Biomedical subjects

Wenxin Liu

Publications and source records attributed to Wenxin Liu.

12 recordsLinked to original sources

PubMed2026

The OsUVR8-OsNAC3-OsERF117 signaling module mediates metabolic acclimation and climate adaptation in rice.

Ultraviolet-B (UV-B; 280 to 315 nanometers) radiation increasingly threatens crop productivity, yet the genetic basis of plant adaptation remains poorly understood. We delineate a UV-B signaling module in rice that links photoreceptor activation to transcriptional reprogramming and metabolic acclimation. The AP2/ERF transcription factor OsERF117 acts as a central regulator, directly activating flavonoid and melatonin biosynthetic genes to drive photoprotective metabolite accumulation and enhance UV-B stress tolerance. Promoter variation in OsERF117 defines 10 haplotypes across 4093 rice accessions, with high-expression haplotypes enriched in high-UV-B regions and correlated with adaptive divergence. OsERF117 is transcriptionally activated by OsNAC3, with a cis-regulatory SNP at an OsNAC3-binding site modulating responsiveness and contributing to subspecies diversification. Genetic and biochemical evidence supports a model in which UV-B-activated OsUVR8 promotes OsNAC3 activity and antagonizes OsCOP1-mediated ubiquitination and degradation in rice. This OsUVR8-OsCOP1-OsNAC3-OsERF117 module reveals how UV-B perception drives regulatory and metabolic diversification, offering targets for breeding UV-B-resilient crops.

Oryza↗

PubMed2025

Plasma Proteomic Profiles Predict Individual Future Osteoarthritis Risk.

OBJECTIVE: Osteoarthritis (OA) is a widespread degenerative joint disease that causes a considerable socioeconomic burden. Despite progress in genetic and environmental insights, early diagnosis is still limited by the lack of evident symptoms during the initial phases and accurate biomarkers. This study aims to identify plasma proteins associated with future risk of OA and develop a predictive model. METHODS: We conducted a large-scale proteomic analysis of 45,307 participants from the UK Biobank, excluding those with baseline OA. Plasma samples were assayed using the Olink Explore Proximity Extension Assay targeting 1,463 unique proteins. Clinical variables and OA outcomes were extracted and linked to electronic health records. A predictive model was constructed using the LightGBM machine learning method, and SHapley Additive exPlanations (SHAP) were applied to evaluate the importance of variables. RESULTS: We identified a panel of proteins significantly associated with the risk of developing OA. Notably, after adjusting for multiple confounders, collagen type IX alpha 1 chain (COL9A1) and cartilage acidic protein 1 (CRTAC1) were the most significant predictors of incident OA, with hazard ratios of 1.54 (95% confidence interval [CI] 1.48-1.61) and 1.65 (95% CI 1.54-1.78), respectively. SHAP analysis allowed a profound interpretation of the contribution of each protein and clinical variable to the model, revealing the multifactorial nature of OA risk prediction. The temporal trajectories of plasma proteins indicated that the levels of COL9A1 and CRTAC1 began to deviate from normal for more than a decade before OA onset, suggesting their potential use in early detection strategies. The predictive model, developed using the LightGBM algorithm, integrated proteins with clinical covariates and demonstrated an area under the curve (AUC) of 0.729 for 5-year OA prediction, 0.721 for 10-year prediction, and 0.723 for all incident OA. The predictive accuracy of the model was further enhanced for hip and knee OA, achieving AUCs of 0.820 and 0.803 for 5-year predictions. CONCLUSION: Our study identified the role of plasma proteomics in predicting future OA risk, which could contribute to preemptive measures. The innovative model, which integrates proteomic biomarkers with clinical data, offers a potential tool for risk assessment, potentially optimizing OA management strategies and enhancing prevention efforts.

Humans↗

PubMed2006

A chemical extraction method for mimicking bioavailability of polycyclic aromatic hydrocarbons to wheat grown in soils containing various amounts of organic matter.

