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2. Storage effect on olive oil phenols: cultivar-specific responses.

Author

Vendrell Calatayud, Mario, Li, Xueqi, Brizzolara, Stefano, Tonutti, Pietro, and Wang, Selina

Subjects
oil composition, olive cultivars, oxidation, phenols, quality
Abstract

INTRODUCTION: Olive oil is a widely recognized and appreciated food commodity, its quality and health benefits can be compromised when the oil goes through oxidative processes that may occur during production and storage. This study aimed to investigate the effects of the olive genotype on polar phenolic content after seven months of storage. METHODS: Oil produced from eight different olive cultivars (Leccino, Leccio del Corno, Moraiolo, Frantoio, Bianchera, Pendolino, Maurino, and Caninese) grown in southern Tuscany, Italy, were subjected to chemical analysis such as free fatty acids, peroxide value, K232 and K268, phenolics and UPLC-DAD at the beginning of the trial (Control) and seven months later (Stored). RESULTS AND CONCLUSIONS: Free fatty acids, peroxide values, K232 and K268, significantly increased, suggesting heightened hydrolysis and oxidation after storage. A cultivar effect was observed, with Leccino, Moraiolo, and Pendolino showing less susceptibility to oxidation (low differences between Control and Stored). In contrast, others (Bianchera and Caninese) are more affected (higher differences between Control and Stored). Phenolics analysis supports this observation, revealing that samples with higher resistance to oxidation exhibit elevated levels of hydroxytyrosol, tyrosol, vanillic acid, caffeic acid, p-coumaric acid, and ferulic acid. Principal Component Analysis highlights that Bianchera and Caninese cultivars correlate with rutin, tyrosol, and pinoresinol. As this research delves into the intricate relationship between genotype diversity, phenolic composition, and oxidative stability, a nuanced understanding emerges, shedding light on how different cultivars may present varying compositions and concentrations of phenols, ultimately influencing the oils resistance to the oxidation that occurred during storage.

Published
2024

4. Reducing crop losses by gene-editing control of organ developmental physiology

Author

Tonutti, Pietro, Brizzolara, Stefano, and Beckles, Diane M

Subjects
Agricultural, Veterinary and Food Sciences, Crop and Pasture Production, Horticultural Production, Genetics, Gene Editing, Edible Grain, Genomics, Phenotype, Promoter Regions, Genetic, Biological Sciences, Engineering, Technology, Biotechnology, Agricultural biotechnology, Industrial biotechnology, Medical biotechnology
Abstract

Some physiological processes in reproductive organs, if not controlled, can lead to crop loss even in the absence of environmental stress. These processes may occur pre- or post- harvest, and in diverse species and include abscission processes in cereal grain, e.g., shattering and in immature fruit, e.g., preharvest drop, preharvest sprouting of cereals, and postharvest senescence in fruit. Some of the molecular mechanisms and genetic determinants underlying these processes are now better detailed, making it possible to refine them by gene editing. Here, we discuss using advanced genomics to identify genetic determinants underlying crop physiological traits. Examples of improved phenotypes developed for preharvest problems are provided, and suggestions for reducing postharvest fruit losses by gene and promoter editing were made.

Published
2023

5. A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patients

Author

Izdebski, Adam, Thoral, Patrick J., Lalisang, Robbert C. A., McHugh, Dean M., Gommers, Diederik, Cremer, Olaf L., Bosman, Rob J., Rigter, Sander, Wils, Evert-Jan, Frenzel, Tim, Dongelmans, Dave A., de Jong, Remko, Peters, Marco A. A., Kamps, Marlijn J. A, Ramnarain, Dharmanand, Nowitzky, Ralph, Nooteboom, Fleur G. C. A., de Ruijter, Wouter, Urlings-Strop, Louise C., Smit, Ellen G. M., Mehagnoul-Schipper, D. Jannet, Dormans, Tom, de Jager, Cornelis P. C., Hendriks, Stefaan H. A., Achterberg, Sefanja, Oostdijk, Evelien, Reidinga, Auke C., Festen-Spanjer, Barbara, Brunnekreef, Gert B., Cornet, Alexander D., Tempel, Walter van den, Boelens, Age D., Koetsier, Peter, Lens, Judith, Faber, Harald J., Karakus, A., Entjes, Robert, de Jong, Paul, Rettig, Thijs C. D., Arbous, Sesmu, Fleuren, Lucas M., Dam, Tariq A., Tonutti, Michele, de Bruin, Daan P., Elbers, Paul W. G., and Cinà, Giovanni

