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3. Semi-Supervised GCN for learning Molecular Structure-Activity Relationships

Author

Ragno, Alessio, Savoia, Dylan, and Capobianco, Roberto

Subjects
Quantitative Biology - Biomolecules, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Since the introduction of artificial intelligence in medicinal chemistry, the necessity has emerged to analyse how molecular property variation is modulated by either single atoms or chemical groups. In this paper, we propose to train graph-to-graph neural network using semi-supervised learning for attributing structure-property relationships. As initial case studies we apply the method to solubility and molecular acidity while checking its consistency in comparison with known experimental chemical data. As final goal, our approach could represent a valuable tool to deal with problems such as activity cliffs, lead optimization and de-novo drug design., Comment: ELLIS Machine Learning for Molecules workshop (ML4Molecules) 2021

Published
2022

4. Molecule Generation from Input-Attributions over Graph Convolutional Networks

Author

Savoia, Dylan, Ragno, Alessio, and Capobianco, Roberto

Subjects
Quantitative Biology - Biomolecules, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

It is well known that Drug Design is often a costly process both in terms of time and economic effort. While good Quantitative Structure-Activity Relationship models (QSAR) can help predicting molecular properties without the need to synthesize them, it is still required to come up with new molecules to be tested. This is mostly done in lack of tools to determine which modifications are more promising or which aspects of a molecule are more influential for the final activity/property. Here we present an automatic process which involves Graph Convolutional Network models and input-attribution methods to generate new molecules. We also explore the problems of over-optimization and applicability, recognizing them as two important aspects in the practical use of such automatic tools., Comment: ELLIS Machine Learning for Molecules workshop (ML4Molecules) 2021

Published
2022

5. Retraction Note: Dissecting the role of novel EZH2 inhibitors in primary glioblastoma cell cultures: effects on proliferation, epithelialmesenchymal transition, migration, and on the pro-inflammatory phenotype

Author

Stazi, Giulia, Taglieri, Ludovica, Nicolai, Alice, Romanelli, Annalisa, Fioravanti, Rossella, Morrone, Stefania, Sabatino, Manuela, Ragno, Rino, Taurone, Samanta, Nebbioso, Marcella, Carletti, Raffaella, Artico, Marco, Valente, Sergio, Scarpa, Susanna, and Mai, Antonello

Published
2023
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9. Bcl-2 family inhibitors sensitize human cancer models to therapy

Author

Valentini, Elisabetta, Di Martile, Marta, Brignone, Matteo, Di Caprio, Marica, Manni, Isabella, Chiappa, Michela, Sergio, Ilaria, Chiacchiarini, Martina, Bazzichetto, Chiara, Conciatori, Fabiana, D’Aguanno, Simona, D’Angelo, Carmen, Ragno, Rino, Russillo, Michelangelo, Colotti, Gianni, Marchesi, Francesco, Bellone, Maria Laura, Dal Piaz, Fabrizio, Felli, Maria Pia, Damia, Giovanna, and Del Bufalo, Donatella

Published
2023
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11. An Exploratory Multicase Study of Mainstream Teachers' Experiences Teaching English Learners

Author

Jane Cullen Ragno

Abstract

As the number of English learners (ELs) in the U.S. continues to rise, and the push for inclusion models grows, so too does the need to prepare mainstream teachers to educate this diverse population of learners. However, most mainstream teachers lack the specific theoretical background and skillset necessary to provide optimal instruction for ELs. This dissertation describes an exploratory multicase study, combined with ethnographic methods, that features three mainstream teachers' experiences as teachers of ELs in a Queens, New York City elementary school. Data sources included monthly interviews, teacher observations, and weekly teacher-kept journals. I arrived at three themes: (a) mainstream teachers attempted to create a supportive environment for ELs; (b) mainstream teachers experienced social, institutional, and personal challenges related to teaching ELs; and (c) mainstream teachers struggled to recognize, identify, and teach to ELs' needs as English learners. Based on these findings, foremost, teachers of ELs need to develop multilingual awareness--a sense of the ubiquity and power of language in thought and human interaction--in all contexts. For teachers to develop multilingual awareness, school-based professional development and teacher training programs must include implicit bias training and Second Language Acquisition (SLA) theory. Implicit bias training should focus on the impact of teachers' perceptions on their thoughts, actions, and interactions involving students, as well as the influence of personal ideology and social-structural contexts of education. Furthermore, districts and schools must consider the structural constraints related to scheduling, planning time, and parent communication in creating school policy. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2021

12. Teaching and Learning Computational Drug Design: Student Investigations of 3D Quantitative Structure--Activity Relationships through Web Applications

Author

Ragno, Rino, Esposito, Valeria, Di Mario, Martina, Masiello, Stefano, Viscovo, Marco, and Cramer, Richard D.

