| 1. |
- Cescon, Marzia, et al.
(author)
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Predicting Glycemia in Type 1 Diabetes Mellitus with Subspace-Based Linear Multistep Predictors
- 2016
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In: Prediction Methods for Blood Glucose Concentration. - Cham : Springer International Publishing. - 9783319259130 ; , s. 107-132
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Book chapter (peer-reviewed)abstract
- A major challenge for a person with diabetes is to adapt insulin dosage regimens and food intake to keep blood glucose within tolerable limits during daily life activities. The accurate prediction of blood glucose levels in response to inputs would support the patients with invaluable information for appropriate on-the-spot decision making concerning the management of the disease. Against this background, in this paper we propose multistep data-driven predictors to the purpose of predicting blood glucose multiple steps ahead in the future. We formulate the predictors based on the state-space construction step in subspace identification methods for linear systems. The clinical data of 14 type 1 diabetic patients collected during a 3-days long hospital visit were used. We exploited physiological models from the literature to filter the raw information on carbohydrate and insulin intakes in order to retrieve the inputs signals to the predictors. Predictions were based on the collected CGMS measurements, recalibrated against finger stick samples and smoothed through a regularization step. Performances were assessed with respect to YSI blood glucose samples and compared to those achieved with a Kalman filter identified from data. Results proved the competitiveness of the proposed approach.
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| 2. |
- Chargari, Cyrus, et al.
(author)
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Brachytherapy for Pediatric Patients at Gustave Roussy Cancer Campus : A Model of International Cooperation for Highly Specialized Treatments
- 2022
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In: International Journal of Radiation Oncology Biology Physics. - : Elsevier BV. - 0360-3016. ; 113:3, s. 602-613
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Journal article (peer-reviewed)abstract
- Purpose: Childhood cancer is rare, and treatment is frequently associated with long-term morbidity. Disparities in survival and long-term side effects encourage the establishment of networks to increase access to complex organ-conservative strategies, such as brachytherapy. We report our experience of an international cooperation model in childhood cancers. Methods and Materials: We examined the outcome of all children referred to our center from national or international networks to be treated according to a multimodal organ-conservative approach, including brachytherapy. Results: We identified 305 patients whose median age at diagnosis was 2.2 years (range, 1.4 months to 17.2 years). Among these patients, 99 (32.4%) were treated between 2015 and 2020; 172 (56.4%) were referred from national centers; and 133 (43.6%) were international patients from 31 countries (mainly Europe). Also, 263 patients were referred for primary treatment and 42 patients were referred for salvage treatment. Genitourinary tumors were the most frequent sites, with 56.4% bladder/prostate rhabdomyosarcoma and 28.5% gynecologic tumors. In addition to brachytherapy, local treatment consisted of partial tumor resection in 207 patients (67.9%), and 39 patients (13%) had additional external radiation therapy. Median follow-up was 58 months (range, 1 month to 48 years), 93 months for national patients, and 37 months for international patients (P < .0001). Five-year local control, disease-free survival, and overall survival rates were 90.8% (95% confidence interval [CI], 87.3%-94.4%), 84.4% (95% CI, 80.1%-89.0%), and 93.3% (95% CI, 90.1%-96.5%), respectively. Patients referred for salvage treatment had poorer disease-free survival (P < .01). Implementation of image guided pulse-dose-rate brachytherapy was associated with better local control among patients with rhabdomyosarcoma referred for primary treatment (hazard ratio, 9.72; 95% CI, 1.24-71.0). At last follow-up, 16.7% patients had long-term severe treatment-related complications, and 2 patients (0.7%) had developed second malignancy. Conclusions: This retrospective series shows the feasibility of a multinational referral network for brachytherapy allowing high patient numbers in rare pediatric cancers. High local control probability and acceptable late severe complication probability could be achieved despite very challenging situations. This cooperation model could serve as a basis for generating international reference networks for high-tech radiation such as brachytherapy to increase treatment care opportunities and cure probability.
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| 3. |
- Cescon, Marzia, et al.
(author)
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Adaptive Subspace-based prediction of T1DM glycemia
- 2011
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Conference paper (peer-reviewed)abstract
- Blood glucose levels fluctuate widely in Type 1 diabetic patients expecially during stressful situations, intercurrent illness, exercise and changes in meal composition. Furthermore, inter- and intra-subject variability make the prediction of such fluctuations an even harder task. The paper deals with the application of online data-driven multi-step subspace-based patient-specific predictor models to T1DM glycemia prediction, exploiting the interplay between previously injected insulin, meal intake and eventually vital signs. When the unknown underlying model is changing over time we believe such an adaptive scheme may constitute a valuable step towards the development of an advisory tool capable of informing the patient at any time about the evolution of glycemia and possibly give advices on the most appropriate control action to take.
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| 4. |
- Cescon, Marzia, et al.
(author)
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Identification of Individualized Empirical Models of Carbohydrate and Insulin Effects on T1DM Blood Glucose Dynamics
- 2014
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In: International Journal of Control. - : Informa UK Limited. - 0020-7179 .- 1366-5820. ; 87:7, s. 1438-1453
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Journal article (peer-reviewed)abstract
- One of the main limiting factors in improving glucose control for type 1 diabetes mellitus (T1DM) subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing the magnitude and duration of such effects would be useful not only for patients and physicians, but also for the development of a controller targeting glycaemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualised multi-input single-output (MISO) models of the glucose metabolism in T1DM able to reflect the basic dynamical features of the glucose-insulin metabolic system in response to a meal intake or an insulin injection. The models are continuous-time second-order transfer functions relating the amount of carbohydrate of a meal and the insulin units of the accordingly administered dose (inputs) to plasma glucose evolution (output) and consist of few parameters clinically relevant to be estimated. The estimation strategy is continuous-time data-driven system identification and exploits a database in which meals and insulin boluses are separated in time, allowing the unique identification of the model parameters.
