The role of measuring exhaled breath biomarkers in sarcoidosis: A systematic review

Introduction: Sarcoidosis is a chronic granulomatous disease of unknown aetiology with a variable clinical course and prognosis. There is a growing need to identify non-invasive biomarkers to differentiate between clinical phenotypes, identify those at risk of disease progression and monitor response to treatment. Objectives: We undertook a systematic review and meta-analysis, to evaluate the utility of breath-based biomarkers in discriminating sarcoidosis from healthy controls, alongside correlation with existing non-breath based biomarkers used in clinical practice, radiological stage, markers of disease activity and response to treatment. Methods: Electronic searches were undertaken during November 2017 using PubMed, Ebsco, Embase and Web of Science to capture relevant studies evaluating breath-based biomarkers in adult patients with sarcoidosis. Results: 353 papers were screened; 21 met the inclusion criteria and assessed 25 different biomarkers alongside VOCs in exhaled breath gas or condensate. Considerable heterogeneity existed amongst the studies in terms of participant characteristics, sampling and analytical methods. Elevated biomarkers in sarcoidosis included 8-isoprostane, carbon monoxide, neopterin, TGF-β1, TNFα, CysLT and several metallic elements including chromium, silicon and nickel. Three studies exploring VOCs were able to distinguish sarcoidosis from controls. Meta-analysis of four studies assessing alveolar nitric oxide showed no significant difference between sarcoidosis and healthy controls (2.22ppb; 95% CI -0.83, 5.27) however, a high degree of heterogeneity was observed with an I2 of 93.4% (p<0.001). Inconsistent or statistically insignificant results were observed for correlations between several biomarkers and radiological stage, markers of disease activity or treatment. Conclusions: The evidence for using breath biomarkers to diagnose and monitor sarcoidosis remains inconclusive with many studies limited by small sample sizes and lack of standardisation. VOCs have shown promising potential but further research is required to evaluate their prognostic role

FAIR-compliant clinical, radiomics and DICOM metadata of RIDER, interobserver, Lung1 and head-Neck1 TCIA collections

Purpose: One of the most frequently cited radiomics investigations showed that features automatically extracted from routine clinical images could be used in prognostic modeling. These images have been made publicly accessible via The Cancer Imaging Archive (TCIA). There have been numerous requests for additional explanatory metadata on the following datasets — RIDER, Interobserver, Lung1, and Head–Neck1. To support repeatability, reproducibility, generalizability, and transparency in radiomics research, we publish the subjects’ clinical data, extracted radiomics features, and digital imaging and communications in medicine (DICOM) headers of these four datasets with descriptive metadata, in order to be more compliant with findable, accessible, interoperable, and reusable (FAIR) data management principles. Acquisition and validation methods: Overall survival time intervals were updated using a national citizens registry after internal ethics board approval. Spatial offsets of the primary gross tumor volume (GTV) regions of interest (ROIs) associated with the Lung1 CT series were improved on the TCIA. GTV radiomics features were extracted using the open-source Ontology-Guided Radiomics Analysis Workflow (O-RAW). We reshaped the output of O-RAW to map features and extraction settings to the latest version of Radiomics Ontology, so as to be consistent with the Image Biomarker Standardization Initiative (IBSI). Digital imaging and communications in medicine metadata was extracted using a research version of Semantic DICOM (SOHARD, GmbH, Fuerth; Germany). Subjects’ clinical data were described with metadata using the Radiation Oncology Ontology. All of the above were published in Resource Descriptor Format (RDF), that is, triples. Example SPARQL queries are shared with the reader to use on the online triples archive, which are intended to illustrate how to exploit this data submission. Data format: The accumulated RDF data are publicly accessible through a SPARQL endpoint where the triples are archived. The endpoint is remotely queried through a graph database web application at http://sparql.cancerdata.org. SPARQL queries are intrinsically federated, such that we can efficiently cross-reference clinical, DICOM, and radiomics data within a single query, while being agnostic to the original data format and coding system. The feder

Enhancement of toxin- and virus-neutralizing capacity of single-domain antibody fragments by N-glycosylation

Single-domain antibody fragments (VHHs) have several beneficial properties as compared to conventional antibody fragments. However, their small size complicates their toxin- and virus-neutralizing capacity. We isolated 27 VHHs binding Escherichia coli heat-labile toxin and expressed these in Saccharomyces cerevisiae. The most potent neutralizing VHH (LT109) was N-glycosylated, resulting in a large increase in molecular mass. This suggests that N-glycosylation of LT109 improves its neutralizing capacity. Indeed, deglycosylation of LT109 decreased its neutralizing capacity three- to fivefold. We also studied the effect of glycosylation of two previously isolated VHHs on their ability to neutralize foot-and-mouth disease virus. For this purpose, these VHHs that lacked potential N-glycosylation sites were genetically fused to another VHH that was known to be glycosylated. The resulting fusion proteins were also N-glycosylated. They neutralized the virus at at least fourfold-lower VHH concentrations as compared to the single, non-glycosylated VHHs and at at least 50-fold-lower VHH concentrations as compared to their deglycosylated counterparts. Thus, we have shown that N-glycosylation of VHHs contributes to toxin- and virus-neutralizing capacity

Automated ARGET ATRP Accelerates Catalyst Optimization for the Synthesis of Thiol-Functionalized Polymers

Conventional synthesis of polymers by ATRP is relatively low throughput, involving iterative optimization of conditions in an inert atmosphere. Automated, high-throughput controlled radical polymerization was developed to accelerate catalyst optimization and production of disulfide-functionalized polymers without the need of an inert gas. Using ARGET ATRP, polymerization conditions were rapidly identified for eight different monomers, including the first ARGET ATRP of 2-(diethylamino)ethyl methacrylate and di(ethylene glycol) methyl ether methacrylate. In addition, butyl acrylate, oligo(ethylene glycol) methacrylate 300 and 475, 2-(dimethylamino)ethyl methacrylate, styrene, and methyl methacrylate were polymerized using bis(2-hydroxyethyl) disulfide bis(2-bromo-2-methylpropionate) as the initiator, tris(2-pyridylmethyl)amine as the ligand, and tin(II) 2-ethylhexanoate as the reducing agent. The catalyst and reducing agent concentration was optimized specifically for each monomer, and then a library of polymers was synthesized systematically using the optimized conditions. The disulfide-functionalized chains could be cleaved to two thiol-terminated chains upon exposure to dithiothreitol, which may have utility for the synthesis of polymer bioconjugates. Finally, we demonstrated that these new conditions translated perfectly to conventional batch polymerization. We believe the methods developed here may prove generally useful to accelerate the systematic optimization of a variety of chemical reactions and polymerizations.National Institutes of Health (U.S.) (Ruth L. Kirschstein National Research Service Award (Individual Postdoctoral Fellows)National Institutes of Health (U.S.) (Award F32EB011867)Alnylam Pharmaceuticals (Firm)Johannes Gutenberg-Universität (Graduate School of Excellence Materials Science in Mainz (MAINZ))Studienstiftung des Deutschen Volke