Abstract

The increasing use of information technology in the discovery of new molecular entities encourages the use of modern molecular-modeling tools to help teach important concepts of drug design to chemistry and pharmacy undergraduate students. In particular, statistical models such as quantitative structure--activity relationships (QSAR)--often as its 3D QSAR variant--are commonly used in the development and optimization of a leading compound. We describe how these drug discovery methods can be taught and learned by means of free and open-source web applications, specifically the online platform www.3d-qsar.com. This new suite of web applications has been integrated into a drug design teaching course, one that provides both theoretical and practical perspectives. We include the teaching protocol by which pharmaceutical biotechnology master students at Pharmacy Faculty of Sapienza Rome University are introduced to drug design. Starting with a choice among recent articles describing the potencies of a series of molecules tested against a biological target, each student is expected to build a 3D QSAR ligand-based model from their chosen publication, proceeding as follows: creating the initial data set (Py-MolEdit); generating the global minimum conformations (Py-ConfSearch); proposing a promising mutual alignment (Py-Align); and finally, building, and optimizing a robust 3D QSAR models (Py-CoMFA). These student activities also help validate these new molecular modeling tools, especially for their usability by inexperienced hands. To more fully demonstrate the effectiveness of this protocol and its tools, we include the work performed by four of these students (four of the coauthors), detailing the satisfactory 3D QSAR models they obtained. Such scientifically complete experiences by undergraduates, made possible by the efficiency of the 3D QSAR methodology, provide exposure to computational tools in the same spirit as traditional laboratory exercises. With the obsolescence of the classic Comparative Molecular Field Analysis Sybyl host, the 3dqsar web portal offers one of the few available means of performing this well-established 3D QSAR method.

Published
2020
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13. Fabry-Stroke Italian Registry (FSIR): a nationwide, prospective, observational study about incidence and characteristics of Fabry-related stroke in young-adults. Presentation of the study protocol

Author

Romani, Ilaria, Nencini, Patrizia, Sarti, Cristina, Pracucci, Giovanni, Zedde, Marialuisa, Nucera, Antonia, Cianci, Vittoria, Moller, Jessica, Toni, Danilo, Orsucci, Daniele, Casella, Carmela, Pinto, Vincenza, Palumbo, Pasquale, Barbarini, Leonardo, Bella, Rita, Ragno, Michele, Scoditti, Umberto, Mezzapesa, Domenico Maria, Tassi, Rossana, Diomedi, Marina, Cavallini, Anna, Volpi, Gino, Chiti, Alberto, Bigliardi, Guido, Sacco, Simona, Linoli, Giovanni, Ricci, Stefano, Giordano, Antonello, Bonetti, Bruno, Rasura, Maurizia, Cecconi, Emanuela, Princiotta Cariddi, Lucia, Currò Dossi, Roberto, Melis, Marta, Consoli, Domenico, Guidetti, Donata, Biagini, Silvia, Accavone, Donatella, and Inzitari, Domenico

Published
2022
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14. Increasing probability of mortality during Indian heat waves.

Author

Mazdiyasni, Omid, AghaKouchak, Amir, Davis, Steven J, Madadgar, Shahrbanou, Mehran, Ali, Ragno, Elisa, Sadegh, Mojtaba, Sengupta, Ashmita, Ghosh, Subimal, Dhanya, CT, and Niknejad, Mohsen

Subjects
Humans, Mortality, Climate, Infrared Rays, Algorithms, Models, Theoretical, India, Hot Temperature, Heatwaves, climate extremes, mortality, Models, Theoretical, Climate Change, Climate-Related Exposures and Conditions
Abstract

