Quantification of mixed contributions of primary producers from amino acid δ15N of marine consumers: a Bayesian approach.

Estimations of the trophic position (TP) and the food web nitrogen baseline from compound-specific isotope analysis of individual amino acids (CSIA-AA) are challenged when the diet of consumer organisms relies on different proportions of vascular and non-vascular primary producers. Here we provide a new method to infer such proportions using the δ15N patterns from individual AAs (δ15NAA) in the consumer. Combining published and new data, we first characterized the δ15NAA signatures in primary producers and determined the isotopic enrichment (β) for the major taxa of primary producers. Then, we applied MixSIAR Bayesian isotope mixing models to investigate the transfer of these signatures to marine primary consumers (molluscs, green turtles, zooplankton and fish), and their utility to quantify autotrophic sources. Reliable source proportions were quantified, using appropriate combinations of trophic discrimination factors (TDFs), and were used to estimate β values for each consumer. We demonstrated that phytoplankton, macroalgae and vascular plants have singular δ15NAA fingerprints that can be tracked from the δ15NAA values in their primary consumers, and can be used to estimate mixed baseline sources. This method is useful to accurately estimate βmix values from consumer δ15NAA signatures with no requirement to sample or characterize the primary producers supporting the food web, thus providing reliable TP estimates in complex environments dominated by vascular and non-vascular autotrophs. This study evidences a suitable integration of δ15NAA fingerprinting and MixSIAR for quantitative estimations of autotrophic sources, complementing other methods to quantify resource utilization in natural systems. This method represents a major advance to unravel trophic dynamics at the aquatic/terrestrial interface using CSIA-AA.PID2020-115620RB-100, funded by MCIN/AEI/10.13039/50110001103

Hyaluronic acid as neuropathic ulcer treatment: a case report

La prevalencia de la polineuropatía diabética en España es del 22%, incrementándose con la edad, situándose en menos del 5% en pacientes entre 15 y 19 años y alcanzando el 29,8% en edades comprendidas entre los 70 y 74 años de edad. La infección en el pie diabético representa una importante complicación que a menudo se asocia a la amputación menor o incluso a la pérdida de la extremidad inferior. Se presenta un caso clínico de varón de 68 años de edad que acude a la consulta con una úlcera de pie diabético, diagnosticada dos años atrás, en la zona metatarsal del pie derecho, sin éxito de cura. Se realiza protocolo de exploración de pie diabético, un desbridamiento quirúrgico y se instaura procedimiento de cura mediante ácido hialurónico puro vendaje y descarga del pie. Tras 69 días de cura se consigue la cicatrización completa de la lesión. Una vez cicatrizada la lesión se realiza exploración biomecánica y confección de soporte plantar para evitar la aparición de la lesión por una hiperpresión de la zona.The prevalence of diabetic polyneuropathy in Spain is 22% increasing with age, standing at less than 5% in patients between 15 and 19 years and reaching 29.8% in those aged 70 to 74 years age. Infection is an important complication in Diabetic Foot, frequently associated with minor amputation and even lower extremity amputation. The study presents a clinical case of a 68-year-old man who consulted for a diabetic foot ulcer in the metatarseal area of the right foot, diagnosed two years ago and without healing success. An exploration protocol of the diabetic food was made. Afterwards, a surgical debridement was done and a cure procedure with pure hyaluronic acid, a bandage and foot unloading was followed. After 69 days of treatment, a complete ulcer healing was achieved. After the injure healing, a biomechanical exploration was made and a plantar support was produced to avoid the reappearance of the injury because of local hyperpressure.peerReviewe

Association between vertical and horizontal force-velocity-power profiles in netball players

