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This study aimed to explore the prevalence and influencing factors of anemia in patients with ankylosing spondylitis (AS) using real-world data and to construct a predictive model for anemia in AS. In November 2023, we accessed the database from China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN). Clinical data of AS collected from the CERTAIN between March 2022 and September 2023 were analyzed. Demographic information, clinical assessment scales, and laboratory test results of the patients were collected. According to the anemia diagnostic criteria established by the World Health Organization (WHO) in 2018, patients were divided into anemia group and non-anemia group. Statistical analyses were performed using SPSS 25.0 software, including χ2 tests, independent sample t-tests to compare differences between the two groups, and multivariate stepwise logistic regression analysis to explore the influencing factors of anemia in AS. The predictive efficacy of the model was evaluated by plotting receiver operating characteristic (ROC) curves. Calibration was assessed through the Hosmer-Lemeshow goodness-of-fit test, and a calibration curve was plotted to comprehensively evaluate the predictive capability of the model. A total of 251 patients were included in this study, among which 58 cases had anemia (23.1%). There were significant differences in gender, ossification, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) indicators, and clinical assessment scale results between the two groups (P < 0.05). The results of multivariate stepwise logistic regression analysis showed that female gender, underweight, ossification, abnormal CRP and ESR were independent risk factors for anemia in AS (P < 0.05). Based on the results of multivariate stepwise logistic regression analysis, a predictive model for anemia in AS was established as Logit(P) = -5.02 + 2.041 × gender -1.11 × BMI(body mass index) category + 1.103 × ossification category + 0.942 × CRP category + 1.476 × ESR category. The ROC curve analysis showed that the area under the curve of the model for predicting anemia in AS was 0.857 (95% CI: 0.808 ~ 0.906). The Omnibus test of model coefficients yielded χ2 = 85.265, P < 0.001. The Hosmer-Lemeshow test showed χ2 = 7.005, P = 0.536 (P > 0.05). Analysis of real-world AS diagnosis and treatment data showed that the prevalence of anemia in Chinese AS was 23.1%. The occurrence of anemia was closely related to female gender, underweight, ossification, and abnormal CRP and ESR. The logistic model constructed based on these indicators for predicting the risk of anemia in AS demonstrated good efficacy.

Soil aeration plays a critical role in regulating root development and soil nutrient dynamics, which are essential for optimizing tomato fruit yield. However, the mechanisms underpinning how different soil aeration techniques influence root characteristics and soil nitrogen cycling remain underexplored. This study aims to evaluate the effects of micro-nano bubble aeration and underground air layer treatments on soil oxygen concentration, root morphology, nitrogen cycling, and ultimately tomato fruit yield. A two-season field experiment was conducted in Xi’an, China. Micro-nano bubble aeration treatments were applied before irrigation with dissolved oxygen levels set at 6.5 mg/L (N1) and 8.0 mg/L (N2). Additionally, underground air layer treatments were implemented without vertical pipes (L1) and with vertical pipes (L2). Measurements included soil pore O 2 and CO 2 concentrations, root morphology and activity, root extract concentrations, soil nitrogen forms (NO 3 − -N and NH 4 + -N), and tomato yield. Both aeration treatments significantly increased soil pore O 2 while reducing CO 2 levels, promoting improved root morphology, higher root extract concentrations, and elevated root activity. This led to enhanced tomato yields. Soil aeration also altered nitrogen cycling, increasing nitrate (NO 3 − -N) and decreasing ammonium (NH 4 + -N) concentrations. It is recommended to maintain soil moisture at 60%-90% field capacity for optimal results, with the N2 treatment preferred for short-term cultivation and the underground air layer treatment advised for long-term tomato production. This study provides comprehensive insights into how soil aeration techniques regulate root systems and soil nitrogen dynamics, offering practical recommendations for improving tomato yield through enhanced soil management.

