The 2020 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers’ meeting was held from January 13th to January 17th 2020 in Nyborg, Denmark. Among the participants were scientists as well as developers working in the field of computational mass spectrometry (MS) and proteomics. The 4-day program was split between introductory keynote lectures and parallel hackathon sessions. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts, and to actively contribute to highly relevant research projects. We successfully produced several new tools that will be useful to the proteomics community by improving data analysis as well as facilitating future research. All keynote recordings are available on https://doi.org/10.5281/zenodo.3890181.
Mountain and upland regions provide a wide range of ecosystem services to residents and visitors. While ecosystem research in mountain regions is on the rise, the linkages between sociocultural benefits and ecological systems remain little explored. Mountainous regions close to urban areas provide numerous benefits to a large number of individuals, suggesting a high social value, particularly for cultural ecosystem services. We explored and compared visitors' valuation of ecosystem services in the Pentland Hills, an upland range close to the city of Edinburgh, Scotland, and urban green spaces within Edinburgh. Based on 715 responses to user surveys in both study areas, we identified intense use and high social value for both areas. Several ecosystem services were perceived as equally important in both areas, including many cultural ecosystem services. Significant differences were revealed in the value of physically using nature, which Pentland Hills users rated more highly than those in the urban green spaces, and of mitigation of pollutants and carbon sequestration, for which the urban green spaces were valued more highly. Major differences were further identified for preferences in future land management, with nature-oriented management preferred by about 57% of the interviewees in the Pentland Hills, compared to 31% in the urban parks. The study highlights the substantial value of upland areas in close vicinity to a city for physically using and experiencing nature, with a strong acceptance of nature conservation.
Background and purpose: Although carbon monoxide (CO) can modulate inflammatory processes, the influence of CO on adhesion molecules is less clear. This might be due to the limited amount of CO generated by haem degradation. We therefore tested the ability of a CO releasing molecule (CORM-3), used in supra-physiological concentrations, to modulate the expression of vascular cell adhesion molecule (VCAM)-1 and E-selectin on endothelial cells and the mechanism(s) involved. Experimental approach: Human umbilical vein endothelial cells (HUVECs) were stimulated with tumour necrosis factor (TNF)-alpha in the presence or absence of CORM-3. The influence of CORM-3 on VCAM-1 and E- selectin expression and the nuclear factor (NF)-kappa B pathway was assessed by flow cytometry, Western blotting and electrophoretic mobility shift assay. Key results: CORM-3 inhibited the expression of VCAM-1 and E-selectin on TNF-alpha- stimulated HUVEC. VCAM-1 expression was also inhibited when CORM-3 was added 24 h after TNF-alpha stimulation or when TNF-alpha was removed. This was paralleled by deactivation of NF-kappa B and a reduction in VCAM-1 mRNA. Although TNF- alpha removal was more effective in this regard, VCAM-1 protein was down-regulated more rapidly when CORM-3 was added. CORM-3 induced haem oxygenase-1 (HO-1) in a dose- and time-dependent manner, mediated by the transcription factor, Nrf2. CORM-3 was still able to down-regulate VCAM-1 expression in HUVEC transfected with siRNA for HO-1 or Nrf2. Conclusions and implications: Down-regulation of VCAM and E-selectin expression induced by CORM-3 was independent of HO-1 up- regulation and was predominantly due to inhibition of sustained NF-kappa B activation.
Polyglycolide (PGA) is a biodegradable polymer with multiple applications in the medical sector. Here the synthesis of high molecular weight polyglycolide by ring-opening polymerization of diglycolide is reported. For the first time stabilizer free supercritical carbon dioxide (scCO(2)) was used as a reaction medium. scCO(2) allowed for a reduction in reaction temperature compared to conventional processes. Together with the lowering of monomer concentration and consequently reduced heat generation compared to bulk reactions thermal decomposition of the product occurring already during polymerization is strongly reduced. The reaction temperatures and pressures were varied between 120 and 150 degrees C and 145 to 1400 bar. Tin(II) ethyl hexanoate and 1-dodecanol were used as catalyst and initiator, respectively. The highest number average molecular weight of 31 200 g mol(-1) was obtained in 5 hours from polymerization at 120 degrees C and 530 bar. In all cases the products were obtained as a dry white powder. Remarkably, independent of molecular weight the melting temperatures were always at (219 +/- 2)degrees C.
Polyglycolide (PGA) is a biodegradable polymer with multiple applications in the medical sector. Here the synthesis of high molecular weight polyglycolide by ring-opening polymerization of diglycolide is reported. For the first time stabilizer free supercritical carbon dioxide (scCO2) was used as a reaction medium. scCO2 allowed for a reduction in reaction temperature compared to conventional processes. Together with the lowering of monomer concentration and consequently reduced heat generation compared to bulk reactions thermal decomposition of the product occurring already during polymerization is strongly reduced. The reaction temperatures and pressures were varied between 120 and 150 °C and 145 to 1400 bar. Tin(II) ethyl hexanoate and 1-dodecanol were used as catalyst and initiator, respectively. The highest number average molecular weight of 31 200 g mol−1 was obtained in 5 hours from polymerization at 120 °C and 530 bar. In all cases the products were obtained as a dry white powder. Remarkably, independent of molecular weight the melting temperatures were always at (219 ± 2) °C.
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Metabolic signatures of healthy lifestyle patterns and colorectal cancer risk in a European cohort
(2020)
BACKGROUND & AIMS: Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort.
METHODS: Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression.
RESULTS: Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants.
CONCLUSIONS: Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.
Understanding and accounting for the effect of exchange rate fluctuations on global learning rates
(2020)
Learning rates are a central concept in energy system models and integrated assessment models, as they allow researchers to project the future costs of new technologies and to optimize energy system costs. Here we argue that exchange rate fluctuations are an important, but thus far overlooked, determinant of the learning-rate variance observed in the literature. We explore how empirically observed global learning rates depend on where technologies are installed and which currency is used to calculate the learning rate. Using global data of large-scale photovoltaic (>= 5 MW) plants, we show that the currency choice can result in learning-rate differences of up to 16 percentage points. We then introduce an adjustment factor to correct for the effect of exchange rate and market focus fluctuations and discuss the implications of our findings for innovation scholars, energy modellers and decision makers. <br /> Learning rates are a measure of reduction in costs of energy from technologies such as solar photovoltaics. These are often estimated internationally with all monetary figures converted to a single currency, often US dollars. Lilliestam et al. show that such conversions can significantly affect the learning rate estimates.