNN, SSD, and the original YOLOv8n, with improvements of 14.34%, 8.85%, and 2.18%, respectively. In summary, the intelligent tea garden pest identification model proposed in this study excels at precise the detection of key pests in tea plantations, enhancing the efficiency and accuracy of pest management through the application of advanced techniques in applied science.

The high tillage resistance of agricultural soil-engaging tools (TASTs) in farmland operations (e.g., tillage, sowing, crop management, and harvesting) increases fuel consumption and harmful gas emissions, which negatively affect the development of sustainable agriculture. Biomimetic methods are promising and effective technologies for reducing the TASTs and have been developed in the past few years. This review comprehensively summarizes the typical agricultural soil-engaging tools (ASETs) and their characteristics and presents existing biomimetic methods for decreasing TASTs. The introduction of TAST reduction was performed on aspects of tillage, sowing, crop management, and harvesting. The internal mechanisms and possible limitations of current biomimetic methods for various ASETs were investigated. The tillage resistance reduction rates of ASETs, as affected by various biomimetic methods, were quantitatively compared under different soil conditions with statistical analyses. Additionally, three future research directions were recommended in the review to further reduce TASTs and encourage the development of sustainable agriculture.

Abstract Cancer remains the leading cause of death around the world. In cancer treatment, over 50% of cancer patients receive radiotherapy alone or in multimodal combinations with other therapies. One of the adverse consequences after radiation exposure is the occurrence of radiation-induced tissue fibrosis (RIF), which is characterized by the abnormal activation of myofibroblasts and the excessive accumulation of extracellular matrix. This phenotype can manifest in multiple organs, such as lung, skin, liver and kidney. In-depth studies on the mechanisms of radiation-induced fibrosis have shown that a variety of extracellular signals such as immune cells and abnormal release of cytokines, and intracellular signals such as cGAS/STING, oxidative stress response, metabolic reprogramming and proteasome pathway activation are involved in the activation of myofibroblasts. Tissue fibrosis is extremely harmful to patients' health and requires early diagnosis. In addition to traditional serum markers, histologic and imaging tests, the diagnostic potential of nuclear medicine techniques is emerging. Anti-inflammatory and antioxidant therapies are the traditional treatments for radiation-induced fibrosis. Recently, some promising therapeutic strategies have emerged, such as stem cell therapy and targeted therapies. However, incomplete knowledge of the mechanisms hinders the treatment of this disease. Here, we also highlight the potential mechanistic, diagnostic and therapeutic directions of radiation-induced fibrosis.

Abstract Background Ovarian development is an important prerequisite and basis for animal reproduction. In many vertebrates, it is regulated by multiple genes and influenced by sex steroid hormones and environmental factors. However, relative information is limited in shellfish. To explore the biological functions and molecular mechanisms of mRNA and non-coding RNA that regulate ovarian development in Scapharca broughtonii, we performed whole transcriptome sequencing analysis on ovaries at three developmental stages. Furthermore, the biological processes involved in the differential expression of mRNA and ncRNA were analyzed. Results A total of 11,342 mRNAs, 6897 lncRNAs, 135 circRNAs, and 275 miRNAs were differentially expressed. By mapping the differentially expressed RNAs from the three developmental stages of Venn diagram, multiple groups of shared mRNAs and lncRNAs were found to be associated with ovarian development, with some mRNA and ncRNA functions associated with steroid hormone. In addition, we constructed and visualized the lncRNA/circRNA-miRNA-mRNA network based on ceRNA targeting relationships. Conclusions These findings may facilitate our further understanding the mRNA and ncRNAs roles in the regulation of shellfish reproduction.

Abstract Graphene has aroused great attention due to the intriguing properties associated with its low-energy Dirac Hamiltonian. When graphene is coupled with a correlated insulating substrate, electronic states that cannot be revealed in either individual layer may emerge in a synergistic manner. Here, we theoretically study the correlated and topological states in Coulomb-coupled and gate-tunable graphene-insulator heterostructures. By electrostatically aligning the electronic bands, charge carriers transferred between graphene and the insulator can yield a long-wavelength electronic crystal at the interface, exerting a superlattice Coulomb potential on graphene and generating topologically nontrivial subbands. This coupling can further boost electron-electron interaction effects in graphene, leading to a spontaneous bandgap formation at the Dirac point and interaction-enhanced Fermi velocity. Reciprocally, the electronic crystal at the interface is substantially stabilized with the help of cooperative interlayer Coulomb coupling. We propose a number of substrate candidates for graphene to experimentally demonstrate these effects.