Rising global temperatures are causing increases in the frequency and severity of extreme climatic events, such as floods, droughts, and heat waves. We analyze changes in summer temperatures, the frequency, severity, and duration of heat waves, and heat-related mortality in India between 1960 and 2009 using data from the India Meteorological Department. Mean temperatures across India have risen by more than 0.5°C over this period, with statistically significant increases in heat waves. Using a novel probabilistic model, we further show that the increase in summer mean temperatures in India over this period corresponds to a 146% increase in the probability of heat-related mortality events of more than 100 people. In turn, our results suggest that future climate warming will lead to substantial increases in heat-related mortality, particularly in developing low-latitude countries, such as India, where heat waves will become more frequent and populations are especially vulnerable to these extreme temperatures. Our findings indicate that even moderate increases in mean temperatures may cause great increases in heat-related mortality and support the efforts of governments and international organizations to build up the resilience of these vulnerable regions to more severe heat waves.

Published
2017

16. Coverage of the requirements of first and second level stroke unit in Italy

Author

Bandettini di Poggio, Monica, Toni, Danilo, Gandolfo, Carlo, Paolicelli, Damiano, Zini, Andrea, Agostoni, Elio, Bandini, Fabio, Ragno, Michele, Altavista, Maria Concetta, Bertolotto, Antonio, Siciliano, Gabriele, Vecchio, Michele, Tambasco, Nicola, Gambardella, Antonio, Manganotti, Paolo, Melis, Maurizio, Onofrj, Marco, De Michele, Giuseppe, Reale, Nicoletta, Tedeschi, Gioacchino, and Mancardi, GianLuigi

Published
2021
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22. Altered mitochondrial function in cells carrying a premutation or unmethylated full mutation of the FMR1 gene

Author

Nobile, Veronica, Palumbo, Federica, Lanni, Stella, Ghisio, Valentina, Vitali, Alberto, Castagnola, Massimo, Marzano, Valeria, Maulucci, Giuseppe, De Angelis, Claudio, De Spirito, Marco, Pacini, Laura, D’Andrea, Laura, Ragno, Rino, Stazi, Giulia, Valente, Sergio, Mai, Antonello, Chiurazzi, Pietro, Genuardi, Maurizio, Neri, Giovanni, and Tabolacci, Elisabetta

Published
2020
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24. Teachers' Perceptions of the School Breakfast Program.

Author

Connecticut State Dept. of Education, Hartford. and Ragno, Mary B.

Abstract

Noting that there is a relationship between hunger and the ability to learn, this study examines teacher opinions of the impact of a school breakfast program on student success. A survey, focusing on grades 1 through 3, was completed by 188 elementary teachers in 100 Connecticut schools in which breakfast programs had been implemented. Respondents were asked about the influence of the breakfast program on children's attendance and hunger awareness, and about the impact of the program on teachers' ability to perform their job. Survey participants indicated that the School Breakfast Program had a significant influence on children's behaviors, enhancing attention and alertness, energy, motivation, concentration, and self-discipline. In addition, they believed that the program improved student attributes in ratings of cooperation, and responsibility. The results support the breakfast program as a valuable part of the school day because it improves the children's chances for learning. (AP)

Published
1994

25. A Longitudinal Multiinstitutional Study of Vulvar Lichen Sclerosus: From Childhood to Perimenopause

Author

Di Giuseppe, Jacopo, Delli Carpini, Giovanni, Giannella, Luca, Terenzi, Tomas, Fichera, Mariasole, Ragno, Federica, Campanati, Anna, Boero, Veronica, Caia, Carlotta, Pesce, Elisa, Vercellini, Paolo, Gardella, Barbara, Dominoni, Mattia, Spinillo, Arsenio, Sopracordevole, Francesco, Clemente, Nicolò, Del Fabro, Anna, Rossi, Riccardo, Corazza, Monica, Borghi, Alessandro, Martinello, Ruby, Greco, Pantaleo, Rizzo, Giuseppe, Criscuolo, Anna Angela, Mappa, Ilenia, Matteini, Enrico, Botti, Elisabetta, Campione, Elena, Bianchi, Luca, and Ciavattini, Andrea

Published
2024
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26. Genomic history of the Italian population recapitulates key evolutionary dynamics of both Continental and Southern Europeans

Author

Sazzini, Marco, Abondio, Paolo, Sarno, Stefania, Gnecchi-Ruscone, Guido Alberto, Ragno, Matteo, Giuliani, Cristina, De Fanti, Sara, Ojeda-Granados, Claudia, Boattini, Alessio, Marquis, Julien, Valsesia, Armand, Carayol, Jerome, Raymond, Frederic, Pirazzini, Chiara, Marasco, Elena, Ferrarini, Alberto, Xumerle, Luciano, Collino, Sebastiano, Mari, Daniela, Arosio, Beatrice, Monti, Daniela, Passarino, Giuseppe, D’Aquila, Patrizia, Pettener, Davide, Luiselli, Donata, Castellani, Gastone, Delledonne, Massimo, Descombes, Patrick, Franceschi, Claudio, and Garagnani, Paolo

Published
2020
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30. RETRACTED ARTICLE: Dissecting the role of novel EZH2 inhibitors in primary glioblastoma cell cultures: effects on proliferation, epithelial-mesenchymal transition, migration, and on the pro-inflammatory phenotype

Author

Stazi, Giulia, Taglieri, Ludovica, Nicolai, Alice, Romanelli, Annalisa, Fioravanti, Rossella, Morrone, Stefania, Sabatino, Manuela, Ragno, Rino, Taurone, Samanta, Nebbioso, Marcella, Carletti, Raffaella, Artico, Marco, Valente, Sergio, Scarpa, Susanna, and Mai, Antonello

Published
2019
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32. Screening of the activity of sixty essential oils against plasmodium early mosquito stages in vitro and machine learning analysis reveals new putative inhibitors of malaria parasites.

Author

Deligianni, Elena, Pizzi, Elisabetta, Kavelaki, Ioanna, Siden-Kiamos, Inga, Sapienza, Filippo Umberto, Fioravanti, Rossella, Garzoli, Stefania, Pace, Tomasino, Ponzi, Marta, Ragno, Rino, and Currà, Chiara

Abstract

Malaria, an infectious disease with a tremendous impact on human health is caused by Plasmodium parasites, and transmitted by Anopheles mosquitoes. New approaches to control the disease involve transmission blocking strategies aiming to target the parasite in the mosquito. Here, we investigated the putative inhibitory activity of essential oils and their components on the early mosquito stages of the parasite. We employed an in vitro assay of gametocyte-to-ookinete development of the rodent model parasite Plasmodium berghei combined with high content screening. 60 essential oils with known composition were tested. The results revealed that fifteen EOs had inhibitory activity. Furthermore, a machine learning approach was used to identify the putative inhibitory components. Five of the most important chemical components indicated by the machine learning-based models were actually confirmed by the experimental approach. This combined approach was used for the first time to identify the potential transmission blocking activity of essential oils and single components at the zygote and ookinete stages. [Display omitted] [ABSTRACT FROM AUTHOR]

Published
2023
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34. Advancing Process-Based Nonstationary Analysis of Climate Extremes: Modeling, Uncertainty Assessment and Multivariate Attribution

Author

Ragno, Elisa

Subjects
Hydrologic sciences, Climate change, Civil engineering
Abstract

Extreme weather events are inherent in climate variability and they can cause ecosystem alterations, infrastructure damages, suspension of food supply chains, and loss of lives. Today's highly populated and urbanized society is more vulnerable than ever to natural hazards and their disruptive consequences. Projected population growth and changes in climate variability are expected to exacerbate the societal and economic impact of climatic extremes. The scientific community, global organizations, and other stakeholders have all recognized the urgency of improving our understanding of both natural and human-induced climate variability. The overarching goal of this thesis is to advance the current methods for nonstationary analysis of climatic extremes and their attributions. Here we propose a methodological framework for investigating hydroclimatic extremes over time and in response to a physical driver/covariate. The Process-based Nonstationary Extreme Value Analysis (ProNEVA) framework is unique in that it allows for incorporating a physical component into traditional frequency analysis techniques to account for observed or process-based changes in the variable of interest. The model can be used for both stationary and nonstationary analyses of extremes and includes a Graphical User Interface (GUI) for easier implementation. We then shed light on the uncertainty inherent in the estimation of climatic extremes. We propose a generalized approach for including uncertainty information in the recurrence interval of extremes. The approach offers insights on how information about extremes should be interpreted by planners and decision-makers under conditions of uncertainty. Using the method developed in this thesis, we show how extreme precipitation is expected to change in the future. We also highlight the importance of merging information from observations and climate model simulations for risk assessment purposes. Finally, we outline a methodological framework for attribution of changes in multiple extremes or multiple features of an extreme event. We show the potential of copula functions for attribution of changes in both the magnitude and the dependence structure between characteristics of a natural phenomenon or, more generally, between two dependent variables.

