Metabolite profiling of Dioscorea (yam) species reveals underutilised biodiversity and renewable sources for high-value compounds

Yams (Dioscorea spp.) are a multispecies crop with production in over 50 countries generating ~50 MT of edible tubers annually. The long-term storage potential of these tubers is vital for food security in developing countries. Furthermore, many species are important sources of pharmaceutical precursors. Despite these attributes as staple food crops and sources of high-value chemicals, Dioscorea spp. remain largely neglected in comparison to other staple tuber crops of tropical agricultural systems such as cassava (Manihot esculenta) and sweet potato (Ipomoea batatas). To date, studies have focussed on the tubers or rhizomes of Dioscorea, neglecting the foliage as waste. In the present study metabolite profiling procedures, using GC-MS approaches, have been established to assess biochemical diversity across species. The robustness of the procedures was shown using material from the phylogenetic clades. The resultant data allowed separation of the genotypes into clades, species and morphological traits with a putative geographical origin. Additionally, we show the potential of foliage material as a renewable source of high-value compounds

Modeling gas turbine materials’ hot corrosion degradation in combustion environments from H2‐rich syngas

Components of gas turbines (such as blades, vanes, combustor cans) exposed to combustion environments at high temperature are susceptible to hot corrosion attack. To successfully plan maintenance and to determine whether to operate in novel combustion modes (e.g., in integrated gasification combined cycles that incorporate pre-combustion carbon capture) predictions of hot corrosion component life must be made. In this paper, hot corrosion datasets relating to two alloys, MarM 509 (a cobalt-based superalloy), and Rene 80 (a nickel-based superalloy) form the basis of hot corrosion predictive lifetime models. The model framework is based on the two stages of incubation and propagation, with the transitions from incubation to propagation around the samples being based on Weibull statistics. The impact of a range of temperatures (including 700 and 900 °C), gas compositions (simulating the combustion of natural gas, H2-rich syngas, or partially cleaned syngas), and deposit chemistries/fluxes have been assessed. Predictions have been made including the expected damage spread for a range of different exposure conditions

A randomised, double-blind, placebo-controlled trial of repeated nebulisation of non-viral cystic fibrosis transmembrane conductance regulator (CFTR) gene therapy in patients with cystic fibrosis

BACKGROUND: Cystic fibrosis (CF) is a chronic, life-limiting disease caused by mutations in the CF transmembrane conductance regulator (CFTR) gene leading to abnormal airway surface ion transport, chronic lung infections, inflammation and eventual respiratory failure. With the exception of the small-molecule potentiator, ivacaftor (Kalydeco®, Vertex Pharmaceuticals, Boston, MA, USA), which is suitable for a small proportion of patients, there are no licensed therapies targeting the basic defect. The UK Cystic Fibrosis Gene Therapy Consortium has taken a cationic lipid-mediated CFTR gene therapy formulation through preclinical and clinical development. OBJECTIVE: To determine clinical efficacy of the formulation delivered to the airways over a period of 1 year in patients with CF. DESIGN: This was a randomised, double-blind, placebo-controlled Phase IIb trial of the CFTR gene–liposome complex pGM169/GL67A. Randomisation was performed via InForm™ version 4.6 (Phase Forward Incorporated, Oracle, CA, USA) and was 1 : 1, except for patients in the mechanistic subgroups (2 : 1). Allocation was blinded by masking nebuliser chambers. SETTINGS: Data were collected in the clinical and scientific sites and entered onto a trial-specific InForm, version 4.6 database. PARTICIPANTS: Patients with CF aged ≥ 12 years with forced expiratory volume in the first second (FEV1) between 50% and 90% predicted and any combination of CFTR mutations. The per-protocol group (≥ 9 doses) consisted of 54 patients receiving placebo (62 randomised) and 62 patients receiving gene therapy (78 randomised). INTERVENTIONS: Subjects received 5 ml of nebulised pGM169/G67A (active) or 0.9% saline (placebo) at 28 (±5)-day intervals over 1 year. MAIN OUTCOME MEASURES: The primary end point was the relative change in percentage predicted FEV1 over the 12-month period. A number of secondary clinical outcomes were assessed alongside safety measures: other spirometric values; lung clearance index (LCI) assessed by multibreath washout; structural disease on computed tomography (CT) scan; the Cystic Fibrosis Questionnaire – Revised (CFQ-R), a validated quality-of-life questionnaire; exercise capacity and monitoring; systemic and sputum inflammatory markers; and adverse events (AEs). A mechanistic study was performed in a subgroup in whom transgene deoxyribonucleic acid (DNA) and messenger ribonucleic acid (mRNA) was measured alongside nasal and lower airway potential difference. RESULTS: There was a significant (p = 0.046) treatment effect (TE) of 3.7% [95% confidence interval (CI) 0.1% to 7.3%] in the primary end point at 12 months and in secondary end points, including forced vital capacity (FVC) (p = 0.031) and CT gas trapping (p = 0.048). Other outcomes, although not reaching statistical significance, favoured active treatment. Effects were noted by 1 month and were irrespective of sex, age or CFTR mutation class. Subjects with a more severe baseline FEV1 had a FEV1 TE of 6.4% (95% CI 0.8% to 12.1%) and greater changes in many other secondary outcomes. However, the more mildly affected group also demonstrated benefits, particularly in small airway disease markers such as LCI. The active group showed a significantly (p = 0.032) greater bronchial chloride secretory response. No difference in treatment-attributable AEs was seen between the placebo and active groups. CONCLUSIONS: Monthly application of the pGM169/GL67A gene therapy formulation was associated with an improvement in lung function, other clinically relevant parameters and bronchial CFTR function, compared with placebo. LIMITATIONS: Although encouraging, the improvement in FEV1 was modest and was not accompanied by detectable improvement in patients’ quality of life. FUTURE WORK: Future work will focus on attempts to increase efficacy by increasing dose or frequency, the coadministration of a CFTR potentiator, or the use of modified viral vectors capable of repeated administration. TRIAL REGISTRATION: ClinicalTrials.gov NCT01621867

