Interrogation Of Data Research Articles

Utilizing imaging mass spectrometry to analyze microbial biofilm chemical responses to exogenous compounds.

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) is an appealing label-free method for imaging biological samples which focuses on the spatial distribution of chemical signals. This approach has been used to study the chemical ecology of microbes and can be applied to study the chemical responses of microbes to treatment with exogenous compounds. Specific conjugated cholic acids such as taurocholic acid (TCA), have been shown to inhibit biofilm formation in the enteric pathogen Vibrio cholerae and MALDI-IMS can be used to directly observe the chemical responses of V. cholerae biofilm colonies to treatment with TCA. A major challenge of MALDI-IMS is optimizing the sample preparation and drying for a particular growth condition and microbial strain. Here we demonstrate how V. cholerae is cultured and prepared for MALDI-IMS analysis and highlight critical steps to ensure proper sample adherence to a MALDI target plate and maintain spatial distributions when applying this technique to any microbial strain. We additionally show how to use both manual interrogation and statistical analyses of MALDI-IMS data to establish the adequacy of the sample preparation protocol. This protocol can serve as a guideline for the development of sample preparation techniques and the acquisition of high quality MALDI-IMS data.

Building a Foundation for Precision Onco-Nutrition: Docosahexaenoic Acid and Breast Cancer.

Simple SummaryPrecision onco-nutrition (PON) is the use of specific nutrients and dietary factors to enhance cancer treatment efficacy and to improve the prognosis for long-term survival. PON requires integration of an understanding of nutrient metabolism with knowledge of the signaling pathways characteristic of each molecular subtype of cancer which can be targeted to improve treatment and control efficacies. Herein we report differences among n-3 fatty acids on the growth and survival of established breast cancer cell lines. Docosahexaenoic acid (DHA) is shown to have greater anticancer activity than eicosapentaenoic acid (EPA). Moreover, we show that a penultimate metabolite of one pathway by which DHA is metabolized inhibited the growth of common molecular subtypes of breast cancer via differential effects on identified canonical signaling pathways and the functions within the cell that they regulate. These findings provide a knowledge base for juxtaposing molecular subtype targeted treatment strategies with the adjuvant use of specific n-3 fatty acid metabolites as an example of precision onco-nutrition for the management and control of breast cancer.In vivo evidence of heterogeneous effects of n-3 fatty acids (N3FA) on cell signaling pathways associated with the reduced growth of breast cancer has been reported and is consistent with the expectation that N3FA will not exert uniform effects on all molecular subtypes of the disease. Similarly, available evidence indicates that many metabolites of N3FA are synthesized by mammalian cells and that they exert metabolite-specific biological activities. To begin to unravel the complex relationships among molecular subtypes and effects exerted by specific N3FA metabolites on those pathways, proof-of-concept experiments were conducted using cell lines representative of common molecular subtypes of human breast cancer. N3FA differed in anticancer activity with docosahexaenoic acid (DHA) having greater anticancer activity than eicosapentaenoic acid. 4-oxo-docosahexaenoic (4-oxo-DHA), a penultimate metabolite of 5-lipoxygenase mediated DHA metabolism, induced dose-dependent inhibition of cell number accumulation with apoptosis as a primary effector mechanism. Interrogation of protein expression data using the Ingenuity Pathway Analysis (IPA) bioinformatics platform indicated that 4-oxo-DHA differentially impacted six canonical pathways and the cellular functions they regulate across common molecular subtypes of breast cancer. This included the endocannabinoid pathway for cancer inhibition that has not been previously reported. These findings provide a rationale for juxtaposing molecular subtype targeted treatment strategies with the adjuvant use of specific N3FA metabolites as an example of precision onco-nutrition (PON) for the management and control of breast cancer.

