Lupus autoantibodies interact directly with distinct glomerular and vascular cell surface antigens

Lupus autoantibodies interact directly with distinct glomerular and vascular cell surface antigens. We have identified monoclonal anti-DNA antibodies derived from lupus prone MRL-lpr/lpr mice that produce glomerular immune deposits and nephritis after passive transfer to normal mice. Particularly noteworthy is that the location of immune deposition varied among nephritogenic Ig, and this was associated with distinctive histologies and clinical disease profiles. Although their autoantigen binding properties differed, they were highly cross-reactive, in a manner similar to Ig deposited in glomeruli of lupus mice. This antigen binding profile was also typical of other previously described nephritogenic autoantibodies that bound directly to glomerular antigens to initiate immune deposit formation. In this study, we questioned whether ligation of different glomerular antigens by individual autoantibodies could contribute to the observed differences in the location of immune deposits. To examine this possibility, monoclonal anti-DNA antibodies (IgG2a) that produced glomerular immune deposits in different locations were evaluated. H221 produced mesangial, intracapillary (that is, intraluminal or within the capillary lumen) and subendothelial deposits associated with heavy proteinuria, whereas H147 produced mesangial, subendothelial and linear basement membrane deposits associated with proliferative glomerulonephritis. Initially, the capacity of H221 and H147 to bind directly to glomerular and vascular cell surfaces was evaluated. As demonstrated by FACS, H221 bound preferentially to mesangial cells whereas H147 bound preferentially to endothelial cells. To identify possible target cell surface antigens, Western blots, immunoprecipitation of surface labeled cells, and 2D gel electrophoresis were employed. H221 reacted with a 108kDa protein on mesangial cells not identified by H147, whereas H147 reacted with a 45kDa protein on endothelial cells not identified by H221. These results support the hypothesis that some nephritogenic lupus autoantibodies initiate immune deposit formation through direct interaction with glomerular antigens. Furthermore, they suggest that the site of immune deposition is determined by both antigen binding properties of the relevant antibody and the location of its target ligand within the glomerulus. In a given individual, therefore, the predominant autoantibody-glomerular antigen interaction may influence the morphologic and clinical phenotype expressed. Variation in the predominant interaction may also contribute to variations in disease expression among individuals with lupus nephritis

Using the relationship between brain tissue regional saturation of oxygen and mean arterial pressure to determine the optimal mean arterial pressure in patients following cardiac arrest: A pilot proof-of-concept study.

INTRODUCTION: Prospectively assess cerebral autoregulation and optimal mean arterial pressure (MAPOPT) using the dynamic relationship between MAP and regional saturation of oxygen (rSO2) using near-infrared spectroscopy. METHODS: Feasibility study of twenty patients admitted to the intensive care unit following a cardiac arrest. All patients underwent continuous rSO2 monitoring using the INVOS(®) cerebral oximeter. ICM+(®) brain monitoring software calculates the cerebral oximetry index (COx) in real-time which is a moving Pearson correlation coefficient between 30 consecutive, 10-s averaged values of MAP and correspond rSO2 signals. When rSO2 increases with increasing MAP (COx ≥0.3), cerebral autoregulation is dysfunctional. Conversely, when rSO2 remains constant or decreases with increasing MAP (COx <0.3), autoregulation is preserved. ICM+(®) fits a U-shaped curve through the COx values plotted vs. MAP. The MAPOPT is nadir of this curve. RESULTS: The median age was 59 years (IQR 54-67) and 7 of 20 were female. The cardiac arrest was caused by myocardial infarction in 12 (60%) patients. Nineteen arrests were witnessed and return of spontaneous circulation occurred in a median of 15.5min (IQR 8-33). Patients underwent a median of 30h (IQR 23-46) of monitoring. COx curves and MAPOPT were generated in all patients. The mean overall MAP and MAPOPT were 76mmHg (SD 10) and 76mmHg (SD 7), respectively. MAP was outside of 5mmHg from MAPOPT in 50% (SD 15) of the time. Out of the 7672 5-min averaged COx measurements, 1182 (15%) were at 0.3 or above, indicating absence of autoregulation. Multivariable polynomial fractional regression demonstrated an increase in COx with increasing temperature (P=0.008). CONCLUSIONS: We demonstrated the feasibility to determine a MAPOPT using cerebral oximetry in patients after cardiac arrest

WorldFAIR (D10.3) Agricultural biodiversity FAIR data assessment rubrics

The WorldFAIR Case Study on Agricultural Biodiversity (WP10) addresses the challenges of advancing interoperability and mobilising plant-pollinator interactions data for reuse. Previous efforts, reported in WorldFAIR Deliverable 10.1, ‘Agriculture-related pollinator data standards use cases report’ (Trekels et al., 2023), provided an overview of projects, good practices, tools, and examples for creating, managing and sharing data related to plant-pollinator interactions. It also outlined a work plan for conducting pilot studies. Deliverable 10.2 (Drucker et al., 2024) presented Agricultural Biodiversity Standards, Best Practices and Guidelines Recommendations. This deliverable presented results from six pilot studies that adopted standards and recommendations from the earlier report. The current report complements the efforts with Agricultural Biodiversity FAIR data assessment rubrics.We introduce a set of FAIR assessment tools tailored to the plant-pollinator interactions domain. These tools are designed to help researchers and institutions evaluate adherence to the FAIR principles. In the discovery phase, we found that a significant amount of data on plant-pollinator interactions is available as supplementary files of research articles, in a diversity of formats such as PDFs, Excel spreadsheets, and text files. The diversity of approaches and the lack of appropriate data vocabularies lead to confusion, information loss, and the need for complex data interpretation and transformation. Our proposed framework primarily targets researchers in this domain who wish to assess the FAIRness of the data they produce and take action to improve it. However, we believe it can also benefit data reviewers, data stewards, data repository managers and librarians dealing with plant-pollinator data. Our approach focuses on being as familiar as possible with the researcher's practices, language, and jargon. Ultimately, we aim to promote data publishing and reuse in the plant-pollinator interactions domain.We present a ‘Rubric for the assessment of Plant-Pollinator Interactions Data’ with examples from the data from the pilots developed in Deliverable 10.2 and in relation to the FAIR Implementation Profile (FIP) created by Work Package 10. We conduct ‘dataset assessments’ of available data from research projects surveyed in the discovery phase. Additionally, we describe in detail the ‘Automated FAIR-enabled Data Reviews’ generated by the Global Biotic Interactions (GLoBI) infrastructure, with examples from the pilots. We believe the tools described in this report will encourage data publishing and reuse in the plant-pollinator interactions domain. Moving from diverse approaches and siloed initiatives to widely available FAIR plant-pollination interactions data for scientists and decision-makers will enable the development of integrative studies that enhance our understanding of species biology, behaviour, ecology, phenology, and evolution