Netball is a collective sport characterized by intermittent high-intensity actions. Therefore, the players must develop high levels of relative bilateral and unilateral strength and power for both improve performance and also reduce injury risk. The purpose of this study was (i) to provide a reference about the mechanical outputs obtained in the vertical (jumping) and horizontal force-velocity-power (FVP) profile and (ii) observe their relationship, besides the performance in jumping and sprinting in amateur female netball players (age = 24.3 ± 3.2 years, BM = 64.5 ± 5 Kg, height = 172.5 ± 6.2 cm). The variables for both FVP profiles (theoretical maximal force (F0), theoretical maximal velocity (V0) and theoretical maximal power output (Pmax)) were measured with two scientifically validated apps for iOS (My Jump 2 and My Sprint). Our results in regards to the vertical FVP suggest that netball players have low force deficit (36.2 ± 14.6%) and individualized training based on F-V profiling could be beneficial to address their deficit. The moderate correlations found for performance, V0 and Pmax suggest that the improvement in one of the skills (jumping or sprinting) may produce some positive adaptation to the other. However, no association was found in the force production (F0) of the lower limbs for both FVP. Therefore, we recommend that netball players must train specifically ballistic actions in the vertical (jumping) and horizontal direction (sprinting) due to the specificity of both skills and the consequent impact of them on netball performance.Ministry of Economy and Infrastructure of the Junta de Extremadura through the European Regional Development Fund. A way to make Europe. (GR18129)

Experimental evidences for the use of two macroalgal species, Ascophyllum nodosum and Fucus vesiculosus as biomonitors of N sources

Proyecto ANILE (CTM2009-08396, CTM2010-08804-E) Plan Nacional de I+D+i y Proyecto RADIALES (IEO)Postprint2,263

The NWP Activities at AEMET (Spain): 28th ALADIN Workshop & HIRLAM ASM

Póster presentado en: Joint 28th ALADIN Workshop & HIRLAM All Staff Meeting, celebrado del 16 al 20 de abril de 2018 en Toulouse (Francia)

Robust proxy sensor model for estimating black carbon concentrations using low-cost sensors

Air quality monitoring sensor networks focusing on air pollution measure pollutants that are regulated by the authorities, such as CO, NO2, NO, SO2, O3, and particulate matter (PM10, PM2.5). However, there are other pollutants, such as black carbon (BC), which are not regulated, have a major impact on health, and are rarely measured. One solution is to use proxies, which consist of creating a mathematical model that infers the measurement of the pollutant from indirect measurements of other pollutants. In this paper, we propose a robust machine learning proxy (RMLP) framework for estimating BC based on nonlinear machine learning methods, calibrating the low-cost sensors (LCSs), and adding robustness against noise and data missing in the LCS. We show the impact of LCS data aggregation, denoising and missing imputation on BC estimation, and how the concentrations estimated by the BC proxy approximate the values obtained by a reference instrument with an accurate BC sensor.This work is supported by projects H2020 FIRE-RES, PID 2019-107910RB-I00, CEX 2018-000794-S, 2017 SGR41, 2021 SGR01059, and the support of Sec. d’Universitats i Recerca de la Generalitat de Catalunya i del Fons Social Europeu.Peer ReviewedPostprint (author's final draft

Weak pressure gradient over the Iberian Península and African dust outbreaks: a new dust long transport scenario

African dust outbreaks over the Iberian Peninsula have been related to four synoptic patterns responsible for the advection of dust: 1. A North African high located at surface level. 2. An Atlantic depression centered over northwestern Africa, western Iberia or the southwest of the Portuguese coast with an associated high or ridge over the Mediterranean Sea. 3. A North African depression. 4. A North African high located at upper levels. Consequently, particulate matter (PM) levels in Iberia are expected to rise when any of these atmospheric synoptic scenarios prevail. Nevertheless, PM levels might not increase due to wet deposition, as Spain receives the most African-derived dust rain events of any European country. In this study, a meteorological scenario different than the above situations is evaluated

Non-linear models for black carbon exposure modelling using air pollution datasets

