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8. Why are so huge differences reported in the occurrence rate of skin lipohypertrophy? Does it depend on method defects or on lack of interest?

Author

Brancario, C., Corigliano, M., Cozzolino, G., Improta, M.R., Fasolino, A., Lamberti, C., Lapice, M., Martino, C., Oliva, D., Raffaele, A., Selleri, A., Simonetti, R., Stile, A., Vecchiato, A., Vetrano, A., Volpe, P., Caputo, G., Del Sorbo, A., Di Capua, M.G., Durazzo, G., Egidio, M., Garofalo, G., Grasso, L., Meo, A., Murano, A., Perillo, L., Procida, R., Vietsi, F., Gentile, S., Strollo, F., and Guarino, G.

Published
2019
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23. BIODEGRADABLE POLYMER-BASED COMPOSITES FILLED WITH BIOCHAR FOR TUNABLE RELEASE OF CARVACROL

Author

Botta L., Lopresti F., Pernice G., Garofalo G., Gaglio R., Botta L., Lopresti F., Pernice G., Garofalo G., and Gaglio R.

Subjects
carvacrol, PBAT, biochar, bio-composite
Abstract

Bio-composites are commonly obtained by combining biodegradable polymers with fillers collected from natural resources. In this context, biochar (BC) is attracting high interest as filler for polymer-based composites due to its challenging properties, including ecosustainability. This study aimed to prepare and characterize bio-composites with antimicrobial properties evaluating the role of the filler in the release kinetics. In particular, BC as filler and carvacrol (CRV) as antimicrobial agent, were incorporated via melt-compounding in poly(butylene adipate-co-terephthalate) (PBAT) samples. The rheological, tensile, and antimicrobial properties of the obtained bio-composites were evaluated paying particular attention to the influence of BC concentration, i.e., 5, 10, and 20 wt%, on the investigated properties. Moreover, the influence of BC content on the release kinetics of carvacrol was studied and mathematically modeled to evaluate the release mechanism. The results showed that the presence of biochar modified the carvacrol release in comparison with the unfilled system thus allowing to tune the release kinetics.

Published
2022

27. Efficacy of a reduced pill burden on therapeutic adherence to calcineurin inhibitors in renal transplant recipients: an observational study

Author

Sabbatini M, Garofalo G, Borrelli S, Vitale S, Torino M, Capone D, Russo L, Pisani A, Carrano R, Gallo R, and Federico S

Subjects
Medicine (General), R5-920
Abstract

Massimo Sabbatini,1 Gianluca Garofalo,1 Silvio Borrelli,2 Sossio Vitale,1 Massimiliano Torino,1 Domenico Capone,3 Luigi Russo,3 Antonio Pisani,1 Rosa Carrano,1 Riccardo Gallo,1 Stefano Federico11Nephrology, Department of Public Health, University Federico II of Naples, 2Department of Nephrology, Second University of Naples, 3Department of Neurosciences, Unit of Clinical Pharmacology, University Federico II of Naples, Naples, ItalyPurpose: The aim of this study was to determine the prevalence of nonadherence in a cohort of renal transplant recipients (RTRs) and to evaluate prospectively whether more intense clinical surveillance and reduced pill number enhanced adherence.Patients and methods: The study was carried out in 310 stable RTRs in whom adherence, life satisfaction, and transplant care were evaluated by specific questionnaires (time 0). The patients under tacrolimus (TAC; bis in die [BID]) were then shifted to once-daily TAC (D-TAC) to reduce their pill burden (Shift group) and were followed up for 6 months to reevaluate the same parameters. Patients on cyclosporin or still on BID-TAC constituted a time-control group.Results: The prevalence of nonadherence was 23.5% and was associated with previous rejection episodes (P

Published
2014

28. Machine Learning Meets Data Modification: The Potential of Pre-processing for Privacy Enchancement

Author

Batina, L., Bäck, T., Buhan, I., Picek, S., Garofalo, G., Slokom, M., Preuveneers, D., Joosen, W., Larson, M., Batina, L., Bäck, T., Buhan, I., Picek, S., Garofalo, G., Slokom, M., Preuveneers, D., Joosen, W., and Larson, M.

