This research examines the role of plant functional traits in driving ecosystem stability across distinct environmental contexts, specifically temperate and alpine grasslands in China. The study leverages a comprehensive dataset that includes in situ measurements of 16 morphological and chemical traits from 343 plant species, alongside 23 years of satellite-derived ecosystem productivity indices. By combining field data with advanced analytical approaches, including principal component analysis (PCA), Bayesian univariate and multivariate models, and Bayesian structural equation modeling (BSEM), this work provides a nuanced understanding of how trait-stability relationships are mediated by environmental conditions.To facilitate transparency and reproducibility, we have uploaded the complete set of R code used in the analysis. This includes scripts for performing PCA, Bayesian univariate and multivariate analyses, and BSEM, as well as generating the primary figures and key results presented in the manuscript. As the manuscript undergoes revisions, the code may be updated accordingly to reflect methodological refinements or new insights.If you have any questions regarding the analysis or the uploaded materials, please feel free to contact Dr. Pu Yan at pyan40@gatech.edu.

Supplementary files for article "The seventh blind test of crystal structure prediction: structure generation methods"

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures.

(Please refer to https://hdl.handle.net/2134/27979856.v1 for full list of Authors)

© The Author(s), CC BY 4.0

Supplementary files for article "The seventh blind test of crystal structure prediction: structure generation methods"

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures.

(Please refer to https://hdl.handle.net/2134/27979856.v1 for full list of Authors)

© The Author(s), CC BY 4.0

This research examines the role of plant functional traits in driving ecosystem stability across distinct environmental contexts, specifically temperate and alpine grasslands in China. The study leverages a comprehensive dataset that includes in situ measurements of 16 morphological and chemical traits from 343 plant species, alongside 23 years of satellite-derived ecosystem productivity indices. By combining field data with advanced analytical approaches, including principal component analysis (PCA), Bayesian univariate and multivariate models, and Bayesian structural equation modeling (BSEM), this work provides a nuanced understanding of how trait-stability relationships are mediated by environmental conditions.To facilitate transparency and reproducibility, we have uploaded the complete set of R code used in the analysis. This includes scripts for performing PCA, Bayesian univariate and multivariate analyses, and BSEM, as well as generating the primary figures and key results presented in the manuscript. As the manuscript undergoes revisions, the code may be updated accordingly to reflect methodological refinements or new insights.If you have any questions regarding the analysis or the uploaded materials, please feel free to contact Dr. Pu Yan at pyan40@gatech.edu.

Stomata are the valves controlling the exchange of carbon dioxide and water vapor between plants and the atmosphere, and their evolution played a crucial role in enabling the colonization of terrestrial habitats and formation of terrestrial ecosystems 1. Stomata are made up of pairs of guard cells, which are kidney-shaped in most plants, and dumbbell-shaped in grasses, and flanked by specialized subsidiary cells. Several studies among small, diverse species showed that the opening and closing processes of these stomatal types differ.

Stomata are the valves controlling the exchange of carbon dioxide and water vapor between plants and the atmosphere, and their evolution played a crucial role in enabling the colonization of terrestrial habitats and formation of terrestrial ecosystems 1. Stomata are made up of pairs of guard cells, which are kidney-shaped in most plants, and dumbbell-shaped in grasses, and flanked by specialized subsidiary cells. Several studies among small, diverse species showed that the opening and closing processes of these stomatal types differ.

