Search

Your search keyword '"Gangi, D"' showing total 17 results
Start Over Author "Gangi, D" Search Limiters Full Text
17 results on '"Gangi, D"'

1. NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients

Author

Borgheresi, R, Barucci, A, Colantonio, S, Aghakhanyan, G, Assante, M, Bertelli, E, Carlini, E, Carpi, R, Caudai, C, Cavallero, D, Cioni, D, Cirillo, R, Colcelli, V, Dell'Amico, A, Di Gangi, D, Erba, P, Faggioni, L, Falaschi, Z, Gabelloni, M, Gini, R, Lelii, L, Lio, P, Lorito, A, Lucarini, S, Manghi, P, Mangiacrapa, F, Marzi, C, Mazzei, M, Mercatelli, L, Mirabile, A, Mungai, F, Miele, V, Olmastroni, M, Pagano, P, Paiar, F, Panichi, G, Pascali, M, Pasquinelli, F, Shortrede, J, Tumminello, L, Volterrani, L, Neri, E, Borgheresi R., Barucci A., Colantonio S., Aghakhanyan G., Assante M., Bertelli E., Carlini E., Carpi R., Caudai C., Cavallero D., Cioni D., Cirillo R., Colcelli V., Dell'Amico A., Di Gangi D., Erba P. A., Faggioni L., Falaschi Z., Gabelloni M., Gini R., Lelii L., Lio P., Lorito A., Lucarini S., Manghi P., Mangiacrapa F., Marzi C., Mazzei M. A., Mercatelli L., Mirabile A., Mungai F., Miele V., Olmastroni M., Pagano P., Paiar F., Panichi G., Pascali M. A., Pasquinelli F., Shortrede J. E., Tumminello L., Volterrani L., Neri E., Borgheresi, R, Barucci, A, Colantonio, S, Aghakhanyan, G, Assante, M, Bertelli, E, Carlini, E, Carpi, R, Caudai, C, Cavallero, D, Cioni, D, Cirillo, R, Colcelli, V, Dell'Amico, A, Di Gangi, D, Erba, P, Faggioni, L, Falaschi, Z, Gabelloni, M, Gini, R, Lelii, L, Lio, P, Lorito, A, Lucarini, S, Manghi, P, Mangiacrapa, F, Marzi, C, Mazzei, M, Mercatelli, L, Mirabile, A, Mungai, F, Miele, V, Olmastroni, M, Pagano, P, Paiar, F, Panichi, G, Pascali, M, Pasquinelli, F, Shortrede, J, Tumminello, L, Volterrani, L, Neri, E, Borgheresi R., Barucci A., Colantonio S., Aghakhanyan G., Assante M., Bertelli E., Carlini E., Carpi R., Caudai C., Cavallero D., Cioni D., Cirillo R., Colcelli V., Dell'Amico A., Di Gangi D., Erba P. A., Faggioni L., Falaschi Z., Gabelloni M., Gini R., Lelii L., Lio P., Lorito A., Lucarini S., Manghi P., Mangiacrapa F., Marzi C., Mazzei M. A., Mercatelli L., Mirabile A., Mungai F., Miele V., Olmastroni M., Pagano P., Paiar F., Panichi G., Pascali M. A., Pasquinelli F., Shortrede J. E., Tumminello L., Volterrani L., and Neri E.

Abstract

NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project’s goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.

Published
2022

2. Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model

Author

Campajola C., Di Gangi D., Lillo F., and Tantari D.

Subjects
Kinetics, Social Networking
Abstract

A common issue when analyzing real-world complex systems is that the interactions between their elements often change over time. Here we propose a new modeling approach for time-varying interactions generalising the well-known Kinetic Ising Model, a minimalistic pairwise constant interactions model which has found applications in several scientific disciplines. Keeping arbitrary choices of dynamics to a minimum and seeking information theoretical optimality, the Score-Driven methodology allows to extract from data and interpret the presence of temporal patterns describing time-varying interactions. We identify a parameter whose value at a given time can be directly associated with the local predictability of the dynamics and we introduce a method to dynamically learn its value from the data, without specifying parametrically the system's dynamics. We extend our framework to disentangle different sources (e.g. endogenous vs exogenous) of predictability in real time, and show how our methodology applies to a variety of complex systems such as financial markets, temporal (social) networks, and neuronal populations.