Abstract

Item does not contain fulltext, We explore how data modification can enhance privacy by examining the connection between data modification and machine learning. Specifically, machine learning “meets” data modification in two ways. First, data modification can protect the data that is used to train machine learning models focusing it on the intended use and inhibiting unwanted inference. Second, machine learning can provide new ways of creating modified data. In this chapter, we discuss data modification approaches, applied during data pre-processing, that are suited for online data sharing scenarios. Specifically, we define two scenarios “User data sharing” and “Data set sharing” and describe the threat models associated with each scenario and related privacy threats. We then survey the landscape of privacy-enhancing data modification techniques that can be used to counter these threats. The picture that emerges is that data modification approaches hold promise to enhance privacy, and can be used alongside of conventional cryptographic approaches. We close with an outlook on future directions focusing on new types of data, the relationship among privacy, and the importance of taking an interdisciplinary approach to data modification for privacy enhancement.

Published
2022

31. Le piccole e medie imprese italiane nella riflessione di Francesco Parrillo e nel contesto dell’economia italiana del III millennio: un percorso di ricerca sul capitalismo italiano con una verifica empirica

Author

Garofalo, G, Guarini, G, Chiacchierini, C, GAROFALO,G, GUARINI, G, CHIACCHIERINI, C, Garofalo, G, Guarini, G, Chiacchierini, C, GAROFALO,G, GUARINI, G, and CHIACCHIERINI, C

Abstract

Partendo dall’esame di alcuni contributi di Francesco Parrillo, compresi in un arco temporale che va dal 1983 al 1999, sul tema delle PMI (anche nei suoi riflessi finanziari), l’articolo propone una attualizzazione di quella riflessione per interpretare la realtà del sistema produttivo italiano nella seconda decade del nuovo millennio. I temi emergenti sono legati alla vitalità delle medie imprese, alla nuova manifattura digitale, ad una maggiore attenzione per la diversificazione delle fonti di finanziamento. A fronte di questi spiragli, permangono alcuni nodi critici strutturali come le difficoltà della maggior parte delle imprese, segnate dalla ridotta dimensione, la loro sottocapitalizzazione, i modelli superati di governance, che, a livello macroeconomico, comportano bassi livelli di produttività. Al riguardo viene condotta un’analisi econometrica per testare l’ipotesi che una “soluzione” possa venire da reti d’impresa che collaborano su progetti mirati di innovazione (e/o internazionalizzazione)., Starting from an accurate selection of contributions written, in the 1983-1999 period, by Francesco Parrillo on SMEs (also in its financial implications), the paper proposes to contextualize its analysis in recent times, in order to interpret the modern nature of the Italian productive system. Emerging relevant topics arerelated to the dynamism of Medium-sized firms, the new digital manufacture, and to the diversification of funding sources. However, critical issues still remain, such as small dimension, undercapitalization, outdated governance, which imply low productivity levels. In this regard, we propose an econometric analysis to test the hypothesis that a “solution” can come from business networks with firms that collaborate on targeted innovation (and/or internationalization) projects.

Published
2020

32. Risk factors and action thresholds for the novel coronavirus pandemic. Insights from the Italian Society of Nephrology COVID-19 Survey

