The Experts below are selected from a list of 141078 Experts worldwide ranked by ideXlab platform
Marina López-nogueroles - One of the best experts on this subject based on the ideXlab platform.
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New screening approach for Alzheimer's disease risk assessment from urine lipid peroxidation compounds
Scientific Reports, 2019Co-Authors: Carmen Peña-bautista, Claire Vigor, Jean-marie Galano, Camille Oger, Thierry Durand, Inés Ferrer, Ana Cuevas, Rogelio López-cuevas, Miguel Baquero, Marina López-noguerolesAbstract:Alzheimer Disease (AD) standard biological diagnosis is based on expensive or invasive procedures. Recent research has focused on some molecular mechanisms involved since early AD stages, such as lipid peroxidation. therefore, a non-invasive screening approach based on new lipid peroxidation compounds determination would be very useful. Well-defined early AD patients and healthy participants were recruited. Lipid peroxidation compounds were determined in urine using a validated analytical method based on liquid chromatography coupled to tandem mass spectrometry. Statistical studies consisted of the evaluation of two different linear (Elastic Net) and non-linear (Random Forest) regression models to discriminate between groups of participants. The regression models fitted to the data from some lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes) in urine as potential predictors of early AD. these prediction models achieved fair validated area under the receiver operating characteristics (AUc-Rocs > 0.68) and their results corroborated each other since they are based on different analytical principles. A satisfactory early screening approach, using two complementary regression models, has been obtained from urine levels of some lipid peroxidation compounds, indicating the Individual Probability of suffering from early AD.
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Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection
Free Radical Biology and Medicine, 2018Co-Authors: Carmen Peña-bautista, Claire Vigor, Jean-marie Galano, Camille Oger, Thierry Durand, Inés Ferrer, Ana Cuevas, Rogelio López-cuevas, Miguel Baquero, Marina López-noguerolesAbstract:Introduction: Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role. Methods: Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment. Results: The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities. Conclusion: A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the Individual Probability of suffering from early AD.
Carmen Peña-bautista - One of the best experts on this subject based on the ideXlab platform.
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New screening approach for Alzheimer's disease risk assessment from urine lipid peroxidation compounds
Scientific Reports, 2019Co-Authors: Carmen Peña-bautista, Claire Vigor, Jean-marie Galano, Camille Oger, Thierry Durand, Inés Ferrer, Ana Cuevas, Rogelio López-cuevas, Miguel Baquero, Marina López-noguerolesAbstract:Alzheimer Disease (AD) standard biological diagnosis is based on expensive or invasive procedures. Recent research has focused on some molecular mechanisms involved since early AD stages, such as lipid peroxidation. therefore, a non-invasive screening approach based on new lipid peroxidation compounds determination would be very useful. Well-defined early AD patients and healthy participants were recruited. Lipid peroxidation compounds were determined in urine using a validated analytical method based on liquid chromatography coupled to tandem mass spectrometry. Statistical studies consisted of the evaluation of two different linear (Elastic Net) and non-linear (Random Forest) regression models to discriminate between groups of participants. The regression models fitted to the data from some lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes) in urine as potential predictors of early AD. these prediction models achieved fair validated area under the receiver operating characteristics (AUc-Rocs > 0.68) and their results corroborated each other since they are based on different analytical principles. A satisfactory early screening approach, using two complementary regression models, has been obtained from urine levels of some lipid peroxidation compounds, indicating the Individual Probability of suffering from early AD.
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Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection
Free Radical Biology and Medicine, 2018Co-Authors: Carmen Peña-bautista, Claire Vigor, Jean-marie Galano, Camille Oger, Thierry Durand, Inés Ferrer, Ana Cuevas, Rogelio López-cuevas, Miguel Baquero, Marina López-noguerolesAbstract:Introduction: Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role. Methods: Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment. Results: The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities. Conclusion: A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the Individual Probability of suffering from early AD.
Jean Mantz - One of the best experts on this subject based on the ideXlab platform.
