Accelerated Solar-Driven Polyolefin Degradation via Self-Activated Hydroxy-Rich ZnIn2S4.

Degradation of polyolefin (PE) plastic by a traditional chemical method requires a high pressure and a high temperature but generates complex products. Here, sulfur vacancy-rich ZnIn2S4 and hydroxy-rich ZnIn2S4 were rationally fabricated to realize photocatalytic degradation of PE in an aqueous solution under mild conditions. The results reveal that the optimized photocatalyst could degrade PE into CO2 and CO, and PE had a weight loss of 84.5% after reaction for 60 h. Systematic experiments confirm that the synergetic effect of hydroxyl groups and S vacancies contributes to improve the photocatalytic degradation properties of plastic wastes. In-depth investigation illustrates that the active radicals attack (h+ and •OH) weak spots (C-H and C-C bonds) of the PE chain to form CO2, which is further selectively photoreduced to CO. Multimodule synergistic tandem catalysis can further improve the utilization value of plastic wastes; for example, product CO2/CO in the plastic degradation process can be converted in situ into HCOOH by coupling with electrocatalytic technology.

Non-targeted metabolomic analysis of non-volatile metabolites in a novel Chinese industrially fermented low-salt kohlrabi.

Low-temperature and low-salt fermented Chinese kohlrabi (LSCK) represents a novel approach to producing low-salt kohlrabi without the need for desalination during processing, as compared to traditional techniques. However, the profile of its non-volatile metabolites remains unclear. In order to investigate the non-volatile metabolites and their changes in LSCK during fermentation, the LSCKs fermented for 0 day (0D), 45 days (45D) and 90 days (90D) were analyzed using LC-MS/MS non-targeted metabolomics coupled with multivariate statistical analysis. The results showed that 60, 74, and 68 differential metabolites were identified in the three groups A1 (0D and 45D), A2 (0D and 90D), and A3 (45D and 90D) (VIP >1, p < 0.05, Log2FC >1), respectively. The differential metabolites were mainly amino acids, peptides, and analogues, fatty acyls, organic acids and derivatives, and carbohydrates and carbohydrate conjugates. Seventeen common differential metabolites were identified in A1, A2, and A3 groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that the alanine, aspartate and glutamate metabolism, butanoate metabolism, α-linolenic acid metabolism, arginine biosynthesis, and phenylalanine metabolism were significantly correlated with the differential metabolites. The present study elucidates for the first time the changes in non-volatile differential metabolites and their associated metabolic pathways in the novel Chinese low-salt kohlrabi, providing a theoretical basis for improving the industrial fermentation process of this innovative product.

Comparison and use of explainable machine learning-based survival models for heart failure patients.

Objective: Explainable machine learning (XAI) was introduced in this study to improve the interpretability, explainability and transparency of the modelling results. The survex package in R was used to interpret and compare two survival models - the Cox proportional hazards regression (coxph) model and the random survival forest (rfsrc) model - and to estimate overall survival (OS) and its determinants in heart failure (HF) patients using these models. Methods: We selected 1159 HF patients hospitalised at the First Affiliated Hospital of Kunming Medical University. First, the performance of the two models was investigated using the C-index, the integrated C/D AUC, and the integrated Brier score. Second, a global explanation of the whole cohort was carried out using the time-dependent variable importance and the partial dependence survival profile. Finally, the SurvSHAP(t) and SurvLIME plots and the ceteris paribus survival profile were used to obtain a local explanation for each patient. Results: By comparing the C-index, the C/D AUC, and the Brier score, this study showed that the model performance of rfsrc was better than coxph. The global explanation of the whole cohort suggests that the C-reactive protein, lg BNP (brain natriuretic peptide), estimated glomerular filtration rate, albumin, age and blood chloride were significant unfavourable predictors of OS in HF patients in both the cxoph and the rfsrc models. By including individual patients in the model, we can provide a local explanation for each patient, which guides the clinician in individualising the patient's treatment. Conclusion: By comparison, we conclude that the model performance of rfsrc is better than that of coxph. These two predictive models, which address not only the whole population but also selected patients, can help clinicians personalise the treatment of each HF patient according to his or her specific situation.

Lithium metal based battery systems with ultra-high energy density beyond 500 W h kg-1.

