Global warming will affect the maximum potential abundance of boreal plant species

Forecasting the impact of future global warming on biodiversity requires understanding how temperature limits the distribution of species. Here we rely on Liebig's Law of Minimum to estimate the effect of temperature on the maximum potential abundance that a species can attain at a certain location. We develop 95%‐quantile regressions to model the influence of effective temperature sum on the maximum potential abundance of 25 common understory plant species of Finland, along 868 nationwide plots sampled in 1985. Fifteen of these species showed a significant response to temperature sum that was consistent in temperature‐only models and in all‐predictors models, which also included cumulative precipitation, soil texture, soil fertility, tree species and stand maturity as predictors. For species with significant and consistent responses to temperature, we forecasted potential shifts in abundance for the period 2041–2070 under the IPCC A1B emission scenario using temperature‐only models. We predict major potential changes in abundance and average northward distribution shifts of 6–8 km yr−1. Our results emphasize inter‐specific differences in the impact of global warming on the understory layer of boreal forests. Species in all functional groups from dwarf shrubs, herbs and grasses to bryophytes and lichens showed significant responses to temperature, while temperature did not limit the abundance of 10 species. We discuss the interest of modelling the ‘maximum potential abundance’ to deal with the uncertainty in the predictions of realized abundances associated to the effect of environmental factors not accounted for and to dispersal limitations of species, among others. We believe this concept has a promising and unexplored potential to forecast the impact of specific drivers of global change under future scenarios.202

Expression of Trichoderma reesei cellulases CBHI and EGI in Ashbya gossypii

To explore the potential of Ashbya gossypii as a host for the expression of recombinant proteins and to assess whether protein secretion would be more similar to the closely related Saccharomyces cerevisiae or to other filamentous fungi, endoglucanase I (EGI) and cellobiohydrolase I (CBHI) from the fungus Trichoderma reesei were successfully expressed in A. gossypii from plasmids containing the two micron sequences from S. cerevisiae, under the S. cerevisiae PGK1 promoter. The native signal sequences of EGI and CBHI were able to direct the secretion of EGI and CBHI into the culture medium in A. gossypii. Although CBHI activity was not detected using 4- methylumbelliferyl-β-D-lactoside as substrate, the protein was detected by Western blot using monoclonal antibodies. EGI activity was detectable, the specific activity being comparable to that produced by a similar EGI producing S. cerevisiae construct. More EGI was secreted than CBHI, or more active protein was produced. Partial characterization of CBHI and EGI expressed in A. gossypii revealed overglycosylation when compared with the native T. reesei proteins, but the glycosylation was less extensive than on cellulases expressed in S. cerevisiae.Fundação para a Ciência e a Tecnologia (FCT

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

The case for an international severity of illness scoring system

Severity of illness scores in the critical care context have evolved to serve multiple functions. These scores enable risk-adjusted outcomes to be benchmarked for the assessment of intensive care unit (ICU) performance, inform resource allocation, and enable the characterization of disease severity. Numerous illness severity scores have been developed to optimize calibration at the national level, but few studies have examined the international application of such scores.() The COVID-19 pandemic demonstrated the value of benchmarking outcomes across heterogeneous populations and across various health care systems. Severity of illness scores were widely used to describe trial populations, assess treatment effects and evaluate the quality of care during the pandemic. Similar use cases apply to other priorities for international critical care research and quality improvement, such as improving outcomes following traumatic injuries and expanding access to complex medical, surgical and obstetric care.(,) Therefore, this article argues that the development of an international illness severity score is an urgent priority for critical care research

Neurofilament light compared to neuron-specific enolase as a predictor of unfavourable outcome after out-of-hospital cardiac arrest

Aim: We compared the prognostic abilities of neurofilament light (NfL) and neuron-specific enolase (NSE) in patients resuscitated from out-ofhospital cardiac arrest (OHCA) of various aetiologies. Methods: We analysed frozen blood samples obtained at 24 and 48 hours from OHCA patients treated in 21 Finnish intensive care units in 2010 and 2011. We defined unfavourable outcome as Cerebral Performance Category (CPC) 3-5 at 12 months after OHCA. We evaluated the prognostic ability of the biomarkers by calculating the area under the receiver operating characteristic curves (AUROCs [95% confidence intervals]) and compared these with a bootstrap method. Results: Out of 248 adult patients, 12-month outcome was unfavourable in 120 (48.4%). The median (interquartile range) NfL concentrations for patients with unfavourable and those with favourable outcome, respectively, were 689 (146-1804) pg/mL vs. 31 (17-61) pg/mL at 24 h and 1162 (147-4360) pg/mL vs. 36 (21-87) pg/mL at 48 h, p < 0.001 for both. The corresponding NSE concentrations were 13.3 (7.2-27.3) mg/L vs. 8.5 (5.8- 13.2) mg/L at 24 h and 20.4 (8.1-56.6) mg/L vs. 8.2 (5.9-12.1) mg/L at 48 h, p < 0.001 for both. The AUROCs to predict an unfavourable outcome were 0.90 (0.86-0.94) for NfL vs. 0.65 (0.58-0.72) for NSE at 24 h, p < 0.001 and 0.88 (0.83-0.93) for NfL and 0.73 (0.66-0.81) for NSE at 48 h, p < 0.001. Conclusion: Compared to NSE, NfL demonstrated superior accuracy in predicting long-term unfavourable outcome after OHCA.Peer reviewe