Los Eleatas: Parménides, Zenón y Meliso

Presentamos la traducción al castellano, hecha directamente del griego, de los Fragmentos conocidos hasta ahora de los tres filósofos eleatas Parménides, Zenón de Elea y Meliso

Los Eleatas: Zenón y Meliso

Al infinito en magnitud lo demostró primeramente mediante la misma argumentación. Habiendo pues antes demostrado que «si no tiene magnitud el ser, no existe», arguye «si pues existe, es necesario que cada parte tenga alguna magnitud y grosor y difieran en esto la una de la otra. Y acerca de la precedente, se diga lo mismo. Pues también ella tendrá magnitud, y tendrá delante de sí, otra. Y haber dicho esto una vez es lo mismo que decirlo para siempre. Pues ninguna de las tales partes del mismo será la última, ni dejará de haber una después de otra. Así, si son muchas partes, es necesario que éstas sean pequeñas y grandes: pequeñas, de tal modo que no tengan magnitud; grandes, de modo que sean infinitas» (= infinitamente extensas)

Virus satellites drive viral evolution and ecology

Virus satellites are widespread subcellular entities, present both in eukaryotic and in prokaryotic cells. Their modus vivendi involves parasitism of the life cycle of their inducing helper viruses, which assures their transmission to a new host. However, the evolutionary and ecological implications of satellites on helper viruses remain unclear. Here, using staphylococcal pathogenicity islands (SaPIs) as a model of virus satellites, we experimentally show that helper viruses rapidly evolve resistance to their virus satellites, preventing SaPI proliferation, and SaPIs in turn can readily evolve to overcome phage resistance. Genomic analyses of both these experimentally evolved strains as well as naturally occurring bacteriophages suggest that the SaPIs drive the coexistence of multiple alleles of the phage-coded SaPI inducing genes, as well as sometimes selecting for the absence of the SaPI depressing genes. We report similar (accidental) evolution of resistance to SaPIs in laboratory phages used for Staphylococcus aureus typing and also obtain the same qualitative results in both experimental evolution and phylogenetic studies of Enterococcus faecalis phages and their satellites viruses. In summary, our results suggest that helper and satellite viruses undergo rapid coevolution, which is likely to play a key role in the evolution and ecology of the viruses as well as their prokaryotic hosts

Using the Uniform Theory of Diffraction to Analyze Radio Wave Propagation along Urban Street Canyons for Device-to-Device Communication

This paper examines the propagation of radio waves in so-called urban street canyons through formulations based on Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD). As this type of environment comprises a street flanked by tall buildings more or less equally spaced on both sides (creating a canyon-like morphology), estimating the attenuation that radio signals may experience in these scenarios is crucial to the planning of urban device-to-device (D2D) wireless communication. In this sense, the results obtained through the analysis based on GO/UTD (in the horizontal plane containing the transmitter and receiver) are validated by a comparison with experimental measurements, showing good agreement. This work demonstrates how the use of GO/UTD-based formulations can contribute to a simpler and computationally more efficient planning of D2D mobile communication systems in which the considered propagation environment can be modeled as an urban street canyon comprising rectangular and equispaced buildings.This work was supported by the Ministerio de Ciencia e Innovación, Spain, under Grant PID2019-107885GB-C33. Partial funding for open access charge: Universidad de Málag