As industries and consumption patterns evolve, new electrical appliances are increasingly playing critical roles in national production, defense, and cognitive exploration. However, the slow development of energy storage devices with ultra-high energy density (beyond 500 W h kg-1) has impeded the promotion and widespread application of the next generation of intelligent, multi-scenario electrical equipment. Among the numerous ultra-high specific energy battery systems, lithium metal batteries (LMBs) hold significant potential for applications in advanced and sophisticated fields. This potential is primarily due to lithium metal's high specific capacity (3860 mA h g-1). However, LMBs face numerous challenges, including the growth of lithium dendrites, poor cycle stability, and safety concerns. In recent years, research on the mechanisms of Li metal-based battery systems, innovation in electrode materials, and optimization of device configurations have made significant progress. In this highlight, we provide a comprehensive overview of the storage mechanisms and the latest advancements in high-energy-density LMBs, represented by systems such as Li-Li1-xMO2, Li-S/Se, Li-gas (CO2/air/O2), Li-CFx, and all-solid-state LMBs. By integrating the current research findings, we highlight the opportunities and future research directions for high-energy-density LMBs, offering new guiding perspectives for their development under practical conditions.

Infection microenvironment-triggered nanoparticles eradicate MRSA by thermally amplified chemodynamic therapy and M1 macrophage.

It is of great significance to develop a novel approach to treat bacterial infections, as the frequent misuse of antibiotics leads to the serious problem of bacterial resistance. This study proposed antibiotic-free antibacterial nanoparticles for eliminating methicillin-resistant Staphylococcus aureus (MRSA) based on a multi-model synergistic antibacterial ability of chemodynamic therapy (CDT), photothermal effect, and innate immunomodulation. Specifically, a polydopamine (PDA) layer coated and Ag nanoparticles loaded core-shell structure Fe3O4 nanoparticles (Fe3O4@PDA-Ag) is prepared. The Fe3O4 catalyzes H2O2 present in acidic microenvironment of bacterial infection into more toxic reactive oxygen species (ROS) and synergizes with the released Ag ions to exert a stronger bactericidal capacity, which can be augmented by photothermal action of PDA triggered by near-infrared light and loosen the biofilm by photothermal action to promote the penetration of ROS and Ag ion into the biofilm, result in disrupting biofilm structure along with killing encapsulated bacteria. Furthermore, Fe3O4@PDA-Ag exerts indirect antibacterial effects by promoting M1 macrophage polarizing. Animal models demonstrated that Fe3O4@PDA-Ag effectively controlled MRSA-induced infections through photothermal enhanced CDT, Ag+ releasing, and macrophage-mediated bactericidal properties. The acid-triggered antibacterial nanoparticles are expected to combat drug-resistant bacteria infection.

Spatial accumulation of lignin monomers and cellulose underlying stalk strength in maize.

Lodging largely affects yield, quality and mechanical harvesting of maize. Stalk strength is one of the major factors that affect maize lodging. Although plant cell wall components including lignin and cellulose were known to be associated with stalk strength and lodging resistance, spatial accumulation of specific lignin monomers and cellulose in different tissues and their association with stalk strength in maize was not clearly understood. In this study, we found that both G and S lignin monomers accumulate highest in root, stem rind and leaf vein. Consistently, most lignin biosynthetic genes were expressed higher in root and stem than in other tissues. However, cellulose appears to be lowest in root. There are only mild changes of G lignin and cellulose in different internodes. Instead, we noticed a dramatic decrease of S-lignin accumulation and lignin biosynthetic gene expression in 2nd to 4th internodes wherein stem breakage usually occurs, thereby revealing a few candidate lignin biosynthetic genes associated with stalk strength. Moreover, stalk strength is positively correlated with G, S lignin, and cellulose, but negatively correlated with S/G ratio based on data of maize lines with high or low stalk strength. Loss-of-function of a caffeic acid o-methyltransferase (COMT), which is involved in S lignin biosynthesis, in the maize bm3 mutant, leads to lower stalk strength. Our data collectively suggest that stalk strength is determined by tissue-specific accumulation of lignin monomers and cellulose, and manipulation of the cell wall components by genetic engineering is vital to improve maize stalk strength and lodging resistance.

Plant leaf disease recognition based on improved SinGAN and improved ResNet34.

