Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring

High-throughput data analysis challenges in laboratory automation and lab-on-a-chip devices’ applications are continuously increasing. In cell culture monitoring, specifically, the electrical cell-substrate impedance sensing technique (ECIS), has been extensively used for a wide variety of applications. One of the main drawbacks of ECIS is the need for implementing complex electrical models to decode the electrical performance of the full system composed by the electrodes, medium, and cells. In this work we present a new approach for the analysis of data and the prediction of a specific biological parameter, the fill-factor of a cell culture, based on a polynomial regression, data-analytic model. The method was successfully applied to a specific ECIS circuit and two different cell cultures, N2A (a mouse neuroblastoma cell line) and myoblasts. The data-analytic modeling approach can be used in the decoding of electrical impedance measurements of different cell lines, provided a representative volume of data from the cell culture growth is available, sorting out the difficulties traditionally found in the implementation of electrical models. This can be of particular importance for the design of control algorithms for cell cultures in tissue engineering protocols, and labs-on-a-chip and wearable devices applicationsEspaña, Ministerio de Ciencia e Innovación y Universidades project RTI2018-093512-B-C2

Immunophenotype and Transcriptome Profile of Patients With Multiple Sclerosis Treated With Fingolimod: Setting Up a Model for Prediction of Response in a 2-Year Translational Study

BackgroundFingolimod is a functional sphingosine-1-phosphate antagonist approved for the treatment of multiple sclerosis (MS). Fingolimod affects lymphocyte subpopulations and regulates gene expression in the lymphocyte transcriptome. Translational studies are necessary to identify cellular and molecular biomarkers that might be used to predict the clinical response to the drug. In MS patients, we aimed to clarify the differential effects of fingolimod on T, B, and natural killer (NK) cell subsets and to identify differentially expressed genes in responders and non-responders (NRs) to treatment.Materials and methodsSamples were obtained from relapsing–remitting multiple sclerosis patients before and 6 months after starting fingolimod. Forty-eight lymphocyte subpopulations were measured by flow cytometry based on surface and intracellular marker analysis. Transcriptome sequencing by next-generation technologies was used to define the gene expression profiling in lymphocytes at the same time points. NEDA-3 (no evidence of disease activity) and NEDA-4 scores were measured for all patients at 1 and 2 years after beginning fingolimod treatment to investigate an association with cellular and molecular characteristics.ResultsFingolimod affects practically all lymphocyte subpopulations and exerts a strong effect on genetic transcription switching toward an anti-inflammatory and antioxidant response. Fingolimod induces a differential effect in lymphocyte subpopulations after 6 months of treatment in responder and NR patients. Patients who achieved a good response to the drug compared to NR patients exhibited higher percentages of NK bright cells and plasmablasts, higher levels of FOXP3, glucose phosphate isomerase, lower levels of FCRL1, and lower Expanded Disability Status Scale at baseline. The combination of these possible markers enabled us to build a probabilistic linear model to predict the clinical response to fingolimod.ConclusionMS patients responsive to fingolimod exhibit a recognizable distribution of lymphocyte subpopulations and a different pretreatment gene expression signature that might be useful as a biomarker

Manual de simulación clínica en especialidades médicas

Manual sobre técnicas y modos de simulación clínica en diversas especialidades médicas.La enseñanza y formación en medicina necesita el uso de la simulación. Existen evidencias de su uso desde hace cientos de años, pero, en los últimos años se ha incrementado y diseminado. La simulación clínica está validada científicamente en múltiples contextos médicos y de otras áreas profesionales de la salud. Y es considerada de gran importancia como proceso de entrenamiento y de mejora de las competencias y adquisición de habilidades médicas en campos que incluye desde la historia clínica, comunicación con el paciente, exploración, diagnóstico terapéutica médica-farmacológica y quirúrgica y seguridad al tratar al paciente. Hoy en día, para muchas técnicas y situaciones clínicas es inaceptable llegar junto a los pacientes sin un dominio adquirido en simulación. La simulación puede ocurrir sin el uso de recursos adicionales, solo las personas, o utilizando pocos o muchos recursos de baja hasta alta tecnología y se puede adaptar a los recursos disponibles, abarcando todas las áreas de conocimiento, y dentro de ellas competencias técnicas o actitudes, solas o en conjunto. El uso racional y basado en evidencia de la simulación es de la mayor importancia por la necesidad de una mayor efectividad y eficiencia en la transformación de los profesionales de la salud para que puedan mejorar su capacidad de atender a los pacientes. La simulación es también una buena herramienta de evaluación de competencias y habilidades en Medicina y otras disciplinas de las Ciencias de la Salud Este manual incluye técnicas y modos de simulación clínica en diversas especialidades médicas, útiles, para quien busque un manual práctico y actualizado.Cátedra de Mecenazgo de la Universidad de Málaga. Cátedra de Terapias Avanzadas en Patología Cardiovascular Cátedra de Mecenazgo de la Universidad de Málaga. Cátedra de Investigación Biomédica Quirón Salu

Games without secrets: The App which teaches youngsters with intellectual disabilities about sexuality

El trabajo de las investigadoras de la Universidad del Rosario, ángela María Ruiz, Lilia Virginia García e Inés Elvira Restrepo, con esta población permitió conocer a fondo su realidad y crear una novedosa herramienta para que estos niños y jóvenes no sean víctimas de abuso y se respeten sus derechos.A study of this sector of the population by ángela María Ruiz, Lilia Virginia García and Inés Elvira Restrepo, researchers at the Universidad de Rosario, enabled them to attain an indepth understanding of their reality and create a novel tool to prevent these children and youngsters from becoming the victims of abuse and ensure that their rights are respected

