Predictores del estado post-ictus en el alta hospitalaria. Importancia en enfermería

Nurses are often asked to predict factors that influence post-stroke outcome by the patient and family. Many studies have been carried out in order to determine the factors that influence the neurological status of the post-stroke patient at the moment of the discharge from the hospital. However, machine learning techniques have not been used for this purpose. Therefore, with the objective of obtaining association rules of neurological prognosis, a double analysis, both clinical and with machine learning techniques of the possible associations of factors that influence the neurological status of the post-stroke patients has been carried out. The Apriori algorithm detected several association rules with high confidence (≥ 95%), from which the following pattern: In patients in the age range of 50-80 years, the association of a NIHSS between 11 and 15 points (intermediate/low NIHSS), along with thrombectomy, leads to recovery ad integrum at discharge. With the SMOTE resampling technique, the 100% confidence was reached for the association of high NIHSS (>20) and involvement of the carotid and basilar arteries, with a dire prognosis (exitus). These rules confirm, for the first time with machine learning, the importance of the association of some predictors, in the post-stroke prognosis. The knowledge by the nurses of these association rules can successfully improve stroke outcome. In addition, the role of nurses in education programs that teach knowledge of risk factors and stroke prognosis becomes essential.A menudo, por parte del paciente y de la familia, se solicita a los profesionales de enfermería que predigan los factores que influyen en el estado post-ictus. Se han realizado numerosos estudios para determinar los factores que influyen en el estado neurológico post-ictus en el momento del alta hospitalaria. Sin embargo, las técnicas de aprendizaje automático no se han utilizado para este propósito. Con el objetivo de obtener reglas de asociación del pronóstico neurológico, se ha llevado a cabo un doble análisis, tanto clínico como con técnicas de aprendizaje automático, de las posibles asociaciones de factores que influyen en el estado neurológico de los pacientes post-ictus. El algoritmo Apriori detectó varias reglas de asociación con alta confianza (≥ 95%), con el siguiente patrón: En pacientes en el rango de edad de 50-80 años, la asociación de un NIHSS entre 11 y 15 puntos (NIHSS intermedio/bajo), junto con la trombectomía, conduce a la recuperación ad integrum al alta. Con la técnica de remuestreo SMOTE, se alcanzó el 100% de confianza para la asociación de NIHSS elevado (>20) y afectación de las arterias carótida y basilar, con pronóstico nefasto (exitus). Estas reglas confirman, por primera vez con aprendizaje automático, la importancia de la asociación de algunos predictores, en el pronóstico post-ictus. El conocimiento por parte de las enfermeras de estas reglas puede mejorar los resultados del ictus. Adicionalmente, el papel de la enfermería en los programas de educación sobre los factores de riesgo, y pronóstico de un ictus se torna imprescindible

Diseño e incorporación de un banco virtual de imágenes en cariología como apoyo virtual a la docencia presencial

Memoria ID-0047. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2015-2016

Puesta en marcha del inicio a la investigación virtual en odontología conservadora

Memoria ID-0043. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2014-2015

Simulación Clínica en la enseñanza práctica de la Reanimación Cardiopulmonar en el Grado de Odontología

Memoria ID12-0140. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2012-2013

Utilización del maniquí de alta afinidad SinMan3G para adquisición de habilidades en el Grado en Medicina

Memoria ID-0185. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2015-2016

Strategy for the identification of the tumor intrinsic QTL determining the response to treatment of ERBB2 breast cancer

Resumen del póster presentado al VII Simposium Bases Biológicas del Cáncer y Terapias Personalizadas, celebrado en el Centro de Investigación del Cáncer (CIC-IBMCC) del 21 al 22 de mayo de 2015.-- et al.Este póster ha ganado el 1er premio en el Concurso de Pósters de Oncología Básica y Traslacional en Oncología para Jóvenes Investigadores, celebrado durante el VII Simposium Bases Biológicas del Cáncer y Terapias Personalizadas.An essential aspect of breast cancer is its different evolution among patients with the same histopathological disease. Moreover, cancer is a tissue growing in the context of a complex organism, thus it can be identified two main sources of variability responsible for the disease behavior: intrinsic and extrinsic factors which act, respectively, mainly inside the tumor cells and outside them at local or systemic levels. Our aim is to identify intrinsic factors to the tumor cells responsible for the different responses of breast cancer to chemotherapy with Doxorubicin and Docetaxel. For this purpose, we collected tumors developed in a cohort of genetically heterogeneous mice from a backcross between a resistant strain to breast cancer (C57BL/6) and a susceptible one (FVB) which overexpress the cNeu/ErbB2 protooncogene controlled by the MMTV promoter. The backcross mice were genotyped by SNP analysis. To identify tumor intrinsic factors controlling the response to chemotherapy, we transplanted 125 tumors collected from the backcross mice into singenic F1-C57/FVB mice to remove variability coming from the host compartments. Each tumor was transplanted into two F1 recipient mice; each one was treated with Doxorubicin or Docetaxel, and we studied tumor response to treatment. Linkage analysis permits us to identify QTL (Quantitative Trait Loci) controlling susceptibility to mammary cancer and evolution of the disease in the backcross population, and the specific intrinsic QTL associated with different chemotherapy responses in the F1 mice. Moreover, we are studying molecular and signalling pathways that control chemotherapy responses and the QTL associated with them. The identification of breast cancer susceptibility genes and their pathways associated with different response to chemotherapy will be important for the prediction of human breast cancer evolution during therapy, and to learn about the mechanisms involved in resistance to chemotherapy, thus it would help to develop new preventive and therapeutic strategies.Peer Reviewe