Published
2022

5. Use of livestock waste composts as nursery growing media: Effect of a washing pre-treatment

Author

European Commission, Bustamante, M. A., Gomis, M. P., Perez-Murcia, M. D., Gangi, D., Ceglie, F. G, Paredes, Concepción, Pérez-Espinosa, A., Bernal Calderón, M. Pilar, Moral, Raul, European Commission, Bustamante, M. A., Gomis, M. P., Perez-Murcia, M. D., Gangi, D., Ceglie, F. G, Paredes, Concepción, Pérez-Espinosa, A., Bernal Calderón, M. Pilar, and Moral, Raul

Abstract

The search for alternative materials for peat substitution in soilless systems has led to an increasing use of compost as ingredient of growing media. These materials may have similar characteristics to peat for their potential use as substitutes of this non-renewable material. However, the high salinity is one of the most usual limiting factors in compost for its use in growing media. This work evaluates the effect of the use of a washing pre-treatment to improve the quality of livestock waste-derived composts as peat substitutes in substrates for pepper (Capsicum annuum L.) seedling production. For this, different growing media were prepared using as ingredients five composts from livestock manures and anaerobic digestates (M1, M2, M3, D1 and D2), with or without a washing pre-treatment. Each respective material was mixed with peat in the proportions 25 %, 50 % and 75 % (volume:volume), using as control treatment pure (100 %) peat. The main physico-chemical, chemical and physical characteristics of the composts before and after washing and those of the growing media were studied, as well as germination and biomass production of the seedlings. The use of a washing pre-treatment was effective in the reduction of compost salinity, without implying a negative effect on the physical properties and nutrient content of the growing media, which were adequate for being used in seedling production, as reflected in the beneficial effects on the germination and growth of pepper seedlings.

Published
2021

12. Wortmannin-sensitive trafficking pathways in Chinese hamster ovary cells. Differential effects on endocytosis and lysosomal sorting.

Author

Martys, J L, Wjasow, C, Gangi, D M, Kielian, M C, McGraw, T E, and Backer, J M

Abstract

Phosphatidylinositol (PI) 3'-kinases are a family of lipid kinases implicated in the regulation of cell growth by oncogene products and tyrosine kinase growth factor receptors. The catalytic subunit of the p85/p110 PI 3'-kinase is homologous to VPS-34, a phosphatidylinositol-specific lipid kinase involved in the sorting of newly synthesized hydrolases to the yeast vacuole. This suggests that PI 3'-kinases may play analogous roles in mammalian cells. We have measured a number of secretory and endocytic trafficking events in Chinese hamster ovary cells in the presence of wortmannin, a potent inhibitor of PI 3'-kinase. Wortmannin caused a 40-50% down-regulation of surface transferrin receptors, with a dose dependence identical to that required for maximal inhibition of the p85/p110 PI 3'-kinase in intact cells. The redistribution of transferrin receptors reflected a 60% increase in the internalization rate and a 35% decrease in the recycling rate. Experiments with fluorescent transferrin showed that entry of transferrin receptors into the recycling compartment and efflux of receptors out of the compartment were slowed by wortmannin. Wortmannin altered the morphology of the recycling compartment, which was more vesiculated than in untreated cells. Using Semliki Forest virus as a probe, we also found that delivery of the endocytosed virus to its lysosomal site of degradation was slowed by wortmannin, whereas endosomal acidification was unaffected. In contrast to these effects on endocytosis and recycling, wortmannin did not affect intracellular processing of newly synthesized viral spike proteins. Wortmannin did induce missorting of the lysosomal enzyme cathepsin D to the secretory pathway, but only at a dose 20-fold greater than that required to inhibit p85/p110 PI 3'-kinase activity or to redistribute transferrin receptors. Our data demonstrate the presence of wortmannin-sensitive enzymes at three distinct steps of the endocytic cycle in Chinese hamster ovary cells: internalization, transit from early endosomes to the recycling and degradative compartments, and transit from the recycling compartment back to the cell surface. The wortmannin-sensitive enzymes critical for endocytosis and recycling are distinct from those involved in sorting newly synthesized lysosomal enzymes.