Grading tea leaves efficiently in a natural environment is a crucial technological foundation for the automation of tea-picking robots. In this study, to solve the problems of dense distribution, limited feature-extraction ability, and false detection in the field of tea grading recognition, an improved YOLOv8n model for tea grading and counting recognition was proposed. Firstly, the SPD-Conv module was embedded into the backbone of the network model to enhance the deep feature-extraction ability of the target. Secondly, the Super-Token Vision Transformer was integrated to reduce the model’s attention to redundant information, thus improving its perception ability for tea. Subsequently, the loss function was improved to MPDIoU, which accelerated the convergence speed and optimized the performance. Finally, a classification-positioning counting function was added to achieve the purpose of classification counting. The experimental results showed that, compared to the original model, the precision, recall and average precision improved by 17.6%, 19.3%, and 18.7%, respectively. The average precision of single bud, one bud with one leaf, and one bud with two leaves were 88.5%, 89.5% and 89.1%. In this study, the improved model demonstrated strong robustness and proved suitable for tea grading and edge-picking equipment, laying a solid foundation for the mechanization of the tea industry.

Learning a deep model from small data is an opening and challenging problem. In high-dimensional spaces, few samples only occupy an extremely small portion of the space, often exhibiting sparsity issues. Classifying in this globally sparse sample space poses significant challenges. However, by using a single sample category as a reference object for comparing and recognizing other samples, it is possible to construct a local space. Conducting contrastive learning in this local space can overcome the sparsity issue of a few samples. Based on this insight, we proposed a novel deep learning approach named Local Contrast Learning (LCL). This is analogous to a key insight into human cognitive behavior, where humans identify the objects in a specific context by contrasting them with the objects in that context or from their memory. LCL is used to train a deep model that can contrast the recognized sample with a couple of contrastive samples that are randomly drawn and shuffled. On a one-shot classification task on Omniglot, the deep model-based LCL with 86 layers and 1.94 million parameters, which was trained on a tiny dataset with only 60 classes and 20 samples per class, achieved an accuracy of 98.95%. Furthermore, it achieved an accuracy of 99.24% at 156 classes and 20 samples per class. LCL is a fundamental idea that can be applied to alleviate the parametric model’s overfitting resulting from a lack of training samples.

IntroductionIn order to solve the problem of precise identification and counting of tea pests, this study has proposed a novel tea pest identification method based on improved YOLOv7 network.MethodsThis method used MPDIoU to optimize the original loss function, which improved the convergence speed of the model and simplifies the calculation process. Replace part of the network structure of the original model using Spatial and Channel reconstruction Convolution to reduce redundant features, lower the complexity of the model, and reduce computational costs. The Vision Transformer with Bi-Level Routing Attention has been incorporated to enhance the flexibility of model calculation allocation and content perception.ResultsThe experimental results revealed that the enhanced YOLOv7 model significantly boosted Precision, Recall, F1, and mAP by 5.68%, 5.14%, 5.41%, and 2.58% respectively, compared to the original YOLOv7. Furthermore, when compared to deep learning networks such as SSD, Faster Region-based Convolutional Neural Network (RCNN), and the original YOLOv7, this method proves to be superior while being externally validated. It exhibited a noticeable improvement in the FPS rates, with increments of 5.75 HZ, 34.42 HZ, and 25.44 HZ respectively. Moreover, the mAP for actual detection experiences significant enhancements, with respective increases of 2.49%, 12.26%, and 7.26%. Additionally, the parameter size is reduced by 1.39 G relative to the original model.DiscussionThe improved model can not only identify and count tea pests efficiently and accurately, but also has the characteristics of high recognition rate, low parameters and high detection speed. It is of great significance to achieve realize the intelligent and precise prevention and control of tea pests.

