Competition mode and soil nutrient status shape the role of soil microbes in the diversity-invasibility relationship.

Understanding the relationship between plant diversity and invasibility is essential in invasion ecology. Species-rich communities are hypothesized to be more resistant to invasions than species-poor communities. However, while soil microorganisms play a crucial role in regulating this diversity-invasibility relationship, the effects of plant competition mode and soil nutrient status on their role remain unclear. To address this, we conducted a two-stage greenhouse experiment. Soils were first conditioned by growing nine native species separately in them for 1 year, then mixed in various configurations with soils conditioned using one, three, or six species, respectively. Next, we inoculated the mixed soil into sterilized substrate soil and planted the alien species Rhus typhina and native species Ailanthus altissima as test plants. We set up two competition modes (intraspecific and interspecific) and two nutrient levels (fertilization using slow-release fertilizer and nonfertilization). Under intraspecific competition, regardless of fertilization, the biomass of the alien species was higher in soil conditioned by six native species. By contrast, under interspecific competition, the biomass increased without fertilization but remained stable with fertilization in soil conditioned by six native species. Analysis of soil microbes suggests that pathogens and symbiotic fungi in diverse plant communities influenced R. typhina growth, which varied with competition mode and nutrient status. Our findings suggest that the soil microbiome is pivotal in mediating the diversity-invasibility relationship, and this influence varies according to competition mode and nutrient status.

Crowdsourcing Skin Demarcations of Chronic Graft-Versus-Host Disease in Patient Photographs: Training Versus Performance Study.

BACKGROUND: Chronic graft-versus-host disease (cGVHD) is a significant cause of long-term morbidity and mortality in patients after allogeneic hematopoietic cell transplantation. Skin is the most commonly affected organ, and visual assessment of cGVHD can have low reliability. Crowdsourcing data from nonexpert participants has been used for numerous medical applications, including image labeling and segmentation tasks. OBJECTIVE: This study aimed to assess the ability of crowds of nonexpert raters-individuals without any prior training for identifying or marking cGHVD-to demarcate photos of cGVHD-affected skin. We also studied the effect of training and feedback on crowd performance. METHODS: Using a Canfield Vectra H1 3D camera, 360 photographs of the skin of 36 patients with cGVHD were taken. Ground truth demarcations were provided in 3D by a trained expert and reviewed by a board-certified dermatologist. In total, 3000 2D images (projections from various angles) were created for crowd demarcation through the DiagnosUs mobile app. Raters were split into high and low feedback groups. The performances of 4 different crowds of nonexperts were analyzed, including 17 raters per image for the low and high feedback groups, 32-35 raters per image for the low feedback group, and the top 5 performers for each image from the low feedback group. RESULTS: Across 8 demarcation competitions, 130 raters were recruited to the high feedback group and 161 to the low feedback group. This resulted in a total of 54,887 individual demarcations from the high feedback group and 78,967 from the low feedback group. The nonexpert crowds achieved good overall performance for segmenting cGVHD-affected skin with minimal training, achieving a median surface area error of less than 12% of skin pixels for all crowds in both the high and low feedback groups. The low feedback crowds performed slightly poorer than the high feedback crowd, even when a larger crowd was used. Tracking the 5 most reliable raters from the low feedback group for each image recovered a performance similar to that of the high feedback crowd. Higher variability between raters for a given image was not found to correlate with lower performance of the crowd consensus demarcation and cannot therefore be used as a measure of reliability. No significant learning was observed during the task as more photos and feedback were seen. CONCLUSIONS: Crowds of nonexpert raters can demarcate cGVHD images with good overall performance. Tracking the top 5 most reliable raters provided optimal results, obtaining the best performance with the lowest number of expert demarcations required for adequate training. However, the agreement amongst individual nonexperts does not help predict whether the crowd has provided an accurate result. Future work should explore the performance of crowdsourcing in standard clinical photos and further methods to estimate the reliability of consensus demarcations.

Research on primary Sjögren's syndrome in 2004-2021: a Web of Science-based cross-sectional bibliometric analysis.

The extent, range, and nature of available research in the field of primary Sjögren's syndrome (pSS) have not been understood fully. This study aimed to map the literature available on pSS, and identify global hotspots and trends in the research. Papers on pSS published between 2004 and 2021 were searched from Web of Science Core Collection. The quantity and citations of publications, and the research hotspots and trends in the field of pSS were analyzed and presented visually by Microsoft Excel and Citespace software. A total of 3606 papers mainly from 526 institutions in 83 countries/regions were included for analysis. The number of publications presented an overall upward trend in the field of pSS from 2004 to 2021. The USA ranked first in the number of publications (n = 661), followed by China (n = 491), Italy (n = 405), France (n = 351), and Japan (n = 292). Moreover, seven of the top ten countries by the number of publications on pSS were from Europe. The University of Groningen (n = 661), Xavier Mariette (n = 95), and Clinical and Experimental Rheumatology (n = 184) were the most prolific affiliation, author, and journal, respectively. Vitali C (n = 2009) and Arthritis and Rheumatism (n = 3918) held the record for the most cited papers by an author and journal, respectively. At present, the hot keywords in the field of pSS include disease activity, ultrasonography, management, consensus, and data-driven. Lymphoid organization, clinical phenotypes outcome, salivary gland ultrasonography, and Toll-like receptor are the emerging research trends in pSS. Research on pSS is flourishing. Current research of pSS mainly focuses on disease activity, ultrasonography, and management. While, the emerging research trends in pSS are lymphoid organization, clinical phenotypes outcome, salivary gland ultrasonography, and Toll-like receptor.

