The transformation in biomarker detection and management of drug-induced liver injury

Drug-induced liver injury (DILI) is a major concern for patients, care givers and the pharmaceutical industry. Interpretation of the serum biomarkers routinely used to detect and monitor DILI, which have not changed in almost 50 years, can be improved with recently proposed models employing quantitative systems pharmacology. In addition, several newer serum biomarkers are showing great promise. Studies in rodents indicate that the ratio of the caspase cleaved fragment of cytokeratin 18 to total K18 in serum (termed the “apoptotic index”) estimates the relative proportions of apoptosis vs necrosis during drug-induced liver injury. Glutamate dehydrogenase can reliably differentiate liver from muscle injury and, when serum is properly prepared, may also detect mitochondrial toxicity as a mechanism of liver injury. MicroRNA-122 is liver-specific, but recent data suggests it can be actively released from hepatocytes in the absence of overt toxicity limiting enthusiasm for it as a DILI biomarker. Finally, damage associated molecular patterns, particularly high mobility group box 1 and its various modified forms, are promising biomarkers of innate immune activation, which may be useful in distinguishing benign elevations in aminotransferases from those that portend clinically important liver injury. These new biomarkers are already being measured in early clinical trials, but broad acceptance will require widespread archiving of serum from diverse clinical trials and probably pre-competitive analysis efforts. We believe that utilization of a panel of traditional and newer biomarkers in conjunction with quantitative systems pharmacology modeling approaches will transform DILI detection and risk management

Prostaglandin E2 Produced by the Lung Augments the Effector Phase of Allergic Inflammation

Elevated PGE2 is a hallmark of most inflammatory lesions. This lipid mediator can induce the cardinal signs of inflammation, and the beneficial actions of non-steroidal anti-inflammatory drugs are attributed to inhibition of cyclooxygenase COX-1 and COX-2, enzymes essential in the biosynthesis of PGE2 from arachidonic acid. However, both clinical studies and rodent models suggest that, in the asthmatic lung, PGE2 acts to restrain the immune response and limit physiological change secondary to inflammation. To directly address the role of PGE2 in the lung, we examined the development of disease in mice lacking microsomal prostaglandin E synthase 1 (mPGES1), which converts COX-1/COX-2 derived PGH2 to PGE2. We show that mPGES1 determines PGE2 levels in the naïve lung and is required for increases in PGE2 after ovalbumin (OVA) induced allergy. While loss of either COX-1 or COX-2 increases the disease severity, surprisingly mPGES1 −/− mice show reduced inflammation. However, an increase in serum IgE is still observed in the mPGES1 −/− mice, suggesting that loss of PGE2 does not impair induction of a TH2 response. Furthermore, mPGES1 −/− mice expressing a transgenic OVA-specific T cell receptor are also protected, indicating that PGE2 acts primarily after challenge with inhaled antigen. PGE2 produced by the lung plays the critical role in this response, as loss of lung mPGES1 is sufficient to protect against disease. Together this supports a model in which mPGES1-dependent PGE2 produced by populations of cells native to the lung contributes to the effector phase of some allergic responses

Deep Sea Biofilms, Historic Shipwreck Preservation and the Deepwater Horizon Spill

Exposure to oil from the Deepwater Horizon spill may have lasting impacts on preservation of historic shipwrecks in the Gulf of Mexico. Submerged steel structures, including shipwrecks, serve as artificial reefs and become hotspots of biodiversity in the deep-sea. Marine biofilms on submerged structures support settlement of micro- and macrobiota and may enhance and protect against corrosion. Disruptions in the local environment, including oil spills, may impact the role that biofilms play in reef preservation. To determine how the Deepwater Horizon spill potentially impacted shipwreck biofilms and the functional roles of the biofilm microbiome, experiments containing carbon steels disks (CSDs) were placed at five historic shipwreck sites located within, and external to the benthic footprint of the Deepwater Horizon spill. The CSDs were incubated for 16 weeks to enable colonization by biofilm-forming microorganisms and to provide time for in situ corrosion to occur. Biofilms from the CSDs, as well as sediment and water microbiomes, were collected and analyzed by 16S rRNA amplicon gene sequencing to describe community composition and determine the source of taxa colonizing biofilms. Biofilm metagenomes were sequenced to compare differential gene abundances at spill-impacted and reference sites. Biofilms were dominated by Zeta-, Alpha-, Epsilon and Gammaproteobacteria. Sequences affiliated with the Mariprofundus and Sulfurimonas genera were prolific, and Roseobacter, and Colwellia genera were also abundant. Analysis of 16S rRNA sequences from sediment, water, and biofilms revealed sediment to be the main known source of taxa to biofilms at impacted sites. Differential gene abundance analysis revealed the two-component response regulator CreC, a gene involved in environmental stress response, to be elevated at reference sites compared to impacted sites within the spill plume fallout area on the seafloor. Genes for chemotaxis, motility, and alcohol dehydrogenases were differentially abundant at reference vs. impacted sites. Metal loss on CSDs was elevated at sites within the spill fallout plume. Time series images reveal that metal loss at a heavily impacted site, the German Submarine U-166, has accelerated since the spill in 2010. This study provides evidence that spill residues on the seafloor may impact biofilm communities and the preservation of historic steel shipwrecks