While horizontal gradients of biodiversity have been examined extensively in the past, vertical diversity gradients (elevation, water depth) are attracting increasing attention. We compiled data from 443 elevational gradients involving diverse organisms worldwide to investigate how elevational diversity patterns may vary between the Northern and Southern hemispheres and across latitudes. Our results show that most elevational diversity curves are positively skewed (maximum diversity below the middle of the gradient) and the elevation of the peak in diversity increases with the elevation of lower sampling limits and to a lesser extent with upper limit. Mountains with greater elevational extents and taxonomic groups that are more inclusive, show proportionally more unimodal patterns whereas other ranges and taxa show highly variable gradients. The two hemispheres share some interesting similarities but also remarkable differences, likely reflecting differences in landmass and mountain configurations. Different taxonomic groups exhibit diversity peaks at different elevations, probably reflecting both physical and physiological constraints.

Potato starch noodles (PSN), a characteristic gluten-free Asian food, are essentially high-concentration starch gels (about 35% starch) formed through gelatinization and retrogradation. This study systematically investigates freezing temperature effects, particularly across the glass transition temperature, on PSN texture and microstructure. We found that fresh PSN have a freezing point of −1 °C, supercooling temperature of −4.5 °C, and a Tg’ value of −3.1 °C. Freezing significantly reduced the adhesiveness of PSN and increased the hardness. During the 48 h freezing process, noodles frozen at −3 °C, the closest to Tg’, exhibited the highest hardness (14,065.77 g), springiness (0.98), cohesiveness (0.93), chewiness (11,971.06), and resilience (0.84), and the least adhesiveness. PSN frozen within the range near Tg’ (−3 °C) showed superior texture, continuous solid cross-section, and dense surface, attributed to the reverse transformation of starch, high mobility of starch chains, and smaller ice crystals. PSN frozen at −3 °C for 24 h displayed the most compact and desirable texture compared to the other samples. These findings deepen the understanding of the role of glass transition temperature in the texture formation of starch gel during freezing and provide valuable insights for optimizing the frozen processing of starch gel-based food.

Constructed wetlands have become crucial ecosystems for the purification of industrial and agricultural water. The health of wetland plants and the efficacy of water purification are strongly influenced by root-associated bacteria. However, our understanding of the functions of bacterial communities in the plant different root components (i.e., rhizosphere, rhizoplane, and endosphere) and their impact on water purification is still limited. To address this knowledge gap, we employed high-resolution 16S rRNA deep amplicon sequencing to explore the bacterial community structure and assembly within the root components of three plant species (i.e. , , and ) found in constructed wetlands. Our findings revealed that the pollutant removal efficiency was higher in the wet season than in the dry season. The specific root compartment, plant species, environmental factors, and seasonality significantly influenced the bacterial composition, diversity and abundance. Across all three plant species, Proteobacteria emerged as the dominant bacterial groups in all root components. The abundance and diversity of bacterial communities exhibited a decline from the rhizosphere to the endosphere, accompanied by an increase in the number of distinctive biomarkers from the rhizosphere to the endosphere. The bacterial composition exhibited significant similarity in the rhizosphere in the dry season and the endosphere in the wet season. Bacterial genes in the rhizosphere-rhizoplane were associated with environmental information processing, transportation and metabolism, while those in the rhizoplane-endosphere primarily handle metabolic processes. The bacterial community positively correlated with total nitrogen content, chemical oxygen demand, and NO -N in the dry season, while associated with total phosphorus, total organic carbon, and NO -N content in the wet season. The structure and function of the bacterial community within the root rhizoplane-endosphere can serve as indicators of the water purification efficacy of constructed wetlands.

Axial spondyloarthritis (axSpA) is a globally prevalent and challenging autoimmune disease. Characterised by insidious onset and slow progression, the absence of specific clinical manifestations and biomarkers often leads to misdiagnosis, thereby complicating early detection and diagnosis of axSpA. Furthermore, the high heterogeneity of axSpA, its complex pathogenesis and the lack of specific drugs means that traditional classification standards and treatment guidelines struggle to meet the demands of personalised treatment. Recently, machine learning (ML) has seen rapid advancements in the medical field. By integrating large-scale data with diverse algorithms and using multidimensional data, such as patient medical records, laboratory examinations, radiological data, drug usage and molecular biology information, ML can be modelled based on real-world clinical issues. This enables the diagnosis, stratification, therapeutic efficacy prediction and prognostic evaluation of axSpA, positioning it as an emerging research topic. This study explored the application and progression of ML in the diagnosis and therapy of axSpA from five perspectives: early diagnosis, stratification, disease monitoring, drug efficacy evaluation and comorbidity prediction. This study aimed to provide a novel direction for exploring rational diagnostic and therapeutic strategies for axSpA.