The identification of plant leaf diseases is crucial in precision agriculture, playing a pivotal role in advancing the modernization of agriculture. Timely detection and diagnosis of leaf diseases for preventive measures significantly contribute to enhancing both the quantity and quality of agricultural products, thereby fostering the in-depth development of precision agriculture. However, despite the rapid development of research on plant leaf disease identification, it still faces challenges such as insufficient agricultural datasets and the problem of deep learning-based disease identification models having numerous training parameters and insufficient accuracy. This paper proposes a plant leaf disease identification method based on improved SinGAN and improved ResNet34 to address the aforementioned issues. Firstly, an improved SinGAN called Reconstruction-Based Single Image Generation Network (ReSinGN) is proposed for image enhancement. This network accelerates model training speed by using an autoencoder to replace the GAN in the SinGAN and incorporates a Convolutional Block Attention Module (CBAM) into the autoencoder to more accurately capture important features and structural information in the images. Random pixel Shuffling are introduced in ReSinGN to enable the model to learn richer data representations, further enhancing the quality of generated images. Secondly, an improved ResNet34 is proposed for plant leaf disease identification. This involves adding CBAM modules to the ResNet34 to alleviate the limitations of parameter sharing, replacing the ReLU activation function with LeakyReLU activation function to address the problem of neuron death, and utilizing transfer learning-based training methods to accelerate network training speed. This paper takes tomato leaf diseases as the experimental subject, and the experimental results demonstrate that: (1) ReSinGN generates high-quality images at least 44.6 times faster in training speed compared to SinGAN. (2) The Tenengrad score of images generated by the ReSinGN model is 67.3, which is improved by 30.2 compared to the SinGAN, resulting in clearer images. (3) ReSinGN model with random pixel Shuffling outperforms SinGAN in both image clarity and distortion, achieving the optimal balance between image clarity and distortion. (4) The improved ResNet34 achieved an average recognition accuracy, recognition precision, recognition accuracy (redundant as it's similar to precision), recall, and F1 score of 98.57, 96.57, 98.68, 97.7, and 98.17%, respectively, for tomato leaf disease identification. Compared to the original ResNet34, this represents enhancements of 3.65, 4.66, 0.88, 4.1, and 2.47%, respectively.

Interstitial Boron Atoms in Pd Aerogel Selectively Switch the Pathway for Glycolic Acid Synthesis from Waste Plastics.

Electro-reforming of poly(ethylene terephthalate) (PET) into valuable chemicals is garnering significant attention as it opens a mild avenue for waste resource utilization. However, achieving high activity and selectivity for valuable C2 products during ethylene glycol (EG) oxidation in PET hydrolysate on Pd electrocatalysts remains challenging. The strong interaction between Pd and carbonyl (*CO) intermediates leads to undesirable over-oxidation and poisoning of Pd sites, which hinders the highly efficient C2 products production. Herein, a nonmetallic alloying strategy is employed to fabricate a Pd-boron alloy aerogel (PdB), wherein B atoms are induced to regulate the electron structure and surface oxophilicity. This approach allows a remarkable mass activity of 6.71 A mgPd -1, glycolic acid (GA) Faradaic efficiency (FE) of 93.8%, and stable 100 h cyclic electrolysis. In situ experiments and density functional theory calculations reveal the contributions of B inserted in Pd lattice on highly effective EG-to-GA conversion. Interestingly, the heightened surface oxophilicity and regulated electronic structure by B incorporation weakened *CO intermediates adsorption and enhanced hydroxyl species affinity to accelerate oxidative *OH adspecies formation, thereby synergistically avoiding over-oxidation and boosting GA synthesis. This work provides valuable insights for the rational design of high-performance electrocatalysts for GA synthesis via an oxophilic B motifs incorporation strategy.

New Monoterpenoid Glycosides from the Fruits of Hypericum patulum Thunb.