Author

Nordio, M., Reboldi, G., Di Napoli, A., Quintaliani, G., Alberici, F., Postorino, M., Aucella, F., Messa, P., Brunori, G., Bosco, M., Malberti, F., Mandreoli, M., Mazzaferro, S., Movilli, E., Ravera, M., Salomone, M., Santoro, D., Postorinolimido, M. A., Bonomini, M., Stingone, A., Maccarone, M., Di Loreto, E., Stacchiotti, L., Malandra, R., Chiarella, S., D'Agostino, F., Fuiano, G., Nicodemo, L., Bonofiglio, R., Greco, S., Mallamaci, F., Barreca, E., Caserta, C., Bruzzese, V., Galati, D., Tramontana, D., Viscione, M., Chiuchiolo, L., Tuccillo, S., Sepe, M., Vitale, F., Ciriana, E., Martignetti, V., Caserta, D., Stizzo, A., Romano, A., Iulianiello, G., Cascone, E., Minicone, P., Chiricone, D., Delgado, G., Barbato, A., Celentano, S., Molfino, I., Coppola, S., Raiola, I., Abategiovanni, M., Borrelli, S., Margherita, C., Bruno, F., Ida, M., Aliperti, E., Potito, D., Cuomo, G., De Luca, M., Merola, M., Botta, C., Garofalo, G., Alinei, P., Paglionico, C., Roano, M., Vitale, S., Ierardi, R., Fimiani, V., Conte, G., Di Natale, G., Romano, M., Di Marino, V., Scafarto, A., Meccariello, S., Pecoraro, C., Di Stazio, E., Di Meglio, E., Cuomo, A., Maresca, B., Rotaia, E., Capasso, G., Auricchio, M., Pluvio, C., Maddalena, L., De Maio, A., Palladino, G., Buono, F., Gigliotti, G., Mancini, E., La Manna, G., Storari, A., Mosconi, G., Cappelli, G., Scarpioni, R., Gregorini, M., Rigotti, A., Mancini, W., Bianco, F., Boscutti, G., Amici, G., Tosto, M., Fini, R., Pace, G., Cioffi, A., Boccia, E., Di Lullo, L., Di Zazzo, G., Simonelli, R., Bondatti, F., Miglio, L., Rifici, N., Treglia, A., Muci, M., Baldinelli, G., Rizzi, E., Lonzi, M., De Cicco, C., Forte, F., De Paolis, P., Grandaliano, Giuseppe, Cuzziol, C., Torre, V. M., Sfregola, P., Rossi, V., Fabio, G., Flammini, A., Filippini, A., Onorato, L., Vendola, F., Di Daniela, N., Alfarone, C., Scabbia, L., Ferrazzano, M., Grotta, B. D., Gamberini, M., Fazzari, L., Mene, P., Morgia, A., Catucci, A., Palumbo, R., Puliti, M., Marinelli, R., Polito, P., Marrocco, F., Morabito, S., Rocca, R., Nazzaro, L., Lavini, R., Iamundo, V., Chiappini, M., Casarci, M., Morosetti, M., Hassan, S., Firmi, G., Galliani, M., Serraiocco, M., Feriozzi, S., Valentini, W., Sacco, P., Garibotto, G., Cappelli, V., Saffioti, C., Repetto, M., Rolla, D., Lorenz, M., Pedrini, L., Polonioli, D., Galli, E., Ruggenenti, P., Scolari, F., Bove, S., Costantino, E., Bracchi, M., Mangano, S., Depetri, G., La Milia, V., Farina, M., Zecchini, S., Savino, R., Melandri, M., Guastoni, C., Paparella, M., Gallieni, M., Minetti, E., Bisegna, S., Righetti, M., Badalamenti, S., Alberghini, E., Bertoli, S., Fabbrini, P., Albrizio, P., Rampino, T., Colturi, C., Rombola, G., Lucatello, A., Guerrini, E., Ranghino, A., Lenci, F., Fanciulli, E., Santarelli, S., Damiani, C., Garofalo, D., Sopranzi, F., Santoferrara, A., Di