A new role of SNAI2 in postlactational involution of the mammary gland links it to luminal breast cancer development

PMCID: PMC4560637Breast cancer is a major cause of mortality in women. The transcription factor SNAI2 has been implicated in the pathogenesis of several types of cancer, including breast cancer of basal origin. Here we show that SNAI2 is also important in the development of breast cancer of luminal origin in MMTV-ErbB2 mice. SNAI2 deficiency leads to longer latency and fewer luminal tumors, both of these being characteristics of pretumoral origin. These effects were associated with reduced proliferation and a decreased ability to generate mammospheres in normal mammary glands. However, the capacity to metastasize was not modified. Under conditions of increased ERBB2 oncogenic activity after pregnancy plus SNAI2 deficiency, both pretumoral defects - latency and tumor load - were compensated. However, the incidence of lung metastases was dramatically reduced. Furthermore, SNAI2 was required for proper postlactational involution of the breast. At 3 days post lactational involution, the mammary glands of Snai2-deficient mice exhibited lower levels of pSTAT3 and higher levels of pAKT1, resulting in decreased apoptosis. Abundant noninvoluted ducts were still present at 30 days post lactation, with a greater number of residual ERBB2+ cells. These results suggest that this defect in involution leads to an increase in the number of susceptible target cells for transformation, to the recovery of the capacity to generate mammospheres and to an increase in the number of tumors. Our work demonstrates the participation of SNAI2 in the pathogenesis of luminal breast cancer, and reveals an unexpected connection between the processes of postlactational involution and breast tumorigenesis in Snai2-null mutant mice.JPL was partially supported by FEDER and MICINN (PLE2009-119, SAF2014-56989-R), Instituto de Salud Carlos III (PI07/0057, PI10/00328, PIE14/00066), Junta de Castilla y León (SAN673/SA26/08, SAN126/SA66/09, SA078A09, CSI034U13), the “Fundación Eugenio Rodríguez Pascual”, the “Fundación Inbiomed” (Instituto Oncológico Obra Social de la Caja Guipozcoa-San Sebastian, Kutxa), and the “Fundación Sandra Ibarra de Solidaridad frente al Cáncer”. AC was supported by FIS (PI07/0057) and MICINN (PLE2009-119). SCLL was funded by a JAEdoc Fellowship (CSIC)/FSE. MMSF and ABG are funded by fellowships from the Junta de Castilla y Leon. JHM was supported by the National Institutes of Health, a National Cancer Institute grant (R01 CA116481), and the Low-Dose Scientific Focus Area, Office of Biological & Environmental Research, US Department of Energy (DE-AC02-05CH11231).Peer Reviewe

The biological age linked to oxidative stress modifies breast cancer aggressiveness

The incidence of breast cancer increases with age until menopause, and breast cancer is more aggressive in younger women. The existence of epidemiological links between breast cancer and aging indicates that both processes share some common mechanisms of development. Oxidative stress is associated with both cancer susceptibility and aging. Here we observed that ERBB2-positive breast cancer, which developed in genetically heterogeneous ERBB2-positive transgenic mice generated by a backcross, is more aggressive in chronologically younger than in older mice (differentiated by the median survival of the cohort that was 79 weeks), similar to what occurs in humans. In this cohort, we estimated the oxidative biological age using a mathematical model that integrated several subphenotypes directly or indirectly related to oxidative stress. The model selected the serum levels of HDL-cholesterol and magnesium and total AKT1 and glutathione concentrations in the liver. The grade of aging was calculated as the difference between the predicted biological age and the chronological age. This comparison permitted the identification of biologically younger and older mice compared with their chronological age. Interestingly, biologically older mice developed more aggressive breast cancer than the biologically younger mice. Genomic regions on chromosomes 2 and 15 linked to the grade of oxidative aging were identified. The levels of expression of Zbp1 located on chromosome 2, a gene related to necroptosis and inflammation, positively correlated with the grade of aging and tumour aggressiveness. Moreover, the pattern of gene expression of genes linked to the inflammation and the response to infection pathways was enriched in the livers of biologically old mice. This study shows part of the complex interactions between breast cancer and aging.JPL was partially supported by FEDER and the MICINN (SAF2014-56989-R and SAF2017-88854R), the Instituto de Salud Carlos III (PIE14/00066), >Proyectos Integrados IBSAL 2015> (IBY15/00003), the Sandra Ibarra Foundation >de Solidaridad Frente al Cáncer> Foundation and >We can be heroes> Foundation. JHM was supported by the National Institutes of Health, a National Cancer Institute grant (R01 CA116481), and the Low-Dose Scientific Focus Area, Office of Biological & Environmental Research, US Department of Energy (DE-AC02-05CH11231).Peer Reviewe