Identification of the Molecular Subgroups in Idiopathic Pulmonary Fibrosis by Gene Expression Profiles.

BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is one of the most common idiopathic interstitial pneumonia, which can occur all over the world. The median survival time of patients is about 3-5 years, and the mortality is relatively high. OBJECTIVE: To reveal the potential molecular characteristics of IPF and deepen the understanding of the molecular mechanism of IPF. In order to provide some guidance for the clinical treatment, new drug development, and prognosis judgment of IPF. Although the preliminary conclusion of this study has certain guiding significance for the treatment of IPF and so on, it needs more accurate analytical approaches and large sample clinical trials to verify. METHODS: 220 patients with IPF were divided into different subgroups according to the gene expression profiles, which were obtained from the Gene Expression Omnibus (GEO) database. In addition, these subgroups present different expression forms and clinical features. Therefore, weighted gene coexpression analysis (WGCNA) was used to seek the differences between subtypes. And six subgroup-specific WGCNA modules were identified. RESULTS: Combined with the characteristics of WGCNA and KEGG enrichment modules, the autophagic pathway was only upregulated in subgroup I and enriched significantly. The differentiation pathways of Th1 and Th2 cells were only upregulated and enriched in subgroup II. At the same time, combined with clinical information, IPF patients in subgroup II were older and more serious, which may be closely related to the differentiation of Th1 and Th2 cells. In contrast, the neuroactive ligand-receptor interaction pathway and Ca+ signaling pathway were significantly upregulated and enriched in subgroup III. Although there was no significant difference in prognosis between subgroup I and subgroup III, their intrinsic biological characteristics were very different. These results suggest that the subtypes may represent risk factors of age and intrinsic biological characteristics and may also partly reflect the severity of the disease. CONCLUSION: In conclusion, current studies have improved our understanding of IPF-related molecular mechanisms. At the same time, because the results show that patients from different subgroups may have their own unique gene expression patterns, it reminds us that patients in each subgroup should receive more personalized treatment.

Quantifying compliance with COVID-19 mitigation policies in the US: A mathematical modeling study.

The outbreak of COVID-19 disrupts the life of many people in the world. In response to this global pandemic, various institutions across the globe had soon issued their prevention guidelines. Governments in the US had also implemented social distancing policies. However, those policies, which were designed to slow the spread of COVID-19, and its compliance, have varied across the states, which led to spatial and temporal heterogeneity in COVID-19 spread. This paper aims to propose a spatio-temporal model for quantifying compliance with the US COVID-19 mitigation policies at a regional level. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with short-term predictions. The proposed model describes the combined effects of transboundary spread among state clusters in the US and human mobilities on the transmission of COVID-19. The model can help inform policymakers as they decide how to react to future outbreaks.

Spatial-temporal pattern evolution and driving force analysis of ecological environment vulnerability in Panzhihua City.

Panzhihua City, a typical eco-fragile region for agro-sylvo-pastoral industry in China, is located in the dry-hot valley of the Jinsha River, characterized by its big landform undulation, great elevation difference, uneven hydrothermal conditions, and complex geological structure. As a crucial ecological barrier in upper reaches of the Yangtze River, this area is abundant in water resources and mineral resources, such as vanadium and titanium. However, due to its over-development for nonnatural urban economy in the mining industry, agriculture, and animal husbandry, ecological problems are getting worse. Such problems as soil erosion and groundwater pollution have led obvious ecological degeneration in Panzhihua city. Therefore, for protecting the eco-environment and planning construction, it is significant to scientifically recognize that how eco-environment changes based on spatial-temporal, and how the driving mechanism affects Panzhihua city. Nowadays, there are some theories and methods that study eco-environmental protection and city construction in Panzhihua, but they are not comprehensive enough to study its spatial-temporal evolution and driving-force system. This study takes Panzhihua City as the research area of which evaluation factors, for example, topography, soil, vegetation, and meteorological factors, are chosen to construct an evaluation system suitable for the ecological environment vulnerability of Panzhihua City. These factors are selected in three aspects, which are ecological sensitivity, ecological recovery, and ecological pressure from 2005 to 2015 in this area. Then, spatial principal component analysis method, CA-Markov model, and dynamic degree model are applied to analyze the spatial-temporal evolution for ecological vulnerability based on three periods from 2005 to 2015 in Panzhihua City. Besides, GeoDetector is used to quantitatively analyze how spatial-temporal disparities change and what drives them to change. The results show that (1) during these 10 years, the overall ecological fragility of Panzhihua City is steadily increasing from northwest to southeast. The overall ecological quality is moderate, and regional differences are obvious. Places of moderate vulnerability or above are distributed in central and eastern regions of frequent human activities; places of mild vulnerability or below are distributed in the regions of Yanbian County and Miyi County. (2) The comparison of the changing rates based on vulnerability levels is severe > potential > moderate > mild > slight. The overall vulnerability changes within a small trend, showing a balanced two-way transition state between adjacent vulnerability levels. The comprehensive index for overall ecological vulnerability decreases period by period. (3) The interactions between each two factors toward spatial differentiation and explanatory power by ecological vulnerability show a two-factor-enhanced relation, indicating that multiple factors form the ecological vulnerability of Panzhihua City.