Comparison of the burden of digestive diseases between China and the United States from 1990 to 2019.

Introduction: China has experienced unprecedented transformations unseen in a century and is gradually progressing toward an emerging superpower. The epidemiological trends of digestive diseases in the United States (the US) have significant prescient effects on China. Methods: We extracted data on 18 digestive diseases from the Global Burden of Diseases 2019 Data Resource. Linear regression analysis conducted by the JoinPoint software assessed the average annual percentage change of the burden. We performed subgroup analyses based on sex and age group. Results: In 2019, there were 836.01 and 180.91 million new cases of digestive diseases in China and the US, causing 1558.01 and 339.54 thousand deaths. The age-standardized incidence rates of digestive diseases in China and the US were 58417.87/100,000 and 55018.65/100,000 respectively, resulting in age-standardized mortality rates of 81.52/100,000 and 60.88/100,000. The rates in China annually decreased by 2.149% for mortality and 2.611% for disability-adjusted life of year (DALY). The mortality and DALY rates of the US, respectively, had average annual percentage changes of -0.219 and -0.251. Enteric infections and cirrhosis and other chronic liver diseases accounted for the highest incidence and prevalence in both counties, respectively. The burden of multiple digestive diseases exhibited notable sex disparities. The middle-old persons had higher age-standardized prevalence rates. Conclusion: China bore a greater burden of digestive diseases, and the evolving patterns were more noticeable. Targeted interventions and urgent measures should be taken in both countries to address the specific burden of digestive diseases based on their different epidemic degree.

N-Salicyloyl Tryptamine Derivatives as Potent Neuroinflammation Inhibitors by Constraining Microglia Activation via a STAT3 Pathway.

Neuroinflammation is an important factor that exacerbates neuronal death and abnormal synaptic function in neurodegenerative diseases (NDDs). Due to the complex pathogenesis and the presence of blood-brain barrier (BBB), no effective clinical drugs are currently available. Previous results showed that N-salicyloyl tryptamine derivatives had the potential to constrain the neuroinflammatory process. In this study, 30 new N-salicyloyl tryptamine derivatives were designed and synthesized to investigate a structure-activity relationship (SAR) for the indole ring of tryptamine in order to enhance their antineuroinflammatory effects. Among them, both in vitro and in vivo compound 18 exerted the best antineuroinflammatory effects by suppressing the activation of microglia, which is the culprit of neuroinflammation. The underlying mechanism of its antineuroinflammatory effect may be related to the inhibition of transcription, expression and phosphorylation of signal transducer and activator of transcription 3 (STAT3) that subsequently regulated downstream cyclooxygenase-2 (COX-2) expression and activity. With its excellent BBB permeability and pharmacokinetic properties, compound 18 exhibited significant neuroprotective effects in the hippocampal region of lipopolysaccharides (LPS)-induced mice than former N-salicyloyl tryptamine derivative L7. In conclusion, compound 18 has provided a new approach for the development of highly effective antineuroinflammatory therapeutic drugs targeting microglia activation.

Exogenous silicon induces aluminum tolerance in white clover (Trifolium repens) by reducing aluminum uptake and enhancing organic acid secretion.

Excessive aluminum (Al) in acidic soils is a primary factor that hinders plant growth. The objective of the present study was to investigate the effect and physiological mechanism of exogenous silicon (Si) in alleviating aluminum toxicity. Under hydroponic conditions, 4 mM Al significantly impeded the growth of white clover; however, pretreatments with 1 mM Si mitigated this inhibition, as evidenced by notable changes in growth indicators and physiological parameters. Exogenous silicon notably increased both shoot and root length of white clover and significantly decreased electrolyte leakage (EL) and malondialdehyde (MDA) content compared to aluminum treatments. This positive effect was particularly evident in the roots. Further analysis involving hematoxylin staining, scanning electron microscopy (SEM), and examination of organic acids (OAs) demonstrated that silicon relieved the accumulation of bioactive aluminum and ameliorated damage to root tissues in aluminum-stressed plants. Additionally, energy-dispersive X-ray (EDX) analysis revealed that additional silicon was primarily distributed in the root epidermal and cortical layers, effectively reducing the transport of aluminum and maintaining the balance of exchangeable cations absorption. These findings suggest that gradual silicon deposition in root tissues effectively prevents the absorption of biologically active aluminum, thereby reducing the risk of mineral nutrient deficiencies induced by aluminum stress, promoting organic acids exudation, and compartmentalizing aluminum in the outer layer of root tissues. This mechanism helps white clover alleviate the damage caused by aluminum toxicity.