AbstractTo systematically and thoroughly analyze the sensitivity and reliability of the MSBAS regularization for the estimation of surface deformation over a mine in combination with an application example, this study processed 101 Sentinel-1A/B SAR images, constructed and solved the 2D deformation models using SVD and Tikhonov regularization methods with different orders and parameters, and estimated the vertical and east-west surface deformation time series in a mine of China. Then, this study collected the leveling-monitoring vertical surface deformation data on three leveling points, and compared and analyzed the sensitivity and reliability of the MSBAS regularization methods for estimating vertical surface deformation. The results indicate that different regularization orders and parameters can lead to thousands of times differences in condition numbers and significant differences in ill-posed degree of the deformation models. The zero-order Tikhonov regularized deformation model with regularization parameter of 0.1 has the minimum condition number and the equation is not ill-posed. The first-order Tikhonov regularized deformation model with regularization parameter of 0.001 has the maximum condition number and the equation is seriously ill-posed. As a result, the estimates of 2D surface deformation models with different parameters and orders are also different in terms of numerical values and accuracy. Compared with the leveling-monitoring data, the first- and second-order MSBAS regularization methods with parameter 0.1 have the minimum fluctuation and the maximum correlation coefficients between the estimated values and the leveling-monitoring values, and are also closest to the leveling-monitoring results with the highest accuracy.

Abstract The realization of graphene gapped states with large on/off ratios over wide doping ranges remains challenging. Here, we investigate heterostructures based on Bernal-stacked bilayer graphene (BLG) atop few-layered CrOCl, exhibiting an over-1-GΩ-resistance insulating state in a widely accessible gate voltage range. The insulating state could be switched into a metallic state with an on/off ratio up to 107 by applying an in-plane electric field, heating, or gating. We tentatively associate the observed behavior to the formation of a surface state in CrOCl under vertical electric fields, promoting electron–electron (e–e) interactions in BLG via long-range Coulomb coupling. Consequently, at the charge neutrality point, a crossover from single particle insulating behavior to an unconventional correlated insulator is enabled, below an onset temperature. We demonstrate the application of the insulating state for the realization of a logic inverter operating at low temperatures. Our findings pave the way for future engineering of quantum electronic states based on interfacial charge coupling.

Injectable materials show their special merits in regeneration of damaged/degenerated bones in minimally-invasive approach. Injectable calcium phosphate bone cement (CPC) has attracted broad attention for its bioactivity, as compared to non-degradable polymethyl methacrylate cement. However, its brittleness, poor anti-washout property and uncontrollable biodegradability are the main challenges to limit its further clinical application mainly because of its stone-like dense structure and fragile inorganic-salt weakness. Herein, we developed a kind of injectable CPC bone cement with porous structure and improved robustness by incorporating poly(lactide-co-glycolic acid) (PLGA) nanofiber into CPC, with carboxymethyl cellulose (CMC) to offer good injectability as well as anti-wash-out capacity. Furthermore, the introduction of PLGA and CMC also enabled a formation of initial porous structure in the cements, where PLGA nanofiber endowed the cement with a dynamically controllable biodegradability which provided room for cell movement and bone ingrowth. Interestingly, the reinforced biodegradable cement afforded a sustainable provision of Ca2+ bioactive components, together with its porous structure, to improve synergistically new bone formation and osteo-integration in vivo by using a rat model of femur condyle defect. Further study on regenerative mechanisms indicated that the good minimally-invasive bone regeneration may come from the synergistic enhanced osteogenic effect of calcium ion enrichment and the improved revascularization capacity contributed from the porosity as well as the lactic acid released from PLGA nanofiber. These results indicate the injectable bone cement with high strength, anti-washout property and controllable biodegradability is a promising candidate for bone regeneration in a minimally-invasive approach.

