The LTAR Grazing Land Common Experiment at Northern Plains.

The USDA Long-Term Agroecosystem Research (LTAR) network aims to enhance sustainable agricultural management practices through a coordinated, cross-site common experiment involving 18 locations across the United States. The objective of this paper is to provide an overview of the LTAR grazing lands common experiment at the Northern Plains (NP) site, where an experiment was initiated in 2019 to answer producers' and researchers' questions about whether the tactical application of fire or grazing can reduce the dominance of invasive Kentucky bluegrass in northern Great Plains ecosystems. As part of the LTAR common experiment, we contrast a prevailing practice (season-long grazing at moderate stocking rate) with four alternative practices at a half-hectare plot scale: (1) mob grazing by cattle, (2) multi-species grazing (mob grazing by cattle, with goats foraging at key times of the year), (3) prescribed fire, and (4) prescribed fire followed by cattle grazing. A stakeholder group is engaged in the co-production process to determine alternative practices and how to apply them. Every 5 years, the treatment with the best overall outcomes is applied at a field scale (15 ha), resulting in a core treatment contrast of prevailing versus alternative grazing management systems. This experiment aims to develop alternative agroecological practices that optimize current and future economic and ecosystem benefits.

MAMS: matrix and analysis metadata standards to facilitate harmonization and reproducibility of single-cell data.

Many datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While biospecimen and experimental information is often captured, detailed metadata standards related to data matrices and analysis workflows are currently lacking. To address this, we develop the matrix and analysis metadata standards (MAMS) to serve as a resource for data centers, repositories, and tool developers. We define metadata fields for matrices and parameters commonly utilized in analytical workflows and developed the rmams package to extract MAMS from single-cell objects. Overall, MAMS promotes the harmonization, integration, and reproducibility of single-cell data across platforms.

Integrated vegetation management within electrical transmission landscapes promotes floral resource and flower-visiting insect diversity.

Electrical transmission rights-of-way are ubiquitous and critical infrastructure across the landscape. Active vegetation management of these rights-of-way, a necessity to deliver electricity more safely, maintains these landscape features as stages of early successional habitat, a rarity in many regions, making these areas viable movement corridors for many taxa. The goals of this study were to (i) evaluate the effects of different electrical transmission landscape management practices on flowering plant and flower-visiting insect diversity parameters and (ii) generate conservation management inferences for these landscapes. In this study we tested the impact of three vegetation management levels across 18 electrical transmission sites. We evaluated the effects of treatment on bloom abundance and species richness as well as flower-visiting insect abundance and family richness. We identified 76541 flowers/inflorescences across 456 transects, including 188 species in 56 plant families. Additionally, we obtained data on 11361 flower-visitoring insects representing 33 families from 2376 pan trap sets. High vegetation management favored the reduction of coarse woody debris in the sites and harbored the highest level of abundance and richness of both floral resources and flower-visiting insects. We discuss that we can align social and ecological values of rights-of-way, ensuring their sustainability by applying regular and targeted integrated vegetation management. Thus, we can use rights-of-way landscapes not only as an effective management strategy for the delivery of essential human services, but also to provide conservation benefits for wild pollinators.

PGC-1α agonism induces fetal hemoglobin and exerts antisickling effects in sickle cell disease.

Sickle cell disease is a growing health burden afflicting millions around the world. Clinical observation and laboratory studies have shown that the severity of sickle cell disease is ameliorated in individuals who have elevated levels of fetal hemoglobin. Additional pharmacologic agents to induce sufficient fetal hemoglobin to diminish clinical severity is an unmet medical need. We recently found that up-regulation of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) can induce fetal hemoglobin synthesis in human primary erythroblasts. Here, we report that a small molecule, SR-18292, increases PGC-1α leading to enhanced fetal hemoglobin expression in human erythroid cells, ß-globin yeast artificial chromosome mice, and sickle cell disease mice. In SR-18292-treated sickle mice, sickled red blood cells are significantly reduced, and disease complications are alleviated. SR-18292, or agents in its class, could be a promising additional therapeutic for sickle cell disease.

