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Understanding the interplay between plant leaf functional traits and plant and soil factors under different soil thicknesses is significant for quantifying the interaction between plant growth and the environment. However, in the context of ecological restoration of vegetation in mining areas, there has been a lot of research on trees, shrubs, and grasses, but the characteristics and correlations of leaf functional traits of vines have not been fully studied to a large extent. Here, we report the differences in leaf functional traits of six vine plants (, , , , , and ) with distinct growth forms in different soil cover thicknesses (20 cm, 40 cm, and 60 cm). In addition, soil factor indicators under different soil cover thicknesses were measured to elucidate the linkages between leaf functional traits of vine plants and soil factors. We found that showed a resource acquisition strategy, while demonstrated a resource conservation strategy. and shifted toward more conservative resource allocation strategies as the soil cover thickness increased, whereas showed the opposite trend. In the plant trait-trait relationships, there were synergistic associations between specific leaf area (SLA) and leaf nitrogen content (LNC); leaf moisture content (LMC) and leaf nitrogen-to-phosphorus ratio (LN/P); and leaf specific dry weight (LSW), leaf succulence degree (LSD), and leaf dry matter content (LDMC). Trade-offs were observed between SLA and LSW, LSD, and LDMC; between leaf phosphorus content (LPC) and LN/P; and between LMC, LSW, and LDMC. In the plant trait-environment relationships, soil nutrients (pH, soil total phosphorus content (STP), and soil ammonium nitrogen content (SAN)) and soil enzyme activities (cellulase (CB), leucine aminopeptidase (LAP), enzyme C/N activity ratio, and enzyme N/P activity ratio) were identified as the primary drivers of variation in leaf functional traits. Interestingly, nitrogen deficiency constrained the growth of vine plants in the mining area. Our study revealed that the responses of leaf functional traits of different vines under different soil thicknesses have significant species specificity, and each vine shows different resource acquisition and conservation strategies. Furthermore, soil cover thickness primarily influences plant functional traits by directly affecting soil enzyme activities and nutrients. However, the pathways through which soil thickness impacts these traits differ among various functional traits. Our findings provide a theoretical basis and practical reference for selecting vine plants and optimizing soil cover techniques for ecological restoration in mining areas.
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http://dx.doi.org/10.3390/plants14142225 | DOI Listing |
Genome Biol
September 2025
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
Background: Soil salinization represents a critical global challenge to agricultural productivity, profoundly impacting crop yields and threatening food security. Plant salt-responsive is complex and dynamic, making it challenging to fully elucidate salt tolerance mechanism and leading to gaps in our understanding of how plants adapt to and mitigate salt stress.
Results: Here, we conduct high-resolution time-series transcriptomic and metabolomic profiling of the extremely salt-tolerant maize inbred line, HLZY, and the salt-sensitive elite line, JI853.
Theor Appl Genet
September 2025
Institute for Breeding Research on Agricultural Crops, Julius Kühn Institute (JKI) - Federal Research Centre for Cultivated Plants, Sanitz, 18190, Germany.
Low-cost and high-throughput RNA sequencing data for barley RILs achieved GP performance comparable to or better than traditional SNP array datasets when combined with parental whole-genome sequencing SNP data. The field of genomic selection (GS) is advancing rapidly on many fronts including the utilization of multi-omics datasets with the goal of increasing prediction ability and becoming an integral part of an increasing number of breeding programs ensuring future food security. In this study, we used RNA sequencing (RNA-Seq) data to perform genomic prediction (GP) on three related barley RIL populations.
View Article and Find Full Text PDFUrol Oncol
September 2025
Nutritional, Genes and Human Disease Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh. Electronic address:
Background: Understanding the mutational landscape is critical for elucidating the molecular mechanisms driving cancer progression. This study aimed to profile somatic mutations in bladder cancer patients (N=7) from Bangladesh to provide insights into the genetic alterations underlying this malignancy.
Methods: We performed targeted sequencing of 50 oncogenes and tumor suppressor genes using the Ion AmpliSeq Cancer Hotspot Panel v2 on tumor and matched blood samples from seven bladder cancer patients.
J Safety Res
September 2025
MAIC/UniSC Road Safety Research Collaboration, University of the Sunshine Coast, 90 Sippy Downs Drive, Sippy Downs, Queensland 4556, Australia.
Introduction: Despite decades of research and intervention, aggressive driving behavior (ADB) remains a prevalent risk on our roads. This study aimed to systematically review how drivers' personality traits, perceptual tendencies, self-regulatory capacity, and psychological functioning, have been linked to the engagement of ADBs.
Method: Under guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, a literature search was performed in four databases, followed by a manual search in Google Scholar.
Brain Behav Immun
September 2025
Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. Electronic address:
Background: The proteome is a valuable resource for pinpointing therapeutic targets. Therefore, we conducted a proteome-wide Mendelian randomization (MR) study aimed at identifying potential protein markers and therapeutic targets for Anti-N-Methyl-D-Aspartate Receptor Encephalitis (NMDAR-E).
Methods: Protein quantitative trait loci (pQTLs) were obtained from seven published genome-wide association studies (GWASs) focusing on the plasma proteome, resulting in summary-level data for 734 circulating protein markers.