Explore the vast range of titles available.

Acute kidney injury (AKI) is a life-threatening complication of severe rhabdomyolysis. This study was conducted to assess risk factors for AKI and to develop a risk score for early prediction. Retrospective observational cohort study with a 9-year follow-up, carried out in an acute-care teaching-affiliated hospital. A total of 126 patients with severe rhabdomyolysis defined as serum creatine kinase (CK) > 5,000 IU/L fulfilled the inclusion criteria. Univariate and logistic regression analyses were performed to determine risk factors for AKI. Based on the values obtained for each variable, a risk score and prognostic probabilities were estimated to establish the risk for developing AKI. The incidence of AKI was 58%. Death during hospitalization was significantly higher among patients with AKI, compared to patients without AKI (19.2% vs 3.6%, p = 0.008). The following variables were independently associated with AKI: peak CK (odds ratio [OR] 4.9, 95%CI 1.4-16.8), hypoalbuminemia (< 33 mg/dL, [OR 5.1, 95%CI 1.4-17-7]), metabolic acidosis (OR 5.3, 95%CI 1.4-20.3), and decreased prothrombin time (OR 4.4, 95% CI 1.3-14.5). A risk score for AKI was calculated for each patient, with an OR of 1.72 (95%CI 1.45-2.04). The discrimination value of the predictive model was established by means of a ROC curve, with the area under the curve of 0.871 (p<0.001). The identification of independent factors associated with AKI and a risk score for early prediction of this complication in patients with severe rhabdomyolysis may be useful in clinical practice, particularly to implement early preventive measures.

We demonstrate the utility of using the equivalent bottom roughness for calculating the friction factor and the drag coefficient of a seagrass meadow for conditions in which the meadow height is small compared to the water depth. Wave attenuation induced by the seagrassPosidonia oceanicais evaluated using field data from bottom-mounted acoustic doppler velocimeters (ADVs). Using the data from one storm event, the equivalent bottom roughness is calculated for the meadow ask s~ 0.40 m. This equivalent roughness is used to predict the wave friction factorƒ w, the drag coefficient on the plant,C D, and ultimately the wave attenuation for other storms. Root mean squared wave height (H rms) is reduced by around 50% for incident waves of 1.1 m propagating over ~ 1000 m of a meadow ofP. oceanicawith shoot density of ~600 shoots m−2.

Waves and currents influence not only the spatial distribution of seagrass meadows but also the transport, establishment and survivorship of seagrass propagules and hence the success of seagrass recruitment from sexual reproduction. We quantified the dispersal of propagules of 3 seagrass species (Posidonia oceanica, Cymodocea nodosa and Zostera marina) over substrata of different complexities (sand, coarse gravel and P. oceanica mattes of different shoot abundances) under unidirectional flow in a hydraulic flume. Threshold velocities indicate that Z. marina seeds start to move earlier over a flat sandy bottom (14 cm s−1) than seeds of P. oceanica (20 cm s−1) and C. nodosa (21 cm s−1). Propagule trapping increased with bottom complexity, which was related to the flow reduction that each substratum generated and the boundary layer thickness. Trapping rates were higher in coarse gravel and in mattes with higher abundances of dead shoots, where flow was reduced more than 50%. Over sand, flow reduction was minimal and propagules were not trapped. Furthermore, notable differences between P. oceanica early life stages were observed, with seeds trapped first, followed by seedlings of increasing ages. This result may be related to the smaller frontal area (area exposed to water flow) and higher settling velocity of the younger life stages. Together, our results provide important insights into the drivers of seagrass recruitment, which are of interest for restoration purposes and numerical modelling.

Understanding how the surface dynamics of the ocean influence the spawning and larval ecology of many large pelagic species, in particular tuna species, is a major challenge. For temperate tunas, the selection of geographically restricted spawning grounds is influenced by environmental conditions, but the influence of surface mixing properties on the early life stages of these species remains poorly understood. Here, based on ichthyoplankton samples collected over 4 yr and satellite-derived finite size Lyapunov exponents (FSLEs), we examined how horizontal mixing activity drives the probability of presence of Atlantic bluefin tuna Thunnus thynnus larvae. We further analyzed the spatial and temporal scales of the FSLE variability at which the relationship between larval presence and mesoscale activity is maximized. We found that moderate mixing activity strongly favors the spatial-temporal distribution of larval habitats, evidencing an optimal environmental window of bluefin tuna spawning and early life development within the mesoscale dynamics. During the spawning season, the Balearic Sea presents a unique spatial and temporal hydrodynamic scenario within the Western Mediterranean. These results can be used for developing oceanographic indicators and improving larval abundance indices that are currently used in Atlantic bluefin tuna stock assessments.

Numerous microbial taxa establish natural relations with plants, and especially endophytes can be relevant in the development and growth promotion of their host. In this work, we explore the diversity of non-halophilic microorganisms inhabiting the endosphere of the halophyte Arthrocnemum macrostachyum. A total of 1045 isolates were recovered using standard non-saline media, which clustered into 22 operational phylogenetic units (OPUs) including 7 putative new species and 13 OPUs not previously detected as endophytes. The more abundant isolates corresponded to close relatives of Kushneria indalinina/K. marisflavi, Providencia rettgeri, Pseudomonas zhaodongensis and Bacillus safensis, which made up to ∼ 62% of the total isolates. We also isolated OPUs not detected by the culture-independent approach reinforcing the need of culturing to reveal the microbial diversity associated with plants. Additionally, the plant growth promoting activity was evaluated by representative strains of the more abundant OPUs (total = 94 strains) including also some previously isolated halophiles from the same plants. Under both saline and non-saline conditions, some strains principally those affiliated to Paenibacillus borealis, Staphylococcus equorum, Salinicola halophilus and Marinococcus tarijensis, presented growth promoting activity in Arabidopsis thaliana, which was evaluated as an increment of weight and root length.