Luca, M., Galiotta, P., Brigante, M., Manganaro, M., Maffei, S., Berto, I., Besso, L., Viglino, G., Cusinato, S., Chiarinottichiappero, D. F., Tognarelli, G., Gianoglio, B., Forneris, G., Biancone, L., Savoldi, S., Vitale, C., Boero, R., Filiberti, O., Borzumati, M., Gesualdo, L., Lomonte, C., Gernone, G., Pallotta, G., Di Paolo, S., Vernaglione, L., Specchio, A., Stallone, G., Dell'Aquila, R., Sandri, G., Russo, F., Napoli, M., Marangi, A., Morrone, L., Di Stratis, C., Fresu, A., Cicu, F., Murtas, S., Manca, O., Pani, A., Pilloni, M., Pistis, R., Cadoni, M., Contu, B., Logias, F., Ivaldi, R., Fancello, S., Cossu, M., Lepori, G., Vittoria, S., Battiati, E., Arnone, M., Rome, M., Barbera, A., Granata, A., Collura, G., Dico, C. L., Pugliese, G., Di Natale, E., Rizzari, G., Cottone, L., Longo, N., Battaglia, G., Marcantoni, C., Giannetto, G., Tumino, G., Randazzo, F., Bellissimo, L., Faro, F. L., Grippaldi, F., Urso, S., Quattrone, G., Todaro, I., Vincenzo, D., Murgo, A., Masuzzo, M., Pisacane, A., Monardo, P., Pontorierro, M., Quari, C., Bauro, A., Chimenz, R. R., Alfio, D., Girasole, F., Cascio, A. L., Caviglia, A., Tornese, F., Sirna, F., Altieri, C., Cusumano, R., Saveriano, V., La Corte, A., Locascio, G., Rotolo, U., Musso, S., Risuglia, L., Blanco, G., Minardo, G., Castellino, S., Zappulla, Z., Randone, S., Di Francesca, M., Cassetti, C. C., Oddo, G., Buscaino, G., Mucaria, F., Barraco, V. I., Di Martino, A., Rallo, D., Dani, L., Campolo, G., Manescalchi, F., Biagini, M., Agate, M., Panichi, V., Casani, A., Traversari, L., Garosi, G., Tabbi, M., Selvi, A., Cencioni, L., Fagugli, R., Timio, F., Leveque, A., Manes, M., Mennella, G., Calo, L., Fiorini, F., Abaterusso, C., Calzavara, P., Meneghel, G., Bonesso, C., Gambaro, G., Gammaro, L., Rugiu, C., Ronco, C., Nordio M., Reboldi G., Di Napoli A., Quintaliani G., Alberici F., Postorino M., Aucella F., Messa P., Brunori G., Bosco M., Malberti F., Mandreoli M., Mazzaferro S., Movilli E., Ravera M., Salomone M., Santoro D., PostorinoLimido M.A., Bonomini M., Stingone A., Maccarone M., Di Loreto E., Stacchiotti L., Malandra R., Chiarella S., D'Agostino F., Fuiano G., Nicodemo L., Bonofiglio R., Greco S., Mallamaci F., Barreca E., Caserta C., Bruzzese V., Galati D., Tramontana D., Viscione M., Chiuchiolo L., Tuccillo S., Sepe M., Vitale F., Ciriana E., Martignetti V., Caserta D., Stizzo A., Romano A., Iulianiello G., Cascone E., Minicone P., Chiricone D., Delgado G., Barbato A., Celentano S., Molfino I., Coppola S., Raiola I., Abategiovanni M., Borrelli S., Margherita C., Bruno F., Ida M., Aliperti E., Potito D., Cuomo G., De Luca M., Merola M., Botta C., Garofalo G., Alinei P., Paglionico C., Roano M., Vitale S., Ierardi R., Fimiani V., Conte G., Di Natale G., Romano M., Di Marino V., Scafarto A., Meccariello S., Pecoraro C., Di Stazio E., Di Meglio E., Cuomo A., Maresca B., Rotaia E., Capasso G., Auricchio M., Pluvio C., Maddalena L., De Maio A., Palladino G., Buono F., Gigliotti G., Mancini E., La Manna G., Storari A., Mosconi G., Cappelli G., Scarpioni R., Gregorini M., Rigotti A., Mancini