In this study, we have evaluated the extent to which organic matter contents in soils influence the accumulation of PAHs by the roots of wheat plants and have developed a rapid chemical method for determining the bioavailability of PAH. Four polycyclic aromatic hydrocarbons (PAHs), naphthalene, acenaphthylene, fluorene, and phenanthrene, were added to natural soil samples with different amounts of organic matterfor pot experiments to evaluate apparent bioavailability of PAHs to wheat roots (Triticum aestivum L.). The extractabilities of PAHs in the soil were tested by a sequential extraction scheme using accelerated solvent extraction with water, n-hexane, and a mixture of dichloromethane and acetone as solvents. The water or n-hexane-extractable PAHs were positively correlated to dissolved organic matter (DOM) and negatively correlated to total organic matter (TOM), indicating mobilization and immobilization effects of DOM and TOM on soil PAHs, respectively. The apparent accumulation of PAHs by wheat roots was also positively and negatively correlated to DOM and TOM, respectively. As a result, there are positive correlations between the amounts of PAHs extracted by water or n-hexane and the quantities accumulated in plant roots, suggesting the feasibility of using water- or n-hexanes-extractable fractions as indicators of PAH availability to plants.

Biological Availability↗

PubMed2006

Emission of polycyclic aromatic hydrocarbons in China.

Emission of 16 polycyclic aromatic hydrocarbons (PAHs) listed as U.S. Environmental Protection Agency (U.S. EPA) priority pollutants from major sources in China were compiled. Geographical distribution and temporal change of the PAH emission, as well as emission profiles, are discussed. It was estimated that the total PAH emission in China was 25,300 tons in 2003. The emission profile featured a relatively higher portion of high molecular weight (HMW) species with carcinogenic potential due to large contributions of domestic coal and coking industry. Among various sources, biomass burning, domestic coal combustion, and coking industry contributed 60%, 20%, and 16% of the total emission, respectively. Total emission, emission density, emission intensity, and emission per capita showed geographical variations. In general, the southeastern provinces were characterized by higher emission density, while those in western and northern China featured higher emission intensity and population-normalized emission. Although energy consumption in China went up continuously during the past two decades, annual emission of PAHs fluctuated depending on the amount of domestic coal consumption, coke production, and the efficiency of energy utilization.

Air Pollutants↗

PubMed2006

Two-compartment sorption of phenanthrene on eight soils with various organic carbon contents.

Sorption characteristics of phenanthrene (PHE) were studied on eight soils with organic carbon contents spanning over an order of magnitude using phase distribution relationships (PDRs) at 1 h, 48 h, and 720 h contact times. A new algebraic method was employed to describe the sorption characteristics at different time intervals (between 1 h and 48 h, and 1 h and 720 h). It was found that nonlinearity increased with increasing contact time and sorption that occurred in the subsequent time interval following the initial 1 h exhibited stronger isotherm nonlinearity. Sorption coefficients were positively correlated with the organic carbon contents of the soils. Detailed sorption dynamics were also examined on these soils. A two-compartment, first-order model was used to describe the sorption dynamics. The rate constants of the two compartments differed 18-170 times, suggesting the dissimilar sorption behaviors of the mathematically separated compartments. These two compartments were labeled fast and slow sorption compartment according to the rate constants. Calculation showed that the fast compartment accounted for over 80% of the overall sorption at the initial 1 h, while the slow compartment predominated the total sorption in the following 47 h. By combining the discussion of PDRs and sorption dynamics, the contributions of the two compartments to linear and nonlinear sorption were differentiated. The slow sorption compartment made a major contribution to nonlinear sorption and possibly to sequestration of organic pollutants by these soils.

Adsorption↗

PubMed2006

An approach to assess ecological risk for polycyclic aromatic hydrocarbons (PAHs) in surface water from Tianjin.

