Regional adaptation defines sensitivity to future ocean acidification

Physiological responses to temperature are known to be a major determinant of species distributions and can dictate the sensitivity of populations to global warming. In contrast, little is known about how other major global change drivers, such as ocean acidification (OA), will shape species distributions in the future. Here, by integrating population genetics with experimental data for growth and mineralization, physiology and metabolomics, we demonstrate that the sensitivity of populations of the gastropod Littorina littorea to future OA is shaped by regional adaptation. Individuals from populations towards the edges of the natural latitudinal range in the Northeast Atlantic exhibit greater shell dissolution and the inability to upregulate their metabolism when exposed to low pH, thus appearing most sensitive to low seawater pH. Our results suggest that future levels of OA could mediate temperature-driven shifts in species distributions, thereby influencing future biogeography and the functioning of marine ecosystems

Evidence for rangewide panmixia despite multiple barriers to dispersal in a marine mussel

Oceanographic features shape the distributional and genetic patterns of marine species by interrupting or promoting connections among populations. Although general patterns commonly arise, distributional ranges and genetic structure are species-specific and do not always comply with the expected trends. By applying a multimarker genetic approach combined with Lagrangian particle simulations (LPS) we tested the hypothesis that oceanographic features along northeastern Atlantic and Mediterranean shores influence dispersal potential and genetic structure of the intertidal mussel Perna perna. Additionally, by performing environmental niche modelling we assessed the potential and realized niche of P. perna along its entire native distributional range and the environmental factors that best explain its realized distribution. Perna perna showed evidence of panmixia across > 4,000 km despite several oceanographic breaking points detected by LPS. This is probably the result of a combination of life history traits, continuous habitat availability and stepping-stone dynamics. Moreover, the niche modelling framework depicted minimum sea surface temperatures (SST) as the major factor shaping P. perna distributional range limits along its native areas. Forthcoming warming SST is expected to further change these limits and allow the species to expand its range polewards though this may be accompanied by retreat from warmer areas.Fundacao para a Ciencia e Tecnologia (FCT-MEC, Portugal) [UID/Multi/04326/2013, IF/01413/2014/CP1217/CT0004]; South African Research Chairs Initiative (SARChI) of the Department of Science and Technology; National Research Foundation; South African National Research Foundation (NRF); Portuguese Fundacao para a Ciencia e Tecnologia (FCT) [SFRH/BPD/85040/2012, SFRH/BPD/111003/2015]info:eu-repo/semantics/publishedVersio

Saberes digitales: una aproximación desde las voces de los estudiantes

The second decade of the new century is about to end. In educational matters, it could be affirmed that many learning has left us the insertion of technologies in the classroom in these years, at all levels schoolchildren without exception. However, it could also be ensured that challenges in the short term arising from the current revolution social and technological, which on many occasions has left us without Enough spaces to reflect on its progress and implications It is interesting and challenging how the training processes in these last 20 years, when technologies of information and communications (ICT) have evolved step by step accelerated. Interesting, on the one hand, since one of the most important contributions important of the ICT is to act as large portals with access to the world, which both students, teachers and researchers open daily to understand the progress of their areas of knowledge and use tools that allow establishing better connectivity networks for the learning. Challenging, on the other hand, due to changes in paradigm that is being built around what has been understood for years regarding what the training process requires in terms of planning, didactic strategies, use of learning resources and the evaluation, to mention the main

Dynamic Predictive Modeling Under Measured and Unmeasured Continuous-Time Stochastic Input Behavior

Many input variables of chemical processes have a continuous-time stochastic (CTS) behavior. The nature of these variables is a persistent, time-correlated variation that manifests as process variation as the variables deviate in time from their nominal levels. This work introduces methodologies in process identification for improving the modeling of process outputs by exploiting CTS input modeling under cases where the input is measured and unmeasured. In the measured input case, the output variable is measured offline, infrequently, and at a varying sampling rate. A method is proposed for estimating CTS parameters from the measured input by exploiting statistical properties of its CTS model. The proposed approach is evaluated based on both output accuracy and predictive ability several steps ahead of the current input measurement. Two parameter estimation techniques are proposed when the input is unmeasured. The first is a derivative-free approach that uses sample moments and analytical expressions for population moments to estimate the CTS model parameters. The second exploits the CTS input model and uses the analytical solution of the dynamic model to estimate these parameters. The predictive ability of the latter approach is evaluated in the same way as the measured input case. All of the data in this work were artificially generated under the probabilistic CTS model.Reprinted (adapted) with permission from Industrial and Engineering Chemistry Research 51 (2012): 5469, doi: 10.1021/ie201998b. Copyright 2012 American Chemical Society.</p

Assessing adherence to current national guidelines for appropriate albumin use at an academic medical center

Objective: To assess adherence to current national guidelines for appropriate albumin use at an academic medical center. Methods: This retrospective chart review of 150 randomly selected patients prescribed and administered at least one dose of albumin was conducted in an urban academic medical center to evaluate the adherence of albumin orders to current national guidelines. Inclusion criteria consisted of discharged patients at least 18-years-old admitted to the intensive care unit or medical/surgical unit from September 1, 2015 to August 31, 2016. The primary outcome was the number of patients who inappropriately received albumin based on national guidelines and FDA approved indications. Secondary outcomes included the number of patients who received the incorrect concentration or dose of albumin based on indication, as well as the cost associated with inappropriate albumin prescribing. Descriptive statistics were used to report outcomes. Results: There were 68 instances (45%) where albumin was prescribed inappropriately according to guideline recommendations. Of the 82 instances where albumin was used appropriately, 18 patients received an incorrect dose (22%), and 6 received the inappropriate concentration of albumin (7%). The cost for the 150 patients included in the study associated with inappropriate albumin prescribing was approximately $13,000. Conclusions: This study identified areas for pharmacist intervention to ensure appropriate albumin utilization, as well as proper dosing for the most frequently incorrectly dosed indications, including hepato-renal syndrome, spontaneous bacterial peritonitis, and paracentesis. This study also identified an unexpected indication with significant inappropriate albumin utilization, perioperative hypotension, which is an area for further intervention to monitor and decrease use