Direct liquefaction of coal with coal-derived solvents to produce precursors for carbon products

Direct liquefaction (hydrogenation) of coal has frequently been pursued as one avenue for the production of value added products from coal. The focus of this research was to evaluate five coal-derived liquids as substitutes for tetralin in the coal hydrogenation process. A mid-distillate by-product liquid from the production of high quality char was obtained from Antaeus Technical Services, Inc. and split into three fractions, the original liquid (RACL), its heavy fraction (DACL-H), and its light fraction (DACL-L). The other two liquids were heavy creosote oil (HCO) and carbon black base #1 (CBB) from Koppers Industries, Inc. These liquids were used as hydrogenation solvents under varying reaction conditions such as gas pressure, gas composition, and solvent-to-coal ratio. The products were separated by filtration and vacuum distillation to produce three fractions, the THF insolubles, pitch, and recycle solvent. The coal-alone conversions were calculated for each hydrogenation reaction and the pitch fractions were characterized as possible carbon-product precursors by softening point, ash content, coke yield, elemental analysis, and optical texture. (Abstract shortened by UMI.)

Tertiary lymphoid structures are associated with higher tumor grade in primary operable breast cancer patients

Published version, also available at http://dx.doi.org/10.1186/s12885-015-1116-1Background: Tertiary lymphoid structures (TLS) are highly organized immune cell aggregates that develop at sites of inflammation or infection in non-lymphoid organs. Despite the described role of inflammation in tumor progression, it is still unclear whether the process of lymphoid neogenesis and biological function of ectopic lymphoid tissue in tumors are beneficial or detrimental to tumor growth. In this study we analysed if TLS are found in human breast carcinomas and its association with clinicopathological parameters. Methods: In a patient group (n = 290) who underwent primary surgery between 2011 and 2012 we assessed the interrelationship between the presence of TLS in breast tumors and clinicopathological factors. Prognostic factors were entered into a binary logistic regression model for identifying independent predictors for intratumoral TLS formation. Results: There was a positive association between the grade of immune cell infiltration within the tumor and important prognostic parameters such as hormone receptor status, tumor grade and lymph node involvement. The majority of patients with high grade infiltration of immune cells had TLS positive tumors. In addition to the degree of immune cell infiltration, the presence of TLS was associated with organized immune cell aggregates, hormone receptor status and tumor grade. Tumors with histological grade 3 were the strongest predictor for the presence of TLS in a multivariate regression model. The model also predicted that the odds for having intratumoral TLS formation were ten times higher for patients with high grade of inflammation than low grade. Conclusions: Human breast carcinomas frequently contain TLS and the presence of these structures is associated with aggressive forms of tumors. Locally generated immune response with potentially antitumor immunity may control tumorigenesis and metastasis. Thus, defining the role of TLS formation in breast carcinomas may lead to alternative therapeutic approaches targeting the immune system

Novel long-coding RNAs of relevance for ulcerative colitis pathogenesis

Poster presented at the Norwegian Bioinformatics Days 2022, Sundvolden, 28-30 September 2022.Introduction - LncRNAs have become a growing field of research. They are involved in diverse biological processes including expression regulation, and chromatin modification. Many lncRNAs have been characterized as involved in the occurrence and development of various human diseases, including cancer. A growing body of evidence implies a role for lncRNAs in UC by modulating the intestinal barrier, regulating the expression of inflammatory cytokines, and polarization of macrophages. Problems - Accurate quantification of lncRNA transcripts is challenging due to the low expression of lncRNAs, and their exons overlap protein-coding exons on the same strand. Aims - The study aimed to define the role of uncharacterized long noncoding RNAs (lncRNAs) in treatment-naïve ulcerative colitis (UC). Method - To overcome difficulties in lncRNA transcript quantification, multiple and “stringent” strategies were applied. New insights in the regulation of functional genes and pathways of relevance for UC through expression of lncRNAs are expected Conclusion - This study identified a set of 15 yet uncharacterized lncRNAs which may be of importance for UC pathogenesis. These lncRNAs may serve as potential diagnostic biomarkers and might be of use for the development of UC treatment strategies in the future. The proposed method can also be helpful to quantify low expressed lncRNA transcripts in other datasets

Novel long non-coding RNAs of relevance for ulcerative colitis pathogenesis

Background and aims: The study aimed to identify yet unknown and uncharacterized long non-coding RNAs (lncRNAs) in treatment-naïve ulcerative colitis (UC), and to define their possible roles in UC pathogenesis. For that purpose, accurate quantification methods for lncRNA transcript detection, multiple and “stringent” strategies were applied. New insights in the regulation of functional genes and pathways of relevance for UC through expression of lncRNAs are expected. Methods: The study was based on sequencing data derived from a data set consisting of treatment-naïve UC patients (n = 14) and control subjects (n = 16). Two complementary aligners were used to identify lncRNAs. Several different steps were used to validate differential expression including plotting the reads over the annotation for manual inspection. To help determine potential lncRNA involvement in biological processes, KEGG pathway enrichment was done on protein-coding genes which co-expressed with the lncRNAs. Results: A total of 99 lncRNAs were identified in UC. The lncRNAs which were not previously characterized (n = 15) in UC or other autoimmune diseases were selected for down-stream analysis. In total, 602 protein-coding genes correlated with the uncharacterized lncRNAs. KEGG pathway enrichment analysis revealed involvement of lncRNAs in two significantly enriched pathways, lipid and atherosclerosis, and T-cell receptor signaling. Conclusion: This study identified a set of 15 yet uncharacterized lncRNAs which may be of importance for UC pathogenesis. These lncRNAs may serve as potential diagnostic biomarkers and might be of use for the development of UC treatment strategies in the future