The complete mitochondrial genome of the rodent flea Nosopsyllus laeviceps: genome description, comparative analysis, and phylogenetic implications.

BACKGROUND: Fleas are one of the most common and pervasive ectoparasites worldwide, comprising at least 2500 valid species. They are vectors of several disease-causing agents, such as Yersinia pestis. Despite their significance, however, the molecular genetics, biology, and phylogenetics of fleas remain poorly understood. METHODS: We sequenced, assembled, and annotated the complete mitochondrial (mt) genome of the rodent flea Nosopsyllus laeviceps using next-generation sequencing technology. Then we combined the new mitogenome generated here with mt genomic data available for 23 other flea species to perform comparative mitogenomics, nucleotide diversity, and evolutionary rate analysis. Subsequently, the phylogenetic relationship within the order Siphonaptera was explored using the Bayesian inference (BI) and maximum likelihood (ML) methods based on concentrated data for 13 mt protein-coding genes. RESULTS: The complete mt genome of the rodent flea N. laeviceps was 16,533 base pairs (bp) in a circular DNA molecule, containing 37 typical genes (13 protein-coding genes, 22 transfer RNA [tRNA] genes, and two ribosomal RNA [rRNA] genes) with one large non-coding region (NCR). Comparative analysis among the order Siphonaptera showed a stable gene order with no gene arrangement, and high AT content (76.71-83.21%) with an apparent negative AT and GC skew except in three fleas Aviostivalius klossi bispiniformis, Leptopsylla segnis, and Neopsylla specialis. Moreover, we found robust evidence that the cytochrome c oxidase subunit 1 (cox1) gene was the most conserved protein-coding gene (Pi = 0.15, non-synonymous/synonymous [Ka/Ks] ratio = 0.13) of fleas. Phylogenomic analysis conducted using two methods revealed different topologies, but both results strongly indicated that (i) the families Ceratophyllidae and Leptopsyllidae were paraphyletic and were the closest to each other, and (ii) the family Ctenophthalmidae was paraphyletic. CONCLUSIONS: In this study, we obtained a high-quality mt genome of the rodent flea N. laeviceps and performed comparative mitogenomics and phylogeny of the order Siphonaptera using the mt database. The results will enrich the mt genome data for fleas, lay a foundation for the phylogenetic analysis of fleas, and promote the evolutionary analysis of Siphonaptera.

Target Identification and Mechanistic Characterization of Indole Terpenoid Mimics: Proper Spindle Microtubule Assembly Is Essential for Cdh1-Mediated Proteolysis of CENP-A.

Centromere protein A (CENP-A), a histone H3 variant specific to centromeres, is crucial for kinetochore positioning and chromosome segregation. However, its regulatory mechanism in human cells remains incompletely understood. A structure-activity relationship (SAR) study of the cell-cycle-arresting indole terpenoid mimic JP18 leads to the discovery of two more potent analogs, (+)-6-Br-JP18 and (+)-6-Cl-JP18. Tubulin is identified as a potential cellular target of these halogenated analogs by using the drug affinity responsive target stability (DARTS) based method. X-ray crystallography analysis reveals that both molecules bind to the colchicine-binding site of ß-tubulin. Treatment of human cells with microtubule-targeting agents (MTAs), including these two compounds, results in CENP-A accumulation by destabilizing Cdh1, a co-activator of the anaphase-promoting complex/cyclosome (APC/C) E3 ubiquitin ligase. This study establishes a link between microtubule dynamics and CENP-A accumulation using small-molecule tools and highlights the role of Cdh1 in CENP-A proteolysis.

Terahertz s-SNOM Imaging of a Single Cell with Nanoscale Resolution.

Terahertz scattering scanning near-field optical microscopy is a robust spectral detection technique with a nanoscale resolution. However, there are still major challenges in investigating the heterogeneity of cell membrane components in individual cells. Here, we present a novel and comprehensive analytical approach for detecting and investigating heterogeneity in cell membrane components at the single-cell level. In comparison to the resolution of the topographical atomic force microscopy image, the spatial resolution of the terahertz near-field amplitude image is 3 times that of the former. This ultrafine resolution enables the compositional distribution in the cell membrane, such as the distribution of extracellular vesicles, to be finely characterized. Furthermore, via extraction of the near-field absorption images at specific frequencies, the visualization and compositional difference analysis of cell membrane components can be presented in detail. These findings have significant implications for the intuitive and visual analysis of cell development and disease evolutionary pathways.

