The role of scattered trees and habitat diversity for biodiversity of Iberian dehesas

PosterWe studied 10 dehesas of CW Spain (40º 00’-10’ N, 06º 10’-20’ W), mapping every habitat according to a standardized protocol developed by the European BioBio project. We defined 35 habitat types, with 19 habitat types (split in 85 plots) per dehesa, on average. In one randomly selected plot per habitat type diversity of the four taxa, plants, bees, spiders and earthworms, were assessed. In total, 450 plant species (average of 189 per farm and 36 per habitat), 63 bee species (17.6 and 3.2), 130 spider species (43.8 and 7.4), and 17 earthworm species ( 7.8 and 2.5) were recorded. In each taxa, only some species were very abundant, while most of the species were found only in few farms/habitats. A high proportion of species (ca. 40%) were observed only in just one habitat per farm, indicating that farm biodiversity strongly depends on the habitat diversity. The analysis of unique and shared species among habitats revealed that every habitat contribute significantly to farm biodiversity. By contrast, species richness was poorly explained by the presence of scattered trees, whereas the combination of wood pastures and open pastures was a significant predictor. Summarizing, our extensive survey showed that diversity of the four taxa was strongly related to the existence of a wide mosaic of habitats, including non-productive habitats and linear elements, which harbor a disproportionate number of species compared to the low area occupied. Moreover, these habitats harbor a high number of exclusive species. As a next step, the importance of the spatial arrangement of main and non-productive habitats for biodiversity at the farm and landscape levels, need to be checked

SARS-CoV-2 viral load in nasopharyngeal swabs is not an independent predictor of unfavorable outcome

The aim was to assess the ability of nasopharyngeal SARS-CoV-2 viral load at first patient’s hospital evaluation to predict unfavorable outcomes. We conducted a prospective cohort study including 321 adult patients with confirmed COVID-19 through RT-PCR in nasopharyngeal swabs. Quantitative Synthetic SARS-CoV-2 RNA cycle threshold values were used to calculate the viral load in log10 copies/mL. Disease severity at the end of follow up was categorized into mild, moderate, and severe. Primary endpoint was a composite of intensive care unit (ICU) admission and/or death (n = 85, 26.4%). Univariable and multivariable logistic regression analyses were performed. Nasopharyngeal SARS-CoV-2 viral load over the second quartile (≥ 7.35 log10 copies/mL, p = 0.003) and second tertile (≥ 8.27 log10 copies/mL, p = 0.01) were associated to unfavorable outcome in the unadjusted logistic regression analysis. However, in the final multivariable analysis, viral load was not independently associated with an unfavorable outcome. Five predictors were independently associated with increased odds of ICU admission and/or death: age ≥ 70 years, SpO2, neutrophils > 7.5 × 103/µL, lactate dehydrogenase ≥ 300 U/L, and C-reactive protein ≥ 100 mg/L. In summary, nasopharyngeal SARS-CoV-2 viral load on admission is generally high in patients with COVID-19, regardless of illness severity, but it cannot be used as an independent predictor of unfavorable clinical outcome

Dendritic cell deficiencies persist seven months after SARS-CoV-2 infection

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2 infection induces an exacerbated inflammation driven by innate immunity components. Dendritic cells (DCs) play a key role in the defense against viral infections, for instance plasmacytoid DCs (pDCs), have the capacity to produce vast amounts of interferon-alpha (IFN-α). In COVID-19 there is a deficit in DC numbers and IFN-α production, which has been associated with disease severity. In this work, we described that in addition to the DC deficiency, several DC activation and homing markers were altered in acute COVID-19 patients, which were associated with multiple inflammatory markers. Remarkably, previously hospitalized and nonhospitalized patients remained with decreased numbers of CD1c+ myeloid DCs and pDCs seven months after SARS-CoV-2 infection. Moreover, the expression of DC markers such as CD86 and CD4 were only restored in previously nonhospitalized patients, while no restoration of integrin β7 and indoleamine 2,3-dyoxigenase (IDO) levels were observed. These findings contribute to a better understanding of the immunological sequelae of COVID-19

