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768 results on '"Rocchi, L"'

17. Versatility of the perforator radial artery flap in the reconstruction of the upper limbs and comparison of the outcomes with the “classic” radial flap, a retrospective study

Author

Fulchignoni, Camillo, Rovere, Giuseppe, Greco, Tommaso, Perisano, Carlo, Smakaj, Amarildo, Fidanza, A., Rocchi, Lorenzo, Pataia, Elisabetta, Fulchignoni C., Rovere G., Greco T., Perisano C., Smakaj A., Rocchi L. (ORCID:0000-0001-9983-3800), Pataia E., Fulchignoni, Camillo, Rovere, Giuseppe, Greco, Tommaso, Perisano, Carlo, Smakaj, Amarildo, Fidanza, A., Rocchi, Lorenzo, Pataia, Elisabetta, Fulchignoni C., Rovere G., Greco T., Perisano C., Smakaj A., Rocchi L. (ORCID:0000-0001-9983-3800), and Pataia E.

Abstract

Introduction: Radial forearm flap, first described in the early eighties in China, is a well-known and handy flap to cover soft tissue defects of the distal upper limb. It has, though, some inconveniences, such as the sacrifice of the radial artery and non-neglectable esthetic sequelae in the donor site. In the following years, a similar flap based on the perforators of the radial artery has been described as achieving similar results, allowing to spare a main vessel. The authors reviewed retrospectively the patients that underwent surgery with one of those two flaps in their center to compare outcomes. Materials and methods: Patients operated between January 2016 and January 2022 have been reviewed. Ten had a classic radial artery flap, and ten had a radial artery perforator flap. Twelve weeks after surgery, Vancouver Scar Scale was used to assess the results at the donor site and over the flap. Reintervention and failure rate within one year and patient satisfaction -using a visual analog scale ranging from 0 to ten-at 12 months were also assessed. Results: All classic radial artery flap group patients had “successful” surgery, and none needed secondary surgery. On the other side, three patients required a second surgery in the perforator flap group, and nine out of ten ended up with “successful” flaps. Mean Vancouver Scar Scale results regarding the flap are comparable, whereas those at the donor site are significantly better in the patients with the perforator flap. Patients’ satisfaction results are similar in both groups. Conclusion: The radial artery perforator flap is an important flap to be held in mind by all surgeons approaching reconstruction of the elbow, the forearm, and the hand, and should be preferred, when possible, to the classic radial forearm flap.

Published
2023

18. Iliac bone graft for the treatment of bone loss and non-union of the distal radius

Author

Saracco, M., Merendi, Gianfranco, Rocchi, Lorenzo, Merendi G., Rocchi L. (ORCID:0000-0001-9983-3800), Saracco, M., Merendi, Gianfranco, Rocchi, Lorenzo, Merendi G., and Rocchi L. (ORCID:0000-0001-9983-3800)

Abstract

Background/Aim of the work: Open distal radius fractures are rare compared to closed ones. They mainly affect young people with high-energy trauma and are burdened with a high number of complications, including non-union. In this case report, we describe the technique used to manage bone loss and non-union of the distal radius of a polytraumatized patient with an open Gustilo IIIB fracture of the wrist. Case Report: 58-year-old man, suffering from head trauma and open right wrist fracture after motorcycle accident, underwent emergency damage control with debridement, antibiotic prophylaxis and stabilization in an external fixator. Then, he developed infection and bone loss, associated with an injury of the median nerve. Nonunion were treated with iliac crest bone graft, open reduction and internal fixation (ORIF). Outcomes: At the follow-up 6 months after the bone graft and ORIF procedure and 9 months after the trauma, the patient was clinically healed, with good performance status. Conclusions: Treatment of non-union in open distal radius fractures with iliac crest bone graft is a viable, safe and easy surgical choice.

Published
2023

20. Cerebellar noninvasive neuromodulation influences the reactivity of the contralateral primary motor cortex and surrounding areas: a TMS-EMG-EEG study

Author

Rocchi, L., Spampinato, D., Pezzopane, V., Orth, M., Bisiacchi, P., Rothwell, J., and Casula, E.