ICAM1 expression is induced by proinflammatory cytokines and associated with TLS formation in aggressive breast cancer subtypes

Source at https://doi.org/10.1038/s41598-018-29604-2.Intratumoral formation of tertiary lymphoid structures (TLS) within the tumor microenvironment is considered to be a consequence of antigen challenge during anti-tumor responses. Intracellular adhesion molecule 1 (ICAM1) has been implicated in a variety of immune and inflammatory responses, in addition to associate with triple negative breast cancer (TNBC). In this study, we detected TLS in the aggressive tumor phenotypes TNBC, HER2+ and luminal B, whereas the TLS negative group contained solely tumors of the luminal A subtype. We show that ICAM1 is exclusively expressed in TNBC and HER2 enriched subtypes known to be associated with inflammation and the formation of TLS. Furthermore, cell from normal mammary epithelium and breast cancer cell lines expressed ICAM1 upon stimulation with the proinflammatory cytokines TNFα, IL1β and IFNγ. ICAM1 overexpression was induced in MCF7, MDA-MB-468 and SK-BR-3 cells regardless of hormone receptor status. Taken together, our findings show that ICAM1 is expressed in aggressive subtypes of breast cancer and its expression is inducible by well-known proinflammatory cytokines. ICAM1 may be an attractive molecular target for TNBC, but further investigations elucidating the role of ICAM1 in targeted therapies have to take into consideration selective subtypes of breast cancer

Methylation-regulated long non-coding RNA expression in ulcerative colitis

Long non-coding RNAs (lncRNAs) have been shown to play a role in the pathogenesis of ulcerative colitis (UC). Although epigenetic processes such as DNA methylation and lncRNA expression are well studied in UC, the importance of the interplay between the two processes has not yet been fully explored. It is, therefore, believed that interactions between environmental factors and epigenetics contribute to disease development. Mucosal biopsies from 11 treatment-naïve UC patients and 13 normal controls were used in this study. From each individual sample, both whole-genome bisulfite sequencing data (WGBS) and lncRNA expression data were analyzed. Correlation analysis between lncRNA expression and upstream differentially methylated regions (DMRs) was used to identify lncRNAs that might be regulated by DMRs. Furthermore, proximal protein-coding genes associated with DMR-regulated lncRNAs were identified by correlating their expression. The study identified UC-associated lncRNAs such as MIR4435-2HG, ZFAS1, IL6-AS1, and Pvt1, which may be regulated by DMRs. Several genes that are involved in inflammatory immune responses were found downstream of DMR-regulated lncRNAs, including SERPINB1, CCL18, and SLC15A4. The interplay between lncRNA expression regulated by DNA methylation in UC might improve our understanding of UC pathogenesis

Reconstructing Cardiac Electrical Excitations from Optical Mapping Recordings

The reconstruction of electrical excitation patterns through the unobserved depth of the tissue is essential to realizing the potential of computational models in cardiac medicine. We have utilized experimental optical-mapping recordings of cardiac electrical excitation on the epicardial and endocardial surfaces of a canine ventricle as observations directing a local ensemble transform Kalman Filter (LETKF) data assimilation scheme. We demonstrate that the inclusion of explicit information about the stimulation protocol can marginally improve the confidence of the ensemble reconstruction and the reliability of the assimilation over time. Likewise, we consider the efficacy of stochastic modeling additions to the assimilation scheme in the context of experimentally derived observation sets. Approximation error is addressed at both the observation and modeling stages, through the uncertainty of observations and the specification of the model used in the assimilation ensemble. We find that perturbative modifications to the observations have marginal to deleterious effects on the accuracy and robustness of the state reconstruction. Further, we find that incorporating additional information from the observations into the model itself (in the case of stimulus and stochastic currents) has a marginal improvement on the reconstruction accuracy over a fully autonomous model, while complicating the model itself and thus introducing potential for new types of model error. That the inclusion of explicit modeling information has negligible to negative effects on the reconstruction implies the need for new avenues for optimization of data assimilation schemes applied to cardiac electrical excitation.Comment: main text: 18 pages, 10 figures; supplement: 5 pages, 9 figures, 2 movie

Employing Gaussian process priors for studying spatial variation in the parameters of a cardiac action potential model

Cardiac cells exhibit variability in the shape and duration of their action potentials in space within a single individual. To create a mathematical model of cardiac action potentials (AP) which captures this spatial variability and also allows for rigorous uncertainty quantification regarding within-tissue spatial correlation structure, we developed a novel hierarchical Bayesian model making use of a latent Gaussian process prior on the parameters of a simplified cardiac AP model which is used to map forcing behavior to observed voltage signals. This model allows for prediction of cardiac electrophysiological dynamics at new points in space and also allows for reconstruction of surface electrical dynamics with a relatively small number of spatial observation points. Furthermore, we make use of Markov chain Monte Carlo methods via the Stan modeling framework for parameter estimation. We employ a synthetic data case study oriented around the reconstruction of a sparsely-observed spatial parameter surface to highlight how this approach can be used for spatial or spatiotemporal analyses of cardiac electrophysiology