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Individual Probability of allogeneic erythrocyte transfusion in elective spine surgery the predictive model of transfusion in spine surgery
Anesthesiology, 2009Co-Authors: Brigitte Lenoir, Mariemadeleine Agostini, P Merckx, Catherine Paugamburtz, Cyril Dauzac, Pierre Guigui, Jean MantzAbstract:Background: The aim of this study was to generate a score based on preoperative characteristics and predictive of the Individual Probability of allogeneic erythrocyte transfusion in patients undergoing elective thoracolumbar spine surgery. Methods: Two hundred thirty consecutive patients were retrospectively included over a 15-month period (derivation set). Preoperative independent predictors of erythrocyte transfusion from the day of surgery until postoperative day 5 were determined by multivariable analysis, from which a model of Individual Probability of transfusion was derived and prospectively validated in 125 additional patients (validation set). Results: Four preoperative independent predictors were associated with transfusion: age older than 50 yr (adjusted odds ratio = 4.9 [2-13.5]), preoperative hemoglobin level less than 12 g/dl (adjusted odds ratio = 6.9 [3.1-17.2]), fusion of more than two levels (adjusted odds ratio = 6.7 [3.1-15.2]), and transpedicular osteotomy (adjusted odds ratio = 19.9 [5.6-98.2]). A 0-4 score (0 = no risk, 4 = maximum risk) predictive of allogeneic transfusion was derived by weighting estimate parameters for each variable in a multivariable logistic regression model. Discriminating capacity of the score was 0.86 [0.81-0.92] in the receiver operating characteristics in the derivation sample and 0.83 [0.75-0.91] in the validation sample. The observed transfusion rates in the validation set and the Individual probabilities of erythrocyte transfusion from the score were well correlated (y = 0.98x + 0.04; P < 0.0001), and the observed differences were not statistically different (goodness-of-fit chi-square, P = 0.125). The score was also correlated with the number of erythrocyte units transfused (Spearman p = 0.61; P < 0.0001). Conclusion: The Predictive Model of Transfusion in Spine Surgery may be useful in clinical practice to identify patients undergoing spine surgery at risk of massive bleeding and encourage erythrocyte-saving strategies in these patients.
Tsungyao Chang - One of the best experts on this subject based on the ideXlab platform.
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Continuous learning and inference of Individual Probability of SARS-CoV-2 infection based on interaction data.
Scientific reports, 2021Co-Authors: Shangching Liu, Koyun Liu, Hwaihai Chiang, Jianwei Zhang, Tsungyao ChangAbstract:This study presents a new approach to determine the likelihood of asymptomatic carriers of the SARS-CoV-2 virus by using interaction-based continuous learning and inference of Individual Probability (CLIIP) for contagious ranking. This approach is developed based on an Individual directed graph (IDG), using multi-layer bidirectional path tracking and inference searching. The IDG is determined by the appearance timeline and spatial data that can adapt over time. Additionally, the approach takes into consideration the incubation period and several features that can represent real-world circumstances, such as the number of asymptomatic carriers present. After each update of confirmed cases, the model collects the interaction features and infers the Individual person's Probability of getting infected using the status of the surrounding people. The CLIIP approach is validated using the Individualized bidirectional SEIR model to simulate the contagion process. Compared to traditional contact tracing methods, our approach significantly reduces the screening and quarantine required to search for the potential asymptomatic virus carriers by as much as 94%.
Miguel Baquero - One of the best experts on this subject based on the ideXlab platform.
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New screening approach for Alzheimer's disease risk assessment from urine lipid peroxidation compounds
Scientific Reports, 2019Co-Authors: Carmen Peña-bautista, Claire Vigor, Jean-marie Galano, Camille Oger, Thierry Durand, Inés Ferrer, Ana Cuevas, Rogelio López-cuevas, Miguel Baquero, Marina López-noguerolesAbstract:Alzheimer Disease (AD) standard biological diagnosis is based on expensive or invasive procedures. Recent research has focused on some molecular mechanisms involved since early AD stages, such as lipid peroxidation. therefore, a non-invasive screening approach based on new lipid peroxidation compounds determination would be very useful. Well-defined early AD patients and healthy participants were recruited. Lipid peroxidation compounds were determined in urine using a validated analytical method based on liquid chromatography coupled to tandem mass spectrometry. Statistical studies consisted of the evaluation of two different linear (Elastic Net) and non-linear (Random Forest) regression models to discriminate between groups of participants. The regression models fitted to the data from some lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes) in urine as potential predictors of early AD. these prediction models achieved fair validated area under the receiver operating characteristics (AUc-Rocs > 0.68) and their results corroborated each other since they are based on different analytical principles. A satisfactory early screening approach, using two complementary regression models, has been obtained from urine levels of some lipid peroxidation compounds, indicating the Individual Probability of suffering from early AD.
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Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection
Free Radical Biology and Medicine, 2018Co-Authors: Carmen Peña-bautista, Claire Vigor, Jean-marie Galano, Camille Oger, Thierry Durand, Inés Ferrer, Ana Cuevas, Rogelio López-cuevas, Miguel Baquero, Marina López-noguerolesAbstract:Introduction: Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role. Methods: Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment. Results: The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities. Conclusion: A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the Individual Probability of suffering from early AD.