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Despite the recent progress in the field of causal inference, to date there is no agreed upon methodology to glean treatment effect estimation from observational data. The consequence on clinical practice is that, when lacking results from a randomized trial, medical personnel is left without guidance on what seems to be effective in a real-world scenario. This article proposes a pragmatic methodology to obtain preliminary but robust estimation of treatment effect from observational studies, to provide front-line clinicians with a degree of confidence in their treatment strategy. Our study design is applied to an open problem, the estimation of treatment effect of the proning maneuver on COVID-19 Intensive Care patients.

Published
2021

8. Uncertainty estimation for classification and risk prediction on medical tabular data

Author

Meijerink, Lotta, Cinà, Giovanni, and Tonutti, Michele

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

In a data-scarce field such as healthcare, where models often deliver predictions on patients with rare conditions, the ability to measure the uncertainty of a model's prediction could potentially lead to improved effectiveness of decision support tools and increased user trust. This work advances the understanding of uncertainty estimation for classification and risk prediction on medical tabular data, in a two-fold way. First, we expand and refine the set of heuristics to select an uncertainty estimation technique, introducing tests for clinically-relevant scenarios such as generalization to uncommon pathologies, changes in clinical protocol and simulations of corrupted data. We furthermore differentiate these heuristics depending on the clinical use-case. Second, we observe that ensembles and related techniques perform poorly when it comes to detecting out-of-domain examples, a critical task which is carried out more successfully by auto-encoders. These remarks are enriched by considerations of the interplay of uncertainty estimation with class imbalance, post-modeling calibration and other modeling procedures. Our findings are supported by an array of experiments on toy and real-world data.

Published
2020

9. Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications

Author

Ruhe, David, Cinà, Giovanni, Tonutti, Michele, de Bruin, Daan, and Elbers, Paul

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

The Intensive Care Unit (ICU) is a hospital department where machine learning has the potential to provide valuable assistance in clinical decision making. Classical machine learning models usually only provide point-estimates and no uncertainty of predictions. In practice, uncertain predictions should be presented to doctors with extra care in order to prevent potentially catastrophic treatment decisions. In this work we show how Bayesian modelling and the predictive uncertainty that it provides can be used to mitigate risk of misguided prediction and to detect out-of-domain examples in a medical setting. We derive analytically a bound on the prediction loss with respect to predictive uncertainty. The bound shows that uncertainty can mitigate loss. Furthermore, we apply a Bayesian Neural Network to the MIMIC-III dataset, predicting risk of mortality of ICU patients. Our empirical results show that uncertainty can indeed prevent potential errors and reliably identifies out-of-domain patients. These results suggest that Bayesian predictive uncertainty can greatly improve trustworthiness of machine learning models in high-risk settings such as the ICU., Comment: Presented at AISG @ ICML2019: https://aiforsocialgood.github.io/icml2019/index.htm

Published
2019

12. Robust and Subject-Independent Driving Manoeuvre Anticipation through Domain-Adversarial Recurrent Neural Networks

Author

Tonutti, Michele, Ruffaldi, Emanuele, Cattaneo, Alessandro, and Avizzano, Carlo Alberto

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning, 68T99, I.2.m
Abstract

Through deep learning and computer vision techniques, driving manoeuvres can be predicted accurately a few seconds in advance. Even though adapting a learned model to new drivers and different vehicles is key for robust driver-assistance systems, this problem has received little attention so far. This work proposes to tackle this challenge through domain adaptation, a technique closely related to transfer learning. A proof of concept for the application of a Domain-Adversarial Recurrent Neural Network (DA-RNN) to multi-modal time series driving data is presented, in which domain-invariant features are learned by maximizing the loss of an auxiliary domain classifier. Our implementation is evaluated using a leave-one-driver-out approach on individual drivers from the Brain4Cars dataset, as well as using a new dataset acquired through driving simulations, yielding an average increase in performance of 30% and 114% respectively compared to no adaptation. We also show the importance of fine-tuning sections of the network to optimise the extraction of domain-independent features. The results demonstrate the applicability of the approach to driver-assistance systems as well as training and simulation environments., Comment: 40 pages, 4 figures. Published online in Robotics and Autonomous Systems

Published
2019
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18. Predictors for extubation failure in COVID-19 patients using a machine learning approach

