Single-cell transcriptomics reveals stage- and side-specificity of gene modules in colorectal cancer.

BACKGROUND: An understanding of mechanisms underlying colorectal cancer (CRC) development and progression is yet to be fully elucidated. This study aims to employ network theoretic approaches to analyse single cell transcriptomic data from CRC to better characterize its progression and sided-ness. METHODS: We utilized a recently published single-cell RNA sequencing data (GEO-GSE178341) and parsed the cell X gene data by stage and side (right and left colon). Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified gene modules with varying preservation levels (weak or strong) of network topology between early (pT1) and late stages (pT234), and between right and left colons. Spearman's rank correlation (ρ) was used to assess the similarity or dissimilarity in gene connectivity. RESULTS: Equalizing cell counts across different stages, we detected 13 modules for the early stage, two of which were non-preserved in late stages. Both non-preserved modules displayed distinct gene connectivity patterns between the early and late stages, characterized by low ρ values. One module predominately dealt with myeloid cells, with genes mostly enriched for cytokine-cytokine receptor interaction potentiallystimulating myeloid cells to participate in angiogenesis. The second module, representing a subset of epithelial cells, was mainly enriched for carbohydrate digestion and absorption, influencing the gut microenvironment through the breakdown of carbohydrates. In the comparison of left vs. right colons, two of 12 modules identified in the right colon were non-preserved in the left colon. One captured a small fraction of epithelial cells and was enriched for transcriptional misregulation in cancer, potentially impacting communication between epithelial cells and the tumor microenvironment. The other predominantly contained B cells with a crucial role in maintaining human gastrointestinal health and was enriched for B-cell receptor signalling pathway. CONCLUSIONS: We identified modules with topological and functional differences specific to cell types between the early and late stages, and between the right and left colons. This study enhances the understanding of roles played by different cell types at different stages and sides, providing valuable insights for future studies focused on the diagnosis and treatment of CRC.

Molecular Atlas of HER2+ Breast Cancer Cells Treated with Endogenous Ligands: Temporal Insights into Mechanisms of Trastuzumab Resistance.

Trastuzumab therapy in HER2+ breast cancer patients has mixed success owing to acquired resistance to therapy. A detailed understanding of downstream molecular cascades resulting from trastuzumab resistance is yet to emerge. In this study, we investigate the cellular mechanisms underlying acquired resistance using trastuzumab-sensitive and -resistant cancer cells (BT474 and BT474R) treated with endogenous ligands EGF and HRG across time. We probe early receptor organization through microscopy and signaling events through multiomics measurements and assess the bioenergetic state through mitochondrial measurements. Integrative analyses of our measurements reveal significant alterations in EGF-treated BT474 HER2 membrane dynamics and robust downstream activation of PI3K/AKT/mTORC1 signaling. EGF-treated BT474R shows a sustained interferon-independent activation of the IRF1/STAT1 cascade, potentially contributing to trastuzumab resistance. Both cell lines exhibit temporally divergent metabolic demands and HIF1A-mediated stress responses. BT474R demonstrates inherently increased mitochondrial activity. HRG treatment in BT474R leads to a pronounced reduction in AR expression, affecting downstream lipid metabolism with implications for treatment response. Our results provide novel insights into mechanistic changes underlying ligand treatment in BT474 and BT474R and emphasize the pivotal role of endogenous ligands. These results can serve as a framework for furthering the understanding of trastuzumab resistance, with therapeutic implications for women with acquired resistance.

The Janus face of proliferating plasmablasts in dengue and COVID-19 infections.