Three approaches were applied and compared to evaluate additive toxic effects of eight PAHs to aquatic organisms in rivers in the Tianjin area. Although the toxicity of the studied PAH compounds did not significantly increase the risk to aquatic organisms, the results of all three approaches indicated that the additive effect of the eight PAHs was significantly stronger than any individual compound acting alone, which indicated the applicability of the approaches. Further, of the compounds studied, anthracene was the major contributor to the overall toxic effect of the mixture. The calculated geometric means of the hazard quotient for the additive effect varied from 0.00055 to 0.00062, compared to the hazard quotient of individual PAHs which ranged from 5.1 x 10-6 to 0.00053. The hazard quotient distribution geometric mean was 0.00058, with 95% of the quotient between 6.6 x 10-5 and 0.051. Overlapping areas varied from 0.00015 to 0.02 for individual PAHs and was 0.03 for additive toxicity.

Animals↗

PubMed2004

Multimedia fate model for hexachlorocyclohexane in Tianjin, China.

A level III fugacity model was applied to characterize the fate of gamma-HCH in Tianjin, China, before the 1990s when the contamination reached its maximum at steady state. Geometric means were used as model inputs. The concentrations of gamma-HCH in air, surface water, soil, sediment, crops, and fish as well as transfer fluxes across the interface between the compartments were derived under the assumption of steady state. The calculated concentrations were validated by independent data collected from the literature. There was generally good agreement between the estimated and the observed concentrations, and the differences were all less than 0.6 log units for air, water, soil, sediment, and fish and approximately 1 order of magnitude for crops. Around 97% of gamma-HCH accumulated in soil and sediment. Wastewater irrigation was not an important pathway for delivering gamma-HCH to soil as compared to the dominant source of agricultural application. Degradation and advective airflow carried much gamma-HCH out of the system. Sensitivities of the model estimates to input parameters were tested, and a coefficient of variation normalized sensitivity coefficient was defined for the test. The most influential parameters were degradation rates in sediment and soil, application rates, concentrations in wastewater, and adsorption coefficients. Monte Carlo simulation was conducted for model uncertainty analysis. The model was run 20 000 times using randomly generated data from predefined log-normal distribution density functions. All calculated concentrations and fluxes were log-normally distributed. The dispersions of the calculated and observed concentrations were compared in terms of coefficients of variation to distinguish between true variability and model uncertainty.

Air↗

PubMed2003

Fate modeling of phenanthrene with regional variation in Tianjin, China.

A multimedia fate model with spatially resolved air and soil phases was developed and evaluated. The model was used for calculation of phenanthrene concentrations in air, water, soil, and sediment in Tianjin area and transport fluxes between the adjacent bulk phases under steady-state assumption. Both air and soil phases were divided into 3113 individual compartments of 4 km2 each to assess the spatial variation of phenanthrene concentrations and fluxes. Independently measured phenanthrene concentrations in air, water, and soil were used for model validation. The spatial variation in soil was validated using a set of measured phenanthrene concentrations of 188 surface soil samples collected from the area. Most data used either for model calculation or for model validation were collected during the last 5 years. As the results of the model validation, the calculated mean values for phenanthrene concentrations in various bulk phases are in fair agreement with those independently observed and are very close to those calculated using the model without spatial variation. The absolute difference between the calculated and the measured mean concentrations are 0.14, 0.48, and 0.13 log-units (mol/m3) for air, water, and soil, respectively. The spatial distribution patterns of phenanthrene in both air and soil were well modeled. Spatially, however, the model overestimated the soil phenanthrene level at low concentration range and underestimated it at high concentration range. The calculated distribution of phenanthrene in the air matches well with the emission from fossil fuel combustion, while the calculated distribution pattern in the soil is similar to that observed.

China↗

PubMed2003

[Multimedia fate modeling with spatial resolution for phenanthrene in Tianjin].