Type 2 diabetes self-management: spirituality, coping and responsibility

BackgroundIn England, although The National Institute of Health and Care Excellence recommends that patients’ religious beliefs should be incorporated into individual healthcare plans, these components are often neglected in diabetes management care plans. A literature review identified a paucity of research regarding how the spirituality of British people may influence their approach to their self-management of type 2 diabetes (T2D).AimsTo explore how the spirituality of a small group of adults with T2D, living in England, influenced their coping strategies and self-management of diet and exercise.MethodsBiographic Narrative Interpretive Method of two interviews per participant and thematic analysis for data interrogation (n = 8). Data as glycated haemoglobin, living situation, age, length of time since T2D diagnosis, body mass index and diabetic medicines contextualised the interview data.ResultsParticipants’ spirituality, health beliefs, coping and sense of responsibility for T2D self-management overlapped in complex layers. Three themes were generated: (a) spirituality influences expectations in life; (b) beliefs influence coping styles of diabetes self-management; and (c) responsibility influences diabetes self-management. A model was created to assist nurses in addressing these components.ConclusionNurses should consider how patients’ self-management of T2D may be influenced by their spirituality, health beliefs, coping and sense of responsibility.

Technology Focus: Hydraulic Fracturing Modeling (November 2021)

In the past decades, the success of unconventional hydrocarbon resource development can be attributed primarily to the improved understanding of fracture systems, including both hydraulically induced fractures and natural fracture networks. To tackle the fracture characterization problem, several recent papers have provided novel insights into fracture modeling technique. Because of the complex nature and heterogeneity of rock discontinuity, fabric, and texture, the fracture-modeling process typically suffers from limited data availability. Research shows that modeling results reached without interrogation of high-resolution petrophysical and geomechanical data can mislead because the fluid flow is actually controlled by fine-scale rock properties. A more-reliable fracture geometry can be obtained from an enhanced modeling process that preserves the signature from high-frequency data. Advanced techniques to model fracturing processes with proppant transportation and thermodynamics require even more-sophisticated simulation and computation power. When the subsurface is too puzzling to be described by a physical model and existing data, machine learning and artificial intelligence can be adapted as a practical alternative to interpret complex fracture systems. Taking a discrete fracture network (DFN) as an example, a data-driven approach has been introduced to learn from outcrop, borehole imaging, core computed tomography scan, and seismic data to recognize stratigraphic bedding, faults, subseismic fractures, and hydraulic fractures. Input data can be collected by hand, 3D stereophotogrammetry, or drone. When upscaling DFN into a coarse grid for reservoir simulation, deep-learning techniques such as convolutional neuron networks can be used to populate fracture properties into a dual-porosity/dual-permeability model approved to yield high accuracy compared with a fine-grid model. Furthermore, the new techniques greatly extend the application of fracture modeling in the arena of the energy transition, such as in geothermal optimization. Recommended additional reading at OnePetro: www.onepetro.org. SPE 203927 - Numerical Simulation of Proppant Transport in Hydraulically Fractured Reservoirs by Seyhan Emre Gorucu, Computer Modelling Group, et al. SPE 202679 - Deep-Learning Approach To Predict Rheological Behavior of Supercritical CO2 Foam Fracturing Fluid Under Different Operating Conditions by Shehzad Ahmed, Khalifa University of Science and Technology, et al. SPE 203983 - A 3D Coupled Thermal/Hydraulic/Mechanical Model Using EDFM and XFEM for Hydraulic-Fracture-Dominated Geothermal Reservoirs by Xiangyu Yu, Colorado School of Mines, et al.

SP4.2.10 COVID-19 and General Surgery in a District General; Safety and Quality data

AimThe Covid-19 pandemic forced departments to change standard modes of delivery of care. Within our unit, reductions in junior workforce and changed operating protocols resulted in greater consultant presence on in-patient wards and the ambulatory unit. This study aimed to determine the effect on patient outcomes by interrogation of data collected from weekly Safety and Quality Clinical Governance meetings.MethodsPatients admitted between December 2019 and February 2020 were compared to those admitted between April 2020 and June 2020. The weekly meeting mandates consultant discussion of all readmissions, all patients who had a length of stay (LoS) of > 7 days and all admissions to critical care. Outcomes between the two time periods were compared.ResultsThere was a marked reduction in admissions during the second study period. However, the proportion of patients discharged from ambulatory care increased as did the proportion of readmissions; in the pre-Covid period, there were 429 readmissions of which 188 (44%) were unplanned but in the post-Covid period, there were 311 readmissions. There were no serious adverse events from discharged patients or readmissions.There were markedly fewer patients who had a LoS > 7days (179 patients versus 87) and a greater number of unplanned admissions to critical care (44% versus 64%).ConclusionsIncreased consultant presence may explain the reduced LoS and increased readmissions due to the greater ‘risk’ that senior clinicians are prepared to take. Enhanced consultant presence should be a permanent change, even after the pandemic is over.