[Meta-analysis of plant restoration impacts on soil microbial community structure in mining areas]. / 植被恢复对矿区土壤微生物群落结构影响的整合分析.

Mining causes severe damage to soil ecosystems. Vegetation restoration in abandoned mine areas is an inevitable requirement for sustainable development. Soil microbes, as the most active component of soil organic matter, play a crucial role in the transformation of carbon, nitrogen, phosphorus, and other elements. They are often used as indicators to assess the extent of vegetation restoration in ecologically fragile areas. However, the impacts of vegetation restoration on soil microbial community structure in mining areas at the global scale remains largely unknown. Based on 310 paired observations from 44 papers, we employed the meta-analysis approach to examine the influence of vegetation restoration on soil microbial abundance and biomass in mining area. The results indicated that vegetation restoration significantly promotes soil microbial biomass in mining areas. In comparison to bare soil, vegetation restoration leads to a significant 95.1% increase in soil microbial biomass carbon and a 87.8% increase in soil microbial biomass nitrogen. The abundance of soil bacteria, fungi, and actinomycetes are significantly increased by 1005.4%, 472.4%, and 177.7%, respectively. Among various vegetation restoration types, the exclusive plan-ting of trees exhibits the most pronounced promotion effect on soil microbial biomass and population, which results in a significant increase of 540.3% in soil fungi and 104.5% in actinomycetes, along with a respective enhancement of 110.3% and 106.4% in microbial biomass carbon and nitrogen. Model selection results revealed that soil satura-ted water content and vegetation restoration history contribute most significantly to the abundance of soil bacteria and fungi. Soil available nitrogen has the most significant impact on the abundance of actinomycetes and microbial biomass carbon, while soil available phosphorus emerges as a crucial factor affecting microbial biomass nitrogen. This research could contribute to understanding the relationship between vegetation restoration and the structure of soil microbial communities in mining areas, and providing scientific support for determining appropriate vegetation restoration types in mining areas.

Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images.

Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their diagnosis and treatment. The rapid advancement of artificial intelligence in imaging technology holds promise for the development of AI-based radiomics predictive models. These models could potentially enable the automatic detection and diagnosis of intracranial aneurysms, assess their status, and predict outcomes, thereby assisting in the creation of personalized treatment plans. In addition, these techniques could improve diagnostic efficiency for physicians and patient prognoses. This article aims to review the progress of artificial intelligence radiomics in the study of intracranial aneurysms, addressing the challenges faced and future prospects, in hopes of introducing new ideas for the precise diagnosis and treatment of intracranial aneurysms.

Synergetic Responses of Multiple Functions Induced by Phase Transition in Molecular Materials.

Materials that integrate magnetism, electricity and luminescence can not only improve the operational efficiency of devices, but also potentially generate new functions through their coupling. Therefore, multifunctional synergistic effects have broad application prospects in fields such as optoelectronic devices, information storage and processing, and quantum computing. However, in the research field of molecular materials, there are few reports on the synergistic multifunctional properties. The main reason is that there is insufficient awareness of how to obtain such material. In this brief review, we summarized the molecular materials with this characteristic. The structural phase transition of substances will cause changes in their physical properties, as the electronic configurations of the active unit in different structural phases are different. Therefore, we will classify and describe the multifunctional synergistic complexes based on the structural factors that cause the first-order phase transition of the complexes. This enables us to quickly screen complexes with synergistic responses to these properties through structural phase transitions, providing ideas for studying the synergistic response of physical properties in molecular materials.

Enhanced and asymmetric signatures of hybridization at climatic margins: Evidence from closely related dioecious fig species.