Systemic lupus erythematosus (SLE), an autoimmune condition, presents pregnancy-related risks, impacting maternal and fetal health. The immune cell composition and gene expression profiles in pregnant SLE patients, as well as the molecular mechanisms of active SLE patients during pregnancy, remain unclear. In our study, we enrolled 12 patients: three active SLE individuals (SLE-AT group, SLEDAI > 12, non-pregnant women), three inactive SLE individuals (SLE-NP group, SLEDAI ranging 0 to 6, non-pregnant women), three pregnant women with active SLE (SLE-C group, SLEDAI > 12), and three pregnant women with inactive SLE (SLE-NC group, SLEDAI range 0 to 6 score). Transcriptome analysis of peripheral blood mononuclear cells (PBMCs) was conducted using the 10x Genomics technique. We observed upregulation of genes like CCDC15 and TRBV4-2 in T cells and CMPK2, IFIT1, and OAS2 in monocytes in the SLE-C group. Notably, gene sets related to Cell Cycle and IFN Response showed significant differences between the SLE-C and SLE-NC groups in naïve CD8 T cells. Our comparison of immune cell type ratios and transcriptional patterns between active and inactive SLE during pregnancy sheds light on the single-cell level changes in SLE status during pregnancy, offering insights for future SLE prediction and treatment strategies. Systemic lupus erythematosus (SLE) is a complex autoimmune disease. Furthermore, SLE women have an increased likelihood of encountering adverse pregnancy outcomes such as diabetes and hypertension. The etiology of SLE involves a multifaceted interplay of genetic, immune, endocrine, and environmental factors, which contributes to a breakdown in the immune system’s tolerance to self-antigens. Recent studies have highlighted a strong correlation between the severity of renal involvement in lupus nephritis and B cell dysfunction in patients, as elucidated through single-cell transcriptomics. Additionally, comparative studies have revealed notable differences in the immune cell profile between pregnant women with lupus and healthy pregnant women. A key observation the marked reduction in the proportion of CD4+ T cells in pregnant women suffering from lupus. Despite these findings, the detailed transcriptomic alterations within high-resolution immune cell profiling during activate phase of SLE in pregnancy remain inadequately understood. In our study, we focused on comparing the transcriptomic expression patterns of peripheral blood immune cells between pregnant women with active SLE and those with stable SLE. Our data confirmed significant differences in IFN signaling and pregnancy-related factors in T cells, NK cells, B cells, and macrophages, contrasting the immune cells of pregnant women with active SLE against those with stable SLE. Additionally, the proportion of CD56+ NK cells was significantly increased in pregnant women with SLE. The correlation between the transcriptomic profiles of immune cells and the activity of SLE during pregnancy may provide potential strategies for predicting and treating SLE during pregnancy.

Systemic lupus erythematosus (SLE), an autoimmune condition, presents pregnancy-related risks, impacting maternal and fetal health. The immune cell composition and gene expression profiles in pregnant SLE patients, as well as the molecular mechanisms of active SLE patients during pregnancy, remain unclear. In our study, we enrolled 12 patients: three active SLE individuals (SLE-AT group, SLEDAI > 12, non-pregnant women), three inactive SLE individuals (SLE-NP group, SLEDAI ranging 0 to 6, non-pregnant women), three pregnant women with active SLE (SLE-C group, SLEDAI > 12), and three pregnant women with inactive SLE (SLE-NC group, SLEDAI range 0 to 6 score). Transcriptome analysis of peripheral blood mononuclear cells (PBMCs) was conducted using the 10x Genomics technique. We observed upregulation of genes like CCDC15 and TRBV4-2 in T cells and CMPK2, IFIT1, and OAS2 in monocytes in the SLE-C group. Notably, gene sets related to Cell Cycle and IFN Response showed significant differences between the SLE-C and SLE-NC groups in naïve CD8 T cells. Our comparison of immune cell type ratios and transcriptional patterns between active and inactive SLE during pregnancy sheds light on the single-cell level changes in SLE status during pregnancy, offering insights for future SLE prediction and treatment strategies. Systemic lupus erythematosus (SLE) is a complex autoimmune disease. Furthermore, SLE women have an increased likelihood of encountering adverse pregnancy outcomes such as diabetes and hypertension. The etiology of SLE involves a multifaceted interplay of genetic, immune, endocrine, and environmental factors, which contributes to a breakdown in the immune system’s tolerance to self-antigens. Recent studies have highlighted a strong correlation between the severity of renal involvement in lupus nephritis and B cell dysfunction in patients, as elucidated through single-cell transcriptomics. Additionally, comparative studies have revealed notable differences in the immune cell profile between pregnant women with lupus and healthy pregnant women. A key observation the marked reduction in the proportion of CD4+ T cells in pregnant women suffering from lupus. Despite these findings, the detailed transcriptomic alterations within high-resolution immune cell profiling during activate phase of SLE in pregnancy remain inadequately understood. In our study, we focused on comparing the transcriptomic expression patterns of peripheral blood immune cells between pregnant women with active SLE and those with stable SLE. Our data confirmed significant differences in IFN signaling and pregnancy-related factors in T cells, NK cells, B cells, and macrophages, contrasting the immune cells of pregnant women with active SLE against those with stable SLE. Additionally, the proportion of CD56+ NK cells was significantly increased in pregnant women with SLE. The correlation between the transcriptomic profiles of immune cells and the activity of SLE during pregnancy may provide potential strategies for predicting and treating SLE during pregnancy.

Functional diversity and soil nutrients regulate the interannual variability in gross primary productivity

Functional diversity and soil nutrients regulate the interannual variability in gross primary productivity