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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

[Opening experiments: synthesis, purification, and characterization of polyethyleneimine-modified carbon dots].

Open experiments are an effective means of cultivating top-notch innovative talents. Based on student interests, research hotspots and our laboratory conditions, an experimental scheme was designed. In this experiment, polyethyleneimine modified carbon dots (PEI-CDs) were prepared via a one-step hydrothermal method using citric acid (CA) as the carbon source and PEI as the surface passivator. First, CA and PEI were completely dissolved in 0.1 mol/L HCl and transferred into an autoclave. The autoclave was heated to 130 ℃ for 2 h. PEI-CDs solution was obtained. After cooling to room temperature, the solution was concentrated to 2 mL by rotary evaporation. Finally, the PEI-CDs were precipitated, washed with ethanol, and dried under vacuum at 70 ℃ for 12 h. The obtained PEI-CDs were characterized by fluorescence spectrophotometry, absorption spectrophotometry, infrared spectrometry, and transmission electron microscopy. The results indicated that anhydrous-ethanol precipitation is a simple, rapid, economical, and green purification method. The as-prepared PEI-CDs had unique properties, such as good water solubility, high luminescence, uniform particle sizes, and good stability. Through this open experiment, students can not only master the operation of large-scale instruments but also enhance their interest in scientific research.

Identification of naphthalimide-derivatives as novel PBD-targeted polo-like kinase 1 inhibitors with efficacy in drug-resistant lung cancer cells.

Targeting polo-box domain (PBD) small molecule for polo-like kinase 1 (PLK1) inhibition is a viable alternative to target kinase domain (KD), which could avoid pan-selectivity and dose-limiting toxicity of ATP-competitive inhibitors. However, their efficacy in these settings is still low and inaccessible to clinical requirement. Herein, we utilized a structure-based high-throughput virtual screen to find novel chemical scaffold capable of inhibiting PLK1 via targeting PBD and identified an initial hit molecule compound 1a. Based on the lead compound 1a, a structural optimization approach was carried out and several series of derivatives with naphthalimide structural motif were synthesized. Compound 4Bb was identified as a new potent PLK1 inhibitor with a KD value of 0.29 µM. 4Bb could target PLK1 PBD to inhibit PLK1 activity and subsequently suppress the interaction of PLK1 with protein regulator of cytokinesis 1 (PRC1), finally leading to mitotic catastrophe in drug-resistant lung cancer cells. Furthermore, 4Bb could undergo nucleophilic substitution with the thiol group of glutathione (GSH) to disturb the redox homeostasis through exhausting GSH. By regulating cell cycle machinery and increasing cellular oxidative stress, 4Bb exhibited potent cytotoxicity to multiple cancer cells and drug-resistant cancer cells. Subcutaneous and oral administration of 4Bb could effectively inhibit the growth of drug-resistant tumors in vivo, doubling the survival time of tumor bearing mice without side effects in normal tissues. Thus, our study offers an orally-available, structurally-novel PLK1 inhibitor for drug-resistant lung cancer therapy.

Identifying the geospatial relationship of surface ozone pollution in China: Implications for key pollution control regions.

Surface ozone pollution, as a pressing environmental concern, has garnered widespread attention across China. Due to air mass transport, effective control of ozone pollution is highly dependent on collaborative efforts across neighboring regions. However, specific regions with strong internal interactions of ozone pollution are not yet well identified. Here, we introduced the Geospatial SHapley Additive exPlanation (GeoSHAP) approach, which primarily involves machine learning and geostatistical algorithms. Based on extensive atmospheric environmental monitoring data from 2017 to 2021, machine learning models were employed to train and predict ozone concentrations at the target location. The R2 values on the test sets of different scale regions all reached 0.98 in the overall condition, indicating that the core model has good accuracy and generalization ability. The results highlight key regions with high ozone geospatial relationship (OGR) index, predominantly located in the Northern District (ND), spanning the Fen-Wei Plain, the Loess Plateau, and the North China Plain, as well as within portions of the Yangtze River Delta (YRD) and the Pearl River Delta (PRD). Further investigation indicated that high geospatial relationships stem from a synergy between anthropogenic and natural factors, with anthropogenic factors serving as a pivotal element. This study revealed key regions with the most urgent need for joint control of anthropogenic sources to mitigate ozone pollution.

Multiscale Synergistic Gecko-Inspired Adhesive for Stable Adhesion under Varying Preload and Surface Roughness.

Inspired by geckos, fibrillar microstructures hold great promise as controllable and reversible adhesives in the engineering field. However, enhancing the adhesion strength and stability of gecko-inspired adhesives (GIAs) under complex real-world contact conditions, such as rough surfaces and varying force fields, is crucial for its commercialization, yet further research is lacking. Here, we propose a hierarchically designed GIA, which features a silicone foam (SF) backing layer and a film-terminated fibrillar microstructure under a subtle multiscale design. This structure has been proven to have a "multiscale synergistic effect", allowing the material to maintain strong and stable adhesion to surfaces with changing normal pressures and roughness. Specifically, under a high load, the adhesive strength is 2 times more than that of conventional GIA, and it is 1.5 times stronger on rough surfaces compared to conventional GIA. Under high pressure and high surface roughness simultaneously, the adhesive strength is 3.3 times higher compared to conventional GIA. Our research demonstrates that the synergistic effect of multiscale biomimetic adhesion structures is highly effective in enhancing the adhesive strength of GIA under some harsh contact conditions.

Monolayer Vacancy-Induced MXene Memory for Write-Verify-Free Programming.

The fundamental logic states of 1 and 0 in Complementary Metal-Oxide-Semiconductor (CMOS) are essential for modern high-speed non-volatile solid-state memories. However, the accumulated storage signal in conventional physical components often leads to data distortion after multiple write operations. This necessitates a write-verify operation to ensure proper values within the 0/1 threshold ranges. In this work, a non-gradual switching memory with two distinct stable resistance levels is introduced, enabled by the asymmetric vertical structure of monolayer vacancy-induced oxidized Ti3C2Tx MXene for efficient carrier trapping and releasing. This non-cumulative resistance effect allows non-volatile memories to attain valid 0/1 logic levels through direct reprogramming, eliminating the need for a write-verify operation. The device exhibits superior performance characteristics, including short write/erase times (100 ns), a large switching ratio (≈3 × 104), long cyclic endurance (>104 cycles), extended retention (>4 × 106 s), and highly resistive stability (>104 continuous write operations). These findings present promising avenues for next-generation resistive memories, offering faster programming speed, exceptional write performance, and streamlined algorithms.

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.