Black carbon (BC) is a product of incomplete combustion, present in urban aerosols and sourcing mainly from road traffic. Epidemiological evidence reports positive associations between BC and cardiovascular and respiratory disease. Despite this, BC is currently not regulated by the EU Air Quality Directive, and as a result BC data are not available in urban areas from reference air quality monitoring networks in many countries. To fill this gap, a machine learning approach is proposed to develop a BC proxy using air pollution datasets as an input. The proposed BC proxy is based on two machine learning models, support vector regression (SVR) and random forest (RF), using observations of particle mass and number concentrations (N), gaseous pollutants and meteorological variables as the input. Experimental data were collected from a reference station in Barcelona (Spain) over a 2-year period (2018–2019). Two months of additional data were available from a second urban site in Barcelona, for model validation. BC concentrations estimated by SVR showed a high degree of correlation with the measured BC concentrations (R2 = 0.828) with a relatively low error (RMSE = 0.48 µg/m3). Model performance was dependent on seasonality and time of the day, due to the influence of new particle formation events. When validated at the second station, performance indicators decreased (R2 = 0.633; RMSE = 1.19 µg/m3) due to the lack of N data and PM2.5 and the smaller size of the dataset (2 months). New particle formation events critically impacted model performance, suggesting that its application would be optimal in environments where traffic is the main source of ultrafine particles. Due to its flexibility, it is concluded that the model can act as a BC proxy, even based on EU-regulatory air quality parameters only, to complement experimental measurements for exposure assessment in urban areas.The authors would like to acknowledge the support from the Generalitat de Catalunya (Dept. Medi Ambient) by providing the air quality data. This work was partly supported by H2020 project RI-URBANS (H2020-LC-GD-2020-6, reference 101036245), the Spanish Ministry of Science and Innovation (projects CEX2018-000794-S and PID2019- 107910RB-I00), Academy of Finland via flagship on Atmosphere and Climate Competence Center (ACCC, project number 337549) and by AGAUR (project 2017 SGR41 and 2017 SGR 990). It was carried out in the framework of a joint collaboration between IDAEA-CSIC and University of Barcelona (Physics Faculty).Peer ReviewedPostprint (published version

Temperature Dependence of Water Absorption in the Biological Windows and Its Impact on the Performance of Ag2S Luminescent Nanothermometers

The application of nanoparticles in the biological context generally requires their dispersion in aqueous media. In this sense, luminescent nanoparticles are an excellent choice for minimally invasive imaging and local temperature sensing (nanothermometry). For these applications, nanoparticles must operate in the physiological temperature range (25–50 °C) but also in the nearinfrared spectral range (750–1800 nm), which comprises the three biological windows of maximal tissue transparency to photons. In this range, water displays several absorption bands that can strongly affect the optical properties of the nanoparticles. Therefore, a full understanding of the temperature dependence of water absorption in biological windows is of paramount importance for applications based on these optical properties. Herein, the absorption spectrum of water in the biological windows over the 25–65 °C temperature range is systematically analyzed, and its temperature dependence considering the coexistence of two states of water is interpreted. Additionally, to illustrate the importance of state-of-the-art applications, the effects of the absorption of water on the emission spectrum of Ag2S nanoparticles, the most sensitive luminescent nanothermometers for in vivo applications to date, are presented. The spectral shape of the nanoparticles’ emission is drastically affected by the water absorption, impacting their thermometric performanceThis work was financed by the Spanish Ministerio de Ciencia e Innovación under project PID2019-106211RB-I00, by the Instituto de Salud Carlos III (PI19/00565), by the Comunidad Autónoma de Madrid (S2017/BMD3867 RENIM-CM) and co-financed by the European structural and investment fund. Additional funding was provided by the European Union Horizon 2020 FETOpen project NanoTBTech (801305), the Fundación para la Investigación Biomédica del Hospital Universitario Ramón y Cajal project IMP21_A4 (2021/0427), and by COST action CA17140. A.B. acknowledges funding support through the TALENTO 2019T1/IND14014 contract (Comunidad Autónoma de Madrid). F.E.M. and L.D.C. acknowledge the financial support received from the project Shape of Water (PTDC/NAN-PRO/3881/2020) through Portuguese fund