Integrating automated machine learning and metabolic reprogramming for the identification of microplastic in soil: A case study on soybean.

The accumulation of polyethylene microplastic (PE-MPs) in soil can significantly impact plant quality and yield, as well as affect human health and food chain cycles. Therefore, developing rapid and effective detection methods is crucial. In this study, traditional machine learning (ML) and H2O automated machine learning (H2O AutoML) were utilized to offer a powerful framework for detecting PE-MPs (0.1 %, 1 %, and 2 % by dry soil weight) and the co-contamination of PE-MPs and fomesafen (a common herbicide) in soil. The development of the framework was based on the results of the metabolic reprogramming of soybean plants. Our study stated that traditional ML exhibits lower accuracy due to the challenges associated with optimizing complex parameters. H2O AutoML can accurately distinguish between clean soil and contaminated soil. Notably, H2O AutoML can detect PE-MPs as low as 0.1 % (with 100 % accuracy) and co-contamination of PE-MPs and fomesafen (with 90 % accuracy) in soil. The VIP and SHAP analyses of the H2O AutoML showed that PE-MPs and the co-contamination of PE-MPs and fomesafen significantly interfered with the antioxidant system and energy regulation of soybean. We hope this study can provide a reliable scientific basis for sustainable development of the environment.

Quantum state tracking and control of a single molecular ion in a thermal environment.

Understanding molecular state evolution is central to many disciplines, including molecular dynamics, precision measurement, and molecule-based quantum technology. Details of this evolution are obscured when observing a statistical ensemble of molecules. Here, we report real-time observations of thermal radiation-driven transitions between individual states ("jumps") of a single molecule. We reversed these jumps through microwave-driven transitions, which resulted in a 20-fold improvement in the time the molecule dwells in a chosen state. The measured transition rates showed anisotropy in the thermal environment, pointing to the possibility of using single molecules as in situ probes for the strengths of ambient fields. Our approaches for state detection and manipulation could apply to a wide range of species, facilitating their uses in fields including quantum science, molecular physics, and ion-neutral chemistry.

A nomogram based on inflammation and nutritional biomarkers for predicting the survival of breast cancer patients.

Background: We aim to develop a new prognostic model that incorporates inflammation, nutritional parameters and clinical-pathological features to predict overall survival (OS) and disease free survival (DFS) of breast cancer (BC) patients. Methods: The study included clinicopathological and follow-up data from a total of 2857 BC patients between 2013 and 2021. Data were randomly divided into two cohorts: training (n=2001) and validation (n=856) cohorts. A nomogram was established based on the results of a multivariate Cox regression analysis from the training cohorts. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. Furthermore, decision curve analysis (DCA) was performed to assess the clinical value of the nomogram. Results: A nomogram was developed for BC, incorporating lymphocyte, platelet count, hemoglobin levels, albumin-to-globulin ratio, prealbumin level and other key variables: subtype and TNM staging. In the prediction of OS and DFS, the concordance index (C-index) of the nomogram is statistically greater than the C-index values obtained using TNM staging alone. Moreover, the time-dependent AUC, exceeding the threshold of 0.7, demonstrated the nomogram's satisfactory discriminative performance over different periods. DCA revealed that the nomogram offered a greater overall net benefit than the TNM staging system. Conclusion: The nomogram incorporating inflammation, nutritional and clinicopathological variables exhibited excellent discrimination. This nomogram is a promising instrument for predicting outcomes and defining personalized treatment strategies for patients with BC.

Angiogenesis related genes based prognostic model of glioma patients developed by multi-omics approach.

