Intracystic Hemorrhage In A Simple Liver Cyst Due To Dual Anti-Platelet Therapy After Percutaneous Coronary Intervention

Hemorrhage into a simple hepatic cyst often results in development of a complex cystic lesion, which makes this identical to a cystic tumor. We present a striking example of this decision-making in a patient with suspected intracystic hemorrhage from recent anti-platelet medication use post-percutaneous coronary intervention (PCI). 83-year-old male presented to the hospital with acute right upper quadrant (RUQ) abdominal pain, severe and constant. This was associated with nausea and constipation. Medical history was significant for recent PCI and initiation of dual anti-platelet therapy (DAPT) ten days ago, and chronic thrombocytopenia. Ultrasound and CT confirmed complex 12.8 x 11.4 x 12.4 cm hepatic cyst, with suspected, intracystic hemorrhage of a simple liver cyst. Given failed conservative management, surgical route was opted. Laparoscopic fenestration of the cyst yielded a large volume of bloody material confirming the diagnosis. Biopsy of the cyst wall showed simple liver cyst with an adherent blood clot. Aspirin was resumed post-operatively, and ticagrelor was continued throughout given the high risk of stent thrombosis. Intracystic hemorrhage in a simple liver cyst, though rare, is a possible complication of DAPT use after PCI. Further use of DAPT usually requires tailored approach to patient’s coronary anatomy, nature of stent used, underlying risk factors and type of bleed

Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks

The idea of 'date' and 'party' hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. Thus, we suggest that a date/party dichotomy is not meaningful and it might be more useful to conceive of roles for protein-protein interactions rather than individual proteins. We find significant correlations between interaction centrality and the functional similarity of the interacting proteins.Comment: 27 pages, 5 main figures, 4 supplementary figure

Impact of Active and Historical Cancers on the Management and Outcomes of Acute Myocardial Infarction Complicating Cardiogenic Shock

BACKGROUND: There are limited data on the outcomes of acute myocardial infarction-cardiogenic shock (AMI-CS) in patients with concomitant cancer. METHODS: A retrospective cohort of adult AMI-CS admissions was identified from the National Inpatient Sample (2000-2017) and stratified by active cancer, historical cancer, and no cancer. Outcomes of interest included in-hospital mortality, use of coronary angiography, use of percutaneous coronary intervention, do-not-resuscitate status, palliative care use, hospitalization costs, and hospital length of stay. RESULTS: Of the 557,974 AMI-CS admissions during this 18-year period, active and historical cancers were noted in 14,826 (2.6%) and 27,073 (4.8%), respectively. From 2000 to 2017, there was a decline in active cancers (adjusted odds ratio, 0.70 [95% CI, 0.63-0.79]; P \u3c .001) and an increase in historical cancer (adjusted odds ratio, 2.06 [95% CI, 1.89-2.25]; P \u3c .001). Compared with patients with no cancer, patients with active and historical cancer received less-frequent coronary angiography (57%, 67%, and 70%, respectively) and percutaneous coronary intervention (40%, 47%, and 49%%, respectively) and had higher do-not-resuscitate status (13%, 15%, 7%%, respectively) and palliative care use (12%, 10%, 6%%, respectively) (P \u3c .001). Compared with those without cancer, higher in-hospital mortality was found in admissions with active cancer (45.9% vs 37.0%; adjusted odds ratio, 1.29 [95% CI, 1.24-1.34]; P \u3c .001) but not historical cancer (40.1% vs 37.0%; adjusted odds ratio, 1.01 [95% CI, 0.98-1.04]; P = .39). AMI-CS admissions with cancer had a shorter hospitalization duration and lower costs (all P \u3c .001). CONCLUSION: Concomitant cancer was associated with less use of guideline-directed procedures. Active, but not historical, cancer was associated with higher mortality in patients with AMI-CS