Gesture analysis for physics education researchers

Systematic observations of student gestures can not only fill in gaps in students' verbal expressions, but can also offer valuable information about student ideas, including their source, their novelty to the speaker, and their construction in real time. This paper provides a review of the research in gesture analysis that is most relevant to physics education researchers and illustrates gesture analysis for the purpose of better understanding student thinking about physics.Comment: 14 page

Application of a Mechanistic Model to Evaluate Putative Mechanisms of Tolvaptan Drug-Induced Liver Injury and Identify Patient Susceptibility Factors

Tolvaptan is a selective vasopressin V2 receptor antagonist, approved in several countries for the treatment of hyponatremia and autosomal dominant polycystic kidney disease (ADPKD). No liver injury has been observed with tolvaptan treatment in healthy subjects and in non-ADPKD indications, but ADPKD clinical trials showed evidence of drug-induced liver injury (DILI). Although all DILI events resolved, additional monitoring in tolvaptan-treated ADPKD patients is required. In vitro assays identified alterations in bile acid disposition and inhibition of mitochondrial respiration as potential mechanisms underlying tolvaptan hepatotoxicity. This report details the application of DILIsym software to determine whether these mechanisms could account for the liver safety profile of tolvaptan observed in ADPKD clinical trials. DILIsym simulations included physiologically based pharmacokinetic estimates of hepatic exposure for tolvaptan and2 metabolites, and their effects on hepatocyte bile acid transporters and mitochondrial respiration. The frequency of predicted alanine aminotransferase (ALT) elevations, following simulated 90/30 mg split daily dosing, was 7.9% compared with clinical observations of 4.4% in ADPKD trials. Toxicity was multifactorial as inhibition of bile acid transporters and mitochondrial respiration contributed to the simulated DILI. Furthermore, simulation analysis identified both pre-treatment risk factors and on-treatment biomarkers predictive of simulated DILI. The simulations demonstrated that in vivo hepatic exposure to tolvaptan and the DM-4103 metabolite, combined with these 2 mechanisms of toxicity, were sufficient to account for the initiation of tolvaptan-mediated DILI. Identification of putative risk-factors and potential novel biomarkers provided insight for the development of mechanism-based tolvaptan risk-mitigation strategies

Deep-Sea Biofilms, Historic Shipwreck Preservation and the Deepwater Horizon Spill

Exposure to oil from the Deepwater Horizon spill may have lasting impacts on preservation of historic shipwrecks in the Gulf of Mexico. Submerged steel structures, including shipwrecks, serve as artificial reefs and become hotspots of biodiversity in the deep sea. Marine biofilms on submerged structures support settlement of micro- and macro-biota and may enhance and protect against corrosion. Disruptions in the local environment, including oil spills, may impact the role that biofilms play in reef preservation. To determine how the Deepwater Horizon spill potentially impacted shipwreck biofilms and the functional roles of the biofilm microbiome, experiments containing carbon steels disks (CSDs) were placed at five historic shipwreck sites located within, and external to the benthic footprint of the Deepwater Horizon spill. The CSDs were incubated for 16 weeks to enable colonization by biofilm-forming microorganisms and to provide time for in situ corrosion to occur. Biofilms from the CSDs, as well as sediment and water microbiomes, were collected and analyzed by 16S rRNA amplicon gene sequencing to describe community composition and determine the source of taxa colonizing biofilms. Biofilm metagenomes were sequenced to compare differential gene abundances at spill-impacted and reference sites. Biofilms were dominated by Zeta-, Alpha-, Epsilon-, and Gamma-proteobacteria. Sequences affiliated with the Mariprofundus and Sulfurimonas genera were prolific, and Roseobacter, and Colwellia genera were also abundant. Analysis of 16S rRNA sequences from sediment, water, and biofilms revealed sediment to be the main known source of taxa to biofilms at impacted sites. Differential gene abundance analysis revealed the two-component response regulator CreC, a gene involved in environmental stress response, to be elevated at reference sites compared to impacted sites within the spill plume fallout area on the seafloor. Genes for chemotaxis, motility, and alcohol dehydrogenases were differentially abundant at reference vs. impacted sites. Metal loss on CSDs was elevated at sites within the spill fallout plume. Time series images reveal that metal loss at a heavily impacted site, the German Submarine U-166, has accelerated since the spill in 2010. This study provides evidence that spill residues on the seafloor may impact biofilm communities and the preservation of historic steel shipwrecks