INTRODUCTION: Glioma, particularly glioblastoma (GBM), is a highly malignant brain tumor with poor prognosis despite current therapeutic approaches. The tumor microenvironment (TME), plays a crucial role in glioma progression by promoting invasion and drug resistance. Angiogenesis, the formation of new blood vessels, is a tightly regulated process involving endothelial cell activation, proliferation, and migration. In cancer, angiogenesis becomes dysregulated, leading to excessive blood vessel formation. METHODS: We enrolled bulk data of TCGA-LGG/GBM, CGGA-693, and CGGA-325 cohorts, scRNA data of GSE162631, GSE84465, and GSE138794 cohorts. Identification of malignant cells was conducted by "copycat" R package. The "AUCell" R package scored the activity of target gene set of each single cell. Consensus clustering was applied using the "ConsensusClusterPlus" R package, while tumor-infiltrating immune cells were determined using "IOBR" R package. To construct a prognostic model, we used LASSO and multiCOX algorithms based on the expression levels of the 15 hub genes, the efficacy of which was verified by KM and ROC analysis. RESULTS: We identified 4 different malignant cell subclusters in glioma and disclosed their distinct gene expression patterns and interactions within TME. We identified differentially expressed immune-related genes (DE-ARGs) in glioma and found 15 genes that were specifically expressed in the malignant glioma cell populations. Glioma cells with higher expression of these DE-ARGs were associated with gliogenesis, glial cell development, and vasculature development. We found that tumor-infiltrating monocytes were the main interacting cell type within glioma TME. Using the expression patterns of the 15 screened DE-ARGs, we categorized glioma samples into 2 molecular clusters with distinct immune features, suggesting a possible relationship between angiogenesis and immune activation and recruitment. We constructed a prognostic model based on the expression levels of the 15 DE-ARGs and evaluated its predictive ability for glioma patient outcomes, which displayed exceedingly high efficacy. CONCLUSION: We characterized different malignant cell subclusters in glioma and investigate their gene expression patterns and interactions within TME. We constructed a prognostic model based on the expression levels of the 15 DE-ARGs and evaluated its predictive ability for glioma patient outcomes, which displayed exceedingly high efficacy.

Highly efficient recycling of polyester wastes to diols using Ru and Mo dual-atom catalyst.

The chemical recycling of polyester wastes is of great significance for sustainable development, which also provides an opportunity to access various oxygen-containing chemicals, but generally suffers from low efficiency or separation difficulty. Herein, we report anatase TiO2 supported Ru and Mo dual-atom catalysts, which achieve transformation of various polyesters into corresponding diols in 100% selectivity via hydrolysis and subsequent hydrogenation in water under mild conditions (e.g., 160 °C, 4 MPa). Compelling evidence is provided for the coexistence of Ru single-atom and O-bridged Ru and Mo dual-atom sites within this kind of catalysts. It is verified that the Ru single-atom sites activate H2 for hydrogenation of carboxylic acid derived from polyester hydrolysis, and the O-bridged Ru and Mo dual-atom sites suppress hydrodeoxygenation of the resultant alcohols due to a high reaction energy barrier. Notably, this kind of dual-atom catalysts can be regenerated with high activity and stability. This work presents an effective way to reconstruct polyester wastes into valuable diols, which may have promising application potential.

Engineering of dual recognition functional aptamer-molecularly imprinted polymeric solid-phase microextraction for detecting of 17ß-estradiol in meat samples.

In this study, an enhanced selective recognition strategy was employed to construct a novel solid-phase microextraction fiber coating for the detection of 17ß-estradiol, characterized by the combination of aptamer biorecognition and molecularly imprinted polymer recognition. Benefiting from the combination of molecularly imprinted and aptamer, aptamer-molecularly imprinted (Apt-MIP) fiber coating had synergistic recognition effect. The effects of pH, ion concentration, extraction time, desorption time and desorption solvent on the adsorption capacity of Apt-MIP were investigated. The adsorption of 17ß-estradiol on Apt-MIP followed pseudo-second order kinetic model, and the Freundlich isotherm. The process was exothermic and thermodynamically spontaneous. Compared with polymers that only rely on imprinted recognition, non-imprinted recognition or aptamer affinity, Apt-MIP had the best recognition performance, which was 1.30-2.20 times that of these three materials. Furthermore, the adsorption capacity of Apt-MIP for 17ß-estradiol was 885.36-1487.52 times than that of polyacrylate and polydimethylsiloxane/divinylbenzone commercial fiber coatings. Apt-MIP fiber coating had good stability and could be reused for more than 15 times. Apt-MIP solid-phase microextraction coupled with high-performance liquid chromatography was successfully applied to the determination of 17ß-estradiol in pork, chicken, fish and shrimp samples, with satisfactory recoveries of 79.61 %-105.70 % and low limits of detection (0.03 µg/kg). This work provides new perspectives and strategies for sample pretreatment techniques based on molecular imprinting technology and improves analytical performance.

Hydroxyl carboxylate anion catalyzed depolymerization of biopolyesters and transformation to chemicals.