The calcifying interface in a stony coral primary polyp: An interplay between seawater and an extracellular calcifying space

Stony coral exoskeletons build the foundation for the most biologically diverse marine ecosystems on Earth, coral reefs, which face major threats due to many anthropogenic–related stressors. Therefore, understanding coral biomineralization mechanisms is crucial for coral reef management in the coming decades and for using coral skeletons in geochemical studies. This study combines in–vivo imaging with cryo-electron microscopy and cryo–elemental mapping to gain novel insights into the biological microenvironment and the ion pathways that facilitate biomineralization in primary polyps of the stony coral Stylophora pistillata. We document increased tissue permeability in the primary polyp and a highly dispersed cell packing in the tissue directly responsible for producing the coral skeleton. This tissue arrangement may facilitate the intimate involvement of seawater at the mineralization site, also documented here. We further observe an extensive filopodial network containing carbon-rich vesicles extruding from some of the calicoblastic cells. Single-cell RNA-Sequencing data interrogation supports these morphological observations by showing higher expression of genes involved in filopodia and vesicle structure and function in the calicoblastic cells. These observations provide a new conceptual framework for resolving the ion pathway from the external seawater to the tissue-mineral interface in stony coral biomineralization processes.

Gender differences in reverse cardiac remodeling following initiation of sacubitril/valsartan in heart failure with reduced ejection fraction: real world experience

Abstract Background Gender related differences in physiology and pharamocokinetics have long been appreciated; however, the clinical relevance of these differences are unclear (1). Sacubitril/Valsartan has become established as a guideline directed therapy for the treatment of heart failure with reduced ejection therapy (HFref) and NYHA class II-IV symptoms. Interestingly; recent secondary analysis of key trials such as PARAGON-HF and PARADIGM, have highlighted possible differential gender specific benefits from Sacubitril/Valsartan therapy (2). We therefore sought to evaluate if there were gender specific effects of Sacubitril/Valsartan on both quantitative and qualitative measures of heart failure outcomes. Methods We performed a retrospective data interrogation of all patients commenced on Sacubitril/valsartan therapy in the SHSCT between 2016 and 2019. Data was extracted using electronic care records. Local ethical approval was granted. The primary endpoint were change in LVEF% on echocardiography and improvement in QOL (defined as NYHA score) at one year following initiation of Sacubitril/Valsartan. Differences in means between baseline and one year were assessed using a paired student's t-test. Interaction of gender on respective outcomes was assessed using a two way ANOVA. Significance defined as p<0.05. Data expressed as mean ± SD. Analysis performed using SPSS™. Results A total of 422 patients were included (mean age 69.1±12.1 years; 66% male). The predominant NYHA class' were II (n=298, 67.7%) and III (n=118, 26.8%). Aetiology and comorbidities were similar across male and females. In both groups, there was a statistically significant improvement in LVEF% at one year following initiation of Sacubitril/Valsartan (female; 27.1±8.6 to 34.6±9.5, n=40 p<0.01) (male; 27.4±7.5% to 32.6±9.3%, n=91, p<0.01). There was a statistically significant interaction between gender and degree of reverse cardiac remodeling defined as LVEF% on echocardiography following initiation of Sacubitril/Valsartan (F[2,52]=8.280, p=0.04, partial n2=0.27) (Figure 1). Similarly, there was a significant improvement in NYHA scores in both groups (male; 2.2±0.5 to 2.02±0.6, n=331, p<0.05) (female; 2.29±0.6 to 2.07±0.5, n=91, p<0.05) (Figure 2). However; there was no statistically significant interaction between gender and NYHA score following initiation of Sacubitril/Valsartan (F[2,52]=0.133, P=0.716, partial n2≤0.0). Conclusion Sacubitril/Valsartan produced significant improvement in reverse cardiac remodelling and QOL measures in both groups. Notably, had a stronger effect of reverse cardiac remodelling in women – suggesting possible gender specific differential benefits. Funding Acknowledgement Type of funding sources: None.

Comparison of polynomial fitting versus single time point analysis of ECIS data for barrier assessment.