Hybridization plays a significant role in biological evolution. However, it is not clear whether ecological contingency differentially influences likelihood of hybridization, particularly at ecological margins where parental species may exhibit reduced fitnesses. Moreover, it is unknown whether future ecosystem change will increase the prevalence of hybridization. Ficus heterostyla and F. squamosa are closely related species co-distributed from southern Thailand to southwest China where hybridization, yielding viable seeds, has been documented. As a robust test of ecological factors driving hybridization, we investigated spatial hybridization signatures based on nuclear microsatellites from extensive population sampling across a widespread contact range. Both species showed high population differentiation and strong patterns of isolation by distance. Admixture estimates exposed asymmetric interspecific gene flow. Signatures of hybridization increase significantly towards higher latitude zones, peaking at the northern climatic margins. Geographic variation in reproductive phenology combined with ecologically challenging marginal habitats may promote this phenomenon. Our work is a first systematic evaluation of such patterns in a comprehensive, latitudinally-based clinal context, and indicates that tendency to hybridize appears strongly influenced by environmental conditions. Moreover, that future climate change scenarios will likely alter and possibly augment cases of hybridization at ecosystem scales.

Synergistic dual sites of Zn-Mg on hierarchical porous carbon as an advanced oxygen reduction electrocatalyst for Zn-air batteries.

The development of cost-effective and high-performance non-noble metal catalysts for the oxygen reduction reaction (ORR) holds substantial promise for real-world applications. Introducing a secondary metal to design bimetallic sites enables effective modulation of a metal-nitrogen-carbon (M-N-C) catalyst's electronic structure, providing new opportunities for enhancing ORR activity and stability. Here, we successfully synthesized an innovative hierarchical porous carbon material with dual sites of Zn and Mg (Zn/Mg-N-C) using polymeric ionic liquids (PILs) as precursors and SBA-15 as a template through a bottom-up approach. The hierarchical porous structure and optimized Zn-Mg bimetallic catalytic centers enable Zn/Mg-N-C to exhibit a half-wave potential of 0.89 V, excellent stability, and good methanol tolerance in 0.1 M KOH solution. Theoretical calculations indicated that the Zn-Mg bimetallic sites in Zn/Mg-N-C effectively lowered the ORR energy barrier. Furthermore, the Zn-air batteries assembled based on Zn/Mg-N-C demonstrated an outstanding peak power density (298.7 mW cm-2) and superior cycling stability. This work provides a method for designing and synthesizing bimetallic site catalysts for advanced catalysis.

Effects of seasonal precipitation regimes on microbial biomass and extracellular enzyme activity during shrub foliar litter decomposition in a subtropical forest.

Elucidating the mechanisms underlying microbial biomass and extracellular enzyme activity responses to the seasonal precipitation regime during foliar litter decomposition is highly important for understanding the material cycle of forest ecosystems in the context of global climate change; however, the specific underlying mechanisms remain unclear. Hence, a precipitation manipulation experiment involving a control (CK) and treatments with decreased precipitation in the dry season and extremely increased precipitation in the wet season (IE) and decreased precipitation in the dry season and proportionally increased precipitation in the wet season (IP) was conducted in a subtropical evergreen broad-leaved forest in China from October 2020 to October 2021. The moisture, microbial biomass, and extracellular enzyme activities of foliar litter from two dominant shrub species, Phyllostachys violascens and Alangium chinense, were measured at six stages during the dry and wet seasons. The results showed that (1) both IE and IP significantly decreased the microbial biomass carbon and microbial biomass nitrogen content and the activities of ß-1,4-glucosidase, ß-1,4-N-acetylglucosaminidase, acid phosphatase and cellulase in the dry season, while the opposite effects were observed in the wet season. (2) Compared with those of IE, the effects of IP on foliar litter microbial biomass and extracellular enzyme activity were more significant. (3) The results from the partial least squares model indicated that extracellular enzyme activity during foliar litter decomposition was strongly controlled by the foliar litter water content, microbial biomass nitrogen, the ratio of total carbon to total phosphorus, foliar litter total carbon, and foliar litter total nitrogen. These results provide an important theoretical basis for elucidating the microbial mechanisms driving litter decomposition in a subtropical forest under global climate change scenarios.

Stand spatial structure and microbial diversity are key drivers of soil multifunctionality during secondary succession in degraded karst forests.