Subjects
TMS-EEG, Neurology, Cerebellum, Motor cortex, Brain oscillations, Electroencephalography, Neurology (clinical), Transcranial evoked potentials, Transcranial magnetic stimulation
Abstract

Understanding cerebellar-cortical physiological interactions is of fundamental importance to advance the efficacy of neurorehabilitation strategies for patients with cerebellar damage. Previous works have aimed to modulate this pathway by applying transcranial electrical or magnetic stimulation (TMS) over the cerebellum and probing the resulting changes in the primary motor cortex (M1) excitability with motor-evoked potentials (MEPs). While these protocols produce changes in cerebellar excitability, their ability to modulate MEPs has produced inconsistent results, mainly due to the MEP being a highly variable outcome measure that is susceptible to fluctuations in the excitability of M1 neurons and spinal interneurons. To overcome this limitation, we combined TMS with electroencephalography (EEG) to directly record TMS-evoked potentials (TEPs) and oscillations from the scalp. In three sessions, we applied intermittent theta-burst stimulation (iTBS), cathodal direct current stimulation (c-DC) or sham stimulation to modulate cerebellar activity. To assess the effects on M1 and nearby cortex, we recorded TMS-EEG and MEPs before, immediately after (T1) and 15 min (T2) following cerebellar neuromodulation. We found that cerebellar iTBS immediately increased TMS-induced alpha oscillations and produced lasting facilitatory effects on TEPs, whereas c-DC immediately decreased TMS-induced alpha oscillations and reduced TEPs. We also found increased MEP following iTBS but not after c-DC. All of the TMS-EEG measures showed high test-retest repeatability. Overall, this work importantly shows that cerebellar neuromodulation influences both cortical and corticospinal physiological measures; however, they are more pronounced and detailed when utilizing TMS-EEG outcome measures. These findings highlight the advantage of using TMS-EEG over MEPs when assessing the effects of neuromodulation.

Published
2022

23. Improving plant disease classification by adaptive minimal ensembling

Author

Bruno A., Moroni D., Dainelli R., Rocchi L., Toscano P., Morelli S., Ferrari E., and Martinelli M.

Subjects
Deep Learning, Convolutional Neural Networks, Plant diseases
Abstract

A novel method for improving plant disease classification, a challenging and time-consuming process, is proposed. First, using as baseline EfficientNet, a recent and advanced family of architectures having an excellent accuracy/complexity trade-off, we have introduced, devised, and applied refined techniques based on transfer learning, regularization, stratification, weighted metrics, and advanced optimizers in order to achieve improved performance. Then, we go further by introducing adaptive minimal ensembling, which is a unique input to the knowledge base of the proposed solution. This represents a leap forward since it allows improving the accuracy with limited complexity using only two EfficientNet-b0 weak models, performing ensembling on feature vectors by a trainable layer instead of classic aggregation on outputs. To the best of our knowledge, such an approach to ensembling has never been used before in literature. Our method was tested on PlantVillage, a public reference dataset used for benchmarking models' performances for crop disease diagnostic, considering both its original and augmented versions. We noticeably improved the state of the art by achieving 100% accuracy in both the original and augmented datasets. Results were obtained using PyTorch to train, test, and validate the models; reproducibility is granted by providing exhaustive details, including hyperparameters used in the experimentation. A Web interface is also made publicly available to test the proposed methods.

Published
2023

24. Recognition of weeds in cereals using AI architecture

Author

Dainelli R., Martinelli M., Bruno A., Moroni D., Morelli S., Silvestri M., Ferrari E., Rocchi L., and Toscano P.

Subjects
Phenotyping, Deep learning, Public dataset, EfficientNet, Weed detection
Abstract

In this study, an automatic system based on open AI architectures was developed and fed with an in-house built image dataset to recognize seven of the most widespread and hard-to-control weeds in wheat in the Mediterranean environment. A total of 10810 images were collected from the post-emergence (S1 dataset) to the pre-flowering stage (S2 dataset). A selection of pictures available from online sources (S3, 825 images) was used as a final and further independent test of the proposed recognition tool. The AI tool in the ensemble configuration achieved 100% accuracy on the validation and test set both for S1 and S2, while for S3 an accuracy of approximately 70% was achieved for weed species in the post-emergence stage.