Electrical cell‐substrate impedance sensing (ECIS) is an in vitro methodology for measuring the barrier integrity of a variety of cell types, including pulmonary endothelial cells. These experiments are frequently used for in vitro assessment of lung injury. The data derived from ECIS experiments consists of repeated measures of resistance across an endothelial monolayer. As such, these data reflect the dynamic changes in electrical resistance that occur over time. Currently methodologies for assessing ECIS data rely on single point assessments of barrier function, such as the maximal drop in trans‐endothelial electrical resistance (TERMax). However, this approach ignores the myriad of changes in resistance that occur before and after the TERMax data point. Herein, we utilize polynomial curve fitting on experimentally generated ECIS data, thus allowing for comparing ECIS experiments by examining the mean polynomial coefficients between groups. We show that polynomial curves accurately fit a variety of ECIS data, and that concordance between TERMax and coefficient analysis varies by type of stimulus, suggesting that TERMax differences may not always correlate with a significant difference in the overall shape of the ECIS profile. Lastly, we identify factors that impact coefficient values obtained in our analyses, including the length of time devoted to baseline measurements before addition of stimuli. Polynomial coefficient analysis is another tool that can be used for more comprehensive interrogation of ECIS data to better understand the biological underpinnings that lead to changes in barrier dysfunction in vitro.

Preimplantation Genetic Testing for Aneuploidy Improves Live Birth Rates with In Vitro Produced Bovine Embryos: A Blind Retrospective Study.

Approximately one million in vitro produced (IVP) cattle embryos are transferred worldwide each year as a way to improve the rates of genetic gain. The most advanced programmes also apply genomic selection at the embryonic stage by SNP genotyping and the calculation of genomic estimated breeding values (GEBVs). However, a high proportion of cattle embryos fail to establish a pregnancy. Here, we demonstrate that further interrogation of the SNP data collected for GEBVs can effectively remove aneuploid embryos from the pool, improving live births per embryo transfer (ET). Using three preimplantation genetic testing for aneuploidy (PGT-A) approaches, we assessed 1713 cattle blastocysts in a blind, retrospective analysis. Our findings indicate aneuploid embryos have a 5.8% chance of establishing a pregnancy and a 5.0% chance of given rise to a live birth. This compares to 59.6% and 46.7% for euploid embryos (p < 0.0001). PGT-A improved overall pregnancy and live birth rates by 7.5% and 5.8%, respectively (p < 0.0001). More detailed analyses revealed donor, chromosome, stage, grade, and sex-specific rates of error. Notably, we discovered a significantly higher incidence of aneuploidy in XY embryos and, as in humans, detected a preponderance of maternal meiosis I errors. Our data strongly support the use of PGT-A in cattle IVP programmes.

Alloimmunisation rate of patients on Daratumumab: A retrospective cohort study of patients in England.

Whilst small-scale studies on rates of alloimmunisation of patients on Daratumumab have been undertaken, no large-scale study has been performed to date on this cohort of patients. Patients with multiple myeloma (MM) who are relapsed or refractory to standard treatment are treated with the anti-CD38 therapeutic monoclonal antibody, Daratumumab. Due to the complexity of pre-transfusion compatibility testing, many MM patients in England are referred to Red Cell Immunohaematology (RCI) laboratories for investigation and provision of Red Blood Cell (RBC) components. Over a 4-month period, patients due to commence, or currently on anti-CD38 therapy were identified and flagged on the RCI Laboratory Information Management System (LIMS). Data was identified and extracted for further analysis. Interrogation of data was performed independently by two subject matter experts, with discrepancies resolved through further enquiry. Of 734 English MM patients, we report an alloimmunisation rate of 0.4% whilst on an anti-CD38 TMAb. This is in line with other smaller cohort studies. Given the low rate of RBC alloimmunisation, consideration should be given to revising the pre-transfusion testing regimen in this cohort. This may improve testing costs, turn-around times and evidence-based patient care.