Coexpression of Nuclear Receptors and Histone Methylation Modifying Genes in the Testis: Implications for Endocrine Disruptor Modes of Action

BACKGROUND: Endocrine disruptor chemicals elicit adverse health effects by perturbing nuclear receptor signalling systems. It has been speculated that these compounds may also perturb epigenetic mechanisms and thus contribute to the early origin of adult onset disease. We hypothesised that histone methylation may be a component of the epigenome that is susceptible to perturbation. We used coexpression analysis of publicly available data to investigate the combinatorial actions of nuclear receptors and genes involved in histone methylation in normal testis and when faced with endocrine disruptor compounds. METHODOLOGY/PRINCIPAL FINDINGS: The expression patterns of a set of genes were profiled across testis tissue in human, rat and mouse, plus control and exposed samples from four toxicity experiments in the rat. Our results indicate that histone methylation events are a more general component of nuclear receptor mediated transcriptional regulation in the testis than previously appreciated. Coexpression patterns support the role of a gatekeeper mechanism involving the histone methylation modifiers Kdm1, Prdm2, and Ehmt1 and indicate that this mechanism is a common determinant of transcriptional integrity for genes critical to diverse physiological endpoints relevant to endocrine disruption. Coexpression patterns following exposure to vinclozolin and dibutyl phthalate suggest that coactivity of the demethylase Kdm1 in particular warrants further investigation in relation to endocrine disruptor mode of action. CONCLUSIONS/SIGNIFICANCE: This study provides proof of concept that a bioinformatics approach that profiles genes related to a specific hypothesis across multiple biological settings can provide powerful insight into coregulatory activity that would be difficult to discern at an individual experiment level or by traditional differential expression analysis methods

WorldFAIR (D10.2) Agricultural Biodiversity Standards, Best Practices and Guidelines Recommendations

The WorldFAIR Case Study on Agricultural Biodiversity (WP10) addresses the challenges of advancing interoperability and mobilising plant-pollinator interactions data for reuse. Previous efforts, reported in Deliverable 10.1 - from our discovery phase - provided an overview of projects, best practices, tools, and examples for creating, managing and sharing data related to plant-pollinator interactions, along with a work plan for conducting pilot studies. The current report presents the results from the pilot phase of the Case Study, which involved six pilot studies adopting standards and recommendations from the discovery phase. The pilots enabled the handling  of concrete examples and the generation of reusable materials tailored to this domain, as well as providing better estimates for the overall costs of adoption for future projects. Our approach for plant-pollinator data standardisation is based on the widely-used standard for representing biodiversity data, Darwin Core, developed and maintained by the Biodiversity Information Standards (TDWG), in conjunction with a data model and vocabulary proposed by the Brazilian Network of Plant-Pollinator Interactions (REBIPP). The pilot studies also underwent a process of “FAIRification” (i.e., transforming data into a format that adheres to the FAIR data principles) using the Global Biotic Interactions (GloBI, Poelen et al. 2014) platform. Additionally, we present the publishing model for Biotic Interactions developed in collaboration with the Global Biodiversity Information Facility (GBIF), which leads the WorldFAIR Case Study on Biodiversity, as part of the proposed GBIF New Data Model, along with a concrete example of its use by one of the pilots. This effort led to the development of ‘FAIR best practices’ guidelines for sharing plant-pollinator interaction data. The primary focus of this work is to enhance the interoperability of data on plant-pollinator interactions, aligning with WorldFAIR efforts  to develop a Cross-Domain Interoperability Framework. We have successfully promoted the adoption of standards and increased the interoperability of plant-pollinator interactions data, resulting in a process that allows for tracing the provenance of the data, as well as facilitating the reuse of datasets crucial for understanding this essential ecosystem service and its changes due to human impact. Our effort demonstrates there are several possible paths for FAIRification, tailored to institutional needs, and we have shown that different approaches can contribute to promoting data interoperability and data availability for reuse, which is the ultimate goal of this initiative. Consequently, we have successfully ensured FAIR data for understanding plant-pollinator interactions at biologically-relevant scales for crops, with broad participation from initiatives in Europe, South America, Africa, North America, and elsewhere. We have also established concrete guidelines on FAIR data best practices customised for pollination data, metadata, and other digital objects, promoting the scalable adoption of these standards and FAIR data best practices by multiple initiatives. We believe this effort can assist similar initiatives in adopting interoperability standards for this domain and contribute to our understanding of how plant-pollinator interactions contribute to sustain life on Earth. Visit WorldFAIR online at http://worldfair-project.eu. WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393. 

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment