Melanoma expression analysis with Big Data technologies

Melanoma is a highly immunogenic tumor. Therefore, in recent years physicians have incorporated drugs that alter the immune system into their therapeutic arsenal against this disease, revolutionizing in the treatment of patients in an advanced stage of the disease. This has led us to explore and deepen our knowledge of the immunology surrounding melanoma, in order to optimize its approach. At present, immunotherapy for metastatic melanoma is based on stimulating an individual’s own immune system through the use of specific monoclonal antibodies. The use of immunotherapy has meant that many of patients with melanoma have survived and therefore it constitutes a present and future treatment in this field. At the same time, drugs have been developed targeting specific mutations, specifically BRAF, resulting in large responses in tumor regression (set up in this clinical study to 18 months), as well as a higher percentage of long-term survivors. The analysis of the gene expression changes and their correlation with clinical changes can be developed using the tools provided by those companies which currently provide gene expression platforms. The gene expression platform used in this clinical study is NanoString, which provides nCounter. However, nCounter has some limitations as the type of analysis is restricted to a predefined set, and the introduction of clinical features is a complex task. This paper presents an approach to collect the clinical information using a structured database and a Web user interface to introduce this information, including the results of the gene expression measurements, to go a step further than the nCounter tool. As part of this work, we present an initial analysis of changes in the gene expression of a set of patients before and after targeted therapy. This analysis has been carried out using Big Data technologies (Apache Spark) with the final goal being to scale up to large numbers of patients, even though this initial study has a limited number of enrolled patients (12 in the first analysis). This is not a Big Data problem, but the underlaying study aims at targeting 20 patients per year just in Málaga, and this could be extended to be used to analyze the 3.600 patients diagnosed with melanoma per year.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This work was funded in part by Grants TIN2014-58304-R (Ministerio de Ciencia e Innovación) and P11-TIC-7529 and P12-TIC-1519 (Plan Andaluz de Investigación, Desarrollo e Innovación). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Portable Multi-Hypothesis Monte Carlo Localization for Mobile Robots

Self-localization is a fundamental capability that mobile robot navigation systems integrate to move from one point to another using a map. Thus, any enhancement in localization accuracy is crucial to perform delicate dexterity tasks. This paper describes a new location that maintains several populations of particles using the Monte Carlo Localization (MCL) algorithm, always choosing the best one as the sytems's output. As novelties, our work includes a multi-scale match matching algorithm to create new MCL populations and a metric to determine the most reliable. It also contributes the state-of-the-art implementations, enhancing recovery times from erroneous estimates or unknown initial positions. The proposed method is evaluated in ROS2 in a module fully integrated with Nav2 and compared with the current state-of-the-art Adaptive ACML solution, obtaining good accuracy and recovery times.Comment: Submission for ICRA 202

Implementación de un aplicativo móvil bajo estándares de calidad de la ISO 25000 y su impacto en la gestión de reservas en las canchas de fútbol en la provincia de Jaén - Cajamarca, 2023

La creciente tendencia para automatizar procesos clave del negocio empleando tecnología (sistemas, aplicativos, etc.) ha llevado a miles de negocios a adquirirlos pues no sólo se trata de una moda sino de una necesidad. La presente investigación tuvo como objetivo implementar un aplicativo móvil bajo estándares de calidad de la ISO 25000 para la gestión de reservas en las canchas de fútbol en la provincia de Jaén. Para la metodología de investigación se siguió un enfoque cuantitativo, el tipo de investigación fue aplicada y el diseño pre – experimental; contemplando como muestra 54 usuarios de las canchas de fútbol ubicadas en Jaén, a quiénes se les aplicó dos cuestionarios, los cuales fueron validados por expertos y se usó el coeficiente de Alpha de Cronbach para validar la confiabilidad de los instrumentos, el valor de este coeficiente fue de 0.924 y 0.902. Para el desarrollo del aplicativo móvil se utilizó la metodología en cascadas, como herramientas de ingenierías principales se usaron el IDE Visual Studio 2019, Android y los lineamientos de la norma ISO 25000 para el desarrollo del aplicativo móvil y su evaluación de calidad. Asimismo, los resultados señalaron que, en un inicio el 78% de usuarios percibía la gestión de reservas como mala, posterior a la implementación del aplicativo móvil, el 0% de encuestados manifestaron que dicha gestión era inadecuada. Se concluyó que, la implementación de un aplicativo móvil bajo los estándares de calidad de la ISO 25000 si mejoró significativamente en un 78% la gestión de reservas de dichos espacios deportivos.The growing trend to automate key business processes using technology (systems, applications, etc.) has led thousands of businesses to acquire them because it's not just a trend but a necessity. The aim of this research was to implement a mobile application under ISO 25000 quality standards for managing football pitch bookings in the province of Jaén. For the research methodology, a quantitative approach was followed; the research type was applied, and the design was pre-experimental. The study involved a sample of 54 users from football pitches located in Jaén. These users were administered two questionnaires, which were validated by experts. The Cronbach's Alpha coefficient was used to assess the reliability of the instruments, with values of 0.924 and 0.902 obtained. For the development of the mobile application, a waterfall methodology was used. The main engineering tools employed were Visual Studio 2019 IDE, Android, and the guidelines of ISO 25000 for both the development and quality evaluation of the mobile application. Additionally, the results indicated that initially, 78% of users perceived the booking management as poor. However, after the implementation of the mobile application, 0% of respondents indicated that the management was inadequate. It was concluded that the implementation of a mobile application under ISO 25000 quality standards significantly improved the booking management of these sports facilities by 78%