Published
1996

14. NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients

Author

Borgheresi, Rita, Barucci, Andrea, Colantonio, Sara, Aghakhanyan, Gayane, Assante, Massimiliano, Bertelli, Elena, Carlini, Emanuele, Carpi, Roberto, Caudai, Claudia, Cavallero, Diletta, Cioni, Dania, Cirillo, Roberto, Colcelli, Valentina, Dell'Amico, Andrea, Di Gangi, Domnico, Erba, Paola Anna, Faggioni, Lorenzo, Falaschi, Zeno, Gabelloni, Michela, Gini, Rosa, Lelii, Lucio, Liò, Pietro, Lorito, Antonio, Lucarini, Silvia, Manghi, Paolo, Mangiacrapa, Francesco, Marzi, Chiara, Mazzei, Maria Antonietta, Mercatelli, Laura, Mirabile, Antonella, Mungai, Francesco, Miele, Vittorio, Olmastroni, Maristella, Pagano, Pasquale, Paiar, Fabiola, Panichi, Giancarlo, Pascali, Maria Antonietta, Pasquinelli, Filippo, Shortrede, Jorge Eduardo, Tumminello, Lorenzo, Volterrani, Luca, Neri, Emanuele, NAVIGATOR Consortium Group, Aghakhanyan, Gayane [0000-0001-5152-497X], Apollo - University of Cambridge Repository, Borgheresi, R, Barucci, A, Colantonio, S, Aghakhanyan, G, Assante, M, Bertelli, E, Carlini, E, Carpi, R, Caudai, C, Cavallero, D, Cioni, D, Cirillo, R, Colcelli, V, Dell'Amico, A, Di Gangi, D, Erba, P, Faggioni, L, Falaschi, Z, Gabelloni, M, Gini, R, Lelii, L, Lio, P, Lorito, A, Lucarini, S, Manghi, P, Mangiacrapa, F, Marzi, C, Mazzei, M, Mercatelli, L, Mirabile, A, Mungai, F, Miele, V, Olmastroni, M, Pagano, P, Paiar, F, Panichi, G, Pascali, M, Pasquinelli, F, Shortrede, J, Tumminello, L, Volterrani, L, and Neri, E

Subjects
Artificial intelligence, Radiomics, Precision medicine, Biomarker, Biobanks, Guideline/Position paper, Artificial Intelligence, Positron-Emission Tomography, Imaging Biobank, Radiology, Nuclear Medicine and imaging, Radiomic, Precision Medicine, Biomarkers, Biobank, Biological Specimen Banks
Abstract

NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project’s goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.

Published
2022

15. NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients.

Author

Borgheresi R, Barucci A, Colantonio S, Aghakhanyan G, Assante M, Bertelli E, Carlini E, Carpi R, Caudai C, Cavallero D, Cioni D, Cirillo R, Colcelli V, Dell'Amico A, Di Gangi D, Erba PA, Faggioni L, Falaschi Z, Gabelloni M, Gini R, Lelii L, Liò P, Lorito A, Lucarini S, Manghi P, Mangiacrapa F, Marzi C, Mazzei MA, Mercatelli L, Mirabile A, Mungai F, Miele V, Olmastroni M, Pagano P, Paiar F, Panichi G, Pascali MA, Pasquinelli F, Shortrede JE, Tumminello L, Volterrani L, and Neri E

Subjects
Biological Specimen Banks, Positron-Emission Tomography, Biomarkers, Precision Medicine methods, Artificial Intelligence
Abstract

NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project's goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence., (© 2022. The Author(s) under exclusive licence to European Society of Radiology.)

Published
2022
Full Text
View/download PDF

16. Simple mathematical law benchmarks human confrontations.

Author

Johnson NF, Medina P, Zhao G, Messinger DS, Horgan J, Gill P, Bohorquez JC, Mattson W, Gangi D, Qi H, Manrique P, Velasquez N, Morgenstern A, Restrepo E, Johnson N, Spagat M, and Zarama R

Subjects
Datasets as Topic, Humans, Aggression, Conflict, Psychological, Models, Theoretical
Abstract

Many high-profile societal problems involve an individual or group repeatedly attacking another - from child-parent disputes, sexual violence against women, civil unrest, violent conflicts and acts of terror, to current cyber-attacks on national infrastructure and ultrafast cyber-trades attacking stockholders. There is an urgent need to quantify the likely severity and timing of such future acts, shed light on likely perpetrators, and identify intervention strategies. Here we present a combined analysis of multiple datasets across all these domains which account for >100,000 events, and show that a simple mathematical law can benchmark them all. We derive this benchmark and interpret it, using a minimal mechanistic model grounded by state-of-the-art fieldwork. Our findings provide quantitative predictions concerning future attacks; a tool to help detect common perpetrators and abnormal behaviors; insight into the trajectory of a 'lone wolf'; identification of a critical threshold for spreading a message or idea among perpetrators; an intervention strategy to erode the most lethal clusters; and more broadly, a quantitative starting point for cross-disciplinary theorizing about human aggression at the individual and group level, in both real and online worlds.

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results