Studying the relationship between biodiversity and ecosystem multifunctionality (the ability of ecosystems to provide multiple ecosystem functions) (BEMF) is a current hotspot in ecology research. Previous studies on BEMF emphasized the role of plant and microbial diversity but rarely mention stand spatial structure. To investigate the effect of stand spatial structure on BEMF, this study established 30 forest dynamic plots in three natural restoration stages (shrubbery, secondary growth forest, and old-growth forest) in Maolan National Nature Reserve, Guizhou province, China. A positive response in soil multifunctionality (SMF), plant species diversity, stand spatial structure, and fungal ß diversity (p < 0.05) followed natural restoration. However, bacterial ß diversity showed a negative response (p < 0.05), while microbial α diversity remained unchanged (p > 0.05). These results based on a structural equation model showed that plant species diversity had no direct or indirect effect on SMF, soil microbial diversity was the only direct driver of SMF, and stand spatial structure indirectly affected SMF through soil microbial diversity. The random forest model showed that soil microbial ß diversity and the Shannon-Wiener index of the diameter at breast height for woody plant species were the optimal variables to characterize SMF and soil microbial diversity, respectively. These results suggested that natural restoration promoted SMF, and microbial diversity had a direct positive effect on SMF. In the meantime, stand spatial structure had a significant indirect effect on SMF, while plant species diversity did not. Future work on degraded karst forest restoration should direct more attention to the role of the stand spatial structure and emphasize the importance of biodiversity.

Predicting Lung Cancer Survival to the Future: Population-Based Cancer Survival Modeling Study.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality globally, with late diagnoses often resulting in poor prognosis. In response, the Lung Ambition Alliance aims to double the 5-year survival rate by 2025. OBJECTIVE: Using the Taiwan Cancer Registry, this study uses the survivorship-period-cohort model to assess the feasibility of achieving this goal by predicting future survival rates of patients with lung cancer in Taiwan. METHODS: This retrospective study analyzed data from 205,104 patients with lung cancer registered between 1997 and 2018. Survival rates were calculated using the survivorship-period-cohort model, focusing on 1-year interval survival rates and extrapolating to predict 5-year outcomes for diagnoses up to 2020, as viewed from 2025. Model validation involved comparing predicted rates with actual data using symmetric mean absolute percentage error. RESULTS: The study identified notable improvements in survival rates beginning in 2004, with the predicted 5-year survival rate for 2020 reaching 38.7%, marking a considerable increase from the most recent available data of 23.8% for patients diagnosed in 2013. Subgroup analysis revealed varied survival improvements across different demographics and histological types. Predictions based on current trends indicate that achieving the Lung Ambition Alliance's goal could be within reach. CONCLUSIONS: The analysis demonstrates notable improvements in lung cancer survival rates in Taiwan, driven by the adoption of low-dose computed tomography screening, alongside advances in diagnostic technologies and treatment strategies. While the ambitious target set by the Lung Ambition Alliance appears achievable, ongoing advancements in medical technology and health policies will be crucial. The study underscores the potential impact of continued enhancements in lung cancer management and the importance of strategic health interventions to further improve survival outcomes.

Compilation of a self-management assessment scale for postoperative patients with aortic dissection.

Objective: The aim of this research was to compile a self-management assessment scale for patients with aortic dissection (AD). The questionnaire is useful in making the patient aware of the need for post-operative care in order to contribute to improving the outcome and quality of life. Methods: The initial version of the "postoperative self-management assessment scale for patients with aortic dissection" was developed using the Delphi expert consultation method based on qualitative research results, consultation of self-management-related literature, reference to the existing self-management scale, and self-efficacy theory, combined with the disease characteristics of AD. By using the convenience sampling method, a total of 201 patients with AD who had undergone surgery were selected as the research participants. The initial version of the scale was used for follow-up investigation, and the scale entries were evaluated and exploratory factor analysis carried out to form the formal version of the "postoperative self-management assessment scale for patients with aortic dissection." A total of 214 patients with AD after surgery were selected as the research participants. The formal version of the scale was used for follow-up investigation, and its reliability and validity were evaluated. Results: The formal version of the scale had 6 dimensions and 35 entries. The Cronbach's α coefficient for the total scale was 0.908, the split-half reliability was 0.790, and the test-retest reliability after 2 weeks was 0.471. The content validity index of the total scale was 0.963. Exploratory factor analysis yielded six common factors, and the cumulative contribution rate of variance was 66.303%. Confirmatory factor analysis showed that except for the incremental fit index, Tucker-Lewis index, and comparative fit index >0.85, slightly lower than 0.90, χ 2/df <3, root mean square of approximation <0.08, parsimonious goodness-of-fit index, and parsimonious normed fit index >0.50; all other model fitting requirements were satisfied, indicating that the model fitting was acceptable. Conclusion: We compiled the postoperative self-management assessment scale for patients with AD, which has demonstrated excellent reliability and validity and can be used as a tool to evaluate the postoperative self-management level in patients with aortic dissection.