W., Bianco F., Boscutti G., Amici G., Tosto M., Fini R., Pace G., Cioffi A., Boccia E., Di Lullo L., Di Zazzo G., Simonelli R., Bondatti F., Miglio L., Rifici N., Treglia A., Muci M., Baldinelli G., Rizzi E., Lonzi M., De Cicco C., Forte F., De Paolis P., Grandaliano G., Cuzziol C., Torre V.M., Sfregola P., Rossi V., Fabio G., Flammini A., Filippini A., Onorato L., Vendola F., Di Daniela N., Alfarone C., Scabbia L., Ferrazzano M., Grotta B.D., Gamberini M., Fazzari L., Mene P., Morgia A., Catucci A., Palumbo R., Puliti M., Marinelli R., Polito P., Marrocco F., Morabito S., Rocca R., Nazzaro L., Lavini R., Iamundo V., Chiappini M., Casarci M., Morosetti M., Hassan S., Firmi G., Galliani M., Serraiocco M., Feriozzi S., Valentini W., Sacco P., Garibotto G., Cappelli V., Saffioti C., Repetto M., Rolla D., Lorenz M., Pedrini L., Polonioli D., Galli E., Ruggenenti P., Scolari F., Bove S., Costantino E., Bracchi M., Mangano S., Depetri G., La Milia V., Farina M., Zecchini S., Savino R., Melandri M., Guastoni C., Paparella M., Gallieni M., Minetti E., Bisegna S., Righetti M., Badalamenti S., Alberghini E., Bertoli S., Fabbrini P., Albrizio P., Rampino T., Colturi C., Rombola G., Lucatello A., Guerrini E., Ranghino A., Lenci F., Fanciulli E., Santarelli S., Damiani C., Garofalo D., Sopranzi F., Santoferrara A., Di Luca M., Galiotta P., Brigante M., Manganaro M., Maffei S., Berto I., Besso L., Viglino G., Cusinato S., ChiarinottiChiappero D.F., Tognarelli G., Gianoglio B., Forneris G., Biancone L., Savoldi S., Vitale C., Boero R., Filiberti O., Borzumati M., Gesualdo L., Lomonte C., Gernone G., Pallotta G., Di Paolo S., Vernaglione L., Specchio A., Stallone G., Dell'Aquila R., Sandri G., Russo F., Napoli M., Marangi A., Morrone L., Di Stratis C., Fresu A., Cicu F., Murtas S., Manca O., Pani A., Pilloni M., Pistis R., Cadoni M., Contu B., Logias F., Ivaldi R., Fancello S., Cossu M., Lepori G., Vittoria S., Battiati E., Arnone M., Rome M., Barbera A., Granata A., Collura G., Dico C.L., Pugliese G., Di Natale E., Rizzari G., Cottone L., Longo N., Battaglia G., Marcantoni C., Giannetto G., Tumino G., Randazzo F., Bellissimo L., Faro F.L., Grippaldi F., Urso S., Quattrone G., Todaro I., Vincenzo D., Murgo A., Masuzzo M., Pisacane A., Monardo P., Pontorierro M., Quari C., Bauro A., Chimenz R.R., Alfio D., Girasole F., Cascio A.L., Caviglia A., Tornese F., Sirna F., Altieri C., Cusumano R., Saveriano V., La Corte A., Locascio G., Rotolo U., Musso S., Risuglia L., Blanco G., Minardo G., Castellino S., Zappulla Z., Randone S., Di Francesca M., Cassetti C.C., Oddo G., Buscaino G., Mucaria F., Barraco V.I., Di Martino A., Rallo D., Dani L., Campolo G., Manescalchi F., Biagini M., Agate M., Panichi V., Casani A., Traversari L., Garosi G., Tabbi M., Selvi A., Cencioni L., Fagugli R., Timio F., Leveque A., Manes M., Mennella G., Calo L., Fiorini F., Abaterusso C., Calzavara P., Meneghel G., Bonesso C., Gambaro G., Gammaro L., Rugiu C., and Ronco C.