A Comparison of Feature Selection and Forecasting Machine Learning Algorithms for Predicting Glycaemia in Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (DM1) is a metabolic disease derived from falls in pancreatic insulin production resulting in chronic hyperglycemia. DM1 subjects usually have to undertake a number of assessments of blood glucose levels every day, employing capillary glucometers for the monitoring of blood glucose dynamics. In recent years, advances in technology have allowed for the creation of revolutionary biosensors and continuous glucose monitoring (CGM) techniques. This has enabled the monitoring of a subject’s blood glucose level in real time. On the other hand, few attempts have been made to apply machine learning techniques to predicting glycaemia levels, but dealing with a database containing such a high level of variables is problematic. In this sense, to the best of the authors’ knowledge, the issues of proper feature selection (FS)—the stage before applying predictive algorithms—have not been subject to in-depth discussion and comparison in past research when it comes to forecasting glycaemia. Therefore, in order to assess how a proper FS stage could improve the accuracy of the glycaemia forecasted, this work has developed six FS techniques alongside four predictive algorithms, applying them to a full dataset of biomedical features related to glycaemia. These were harvested through a wide-ranging passive monitoring process involving 25 patients with DM1 in practical real-life scenarios. From the obtained results, we affirm that Random Forest (RF) as both predictive algorithm and FS strategy offers the best average performance (Root Median Square Error, RMSE = 18.54 mg/dL) throughout the 12 considered predictive horizons (up to 60 min in steps of 5 min), showing Support Vector Machines (SVM) to have the best accuracy as a forecasting algorithm when considering, in turn, the average of the six FS techniques applied (RMSE = 20.58 mg/dL)

Functional and Structural Analysis of C-Terminal BRCA1 Missense Variants

Germline inactivating mutations in BRCA1 and BRCA2 genes are responsible for Hereditary Breast and Ovarian Cancer Syndrome (HBOCS). Genetic testing of these genes is available, although approximately 15% of tests identify variants of uncertain significance (VUS). Classification of these variants into pathogenic or non-pathogenic type is an important challenge in genetic diagnosis and counseling. The aim of the present study is to functionally assess a set of 7 missense VUS (Q1409L, S1473P, E1586G, R1589H, Y1703S, W1718L and G1770V) located in the C-terminal region of BRCA1 by combining in silico prediction tools and structural analysis with a transcription activation (TA) assay. The in silico prediction programs gave discrepant results making its interpretation difficult. Structural analysis of the three variants located in the BRCT domains (Y1703S, W1718L and G1770V) reveals significant alterations of BRCT structure. The TA assay shows that variants Y1703S, W1718L and G1770V dramatically compromise the transcriptional activity of BRCA1, while variants Q1409L, S1473P, E1586G and R1589H behave like wild-type BRCA1. In conclusion, our results suggest that variants Y1703S, W1718L and G1770V can be classified as likely pathogenic BRCA1 mutations

Combined kinetic analysis of SARS-CoV-2 RNAemia, N-antigenemia and virus-specific antibodies in critically ill adult COVID-19 patients

Combined kinetic analysis of plasma SARS‐CoV‐2 RNAemia, Nucleocapsid (N)‐antigenemia and virus‐specific antibodies may help ascertain the role of antibodies in preventing virus dissemination in COVID‐19 patients. We performed this analysis in a cohort of 71 consecutive critically ill COVID‐19 patients (49 male; median age, 65 years) using RT‐PCR assay, lateral flow immunochromatography method and receptor binding domain (RBD) and N‐based immunoassays. A total of 338 plasma specimens collected at a median of 12 days after symptoms onset were available for analyses. SARS‐ CoV‐2 RNAemia and N‐antigenemia were detected in 37 and 43 specimens from 26 (36.5%) and 30 (42.2%) patients, respectively. Free RNA was the main biological form of SARS‐CoV‐2 found in plasma. The detection rate for both viral components was associated with viral load at the upper respiratory tract. Median time to SARS‐CoV‐2‐RBD antibody detection was 14 days (range, 4-38) from onset of symptoms. Decreasing antibody levels were observed in parallel to increasing levels of both RNAemia and N‐antigenemia, yet overall a fairly modest inverse correlation (Rho = −0.35; P < 0.001) was seen between virus RNAemia and SARS‐CoV‐2‐RBD antibody levels. The data cast doubts on a major involvement of antibodies in virus clearance from the bloodstream within the timeframe examined

NLRP3 inflammasome suppression improves longevity and prevents cardiac aging in male mice