Behavior and fate of phenanthrene in various phases in Tianjin were calculated using a multimedia model with spatial resolution under steady-state assumption. Spatial variation of two parameters, namely soil organic carbon content and emission from fossil fuel combustion, were taken into consideration. Both soil and air phases were further divided into 3113 sub-compartments and 6226 equations in total were solved simultaneously under mass-balance assumption. A number of output parameters, therefore, were generated and were used for mapping of phenanthrene concentrations in soil and air, as well as transfer fluxes between compartments. The model was evaluated in two ways. 1. Comparison between the calculated and the observed average concentrations in bulk compartments, and 2. Comparison of spatial distribution of the calculated and the observed phenanthrene concentrations in surface soil. In both cases, the predicted results are in fair agreement with the independently measured values. As the results of the modeling, it was demonstrated that soil and sediment, especially the later, is the primary sink of phenanthrene in the area over 70% of the chemical accumulated in sediment. The spatial distribution pattern of phenanthrene in surface soil depends on content of soil organic matter which prevent the degradation of the material by bacteria. For distribution in ambient air, the dominant controlling factor is the emission.

Air↗

PubMed2002

Surface acid-base behaviors of Chinese loess.

Acid-base titration was applied to investigate the surface acid-base properties of a Chinese loess sample at different ionic strengths. The acidimetric supernatant was regarded as the system blank of titration to correct the influence of particle dissolution on the estimation of proton consumption. The titration behavior of the system blank could be described by the hydrolysis of Al3+ and Si(OH)4 in aqueous solution as well as the production of hydroxyaluminosilicates. The formation of Al-Si species on homogeneous surface sites by hydrous aluminum and silicic acid, released from solid substrate during the acidic titration, was considered in the model description of the back-titration procedure. A surface reaction model was suggested as follows: >SOH<-->>SO(-)+H+, pK(a)(int)=3.48-3.98;>SOH+Al(3+)+H4SiO4<-->>SOAl(OSi(OH)3(+)+2H+, pK(SC)=3.48-4.04. Two simple surface complexation models accounted for the interfacial structure, i.e., the constant capacitance model (CCM) and the diffuse layer model (DLM), and gave a satisfactory description of the experimental data. Considering the effect of ionic strength on the electrostatic profile at the solid-aqueous interface, the DLM was appropriate at the low concentrations (0.01 and 0.005 mol/L) of background electrolyte (NaNO3 in this study), while the CCM was preferable in the case of high ionic strength (0.1 mol/L).

Journal Article↗

PubMedDate not supplied

Design of an adaptive neural network based power system stabilizer.

Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp the low frequency power system oscillations. To overcome the drawbacks of conventional PSS (CPSS), numerous techniques have been proposed in the literature. Based on the analysis of existing techniques, this paper presents an indirect adaptive neural network based power system stabilizer (IDNC) design. The proposed IDNC consists of a neuro-controller, which is used to generate a supplementary control signal to the excitation system, and a neuro-identifier, which is used to model the dynamics of the power system and to adapt the neuro-controller parameters. The proposed method has the features of a simple structure, adaptivity and fast response. The proposed IDNC is evaluated on a single machine infinite bus power system under different operating conditions and disturbances to demonstrate its effectiveness and robustness.

Electric Power Supplies↗

PubMedDate not supplied

Nitrogen transformations modeling in subsurface-flow constructed wetlands.

Subsurface-flow constructed wetlands (CWs) wastewater treatment typically results in satisfactory organics removal. However, the removal of nutrients, particularly nitrogen, is often unreliable, and typically less than desired, and nitrogen transformations in wetlands systems are not well-understood. The principal objective of this study was to establish a basis for quantification of nitrogen transformations through subsurface flow CW systems. Actual performance data from a full-scale facility located near Lincoln, Nebraska, were used to calibrate a proposed nitrogen transformations model, which, in turn, was used to replicate and predict the wetlands performance. To realize this objective, a compartmental analysis technique, which uses a set of differential equations and nonlinear optimization numerical methods, was used for solving nitrogen transformation rates and for predicting wetland performance. The model satisfactorily reproduced the mean effluent concentrations for organic nitrogen, ammonium-nitrogen, and nitrate-nitrogen, but with lesser accuracy with respect to peak high and low effluent concentrations. Nitrogen mass balance in the wetland was used to identify likely nitrogen transformation pathways. Generally, it was found that approximately one-third of the influent nitrogen mass was removed through nitrification and denitrification, one-third was removed through vegetative assimilation, and the remainder was discharged in the wetland effluent.

Biodegradation, Environmental↗