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Sustainable agricultural practices (SAPs) are conducive to increasing agricultural productivity and income while reducing resource and environmental stress. However, due to credit constraints in traditional financial markets, the adoption rate of SAPs remains low among smallholder farmers in rural China. Recently, the emergence of digital finance provides small farmers with a new way to obtain credit and alleviate their credit constraints, which may exert an impact on the adoption of SAPs. To verify this conjecture, this paper examines the impact and mechanism of digital finance use on SAPs adoption among smallholder farmers in China based on survey data collected from 903 apple growers. Empirical results showed that digital finance use significantly increases the number of SAPs adopted by smallholder farmers. Alleviating credit constraints, promoting information acquisition, and facilitating social interactions are the pathways through which digital finance use influences small farmers’ SAPs adoption. Heterogeneity analysis showed that farmers with higher education level, smaller farming size, and who have received extension services adopt more SAPs with the use of digital finance. Therefore, it is suggested that the government should strengthen the construction of rural network infrastructure and provide training to promote smallholder farmers’ access to digital financial services in a cost-effective and secure manner.

The present work focuses on the flame–wall interaction (FWI) based on direct numerical simulations (DNS) of a head-on premixed flame quenching configuration at the statistically stationary state. The effects of FWI on the turbulent flame temperature, wall heat flux, flame dynamics and flow structures were investigated. In turbulent head-on quenching, particularly for high turbulence intensity, the distorted flames generally consist of the head-on flame part and the entrained flame part. The flame properties are jointly influenced by turbulence, heat generation from chemical reactions and heat loss to the cold wall boundary. For the present FWI configuration, as the wall is approached, the ‘influence zone’ can be identified as the region within which the flame temperature, scalar gradient and flame dilatation start to decrease, whereas the wall heat flux tends to increase. As the distance to the wall drops below the flame-quenching distance, approximately where the wall heat flux reaches its maximum value, chemical reactions become negligibly weak inside the ‘quenching zone’. A simplified counter-flow model is also proposed. With the reasonably proposed relation between the flame speed and the flame temperature, the model solutions match well with the DNS results, both qualitatively and quantitatively. Moreover, near-wall statistics of some important flame properties, including the flame dilatation, reaction progress variable gradient, tangential strain rate and curvature were analysed in detail under different wall boundary conditions.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer (BC) with a poor prognosis. To date, the mechanism of TNBC’s aggressive phenotype is still unclear. Based on metabolome analysis, we found that glutamine (Gln) metabolism plays a key role in the difference between TNBC and non-TNBC. We identified a 21-amino-acid survival-associated micropeptide XBP1SBM, encoded by the lncRNA MLLT4-AS1 , which was upregulated in TNBC tissues and Gln-deprived TNBC cell lines. We showed that XBP1SBM expression was upregulated by Gln-deprivation-induced XBP1s transcriptional promotion, and in turn retained XBP1s in the nuclear to enhance the expression of VEGF. Using human endothelial cells, mouse xenograft models and mouse spontaneous BC models, we found that XBP1SBM improved Gln levels and promoted angiogenesis and metastasis in TNBC. Our study showed that a TNBC-specific nutrient deficiency adaption results in aggressive TNBC, and this mechanism provides a novel potential prognostic biomarker and therapeutic target in TNBC.

Objective The present study aimed to explore the distribution patterns of IgE characteristics and peripheral blood inflammatory markers in pediatric patients with allergic reactions. Methods Patients’ data were collected, including age, gender, and peripheral blood parameters, including white blood cells (WBC), neutrophils (NEU), lymphocytes (LYM), monocytes (MON), eosinophils (EOS), red blood cells (RBC), and platelets (PLT). Serum total Immunoglobulin E (tIgE) assays were performed using a fully automated specific protein analysis system, and specific Immunoglobulin E (sIgE) was detected through the AllergyScreen assay. The clinical data of these patients were retrospectively analyzed. Results A total of 405 samples were included in the study, including 335 patients and 70 normal controls. Our study reveals that aeroallergens are the main cause of allergic reactions in children, and 26.3% of sensitized pediatric subjects exhibit atypical immunological profiles characterized by non-elevated tIgE expressions and low sIgE sensitization. Notably, the Eosinophil-to-Lymphocyte Ratio (ELR) demonstrates significant predictive value for IgE pattern and exhibits a positive correlation ( p  < 0.001) with tIgE sensitization intensity. Conclusion These findings position ELR as a promising peripheral blood inflammatory biomarker for assessing the risk of anaphylaxis in pediatric patients with both tIgE and sIgE elevation.