Epidemiological trends of HIV/HCV coinfection in Spain, 2015-2019

Altres ajuts: Spanish AIDS Research Network; European Funding for Regional Development (FEDER).Objectives: We assessed the prevalence of anti-hepatitis C virus (HCV) antibodies and active HCV infection (HCV-RNA-positive) in people living with HIV (PLWH) in Spain in 2019 and compared the results with those of four similar studies performed during 2015-2018. Methods: The study was performed in 41 centres. Sample size was estimated for an accuracy of 1%. Patients were selected by random sampling with proportional allocation. Results: The reference population comprised 41 973 PLWH, and the sample size was 1325. HCV serostatus was known in 1316 PLWH (99.3%), of whom 376 (28.6%) were HCV antibody (Ab)-positive (78.7% were prior injection drug users); 29 were HCV-RNA-positive (2.2%). Of the 29 HCV-RNA-positive PLWH, infection was chronic in 24, it was acute/recent in one, and it was of unknown duration in four. Cirrhosis was present in 71 (5.4%) PLWH overall, three (10.3%) HCV-RNA-positive patients and 68 (23.4%) of those who cleared HCV after anti-HCV therapy (p = 0.04). The prevalence of anti-HCV antibodies decreased steadily from 37.7% in 2015 to 28.6% in 2019 (p < 0.001); the prevalence of active HCV infection decreased from 22.1% in 2015 to 2.2% in 2019 (p < 0.001). Uptake of anti-HCV treatment increased from 53.9% in 2015 to 95.0% in 2019 (p < 0.001). Conclusions: In Spain, the prevalence of active HCV infection among PLWH at the end of 2019 was 2.2%, i.e. 90.0% lower than in 2015. Increased exposure to DAAs was probably the main reason for this sharp reduction. Despite the high coverage of treatment with direct-acting antiviral agents, HCV-related cirrhosis remains significant in this population

Machine learning applied to diagnosis of human diseases: A systematic review

Human healthcare is one of the most important topics for society. It tries to find the correct effective and robust disease detection as soon as possible to patients receipt the appropriate cares. Because this detection is often a difficult task, it becomes necessary medicine field searches support from other fields such as statistics and computer science. These disciplines are facing the challenge of exploring new techniques, going beyond the traditional ones. The large number of techniques that are emerging makes it necessary to provide a comprehensive overview that avoids very particular aspects. To this end, we propose a systematic review dealing with the Machine Learning applied to the diagnosis of human diseases. This review focuses on modern techniques related to the development of Machine Learning applied to diagnosis of human diseases in the medical field, in order to discover interesting patterns, making non-trivial predictions and useful in decision-making. In this way, this work can help researchers to discover and, if necessary, determine the applicability of the machine learning techniques in their particular specialties. We provide some examples of the algorithms used in medicine, analysing some trends that are focused on the goal searched, the algorithm used, and the area of applications. We detail the advantages and disadvantages of each technique to help choose the most appropriate in each real-life situation, as several authors have reported. The authors searched Scopus, Journal Citation Reports (JCR), Google Scholar, and MedLine databases from the last decades (from 1980s approximately) up to the present, with English language restrictions, for studies according to the objectives mentioned above. Based on a protocol for data extraction defined and evaluated by all authors using PRISMA methodology, 141 papers were included in this advanced review.This work was funded by MINECO (Ministry of Economy and Competitiveness, Spain) and ISCIII (Institute of Health Carlos III, Spain), under the contract ELAC2015/T09-0819 SPIDEP. These founders supplied the necessary materials and human resources for the development of this advanced review

