Estudio anatómico del fallo del sistema digestivo en el síndrome de disfunción orgánica múltiple

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Facultad de Medicina. Fecha de lectura: 27 de Junio de 201

Active digital entertainment (ade). Social reality, threats and opportunities of virtual physical activity

El presente trabajo es un estudio analíticodocumental que se ha articulado en torno a un objetivo: investigar la relevancia del uso de las consolas de videojuegos vinculadas a la actividad física como una nueva forma de ocio. Para ello, tras la exposición de un detallado análisis socio-histórico de la actividad física digital, se aportan evidencias, por un lado, del impacto económico de estas plataformas y, por otro, de su aplicación a programas de actividad física saludable y beneficios en composición corporal, condición física y recuperación de lesiones. Asimismo se discuten posibles amenazas, y también fortalezas, de este hecho social que los autores denominan: Ocio Digital Activo (ODA). Se concluye que esta realidad es una de las posibilidades que tienen los profesionales de las ciencias del deporte para promover la práctica de la actividad física saludable, aunque existen algunos peligros relativos a su práctica que se deben valorarThis paper is an analytical-documentary study that has been structured around one aim: to research the relevance of the use of video game consoles linked to physical activity as a new form of entertainment. For this purpose, after the exposure of a detailed sociohistorical analysis of digital physical activity, there are provided evidences of the economic impact of these platforms and their applications to healthy physical activity programs and their benefits to body composition, fitness and injuries recovering. Also, possible threats and strengths of this social fact, named Active Digital Entertainment (ADE) by the authors, are discussed. It is concluded that this reality is a real mean for sports science professionals to promote the practice of healthy physical activity, although there are some dangers related to the use of this resource that should be evaluate

Abnormal Maternal Body Mass Index and Customized Fetal Weight Charts : Improving the Identification of Small for Gestational Age Fetuses and Newborns

Background: Obesity and thinness are serious diseases, but cases with abnormal maternal weight have not been excluded from the calculations in the construction of customized fetal growth curves (CCs). Method: To determine if the new CCs, built excluding mothers with an abnormal weight, are better than standard CCs at identifying SGA. A total of 16,122 neonates were identified as SGA, LGA, or AGA, using the two models. Logistic regression and analysis of covariance were used to calculate the OR and CI for adverse outcomes by group. Gestational age was considered as a covariable. Results: The SGA rates by the new CCs and by the standard CCs were 11.8% and 9.7%, respectively. The SGA rate only by the new CCs was 18% and the SGA rate only by the standard CCs was 0.01%. Compared to AGA by both models, SGA by the new CCs had increased rates of cesarean section, (OR 1.53 (95% CI 1.19, 1.96)), prematurity (OR 2.84 (95% CI 2.09, 3.85)), NICU admission (OR 5.41 (95% CI 3.47, 8.43), and adverse outcomes (OR 1.76 (95% CI 1.06, 2.60). The strength of these associations decreased with gestational age. Conclusion: The use of the new CCs allowed for a more accurate identification of SGA at risk of adverse perinatal outcomes as compared to the standard CC

Abnormal Maternal Body Mass Index and Customized Fetal Weight Charts: Improving the Identification of Small for Gestational Age Fetuses and Newborns

Maternal body mass index; Newborn weight; ObesityÍndice de masa corporal materno; Peso del neonato; ObesidadÍndex de massa corporal matern; Pes del nounat; ObesitatBackground: Obesity and thinness are serious diseases, but cases with abnormal maternal weight have not been excluded from the calculations in the construction of customized fetal growth curves (CCs). Method: To determine if the new CCs, built excluding mothers with an abnormal weight, are better than standard CCs at identifying SGA. A total of 16,122 neonates were identified as SGA, LGA, or AGA, using the two models. Logistic regression and analysis of covariance were used to calculate the OR and CI for adverse outcomes by group. Gestational age was considered as a covariable. Results: The SGA rates by the new CCs and by the standard CCs were 11.8% and 9.7%, respectively. The SGA rate only by the new CCs was 18% and the SGA rate only by the standard CCs was 0.01%. Compared to AGA by both models, SGA by the new CCs had increased rates of cesarean section, (OR 1.53 (95% CI 1.19, 1.96)), prematurity (OR 2.84 (95% CI 2.09, 3.85)), NICU admission (OR 5.41 (95% CI 3.47, 8.43), and adverse outcomes (OR 1.76 (95% CI 1.06, 2.60). The strength of these associations decreased with gestational age. Conclusion: The use of the new CCs allowed for a more accurate identification of SGA at risk of adverse perinatal outcomes as compared to the standard CCs