Subjects
Male, Contextual analysis, medicine.medical_treatment, Population, 030232 urology & nephrology, Recursive partitioning, 030204 cardiovascular system & hematology, Rate ratio, Risk Assessment, 03 medical and health sciences, 0302 clinical medicine, Classification tree, COVID-19, Renal replacement therapy, Risk Factors, Medical, Surveys and Questionnaires, Health care, medicine, Settore MED/14 - NEFROLOGIA, Humans, education, Pandemics, Societies, Medical, Female, Italy, Nephrology, education.field_of_study, business.industry, Multilevel model, Decision rule, Confidence interval, Original Article, Hemodialysis, business, Contextual analysi, Societies, Demography
Abstract

Background and aim: Over 80% (365/454) of the nation’s centers participated in the Italian Society of Nephrology COVID-19 Survey. Out of 60,441 surveyed patients, 1368 were infected as of April 23rd, 2020. However, center-specific proportions showed substantial heterogeneity. We therefore undertook new analyses to identify explanatory factors, contextual effects, and decision rules for infection containment. Methods: We investigated fixed factors and contextual effects by multilevel modeling. Classification and Regression Tree (CART) analysis was used to develop decision rules. Results: Increased positivity among hemodialysis patients was predicted by center location [incidence rate ratio (IRR) 1.34, 95% confidence interval (CI) 1.20–1.51], positive healthcare workers (IRR 1.09, 95% CI 1.02–1.17), test-all policy (IRR 5.94, 95% CI 3.36–10.45), and infected proportion in the general population (IRR 1.002, 95% CI 1.001–1.003) (all p < 0.01). Conversely, lockdown duration exerted a protective effect (IRR 0.95, 95% CI 0.94–0.98) (p < 0.01). The province-contextual effects accounted for 10% of the total variability. Predictive factors for peritoneal dialysis and transplant cases were center location and infected proportion in the general population. Using recursive partitioning, we identified decision thresholds at general population incidence ≥ 229 per 100,000 and at ≥ 3 positive healthcare workers. Conclusions: Beyond fixed risk factors, shared with the general population, the increased and heterogeneous proportion of positive patients is related to the center’s testing policy, the number of positive patients and healthcare workers, and to contextual effects at the province level. Nephrology centers may adopt simple decision rules to strengthen containment measures timely.

Published
2021

39. Le piccole e medie imprese italiane nella riflessione di Francesco Parrillo e nel contesto dell’economia italiana del III millennio: un percorso di ricerca sul capitalismo italiano con una verifica empirica

Author

GAROFALO,G, GUARINI, G, CHIACCHIERINI, C, Garofalo, G, Guarini, G, and Chiacchierini, C

Subjects
Bank-Industry Relationship, Business Network, PMI, Finanza, Reti d’Impresa, SMEs’, SECS-P/01 - ECONOMIA POLITICA, Banca e Industria, Finance
Abstract

Partendo dall’esame di alcuni contributi di Francesco Parrillo, compresi in un arco temporale che va dal 1983 al 1999, sul tema delle PMI (anche nei suoi riflessi finanziari), l’articolo propone una attualizzazione di quella riflessione per interpretare la realtà del sistema produttivo italiano nella seconda decade del nuovo millennio. I temi emergenti sono legati alla vitalità delle medie imprese, alla nuova manifattura digitale, ad una maggiore attenzione per la diversificazione delle fonti di finanziamento. A fronte di questi spiragli, permangono alcuni nodi critici strutturali come le difficoltà della maggior parte delle imprese, segnate dalla ridotta dimensione, la loro sottocapitalizzazione, i modelli superati di governance, che, a livello macroeconomico, comportano bassi livelli di produttività. Al riguardo viene condotta un’analisi econometrica per testare l’ipotesi che una “soluzione” possa venire da reti d’impresa che collaborano su progetti mirati di innovazione (e/o internazionalizzazione). Starting from an accurate selection of contributions written, in the 1983-1999 period, by Francesco Parrillo on SMEs (also in its financial implications), the paper proposes to contextualize its analysis in recent times, in order to interpret the modern nature of the Italian productive system. Emerging relevant topics arerelated to the dynamism of Medium-sized firms, the new digital manufacture, and to the diversification of funding sources. However, critical issues still remain, such as small dimension, undercapitalization, outdated governance, which imply low productivity levels. In this regard, we propose an econometric analysis to test the hypothesis that a “solution” can come from business networks with firms that collaborate on targeted innovation (and/or internationalization) projects.

