Mismeasure of secondary sexual traits: An example with horn growth in the Iberian ibex

Monitoring programmes and studies focused on secondary sexual characters (SSCs) depend on the accuracy of measurements. However, methods of measurements of SSC, such as horns of ungulates, vary throughout the literature. Thus, the accuracy of horn growth measurements as proxies of true horn growth and the comparability of results inferred from different horn growth measurements may be questionable. We used the horns of Iberian ibex Capra pyrenaica to compare horn growth measurements and to analyse reliability with true horn growth. Our results reveal that measurements used in previous studies differed substantially from true horn growth and volume estimated as a barrel appeared as the best proxy of annular segments of horns in the Iberian ibex. Horn growth measurements are not necessarily mutually comparable, just as classical measurements are not necessarily representative of true horn growth. We discuss the wider implications of these results and suggest that biological processes linked to horns of ungulates should be reappraised using improved and accurate measurements because horn growth pattern is a key factor in sustainable management and conservation plans of ungulate species around the world. © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London.Peer Reviewe

Object-Based Image Classification of Summer Crop with Machine Learning Methods

The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have a similar spectral response and cropping pattern. In such cases, crop identification could be improved by combining object-based image analysis and advanced machine learning methods. In this investigation, we evaluated the C4.5 decision tree, logistic regression (LR), support vector machine (SVM) and multilayer perceptron (MLP) neural network methods, both as single classifiers and combined in a hierarchical classification, for the mapping of nine major summer crops (both woody and herbaceous) from ASTER satellite images captured in two different dates. Each method was built with different combinations of spectral and textural features obtained after the segmentation of the remote images in an object-based framework. As single classifiers, MLP and SVM obtained maximum overall accuracy of 88%, slightly higher than LR (86%) and notably higher than C4.5 (79%). The SVM+SVM classifier (best method) improved these results to 89%. In most cases, the hierarchical classifiers considerably increased the accuracy of the most poorly classified class (minimum sensitivity). The SVM+SVM method offered a significant improvement in classification accuracy for all of the studied crops compared to the conventional decision tree classifier, ranging between 4% for safflower and 29% for corn, which suggests the application of object-based image analysis and advanced machine learning methods in complex crop classification tasks.This research was partly financed by the TIN2011-22794 project of the Spanish Ministerial Commission of Science and Technology (MICYT), FEDER funds, the P2011-TIC-7508 project of the “Junta de Andalucía” (Spain) and the Kearney Foundation of Soil Science (USA). The research of Peña was co-financed by the Fulbright-MEC postdoctoral program, financed by the Spanish Ministry for Science and Innovation, and by the JAEDoc Program, supported by CSIC and FEDER funds. ASTER data were available to us through a NASA EOS scientific investigator affiliation.We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).Peer Reviewe

Object-Based Image Classification of Summer Crops with Machine Learning Methods

The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have a similar spectral response and cropping pattern. In such cases, crop identification could be improved by combining object-based image analysis and advanced machine learning methods. In this investigation, we evaluated the C4.5 decision tree, logistic regression (LR), support vector machine (SVM) and multilayer perceptron (MLP) neural network methods, both as single classifiers and combined in a hierarchical classification, for the mapping of nine major summer crops (both woody and herbaceous) from ASTER satellite images captured in two different dates. Each method was built with different combinations of spectral and textural features obtained after the segmentation of the remote images in an object-based framework. As single classifiers, MLP and SVM obtained maximum overall accuracy of 88%, slightly higher than LR (86%) and notably higher than C4.5 (79%). The SVM+SVM classifier (best method) improved these results to 89%. In most cases, the hierarchical classifiers considerably increased the accuracy of the most poorly classified class (minimum sensitivity). The SVM+SVM method offered a significant improvement in classification accuracy for all of the studied crops compared to the conventional decision tree classifier, ranging between 4% for safflower and 29% for corn, which suggests the application of object-based image analysis and advanced machine learning methods in complex crop classification task

Anxiety, Distress and Stress among Patients with Diabetes during COVID-19 Pandemic: A Systematic Review and Meta-Analysis

The prevalence of mental health disorders has increased during the COVID-19 pandemic. Patients with chronic diseases, such as diabetes, are a particularly vulnerable risk group. This study aims to assess the levels and prevalence of anxiety, distress, and stress in patients with diabetes during the COVID-19 pandemic. A systematic review was conducted in CINAHL, Cochrane, LILACS, Medline, SciELO, and Scopus in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Thirty-seven articles with a total of 13,932 diabetic patients were included. Five meta-analyses were performed. The prevalence of anxiety was 23% (95% CI = 19–28) in T1DM and 20% (95% CI = 6–40) in T2DM patients. For diabetes distress it was 41% (95% CI = 24–60) for T1DM and 36% in T2DM patients (95% CI = 2–84). For stress, the prevalence was 79% (95% CI = 49–98) in T1DM patients. People with diabetes have significant psychiatric comorbidity as well as psychological factors that negatively affect disease management, increasing their vulnerability in an emergency situation. To establish comprehensive care in diabetic patients addressing mental health is essential, as well as including specific policy interventions to reduce the potential psychological harm of the COVID-19 pandemic

Negative effect of the arthropod parasite, Sarcoptes scabiei, on testes mass in Iberian ibex, Capra pyrenaica