Repetitive head impacts induce neuronal loss and neuroinflammation in young athletes.

Repetitive head impacts (RHI) sustained from contact sports are the largest risk factor for chronic traumatic encephalopathy (CTE). Currently, CTE can only be diagnosed after death and the multicellular cascade of events that trigger initial hyperphosphorylated tau (p-tau) deposition remain unclear. Further, the symptoms endorsed by young individuals with early disease are not fully explained by the extent of p-tau deposition, severely hampering development of therapeutic interventions. Here, we show that RHI exposure associates with a multicellular response in young individuals (<51 years old) prior to the onset of CTE p-tau pathology that correlates with number of years of RHI exposure. Leveraging single nucleus RNA sequencing of tissue from 8 control, 9 RHI-exposed, and 11 low stage CTE individuals, we identify SPP1+ inflammatory microglia, angiogenic and inflamed endothelial cell profiles, reactive astrocytes, and altered synaptic gene expression in excitatory and inhibitory neurons in all individuals with exposure to RHI. Surprisingly, we also observe a significant loss of cortical sulcus layer 2/3 neurons in contact sport athletes compared to controls independent of p-tau pathology. These results provide robust evidence that multiple years of RHI exposure is sufficient to induce lasting cellular alterations that may underlie p-tau deposition and help explain the early clinical symptoms observed in young former contact sport athletes. Furthermore, these data identify specific cellular responses to repetitive head impacts that may direct future identification of diagnostic and therapeutic strategies for CTE.

Myc Dysregulation in Activated Macrophages Initiates Iron-Mediated Lipid Peroxidation that Fuels Type I Interferon and Compromises TB Resistance.

A quarter of human population is infected with Mycobacterium tuberculosis, but less than 10% of those infected develop clinical, mostly pulmonary, TB. To dissect mechanisms of susceptibility in immunocompetent individuals, we developed a genetically defined sst1-susceptible mouse model that uniquely reproduces a defining feature of human TB: development of necrotic lung lesions after infection with virulent Mtb. In this study, we explored the connectivity of the sst1-regulated pathways during prolonged macrophage activation with TNF. We determined that the aberrant response of the sst1-susceptible macrophages to TNF was primarily driven by conflicting Myc and antioxidant response pathways that resulted in a coordinated failure to properly sequester intracellular iron and activate ferroptosis inhibitor enzymes. Consequently, iron-mediated lipid peroxidation fueled IFNß superinduction and sustained the Type I Interferon (IFN-I) pathway hyperactivity that locked the sst1-susceptible macrophages in a state of unresolving stress and compromised their resistance to Mtb. The accumulation of the aberrantly activated, stressed, macrophages within granuloma microenvironment led to the local failure of anti-tuberculosis immunity and tissue necrosis. Our findings suggest a novel link between metabolic dysregulation in macrophages and susceptibility to TB, offering insights into potential therapeutic targets aimed at modulating macrophage function and improving TB control.

Endothelial Erg Regulates Expression of Pulmonary Lymphatic Junctional and Inflammation Genes in Mouse Lungs Impacting Lymphatic Transport.

The ETS transcription factor ERG is a master regulator of endothelial gene specificity and highly enriched in the capillary, vein, and arterial endothelial cells. ERG expression is critical for endothelial barrier function, permeability, and vascular inflammation. A dysfunctional vascular endothelial ERG has been shown to impair lung capillary homeostasis, contributing to pulmonary fibrosis as previously observed in IPF lungs. Our preliminary observations indicate that lymphatic endothelial cells (LEC) in the human IPF lung also lack ERG. To understand the role of ERG in pulmonary LECs, we developed LEC-specific inducible Erg-CKO and Erg-GFP-CKO conditional knockout (CKO) mice under Prox1 promoter. Whole lung microarray analysis, flow cytometry, and qPCR confirmed an inflammatory and pro-lymphvasculogenic predisposition in Erg-CKO lung. FITC-Dextran tracing analysis showed an increased pulmonary interstitial lymphatic fluid transport from the lung to the axial lymph node. Single-cell transcriptomics confirmed that genes associated with cell junction integrity were downregulated in Erg-CKO pre-collector and collector LECs. Integrating Single-cell transcriptomics and CellChatDB helped identify LEC specific communication pathways contributing to pulmonary inflammation, trans-endothelial migration, inflammation, and Endo-MT in Erg-CKO lung. Our findings suggest that downregulation of lymphatic Erg crucially affects LEC function, LEC permeability, pulmonary LEC communication pathways and lymphatic transcriptomics.