Upcycling biopolyesters (e.g., polyglycolic acid, PGA) into chemicals is an interesting and challenging topic. Herein, we report a novel protocol to upgrade biopolyesters derived from hydroxyl carboxylic acids over ionic liquids with a hydroxyl carboxylate anion (e.g., glycolate, lactate) into various chemicals under metal-free conditions. It is found that as hydrogen-bond donors and acceptors, hydroxyl carboxylate anions can readily activate the ester group via hydrogen bonding and decompose biopolyesters via autocatalyzed-transesterification to form hydroxyl carboxylate anion-based intermediates. These intermediates can react with various nucleophiles (e.g. H2O, methanol, amines and hydrazine) to access the corresponding acids, esters and amides under mild conditions (e.g., 40 °C). For example, 1-ethyl-3-methylimidazolium glycolate can achieve complete transformation of PGA into various chemicals such as glycolic acid, alkyl glycolates, 2-hydroxy amides, 2-(hydroxymethyl)benzimidazole, and 1,3-benzothiazol-2-ylmethanol in excellent yields via hydrolysis, alcoholysis and aminolysis, respectively. This protocol is simple, green, and highly efficient, which opens a novel way to upcycle biopolyesters to useful chemicals.

Magnetic hypercrosslinked polymer microspheres for the detection, spatial distribution, source identification and potential risks assessment of five polycyclic aromatic hydrocarbons in city river of plateau lake, Southwest China.

Polycyclic aromatic hydrocarbons (PAHs) have long been globally distributed, and almost worldwide people are exposed to varying degrees of PAHs. Aqueous medium is an important transmission route of PAHs, but the detection of PAHs in aqueous environment has been a challenge. Herein, a magnetic hypercrosslinked polymer microsphere (Fe3O4@SiO2-PS@HCP) was developed for the effective detection of PAHs. Under the effect of multiple factors (hydrophilicity, intermolecular force and molecular volume), Fe3O4@SiO2-PS@HCP shows excellent performance on the enrichment of five PAHs in aqueous environment. Fe3O4@SiO2-PS@HCP was used to capture PAHs in city river of plateau lake. In-depth data analysis showed that factory activities and traffic emissions are the main pollution sources of PAHs. Ecological, carcinogenic and non-carcinogenic risks are almost within the safe range. The carcinogenic and non-carcinogenic risks of PAHs in children are higher than adults, which needs to be taken seriously. This method breaks the dilemma that it is difficult to enrich weakly hydrophilic pollutants in aqueous media, and complements important pathways for tracing sources of pollutants and assessing associated risks. It brings methodological enlightenment into the development of environmental pollution and human health risk assessment methodology.

Rapid and comprehensive quality evaluation of Huang-qin from different origins by FT-IR and NIR spectroscopy combined with chemometrics.

INTRODUCTION: Quality evaluation of Huang-qin is significant to ensure its clinical efficacy. OBJECTIVE: This study aims to establish an accurate, rapid and comprehensive Huang-qin quality evaluation method to overcome the time-consuming and laborious shortcomings of traditional herbal medicine quality assessment methods. METHODS: The contents of baicalin, baicalein and scutellarin in Huang-qin from five different origins were analyzed by FT-IR and NIR spectra combined with multivariate data technology. The quality of Huang-qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored. RESULTS: Satisfactory prediction results of PLS models were obtained. Relatively, the model based on FT-IR combined with the PLS regression method has higher R2 and smaller RMSE than the NIR combined with the PLS method. TOPSIS and consistency analysis results showed that the quality of Huang-qin from different geographical origins was significantly different. The results showed that the quality of Huang-qin produced in Shanxi Province was the best among the five origins studied. The results also found that the quality of Huang-qin in different growing areas of the same origin was not completely consistent. The correlation study showed that altitude, sunshine duration and rainfall were the main factors that caused the quality difference of medicinal materials in different geographical origins. CONCLUSION: This study provides a reference for the rapid quantitative analysis of the active components of herbal medicine and the quality evaluation of them.

Tunable nonreciprocal metasurfaces based on a nonlinear quasi-bound state in the continuum.

Nonreciprocal devices are essential and crucial in optics for source protection and signal separation. A hybrid grating system consisting of a silicon grating, a graphene layer, and a silicon waveguide layer is employed to create a high-Q quasi-BIC (bound state in the continuum). Then, the high-Q properties of the quasi-BIC are harnessed to enhance the third-order nonlinear effect of silicon, thereby improving the nonreciprocal characteristics of the device. The nonreciprocal transmittance ratio of the device can be tunable by adjusting the graphene Fermi energy level, achieving tunability ranging from 0.0865 to 30.57 dB. It also enables the best performance of the device over a wider range of frequency bands. This study provides a new, to the best of our knowledge, method for designing tunable nonreciprocal devices with a wide range of potential applications.