Introduction: B cells play an integral role in the immune response to both dengue fever and COVID-19. Prior scRNAseq analyses of peripheral plasmablasts in COVID-19 have revealed a heterogeneous population with distinct cell subsets associated with proliferation; prior studies in patients with dengue fever have likewise shown the presence of proliferative pre-plasmablasts in the circulation. These findings may have implications for disease severity. In this study, we sought to gain a mechanistic understanding of the intracellular processes in naive and memory B cells that are associated with and may lead to an expanded proliferative plasmablast population in the circulation. Methods: We analyzed age-controlled (pediatric and adult), peripheral blood mononuclear cell scRNAseq datasets from patients infected with either dengue (primary or secondary) or COVID-19 (non-severe or severe) from previously published studies. Our preliminary analysis showed that pediatric patients with dengue and adults with COVID-19 had an expanded proliferative plasmablast (p-PB) population. By contrast, neither the adults with dengue nor the children with COVID-19 in our dataset had p-PBs. We used this distinctive preliminary signature to guide our analyses design and expanded our analyses to naive and memory B cells. Results: In age/disease conditions with and without p-PBs, we found differences in cell sensing and activation, including via the B cell receptor and downstream signal transduction. Likewise, inflammation was mediated differently: relative to groups without p-PBs, those with p-PBs had increased expression of interferon response and S100 genes (particularly severe COVID-19). Furthermore, several transcription factors at the nexus of activation, inflammation, and cell fate decisions were expressed differently in groups with and without p-PBs. Discussion: We used dengue and COVID-19 infections in adult and pediatric patients (focusing on naive B, memory B, and plasmablast cells) as a model to better understand the mechanisms that may give rise to p-PB populations in the circulation. Our results indicate that a more pro-inflammatory state in naive and memory B cells correlated with - and could influence the generation of- proliferating plasmablasts. Further exploration of these mechanisms will have implications for immune memory, vaccine development, and post-viral autoimmune syndromes.

Impaired Cellular and Antibody immunity after COVID-19 in Chronically Immunosuppressed Transplant Recipients.

Assessment of cellular immunity to the SARS-CoV-2 coronavirus is of great interest in chronically immunosuppressed transplant recipients (Tr), who are predisposed to infections and vaccination failures. We evaluated CD154-expressing T-cells induced by spike (S) antigenic peptides in 204 subjects-103 COVID-19 patients and 101 healthy unexposed subjects. S-reactive CD154+T-cell frequencies were a) higher in 42 healthy unexposed Tr who were sampled pre-pandemic, compared with healthy NT (p=0.02), b) lower in Tr COVID-19 patients compared with healthy Tr (p<0.0001) and were accompanied by lower S-reactive B-cell frequencies (p<0.05), c) lower in Tr with severe COVID-19 (p<0.0001), or COVID-19 requiring hospitalization (p<0.05), compared with healthy Tr. Among Tr with COVID-19, cytomegalovirus co-infection occurred in 34%; further, incidence of anti-receptor-binding-domain IgG (p=0.011) was lower compared with NT COVID-19 patients. Healthy unexposed Tr exhibit pre-existing T-cell immunity to SARS-CoV-2. COVID-19 impairs anti-S T-cell and antibody and predisposes to CMV co-infection in transplant recipients.

Modular and mechanistic changes across stages of colorectal cancer.

BACKGROUND: While mechanisms contributing to the progression and metastasis of colorectal cancer (CRC) are well studied, cancer stage-specific mechanisms have been less comprehensively explored. This is the focus of this manuscript. METHODS: Using previously published data for CRC (Gene Expression Omnibus ID GSE21510), we identified differentially expressed genes (DEGs) across four stages of the disease. We then generated unweighted and weighted correlation networks for each of the stages. Communities within these networks were detected using the Louvain algorithm and topologically and functionally compared across stages using the normalized mutual information (NMI) metric and pathway enrichment analysis, respectively. We also used Short Time-series Expression Miner (STEM) algorithm to detect potential biomarkers having a role in CRC. RESULTS: Sixteen Thousand Sixty Two DEGs were identified between various stages (p-value ≤ 0.05). Comparing communities of different stages revealed that neighboring stages were more similar to each other than non-neighboring stages, at both topological and functional levels. A functional analysis of 24 cancer-related pathways indicated that several signaling pathways were enriched across all stages. However, the stage-unique networks were distinctly enriched only for a subset of these 24 pathways (e.g., MAPK signaling pathway in stages I-III and Notch signaling pathway in stages III and IV). We identified potential biomarkers, including HOXB8 and WNT2 with increasing, and MTUS1 and SFRP2 with decreasing trends from stages I to IV. Extracting subnetworks of 10 cancer-relevant genes and their interacting first neighbors (162 genes in total) revealed that the connectivity patterns for these genes were different across stages. For example, BRAF and CDK4, members of the Ser/Thr kinase, up-regulated in cancer, displayed changing connectivity patterns from stages I to IV. CONCLUSIONS: Here, we report molecular and modular networks for various stages of CRC, providing a pseudo-temporal view of the mechanistic changes associated with the disease. Our analysis highlighted similarities at both functional and topological levels, across stages. We further identified stage-specific mechanisms and biomarkers potentially contributing to the progression of CRC.