The knee has gradually become an important research target for the lower extremity exoskeleton. However, the issue that whether the flexion-assisted profile based on the contractile element (CE) is effective throughout the gait is still a research gap. In this study, we first analyze the effective flexion-assisted method through the passive element’s (PE) energy storage and release mechanism. Specifically, ensuring assisting within an entire joint power period and the human’s active movement is a prerequisite for the CE-based flexion-assisted method. Second, we design the enhanced adaptive oscillator (EAO) to ensure the human’s active movement and the integrity of the assistance profile. Third, a fundamental frequency estimation based on discrete Fourier transform (DFT) is proposed to shorten the convergence time of EAO significantly. The finite state machine (FSM) is designed to improve the stability and practicality of EAO. Finally, we demonstrate the effectiveness of the prerequisite condition for the CE-based flexion-assisted method by using electromyography (EMG) and metabolic indicators in experiments. In particular, for the knee joint, CE-based flexion assistance should be within an entire joint power period rather than just in the negative power phase. Ensuring the human’s active movement will also significantly reduce the activation of antagonistic muscles. This study will aid in designing assistive methods from the perspective of natural human actuation and apply the EAO to the human-exoskeleton system.

Nanoparticles can promote the accumulation of drugs in tumors. However, they find limited clinical applications because they cannot easily penetrate the stroma of cancer tissues, and it is difficult to control drug release. We developed a multiresponse multistage drug-delivery nanogel with improved tumor permeability and responsiveness to the tumor microenvironment for the controlled delivery of anticancer agents. For this purpose, ∼100 nm multistage drug delivery nanogels with pH, redox, near-infrared stimulation, and enzyme responsiveness were grown in situ using 20 nm gold nanoparticles (AuNPs) via an emulsion-aiding crosslinking technique with cysteine crosslinker. An alginate cysteine AuNP (ACA) nanocarrier can efficiently load the cationic drug doxorubicin (DOX) to produce a multistage drug delivery nanocarrier (DOX@ACA). DOX@ACA can maintain the slow release of DOX and reduce its toxicity. In cancer tissues, the high pH and reductase microenvironment combined with the in vitro delivery of alginate and near-infrared light drove drug release. The developed nanoparticles effectively inhibited cancer cells, and in vivo evaluations showed that they effectively enhanced antitumor activity while having negligible in vivo toxicity to major organs.

In the fragile karst desertification ecosystem, forests are the providers of eco-multifunctionality. And the ecosystem service (ES) supply capacity of forests is directly or indirectly affected by various driving factors. The aim of this study is to explore the driving role of forest spatial structure, species diversity, and functional diversity on ecosystem services. In this study, four forest types, namely, broad-leaved monoculture forest (planted economic forest) (F1), broad-leaved mixed forest (F2), coniferous and broad-leaved mixed forest (F3), and coniferous mixed forest (F4), were investigated in karst plateau mountain (KPM), karst plateau canyon (KPC), and karst mountain canyon (KMC) landforms. Variance analysis, correlation analysis and redundancy analysis were used to compare the differences of spatial structure, species diversity, functional diversity, and ES of different forest types and to clarify the driving role of spatial structure, species diversity, and functional diversity on ES. The results showed that the wood supply service of F3 was at least 4.27% higher than that of other forest types; carbon sequestration and oxygen release are at least 4.57 and 3.89% higher; the water holding capacity of litter and soil is higher by 6.24 and 2.26%, respectively; the soil OC, TN, TP, and TK were higher than 6.01, 1.22, 25.55, and 13.34%, respectively. The coniferous mixed forest and broadleaved mixed forest with a more complete spatial structure has a higher level of diversity, which can generate more wood and provide more soil nutrient sources, as well as stronger regulation capacity. Spatial structure affects plant productivity through interspecific relationships; soil fertility is restricted by the level of diversity; gas and water regulation are influenced by both spatial structure and diversity levels. There is a progressive driving relationship among spatial structure, diversity, and ES. In forest management, it is helpful to improve the forest ecosystem’s functioning by adjusting the forest structure using close-to-natural management measures.

The application of gelatin hydrogels is hampered by their poor mechanical properties, which are unfavorable for debridement and diabetic wound healing. Herein, bovine serum albumin (BSA)-bridged gelatin hydrogels biopotentiated by bone marrow mesenchymal stem cell (BMSC)-derived nanovesicles (NV), named NV@BSA-GEL, were fabricated by reinforcement of gelatin hydrogels with genipin and BSA in a one-pot, low-cost green approach based on amide bonding-guided crosslinking. Genipin introduction endowed the crosslinking of gelatin hydrogels with weak mechanical properties that were reinforced by BSA bridging to realize suitable mechanical properties for wound dressing, including excellent flexibility and appropriate rigidity. The bioactivity of NV released by the hydrogels resulted in efficient ROS scavenging and favorable immunomodulatory activity as well as promoted cell proliferation and migration of fibroblasts and vascular endothelial cells. Proteomic analysis confirmed that NV harbors a variety of growth factors that can promote wound healing. In vivo, the NV@BSA-GEL hydrogel had superior wound healing effects compared to BSA-GEL, including faster wound healing, stimulation of angiogenesis, contributing to an anti-inflammatory extracellular matrix, and promoting skin maturation, with no systemic toxicity. Thus, the combined merits of NV@BSA-GEL suggest that it has high potential as a new hydrogel dressing for the safe and efficient treatment of diabetic wounds.

Twisted van der Waals structures represent a versatile platform to investigate topological and correlated electronic states. Here, the authors report the visualization of an electron crystal phase in twisted monolayer-bilayer graphene via scanning tunnelling microscopy, studying the coupling between strong electron correlation and nontrivial band topology.

Over the last decade, the superior properties of graphene have contributed to intensive studies on the fabrication and applications of graphene nanocomposites. Ex-situ homologous recombination and recombination techniques were listed. Because of their remarkable features, including thermal conductivity and high-specific area, graphene and its derivatives have a significant prospective for medical and biological applications, including drug delivery and bio-imaging. The usage of graphene-based nanomaterials is a hot topic in medicinal research. Many research studies have been performed on graphene-based composites, but only a few reviews have been published regarding their applications in the biomedical field and potential risk factors associated with human well-being and the environment. Hence, this review paper aims to provide in-depth information on ongoing knowledge and results about the properties of graphene-based composites. The discovery, developmental methods, structural properties, and synthesis of graphene nanomaterials have been discussed. After a brief description of the most common methods used for fabricating or extracting graphene derivatives, the main steps of graphene-based composite preparation are introduced. Applications of graphene-based composites in drug delivery, medical, and biomedical fields have been addressed. Finally, the future perspectives and challenges associated with the applications of graphene-based composites have been summarized.Highlights Compositions and characteristics of nanocomposite materials reinforced with graphene, graphene oxide, reduced graphene oxide, and modified graphene.The synthesis method of graphene and the manufacturing of graphene-based composites.Latest developments in graphene-based composites for biomedical applications.Consequences of the large-scale production of graphene-based composites.

Tumor-associated macrophages (TAMs), one of the dominating constituents of tumor microenvironment, are important contributors to cancer progression and treatment resistance. Therefore, regulation of TAMs polarization from M2 phenotype towards M1 phenotype has emerged as a new strategy for tumor immunotherapy. Herein, we successfully initiated antitumor immunotherapy by inhibiting TAMs M2 polarization via autophagy intervention with polyethylene glycol-conjugated gold nanoparticles (PEG-AuNPs). PEG-AuNPs suppressed TAMs M2 polarization in both in vitro and in vivo models, elicited antitumor immunotherapy and inhibited subcutaneous tumor growth in mice. As demonstrated by the mRFP-GFP-LC3 assay and analyzing the autophagy-related proteins (LC3, beclin1 and P62), PEG-AuNPs induced autophagic flux inhibition in TAMs, which is attributed to the PEG-AuNPs induced lysosome alkalization and membrane permeabilization. Besides, TAMs were prone to polarize towards M2 phenotype following autophagy activation, whereas inhibition of autophagic flux could reduce the M2 polarization of TAMs. Our results revealed a mechanism underlying PEG-AuNPs induced antitumor immunotherapy, where PEG-AuNPs reduce TAMs M2 polarization via induction of lysosome dysfunction and autophagic flux inhibition. This study elucidated the biological effects of nanomaterials on TAMs polarization and provided insight into harnessing the intrinsic immunomodulation capacity of nanomaterials for effective cancer treatment.