Testes mass is a key factor in male reproductive success and is potentially exposed to so-called 'parasitic castration'. This is the result of the direct destruction or alteration of reproductive cell lineages (parasitic castration sensu stricto), or the indirect detrimental effects - for example, via body condition - on the ability of progenitors to produce or rear offspring (parasitic castration sensu lato). There are enormous gaps in our knowledge on the effects of parasites on the testes of wild mammals and in an attempt to rectify this dearth of data we examined the relationship between the skin parasite Sarcoptes scabiei and testes mass in Iberian ibex Capra pyrenaica. We considered data from 222 males that were culled in the population from the Sierra Nevada in Spain. Our results provide evidence that sarcoptic mange is associated with reduced size-corrected testes mass in Iberian ibex which supports the hypothesis that parasitism is a determining factor in gonad plasticity in male mammals. We discuss several hypothetical causes of this relationship and highlight the need to deepen the sub-lethal effects of pathogens if we are to accurately understand their modulator effects on host population dynamics. © 2010 Elsevier B.V.Peer Reviewe

Oestrid myiasis in European Mouflon from Spain

From February 1992 to March 1997, 245 European mouflon (Ovis orientalis musimon) from Sierras de Cazorla, Segura y Las Villas Natural Park (southern Spain) were surveyed for oestrid larvae in order to estimate prevalence and mean intensity of parasitism by Oestrus ovis. Over 46 percent of the animals surveyed were infected, with a mean intensity of 9.6 larvae/host parasitized. No significant differences in prevalence rates between host sexes were observed, but older mouflons were infected with more larvae than younger ones.Peer Reviewe

Antifungal prophylaxis following heart transplantation : systematic review

Q1Q1Artículo original429-436Patients with heart transplantation have a high incidence of infectious complications, especially fungal infections. The aim of the systematic review was to determine the best pharmacological strategy to prevent fungal infections among patients with heart transplant. We searched the PubMed and Embase databases for studies reporting the effectivenesss of pharmacologic strategies to prevent fungal infections in adult patient with a heart transplant. Our search yielded five studies (1176 patients), four of them with historical controls. Two studies used inhaled amphotericin B deoxycholate, three used itraconazole and one used targeted echinocandin. All studies showed significant reduction in the prophylaxis arm. Different products, doses and outcomes were noted. There is a highly probable benefit of prophylaxis use, however, better studies with standardised doses and comparators should be performed

Preliminary Microbiological Coastal Water Quality Determination along the Department of Atlantico (Colombia): Relationships with Beach Characteristics

Beach water quality is an important factor concerning public health and tourism linked to the "Sun, Sea and Sand" market and is usually assessed in international regulations by the quantification of Escherichia coli and enterococci counts. Despite Salmonella spp. detection not being included in international normative, the presence/absence of this bacteria is also an indicator of seawater quality. The objective of this study was to determine microbiological quality of beach water at 14 beaches along the Department of Atlantico (Colombia) and its relationship with beach characteristics as beach typology (i.e., urban, village, rural and remote areas), presence of beach facilities (e.g., bars, restaurants, etc.) and streams outflowing into the coastline. Sampling program aimed to analyse E. coli and Salmonella spp., by culture-based and real time PCR methods, respectively. Microbiological outcomes were compared with beach characteristics, and a cluster analysis was performed. E. coli and Salmonella spp. were detected in 70% and 20% of samples, respectively. Highest E. coli counts were observed at beaches classified as urban and at Sabanilla, a rural beach with presence of numerous beach restaurants/bars. Salmonella spp. presence was associated with streams that lack wastewater treatment systems. Cluster analysis clearly evidenced the relationship between E. coli and Salmonella spp. and beach characteristics, allowing to obtain indications to implement management programs. According to data obtained, monitoring programs have to be especially carried out in urban areas and at places with beach facilities. This could enhance microbiological water quality and consequently, beachgoers safety and touristic beach attractiveness to international visitors

Evolution of Acute Respiratory Distress Syndrome in Emergency and Critical Care: Therapeutic Management before and during the Pandemic Situation

Background and Objectives: Acute respiratory distress syndrome is a life-threatening lung condition that prevents enough oxygen from getting to the lungs and blood. The causes can be varied, although since the COVID-19 pandemic began there have been many cases related to this virus. The management and evolution of ARDS in emergency situations in the last 5 years was analyzed. Materials and Methods: A systematic review was carried out in the PubMed and Scopus databases. Using the descriptors Medical Subject Headings (MeSH), the search equation was: “Emergency health service AND acute respiratory distress syndrome”. The search was conducted in December 2021. Quantitative primary studies on the care of patients with ARDS in an emergency setting published in the last 5 years were included. Results: In the initial management, adherence to standard treatment with continuous positive airway pressure (CPAP) is recommended. The use of extracorporeal membrane reduces the intensity of mechanical ventilation or as rescue therapy in acute respiratory distress syndrome (ARDS). The prone position in both intubated and non-intubated patients with severe ARDS is associated with a better survival of these patients, therefore, it is very useful in these moments of pandemic crisis. Lack of resources forces triage decisions about which patients are most likely to survive to start mechanical ventilation and this reflects the realities of intensive care and emergency care in a resource-limited setting. Conclusions: adequate prehospital management of ARDS and in emergency situations can improve the prognosis of patients. The therapeutic options in atypical ARDS due to COVID-19 do not seem to vary substantially from conventional ARDS