Immune Response in Severe and Non-Severe Coronavirus Disease 2019 (COVID-19) Infection: A Mechanistic Landscape.

The mechanisms underlying the immune remodeling and severity response in coronavirus disease 2019 (COVID-19) are yet to be fully elucidated. Our comprehensive integrative analyses of single-cell RNA sequencing (scRNAseq) data from four published studies, in patients with mild/moderate and severe infections, indicate a robust expansion and mobilization of the innate immune response and highlight mechanisms by which low-density neutrophils and megakaryocytes play a crucial role in the cross talk between lymphoid and myeloid lineages. We also document a marked reduction of several lymphoid cell types, particularly natural killer cells, mucosal-associated invariant T (MAIT) cells, and gamma-delta T (γδT) cells, and a robust expansion and extensive heterogeneity within plasmablasts, especially in severe COVID-19 patients. We confirm the changes in cellular abundances for certain immune cell types within a new patient cohort. While the cellular heterogeneity in COVID-19 extends across cells in both lineages, we consistently observe certain subsets respond more potently to interferon type I (IFN-I) and display increased cellular abundances across the spectrum of severity, as compared with healthy subjects. However, we identify these expanded subsets to have a more muted response to IFN-I within severe disease compared to non-severe disease. Our analyses further highlight an increased aggregation potential of the myeloid subsets, particularly monocytes, in COVID-19. Finally, we provide detailed mechanistic insights into the interaction between lymphoid and myeloid lineages, which contributes to the multisystemic phenotype of COVID-19, distinguishing severe from non-severe responses.

Impaired T-cell and antibody immunity after COVID-19 infection in chronically immunosuppressed transplant recipients.

Assessment of T-cell immunity to the COVID-19 coronavirus requires reliable assays and is of great interest, given the uncertain longevity of the antibody response. Some recent reports have used immunodominant spike (S) antigenic peptides and anti-CD28 co-stimulation in varying combinations to assess T-cell immunity to SARS-CoV-2. These assays may cause T-cell hyperstimulation and could overestimate antiviral immunity in chronically immunosuppressed transplant recipients, who are predisposed to infections and vaccination failures. Here, we evaluate CD154-expressing T-cells induced by unselected S antigenic peptides in 204 subjects-103 COVID-19 patients and 101 healthy unexposed subjects. Subjects included 72 transplanted and 130 non-transplanted subjects. S-reactive CD154+T-cells co-express and can thus substitute for IFNγ (n=3). Assay reproducibility in a variety of conditions was acceptable with coefficient of variation of 2-10.6%. S-reactive CD154+T-cell frequencies were a) higher in 42 healthy unexposed transplant recipients who were sampled pre-pandemic, compared with 59 healthy non-transplanted subjects (p=0.02), b) lower in Tr COVID-19 patients compared with healthy transplant patients (p<0.0001), c) lower in Tr patients with severe COVID-19 (p<0.0001), or COVID-19 requiring hospitalization (p<0.05), compared with healthy Tr recipients. S-reactive T-cells were not significantly different between the various COVID-19 disease categories in NT recipients. Among transplant recipients with COVID-19, cytomegalovirus co-infection occurred in 34%; further, CMV-specific T-cells (p<0.001) and incidence of anti-receptor-binding-domain IgG (p=0.011) were lower compared with non-transplanted COVID-19 patients. Healthy unexposed transplant recipients exhibit pre-existing T-cell immunity to SARS-CoV-2. COVID-19 infection leads to impaired T-cell and antibody responses to SARS-CoV-2 and increased risk of CMV co-infection in transplant recipients.

