Improvement of soil nutrient cycling by dominant plants in natural restoration of heavy metal polluted areas.

Referring to the natural succession to restore polluted land is one of the most vital assignments to solving the environmental problems. However, there is little understanding of the natural restoration of nutrient biogeochemical cycles in abandoned land with severe metal pollution. To clarify the nutrient cycling process and the influence of organisms on it, we investigated the magnitude of rhizosphere effects on soil nitrogen (N), phosphorus (P) and sulphur (S) cycles in natural restoration of an abandoned metal mine, as well as the roles of plants and microorganisms in the nutrient cycles. Our data revealed that the rhizosphere had higher levels of ammoniation than non-rhizosphere soil at both stages of restoration. In the early stage, the rhizosphere had greater levels of inorganic phosphorus and organophosphorus solubilisation, as well as sulphite oxidation, compared to non-rhizosphere soil. The bacterial composition influenced the N and S cycles, while the fungal composition had the greatest effect on the P cycles. Furthermore, rhizosphere nutrition cycles and microbial communities altered according plant strategy. Overall, the plants that colonize the early stages of natural recovery demonstrate enhanced restoration of nutrient efficiency. These results contribute to further knowledge of nutrient recovery in mining areas, as well as suggestions for selecting remedial microorganisms and plants in metal-polluted environments.

Integrated Transcriptomic and Metabolomic Analysis Reveals the Molecular Regulatory Mechanism of Flavonoid Biosynthesis in Maize Roots under Lead Stress.

Flavonoids are secondary metabolites that play important roles in the resistance of plants to abiotic stress. Despite the widely reported adverse effects of lead (Pb) contamination on maize, the effects of Pb on the biosynthetic processes of flavonoids in maize roots are still unknown. In the present work, we employed a combination of multi-omics and conventional assay methods to investigate the effects of two concentrations of Pb (40 and 250 mg/kg) on flavonoid biosynthesis in maize roots and the associated molecular regulatory mechanisms. Analysis using conventional assays revealed that 40 and 250 mg/kg Pb exposure increased the lead content of maize root to 0.67 ± 0.18 mg/kg and 3.09 ± 0.02 mg/kg, respectively, but they did not result in significant changes in maize root length. The multi-omics results suggested that exposure to 40 mg/kg of Pb caused differential expression of 33 genes and 34 metabolites related to flavonoids in the maize root system, while 250 mg/kg of Pb caused differential expression of 34 genes and 31 metabolites. Not only did these differentially expressed genes and metabolites participate in transferase activity, anthocyanin-containing compound biosynthetic processes, metal ion binding, hydroxyl group binding, cinnamoyl transferase activity, hydroxycinnamoyl transferase activity, and flavanone 4-reductase activity but they were also significantly enriched in the flavonoid, isoflavonoid, flavone, and flavonol biosynthesis pathways. These results show that Pb is involved in the regulation of maize root growth by interfering with the biosynthesis of flavonoids in the maize root system. The results of this study will enable the elucidation of the mechanisms of the effects of lead on maize root systems.

Opposite response of constructed wetland performance in nitrogen and phosphorus removal to short and long terms of operation.

Constructed wetlands (CWs) have been widely used for treating polluted water since the 1950s, with applications in over 50 countries worldwide. Most studies investigating the pollutant removal efficiency of these wetlands have focused on differences among wetland designs, operation strategies, and environmental conditions. However, there still remains a gap in understanding the variation in wetland pollutant removal efficiency over different time scales. Therefore, the main aim of the study is to address this gap by conducting a global meta-analysis to estimate the variation in nitrogen (N) and phosphorus (P) removal by wetland in short- and long-term pollutant treatment. The findings of this study indicated that the total efficiencies of N and P removal increased during short-term wetland operation but decreased during long-term operation. However, for surface flow CWs specifically, the efficiencies of N and P removal increased during short-term operation and remained stable during long-term operation. Moreover, the study discovered that wetland N removal efficiency was influenced by seasons, with an increase in spring and summer and a decrease in autumn and winter. Conversely, there was no significant seasonal effect on P removal efficiency. Additionally, high hydraulic load impaired wetland N and P removal efficiency during long-term operation. This study offers a critical review of the role of wetlands in wastewater treatment and provides valuable reference data for the design and selection of CWs types during wastewater treatment in the aspect of sustainability.