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro.

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. In an exploratory analysis of PBMC datasets, we find that some droplets that were originally called 'empty' due to low levels of RNA contained high levels of ADTs and likely corresponded to neutrophils. We identified a novel type of artifact in the empty droplets called a 'spongelet' which has medium levels of ADT expression and is distinct from ambient noise. ADT expression levels in the spongelets correlate to ADT expression levels in the background peak of true cells in several datasets suggesting that they can contribute to background noise along with ambient ADTs. We then developed DecontPro, a novel Bayesian hierarchical model that can decontaminate ADT data by estimating and removing contamination from these sources. DecontPro outperforms other decontamination tools in removing aberrantly expressed ADTs while retaining native ADTs and in improving clustering specificity. Overall, these results suggest that identification of empty drops should be performed separately for RNA and ADT data and that DecontPro can be incorporated into CITE-seq workflows to improve the quality of downstream analyses.

Characterization of highly active mutational signatures in tumors from a large Chinese population.

The majority of mutational signatures have been characterized in tumors from Western countries and the degree to which mutational signatures are similar or different in Eastern populations has not been fully explored. We leveraged a large-scale clinical sequencing cohort of tumors from a Chinese population containing 25 tumor types and found that the highly active mutational signatures were similar to those previously characterized1,2. The aristolochic acid signature SBS22 was observed in four soft tissue sarcomas and the POLE-associated signature SBS10 was observed in a gallbladder carcinoma. In lung adenocarcinoma, the polycyclic aromatic hydrocarbon (PAH) signature SBS4 was significantly higher in males compared to females but not associated with smoking status. The UV-associated signature SBS7 was significantly lower in cutaneous melanomas from the Chinese population compared to a similar American cohort. Overall, these results add to our understanding of the mutational processes that contribute to tumors from the Chinese population.

Bulk brain tissue cell-type deconvolution with bias correction for single-nuclei RNA sequencing data using DeTREM.

BACKGROUND: Quantifying cell-type abundance in bulk tissue RNA-sequencing enables researchers to better understand complex systems. Newer deconvolution methodologies, such as MuSiC, use cell-type signatures derived from single-cell RNA-sequencing (scRNA-seq) data to make these calculations. Single-nuclei RNA-sequencing (snRNA-seq) reference data can be used instead of scRNA-seq data for tissues such as human brain where single-cell data are difficult to obtain, but accuracy suffers due to sequencing differences between the technologies. RESULTS: We propose a modification to MuSiC entitled 'DeTREM' which compensates for sequencing differences between the cell-type signature and bulk RNA-seq datasets in order to better predict cell-type fractions. We show DeTREM to be more accurate than MuSiC in simulated and real human brain bulk RNA-sequencing datasets with various cell-type abundance estimates. We also compare DeTREM to SCDC and CIBERSORTx, two recent deconvolution methods that use scRNA-seq cell-type signatures. We find that they perform well in simulated data but produce less accurate results than DeTREM when used to deconvolute human brain data. CONCLUSION: DeTREM improves the deconvolution accuracy of MuSiC and outperforms other deconvolution methods when applied to snRNA-seq data. DeTREM enables accurate cell-type deconvolution in situations where scRNA-seq data are not available. This modification improves characterization cell-type specific effects in brain tissue and identification of cell-type abundance differences under various conditions.