Right and left-sided colon cancers - specificity of molecular mechanisms in tumorigenesis and progression.

BACKGROUND: Given the differences in embryonic origin, vascular and nervous supplies, microbiotic burden, and main physiological functions of left and right colons, tumor location is increasingly suggested to dictate tumor behavior affecting pathology, progression and prognosis. Right-sided colon cancers arise in the cecum, ascending colon, hepatic flexure and/or transverse colon, while left-sided colon cancers arise in the splenic flexure, descending, and/or sigmoid colon. In contrast to prior reports, we attempt to delineate programs of tumorigenesis independently for each side. METHODS: Four hundred and eleven samples were extracted from The Cancer Genome Atlas-COAD cohort, based on a conservative sample inclusion criterion. Each side was independently analyzed with respect to their respective normal tissue, at the level of transcription, post-transcription, miRNA control and methylation in both a stage specific and stage-agnostic manner. RESULTS: Our results indicate a suppression of enzymes involved in various stages of carcinogen breakdown including CYP2C8, CYP4F12, GSTA1, and UGT1A within right colon tumors. This implies its reduced capacity to detoxify carcinogens, contributing to a genotoxic tumor environment, and subsequently a more aggressive phenotype. Additionally, we highlight a crucial nexus between calcium homeostasis (sensing, mobilization and absorption) and immune/GPCR signaling within left-sided tumors, possibly contributing to its reduced proliferative and metastatic potential. Interestingly, two genes SLC6A4 and HOXB13 show opposing regulatory trends within right and left tumors. Post-transcriptional regulation mediated by both RNA-binding proteins (e.g. NKRF (in left) and MSI2 (in right)) and miRNAs (e.g. miR-29a (in left); miR-155, miR181-d, miR-576 and miR23a (in right)) appear to exhibit side-specificity in control of their target transcripts and is pronounced in right colon tumors. Additionally, methylation results depict location-specific differences, with increased hypomethylation in open seas within left tumors, and increased hypermethylation of CpG islands within right tumors. CONCLUSIONS: Differences in molecular mechanisms captured here highlight distinctions in tumorigenesis and progression between left and right colon tumors, which will serve as the basis for future studies, influencing the efficacies of existing and future diagnostic, prognostic and therapeutic interventions.

Plasmin Cascade Mediates Thrombotic Events in SARS-CoV-2 Infection via Complement and Platelet-Activating Systems.

Objective: Recently emerged beta-coronavirus SARS-CoV-2, has resulted in the current pandemic designated COVID-19. COVID-19 manifests as severe illness exhibiting systemic inflammatory response syndrome, acute respiratory distress syndrome (ARDS), thrombotic events, and shock, exacerbated further by co-morbidities and age. Recent clinical evidence suggests that the development of ARDS and subsequent pulmonary failure result from a complex interplay between cell types (endothelial, epithelial and immune) within the lung promoting inflammatory infiltration and a pro-coagulative state. How the complex molecular events mediated by SARS-CoV-2 in infected lung epithelial cells lead to thrombosis and pulmonary failure, is yet to be fully understood. Methods: We address these questions here, using publicly available transcriptomic data in the context of lung epithelia affected by SARS-CoV-2 and other respiratory infections, in vitro. We then extend our results to the understanding of in vivo lung, using a publicly available COVID-19 lung transcriptomic study. Results and Conclusions: Our analysis indicates that there exists a complex interplay between the fibrinolytic system particularly plasmin, and the complement and platelet-activating systems upon SARS-CoV-2 infection, with a potential for therapeutic intervention.

Skeletal muscle: A review of molecular structure and function, in health and disease.