Human disturbance and climate change have increased the risk of extinction for rare and endangered wild plant species. One effective way to conserve these rare and endangered species is through reintroduction. In this review,we summarize the advances in wild plant reintroduction from five perspectives：the establishment of reintroduction biology as an important tool for biodiversity conservation;the importance of genetic diversity in reintroduction;reintroduction under global climate change;recruitment limitation in reintroduction;and reintroduction and ecological restoration. In addition,we consider the future of plant reintroduction strategies.

Objective To analyze the status and correlation factors of fatigue in patients with ankylosing spondylitis (AS), and provide a reference for improving the fatigue status of patients with AS. Method Using the AS-specific disease database of the Chinese Rheumatology Registration and Research Information Platform, patients with AS from 9 centers in China were selected as study subjects from March 2022 to September 2023. Functional Assessment of Chronic Illness Therapy Scale (FACIT-F) score, AS disease activity score-C-reactive protein (ASDAS-CRP), AS disease activity score-erythrocyte sedimentation rate (ASDAS-ESR), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Function Index (BASFI), Bath Ankylosing Spondylitis Measurement Index (BASMI), Patient Global Assessment (PGA) score, night pain score, Depression Anxiety Stress Scale (DASS-21) and AS International Community Health Index Assessment (ASAS-HI) were observed. Human leukocyte antigen B27 (HLA-B27), C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) of the patients were detected. The data were analyzed by Spearman correlation and multiple linear regression. Result A total of 338 patients with AS were included in this study. Spearman correlation analysis results of 338 AS patients with fatigue showed that age, disease course, ASDAS-CRP, ASDAS-ESR, BASDAI, PGA, BASFI, BASMI, ASAS-HI and so on were the main correlation factors of fatigue ( P  < 0.05); Multiple linear regression analysis showed that BASDAI, ASAS-HI, depression and so on were independent predictors of fatigue in AS patients ( P  < 0.05). Spearman correlation analysis of no or very mild fatigue group showed that age, ASDAS-CRP, ASDAS-ESR, BASDAI, BASFI, ASAS-HI and so on were the main correlation factors of fatigue ( P  < 0.05); Multiple linear regression analysis showed that age, BASDAI, ASAS-HI were the independent predictor of fatigue in AS patients ( P  < 0.05). Spearman correlation analysis in the mild and moderate fatigue group showed that ASDAS-CRP, BASDAI, PGA, BASFI, ASAS-HI and so on were the main factors influencing fatigue ( P  < 0.05); Multiple linear regression analysis showed that BASDAI, depression and stress were independent predictors of fatigue in AS patients ( P  < 0.05). Conclusion In this study, fatigue was obvious in 37.9% of AS patients, and patients’ fatigue levels were closely related to disease activity (ASDAS, BASDAI and PGA) and psychological factors (anxiety, depression and stress). At the same time, the higher the degree of fatigue, the more obvious the impact of disease activity and psychological factors on fatigue.

Urban greenspaces are vital for human health, providing multiple ecosystem services, yet their distribution often fails to align with population needs, resulting in disparities in exposure and associated benefits. Despite increasing research on greenspace exposure, the role, mechanisms, and future trends of urban greening in exacerbating or mitigating these inequalities remain poorly understood. Here, we developed a novel model to evaluate the impact of urban greening on greenspace exposure inequality (GEI) in China, spanning the period from 2000 and 2020 to projections for 2100. Our findings reveal pronounced spatial heterogeneity in GEI, with newly developed urban areas showing more equitable greenspace exposure than established areas. We provide a pioneering analysis identifying the greening process as the predominant driver of GEI, accounting for 54% of the observed disparities. Future projections under various Shared Socioeconomic Pathways (SSPs) highlight the enduring influence of greening in shaping GEI. These insights advance our understanding of greenspace inequality and provide a robust foundation for formulating equitable urban greening strategies, ensuring that urban development fosters environmental justice and enhances urban well-being.

To feed the growing population, grasslands and forests were destroyed, and lakes and coastal areas were reclaimed (Ren et al. 2007). Since the reform and opening-up policy in 1978, China's economy has grown rapidly.