Vitamin C (VC) can greatly enhance the quality properties of dough and steamed bread in the food field. However, there are few studies on the interaction between VC and gluten, and the mechanism of VC influencing the foaming capacity, emulsifiablity, and dynamic viscosity of gluten is not clear. In this study, different content of VC (0, 1%, 2%, 3%, 4% and 5%) was added to gluten to obtain VC-gluten dough samples (CK, GV1, GV2, GV3, GV4 and GV5), and the properties of the VC-gluten dough were determined. Results showed that the increasing VC content lead to increase in the content of high-, medium- and low-molecular weight gluten, suggesting that VC improved the protein solubility of gluten. The G' and G'' values of dough containing VC were higher than those of the control with the increase of scanning frequency. The foaming ability of gluten increased with the increase of VC content. Emulsibility of the dough of GV1 to GV 5 were significantly lower than that of the CK. Furthermore, VC could reduce the number of bubbles in gluten protein, when the VC content was less than 3%. In conclusion, VC might reduce the emulsifying characteristic and emulsifying stability of gluten, increase the solubility of gluten, and improve the dynamic viscosity of gluten dough by changing the content of disulfide bond in gluten. This study hopes to not only improve the functional characteristics of gluten protein, but also provide the basis for future development and improvement of VC-enriched health foods.

Previous studies of twisted double bilayer graphene have been limited to AB-AB stacking, featuring spin-polarized correlated insulators. Here, the authors fabricate AB-BA devices and report a competition between spin and valley polarization, along with the emergence of valley-polarized correlated insulators tuned by electric field.

Codonopsis Radix, a traditional Chinese medicine in China, has great medicinal and scientific value. Moreover, it can also be used as a health product in daily diet. This paper reviews the botany, ethnopharmacology, phytochemistry, analysis method and quality control, processing methods, pharmacological effects, pharmacokinetics and toxicity related to Codonopsis Radix. The information of Codonopsis Radix is obtained from scientific databases (such as Baidu Scholar, CNKI, Google Scholar, PubMed, Science Direct, Web of Science, and SciFinder Scholar), Chinese herbal classics, Chinese Pharmacopoeia, PhD and MSc dissertations, and so on. The chemical components mainly include alkaloids, alkynes and polyacetylenes, flavonoids, lignans, steroids, terpenoids, organic acids, volatile oils, saccharides and other components, which have a wide range of neuroprotective effects, protection of gastrointestinal mucosa and anti-ulcer, regulation of body immunity, anti-tumor, endocrine regulation, improvement of hematopoietic function, cardiovascular protection, anti-aging and antioxidant effects. In conclusion, this paper summarizes in depth the shortcomings of the current research on Codonopsis Radix and proposes corresponding solutions. At the same time, this paper provides theoretical support for further research on the biological function and potential clinical efficacy of Codonopsis Radix.

Objective: To investigate the effects and mechanisms of Paeoniae radix rubra–Angelicae sinensis radix (P-A) drug pair in the treatment of rheumatoid arthritis (RA).Methods: Mass spectrometry was employed to accurately characterize the main components of the P-A drug pair. Network pharmacology was used to analyze the main components and pathways of the P-A drug pair in the treatment of RA, and Discovery Studio software was used to molecularly dock the key proteins on the pathway with their corresponding compounds. The levels of serum TNF-a, IL-1β, and IL-6 were measured by enzyme linked immunosorbent assay (ELISA). The histopathology of the ankle joint was observed by hematoxylin-eosin (HE) staining, and the positive expression of p-PI3K, p-IKK, p-NF-κB, and p-AKT in the synovial tissue of the ankle joint was detected by immunohistochemical analysis. Finally, the expression of PI3K, IKK, and AKT and their phosphorylation levels were determined by western blot in each group of rats.Results: Network pharmacology combined with molecular docking analysis revealed that the pharmacodynamic mechanism of the P-A drug pair for the treatment of RA may be related to the contents of caffeic acid, quercetin, paeoniflorin, and baicalein in the regulation of the expression of the PI3K/AKT/NF-κB signaling pathway and the targets of PIK3CA, PIK3R1, AKT1, HSP90AA1 and IKBKB in the pathway. Compared with the model group, the P-A drug pair significantly improved the pathological changes of the synovial tissue and reduced feet swelling in RA model rats. Moreover, it regulated the levels of TNF-α, IL-1β, and IL-6 in serum (p < 0.05). The results of the immunohistochemical analysis and western blot showed that the expression of PI3K, IKK, NF-κB, and AKT decreased after phosphorylation in the synovial tissue (p < 0.05).Conclusion: The P-A drug pair exhibited an inhibitory effect on the hyperactivation of the PI3K/AKT/NF-κB signaling pathway in the synovial membrane of RA rats. The mechanism may be related to the downregulation of the phosphorylation levels PI3K, IKK, NF-κB, and AKT, which in turn decreased inflammatory cell infiltration and synovial membrane proliferation.