TrueFootprint, Ltd.: a case study in the use of SME innovation to combat the COVID-19 pandemic

Purpose This case study aims to explore the efforts of a small start-up company, whose unique solutions are being deployed in the fight against COVID-19, with encouraging results. Using innovative technology and local volunteer networks, they have set out to identify the medical needs of local care providers, while reducing the effects of fraud, corruption and mis-management. Design/methodology/approach This case study involved the interrogation of data made available by the company and an interview with the chief executive officer. Findings The research suggests that small enterprises can have a positive impact, far beyond what either the state or the market might assume. By properly equipping and empowering people at the grassroots level, they can identify and solve local resourcing issues and root-out fraud, corruption and mismanagement before they happen. Originality/value This is a unique approach to the problem of resource management in the non-profit sector, with implications for grant projects beyond the COVID-19 pandemic.

Genetic analyses of gynecological disease identify genetic relationships between uterine fibroids and endometrial cancer, and a novel endometrial cancer genetic risk region at the WNT4 1p36.12 locus.

Endometriosis, polycystic ovary syndrome (PCOS) and uterine fibroids have been proposed as endometrial cancer risk factors; however, disentangling their relationships with endometrial cancer is complicated due to shared risk factors and comorbidities. Using genome-wide association study (GWAS) data, we explored the relationships between these non-cancerous gynecological diseases and endometrial cancer risk by assessing genetic correlation, causal relationships and shared risk loci. We found significant genetic correlation between endometrial cancer and PCOS, and uterine fibroids. Adjustment for genetically predicted body mass index (a risk factor for PCOS, uterine fibroids and endometrial cancer) substantially attenuated the genetic correlation between endometrial cancer and PCOS but did not affect the correlation with uterine fibroids. Mendelian randomization analyses suggested a causal relationship between only uterine fibroids and endometrial cancer. Gene-based analyses revealed risk regions shared between endometrial cancer and endometriosis, and uterine fibroids. Multi-trait GWAS analysis of endometrial cancer and the genetically correlated gynecological diseases identified a novel genome-wide significant endometrial cancer risk locus at 1p36.12, which replicated in an independent endometrial cancer dataset. Interrogation of functional genomic data at 1p36.12 revealed biologically relevant genes, including WNT4 which is necessary for the development of the female reproductive system. In summary, our study provides genetic evidence for a causal relationship between uterine fibroids and endometrial cancer. It further provides evidence that the comorbidity of endometrial cancer, PCOS and uterine fibroids may partly be due to shared genetic architecture. Notably, this shared architecture has revealed a novel genome-wide risk locus for endometrial cancer.

Addressing the Challenges of Interoperability and Cultural Heritage Data

One of the ongoing challenges for effective utilization of heritage science data is the lack of access to well-organized and accessible extant data sets and the need to structure data in formats that allow interrogation and integration of related data. This need for data fusion expands to both subjective and objective measurements and descriptors, as well as a long-overdue need for established guidelines for metadata and shared terminologies, or more critically, ontologies. Research into this area has shown the need for Knowledge Organization Systems (KOS) that bridge and integrate multiple ontologies that address specific needs – for example the Getty Vocabularies for cultural heritage terms, the Linked Art model for a simplified core CIDOC-CRM, as well as the OBO Foundry and other scientific ontologies for measurements and heritage science terminology.[1]

OMIC-09. MAPPING THE HISTONE MUTATIONAL LANDSCAPE ACROSS ADULT AND PEDIATRIC CANCER GENOMES UNCOVERS NOVEL SOMATIC MUTATIONS IN PEDIATRIC HIGH-GRADE GLIOMAS

There is a growing role for mutations affecting histone linker and histone core-encoding genes across several adult and pediatric cancers. However, the extent to which somatic histone mutations may bridge across different cancers as common tumorigenic events – particularly in the context of pediatric CNS tumors – remains unclear. To address this knowledge gap, we set out to define a comprehensive pan-cancer landscape of somatic histone mutations. We first queried the ICGC PCAWG and TCGA Pan-Cancer Atlas representing >12,500 adult and pediatric cancer patients. We found lymphomas to be most enriched for histone mutations (50–75%) and, in particular, for mutations in linker histones (HIST1H1B-E), yet also in specific core histone genes (eg, HIST2H2BE). Moreover, we observed a significant enrichment of histone mutations in adult high-grade vs low-grade gliomas (10% vs 6%, P<0.05, n=922 patients). Interrogation of whole genome data from 800 pediatric CNS tumor genomes (PBTA/OpenDIPG), identified novel (non-H3K27/non-H3G34) somatic histone mutations in 5–10% of subjects, including pediatric high-grade gliomas (pHGGs) and diffuse midline gliomas (DMGs). We found an overlapping set of histone genes to be recurrently mutated in non-CNS cancers and pediatric CNS tumors alike (eg, HIST1H1B/C/E). Notably, the only pediatric primary CNS lymphoma patient also harbored a histone linker alteration (HIST1H1B), similar to adult non-CNS lymphoma patients. We validated novel somatic histone mutations in DMGs by Sanger sequencing. Ongoing studies include in vitro assessment of the impact of these mutations on cell proliferation, chromatin accessibility, histone spacing, and gene expression. In addition, we will further assess associations with clinical outcome, age, and tumor subtypes. Collectively, oncohistone vulnerabilities were identified and defined as histone gene families recurrently mutated across all cancer types. Our analyses of adult and pediatric cancer genomes have uncovered previously unknown mutations affecting histone linker and core proteins, which may play a yet-undefined role in tumor etiology.