Author

Fleuren, Lucas M., Dam, Tariq A., Tonutti, Michele, de Bruin, Daan P., Lalisang, Robbert C. A., Gommers, Diederik, Cremer, Olaf L., Bosman, Rob J., Rigter, Sander, Wils, Evert-Jan, Frenzel, Tim, Dongelmans, Dave A., de Jong, Remko, Peters, Marco, Kamps, Marlijn J. A., Ramnarain, Dharmanand, Nowitzky, Ralph, Nooteboom, Fleur G. C. A., de Ruijter, Wouter, Urlings-Strop, Louise C., Smit, Ellen G. M., Mehagnoul-Schipper, D. Jannet, Dormans, Tom, de Jager, Cornelis P. C., Hendriks, Stefaan H. A., Achterberg, Sefanja, Oostdijk, Evelien, Reidinga, Auke C., Festen-Spanjer, Barbara, Brunnekreef, Gert B., Cornet, Alexander D., van den Tempel, Walter, Boelens, Age D., Koetsier, Peter, Lens, Judith, Faber, Harald J., Karakus, A., Entjes, Robert, de Jong, Paul, Rettig, Thijs C. D., Arbous, Sesmu, Vonk, Sebastiaan J. J., Fornasa, Mattia, Machado, Tomas, Houwert, Taco, Hovenkamp, Hidde, Noorduijn Londono, Roberto, Quintarelli, Davide, Scholtemeijer, Martijn G., de Beer, Aletta A., Cinà, Giovanni, Kantorik, Adam, de Ruijter, Tom, Herter, Willem E., Beudel, Martijn, Girbes, Armand R. J., Hoogendoorn, Mark, Thoral, Patrick J., and Elbers, Paul W. G.

Published
2021
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19. The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Author

Fleuren, Lucas M., Dam, Tariq A., Tonutti, Michele, de Bruin, Daan P., Lalisang, Robbert C. A., Gommers, Diederik, Cremer, Olaf L., Bosman, Rob J., Rigter, Sander, Wils, Evert-Jan, Frenzel, Tim, Dongelmans, Dave A., de Jong, Remko, Peters, Marco, Kamps, Marlijn J. A., Ramnarain, Dharmanand, Nowitzky, Ralph, Nooteboom, Fleur G. C. A., de Ruijter, Wouter, Urlings-Strop, Louise C., Smit, Ellen G. M., Mehagnoul-Schipper, D. Jannet, Dormans, Tom, de Jager, Cornelis P. C., Hendriks, Stefaan H. A., Achterberg, Sefanja, Oostdijk, Evelien, Reidinga, Auke C., Festen-Spanjer, Barbara, Brunnekreef, Gert B., Cornet, Alexander D., van den Tempel, Walter, Boelens, Age D., Koetsier, Peter, Lens, Judith, Faber, Harald J., Karakus, A., Entjes, Robert, de Jong, Paul, Rettig, Thijs C. D., Arbous, Sesmu, Vonk, Sebastiaan J. J., Fornasa, Mattia, Machado, Tomas, Houwert, Taco, Hovenkamp, Hidde, Noorduijn-Londono, Roberto, Quintarelli, Davide, Scholtemeijer, Martijn G., de Beer, Aletta A., Cina, Giovanni, Beudel, Martijn, Herter, Willem E., Girbes, Armand R. J., Hoogendoorn, Mark, Thoral, Patrick J., and Elbers, Paul W. G.

Published
2021
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21. Charge Transfer and Charge Broadening of GEM Structures in High Magnetic Fields

Author

Killenberg, M., Lotze, S., Mnich, J., Muennich, A., Roth, S., Sefkow, F., Tonutti, M., Weber, M., and Wienemann, P.

Subjects
Physics - Instrumentation and Detectors
Abstract

We report on measurements of charge transfer in GEM structures in high magnetic fields. These were performed in the framework of the R&D work for a Time Projection Chamber at a future Linear Collider. A small test chamber has been installed into the aperture of a superconducting magnet with the GEM structures mounted perpendicular to the B field direction. The charge transfer is derived from the electrical currents monitored during irradiation with an ${}^{55}$Fe source. No severe loss of primary ionisation charge is observed, but an improved ion feedback suppression is achieved for high magnetic fields. Additionally, the width of the charge cloud released by individual ${}^{55}$Fe photons is measured using a finely segmented strip readout after the triple GEM structure. Charge widths between 0.3 and 0.5 mm RMS are observed, which originate from the charge broadening inside the GEM readout. This charge broadening is only partly suppressed at high magnetic fields., Comment: 11 pages, 9 figures

Published
2004
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22. Modelling and Measurement of Charge Transfer in Multiple GEM Structures

Author

Killenberg, M., Lotze, S., Mnich, J., Roth, S., Schulte, R., Sobloher, B., Struczinski, W., and Tonutti, M.