Long-term spring through fall capture data of Eptesicus fuscus in the eastern USA before and after white-nose syndrome.

Emerging infectious diseases threaten wildlife populations. Without well monitored wildlife systems, it is challenging to determine accurate population and ecosystem losses following disease emergence. North American temperate bats present a unique opportunity for studying the broad impacts of wildlife disease emergence, as their federal monitoring programs were prioritized in the USA throughout the 20th century and they are currently threatened by the invasive fungal pathogen, Pseudogymnoascus destructans (Pd), which causes white-nose syndrome. Here we provide a long-term dataset for capture records of Eptesicus fuscus (big brown bat) across the eastern USA, spanning 16 years before and 14 years after Pd invasion into North America. These data represent 30,496 E. fuscus captures across 3,567 unique sites. We encourage the use of this dataset for quantifying impacts of wildlife disease and other threats to wildlife (e.g., climate change) with the incorporation of other available data. We welcome additional data contributions for E. fuscus captures across North and Central America as well as the inclusion of other variables into the dataset that contribute to the quantification of wildlife health.

Interactive analysis of single-cell data using flexible workflows with SCTK2.

Analysis of single-cell RNA sequencing (scRNA-seq) data can reveal novel insights into the heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analyses. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single-Cell Toolkit 2 (SCTK2), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users.

Integrative genetic and genomic networks identify microRNA associated with COPD and ILD.

Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) are clinically and molecularly heterogeneous diseases. We utilized clustering and integrative network analyses to elucidate roles for microRNAs (miRNAs) and miRNA isoforms (isomiRs) in COPD and ILD pathogenesis. Short RNA sequencing was performed on 351 lung tissue samples of COPD (n = 145), ILD (n = 144) and controls (n = 64). Five distinct subclusters of samples were identified including 1 COPD-predominant cluster and 2 ILD-predominant clusters which associated with different clinical measurements of disease severity. Utilizing 262 samples with gene expression and SNP microarrays, we built disease-specific genetic and expression networks to predict key miRNA regulators of gene expression. Members of miR-449/34 family, known to promote airway differentiation by repressing the Notch pathway, were among the top connected miRNAs in both COPD and ILD networks. Genes associated with miR-449/34 members in the disease networks were enriched among genes that increase in expression with airway differentiation at an air-liquid interface. A highly expressed isomiR containing a novel seed sequence was identified at the miR-34c-5p locus. 47% of the anticorrelated predicted targets for this isomiR were distinct from the canonical seed sequence for miR-34c-5p. Overexpression of the canonical miR-34c-5p and the miR-34c-5p isomiR with an alternative seed sequence down-regulated NOTCH1 and NOTCH4. However, only overexpression of the isomiR down-regulated genes involved in Ras signaling such as CRKL and GRB2. Overall, these findings elucidate molecular heterogeneity inherent across COPD and ILD patients and further suggest roles for miR-34c in regulating disease-associated gene-expression.

Single-Cell Characterization of Pulmonary Nodules Implicates Suppression of Immunosurveillance across Early Stages of Lung Adenocarcinoma.

A greater understanding of molecular, cellular, and immunological changes during the early stages of lung adenocarcinoma development could improve diagnostic and therapeutic approaches in patients with pulmonary nodules at risk for lung cancer. To elucidate the immunopathogenesis of early lung tumorigenesis, we evaluated surgically resected pulmonary nodules representing the spectrum of early lung adenocarcinoma as well as associated normal lung tissues using single-cell RNA sequencing and validated the results by flow cytometry and multiplex immunofluorescence (MIF). Single-cell transcriptomics revealed a significant decrease in gene expression associated with cytolytic activities of tumor-infiltrating natural killer and natural killer T cells. This was accompanied by a reduction in effector T cells and an increase of CD4+ regulatory T cells (Treg) in subsolid nodules. An independent set of resected pulmonary nodules consisting of both adenocarcinomas and associated premalignant lesions corroborated the early increment of Tregs in premalignant lesions compared with the associated normal lung tissues by MIF. Gene expression analysis indicated that cancer-associated alveolar type 2 cells and fibroblasts may contribute to the deregulation of the extracellular matrix, potentially affecting immune infiltration in subsolid nodules through ligand-receptor interactions. These findings suggest that there is a suppression of immune surveillance across the spectrum of early-stage lung adenocarcinoma. SIGNIFICANCE: Analysis of a spectrum of subsolid pulmonary nodules by single-cell RNA sequencing provides insights into the immune regulation and cell-cell interactions in the tumor microenvironment during early lung tumor development.