Decades of research in skeletal muscle physiology have provided multiscale insights into the structural and functional complexity of this important anatomical tissue, designed to accomplish the task of generating contraction, force and movement. Skeletal muscle can be viewed as a biomechanical device with various interacting components including the autonomic nerves for impulse transmission, vasculature for efficient oxygenation, and embedded regulatory and metabolic machinery for maintaining cellular homeostasis. The "omics" revolution has propelled a new era in muscle research, allowing us to discern minute details of molecular cross-talk required for effective coordination between the myriad interacting components for efficient muscle function. The objective of this review is to provide a systems-level, comprehensive mapping the molecular mechanisms underlying skeletal muscle structure and function, in health and disease. We begin this review with a focus on molecular mechanisms underlying muscle tissue development (myogenesis), with an emphasis on satellite cells and muscle regeneration. We next review the molecular structure and mechanisms underlying the many structural components of the muscle: neuromuscular junction, sarcomere, cytoskeleton, extracellular matrix, and vasculature surrounding muscle. We highlight aberrant molecular mechanisms and their possible clinical or pathophysiological relevance. We particularly emphasize the impact of environmental stressors (inflammation and oxidative stress) in contributing to muscle pathophysiology including atrophy, hypertrophy, and fibrosis. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Developmental Biology > Developmental Processes in Health and Disease Models of Systems Properties and Processes > Cellular Models.

Co-Expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A.

Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications. The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into five groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes-Dclk1 and Ostalpha-within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work.

Co-expression Network Approach Reveals Functional Similarities among Diseases Affecting Human Skeletal Muscle.

Diseases affecting skeletal muscle exhibit considerable heterogeneity in intensity, etiology, phenotypic manifestation and gene expression. Systems biology approaches using network theory, allows for a holistic understanding of functional similarities amongst diseases. Here we propose a co-expression based, network theoretic approach to extract functional similarities from 20 heterogeneous diseases comprising of dystrophinopathies, inflammatory myopathies, neuromuscular, and muscle metabolic diseases. Utilizing this framework we identified seven closely associated disease clusters with 20 disease pairs exhibiting significant correlation (p < 0.05). Mapping the diseases onto a human protein-protein interaction network enabled the inference of a common program of regulation underlying more than half the muscle diseases considered here and referred to as the "protein signature." Enrichment analysis of 17 protein modules identified as part of this signature revealed a statistically non-random dysregulation of muscle bioenergetic pathways and calcium homeostasis. Further, analysis of mechanistic similarities of less explored significant disease associations [such as between amyotrophic lateral sclerosis (ALS) and cerebral palsy (CP)] using a proposed "functional module" framework revealed adaptation of the calcium signaling machinery. Integrating drug-gene information into the quantitative framework highlighted the presence of therapeutic opportunities through drug repurposing for diseases affecting the skeletal muscle.

Three distinct cell populations express extracellular matrix proteins and increase in number during skeletal muscle fibrosis.

Tissue extracellular matrix (ECM) provides structural support and creates unique environments for resident cells (Bateman JF, Boot-Handford RP, Lamandé SR. Nat Rev Genet 10: 173-183, 2009; Kjaer M. Physiol Rev 84: 649-98, 2004). However, the identities of cells responsible for creating specific ECM components have not been determined. In striated muscle, the identity of these cells becomes important in disease when ECM changes result in fibrosis and subsequent increased tissue stiffness and dysfunction. Here we describe a novel approach to isolate and identify cells that maintain the ECM in both healthy and fibrotic muscle. Using a collagen I reporter mouse, we show that there are three distinct cell populations that express collagen I in both healthy and fibrotic skeletal muscle. Interestingly, the number of collagen I-expressing cells in all three cell populations increases proportionally in fibrotic muscle, indicating that all cell types participate in the fibrosis process. Furthermore, while some profibrotic ECM and ECM-associated genes are significantly upregulated in fibrotic muscle, the fibrillar collagen gene expression profile is not qualitatively altered. This suggests that muscle fibrosis in this model results from an increased number of collagen I-expressing cells and not the initiation of a specific fibrotic collagen gene expression program. Finally, in fibrotic muscle, we show that these collagen I-expressing cell populations differentially express distinct ECM proteins-fibroblasts express the fibrillar components of ECM, fibro/adipogenic progenitors cells differentially express basal laminar proteins, and skeletal muscle progenitor cells differentially express genes important for the satellite cell.