The whole Hypericum patulum Thunb. plant is utilized in traditional medicine for its properties of clearing heat, detoxifying, soothing meridians, relaxing the liver, and stopping bleeding. In folk medicine, it is frequently used to treat hepatitis, colds, tonsillitis, and bruises. Phytochemical investigation of a 30% ethanol extract of the fresh ripe fruits of H. patulum has resulted in the isolation of two new pinane-type monoterpenoid glycosides 1-2, named patulumside E-F, and three new chain-shaped monoterpenoid glycosides 3-5, named patulumside G-H, J. Their structures were determined using extensive spectroscopic techniques, such as HR-ESI-MS, 1D and 2D NMR spectroscopy, and electronic circular dichroism (ECD) calculation. The anti-inflammatory activities of these compounds were evaluated in the LPS-induced RAW264.7 cells. This research represents the inaugural comprehensive phytochemical study of H. patulum, paving the way for further exploration of monoterpenoid glycosides.

A complete review on the oxygen-containing functional groups of biochar: Formation mechanisms, detection methods, engineering, and applications.

Biochar is a porous carbon material generated by the thermal treatment of biomass under anaerobic or anoxic conditions with wealthy Oxygen-containing functional groups (OCFGs). To date, OCFGs of biochar have been extensively studied for their significant utility in pollutant removal, catalysis, capacitive applications, etc. This review adopted a whole system philosophy and systematically summarizes up-to-date knowledge of formation, detection methods, engineering, and application for OCFGs. The formation mechanisms and detection methods of OCFGs, as well as the relationships between OCFGs and pyrolysis conditions (such as feedstocks, temperature, atmosphere, and heating rate), were discussed in detail. The review also summarized strategies and mechanisms for the oxidation of biochar to afford OCFGs, with the performances and mechanisms of OCFGs in the various application fields (environmental remediation, catalytic biorefinery, and electrode material) being highlighted. In the end, the future research direction of biochar OCFGs was put forward.

Molybdenum disulfide nanosheets based non-oxygen-dependent and heat-initiated free radical nanogenerator with antimicrobial peptides for antimicrobial, biofilm ablation and wound healing.

Chronic refractory wounds caused by multidrug-resistant (MDR) bacterial and biofilm infections are a substantial threat to human health, which presents a persistent challenge in managing clinical wound care. We here synthesized a composite nanosheet AIPH/AMP/MoS2, which can potentially be used for combined therapy because of the photothermal effect induced by MoS2, its ability to deliver antimicrobial peptides, and its ability to generate alkyl free radicals independent of oxygen. The synthesized nanosheets exhibited 61 % near-infrared (NIR) photothermal conversion efficiency, marked photothermal stability and free radical generating ability. The minimal inhibitory concentrations (MICs) of the composite nanosheets against MDR Escherichia coli (MDR E. coli) and MDR Staphylococcus aureus (MDR S. aureus) were approximately 38 µg/mL and 30 µg/mL, respectively. The composite nanosheets (150 µg/mL) effectively ablated >85 % of the bacterial biofilm under 808-nm NIR irradiation for 6 min. In the wound model experiment, approximately 90 % of the wound healed after the 4-day treatment with the composite nanosheets. The hemolysis experiment, mouse embryonic fibroblast (MEFs) cytotoxicity experiment, and mouse wound healing experiment all unveiled the excellent biocompatibility of the composite nanosheets. According to the transcriptome analysis, the composite nanosheets primarily exerted a synergistic therapeutic effect by disrupting the cellular membrane function of S. aureus and inhibiting quorum sensing mediated by the two-component system. Thus, the synthesized composite nanosheets exhibit remarkable antibacterial and biofilm ablation properties and therefore can be used to improve wound healing in chronic biofilm infections.

The Promising Potential of Gallium Based Liquid Metals for Energy Storage.

Energy storage devices play a crucial role in various applications, such as powering electronics, power backup for homes and businesses, and support for the integration of renewable energy sources into electrical grid applications. Electrode materials for energy storage devices are preferred to have a flexible nature, conductive, better capacity, and low-toxicity. Using Gallium based liquid metal alloys, such as Eutectic Gallium-Indium (EGaIn), Eutectic Gallium-Tin (EGaSn), and Eutectic Gallium-Indium-Tin (EGaInSn), as electrode materials play very important role in energy storage devices. These liquid metals have some interesting properties with a self-healing nature, high mechanical stability, compatibility with various materials, fluidity, low young's modulus, high electrical and thermal conductivity. Those properties have made it suitable to be used in various energy storage devices. In this mini review, we have concisely described the advantages and challenges of using liquid metal as electrode materials for various energy storage devices.