A contamination focused approach for optimizing the single-cell RNA-seq experiment.

Droplet-based single-cell RNA-seq (scRNA-seq) data are plagued by ambient contaminations caused by nucleic acid material released by dead and dying cells. This material is mixed into the buffer and is co-encapsulated with cells, leading to a lower signal-to-noise ratio. Although there exist computational methods to remove ambient contaminations post-hoc, the reliability of algorithms in generating high-quality data from low-quality sources remains uncertain. Here, we assess data quality before data filtering by a set of quantitative, contamination-based metrics that assess data quality more effectively than standard metrics. Through a series of controlled experiments, we report improvements that can minimize ambient contamination outside of tissue dissociation, via cell fixation, improved cell loading, microfluidic dilution, and nuclei versus cell preparation; many of these parameters are inaccessible on commercial platforms. We provide end-users with insights on factors that can guide their decision-making regarding optimizations that minimize ambient contamination, and metrics to assess data quality.

Revision Total Knee Arthroplasty for Ballistic Component Damage From an Intra-articular Missile.

Gunshot wounds (GSWs) and total knee arthroplasty (TKA) are increasingly common, yet a GSW to a TKA is a rare injury. A 60-year-old man sustained an intra-articular GSW to a prior TKA. The patient was scheduled for irrigation and debridement with polyethylene liner exchange. Intraoperatively, the new polyethylene liner was unable to engage the tibial tray. Damage to the locking mechanism on the tibial tray was suspected so total revision proceeded. Upon inspection of the explanted components, it was noted that a bullet fragment offline from the missile trajectory had blocked the locking of the polyethylene liner in the tibial tray. Expeditious antibiotics should be given and meticulous debridement should be performed to avoid unnecessary total component revision.

Impact of Large Database Studies on Orthopedic Surgery Literature: Are We Advancing the Field?

Background: While database studies have become more prevalent in the literature, there is concern over their value. In addition, the questions they are suitable to answer are limited. Questions/Purposes: We sought to determine the incidence of database studies in the orthopedic literature and in each subspecialty. In addition, we wanted to assess the impact of database studies on the literature by determining whether citations and Altmetric Attention Scores (AAS) varied by study type (studies using internal or external databases and those not using databases). Methods: We searched PubMed for articles published in impactful orthopedic surgery journals in the year 2018. All articles were discoverable on the Altmetric explorer portal database. Impact was determined by journal impact factor. Study design, subspecialty, number of citations, and AAS were obtained. Univariable analyses were conducted between study type, demographic variables, and the outcome of either citation count or AAS. Multivariable analyses were performed to identify independent predictors of the primary outcomes. Subgroup analyses were performed to differentiate the impact of external and internal database studies compared with non-database studies. Results: A total of 2684 total articles were eligible for inclusion. Of these, 366 studies (13.6%) were database studies. Hip and knee articles had the greatest incidence of database studies. Database studies had significantly more citations (5.9 vs 4.0) and significantly higher AAS (12.8 vs 11.3) compared with non-database studies. External database studies had significantly more citations (6.7 vs 4.8) and significantly higher AAS (14.0 vs 10.7) than internal database studies. Internal database studies had higher traditional citation counts but similar AAS to non-database studies. Conclusions: In 2018, database studies in well-reputed orthopedic journals had a greater number of citations but similar AAS compared with non-database studies. Further studies are warranted.