Effects of Heavy Metals on Stomata in Plants: A Review.

Stomata are one of the important structures for plants to alleviate metal stress and improve plant resistance. Therefore, a study on the effects and mechanisms of heavy metal toxicity to stomata is indispensable in clarifying the adaptation mechanism of plants to heavy metals. With the rapid pace of industrialization and urbanization, heavy metal pollution has been an environmental issue of global concern. Stomata, a special physiological structure of plants, play an important role in maintaining plant physiological and ecological functions. Recent studies have shown that heavy metals can affect the structure and function of stomata, leading to changes in plant physiology and ecology. However, although the scientific community has accumulated some data on the effects of heavy metals on plant stomata, the systematic understanding of the effects of heavy metals on plant stomata remains limited. Therefore, in this review, we present the sources and migration pathways of heavy metals in plant stomata, analyze systematically the physiological and ecological responses of stomata on heavy metal exposure, and summarize the current mechanisms of heavy metal toxicity on stomata. Finally, the future research perspectives of the effects of heavy metals on plant stomata are identified. This paper can serve as a reference for the ecological assessment of heavy metals and the protection of plant resources.

Genome-Wide Analysis of the ATP-Binding Cassette (ABC) Transporter Family in Zea mays L. and Its Response to Heavy Metal Stresses.

The ATP-binding cassette (ABC) transporter family is one of the largest eukaryotic protein families. Its members play roles in numerous metabolic processes in plants by releasing energy for substrate transport across membranes through hydrolysis of ATP. Maize belongs to the monocotyledonous plant family, Gramineae, and is one of the most important food crops in the world. We constructed a phylogenetic tree with individual ABC genes from maize, rice, sorghum, Arabidopsis, and poplar. This revealed eight families, each containing ABC genes from both monocotyledonous and dicotyledonous plants, indicating that the amplification events of ABC gene families predate the divergence of plant monocotyledons. To further understand the functions of ABC genes in maize growth and development, we analyzed the expression patterns of maize ABC family genes in eight tissues and organs based on the transcriptome database on the Genevestigator website. We identified 133 ABC genes expressed in most of the eight tissues and organs examined, especially during root and leaf development. Furthermore, transcriptome analysis of ZmABC genes showed that exposure to metallic lead induced differential expression of many maize ABC genes, mainly including ZmABC 012, 013, 015, 031, 040, 043, 065, 078, 080, 085, 088, 102, 107, 111, 130 and 131 genes, etc. These results indicated that ZmABC genes play an important role in the response to heavy metal stress. The comprehensive analysis of this study provides a foundation for further studies into the roles of ABC genes in maize.

Development and Validation of Machine Learning-Based Models for Prediction of Intensive Care Unit Admission and In-Hospital Mortality in Patients with Acute Exacerbations of Chronic Obstructive Pulmonary Disease.

Background: This present work focused on predicting prognostic outcomes of inpatients developing acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and enhancing patient monitoring and treatment by using objective clinical indicators. Methods: The present retrospective study enrolled 322 AECOPD patients. Registry data downloaded based on the chronic obstructive pulmonary disease (COPD) Pay-for-Performance Program database from January 2012 to December 2018 were used to check whether the enrolled patients were eligible. Our primary and secondary outcomes were intensive care unit (ICU) admission and in-hospital mortality, respectively. The best feature subset was chosen by recursive feature elimination. Moreover, 7 machine learning (ML) models were trained for forecasting ICU admission among AECOPD patients, and the model with the most excellent performance was used. Results: According to our findings, a random forest (RF) model showed superb discrimination performance, and the values of area under the receiver operating characteristic curve were 0.973 and 0.828 in training and test cohorts, separately. Additionally, according to decision curve analysis, the net benefit of the RF model was higher when differentiating patients with a high risk of ICU admission at a <0.55 threshold probability. Moreover, the ML-based prediction model was also constructed to predict in-hospital mortality, and it showed excellent calibration and discrimination capacities. Conclusion: The ML model was highly accurate in assessing the ICU admission and in-hospital mortality risk for AECOPD cases. Maintenance of model interpretability helped effectively provide accurate and lucid risk prediction of different individuals.