Subjects
Physics - Instrumentation and Detectors
Abstract

Measurements and numerical simulations on the charge transfer in Gas Electron Multiplier (GEM) foils are presented and their implications for the usage of GEM foils in Time Projection Chambers are discussed. A small test chamber has been constructed and operated with up to three GEM foils. The charge transfer parameters derived from the electrical currents monitored during the irradiation with an Fe-55 source are compared with numerical simulations. The performance in magnetic fields up to 2 T is also investigated., Comment: 21 pages, 16 figures, submitted to NIM-A

Published
2002
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30. The ANA-reflex test as a model for improving clinical appropriateness in autoimmune diagnostics

Author

Tonutti, Elio, Bizzaro, Nicola, Morozzi, Gabriella, Radice, Antonella, Cinquanta, Luigi, Villalta, Danilo, Tozzoli, Renato, Tampoia, Marilina, Porcelli, Brunetta, Fabris, Martina, Brusca, Ignazio, Alessio, Maria Grazia, Barberio, Giuseppina, Sorrentino, Maria Concetta, Antico, Antonio, Bassetti, Danila, Fontana, Desré Ethel, Imbastaro, Tiziana, Visentini, Daniela, Pesce, Giampaola, Bagnasco, Marcello, and On behalf of the Study Group on Autoimmune Diseases of the Italian Society of Clinical Pathology and Laboratory Medicine

Published
2016
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34. Influence of dietary fat and carbohydrates proportions on plasma lipids, glucose control and low-grade inflammation in patients with type 2 diabetes—The TOSCA.IT Study

Author

Vitale, M., Masulli, M., Rivellese, A. A., Babini, A. C., Boemi, M., Bonora, E., Buzzetti, R., Ciano, O., Cignarelli, M., Cigolini, M., Clemente, G., Citro, G., Corsi, L., Dall’Aglio, E., Del Prato, S., Di Cianni, G., Dolci, M. A., Giordano, C., Iannarelli, R., Iovine, C., Lapolla, A., Lauro, D., Leotta, S., Mazzucchelli, C., Montani, V., Perriello, G., Romano, G., Romeo, F., Santarelli, L., di Cola, R. Schiano, Squatrito, S., Tonutti, L., Trevisan, R., Turco, A. A., Zamboni, C., Riccardi, G., and Vaccaro, O.

Published
2016
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39. Il test ANA-reflex

Author

Tonutti, Elio, Bizzaro, Nicola, Morozzi, Gabriella, Tozzoli, Renato, Villalta, Danilo, Tampoia, Marilina, Porcelli, Brunetta, Radice, Antonella, Fabris, Martina, Barberio, Giuseppina, Alessio, Maria Grazia, Brusca, Ignazio, Manfredi, Maria Angela, Amato, Gaetano, Sorrentino, Maria Concetta, Cinquanta, Luigi, Bassetti, Danila, Imbastaro, Tiziana, and Bagnasco, Marcello

Published
2015
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41. Linee guida per la diagnosi di laboratorio e istologica della malattia celiaca. Revisione 2015

Author

Porcelli, Brunetta, Alessio, Maria Grazia, Villalta, Danilo, Bizzaro, Nicola, Bagnasco, Marcello, Pesce, Giampaola, Tozzoli, Renato, Tampoia, Marilina, Bassetti, Danila, Antico, Antonio, Platzgummer, Stefan, Fabris, Martina, Visentini, Daniela, Brusca, Ignazio, Villanacci, Vincenzo, Salemme, Marianna, Tonutti, Elio, and Gruppo di Studio in Autoimmunologia della Società Italiana di Patologia Clinica e Medicina di Laboratorio

Published
2015
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47. Antinuclear antibodies target unknown autoantigens in porto-sinusoidal vascular disorder (PSVD) without portal hypertension.

Author

Pugliese, N., Tonutti, A., Isailovic, N., Polverini, D., Ceribelli, A., De Nicola, S., De Santis, M., Selmi, C., and Aghemo, A.