Artificial pollination of kiwifruit (Actinidia chinensis Planch. var. chinensis) (Ericales: Actinidiaceae) results in greater fruit set compared to flowers pollinated by managed bees (Apis mellifera L. (Hymenoptera: Apidae) and Bombus impatiens Cresson (Hymenoptera: Apidae)).

Due to a lack of knowledge on the pollination requirements of kiwifruit cultivars grown within the United States, farmers simultaneously implement multiple pollination methods, like the rental of managed bee species or artificial pollination to achieve high fruit yields. However, implementing multiple pollination methods is costly and possibly an inefficient use of resources. We assessed the contribution of two managed bees (Apis mellifera and Bombus impatiens) to the pollination of kiwifruit by i) determining the relative abundance of kiwifruit pollen collected by foragers of each bee species, and ii) comparing fruit set and fruit quality among insect and artificially pollinated flowers through an insect exclusion experiment. A significant difference was observed between the mean relative abundance of kiwifruit pollen carried in the corbicula of A. mellifera and B. impatiens, with B. impatiens carrying on average 46% more kiwifruit pollen than A. mellifera. Artificially pollinated kiwifruit flowers set significantly greater numbers of fruit per flower at four weeks post-bloom and at harvest compared to insect pollination, wind pollination, and pollen exclusion treatment. Artificial pollination produced fruits of greater weight, size, and seed number compared to insect-pollinated flowers, and few fruits were produced in the pollen exclusion and wind pollination treatments. Kiwifruit producers experiencing similar conditions to ours should focus on artificially pollinating their crops rather than relying on managed or wild insects for kiwifruit pollination. Future research should evaluate other methods of artificial pollination to determine their effectiveness, efficiency, and economics in the pollination of kiwifruit grown within the United States.

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro.

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. Using an exploratory analysis of PBMC datasets, we find that some droplets that were originally called "empty" due to low levels of RNA contained high levels of ADTs and likely corresponded to neutrophils. We identified a novel type of artifact in the empty droplets called a "spongelet" which has medium levels of ADT expression and is distinct from ambient noise. ADT expression levels in the spongelets correlate to ADT expression levels in the background peak of true cells in several datasets suggesting that they can contribute to background noise along with ambient ADTs. We then developed DecontPro, a novel Bayesian hierarchical model that can decontaminate ADT data by estimating and removing contamination from these sources. DecontPro outperforms other decontamination tools in removing aberrantly expressed ADTs while retaining native ADTs and in improving clustering specificity. Overall, these results suggest that identification of empty drops should be performed separately for RNA and ADT data and that DecontPro can be incorporated into CITE-seq workflows to improve the quality of downstream analyses.

Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data.

A large number of genomic and imaging datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While much effort has been devoted to capturing information related to biospecimen information and experimental procedures, the metadata standards that describe data matrices and the analysis workflows that produced them are relatively lacking. Detailed metadata schema related to data analysis are needed to facilitate sharing and interoperability across groups and to promote data provenance for reproducibility. To address this need, we developed the Matrix and Analysis Metadata Standards (MAMS) to serve as a resource for data coordinating centers and tool developers. We first curated several simple and complex "use cases" to characterize the types of feature-observation matrices (FOMs), annotations, and analysis metadata produced in different workflows. Based on these use cases, metadata fields were defined to describe the data contained within each matrix including those related to processing, modality, and subsets. Suggested terms were created for the majority of fields to aid in harmonization of metadata terms across groups. Additional provenance metadata fields were also defined to describe the software and workflows that produced each FOM. Finally, we developed a simple list-like schema that can be used to store MAMS information and implemented in multiple formats. Overall, MAMS can be used as a guide to harmonize analysis-related metadata which will ultimately facilitate integration of datasets across tools and consortia. MAMS specifications, use cases, and examples can be found at https://github.com/single-cell-mams/mams/.