Single trajectory characterization via machine learning

[EN] In order to study transport in complex environments, it is extremely important to determine the physical mechanism underlying diffusion and precisely characterize its nature and parameters. Often, this task is strongly impacted by data consisting of trajectories with short length (either due to brief recordings or previous trajectory segmentation) and limited localization precision. In this paper, we propose a machine learning method based on a random forest architecture, which is able to associate single trajectories to the underlying diffusion mechanism with high accuracy. In addition, the algorithm is able to determine the anomalous exponent with a small error, thus inherently providing a classification of the motion as normal or anomalous (sub- or super-diffusion). The method provides highly accurate outputs even when working with very short trajectories and in the presence of experimental noise. We further demonstrate the application of transfer learning to experimental and simulated data not included in the training/test dataset. This allows for a full, high-accuracy characterization of experimental trajectories without the need of any prior information.This work has been funded by the Spanish Ministry MINECO (National Plan 15 Grant: FISICATEAMO No. FIS2016-79508-P, SEVEROOCHOA No. SEV-2015-0522, FPI), European Social Fund, Fundacio Cellex, Generalitat de Catalunya (AGAUR Grant No. 2017 SGR 1341 and CERCA/Program), ERC AdG OSYRIS, EU FETPRO QUIC, and the National Science Centre, Poland-Symfonia Grant No. 2016/20/W/ST4/00314. CM acknowledges funding from the Spanish Ministry of Economy and Competitiveness and the European Social Fund through the Ramon y Cajal program 2015 (RYC-2015-17896) and the BFU2017-85693-R and from the Generalitat de Catalunya (AGAUR Grant No. 2017SGR940). GM acknowledges financial support from Fundacio Social La Caixa. MAGM acknowledges funding from the Spanish Ministry of Education and Vocational Training (MEFP) through the Beatriz Galindo program 2018 (BEAGAL18/00203). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU.Munoz-Gil, G.; Garcia March, MA.; Manzo, C.; Martin-Guerrero, JD.; Lewenstein, M. (2020). Single trajectory characterization via machine learning. New Journal of Physics. 22(1):1-9. https://doi.org/10.1088/1367-2630/ab6065S1922

Purification and genetic characterization of gassericin E, a novel co-culture inducible bacteriocin from Lactobacillus gasseri EV1461 isolated from the vagina of a healthy woman