Simultaneous and sensitive detection of methylparaben and its metabolites by using molecularly imprinted solid-phase microextraction fiber array technique.

BACKGROUND: Methylparaben (MP), a commonly used antibacterial preservative, is widely used in personal care products, foods, and pharmaceuticals. MP and its metabolites are easy to enter the water environment, and their exposure and accumulation have negative effects on the ecological environment and human health, and have endocrine disrupting activity and potential physiological toxicity. It is still the primary issue of environmental analysis and ecological risk assessment to develop simple and reliable methods for simultaneous sensitive detection of these compounds in environmental water. RESULTS: In this paper, a flexible molecularly imprinted fiber array strategy is proposed for simultaneous enrichment and detection of trace MP and its four main metabolites. The experimental results showed that the three-fiber imprinted fiber array constructed by MP imprinted fiber had the best effect on the simultaneous enrichment of these five target analytes. The enrichment capacity of the imprinted fiber array was 214-456 times, 314-1201 times and 38-685 times that of commercial PA, PDMS and PDMS/DVB fiber arrays, respectively. The limit of detection (LOD) of this method was 0.033 µg L-1. The spiked recovery rate was 86.78-113.96 %, and RSD was less than 9.17 %. In addition, this molecularly imprinted SPME fiber array has good stability, long service life and can be used repeatedly at least 100 times. SIGNIFICANCE: This molecularly imprinted fiber array strategy can flexibly assemble different molecularly imprinted SPME fibers together, effectively improve the enrichment ability and detection sensitivity, and achieve simultaneous selective enrichment and detection of several analytes. This is an easy, efficient and reliable method for monitoring several trace analytes simultaneously in intricate environmental matrices.

Label-free electrochemical aptasensor for ultrasensitive lead ion detection based on flower-like AuNPs@MoS2 and core-shell Pt@Pd bimetallic nanoparticles.

A signal-amplified platform was designed to construct a label-free electrochemical aptasensor for lead ions (Pb2+) assay. First, flower-like molybdenum disulfide-supported AuNPs (AuNPs@MoS2) nanocomposites were synthesized and used as substrates for modifying the electrode. The AuNPs@MoS2 material possessed large surface area and superior biocompatibility, which was beneficial to improve the loading amount of the complementary DNA (cDNA) and amplified the response signal. Importantly, the prepared core-shell Pt@Pd bimetallic nanoparticles (Pt@PdNPs) were used to conjugate with redox marker thionine (Thi) and aptamer (Apt) for further signal amplification; the obtained signal probes (Thi-Pt@PdNPs-Apt) were connected by the cDNA assembled on the electrode through DNA hybridization. Differential pulse voltammetry was performed to monitor the signal of Thi. After incubating of aptasensor with Pb2+, the specific recognition of Pb2+ and Apt resulted in the dissociation of aptamer-cDNA complex, thereby the Thi-Pt@PdNPs-Apt separated from the electrode surface and decreased current response was obtained. The prepared electrochemical sensor exhibited linear response to Pb2+ in the range 5.0 × 10-4-100 nM and a detection limit of 1.0 × 10-4 nM was achieved. The sensor was applied to the determination of Pb2+ in actual sample with high sensitivity and accuracy, demonstrating potential applications in heavy metal monitoring.

Molecular imprinting-based Ru@SiO2-embedded covalent organic frameworks composite for electrochemiluminescence detection of cyanidin-3-O-glucoside.

Cyanidin-3-O-glucoside (C3G), a natural antioxidant, plays multiple physiological or pathological roles in maintaining human health; thereby, designing advanced sensors to achieve specific recognition and high-sensitivity detection of C3G is significant. Herein, an imprinted-type electrochemiluminescence (ECL) sensing platform was developed using core-shell Ru@SiO2-CMIPs, which were prepared by covalent organic framework (COF)-based molecularly imprinted polymers (CMIPs) embedded in luminescent Ru@SiO2 cores. The C3G-imprinted COF shell not only helps generate a steady-enhanced ECL signal, but also enables specific recognition of C3G. When C3G is bound to Ru@SiO2-CMIPs with abundant imprinted cavities, resonance energy transfer (RET) behavior is triggered, resulting in a quenched ECL response. The constructed Ru@SiO2-CMIPs nanoprobes exhibit ultra-high sensitivity, absolute specificity, and an ultra-low detection limit (0.15 pg mL-1) for analyzing C3G in food matrices. This study provides a means to construct an efficient and reliable molecular imprinting-based ECL sensor for food analysis.