246-OR: Probing the Role of Alternative Splicing of IKZF1 in Risk for Type 1 Diabetes

Genome wide association studies have identified a region at chromosome 7p12.2, containing the IKZF1 gene, that is associated with type 1 diabetes (T1D). IKZF1 encodes Ikaros, a transcription factor and critical regulator of lymphocyte development and homeostasis. The IKZF1 gene includes 9 exons that produce at least 10 distinct transcripts. Exons 3-5 encode 4 zinc finger motifs that mediate DNA binding, while the last exon encodes 2 zinc fingers that allow homo- or heterodimerization. We examined the expression of IKZF1 using RNA-seq data from different lymphocyte populations. Individual coding exons of IKZF1, notably exons 3 and 5, displayed significant differences in usage between CD4+ T cells, CD8+ T cells and CD19+ B cells among T1D cases as well as between cases and controls in memory CD4+ T cells. This suggested that specific transcript isoforms of IKZF1 are differentially expressed in lymphocyte subtypes as well as in T1D. To explore the role of alternative splicing of IKZF1 in T1D, CRISPR/cas9 was used to generate Jurkat T cell lines with truncating mutations in either IKZF1 exon 3, exon 5 or both. Clones were isolated by serial dilution and characterized by PCR amplification and DNA sequencing. Twenty clones with different IKZF1 mutations were identified. Immunoblots revealed shifts in Ikaros protein isoform abundance consistent with the exon targeting in individual clones. Mutation of exons 3 or 5 resulted in the upregulation of 218 genes and the downregulation of 309 genes, as assayed by RNA-seq. Interrogation of ENCODE project data showed that most of these differentially expressed genes have an IKZF1 ChIP-seq peak within 1kb of the gene, consistent with their being targets of Ikaros regulation. These results suggest that the number of zinc finger domains in Ikaros, rather than their sequence or structure, modulates their impact. More broadly, the differential expression of IKZF1 transcripts distinguishes the transcriptomes of specific lymphocyte populations in both T1D cases and controls. Disclosure L. Pastor palomo: Employee; Spouse/Partner; Cox Business. J. R. B. Newman: None. M. A. Atkinson: None. P. J. Concannon: Stock/Shareholder; Self; Amgen Inc. Funding National Institutes of Health (R01DK116954, P01AI042288)

Cluster Identification Using Modularity Optimization to Uncover Chemical Heterogeneity in Complex Solutions.

Structural heterogeneity is commonly manifested in solutions and liquids that feature competition of different interparticle forces. Identifying and characterizing heterogeneity across different length scales requires multimodal experimental measurement and/or the application of new techniques for the interrogation of atomistic simulation data. Within the latter, the parsing of networks of interparticle interactions (chemical networks) has been demonstrated to be a valuable tool for identifying subensembles of chemical environments. However, chemical networks can adopt a wide variety of topologies that challenge generalizable methods for identifying heterogeneous behavior, and few network analysis algorithms have been proposed for multiscale resolution. In this study, we apply a method of partitioning using the graph theoretic concept of clusters and communities. Using a modularity optimization algorithm, the cluster partition creates subgraphs based on their relative internal and external connectivities. The methodology is tested on two soft matter systems that have significantly different network topologies so as to probe its ability to identify multiple scale features and its generalizability. A binary Lennard-Jones fluid is first examined, where one component causes subgraphs that have high internal network connectivity yet are still connected to the rest of the interparticle network of interactions. The impact of connectivity and edge weighting on the cluster partition is investigated. In the second system, hierarchically organized molecular structures comprised of hydrogen bonded water molecules are identified at a liquid/liquid interface. These structures have a much more sparse network with significantly varied internal connectivity that is a challenge to differentiate from the background hydrogen bonding network of water molecules at the instantaneous interface. The organized macrostructures are effectively isolated from the background network using the cluster partition, and a time-dependent implementation allows us to reveal their reactivity. These studies indicate that cluster partitioning based upon intermolecular network connectivity patterns is broadly generalizable, depending only on user-defined intermolecular connectivity, is operable across different length scales, and is extensible to the study of dynamic phenomena.

