Comprehensive analysis of PLATZ family genes and their responses to abiotic stresses in Barley.

BACKGROUND: Plant A/T-rich protein and zinc-binding protein (PLATZ) transcription factors are pivotal regulators in various aspects of plant biology, including growth, development, and responses to environmental stresses. While PLATZ genes have been extensively studied and functionally characterized in various plants, limited information is available for these genes in barley. RESULTS: Here, we discovered a total of 11 PLATZ genes distributed across seven chromosomes in barley. Based on phylogenetic and conserved motif analysis, we classified PLATZ into five subfamilies, comprising 3, 1, 2, 1 and 4 genes, respectively. Analysis of gene structure demonstrated that these 11 HvPLATZ genes typically possessed two to four exons. Most HvPLATZ genes were found to possess at least one ABRE cis-element in their promoter regions, and a few of them also contained LTR, CAT-box, MRE, and DRE cis-elements. Then, we conducted an exploration of the expression patterns of HvPLATZs, which displayed notable differences across various tissues and in response to abiotic stresses. Functional analysis of HvPLATZ6 and HvPLATZ8 in yeast cells showed that they may be involved in drought tolerance. Additionally, we constructed a regulatory network including miRNA-targeted gene predictions and identified two miRNAs targeting two HvPLATZs, such as hvu-miR5053 and hvu-miR6184 targeting HvPLATZ2, hvu-miR6184 targeting HvPLATZ10. CONCLUSION: In summary, these findings provide valuable insights for future functional verification of HvPLATZs and contribute to a deeper understanding of the role of HvPLATZs in response to stress conditions in barley.

Characterization and source identification of PM2.5-bound polycyclic aromatic hydrocarbons in urban, suburban, and rural ambient air, central China during summer harvest.

Characterization and source identification of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) are conducted in urban Wuhan (WH), suburban Pingdingshan (PDS), and rural Suizhou (SZ) in China during summer harvest. This study analyzes 16 priority PAHs with 38 PM.2.5 samples in June. PAHs had similar physical-chemical properties like polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs), which had been listed as Priority Pollutants. The concentration and detection frequency of OCPs and PCBs were considerably lower than those of PAHs in PM2.5. Results indicate that PDS adjoining the highway has the highest PM2.5-bound PAHs. SZ possesses the lowest concentration of PAHs. Principal component analysis and multivariate linear regression model and molecular diagnostic ratio distinguish the sources. Vehicle emissions and coal combustion are extracted in three sites, while the source of PDS also includes gas combustion. SZ was affected by gas combustion and petroleum. The potential source contribution function and the concentration-weighted trajectory track the potential pollution area. The sampling places might be affected by the local sources and short distance transmission cannot be neglected. The incremental lifetime cancer risks (ILCRs) model evaluates the exposure risk of PAHs. According to the ILCR model, WH and PDS are exposed to harmful PAHs. By contrast, SZ is a substantially safe place.

Biomass burning contributed most to the human cancer risk exposed to the soil-bound PAHs from Chengdu Economic Region, western China.

The purpose of this study was to assess the human cancer risk due to the exposure to the soil-bound polycyclic aromatic hydrocarbons (PAHs) from Chengdu Economic Region (CER), western China with the main concern on cancer risk source apportionment. The total concentrations of sixteen PAHs ranged from 12.5 to 75431 ng g-1, with a mean value of 3106 ng g-1, which suggested that the most areas of CER were contaminated. Source apportionment of PAHs was conducted by the positive matrix factorization (PMF) model and the biomass burning contributed most (63.6%) to the total PAHs, followed by petroleum combustion (16.0%), coke source (11.3%), and petrogenic source (9.2%). Results from incremental lifetime cancer risk (ILCR) calculation showed that soil ingestion exerted the highest cancer risk (accounted for 98.1 - 99.3% of the total cancer risk) on human health among three different exposure pathways, followed by dermal contact (0.66 - 1.83%) and inhalation (0.03 - 0.04%). Among different age groups, adult suffered the highest cancer risk via any exposure pathways. Based on PMF and ILCR methods, the cancer risk source apportionment was conducted and the biomass burning showed moderate cancer risk. The petrogenic, coke, and petroleum sources showed low cancer risks to human. To analyze the sensitivity of the parameters used in ILCR calculation, Monte Carlo simulation was employed. The results indicated that the contribution of each source and exposure duration (ED) were the influential parameters on human health associated with soil-bound PAHs. Therefore, much attentions should be paid to biomass burning to avoid cumulative cancer risk.

[Characteristics and Sources of Elements in PM2.5 During Summer for Three Typical Cities in Pingdingshan-Suizhou-Wuhan, Central China].

This study investigates the elemental characteristics and sources of aerosol fine particulate matter (PM2.5) samples obtained from Pingdingshan, Suizhou, and Wuhan, Central China, in June 2017. Thirteen kinds of elements (Ti, Zn, Cu, Cr, As, Pb, Fe, Ni, Se, V, Sb, Cd, and Co) were analyzed by inductively coupled plasma mass spectrometry (ICP-MS), and three source identification methods-enrichment factor, principle component analysis and multiple linear regression (PCA-MLR), and backward trajectory clustering-were applied. The results showed that Zn was the highest trace element in PM2.5 in samples from Pingdingshan, Suizhou, and Wuhan, and that the concentration of As exceeded the annual limit of Chinese air quality standards (GB 3096-2012). Concentrations of Pb and Cd in PM2.5 in samples from the three cities during the summer were low. The enrichment factor coefficients for Se, Sb, Cd, As, Cu, and Zn exceeded 10, which suggests that summer pollution from human activities was serious, for example, the enrichment factor coefficient for Se was>600. PCA-MLR and backward trajectory clustering analysis results showed that the main pollution sources in Pingdingshan during the summer were industrial fuel oil (57.90% of total), traffic pollution (24.40%), coal combustion (6.10%), and mine soil (11.60%). The main pollution source in Suizhou was fuel, which contributed 54.30% of the total. Wuhan was mainly affected by industrial emissions (60.80% of the total) and motor vehicle pollution (39.20%). Hence, Wuhan and Suizhou were mainly affected by local source emissions, whereas Pingdingshan was jointly affected by local emissions and regional inputs during the summer.

Source apportionment of polycyclic aromatic carbons (PAHs) in sediment core from Honghu Lake, central China: comparison study of three receptor models.

The spatial distribution of polycyclic aromatic hydrocarbons (PAHs) and their source contributions employing receptor models has been widely reported. However, the temporal distribution of PAH source contributions is less studied. Thus, in this paper, three receptor models including principle component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF), and Unmix were used to PAH source apportionment study in a sediment core from Honghu Lake, China. Sixteen USEPA priority PAHs in 37 sliced sediment layers (1-cm interval) were measured, with the concentrations of ∑16PAH (sum of 16 PAHs) ranging from 93.0 to 431 ng g-1. The source apportionment results derived from three receptor models were similar, with three common sources: mixed sources of biomass burning and coal combustion (31.0-41.4% on average), petroleum combustion (31.8-45.5%), and oil leakage (13.1-21.3%). The PMF model segregated an additional source: domestic coal combustion (contributed 20.9% to the ∑16PAHs). Four aspects including intra-comparison, inter-comparison, source numbers and compositions, and source contributions were considered in comparison study. The results indicated that the PMF model was most reasonable in PAH source apportionment research in this study.