A Novel Global Maximum Power Point Tracking Method Based on Measurement Cells

Solar power generation has become a solution to mitigate the severe effects on the everyday higher prices of fossil fuels. Additionally, renewable energies operation -as solar- results in a non-polluting way to supply energy, being of special interest into highly contaminated cities and/or countries. The solar energy efficiency injection system is known to be high and mainly due to the power converters effectiveness, which is over of 95% for low and medium voltage. However, this efficiency is reduced when the solar array is partially shaded because traditional maximum power point tracking (MPPT) algorithms are not able to find the maximum power point (MPP) under irregular radiation. This work presents a new algorithm to find the global MPP (GMPP) based upon two MPPTs algorithms used regularly in uniform solar condition (USC), these are the Measuring Cell (MC) and the Perturb and Observe (P&#x0026;O) methods. The MC ensures to find the surroundings of every local MPP (LMPP) faster and then choose among them the surroundings of the GMPP. Once the surroundings of GMPP are found, the P&#x0026;O is used to get closer to the GMPP but reducing the DC voltage oscillation to zero hence overcoming the main issue of the P&#x0026;O. Thus, the proposed algorithm finds the GMPP in two main steps and eliminates the oscillations around the GMPP in steady state, despite the utilization of the P&#x0026;O. The algorithm is detailed mathematically, illustrated by means of a block diagram, and validated in simulated and experimental results. AuthorOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Exploring the causes of high biodiversity of Iberian dehesas: the importance of wood pastures and marginal habitats

In extensive low input farming and in agroforestry systems, the importance for biodiversity of managed productive fields with respect to unmanaged marginal habitats that occupy a low proportion of farm surface, is still poorly understood, contrasting with the well-known key importance of marginal habitats in intensive systems. We analyzed the importance of open and wood pastures and marginal habitats for species richness of Iberian dehesas in Central-Western Spain. We sampled 155 plots classified into 9 general habitat categories: wood pastures (n = 41 plots); open pastures dominated by annual plants (n = 11), by perennial plants (n = 15) and co-dominated by annuals and perennial plants (n = 16); shrublands (n = 19); agricultural crops (n = 12); herbaceous strips (n = 10); woody strips (n = 11); and water bodies (n = 10). In each plot we measured the abundance and species richness of four taxonomic groups: vascular plants, bees, spiders, and earthworms. We detected 431 plant species (37 ± 2.5 CI95 in 100 m2 on average), 60 bee species (3.1 ± 1.1 in 600 m2), 128 spider species (7.4 ± 1.2 in 1.5 m2) and 18 earthworm species (2.5 ± 1.0 in 0.27 m2) in 145 sampling plots. Wood pastures supported fewer species of spiders and earthworms at the plot level, but more plants and earthworm species at the landscape level than open pastures. The low proportion of shared species among habitats and among plots within each habitat type, and the high proportion of species found in unique plots or habitats indicated that every habitat contributes to farm biodiversity. Overall, our extensive survey confirms the hypothesis that the high diversity of dehesas depends on the coexistence within farms of a wide mosaic of habitats, including marginal habitats, which seemed to harbor a disproportionately high number of species as compared to their small extent. Results support policy measures for the maintenance of farm keystone structures such as linear features, small wood/shrub patches and ponds, and reveal that these measures should not be exclusively applied to more intensive farming systems.This work was funded by the European Union through the FP7 project BioBio (Indicators for biodiversity in organic and low-input farming systems; www.biobio-indicators.org), and is a contribution by MD to the projects Consolider Montes (CSD2008-00040), VULGLO (CGL2010-C03-03), REMEDINAL3-CM (S2013/MAE-2719) and BACCARA (CE: FP7-226299).Peer Reviewe

Fishborne Zoonotic Trematodes Transmitted by Melanoides tuberculata Snails, Peru

We investigated the transmission of the fishborne trematodes Centrocestus formosanus and Haplorchis pumilio by Melanoides tuberculata snails in Peru. We report on results of experimental, morphological, and molecular approaches and discuss the potential risk for future human cases, given the existence of food habits in the country involving the ingestion of raw fish