Published
2019

35. The Evaluation of an Early Childhood Teacher Preparation Program: An Action Research Project

Author

Ragno, Kerry Sullivan

Abstract

The purpose of this dissertation was to evaluate the effectiveness of an Early Childhood Development Associate of Applied Science (AAS) degree program at one community college as part of an ongoing action research project. Prior to this dissertation study, external and internal barriers prevented the associate degree program stakeholders from completing the evaluation phase. Those internal and external barriers were reflective of the historical marginalization of the early childhood education field in the United States, and were similar to those found in other higher education teacher preparation programs. Qualitative data were gathered from stakeholder participants during interviews and focus group sessions in order to answer three research questions: (1) What are the strengths of the Early Childhood Development AAS degree program? (2) What are the challenges of the Early Childhood Development AAS degree program? and (3) What are your suggestions for program improvements? A number of program strengths were identified: program curriculum, student observation and practical participation experiences, workforce preparation, and faculty collaboration. Program challenges included poor academic advising of students, lack of centralized program leadership, inefficient use of faculty, difficulty serving diverse learner needs, and difficulty placing students at observation and practical participation sites. Four suggestions for program improvements were made, including providing a dedicated academic advisor for early childhood students, coordinating student observation and practical participation placements, centralizing coordination of the Early Childhood Development AAS degree program and increasing program cohesion. Implications for practice, public policy, and future research on authentic program evaluation of teacher preparation programs are also presented. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2013

39. Homozygous NOTCH3 null mutation and impaired NOTCH3 signaling in recessive early‐onset arteriopathy and cavitating leukoencephalopathy

Author

Pippucci, Tommaso, Maresca, Alessandra, Magini, Pamela, Cenacchi, Giovanna, Donadio, Vincenzo, Palombo, Flavia, Papa, Valentina, Incensi, Alex, Gasparre, Giuseppe, Valentino, Maria Lucia, Preziuso, Carmela, Pisano, Annalinda, Ragno, Michele, Liguori, Rocco, Giordano, Carla, Tonon, Caterina, Lodi, Raffaele, Parmeggiani, Antonia, Carelli, Valerio, and Seri, Marco

Published
2015
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41. Cervical pessary for preterm birth prevention after an episode of arrested preterm labor: a retrospective cohort study with targeted maximum likelihood estimation of the average treatment effect.

Author

CARPINI, G. DELLI, GIANNELLA, L., CARBONI, M., FICHERA, M., PIZZAGALLI, D., SEGNALINI, N., CONTI, C., TAFURI, E., GIULIANI, L., RAGNO, F., MANCUSI, C., GIANNUBILO, S. R., and CIAVATTINI, A.

Abstract

OBJECTIVE: To evaluate whether cervical pessary effectively reduces the preterm birth < 37 weeks rate in patients who have not delivered after an episode of arrested preterm labor. PATIENTS AND METHODS: Retrospective cohort study was conducted on singleton pregnant patients admitted to our institution between January 2016 and June 2021 for threatened preterm labor and who had a cervical length < 25 mm. Women in whom a cervical pessary was placed were considered as exposed, while women in whom expectant management was preferred were considered as unexposed. The primary outcome was the rate of preterm birth before 37 weeks. A targeted maximum likelihood estimation was used to estimate the average treatment effect of cervical pessary by adjusting for a-priori-defined confounders. RESULTS: A cervical pessary was placed in 152 (36.6%) patients (exposed), while the remaining 263 (63.4%) were managed expectantly (unexposed). The adjusted average treatment effect was -14% (-18 to -11%), -17% (-20 to -13%), and -16% (-20 to -12%) for preterm birth < 37 weeks, < 34 weeks, and < 32 weeks, respectively. The average treatment effect for adverse neonatal outcomes was -7% (-8 to -5%). No difference in gestational weeks at delivery between exposed and unexposed emerged when gestational age at first admission was > 30.1 gestational weeks. CONCLUSIONS: The positioning of a cervical pessary placement may be evaluated to reduce the risk of a subsequent preterm birth after an episode of arrested preterm labor in pregnant patients with onset of symptoms before 30 gestational weeks. [ABSTRACT FROM AUTHOR]

Published
2023

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