Comparisons of long-term clinical outcomes with left bundle branch pacing, left ventricular septal pacing, and biventricular pacing for cardiac resynchronization therapy.

BACKGROUND: Left bundle branch pacing (LBBP) and left ventricular septal pacing (LVSP) are referred to as left bundle branch area pacing. OBJECTIVE: This study investigated whether long-term clinical outcomes differ in patients undergoing LBBP, LVSP, and biventricular pacing (BiVP) for cardiac resynchronization therapy (CRT). METHODS: Consecutive patients with reduced left ventricular ejection fraction (LVEF <50%) undergoing CRT were prospectively enrolled if they underwent successful LBBP, LVSP, or BiVP. The primary composite end point was all-cause mortality or heart failure hospitalization. Secondary end points included all-cause mortality, heart failure hospitalization, and echocardiographic measures of reverse remodeling. RESULTS: A total of 259 patients (68 LBBP, 38 LVSP, and 153 BiVP) were observed for a mean duration of 28.8 ± 15.8 months. LBBP was associated with a significantly reduced risk of the primary end point by 78% compared with both BiVP (7.4% vs 41.2%; adjusted hazard ratio [aHR], 0.22 [0.08-0.57]; P = .002) and LVSP (7.4% vs 47.4%; aHR, 0.22 [0.08-0.63]; P = .004]. The adjusted risk of all-cause mortality was significantly higher in LVSP than in BiVP (31.6% vs 7.2%; aHR, 3.19 [1.38-7.39]; P = .007) but comparable between LBBP and BiVP (2.9% vs 7.2%; aHR, 0.33 [0.07-1.52], P = .155). Propensity score adjustment also obtained similar results. LBBP showed a higher rate of echocardiographic response (ΔLVEF ≥10%: 60.0% vs 36.2% vs 16.1%; P < .001) than BiVP or LVSP. CONCLUSION: LBBP yielded long-term clinical outcomes superior to those of BiVP and LVSP. The role of LVSP for CRT needs to be reevaluated because of its high mortality risk.

Highly Efficient Electrosynthesis of Glycine over an Atomically Dispersed Iron Catalyst.

Glycine is a nonessential amino acid that plays a vital role in various biological activities. However, the conventional synthesis of glycine requires sophisticated procedures or toxic feedstocks. Herein, we report an electrochemical pathway for glycine synthesis via the reductive coupling of oxalic acid and nitrate or nitrogen oxides over atomically dispersed Fe-N-C catalysts. A glycine selectivity of 70.7% is achieved over Fe-N-C-700 at -1.0 V versus RHE. Synergy between the FeN3C structure and pyrrolic nitrogen in Fe-N-C-700 facilitates the reduction of oxalic acid to glyoxylic acid, which is crucial for producing glyoxylic acid oxime and glycine, and the FeN3C structure could reduce the energy barrier of *HOOCCH2NH2 intermediate formation thus accelerating the glyoxylic acid oxime conversion to glycine. This new synthesis approach for value-added chemicals using simple carbon and nitrogen sources could provide sustainable routes for organonitrogen compound production.

Alkyl sulfonate surfactant mediates electroreduction of carbon dioxide to ethylene or ethanol over hydroxide-derived copper catalysts.

For CO2 electroreduction (CO2ER) to C2 compounds, it is generally accepted that the formation of ethylene and ethanol shares the same intermediate, *HCCOH. The majority of studies have achieved high faradaic efficiency (FE) towards ethylene, but faced challenges to get high ethanol FE. Herein, we present an alkyl sulfonate surfactant (e.g., sodium dodecyl sulfonate, SDS) mediated CO2ER to a C2 product over an in situ generated Cu catalyst (Cu@SDS) from SDS-modified Cu(OH)2. It achieves the CO2ER to ethylene as the sole C2 product at low applied voltages with a FE of 55% at -0.6 V vs. RHE and to ethanol as the main product at potentials ≥0.7 V with a maximum FE of 64% and a total C2 FE of 86% at -0.8 V, with a current density of 231 mA cm-2 in a flow cell. Mechanism investigation indicates that SDS modifies the oxidation state of the in situ formed Cu species in Cu@SDS, thus tuning the catalyst activity for CO2ER and lowering the C-C coupling energy barrier; meanwhile, it tunes the adsorption mode of the *HCCOH intermediates on the catalyst, thus mediating the selectivity of CO2ER towards C2 products.

Polyarene Oxides with Tunable Quinone Units for Photocatalytic CO2 Reduction: A Simple Strategy toward Effective and Selective Catalysts.