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| 5. |
- Cescon, Marzia, et al.
(author)
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Individualized Empirical Models of Carbohydrate and Insulin Effects on T1DM Blood Glucose Dynamics
- 2013
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In: Proc. 2013 IEEE Multi-conference on Systems and Control (MSC2013).
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Conference paper (peer-reviewed)abstract
- ne of the main limiting factors in improving glucose control for T1DM subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing magnitude and duration of such effects would be useful not only for patients and physicians but also for the development of a controller targeting glycemia regulation. Therefore, in this paper we focus on estimating low-complexity yet physiologically sound and individualized MISO models of the glucose metabolism in T1DM able to reflect the basic dynamical features of the glucose-insulin metabolic system in response to a meal intake or an insulin injection. The models are continuous-time second-order transfer functions relating the amount of carbohydrate of a meal and the insulin units of the accordingly administered dose (inputs) to plasma glucose evolution (output) and consist of few parameters clinically relevant to be identified. The estimation strategy is data-driven and exploits a database in which meals and insulin boluses are separated in time, allowing the unique identification of the model parameters.
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| 6. |
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| 7. |
- Cescon, Marzia, et al.
(author)
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Modeling the Impact of a Standardized Breakfast on T1DM Fasting Blood Glucose
- 2012
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Conference paper (peer-reviewed)abstract
- The design of a controller for glycemia regulation, either in open or in closed-‐loop, relies on models able to describe the effects of a meal intake and an insulin injection on blood glucose dynamics. The purpose of this study was therefore to propose a physiological relevant yet parsimonious model for carbohydrate action on fasting blood glucose in T1DM patients when no insulin is taken.
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| 8. |
- Cescon, Marzia, et al.
(author)
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Personalized Short-Term Blood Glucose Prediction in T1DM
- 2012
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Conference paper (peer-reviewed)abstract
- Insulin therapy for tight glycemia regulation in T1DM strongly depends on patients ́ daily decisions about insulin delivery adaptations in relation to: health status, current BG, target BG, insulin sensitivity, diet and foreseen activities. A personalized predictor providing near future BG predictions would support the users in the decision-making tasks while letting them maintaining control over their own treatments management.
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| 9. |
- Cescon, Marzia, et al.
(author)
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Subspace-Based Linear Multi-Step Predictors in Type 1 Diabetes Mellitus
- 2015
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In: Biomedical Signal Processing and Control. - : Elsevier BV. - 1746-8094. ; 22, s. 99-110
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Journal article (peer-reviewed)abstract
- A major challenge for a person with diabetes is to adapt insulin dosage regimens and food intake to keep blood glucose within tolerable limits during daily life activities. The early knowledge about the effects of inputs on glycemia would provide the patients with invaluable information for appropriate on-the-spot decision making concerning the management of the disease. Against this background, in this paper we propose multi-step data-driven predictors to the purpose of predicting blood glucose multiple steps ahead in the future, supporting therefore the patients when deciding upon treatments. We formulate the predictors based on the state-space construction step in subspace identification methods for linear systems. Physiological models from the literature were used to filter the raw information on carbohydrate and insulin intakes in order to retrieve the input signals to the predictors. The clinical data of 14 type 1 diabetic patients collected in hospital during a 3-days long visit were used. Half of the data were employed for predictor development and the remaining half for validation. Mean population prediction error standard deviation on 30 min, 60 min, 90 min, 120 min ahead prediction on validation data resulted in, respectively, 19.17 mg/dL, 37.99 mg/dL, 50.62 mg/dL and 58.06 mg/dL. (C) 2014 Elsevier Ltd. All rights reserved.
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| 10. |
- Jeannot, Frédéric, et al.
(author)
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Imidazopyrazinones (IPYs) : Non-Quinolone Bacterial Topoisomerase Inhibitors Showing Partial Cross-Resistance with Quinolones
- 2018
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In: Journal of Medicinal Chemistry. - : American Chemical Society (ACS). - 0022-2623 .- 1520-4804. ; 61:8, s. 3565-3581
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Journal article (peer-reviewed)abstract
- In our quest for new antibiotics able to address the growing threat of multidrug resistant infections caused by Gram-negative bacteria, we have investigated an unprecedented series of non-quinolone bacterial topoisomerase inhibitors from the Sanofi patrimony, named IPYs for imidazopyrazinones, as part of the Innovative Medicines Initiative (IMI) European Gram Negative Antibacterial Engine (ENABLE) organization. Hybridization of these historical compounds with the quinazolinediones, a known series of topoisomerase inhibitors, led us to a novel series of tricyclic IPYs that demonstrated potential for broad spectrum activity, in vivo efficacy, and a good developability profile, although later profiling revealed a genotoxicity risk. Resistance studies revealed partial cross-resistance with fluoroquinolones (FQs) suggesting that IPYs bind to the same region of bacterial topoisomerases as FQs and interact with at least some of the keys residues involved in FQ binding.
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