Polyaniline/Tungsten Trioxide Organic-Inorganic Hybrid Anode for Aqueous Proton Batteries.

Aqueous proton batteries have received increasing attention due to their outstanding rate performance, stability and high capacity. However, the selection of anode materials in strongly acidic electrolytes poses a challenge in achieving high-performance aqueous proton batteries. This study optimized the proton reaction kinetics of layered metal oxide WO3 by introducing interlayer structural water and coating polyaniline (PANI) on its surface to prepare organic-inorganic hybrid material (WO3 ⋅ 2H2O@PANI). We constructed an aqueous proton battery with WO3 ⋅ 2H2O@PANI anode and MnO2@GF cathode. After 1500 cycles at a current density of 10 A g-1, the capacity retention rate can still reach 80.2 %. These results can inspire the development of new aqueous proton batteries.

Metricizing policy texts: Comprehensive dataset on China's Agri-policy intensity spanning 1982-2023.

Due to the lack of direct assessment metrics, existing studies on the intensity of agricultural policies often utilize indicators such as Gross Domestic Product (GDP) of agriculture or the quantity of agricultural policies as measures. Optimizing methods for analyzing the intensity of agricultural policies will significantly impact parameter selection in agricultural policy research and the evaluation of policy effectiveness. In this study, we constructed a Chinese Agricultural Policy Corpus using agricultural policies released by various governmental agencies at the national level in China from 1982 to April 2023. We quantified the values of agricultural domain terms in the corpus and evaluated the intensity of each agricultural policy document. The validation results of this study indicate a strong correlation between the intensity of agricultural policies and agricultural GDP. The trend in agricultural GDP changes lags behind policy intensity by 2.5 years (at a 95% confidence level), thus validating the rationality of our constructed corpus, agricultural policy scoring dataset, and methodology.

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize.

BACKGROUND: Heterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions. RESULTS: In this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication. CONCLUSIONS: The comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

Identification of a Rye Spring Mutant Derived from a Winter Rye Variety by High-Altitude Environment Screening Using RNA Sequencing Technology.

Wintergrazer-70 and Ganyin No1 are high-yield forage varieties suitable for cultivation in high-altitude areas of Tibet (4300 m above sea level). Ganyin No1 was developed from Wintergrazer-70, with the latter serving as its parent variety. Ganyin No1 was identified as a spring variety, and subsequent RNA sequencing was conducted. RNA sequencing analysis identified 4 differentially expressed genes related to vernalization and 28 genes related to photoperiod regulation. The Sc7296g5-i1G3 gene is related to the flowering inhibition of rye, which may be related to the phenotypic difference in the Ganyin No1 variety in winter and spring. This finding provides valuable insights for future research on Ganyin No1, especially in addressing feed shortages in Tibet during winter and spring.

Physiological and molecular mechanisms of ZnO quantum dots mitigating cadmium stress in Salvia miltiorrhiza.

This study delved into the physiological and molecular mechanisms underlying the mitigation of cadmium (Cd) stress in the model medicinal plant Salvia miltiorrhiza through the application of ZnO quantum dots (ZnO QDs, 3.84 nm). A pot experiment was conducted, wherein S. miltiorrhiza was subjected to Cd stress for six weeks with foliar application of 100 mg/L ZnO QDs. Physiological analyses demonstrated that compared to Cd stress alone, ZnO QDs improved biomass, reduced Cd accumulation, increased the content of photosynthetic pigments (chlorophyll and carotenoids), and enhanced the levels of essential nutrient elements (Ca, Mn, and Cu) under Cd stress. Furthermore, ZnO QDs significantly lowered Cd-induced reactive oxygen species (ROS) content, including H2O2, O2-, and MDA, while enhancing the activity of antioxidant enzymes (SOD, POD, APX, and GSH-PX). Additionally, ZnO QDs promoted the biosynthesis of primary and secondary metabolites, such as total protein, soluble sugars, terpenoids, and phenols, thereby mitigating Cd stress in S. miltiorrhiza. At the molecular level, ZnO QDs were found to activate the expression of stress signal transduction-related genes, subsequently regulating the expression of downstream target genes associated with metal transport, cell wall synthesis, and secondary metabolite synthesis via transcription factors. This activation mechanism contributed to enhancing Cd tolerance in S. miltiorrhiza. In summary, these findings shed light on the mechanisms underlying the mitigation of Cd stress by ZnO QDs, offering a potential nanomaterial-based strategy for enhancing Cd tolerance in medicinal plants.