A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury

In preclinical stages of drug development, anticipating potential adverse drug effects such as toxicity is an important issue for both saving resources and preventing public health risks. Current in vitro cytotoxicity tests are restricted by their predictive potential and their ability to provide mechanistic information. This study aimed to develop a metabolomic mass spectrometry-based approach for the detection and classification of drug-induced hepatotoxicity. To this end, the metabolite profiles of human derived hepatic cells (i.e., HepG2) exposed to different well-known hepatotoxic compounds acting through different mechanisms (i.e., oxidative stress, steatosis, phospholipidosis, and controls) were compared by multivariate data analysis, thus allowing us to decipher both common and mechanism-specific altered biochemical pathways. Briefly, oxidative stress damage markers were found in the three mechanisms, mainly showing altered levels of metabolites associated with glutathione and γ-glutamyl cycle. Phospholipidosis was characterized by a decreased lysophospholipids to phospholipids ratio, suggestive of phospholipid degradation inhibition. Whereas, steatosis led to impaired fatty acids β-oxidation and a subsequent increase in triacylglycerides synthesis. The characteristic metabolomic profiles were used to develop a predictive model aimed not only to discriminate between non-toxic and hepatotoxic drugs, but also to propose potential drug toxicity mechanism(s)

Radiogenic and muon-induced backgrounds in the LUX dark matter detector

The Large Underground Xenon (LUX) dark matter experiment aims to detect rare low-energy interactions from Weakly Interacting Massive Particles (WIMPs). The radiogenic backgrounds in the LUX detector have been measured and compared with Monte Carlo simulation. Measurements of LUX high-energy data have provided direct constraints on all background sources contributing to the background model. The expected background rate from the background model for the 85.3 day WIMP search run is (2.6±0.2stat±0.4sys)×10-3 events keVee-1kg-1day-1 in a 118 kg fiducial volume. The observed background rate is (3.6±0.4stat)×10-3 events keVee-1kg-1day-1 , consistent with model projections. The expectation for the radiogenic background in a subsequent one-year run is presented

Identification of Radiopure Titanium for the LZ Dark Matter Experiment and Future Rare Event Searches