The photocatalytic transformation of carbon dioxide (CO2) into valuable chemicals is a challenging process that requires effective and selective catalysts. However, most polymer-based photocatalysts with electron donor-acceptor (D-A) structures are synthesized with a fixed D-A ratio by using expensive monomers. Herein, we report a simple strategy to prepare polyarene oxides (PAOs) with quinone structural units via oxidation treatment of polyarene (PA). The resultant PAOs show tunable D-A structures and electronic band positions depending on the degree of oxidation, which can catalyze the photoreduction of CO2 with water under visible light irradiation, generating CO as the sole carbonaceous product without H2 generation. Especially, the PAO with an oxygen content of 17.6% afforded the highest CO production rate of 161.9 µmol g-1 h-1. It is verified that the redox transformation between quinone and phenolic hydroxyl in PAOs achieves CO2 photoreduction coupled with water oxidation. This study provides a facile way to access conjugated polymers with a tunable D-A structure and demonstrates that the resultant PAOs are promising photocatalysts for CO2 reduction.

Cost-effective prognostic evaluation of breast cancer: using a STAR nomogram model based on routine blood tests.

Background: Breast cancer (BC) is the most common and prominent deadly disease among women. Predicting BC survival mainly relies on TNM staging, molecular profiling and imaging, hampered by subjectivity and expenses. This study aimed to establish an economical and reliable model using the most common preoperative routine blood tests (RT) data for survival and surveillance strategy management. Methods: We examined 2863 BC patients, dividing them into training and validation cohorts (7:3). We collected demographic features, pathomics characteristics and preoperative 24-item RT data. BC risk factors were identified through Cox regression, and a predictive nomogram was established. Its performance was assessed using C-index, area under curves (AUC), calibration curve and decision curve analysis. Kaplan-Meier curves stratified patients into different risk groups. We further compared the STAR model (utilizing HE and RT methodologies) with alternative nomograms grounded in molecular profiling (employing second-generation short-read sequencing methodologies) and imaging (utilizing PET-CT methodologies). Results: The STAR nomogram, incorporating subtype, TNM stage, age and preoperative RT data (LYM, LYM%, EOSO%, RDW-SD, P-LCR), achieved a C-index of 0.828 in the training cohort and impressive AUCs (0.847, 0.823 and 0.780) for 3-, 5- and 7-year OS rates, outperforming other nomograms. The validation cohort showed similar impressive results. The nomogram calculates a patient's total score by assigning values to each risk factor, higher scores indicating a poor prognosis. STAR promises potential cost savings by enabling less intensive surveillance in around 90% of BC patients. Compared to nomograms based on molecular profiling and imaging, STAR presents a more cost-effective, with potential savings of approximately $700-800 per breast cancer patient. Conclusion: Combining appropriate RT parameters, STAR nomogram could help in the detection of patient anemia, coagulation function, inflammation and immune status. Practical implementation of the STAR nomogram in a clinical setting is feasible, and its potential clinical impact lies in its ability to provide an early, economical and reliable tool for survival prediction and surveillance strategy management. However, our model still has limitations and requires external data validation. In subsequent studies, we plan to mitigate the potential impact on model robustness by further updating and adjusting the data and model.

[Discussing the basic ecological relations of sand dune vegetation process]. / è®ºæ²™ä¸˜æ¤è¢«è¿‡ç¨‹çš„åŸºæœ¬ç”Ÿæ€å ³ç³».

Dune is often considered as a degraded ecosystem. Natural vegetation restoration and stable artificial vegetation construction are the basic means restoring dune ecosystem. Based on long-term study of dune ecosystem, by taking into consideration both the philosophical principles of unity of opposites and dynamic change, and related ecological theories, we put forward some ecological relations that should be paid attention to in the study of vegetation assembly from the perspective of the uniqueness of dune ecosystem. We discussed the necessity of coupling relationships of scale-pattern-process and the transformation of synergy-tradeoff relationships, interpreted the importance of distinguishing sand dune stabilized and shifting phases, disturbance and stress, wind erosion and sand burial in the study of vegetation process. We further explored the applied value of niche law or neutral law in the study of dune vegetation process. Finally, we discussed the issues that should be paid attention to in the study of dune vegetation process from the aspects of adaptability to aeolian activities and drought tolerance, physiological and reproductive process, sexual and asexual reproduction of plants. This study would provide theoretical supports for vegetation restoration and stable vegetation construction of dune ecosystem.