Background Orsellinic acid (2,4-dihydroxy-6-methylbenzoic acid, OA) and its structural analog o -Orsellinaldehyde, have become widely used intermediates in clinical drugs synthesis. Although the research on the biosynthesis of such compounds has made significant progress, due to the lack of suitable hosts, there is still far from the industrial production of such compounds based on synthetic biology. Results With the help of genome mining, we found a polyketide synthase (PKS, HerA) in the genome of the Hericium erinaceus , which shares 60% amino acid sequence homology with ArmB from Armillaria mellea , an identified PKS capable of synthesizing OA. To characterize the function of HerA, we cloned herA and heterologously expressed it in Aspergillus oryzae , and successfully detected the production of OA. Subsequently, the introduction of an incomplete PKS (Pks5) from Ustilago maydis containing only three domains (AMP-ACP-R), which was into herA -containing A. oryzae , the resulted in the production of o -Orsellinaldehyde. Considering the economic value of OA and o -Orsellinaldehyde, we then optimized the yield of these compounds in A. oryzae . The screening showed that when maltose was used as carbon source, the yields of OA and o -Orsellinaldehyde were 57.68 mg/L and 15.71 mg/L respectively, while the yields were 340.41 mg/Kg and 84.79 mg/Kg respectively in rice medium for 10 days. Conclusions Herein, we successfully expressed the genes of basidiomycetes using A. oryzae heterologous host. As a fungus of ascomycetes, which not only correctly splices genes of basidiomycetes containing multiple introns, but also efficiently produces their metabolites. This study highlights that A. oryzae is an excellent host for the heterologous production of fungal natural products, and has the potential to become an efficient chassis for the production of basidiomycete secondary metabolites in synthetic biology. Graphical Abstract

A series of Pt catalysts supported on SO42− group modified Al2O3 were synthesized and tested for methane and propane combustion. The introduction of SO42− group promoted the surface acidity but reduced the quantity of exposed surface Pt atoms due to strong coordination effect. The presence of SO42− group significantly promoted the propane combustion reaction but inhibited the methane combustion reaction. It can be inferred that the promotion on propane combustion is ascribed to the enhanced activation of C–C bond (370.3 kJ mol−1) by sulfates. Whereas the sulfates are not favorable for the activation and cracking of C-H bond (439.3 kJ mol−1), and the reduced number of exposed Pt sites results in the activity decrease of methane combustion.Graphic Abstract

Strong coupling has emerged as a central topic in nanophotonics, offering a powerful platform for light–matter interaction studies and advancing quantum technologies. Low-dimensional materials, such as quantum dots (QDs) and two-dimensional (2D) semiconductors, possess pronounced excitonic resonances, high stability, and size-dependent tunability, making them ideal candidates for achieving strong coupling with plasmonic structures. In this review, we systematically summarize recent progress in plasmon low-dimensional material strong coupling. We first introduce the fundamental principles and experimental methods of plasmon–exciton strong coupling, then highlight representative studies on plasmon–QDs and plasmon–2D material hybrid systems, and finally discuss recent advances in multimode strong coupling. This review will provide a comprehensive overview and offer valuable guidance for future studies in strong coupling.