Abstract

Recent evidence links PSVD to connective tissue diseases. Antinuclear antibodies (ANA) are a hallmark of these conditions, but their prevalence and significance in patients with PSVD without portal hypertension (noPH-PSVD) remain unclear. Sera from noPH-PSVD patients were analyzed for ANA using indirect immunofluorescence (IIF) on HEp-2 substrates (HEp-2 IIF). ANA-positive cases underwent RNA immunoprecipitation (RNA-IP) to identify autoantibodies for specific ribonuclear proteins. Patients with cytoplasmic staining on Hep-2 IIF, underwent ELISA for antimitochondrial antibodies (AMA), targeting the E2 subunit of the pyruvate dehydrogenase complex (anti-E2-PDH). Sixteen patients were enrolled, with a median age of 42 years (range 22–58), 56% were female. Autoimmune comorbidities included thyroiditis in 4 patients, multiple sclerosis in one. PSVD diagnosis was based on histological evidence of nodular regenerative hyperplasia on liver biopsy performed for unexplained liver enzyme abnormalities. ANA were found in 8 out of 16 (50%) patients using HEp-2 IIF with titers ranging from 1:80 to 1:320. A cytoplasmic reticular/AMA-like pattern was observed in 4/16 (25%) patients, a speckled pattern in 1/16 (6.25%), a nucleolar pattern in 2/16 (12.5%; one co-occurring with a cytoplasmic reticular pattern) and a mitotic pattern (mitotic centrosome and NuMA-like) in 2 out of 16 (12.5%) cases. RNA-IP did not identify autoantibodies against specific ribonuclear proteins in any patient. Moreover, none of the patients with a cytoplasmic reticular/AMA-like pattern tested positive for anti-E2-PDH autoantibodies via ELISA. In this noPH-PSVD cohort, ANA were detected in 50% of cases using gold-standard techniques. Despite 25% showing an AMA-like pattern, anti-E2-PDH testing by ELISA was negative, suggesting these ANA may target antigens distinct from those in primary biliary cholangitis. A notable proportion of ANA-positive patients showed mitotic staining, uncommon in connective tissue diseases. Although ANA prevalence was high, RNA-IP did not reveal specific autoantibodies, highlighting the need for further investigation. [ABSTRACT FROM AUTHOR]

Published
2025
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48. Ethanol fermentationand ethylene physiologyrelated genes expression profiles in Red Delicious apples stored under variable hypoxic conditions and protocols.

Author

Salamé, E., Brizzolara, S., Rodrigues, M., Iob, M., Tonutti, P., and Ruperti, B.

Subjects
GENE expression profiling, SUCROSE, ALCOHOL dehydrogenase, APPLE growing, ANAEROBIC metabolism, APPLES, ETHYLENE, LACTATE dehydrogenase
Abstract

Dynamic Controlled Atmosphere (DCA) is beneficial in maintaining specific quality parameters but, due to the extreme oxygen levels applied, can cause adverse effects on the fruit by inducing excessive anaerobic metabolism and the production of off flavors. The metabolic adaptation and responses of apples (Malus domestica Borkh.) cv. Red Delicious to static or dynamic oxygen concentrations (0.3 and 0.8%, with sequential shifts) during cold storage for 7 months were studied by monitoring quality parameters and the expression of genes involved in sugar, fermentative metabolism, and ethylene physiology. Ethanol content reached the highest levels (around 400 mg/kg FW) under 0.3% oxygen concentration and fruit firmness appeared to be reduced in samples accumulating the highest levels of ethanol. Oxygen switch was effective in reducing the ethanol concentrations with timingdependent variable effects. The expression of fermentative (alcohol dehydrogenase, lactate dehydrogenase, pyruvate decarboxylase) and sugar metabolism (ß-amylase; phosphofructokinase; sucrose synthase) genes resulted to be differently affected by the hypoxic conditions imposed, in particular during the early stages of storage. Sucrose synthase expression appeared to be highly sensitive to changes in low oxygen concentration. Ethylene biosynthesis (ACC synthase and oxidase) genes showed marked differences in their expression in relation to the static and dynamic protocols and the hypoxic conditions, as well as six Ethylene Responsive Factors (ERF) genes, some of them possibly involved in the oxygen sensing mechanism operating in fruit tissues. [ABSTRACT FROM AUTHOR]

Published
2023
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