The LUX-ZEPLIN (LZ) experiment will search for dark matter particle interactions with a detector containing a total of 10 tonnes of liquid xenon within a double-vessel cryostat. The large mass and proximity of the cryostat to the active detector volume demand the use of material with extremely low intrinsic radioactivity. We report on the radioassay campaign conducted to identify suitable metals, the determination of factors limiting radiopure production, and the selection of titanium for construction of the LZ cryostat and other detector components. This titanium has been measured with activities of $^{238}$U$_{e}$~$<$1.6~mBq/kg, $^{238}$U$_{l}$~$<$0.09~mBq/kg, $^{232}$Th$_{e}$~$=0.28\pm 0.03$~mBq/kg, $^{232}$Th$_{l}$~$=0.25\pm 0.02$~mBq/kg, $^{40}$K~$<$0.54~mBq/kg, and $^{60}$Co~$<$0.02~mBq/kg (68\% CL). Such low intrinsic activities, which are some of the lowest ever reported for titanium, enable its use for future dark matter and other rare event searches. Monte Carlo simulations have been performed to assess the expected background contribution from the LZ cryostat with this radioactivity. In 1,000 days of WIMP search exposure of a 5.6-tonne fiducial mass, the cryostat will contribute only a mean background of $0.160\pm0.001$(stat)$\pm0.030$(sys) counts

Provenancing Archaeological Wool Textiles from Medieval Northern Europe by Light Stable Isotope Analysis (δ13C, δ15N, δ2H)

We investigate the origin of archaeological wool textiles preserved by anoxic waterlogging from seven medieval archaeological deposits in north-western Europe (c. 700-1600 AD), using geospatial patterning in carbon (δ13C), nitrogen (δ15N) and non-exchangeable hydrogen (δ2H) composition of modern and ancient sheep proteins. δ13C, δ15N and δ2H values from archaeological wool keratin (n = 83) and bone collagen (n = 59) from four sites were interpreted with reference to the composition of modern sheep wool from the same regions. The isotopic composition of wool and bone collagen samples clustered strongly by settlement; inter-regional relationships were largely parallel in modern and ancient samples, though landscape change was also significant. Degradation in archaeological wool samples, examined by elemental and amino acid composition, was greater in samples from Iceland (Reykholt) than in samples from north-east England (York, Newcastle) or northern Germany (Hessens). A nominal assignment approach was used to classify textiles into local/non-local at each site, based on maximal estimates of isotopic variability in modern sheep wool. Light element stable isotope analysis provided new insights into the origins of wool textiles, and demonstrates that isotopic provenancing of keratin preserved in anoxic waterlogged contexts is feasible. We also demonstrate the utility of δ2H analysis to understand the location of origin of archaeological protein samples

MetaboSearch: Tool for Mass-Based Metabolite Identification Using Multiple Databases

Searching metabolites against databases according to their masses is often the first step in metabolite identification for a mass spectrometry-based untargeted metabolomics study. Major metabolite databases include Human Metabolome DataBase (HMDB), Madison Metabolomics Consortium Database (MMCD), Metlin, and LIPID MAPS. Since each one of these databases covers only a fraction of the metabolome, integration of the search results from these databases is expected to yield a more comprehensive coverage. However, the manual combination of multiple search results is generally difficult when identification of hundreds of metabolites is desired. We have implemented a web-based software tool that enables simultaneous mass-based search against the four major databases, and the integration of the results. In addition, more complete chemical identifier information for the metabolites is retrieved by cross-referencing multiple databases. The search results are merged based on IUPAC International Chemical Identifier (InChI) keys. Besides a simple list of m/z values, the software can accept the ion annotation information as input for enhanced metabolite identification. The performance of the software is demonstrated on mass spectrometry data acquired in both positive and negative ionization modes. Compared with search results from individual databases, MetaboSearch provides better coverage of the metabolome and more complete chemical identifier information. Availability: The software tool is available at http://omics.georgetown.edu/MetaboSearch.html

LUX-ZEPLIN (LZ) Technical Design Report

In this Technical Design Report (TDR) we describe the LZ detector to be built at the Sanford Underground Research Facility (SURF). The LZ dark matter experiment is designed to achieve sensitivity to a WIMP-nucleon spin-independent cross section of three times ten to the negative forty-eighth square centimeters

From differentiating metabolites to biomarkers

The current developments in metabolomics and metabolic profiling technologies have led to the discovery of several new metabolic biomarkers. Finding metabolites present in significantly different levels between sample sets, however, does not necessarily make these metabolites useful biomarkers. The route to valid and applicable biomarkers (biomarker qualification) is long and demands a significant amount of work. In this overview, we critically discuss the current state-of-the-art of metabolic biomarker discovery, with highlights and shortcomings, and suggest a pathway to clinical usefulness