Identifying Hubs in Protein Interaction Networks

In spite of the scale-free degree distribution that characterizes most protein interaction networks (PINs), it is common to define an ad hoc degree scale that defines "hub" proteins having special topological and functional significance. This raises the concern that some conclusions on the functional significance of proteins based on network properties may not be robust.In this paper we present three objective methods to define hub proteins in PINs: one is a purely topological method and two others are based on gene expression and function. By applying these methods to four distinct PINs, we examine the extent of agreement among these methods and implications of these results on network construction.We find that the methods agree well for networks that contain a balance between error-free and unbiased interactions, indicating that the hub concept is meaningful for such networks

Intrinsic Noise Analyzer: A Software Package for the Exploration of Stochastic Biochemical Kinetics Using the System Size Expansion

The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen’s system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA’s performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with circadian rhythms. The software iNA is freely available as executable binaries for Linux, MacOSX and Microsoft Windows, as well as the full source code under an open source license

Casual Compressive Sensing for Gene Network Inference

We propose a novel framework for studying causal inference of gene interactions using a combination of compressive sensing and Granger causality techniques. The gist of the approach is to discover sparse linear dependencies between time series of gene expressions via a Granger-type elimination method. The method is tested on the Gardner dataset for the SOS network in E. coli, for which both known and unknown causal relationships are discovered

A New Methodology to Associate SNPs with Human Diseases According to Their Pathway Related Context

Genome-wide association studies (GWAS) with hundreds of żthousands of single nucleotide polymorphisms (SNPs) are popular strategies to reveal the genetic basis of human complex diseases. Despite many successes of GWAS, it is well recognized that new analytical approaches have to be integrated to achieve their full potential. Starting with a list of SNPs, found to be associated with disease in GWAS, here we propose a novel methodology to devise functionally important KEGG pathways through the identification of genes within these pathways, where these genes are obtained from SNP analysis. Our methodology is based on functionalization of important SNPs to identify effected genes and disease related pathways. We have tested our methodology on WTCCC Rheumatoid Arthritis (RA) dataset and identified: i) previously known RA related KEGG pathways (e.g., Toll-like receptor signaling, Jak-STAT signaling, Antigen processing, Leukocyte transendothelial migration and MAPK signaling pathways); ii) additional KEGG pathways (e.g., Pathways in cancer, Neurotrophin signaling, Chemokine signaling pathways) as associated with RA. Furthermore, these newly found pathways included genes which are targets of RA-specific drugs. Even though GWAS analysis identifies 14 out of 83 of those drug target genes; newly found functionally important KEGG pathways led to the discovery of 25 out of 83 genes, known to be used as drug targets for the treatment of RA. Among the previously known pathways, we identified additional genes associated with RA (e.g. Antigen processing and presentation, Tight junction). Importantly, within these pathways, the associations between some of these additionally found genes, such as HLA-C, HLA-G, PRKCQ, PRKCZ, TAP1, TAP2 and RA were verified by either OMIM database or by literature retrieved from the NCBI PubMed module. With the whole-genome sequencing on the horizon, we show that the full potential of GWAS can be achieved by integrating pathway and network-oriented analysis and prior knowledge from functional properties of a SNP

Noise Management by Molecular Networks

Fluctuations in the copy number of key regulatory macromolecules (“noise”) may cause physiological heterogeneity in populations of (isogenic) cells. The kinetics of processes and their wiring in molecular networks can modulate this molecular noise. Here we present a theoretical framework to study the principles of noise management by the molecular networks in living cells. The theory makes use of the natural, hierarchical organization of those networks and makes their noise management more understandable in terms of network structure. Principles governing noise management by ultrasensitive systems, signaling cascades, gene networks and feedback circuitry are discovered using this approach. For a few frequently occurring network motifs we show how they manage noise. We derive simple and intuitive equations for noise in molecule copy numbers as a determinant of physiological heterogeneity. We show how noise levels and signal sensitivity can be set independently in molecular networks, but often changes in signal sensitivity affect noise propagation. Using theory and simulations, we show that negative feedback can both enhance and reduce noise. We identify a trade-off; noise reduction in one molecular intermediate by negative feedback is at the expense of increased noise in the levels of other molecules along the feedback loop. The reactants of the processes that are strongly (cooperatively) regulated, so as to allow for negative feedback with a high strength, will display enhanced noise