Published
2020

43. Identifying Persistent Hot Spot Areas of Undersized Fish and Crustaceans in Southern European Waters: Implication for Fishery Management Under the Discard Ban Regulation

Author

European Commission, Fundação para a Ciência e a Tecnologia (Portugal), Agencia Estatal de Investigación (España), Milisenda, Giacomo, Garofalo, G., Fiorentino, Fabio, Colloca, Francesco, Maynou, Francesc, Ligas, Alessandro, Musumeci, Claudia, Bentes, Luis, Gonçalves, Jorge M.S., Erzini, Karim, Russo, Tommaso, D'Andrea, Lorenzo, Vitale, Sergio, European Commission, Fundação para a Ciência e a Tecnologia (Portugal), Agencia Estatal de Investigación (España), Milisenda, Giacomo, Garofalo, G., Fiorentino, Fabio, Colloca, Francesco, Maynou, Francesc, Ligas, Alessandro, Musumeci, Claudia, Bentes, Luis, Gonçalves, Jorge M.S., Erzini, Karim, Russo, Tommaso, D'Andrea, Lorenzo, and Vitale, Sergio

Abstract

The recent establishment of the “landing obligation” under the reformed EU Common Fishery Policy has the twofold objective of reducing the excessive practice of discarding unwanted catch at sea and encouraging more selective and sustainable fisheries. Within this context, the awareness of the spatial distribution of potential unwanted catches is important for devising management measures aimed to decrease discards. This study analyzed the distribution of Hot Spot density areas of demersal fish and crustaceans below the Minimum Conservation Reference Size (MCRS) in four different southern European seas: continental Portuguese coast, Catalan Sea, South of Sicily, Liguria and northern Tyrrhenian Seas using both bottom trawl survey data and information on the spatial distribution of commercial fisheries. Critical areas for discarding were identified as zones where the highest densities of individuals below MCRS were consistently recorded throughout a series of years. Results clearly showed a patchy distribution of undersized individuals in each investigated area, highlighting the overlap between high density patches of both discards and fishing effort. The present findings provide a relevant knowledge for supporting the application of spatial-based management actions, such as the designation of Fisheries Restricted Areas (FRAs), in order to minimize the by-catch of undersized specimens and improve the sustainability of demersal fisheries

Published
2021

44. Utility of ultrasound-guided fine needle aspiration cytology in assessing malignancy in head and neck pathology

Author

Petrone, G., Rossi, E. D., Gallus, R., Petrelli, L., Marrone, S., Rizzo, D., Piras, A., Garofalo, G., Rindi, G., Galli, J., Paludetti, G., Bussu, F., Petrone G., Petrelli L., Rizzo D. (ORCID:0000-0003-1809-5901), Rindi G. (ORCID:0000-0003-2996-4404), Galli J. (ORCID:0000-0001-6353-6249), Paludetti G. (ORCID:0000-0003-2480-1243), Bussu F. (ORCID:0000-0001-6261-2772), Petrone, G., Rossi, E. D., Gallus, R., Petrelli, L., Marrone, S., Rizzo, D., Piras, A., Garofalo, G., Rindi, G., Galli, J., Paludetti, G., Bussu, F., Petrone G., Petrelli L., Rizzo D. (ORCID:0000-0003-1809-5901), Rindi G. (ORCID:0000-0003-2996-4404), Galli J. (ORCID:0000-0001-6353-6249), Paludetti G. (ORCID:0000-0003-2480-1243), and Bussu F. (ORCID:0000-0001-6261-2772)