Every year the Caribbean Sea faces the passage of several tropical cyclones that generate coastal extreme sea levels with potential strong and hazardous impacts. In this work we simulate the storm surges and wind waves induced by a set of 1000 tropical cyclones over the Caribbean Sea that are representative of the present-day climate. These events have been extracted from a global database of synthetic tropical cyclones spanning a 10 000-year period. The atmospheric forcing fields, associated with the set of tropical cyclones, are used to feed a coupled hydrodynamic–wave model with high resolution (∼ 2 km) along the continental and island coasts. Given the large number of events modelled, our results allow detailed statistical analyses of the magnitude and mechanisms of coastal extreme sea levels, as well as the identification of one of the most exposed areas to both storm surges and extreme wind waves.

This work assesses the impacts in reshaping coastlines as a result of sea level rise and changes in wave climate. The methodology proposed combines the SWAN and SWASH wave models to resolve the wave processes from deep waters up to the swash zone in two micro-tidal sandy beaches in Mallorca island, western Mediterranean. In a first step, the modelling approach has been validated with observations from wave gauges and from the shoreline inferred from video monitoring stations, showing a good agreement between them. Afterwards, the modelling set-up has been applied to the 21st century sea level and wave projections under two different climate scenarios, representative concentration pathways RCP45 and RCP85. Sea level projections have been retrieved from state-of-the-art regional estimates, while wave projections were obtained from regional climate models. Changes in the shoreline position have been explored under mean and extreme wave conditions. Our results indicate that the studied beaches would suffer a coastal retreat between 7 and up to 50 m, equivalent to half of the present-day aerial beach surface, under the climate scenarios considered.

The spatial and temporal variability of extreme wave climate in the North Atlantic Ocean and the Mediterranean Sea is assessed using a 31-year wave model hindcast. Seasonality accounts for 50 % of the extreme wave height variability in the North Atlantic Ocean and up to 70 % in some areas of the Mediterranean Sea. Once seasonality is filtered out, the North Atlantic Oscillation and the Scandinavian index are the dominant large-scale atmospheric patterns that control the interannual variability of extreme waves during winters in the North Atlantic Ocean; to a lesser extent, the East Atlantic Oscillation also modulates extreme waves in the central part of the basin. In the Mediterranean Sea, the dominant modes are the East Atlantic and East Atlantic–Western Russia modes, which act strongly during their negative phases. A new methodology for analyzing the atmospheric signature associated with extreme waves is proposed. The method obtains the composites of significant wave height (SWH), mean sea level pressure (MSLP), and 10 m height wind velocity (U10) using the instant when specific climatic indices have a stronger correlation with extreme waves.

In this work, we analyze the seasonal evolution of a Mediterranean pocket beach and its response to different storm episodes. Magalluf, an intermediate medium sand beach located in the Bay of Palma (Balearic Islands) was monitored by topographic levelling during 14 months. Near the beach, a Posidonia oceanica meadow covers most of the seabed and appears to influence the cross-shore beach adjustment. The low variability observed during the sampling period was perturbed by two storm events that caused significant beach evolution and sediment transport. The first storm gave rise to waves from the SE, significant height = 2.4 m, cross-shore sediment transport and along-shore net sediment exchange that resulted in decreased dry beach extension to a minimum. The second storm was characterized by strong northeasterly winds and generated a set-up of 0.5 m and a nearshore drift reversal that redistributed sediment from the berm crest to the beach face, thereby increasing beach extension. Results from numerical simulations of wave propagation show the circulation patterns during both events and their influence on the beach morphology. In general terms, the beach exhibited a homeostatic behaviour characteristic of an equilibrium system.

The impact of the assimilation of HFR (high-frequency radar) observations in a high-resolution regional model is evaluated, focusing on the improvement of the mesoscale dynamics. The study area is the Ibiza Channel, located in the western Mediterranean Sea. The resulting fields are tested against trajectories from 13 drifters. Six different assimilation experiments are compared to a control run (no assimilation). The experiments consist of assimilating (i) sea surface temperature, sea level anomaly, and Argo profiles (generic observation dataset); the generic observation dataset plus (ii) HFR total velocities and (iii) HFR radial velocities. Moreover, for each dataset, two different initialization methods are assessed: (a) restarting directly from the analysis after the assimilation or (b) using an intermediate initialization step applying a strong nudging towards the analysis fields. The experiments assimilating generic observations plus HFR total velocities with the direct restart provide the best results, reducing by 53 % the average separation distance between drifters and virtual particles after the first 48 h of simulation in comparison to the control run. When using the nudging initialization step, the best results are found when assimilating HFR radial velocities with a reduction of the mean separation distance by around 48 %. Results show that the integration of HFR observations in the data assimilation system enhances the prediction of surface currents inside the area covered by both antennas, while not degrading the correction achieved thanks to the assimilation of generic data sources beyond it. The assimilation of radial observations benefits from the smoothing effect associated with the application of the intermediate nudging step.