Abstract Recently the alternating twisted trilayer graphene is discovered to exhibit unconventional superconductivity, which motivates us to study the electronic structures and possible correlation effects for this class of alternating twisted multilayer graphene (ATMG) systems. In this work we consider generic ATMG systems with M-L-N stacking configurations, in which the M (L) graphene layers and the L (N) layers are twisted by an angle θ (−θ). Based on analysis from a simplified k⋅p model approach, we derive generic partition rules for the low-energy electronic structures, which exhibit various band dispersions including two pairs of flat bands and flat bands co-existing with various gapless Fermionic excitations. For a mirror-symmetric ATMG system with doubled flat bands, we further find that Coulomb interactions may drive the system into a state with intertwined electric polarization and orbital magnetization orders, which can exhibit an interaction-driven orbital magnetoelectric effect.

To explore the changes in epigallocatechin gallate (EGCG) content in tea under abiotic stress conditions, we collected tea samples, along with corresponding soil and altitude data, and utilized the measured data for single-factor analysis. At the same time, the LASSO regression method, which is rarely used in agriculture, was employed to screen modeling factors, a prediction model was established, and the Akaike information criterion (AIC) was introduced to compare the goodness of fit. The results show that LASSO screening reduced the AIC value of the model by 13.8%. The average area under the curve of the training set and the validation set was 0.81 and 0.76, respectively, and the calibration curve also showed good consistency. Based on the nomogram model, a visual prediction system was developed, and the content prediction curve was introduced for detailed soil evaluation. The accuracy rate reached 75% after external verification. This study provides a theoretical basis for elucidating the prediction and intervention of Pu’er tea quality under abiotic stress conditions.

Traditional Chinese medicine (TCM) processing is the summary of long-term clinical experience, processing can change the property, taste and meridian of TCM, achieve the purpose of reducing toxicity and increasing efficiency, to ensure the safety of clinical medication. This paper summarizes the research advance of salt processing in recent years from the aspects of the types of excipients, salt processing methods, salt processing purpose and the influence of salt process on the chemical composition, pharmacodynamic effect and in vivo behavior of TCM, and analyzes and discusses the shortcomings of the current research, so as to provide ideas for the further research and development of salt processing of TCM. The literatures were classified and summarized by consulting the scientific database (such as SciFinder Scholar, CNKI, Google Scholar, Baidu Scholar, etc.), Chinese herbal classics and Chinese Pharmacopoeia and so on. The results show that salt processing is helpful to introduce drugs into the kidney channel and enhance the effect of nourishing Yin and falling fire. The pharmacological effect, chemical composition and in vivo behavior of TCM will change after salt processing. In the future, we should strengthen the research on standardizing the dosage of excipients, the quality standard after processing, the relationship between the change of chemical composition after salt processing and the enhancement of pharmacological efficacy, so as to deeply explain the principle of salt processing, and further improve and optimize the salt making process. By combing the influence of the of salt processing of TCM and analyzed the current problems, we hope to provide guidance for the in-depth study of the salt processing mechanism of TCM and the inheritance and innovation of TCM processing technology.

The alignment of three 2D nanosheets leads to the formation of super-moiré atomic lattices, which can influence the electronic properties of van der Waals structures. Here, the authors report evidence of possible correlated insulating states in doubly-aligned hBN/graphene/hBN heterostructures, in a weak-interaction regime.

Facing the high incidence of skin diseases, it is urgent to develop functional materials with high bioactivity for wound healing, where reactive oxygen species (ROS) play an important role in the wound healing process mainly via adjustment of immune response and neovasculation. In this study, we developed a kind of bioabsorbable materials with ROS-mediation capacity for skin disease therapy. Firstly, redox-sensitive poly(N-isopropylacrylamide-acrylic acid) (PNA) nanogels were synthesized by radical emulsion polymerization method using a disulfide molecule as crosslinker. The resulting nanogels were then incorporated into the nanofibrous membrane of poly(l-lactic acid) (PLLA) via airbrushing approach to offer bioabsorbable membrane with redox-sensitive ROS-balance capacity. In vitro biological evaluation indicated that the PNA-contained bioabsorbable membrane improved cell adhesion and proliferation compared to the native PLLA membrane. In vivo study using mouse wound skin model demonstrated that PNA-doped nanofibrous membranes could promote the wound healing process, where the disulfide bonds in them were able to adjust the ROS level in the wound skin for mediation of redox potential to achieve higher wound healing efficacy.