Characterization of the Cytochrome P450 epoxyeicosanoid pathway in non-alcoholic steatohepatitis

Non-alcoholic steatohepatitis (NASH) is an emerging public health problem without effective therapies. Cytochrome P450 (CYP) epoxygenases metabolize arachidonic acid into bioactive epoxyeicosatrienoic acids (EETs), which have potent anti-inflammatory and protective effects. However, the functional relevance of the CYP epoxyeicosanoid metabolism pathway in the pathogenesis of NASH remains poorly understood. Our studies demonstrate that both mice with methionine-choline deficient (MCD) diet-induced NASH and humans with biopsy-confirmed NASH exhibited significantly higher free EET concentrations compared to healthy controls. Targeted disruption of Ephx2 (the gene encoding for soluble epoxide hydrolase) in mice further increased EET levels and significantly attenuated MCD diet-induced hepatic steatosis, inflammation and injury, as well as high fat diet-induced adipose tissue inflammation, systemic glucose intolerance and hepatic steatosis. Collectively, these findings suggest that dysregulation of the CYP epoxyeicosanoid pathway is a key pathological consequence of NASH in vivo, and promoting the anti-inflammatory and protective effects of EETs warrants further investigation as a novel therapeutic strategy for NASH

Low-cost table-top experiments for teaching multi-scale geophysical fluid dynamics

Multi-scale instabilities are ubiquitous in atmospheric and oceanic flows and are essential topics in teaching geophysical fluid dynamics. Yet these topics are often difficult to teach and counter-intuitive to new learners. In this paper, we introduce our state-of-the-art Do-It Yourself Dynamics (DIYnamics) LEGO® robotics kit that allows users to create table-top models of geophysical flows. Deep ocean convection processes are simulated via three experiments – upright convection, thermal wind flows, and baroclinic instability – in order to demonstrate the robust multi-scale modeling capabilities of our kit. Detailed recipes are provided to allow users to reproduce these experiments. Further, dye-visualization measurements show that the table-top experimental results adequately agree with theory. In sum, our DIYnamics setup provides students and educators with an accessible table-top framework by which to model the multi-scale behaviors, inherent in canonical geophysical flows, such as deep ocean convection

Deep learning for prediction of colorectal cancer outcome: a discovery and validation study

Background Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal cancer resection by directly analysing scanned conventional haematoxylin and eosin stained sections using deep learning. Methods More than 12 000 000 image tiles from patients with a distinctly good or poor disease outcome from four cohorts were used to train a total of ten convolutional neural networks, purpose-built for classifying supersized heterogeneous images. A prognostic biomarker integrating the ten networks was determined using patients with a non-distinct outcome. The marker was tested on 920 patients with slides prepared in the UK, and then independently validated according to a predefined protocol in 1122 patients treated with single-agent capecitabine using slides prepared in Norway. All cohorts included only patients with resectable tumours, and a formalin-fixed, paraffin-embedded tumour tissue block available for analysis. The primary outcome was cancer-specific survival. Findings 828 patients from four cohorts had a distinct outcome and were used as a training cohort to obtain clear ground truth. 1645 patients had a non-distinct outcome and were used for tuning. The biomarker provided a hazard ratio for poor versus good prognosis of 3·84 (95% CI 2·72–5·43; p<0·0001) in the primary analysis of the validation cohort, and 3·04 (2·07–4·47; p<0·0001) after adjusting for established prognostic markers significant in univariable analyses of the same cohort, which were pN stage, pT stage, lymphatic invasion, and venous vascular invasion. Interpretation A clinically useful prognostic marker was developed using deep learning allied to digital scanning of conventional haematoxylin and eosin stained tumour tissue sections. The assay has been extensively evaluated in large, independent patient populations, correlates with and outperforms established molecular and morphological prognostic markers, and gives consistent results across tumour and nodal stage. The biomarker stratified stage II and III patients into sufficiently distinct prognostic groups that potentially could be used to guide selection of adjuvant treatment by avoiding therapy in very low risk groups and identifying patients who would benefit from more intensive treatment regimes