Trifolium repens L. recruits root-associated Microbacterium species to adapt to heavy metal stress in an abandoned Pb-Zn mining area.

Root-associated microbiota provide great fitness to hosts under environmental stress. However, the underlying microecological mechanisms controlling the interaction between heavy metal-stressed plants and the microbiota are poorly understood. In this study, we screened and isolated representative amplicon sequence variants (strain M4) from rhizosphere soil samples of Trifolium repens L. growing in areas with high concentrations of heavy metals. To investigate the microecological mechanisms by which T. repens adapts to heavy metal stress in abandoned mining areas, we conducted potting experiments, bacterial growth promotion experiments, biofilm formation experiments, and chemotaxis experiments. The results showed that high concentrations of heavy metals significantly altered the rhizosphere bacterial community structure of T. repens and significantly enriched Microbacterium sp. Strain M4 was demonstrated to significantly increased the biomass and root length of T. repens under heavy metal stress. Additionally, L-proline and stigmasterol could promote bacterial growth and biofilm formation and induce chemotaxis for strain M4, suggesting that they are key rhizosphere secretions of T. repens for Microbacterium sp. recruitment. Our results suggested that T. repens adapted the heavy metal stress by reshaping rhizosphere secretions to modify the rhizosphere microbiota.

Changes in soil microbe-mediated carbon, nitrogen and phosphorus cycling during spontaneous succession in abandoned PbZn mining areas.

The mechanism through which soil microorganisms mediate carbon and nutrient cycling during mine wasteland restoration remained unknown. Using soil metagenome sequencing, we investigated the dynamic changes in soil microbial potential metabolic functions during the transition from biological soil crusts (BSC) to mixed broad-conifer forest (MBF) in a typical PbZn mine. The results showed soil microorganisms favored carbon sequestration through anaerobic and microaerobic pathways, predominantly using efficient, low-energy pathways during succession. Genes governing carbon degradation and aerobic respiration increased by 19.56 % and 24.79 %, respectively, reflecting change toward more efficient and intensive soil carbon utilization in late succession. Nitrogen-cycling genes mediated by soil microorganisms met their maximum influence during early succession (sparse grassland, SGL), leading to a respective increase of 75.29 % and 76.81 % in the net potential nitrification rate and total nitrogen content. Mantel and correlation analyses indicated that TOC, TN, Zn and Cd contents were the main factors affecting the soil carbon and phosphorus cycles. Soil AP content emerged as the primary influencer of genes associated with the nitrogen cycle. These results shed light on the dynamic shifts in microbial metabolic activities during succession, providing a genetic insight into biogeochemical cycling mechanisms and underscoring crucial factors influencing soil biogeochemical processes in mining regions.

Drivers and mechanisms of spontaneous plant community succession in abandoned PbZn mining areas in Yunnan, China.

The drivers and mechanisms underlying succession and the spontaneous formation of plant communities in mining wasteland remain largely unknown. This study investigated the use of nature-based restoration to facilitate the recovery of viable plant communities in mining wasteland. It was found that scientific analyses of spontaneously formed plant communities in abandoned mining areas can provide insights for nature-based restoration. A chronosequence ("space for time") approach was used to establish sites representing three successional periods with six successional stages, and 90 quadrats were constructed to investigate changes in plant species and functional diversity during succession in abandoned PbZn mining areas. A total of 140 soil samples were collected to identify changes in soil properties, including plant nutrient and heavy metal concentrations. Then, this paper used structural equation models to analyze the mechanisms that drive succession. It was found that the functional diversity of plant communities fluctuated substantially during succession. Species had similar functional traits in early and mid-succession, but traits tended to diverge during late succession. Soil bulk density and soil organic matter gradually increased during succession. Total nitrogen (N), pH, and soil Zn concentrations first increased and then decreased during succession. Concentrations of Mn and Cd gradually decreased during succession. During early succession, soil organic matter was the key factor driving plant colonization and succession. During mid-succession, soil Zn functioned as an environmental filter factor limiting the rates of succession in mining wasteland communities. During late succession, soil bulk density and competition for nutrient resources contributed to more balanced differentiation among plant species. This thesis proposed that a nature-based strategy for the stabilization of abandoned mining lands could facilitate effective plant community restoration that promotes ecosystem services and functioning.