ObjectivesIf hilar and mediastinal lymph node metastases occur in solid nodule lung cancer is critical for tumor staging, which determines the treatment strategy and prognosis of patients. We aimed to develop an effective model to predict hilar and mediastinal lymph node metastases by using texture features of solid nodule lung cancer.MethodsTwo hundred eighteen patients with solid nodules on CT images were analyzed retrospectively. The 3D tumors were delineated using ITK-SNAP software. Radiomics features were extracted from unenhanced and enhanced CT images based on AK software. Correlations between radiomics features of unenhanced and enhanced CT images were analyzed with Spearman rank correlation analysis. According to pathological findings, the patients were divided into no lymph node metastasis group and lymph node metastasis group. All patients were randomly divided into training group and test group at a ratio of 7:3. Valuable features were selected. Multivariate logistic regression was used to build predictive models. Two predictive models were established with unenhanced and enhanced CT images. ROC analysis was used to estimate the predictive efficiency of the models.ResultsA total of 7 categories of features, including 107 features, were extracted. There was a high correlation between the 7 categories of features from unenhanced CT images and enhanced CT images (all r > 0.7, p

BackgroundMany artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract.MethodsThis was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning.ResultsOne thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10–12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63–0.83.ConclusionOphthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.

Cyperi Rhizoma (CR) is the dry rhizome of Cyperus rotundus L., a Cyperaceae plant. It has a long history of clinical medication and is known as the “holy medicine” of gynecology. CR smells sweet and bitter. It has the effect of soothing the liver and relieving depression, regulating qi, regulating meridian and relieving pain. It can be used to treat liver qi stagnation, chest pain, spleen and stomach qi stagnation, hernia pain, irregular menstruation and other diseases. At present, the main chemical constituents isolated from CR are volatile oil, flavonoids and terpenes. Modern pharmacological studies have shown that CR has a wide range of pharmacological activities, including antidepressant, hypoglycemic, antioxidant, anti-inflammatory, antipyretic and analgesic effects. In this paper, the botany, traditional application, phytochemistry, pharmacological effects, processing and other aspects of CR are reviewed. At the same time, the shortcomings of current research of CR are discussed in depth, and the possible solutions are put forward in order to find a breakthrough point for future research of CR.

Enterovirus A71 (EV-A71) is a major pathogen that causes severe and fatal cases of hand-foot-and-mouth disease (HFMD), which is an infectious disease that endangers children’s health. However, the pathogenic mechanisms underlying these severe clinical and pathological features remain incompletely understood. Metabolism and stress are known to play critical roles in multiple stages of the replication of viruses. Lipid metabolism and ER stress is an important characterization post viral infection. EV-A71 infection alters the perturbations of intracellular lipid homeostasis and induces ER stress. The characterizations induced by viral infections are essential for optimal virus replication and may be potential antiviral targets. In this study, we found that the addition of the chemical drug of ER stress, PKR IN, an inhibitor, or Tunicamycin, an activator, could significantly reduce viral replication with the decrease of lipid. The replication of viruses was reduced by Chemical reagent TOFA, an inhibitor of acetyl-CoA carboxylase (ACC) or C75, an inhibitor of fatty acid synthase (FASN), while enhanced by oleic acid (OA), which is a kind of exogenous supplement of triacylglycerol. The pharmacochemical reagent of carnitine palmitoyltransferase 1 (CPT1) called Etomoxir could knock down CPT1 to induce EV-A71 replication to decrease. This suggests that lipid, rather than ER stress, is the main factor affecting EV-A71 replication. In conclusion, this study revealed that it is the β-oxidation of lipid that plays a core role, not ER stress, which is only a concomitant change without restrictive effect, on virus replication.