Automatic Filtering and Substantiation of Drug Safety Signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18–49, 50–69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population

Dislocation-based finite element modelling of hydrogen embrittlement in steel alloys

Mechanical properties of many metals are greatly influenced by hydrogen solutes causing a well-known phenomenon of Hydrogen Embrittlement (HE). Hydrogen atoms affect the dislocation core, materials cohesion, and/or vacancies clustering causing the material capacity for plastic deformation to decrease. Such degradation in performance of metals leads to embrittlement resulting of catastrophic failure in structures. In this research, a physically-based constitutive model is developed to study hydrogen embrittlement in steel alloys. The developed model is an extension for Ghoniem-Matthews-Amodeo (GMA) dislocation-based model in order to predict the constitutive relation in the plastic regime for high strength steel alloys while considering hydrogen Effect on plasticity. The proposed physically-based dislocation-density model include the effect of hydrogen solute on dislocation mobility and interaction. The proposed model study the mechanical behavior of high-strength steel of HT-9 tensile test specimen. © The Minerals, Metals Materials Society 2018

Biodistribution Studies of Nanoparticles Using Fluorescence Imaging: A Qualitative or Quantitative Method?

PURPOSE: The biodistribution of Lipid/Calcium/Phosphate (LCP) nanoparticles (NPs) in tumor-bearing mice was investigated using fluorescence imaging. A quantitative validation of this method was done by (3)H and (111)In labeling of the nanoparticles. METHODS: The biodistribution of LCP NPs containing oligonucleotides was investigated using three different probes: Texas-Red labeled oligonucleotides, (3)H-labeled oligonucleotides, and (111)In-labled calcium phosphate. RESULTS: A discrepancy was found between the radioactivity and the fluorescence signals. Signals from (3)H and (111)In exhibited very similar distribution patterns, suggesting that liver and spleen were the major accumulation sites. However, fluorescence imaging indicated that tumor accumulation was predominant. We further confirmed that the fluorescence signals in both liver and spleen were greatly attenuated compared with those in the tumor due to the intrinsic tissue absorption and scattering. Near-infrared (NIR) dye Cy5.5 also suffered from the same problem, in that the quantitative data from whole organs was dramatically affected by absorption and scattering properties of the tissue. CONCLUSIONS: Careful attention must be paid to the quantification and interpretation of fluorescence imaging measurements when comparing different tissues

RNA Nanotechnology

Cite this entry as: Yaradoddi J.S. et al. (2019) RNA Nanotechnology. In: Martínez L., Kharissova O., Kharisov B. (eds) Handbook of Ecomaterials. Springer, Cham Publisher Name: Springer, Cham DOI: https://doi.org/10.1007/978-3-319-68255-6_193 Print ISBN: 978-3-319-68254-9 Online ISBN: 978-3-319-68255-6 First Online: 14 February 2019DNA, RNA, and proteins are seemed to be immensely substantial tools for nanobiotechnological applications; this is since their exceptional biochemical properties and role. Particularly RNA is categorized over comparatively high-temperature stability, varied organizational pliability, and their performance in natural circumstances. Above properties made, RNA, a valued constituent for bionanotechnology processes and usefulness, especially RNA nanotechnology, could synthesize complex molecules using simple molecules through de nova nanostructures having exceptional utility by the strategy, integration, and manipulations of most predominant processes which are usually based on different RNA structures and because of their vital biochemical properties. The current chapter emphasis on the basic principles inspires the normal design of RNA nanostructures, pronounces the important methods that are used in constructing nanoparticles’ self-assemblages, and further describes the associated challenges and excelled opportunities of RNA nanotechnology in near future.Peer reviewe

Biological substantiation of antipsychotic-associated pneumonia: Systematic literature review and computational analyses

INTRODUCTION: Antipsychotic (AP) safety has been widely investigated. However, mechanisms underlying AP-associated pneumonia are not well-defined. AIM: The aim of this study was to investigate the known mechanisms of AP-associated pneumonia through a systematic literature review, confirm these mechanisms using an independent data source on drug targets and attempt to identify novel AP drug targets potentially linked to pneumonia. METHODS: A search was conducted in Medline and Web of Science to identify studies exploring the association between pneumonia and antipsychotic use, from which information on hypothesized mechanism of action was extracted. All studies had to be in English and had to concern AP use as an intervention in persons of any age and for any indication, provided that the outcome was pneumonia. Information on the study design, population, exposure, outcome, risk estimate and mechanism of action was tabulated. Public repositories of pharmacology and drug safety data were used to identify the receptor binding profile and AP safety events. Cytoscape was then used to map biological pathways that could link AP targets and off-targets to pneumonia. RESULTS: The literature search yielded 200 articles; 41 were included in the review. Thirty studies reported a hypothesized mechanism of action, most commonly activation/inhibition of cholinergic, histaminergic and dopaminergic receptors. In vitro pharmacology data confirmed receptor affinities identified in the literature review. Two targets, thromboxane A2 receptor (TBXA2R) and platelet activating factor receptor (PTAFR) were found to be novel AP target receptors potentially associated with pneumonia. Biological pathways constructed using Cytoscape identified plausible biological links potentially leading to pneumonia downstream of TBXA2R and PTAFR. CONCLUSION: Innovative approaches for biological substantiation of drug-adverse event associations may strengthen evidence on drug safety profiles and help to tailor pharmacological therapies to patient risk factors