Increasing attention has recently been focused on complex symbiotic associations, for instance coral and its symbionts. Sea cucumber, harboring diverse fungi, has also attracted more and more attention for their functional diversity. Here, secondary metabolites produced by Chaetomium globosum associated with sea cucumber, Apostichopus japonicus, were investigated using gene mining with third-generation sequencing technology (PacBio SMRT). Nine compounds, including one new compound cytoglobosin X (1), were isolated from cultures of Chaetomium globosum. Compound 1 was identified based on NMR data, HRESIMS, and ECD, and the absolute configurations were identified as 3S, 4R, 7S, 8R, 9R, 16S, 19S, 20S, and 23S. In an antimicrobial assay, compound 4 showed moderate activity against Staphylococcus aureus and methicillin-resistant Staphylococcus aureus with MICs of 47.3 and 94.6 μM, respectively. Our results suggest that the microbiomes associated with sea cucumber could be an important resource for biodiversity and structural novelty, and the bioactive compounds may protect the host from pathogen microbial.

As a decision maker is not always interested in the entire Pareto front, a natural idea is to take into account user preferences in computationally expensive multi-objective optimization to focus on searching the preferred region. However, most existing methods rely on the estimated ideal point. Since the search process of preference-based approaches is always biased towards the region of interest (ROI), it is highly challenging to estimate the ideal point in preference-based expensive multi-objective optimization. Incorrect estimation of the ideal point may lead to the search direction being far away from the ROI and also result in normalization errors for each objective. This paper proposes a preference-based surrogate-assisted algorithm, PMEGO, to overcome this issue. In the preference management module, a set of new reference points derived from the user reference point is used to construct a series of subproblems, with the key merit of not using the ideal point. The Gaussian process model is built on the objective functions. In the model-based optimization, the projection distance with upper confidence bound (UCB) is developed as the fitness of solutions for each subproblem. Finally, the expected achievement scalarizing function improvement (EASFI) is employed to further screen out the best solutions for evaluation using the real objective functions. Comparative experiments are conducted on ZDT, DTLZ, SDTLZ, as well as two real-world applications. The experimental results show that the proposed method is competitive compared to three state-of-the-art algorithms.

Objectives This study aims to identify predictors of knee osteoarthritis (KOA) risk in middle-aged population, construct and validate a nomogram for KOA in this demographic. Methods From June to December 2020, we conducted a cross-sectional survey on 5,527 middle-aged individuals from Changsha and Zhangjiajie cities in Hunan Province, selected using a stratified multi-stage random sampling method. Data collection involved a structured questionnaire encompassing general demographic, physical condition, and lifestyle behaviors dimensions. The dataset was randomly split into a training set (n = 3868) and a validation set (n = 1659) at a 7:3 ratio via computerized randomization. We analyzed the prevalence of self-reported KOA and identified its influencing factors using logistic regression. A nomogram was constructed based on these \"three-dimensional\" factors. Subsequent validation was conducted, and the nomogram's performance was further evaluated through ROC curves, C-index, Hosmer–Lemeshow test, and calibration curves. Results The self-reported prevalence of KOA in the middle-aged population was 11.4% (632/5527). The risk factor with the greatest impact is: diagnosed with osteoporosis(95% CI 2.269–3.568, OR  = 2.845), followed by age between 51 to 60 years (95% CI 2.176–3.151, OR  = 2.619), diagnosed with hypertension(95% CI 1.633–2.499, OR  = 2.02), diagnosed with diabetes ( OR  = 1.689), ethnic Han Chinese (OR = 1.673), exercise according to physical condition ( OR  = 1.643), pay attention to keeping the knee joint warm ( OR  = 1.535), eating habits are mainly light vegetables ( OR  = 1.374), male gender ( OR  = 1.343), drink occasionally in small amounts ( OR  = 1.286); a higher level of education ( OR  = 0.477) and frequently or always apply an external or plaster to relieve symptoms after knee discomfort ( OR  = 0.377; OR  = 0.385) are protective factors. The C-index of the training set model was 0.8107 (95% CI : 0.8102–0.8111), with a statistically significant area under the ROC curve ( AUC  = 0.818), and the calibration curve showed a good fit. The C-index for the validation set was 0.8124 (95% CI : 0.8109–0.8140), with an AUC of 0.812. The Hosmer–Lemeshow test resulted in a P -value of 0.46 ( P  ≥ 0.05)indicating good calibration of the model. Conclusion The three dimensions nomogram generated in this study was a valid and easy-to-use tool for assessing the risk of KOA in middle-aged population, and helped healthcare professionals to screen the high-risk population.