This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) through the Project AGL2012-33400 and AGL2013-41980-P, and by the Junta de Andalucía Excellence Project AGR-07345. These projects included FEDER funds. AMB was the recipient of a post-doctoral grant awarded by the Junta de Andalucía as part of the Project AGR-07345.Background: Lactobacillus gasseri is one of the dominant Lactobacillus species in the vaginal ecosystem. Some strains of this species have a high potential for being used as probiotics in order to maintain vaginal homeostasis, since they may confer colonization resistance against pathogens in the vagina by direct inhibition through production of antimicrobial compounds, as bacteriocins. In this work we have studied bacteriocin production of gassericin E (GasE), a novel bacteriocin produced by L. gasseri EV1461, a strain isolated from the vagina of a healthy woman, and whose production was shown to be promoted by the presence of certain specific bacteria in co-culture. Biochemical and genetic characterization of this novel bacteriocin are addressed. Results: We found that the inhibitory spectrum of L. gasseri EV1461 was broad, being directed to species both related and non-related to the producing strain. Interestingly, L. gasseri EV1461 inhibited the grown of pathogens usually associated with bacterial vaginosis (BV). The antimicrobial activity was due to the production of a novel bacteriocin, gassericin E (GasE). Production of this bacteriocin in broth medium only was achieved at high cell densities. At low cell densities, bacteriocin production ceased and only was restored after the addition of a supernatant from a previous bacteriocin-producing EV1461 culture (autoinduction), or through co-cultivation with several other Gram-positive strains (inducing bacteria). DNA sequence of the GasE locus revealed the presence of two putative operons which could be involved in biosynthesis and immunity of this bacteriocin (gaeAXI), and in regulation, transport and processing (gaePKRTC). The gaePKR encodes a putative three-component regulatory system, involving an autoinducer peptide (GaeP), a histidine protein kinase (GaeK) and a response regulator (GaeR), while the gaeTC encodes for an ABC transporter (GaeT) and their accessory protein (GaeC), involved in transport and processing of the bacteriocin. The gaeAXI, encodes for the bacteriocin gassericin E (GasE), a putative peptide bacteriocin (GaeX), and their immunity protein (GaeI). Conclusions: The origin of the strain (vagina of healthy woman) and its ability to produce bacteriocins with inhibitory activity against vaginal pathogens may be an advantage for using L. gasseri EV1461 as a probiotic strain to fight and/or prevent bacterial infections as bacterial vaginosis (BV), since it could be better adapted to live and compete into the vaginal environment.Publisher PDFPeer reviewe

On the Use of Explainable Artificial Intelligence for the Differential Diagnosis of Pigmented Skin Lesions

En los últimos años, la Inteligencia Artificial Explicable (XAI) ha atraído la atención en la analítica de datos, ya que muestra un gran potencial en la interpretación de los resultados de complejos modelos de aprendizaje automático en la aplicación de problemas médicos. Se trata de que el resultado de las aplicaciones basadas en el aprendizaje automático deben ser comprendidos por los usuarios finales, especialmente en el contexto de los datos médicos, donde las decisiones deben tomarse cuidadosamente. decisiones. Como tal, se han realizado muchos esfuerzos para explicar el resultado de un modelo complejo de aprendizaje profundo en procesos de reconocimiento y clasificación de y clasificación de imágenes, como en el caso del cáncer de melanoma. Este representa un primer intento (hasta donde sabemos) de investigar experimental y técnicamente la explicabilidad de los métodos modernos de XAI modernos de XAI: explicaciones de modelos de diagnóstico interpretables locales (LIME) y Shapley Additive exPlanations (SHAP), en términos de reproducibilidad de resultados y el tiempo de ejecución en un conjunto de datos de clasificación de imágenes de melanoma. Este artículo muestra que los métodos XAI proporcionan ventajas en la interpretación de los resultados del modelo en la clasificación de imágenes de melanoma. interpretación de los resultados del modelo en la clasificación de imágenes de melanoma. Concretamente, LIME se comporta mejor que el explicador de gradiente SHAP en términos de reproducibilidad y tiempo de ejecución.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Transjugular intrahepatic portosystemic shunt (TIPS) in Spain. Clinical-epidemiological considerations in relation to a multicenter registry

Objective: this study aimed to determine the epidemiological, technical and clinical data of transjugular intrahepatic portosystemic shunt (TIPS) performed by Interventional Radiology departments in Spain. Furthermore, the total number of TIPS carried out in Spain was determined and compared with other countries. Material and methods: a retrospective study was performed with the approval of the Ethical Committee of the Spanish Society of Interventional Radiology (SERVEI). A survey was performed with 31 items (demographic, technical and clinical data) for data acquisition on the current status of TIPS in Spain. The survey was sent to the 49 hospitals that SERVEI included in a previous registry with data of TIPS performed in Spain in 2016. Results: of the 49 centers surveyed, 33 (67.35 %) replied to the survey. These centers had completed 265 of the 415 TIPS that year in Spain. The most frequent indication was upper GI bleeding from gastroesophageal varices, which accounted for 144 (54.33 %); 62.26 % of the TIPS were performed urgently and 37.7 % on a scheduled basis. The technical success was 89.16 ± 20.9 %, with a rebleeding rate of 17.9 %. Sixty-nine patients (26.03 %) presented complications, 19.62 % of them minor and 6.41 % major. The 30-day mortality related to the disease was 14.33 %, while mortality at one year was 18.49 %. Conclusion: notably in our study, the complications of TIPS did not show a clear relationship with the number of procedures performed. With regard to other countries like the United States and France, the number of TIPS in Spain per million inhabitants is currently substantially lower. There were no significant changes compared to the number completed in 2013