Ordered mesoporous nanofibers mimicking vascular bundles for lithium metal batteries.

Hierarchical self-assembly with long-range order above centimeters widely exists in nature. Mimicking similar structures to promote reaction kinetics of electrochemical energy devices is of immense interest, yet remains challenging. Here, we report a bottom-up self-assembly approach to constructing ordered mesoporous nanofibers with a structure resembling vascular bundles via electrospinning. The synthesis involves self-assembling polystyrene (PS) homopolymer, amphiphilic diblock copolymer, and precursors into supramolecular micelles. Elongational dynamics of viscoelastic micelle solution together with fast solvent evaporation during electrospinning cause simultaneous close packing and uniaxial stretching of micelles, consequently producing polymer nanofibers consisting of oriented micelles. The method is versatile for the fabrication of large-scale ordered mesoporous nanofibers with adjustable pore diameter and various compositions such as carbon, SiO2, TiO2 and WO3. The aligned longitudinal mesopores connected side-by-side by tiny pores offer highly exposed active sites and expedite electron/ion transport. The assembled electrodes deliver outstanding performance for lithium metal batteries.

Unveiling synergy of strain and ligand effects in metallic aerogel for electrocatalytic polyethylene terephthalate upcycling.

Recently, there has been a notable surge in interest regarding reclaiming valuable chemicals from waste plastics. However, the energy-intensive conventional thermal catalysis does not align with the concept of sustainable development. Herein, we report a sustainable electrocatalytic approach allowing the selective synthesis of glycolic acid (GA) from waste polyethylene terephthalate (PET) over a Pd67Ag33 alloy catalyst under ambient conditions. Notably, Pd67Ag33 delivers a high mass activity of 9.7 A mgPd-1 for ethylene glycol oxidation reaction (EGOR) and GA Faradaic efficiency of 92.7 %, representing the most active catalyst for selective GA synthesis. In situ experiments and computational simulations uncover that ligand effect induced by Ag incorporation enhances the GA selectivity by facilitating carbonyl intermediates desorption, while the lattice mismatch-triggered tensile strain optimizes the adsorption of *OH species to boost reaction kinetics. This work unveils the synergistic of strain and ligand effect in alloy catalyst and provides guidance for the design of future catalysts for PET upcycling. We further investigate the versatility of Pd67Ag33 catalyst on CO2 reduction reaction (CO2RR) and assemble EGOR//CO2RR integrated electrolyzer, presenting a pioneering demonstration for reforming waste carbon resource (i.e., PET and CO2) into high-value chemicals.

Warming affects leaf light use efficiency and functional traits in alpine plants: evidence from a 4-year in-situ field experiment.

Introduction: Light use efficiency (LUE) is a crucial determinant of plant productivity, while leaf functional traits directly affect ecosystem functions. However, it remains unclear how climate warming affects LUE and leaf functional traits of dominant species in alpine meadows. Methods: We conducted a 4-year in-situ field warming experiment to investigate the eco-physiological characteristics for a dominant species (Elymus nutans) and a common species (Potentilla anserina) on the Tibetan Plateau. The leaf traits, photosynthesis and fluorescence characteristics were measured, along with the soil physical-chemical properties associated with the two species. Results and discussions: Experimental warming increased the leaf LUE, maximum photochemical efficiency, non-photochemical quenching, relative water content and specific leaf area for both species. However, there was a decrease in leaf and soil element content. Different species exhibit varying adaptability to warming. Increasing temperature significantly increased the photosynthetic rate, stomatal conductance, transpiration rate, total water content, and specific leaf volume of E. nutans; however, all these traits exhibited an opposite trend in P. anserina. Warming has a direct negative impact on leaf LUE and an indirectly enhances LUE through its effects on leaf traits. The impact of warming on plant photosynthetic capacity is primarily mediated by soil nutrients and leaf traits. These results indicate that the two different species employ distinct adaptive strategies in response to climate change, which are related to their species-specific variations. Such changes can confer an adaptive advantage for plant to cope with environmental change and potentially lead to alterations to ecosystem structure and functioning.