The role of genetic variability in the GABRA6, 5-HTT and BDNF genes in anxiety-related traits

Objective:  The aims of this study were to test the individual association of the serotonin transporter gene (SLC6A4), the brain-derived neurotrophic factor gene (BDNF) and the GABAAα6 receptor subunit gene (GABRA6) with anxiety-related traits and to explore putative gene-gene interactions in a Spanish healthy sample. Method:  A sample of 937 individuals from the general population completed the Temperament and Character Inventory questionnaire to explore Harm Avoidance (HA) dimension; a subsample of 553 individuals also filled in the Big Five Questionnaire to explore the Neuroticism dimension. The whole sample was genotyped for the 5-HTTLPR polymorphism (SLC6A4 gene), the Val66Met polymorphism (BDNF gene) and the T1521C polymorphism (GABRA6 gene). Results:  Homozygous individuals for the T allele of the T1512C polymorphism presented slightly higher scores for HA than C allele carriers (F = 2.96, P = 0.019). In addition, there was a significant gene-gene interaction on HA between the 5-HTTLPR and Val66Met polymorphisms (F = 3.4, P = 0.009). Conclusion:  GABRA6 emerges as a candidate gene involved in the variability of HA. The effect of a significant gene-gene interaction between the SLC6A4 and BDNF genes on HA could explain part of the genetic basis underlying anxiety-related traits

Whole-Blood Mitochondrial DNA Copies Are Associated With the Prognosis of Acute Respiratory Distress Syndrome After Sepsis.

https://pubmed.ncbi.nlm.nih.gov/34557198/#:~:text=Resumen-,El%20s%C3%ADndrome%20de%20dificultad%20respiratoria%20aguda%20(SDRA)%20es%20un%20proceso,v%C3%ADnculos%20mec%C3%A1nicos%20de%20esta%20observaci%C3%B3n%20con%20la%20patogenia%20del%20SDRA.,-Palabras%20clave%3A%20SDR

Activating transcription factor 6 derepression mediates neuroprotection in Huntington disease

Deregulated protein and Ca2+ homeostasis underlie synaptic dysfunction and neurodegeneration in Huntington disease (HD); however, the factors that disrupt homeostasis are not fully understood. Here, we determined that expression of downstream regulatory element antagonist modulator (DREAM), a multifunctional Ca2+-binding protein, is reduced in murine in vivo and in vitro HD models and in HD patients. DREAM downregulation was observed early after birth and was associated with endogenous neuroprotection. In the R6/2 mouse HD model, induced DREAM haplodeficiency or blockade of DREAM activity by chronic administration of the drug repaglinide delayed onset of motor dysfunction, reduced striatal atrophy, and prolonged life span. DREAM-related neuroprotection was linked to an interaction between DREAM and the unfolded protein response (UPR) sensor activating transcription factor 6 (ATF6). Repaglinide blocked this interaction and enhanced ATF6 processing and nuclear accumulation of transcriptionally active ATF6, improving prosurvival UPR function in striatal neurons. Together, our results identify a role for DREAM silencing in the activation of ATF6 signaling, which promotes early neuroprotection in HDThis work was funded by the Instituto de Salud Carlos III/CIBERNED (to J.R. Naranjo, B. Mellström, and A. Rábano), FISS-RIC RD12/0042/0019 (to C. Valenzuela), Madrid regional government/Neurodegmodels (to J.R. Naranjo), MINECO grants SAF2010-21784 and SAF2014-53412-R (to J.R. Naranjo), SAF2012-32209 (to M. Gutierrez-Rodriguez), SAF2010-14916 and SAF2013-45800-R (to C. Valenzuela), and a grant from the Swedish Research Council (J.Y. Li