Dysregulated mechanisms underlying Duchenne muscular dystrophy from co-expression network preservation analysis.

BACKGROUND: Duchenne Muscular Dystrophy (DMD) is an X-linked recessive disorder with its primary insult on the skeletal muscle. Severe muscle wasting, chronic inflammation and fibrosis characterize dystrophic muscle. Here we identify dysregulated pathways in DMD utilizing a co-expression network approach as described in Weighted Gene Co-expression Network Analysis (WGCNA). Specifically, we utilize WGCNA's "preservation" statistics to identify gene modules that exhibit a weak conservation of network topology within healthy and dystrophic networks. Preservation statistics rank modules based on their topological metrics such as node density, connectivity and separability between networks. METHODS: Raw data for DMD was downloaded from Gene Expression Omnibus (GSE6011) and suitably preprocessed. Co-expression networks for each condition (healthy and dystrophic) were generated using the WGCNA library in R. Preservation of healthy network edges was evaluated with respect to dystrophic muscle and vice versa using WGCNA. Highly exclusive gene pairs for each of the low preserved modules within both networks were also determined using a specificity measure. RESULTS: A total of 11 and 10 co-expressed modules were identified in the networks generated from 13 healthy and 23 dystrophic samples respectively. 5 out of the 11, and 4 out of the 10 modules were identified as exhibiting none-to-weak preservation. Functional enrichment analysis identified that these weakly preserved modules were highly relevant to the condition under study. For instance, weakly preserved dystrophic module D2 exhibited the highest fraction of genes exclusive to DMD. The highly specific gene pairs identified within these modules were enriched for genes activated in response to wounding and affect the extracellular matrix including several markers such as SPP1, MMP9 and ITGB2. CONCLUSION: The proposed approach allowed us to identify clusters of genes that are non-randomly associated with the disease. Furthermore, highly specific gene pairs pointed to interactions between known markers of disease and identification of putative markers likely associated with disease. The analysis also helped identify putative novel interactions associated with the progression of DMD.

Systems analysis of transcriptional data provides insights into muscle's biological response to botulinum toxin.

INTRODUCTION: This study provides global transcriptomic profiling and analysis of botulinum toxin A (BoNT-A)-treated muscle over a 1-year period. METHODS: Microarray analysis was performed on rat tibialis anterior muscles from 4 groups (n = 4/group) at 1, 4, 12, and 52 weeks after BoNT-A injection compared with saline-injected rats at 12 weeks. RESULTS: Dramatic transcriptional adaptation occurred at 1 week with a paradoxical increase in expression of slow and immature isoforms, activation of genes in competing pathways of repair and atrophy, impaired mitochondrial biogenesis, and increased metal ion imbalance. Adaptations of the basal lamina and fibrillar extracellular matrix (ECM) occurred by 4 weeks. The muscle transcriptome returned to its unperturbed state 12 weeks after injection. CONCLUSIONS: Acute transcriptional adaptations resemble denervated muscle with some subtle differences, but resolved more quickly compared with denervation. Overall, gene expression across time correlates with the generally accepted BoNT-A time course and suggests that the direct action of BoNT-A in skeletal muscle is relatively rapid.

EpiphaNet: An Interactive Tool to Support Biomedical Discoveries.

UNLABELLED: Background. EpiphaNet is an interactive knowledge discovery system which enables researchers to explore visually sets of relations extracted from MEDLINE using a combination of language processing techniques. In this paper, we discuss the theoretical and methodological foundations of the system, and evaluate the utility of the models that underlie it for literature-based discovery. In addition, we present a summary of results drawn from a qualitative analysis of over six hours of interaction with the system by basic medical scientists. RESULTS: The system is able to simulate open and closed discovery, and is shown to generate associations that are both surprising and interesting within the area of expertise of the researchers concerned. CONCLUSIONS: EpiphaNet provides an interactive visual representation of associations between concepts, which is derived from distributional statistics drawn from across the spectrum of biomedical citations in MEDLINE. This tool is available online, providing biomedical scientists with the opportunity to identify and explore associations of interest to them.