Development and validation of a nomogram to predict the risk of residual low back pain after tubular microdiskectomy of lumbar disk herniation.

OBJECTIVE: Tubular microdiskectomy (tMD) is one of the most commonly used for treating lumbar disk herniation. However, there still patients still complain of persistent postoperative residual low back pain (rLBP) postoperatively. This study attempts to develop a nomogram to predict the risk of rLBP after tMD. METHODS: The patients were divided into non-rLBP (LBP VAS score < 2) and rLBP (LBP VAS score ≥ 2) group. The correlation between rLBP and these factors were analyzed by multivariate logistic analysis. Then, a nomogram prediction model of rLBP was developed based on the risk factors screened by multivariate analysis. The samples in the model are randomly divided into training and validation sets in a 7:3 ratio. The Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the diskrimination, calibration and clinical value of the model, respectively. RESULTS: A total of 14.3% (47/329) of patients have persistent rLBP. The multivariate analysis suggests that higher preoperative LBP visual analog scale (VAS) score, lower facet orientation (FO), grade 2-3 facet joint degeneration (FJD) and moderate-severe multifidus fat atrophy (MFA) are risk factors for postoperative rLBP. In the training and validation sets, the ROC curves, calibration curves, and DCAs suggested the good diskrimination, predictive accuracy between the predicted probability and actual probability, and clinical value of the model, respectively. CONCLUSION: This nomogram including preoperative LBP VAS score, FO, FJD and MFA can serve a promising prediction model, which will provide a reference for clinicians to predict the rLBP after tMD.

Identification of Panax notoginseng origin using terahertz precision spectroscopy and neural network algorithm.

Panax notoginseng (P. notoginseng), a Chinese herb containing various saponins, benefits immune system in medicines development, which from Wenshan (authentic cultivation) is often counterfeited by others for large demand and limited supply. Here, we proposed a method for identifying P. notoginseng origin combining terahertz (THz) precision spectroscopy and neural network. Based on the comparative analysis of four qualitative identification methods, we chose high-performance liquid chromatography (HPLC) and THz spectroscopy to detect 252 samples from five origins. After classifications using Convolutional Neural Networks (CNNs) model, we found that the performance of THz spectra was superior to that of HPLC. The underlying mechanism is that there are clear nonlinear relations among the THz spectra and the origins due to the wide spectra and multi-parameter characteristics, which makes the accuracy of five-classification origin identification up to 97.62%. This study realizes the rapid, non-destructive and accurate identification of P. notoginseng origin, providing a practical reference for herbal medicine.

Genome-wide identification of Aux/IAA gene family in white clover (Trifolium repens L.) and functional verification of TrIAA18 under different abiotic stress.

BACKGROUND: White clover (Trifolium repens L.) is an excellent leguminous cool-season forage with a high protein content and strong nitrogen-fixing ability. Despite these advantages, its growth and development are markedly sensitive to environmental factors. Indole-3-acetic acid (IAA) is the major growth hormone in plants, regulating plant growth, development, and response to adversity. Nevertheless, the specific regulatory functions of Aux/IAA genes in response to abiotic stresses in white clover remain largely unexplored. RESULTS: In this study, we identified 47 Aux/IAA genes in the white clover genome, which were categorized into five groups based on phylogenetic analysis. The TrIAAs promoter region co-existed with different cis-regulatory elements involved in developmental and hormonal regulation, and stress responses, which may be closely related to their diverse regulatory roles. Collinearity analysis showed that the amplification of the TrIAA gene family was mainly carried out by segmental duplication. White clover Aux/IAA genes showed different expression patterns in different tissues and under different stress treatments. In addition, we performed a yeast two-hybrid analysis to investigate the interaction between white clover Aux/IAA and ARF proteins. Heterologous expression indicated that TrIAA18 could enhance stress tolerance in both yeast and transgenic Arabidopsis thaliana. CONCLUSION: These findings provide new scientific insights into the molecular mechanisms of growth hormone signaling in white clover and its functional characteristics in response to environmental stress.