Assessment of PaO2/FiO2 for stratification of patients with moderate and severe acute respiratory distress syndrome

Objectives: A recent update of the definition of acute respiratory distress syndrome (ARDS) proposed an empirical classification based on ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaO2/FiO2) at ARDS onset. Since the proposal did not mandate PaO2/FiO2 calculation under standardised ventilator settings (SVS), we hypothesised that a stratification based on baseline PaO2/FiO2 would not provide accurate assessment of lung injury severity. Design: A prospective, multicentre, observational study. Setting: A network of teaching hospitals. Participants: 478 patients with eligible criteria for moderate (100300). Primary and secondary outcomes Group severity and hospital mortality. Results: At ARDS onset, 173 patients had a PaO2/FiO2≤100 but only 38.7% met criteria for severe ARDS at 24 h under SVS. When assessed under SVS, 61.3% of patients with severe ARDS were reclassified as moderate, mild and non-ARDS, while lung severity and hospital mortality changed markedly with every PaO2/FiO2 category (p<0.000001). Our model of risk stratification outperformed the stratification using baseline PaO2/FiO2 and non-standardised PaO2/FiO2 at 24 h, when analysed by the predictive receiver operating characteristic (ROC) curve: area under the ROC curve for stratification at baseline was 0.583 (95% CI 0.525 to 0.636), 0.605 (95% CI 0.552 to 0.658) at 24 h without SVS and 0.693 (95% CI 0.645 to 0.742) at 24 h under SVS (p<0.000001). Conclusions: Our findings support the need for patient assessment under SVS at 24 h after ARDS onset to assess disease severity, and have implications for the diagnosis and management of ARDS patients. Trial registration numbers NCT00435110 and NCT00736892

Predicting the length of mechanical ventilation in acute respiratory disease syndrome using machine learning: The PIONEER Study

Background: The ability to predict a long duration of mechanical ventilation (MV) by clinicians is very limited. We assessed the value of machine learning (ML) for early prediction of the duration of MV > 14 days in patients with moderate-to-severe acute respiratory distress syndrome (ARDS). Methods: This is a development, testing, and external validation study using data from 1173 patients on MV ≥ 3 days with moderate-to-severe ARDS. We first developed and tested prediction models in 920 ARDS patients using relevant features captured at the time of moderate/severe ARDS diagnosis, at 24 h and 72 h after diagnosis with logistic regression, and Multilayer Perceptron, Support Vector Machine, and Random Forest ML techniques. For external validation, we used an independent cohort of 253 patients on MV ≥ 3 days with moderate/severe ARDS. Results: A total of 441 patients (48%) from the derivation cohort (n = 920) and 100 patients (40%) from the validation cohort (n = 253) were mechanically ventilated for >14 days [median 14 days (IQR 8–25) vs. 13 days (IQR 7–21), respectively]. The best early prediction model was obtained with data collected at 72 h after moderate/severe ARDS diagnosis. Multilayer Perceptron risk modeling identified major prognostic factors for the duration of MV > 14 days, including PaO2/FiO2, PaCO2, pH, and positive end-expiratory pressure. Predictions of the duration of MV > 14 days showed modest discrimination [AUC 0.71 (95%CI 0.65–0.76)]. Conclusions: Prolonged MV duration in moderate/severe ARDS patients remains difficult to predict early even with ML techniques such as Multilayer Perceptron and using data at 72 h of diagnosis. More research is needed to identify markers for predicting the length of MV. This study was registered on 14 August 2023 at ClinicalTrials.gov (NCT NCT05993377)