Abstract

Objective: Fine needle aspiration cytology (FNAC) is a well-established diagnostic procedure for head and neck masses not clearly originating from mucosal or cutaneous surfaces. We analysed head and neck masses evaluated over a 2-year period, to assess the reliability of FNAC for the evaluation of malignancy. Methods: We enrolled all patients undergoing FNAC, from April 2013 to July 2015, in a single service of a large Italian university hospital. Relevant clinical data and ultrasonographic parameters of the lesions were recorded. We performed both conventional and thin-prep smears. Clinical presentation, ultrasonographic features and final cytology diagnoses were analysed and correlated with histology. Results: The series included 301 lesions in 285 patients, with a single (94.4%) or two (5.6%) lesions. Only eight samples were considered non-diagnostic/inadequate (2.6%). Among the cases, 139 FNAC (46.1%) underwent surgery. Cytological-histological correspondence was found in 89% of the cases. Concerning malignancy, we documented less than 4% false positives and less than 2.5% false negatives, with 92.7% sensitivity and 94.6% specificity. Conclusion: FNAC diagnosis can be highly specific. Most importantly, it is highly reliable in assessing malignancy, thus defining the priority and guiding the management procedures.

Published
2021

49. OP03.02: Artificial intelligence applied to ultrasound diagnosis of pelvic gynecological tumours: a systematic scoping review and meta‐analysis.

Author

Garofalo, G., Geysels, A., Timmerman, S., Barreñada, L., De Moor, B., Timmerman, D., Froyman, W., and Van Calster, B.

Subjects
*ARTIFICIAL intelligence, *DEEP learning, *MACHINE learning, *DATABASES, *ADNEXAL diseases, PELVIC tumors
Abstract

This article discusses the use of artificial intelligence (AI) in the diagnosis of pelvic gynecological tumors using ultrasound imaging. The authors conducted a systematic scoping review and meta-analysis of published studies on this topic. They found that while AI has the potential to enhance diagnostic accuracy and efficiency, current AI models for US diagnosis of gynecological tumors have methodological shortcomings. The authors also noted that AI models for diagnosing adnexal malignancy did not outperform the ADNEX model, a logistic regression model based on US measurements. [Extracted from the article]

Published
2024
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50. OC05.03: *Deep learning‐enabled ovarian cancer detection with ADNEX‐AI: a prospective, multicentre study.

Author

Geysels, A., Garofalo, G., Timmerman, S., Ceusters, J., Fischerová, D., Testa, A.C., Moro, F., Buonomo, F., Valentin, L., Sladkevicius, P., Van Holsbeke, C., Kudla, M.J., Czekierdowski, A., Epstein, E., Groszmann, Y., Blaschko, M., De Moor, B., Van Calster, B., Timmerman, D., and Froyman, W.

Subjects
*CONVOLUTIONAL neural networks, *OVARIAN tumors, *DEEP learning, *RECEIVER operating characteristic curves, *EARLY detection of cancer
Abstract

This article discusses a study that introduces a deep learning-based framework called ADNEX-AI for the automated detection of ovarian cancer using ultrasound scans. The study compares the performance of ADNEX-AI with traditional clinical practice in diagnosing ovarian cancer. The results show that ADNEX-AI achieves a high level of accuracy in distinguishing between benign and malignant ovarian tumors. However, the study suggests that the difference in performance between ADNEX-AI and traditional methods may be due to the clinician's ability to examine the tumor from different angles. Overall, ADNEX-AI demonstrates comparable performance to traditional methods when considering the constraints of tumor visibility. [Extracted from the article]

Published
2024
Full Text
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