While NLRP3‐inflammasome has been implicated in cardiovascular diseases, its role in physiological cardiac aging is largely unknown. During aging, many alterations occur in the organism, which are associated with progressive impairment of metabolic pathways related to insulin resistance, autophagy dysfunction, and inflammation. Here, we investigated the molecular mechanisms through which NLRP3 inhibition may attenuate cardiac aging. Ablation of NLRP3‐inflammasome protected mice from age‐related increased insulin sensitivity, reduced IGF‐1 and leptin/adiponectin ratio levels, and reduced cardiac damage with protection of the prolongation of the agedependent PR interval, which is associated with atrial fibrillation by cardiovascular aging and reduced telomere shortening. Furthermore, old NLRP3 KO mice showed an inhibition of the PI3K/AKT/mTOR pathway and autophagy improvement, compared with old wild mice and preserved Nampt‐mediated NAD+ levels with increased SIRT1 protein expression. These findings suggest that suppression of NLRP3 prevented many age‐associated changes in the heart, preserved cardiac function of aged mice and increased lifespan.Andalusian regional government; Consejería de Salud de la Junta de Andalucia, Grant/ Award Number: PI‐0036‐2014; Ministerio de economía y competitividad, Grant/Award Number: SAF2017‐84494‐C2‐1‐

Therapeutic measures in a moving ambulance: Qualitative study of professional opinions regarding prehospital emergencies

Background: current organization of the prehospital emergency teams, decreasing the prehospital times, given the possibility of working during the patient’s transport and, therefore, the consequences that may result from the same improving the prognostic. Objectives: To explore the opinion of professional healthcare experts regarding prehospital emergencies arising when forced to assist a critical patient in a moving vehicle, based on a high-fidelity clinical simulation, as well as the factors influencing them. Methods: An exploratory study of content analysis with qualitative methodology, via semi-structured questionnaires that are self-completed anonymously, before and after the clinical simulation intervention in which participants intubate a mannequin in a moving ambulance. The sample consisted of 36 experts in prehospital emergencies from the province of Alicante (Spain). Codification and assessment of the data obtained was carried out via triangulation, respecting the language and literal expressions of the participants. Results: Thirty-two pre- and post-intervention questionnaires were completed. Four different units of meaning or categories emerged which were organized based on two thematic structures, from the perspective of professional and patient needs. Twenty-three participants had never previously intubated in a moving vehicle. Discussion: Working in a moving vehicle may be yet another aspect to consider in the specialized teaching–learning process of prehospital emergency medicine. Conclusion: Based on the need to decrease prehospital assistance times, a new paradigm has been opened in prehospital emergencies with the possibility of being able to safely assist our patients during their transport on a moving ambulance or helicopter. It will be necessary further research in the future

Monitoring the complex benthic habitat on semi-dark underwater marine caves using photogrammetry-based 3D reconstructions

Marine caves are dark environments considered a priority habitat for conservation included in the EU Habitats Directive (H8330). They harbor fragile benthic communities and represent a major reservoir of marine biodiversity. However, there is a lack of knowledge of these habitats due to the difficulties of creating detailed benthic maps and characterizing the biodiversity, structure, and dynamics of their communities. The uniqueness of marine caves fosters their popularity among recreational divers, who can cause disturbances through abrasion of the biota, resuspension of sediment, and accumulation of exhaled air bubbles in the caves' ceilings. This study aims to build a monitoring framework to characterize the structure and temporal dynamics of this complex habitat using Structurefrom- Motion (SfM) photogrammetry. SfM is a novel, non-invasive technique that allows a major advancement in the monitoring of changes in the cave’s community assemblages. This method relies on images acquired by 4K video footage to build fine-scaled 3D digital models of the substrate using overlapping imagery. For this study, we combined SfM photogrammetry and photo quadrats extracted from the video recordings. We evaluate the effectiveness of this methodology in a marine cave highly frequented by divers, located in Illa de l’Aire (Balearic Islands, Spain), and carried out two surveys before and after the diving season (2019-2021). As a result, we found a loss of 25 colonies of bryozoans with fragile skeletons, like Schizoretepora sp., and 8 individual sponges with globose morphotypes. Our results indicate that this methodology enables accurate and efficient monitoring of benthic communities in underwater caves that allow us to better understand their dynamics and, therefore, to develop the need management measures