Immunophenotype and Transcriptome Profile of Patients With Multiple Sclerosis Treated With Fingolimod: Setting Up a Model for Prediction of Response in a 2-Year Translational Study

Background: Fingolimod is a functional sphingosine-1-phosphate antagonist approved for the treatment of multiple sclerosis (MS). Fingolimod affects lymphocyte subpopulations and regulates gene expression in the lymphocyte transcriptome. Translational studies are necessary to identify cellular and molecular biomarkers that might be used to predict the clinical response to the drug. In MS patients, we aimed to clarify the differential effects of fingolimod on T, B, and natural killer (NK) cell subsets and to identify differentially expressed genes in responders and non-responders (NRs) to treatment. Materials and methods: Samples were obtained from relapsing-remitting multiple sclerosis patients before and 6 months after starting fingolimod. Forty-eight lymphocyte subpopulations were measured by flow cytometry based on surface and intracellular marker analysis. Transcriptome sequencing by next-generation technologies was used to define the gene expression profiling in lymphocytes at the same time points. NEDA-3 (no evidence of disease activity) and NEDA-4 scores were measured for all patients at 1 and 2 years after beginning fingolimod treatment to investigate an association with cellular and molecular characteristics. Results: Fingolimod affects practically all lymphocyte subpopulations and exerts a strong effect on genetic transcription switching toward an anti-inflammatory and antioxidant response. Fingolimod induces a differential effect in lymphocyte subpopulations after 6 months of treatment in responder and NR patients. Patients who achieved a good response to the drug compared to NR patients exhibited higher percentages of NK bright cells and plasmablasts, higher levels of FOXP3, glucose phosphate isomerase, lower levels of FCRL1, and lower Expanded Disability Status Scale at baseline. The combination of these possible markers enabled us to build a probabilistic linear model to predict the clinical response to fingolimod. Conclusion: MS patients responsive to fingolimod exhibit a recognizable distribution of lymphocyte subpopulations and a different pretreatment gene expression signature that might be useful as a biomarker.This work was mostly supported by grants from Novartis (PI110/13 JGM-INM2014-01) and Fondo de Investigación Sanitaria FIS PI12/02672 and PI15/02099 integrated in the Plan Nacional de I+D+I (2008–2011 and 2013–2016, respectively), supported by the ISCIII—subdirección General de Evaluación and co-financed by the Fondo Europeo de Desarrollo Regional (FEDER). The funding sources had no involvement in the study design, data collection, analysis, interpretation, preparation of the manuscript, and the decision to submit the article for publication.S

Immunophenotype and Transcriptome Profile of Patients With Multiple Sclerosis Treated With Fingolimod: Setting Up a Model for Prediction of Response in a 2-Year Translational Study

International audienc

Evaluación del Practicum en industria del Master Universitario de Investigación, Desarrollo y Control de Medicamentos

Podeu consultar la Setena trobada de professorat de Ciències de la Salut completa a: http://hdl.handle.net/2445/43352El principal objetivo de este estudio, que forma parte del proyecto REDICE2010, fue evaluar el practicum de industria del Máster Universitario de Investigación, Desarro-llo y Control de Medicamentos, que se imparte en la Facultad de Farmacia de la UB y su repercusión en las asignaturas relacionadas. Dado que este período de prácticas, que se realiza en una industria del sector far-macéutico o afín, debe proporcionar al alumnado competencias y habilidades que les capacitan para la actividad profesional, se ha recabado la opinión tanto de los estudiantes (actuales y egresados del máster) como de los tutores de la industria y de la universidad y de expertos en el sector industrial y académico que aportan su visión sobre la formación idónea de los alumnos para afrontar con éxito los retos profesionales, a fin de detectar debilidades formativas en el máster y establecer mecanismos de mejora

Data_Sheet_1_Immunophenotype and Transcriptome Profile of Patients With Multiple Sclerosis Treated With Fingolimod: Setting Up a Model for Prediction of Response in a 2-Year Translational Study.PDF

Background<p>Fingolimod is a functional sphingosine-1-phosphate antagonist approved for the treatment of multiple sclerosis (MS). Fingolimod affects lymphocyte subpopulations and regulates gene expression in the lymphocyte transcriptome. Translational studies are necessary to identify cellular and molecular biomarkers that might be used to predict the clinical response to the drug. In MS patients, we aimed to clarify the differential effects of fingolimod on T, B, and natural killer (NK) cell subsets and to identify differentially expressed genes in responders and non-responders (NRs) to treatment.</p>Materials and methods<p>Samples were obtained from relapsing–remitting multiple sclerosis patients before and 6 months after starting fingolimod. Forty-eight lymphocyte subpopulations were measured by flow cytometry based on surface and intracellular marker analysis. Transcriptome sequencing by next-generation technologies was used to define the gene expression profiling in lymphocytes at the same time points. NEDA-3 (no evidence of disease activity) and NEDA-4 scores were measured for all patients at 1 and 2 years after beginning fingolimod treatment to investigate an association with cellular and molecular characteristics.</p>Results<p>Fingolimod affects practically all lymphocyte subpopulations and exerts a strong effect on genetic transcription switching toward an anti-inflammatory and antioxidant response. Fingolimod induces a differential effect in lymphocyte subpopulations after 6 months of treatment in responder and NR patients. Patients who achieved a good response to the drug compared to NR patients exhibited higher percentages of NK bright cells and plasmablasts, higher levels of FOXP3, glucose phosphate isomerase, lower levels of FCRL1, and lower Expanded Disability Status Scale at baseline. The combination of these possible markers enabled us to build a probabilistic linear model to predict the clinical response to fingolimod.</p>Conclusion<p>MS patients responsive to fingolimod exhibit a recognizable distribution of lymphocyte subpopulations and a different pretreatment gene expression signature that might be useful as a biomarker.</p