Ontology-based collection, representation and analysis of drug-associated neuropathy adverse events

Abstract Background Neuropathy often occurs following drug treatment such as chemotherapy. Severe instances of neuropathy can result in cessation of life-saving chemotherapy treatment. Results To support data representation and analysis of drug-associated neuropathy adverse events (AEs), we developed the Ontology of Drug Neuropathy Adverse Events (ODNAE). ODNAE extends the Ontology of Adverse Events (OAE). Our combinatorial approach identified 215 US FDA-licensed small molecule drugs that induce signs and symptoms of various types of neuropathy. ODNAE imports related drugs from the Drug Ontology (DrON) with their chemical ingredients defined in ChEBI. ODNAE includes 139 drug mechanisms of action from NDF-RT and 186 biological processes represented in the Gene Ontology (GO). In total ODNAE contains 1579 terms. Our analysis of the ODNAE knowledge base shows neuropathy-inducing drugs classified under specific molecular entity groups, especially carbon, pnictogen, chalcogen, and heterocyclic compounds. The carbon drug group includes 127 organic chemical drugs. Thirty nine receptor agonist and antagonist terms were identified, including 4 pairs (31 drugs) of agonists and antagonists that share targets (e.g., adrenergic receptor, dopamine, serotonin, and sex hormone receptor). Many drugs regulate neurological system processes (e.g., negative regulation of dopamine or serotonin uptake). SPARQL scripts were used to query the ODNAE ontology knowledge base. Conclusions ODNAE is an effective platform for building a drug-induced neuropathy knowledge base and for analyzing the underlying mechanisms of drug-induced neuropathy. The ODNAE-based methods used in this study can also be extended to the representation and study of other categories of adverse events.http://deepblue.lib.umich.edu/bitstream/2027.42/134596/1/13326_2016_Article_69.pd

Ganoderma Lucidum Polysaccharide Peptide Alleviates Hepatoteatosis via Modulating Bile Acid Metabolism Dependent on FXR-SHP/FGF

Background/Aims: Non-alcoholic fatty liver disease (NAFLD) encompasses a series of pathologic changes ranging from steatosis to steatohepatitis, which may progress to cirrhosis and hepatocellular carcinoma. The purpose of this study was to determine whether ganoderma lucidum polysaccharide peptide (GLPP) has therapeutic effect on NAFLD. Methods: Ob/ ob mouse model and ApoC3 transgenic mouse model were used for exploring the effect of GLPP on NAFLD. Key metabolic pathways and enzymes were identified by metabolomics combining with KEGG and PIUmet analyses and key enzymes were detected by Western blot. Hepatosteatosis models of HepG2 cells and primary hepatocytes were used to further confirm the therapeutic effect of GLPP on NAFLD. Results: GLPP administrated for a month alleviated hepatosteatosis, dyslipidemia, liver dysfunction and liver insulin resistance. Pathways of glycerophospholipid metabolism, fatty acid metabolism and primary bile acid biosynthesis were involved in the therapeutic effect of GLPP on NAFLD. Detection of key enzymes revealed that GLPP reversed low expression of CYP7A1, CYP8B1, FXR, SHP and high expression of FGFR4 in ob/ob mice and ApoC3 mice. Besides, GLPP inhibited fatty acid synthesis by reducing the expression of SREBP1c, FAS and ACC via a FXR-SHP dependent mechanism. Additionally, GLPP reduced the accumulation of lipid droplets and the content of TG in HepG2 cells and primary hepatocytes induced by oleic acid and palmitic acid. Conclusion: GLPP significantly improves NAFLD via regulating bile acid synthesis dependent on FXR-SHP/FGF pathway, which finally inhibits fatty acid synthesis, indicating that GLPP might be developed as a therapeutic drug for NAFLD

Consumption-based greenhouse gas emissions accounting with capital stock change highlights dynamics of fast-developing countries.

Traditional consumption-based greenhouse gas emissions accounting attributed the gap between consumption-based and production-based emissions to international trade. Yet few attempts have analyzed the temporal deviation between current emissions and future consumption, which can be explained through changes in capital stock. Here we develop a dynamic model to incorporate capital stock change in consumption-based accounting. The new model is applied using global data for 1995-2009. Our results show that global emissions embodied in consumption determined by the new model are smaller than those obtained from the traditional model. The emissions embodied in global capital stock increased steadily during the period. However, capital plays very different roles in shaping consumption-based emissions for economies with different development characteristics. As a result, the dynamic model yields similar consumption-based emissions estimation for many developed countries comparing with the traditional model, but it highlights the dynamics of fast-developing countries

Multimillijoule coherent terahertz bursts from picosecond laser-irradiated metal foils

Ultrahigh-power terahertz (THz) radiation sources are essential for many applications, for example, THz-wave-based compact accelerators and THz control over matter. However, to date none of the THz sources reported, whether based upon large-scale accelerators or high-power lasers, have produced THz pulses with energies above the millijoule (mJ) level. Here, we report a substantial increase in THz pulse energy, as high as tens of mJ, generated by a high-intensity, picosecond laser pulse irradiating a metal foil. A further up-scaling of THz energy by a factor of ∼4 is observed when introducing preplasmas at the target-rear side. Experimental measurements and theoretical models identify the dominant THz generation mechanism to be coherent transition radiation, induced by the laser-accelerated energetic electron bunch escaping the target. Observation of THz-field-induced carrier multiplication in high-resistivity silicon is presented as a proof-of-concept application demonstration. Such an extremely high THz energy not only triggers various nonlinear dynamics in matter, but also opens up the research era of relativistic THz optics

Profiling structured product labeling with NDF-RT and RxNorm

Abstract Background Structured Product Labeling (SPL) is a document markup standard approved by Health Level Seven (HL7) and adopted by United States Food and Drug Administration (FDA) as a mechanism for exchanging drug product information. The SPL drug labels contain rich information about FDA approved clinical drugs. However, the lack of linkage to standard drug ontologies hinders their meaningful use. NDF-RT (National Drug File Reference Terminology) and NLM RxNorm as standard drug ontology were used to standardize and profile the product labels. Methods In this paper, we present a framework that intends to map SPL drug labels with existing drug ontologies: NDF-RT and RxNorm. We also applied existing categorical annotations from the drug ontologies to classify SPL drug labels into corresponding classes. We established the classification and relevant linkage for SPL drug labels using the following three approaches. First, we retrieved NDF-RT categorical information from the External Pharmacologic Class (EPC) indexing SPLs. Second, we used the RxNorm and NDF-RT mappings to classify and link SPLs with NDF-RT categories. Third, we profiled SPLs using RxNorm term type information. In the implementation process, we employed a Semantic Web technology framework, in which we stored the data sets from NDF-RT and SPLs into a RDF triple store, and executed SPARQL queries to retrieve data from customized SPARQL endpoints. Meanwhile, we imported RxNorm data into MySQL relational database. Results In total, 96.0% SPL drug labels were mapped with NDF-RT categories whereas 97.0% SPL drug labels are linked to RxNorm codes. We found that the majority of SPL drug labels are mapped to chemical ingredient concepts in both drug ontologies whereas a relatively small portion of SPL drug labels are mapped to clinical drug concepts. Conclusions The profiling outcomes produced by this study would provide useful insights on meaningful use of FDA SPL drug labels in clinical applications through standard drug ontologies such as NDF-RT and RxNorm.</p