Genetic manipulation and immortalized culture of ex vivo primary human germinal center B cells

Next-generation sequencing has transformed our knowledge of the genetics of lymphoid malignancies. However, limited experimental systems are available to model the functional effects of these genetic changes and their implications for therapy. The majority of mature B-cell malignancies arise from the germinal center (GC) stage of B-cell differentiation. Here we describe a detailed protocol for the purification and ex vivo expansion of primary, nonmalignant human GC B cells. We present methodology for the high-efficiency transduction of these cells to enable combinatorial expression of putative oncogenes. We also describe alternative approaches for CRISPR-Cas9-mediated deletion of putative tumor suppressors. Mimicking genetic changes commonly found in lymphoid malignancies leads to immortalized growth in vitro, while engraftment into immunodeficient mice generates genetically customized, synthetic models of human lymphoma. The protocol is simple and inexpensive and can be implemented in any laboratory with access to standard cell culture and animal facilities. It can be easily scaled up to enable high-throughput screening and thus provides a versatile platform for the functional interrogation of lymphoma genomic data.

Interrogation of clonal tracking data using barcodetrackR.

Clonal tracking methods provide quantitative insights into the cellular output of genetically labelled progenitor cells across time and cellular compartments. In the context of gene and cell therapies, clonal tracking methods have enabled the tracking of progenitor cell output both in humans receiving therapies and in corresponding animal models, providing valuable insight into lineage reconstitution, clonal dynamics, and vector genotoxicity. However, the absence of a toolbox for analysis of clonal tracking data has precluded the development of standardized analytical frameworks within the field. Thus, we developed barcodetrackR, an R package and accompanying Shiny app containing diverse tools for the analysis and visualization of clonal tracking data. We demonstrate the utility of barcodetrackR in exploring longitudinal clonal patterns and lineage relationships in a number of clonal tracking studies of hematopoietic stem and progenitor cells (HSPCs) in humans receiving HSPC gene therapy and in animals receiving lentivirally transduced HSPC transplants or tumor cells.

Multi-Modal Characterization of Monocytes in Idiopathic Pulmonary Fibrosis Reveals a Primed Type I Interferon Immune Phenotype.

Idiopathic pulmonary fibrosis (IPF) is the most severe form of chronic lung fibrosis. Circulating monocytes have been implicated in immune pathology in IPF but their phenotype is unknown. In this work, we determined the immune phenotype of monocytes in IPF using multi-colour flow cytometry, RNA sequencing and corresponding serum factors, and mapped the main findings to amount of lung fibrosis and single cell transcriptomic landscape of myeloid cells in IPF lungs. We show that monocytes from IPF patients displayed increased expression of CD64 (FcγR1) which correlated with amount of lung fibrosis, and an amplified type I IFN response ex vivo. These were accompanied by markedly raised CSF-1 levels, IL-6, and CCL-2 in serum of IPF patients. Interrogation of single cell transcriptomic data from human IPF lungs revealed increased proportion of CD64hi monocytes and “transitional macrophages” with higher expression of CCL-2 and type I IFN genes. Our study shows that monocytes in IPF patients are phenotypically distinct from age-matched controls, with a primed type I IFN pathway that may contribute to driving chronic inflammation and fibrosis. These findings strengthen the potential role of monocytes in the pathogenesis of IPF.

Recoup: flexible and versatile signal visualization from next generation sequencing

BackgroundThe relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging.Resultsrecoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations.ConclusionWhile some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.