Published
2023

25. Are all people with diabetes and cardiovascular risk factors or microvascular complications at very high risk? Findings from the Risk and Prevention Study

Author

Marzona, Irene, Avanzini, Fausto, Lucisano, Giuseppe, Tettamanti, Mauro, Baviera, Marta, Nicolucci, Antonio, Roncaglioni, Maria Carla, Tombesi, M., Tognoni, G., Massa, E., Marrocco, W., Micalella, M., Caimi, V., Longoni, P., Avanzini, F., Franzosi, M. G., Roncaglioni, M. C., Marzona, I., Baviera, M., Monesi, L., Pangrazzi, I., Barlera, S., Milani, V., Nicolis, E., Casola, C., Clerici, F., Palumbo, A., Sgaroni, G., Marchioli, R., Silletta, M. G., Pioggiarella, R., Scarano, M., Marfisi, R. M., Flamminio, A., Macino, L., Ferri, B., Pera, C., Polidoro, A., Abbatino, D., Acquati, M., Addorisio, G., Adinolfi, D., Adreani, L., Agistri, M. R., Agneta, A., Agnolio, M. L., Agostini, N., Agostino, G., Airò, A., Alaimo, N., Albano, M., Albano, N., Alecci, G., Alemanno, S., Alexanian, A., Alfarano, M., Alfè, L., Alonzo, N., Alvino, S., Ancora, A., Andiloro, S., Andreatta, E., Angeli, S., Angiari, F., Angilletti, V., Annicchiarico, C., Anzivino, M., Aprea, R., Aprile, A., Aprile, E., Aprile, I., Aprile, L., Armellani, V., Arnetoli, M., Aronica, A., Autiero, V., Bacca, G., Baccalaro, A. M., Bacci, M., Baglio, G., Bagnani, M., Baiano, A., Baldari, A., Ballarini, L., Banchi, G., Bandera, R., Bandini, F., Baratella, M., Barbieri, A., Barbieri Vita, A., Bardi, M., Barlocchi, M., Baron, P., Bartoli, M., Basile, A., Basile, F., Basile, S., Battaggia, A., Battaglia, A., Baù, A., Beconcini, G., Beggio, R., Belfiore, P. A., Belicchi, M., Bellamoli, S., Bellini, C., Bellomo, M., Benetollo, C., Benetti, R., Beretta, E., Bertalero, P., Bertaso, F. G., Bertolani, U., Bettelli, G., Biagiotti, G., Bianchi, S., Bianco, G., Biccari, F., Bigioli, F., Bindi, M., Bisanti, G., Bitetti, E. M., Blasetti, M. P., Blesi, F., Boato, V., Boga, S., Boidi, E., Boldrin, G., Bollati, A., Bolzan, L., Bolzonella, S., Bonardi, P., Bonato, G. B., Bonci, M., Bonfitto, G., Bonincontro, E., Boninsegna, F., Bonissone, D., Bono, L., Bonollo, E., Borghi, M., Borioli, N., Borsatto, M., Bosco, T., Bosisio Pioltelli, M., Botarelli, C., Botassis, S., Bottini, F., Bottos, C., Bova, G., Bova, V., Bozzani, A., Bozzetto, R. M., Braga, V. T., Braglia, M., Bramati, E., Brazzoli, C., Breglia, G., Brescia, A., Briganti, D., Brigato, G., Brocchi, A., Brosio, F. A., Bruni, E., Buscaglia, E., Bussini, M. D., Bussotti, A., Buzzaccarini, F., Buzzatti, A., Caccamo, G., Cacciavillani, C., Caggiano, G., Caimi, V., Calciano, F. P., Calderisi, M., Calienno, S., Caltagirone, P., Calzolari, I., Cammisa, M., Campanaro, M., Campanella, G. B., Campese, F., Canali, G., Candiani, D. E. L., Canepa, R., Canini, D., Canino, A., Cantoro, E. A., Capilupi, V., Capotosto, P., Cappelli, B., Capraro, G., Carafa, F. A., Carano, Q., Carcaterra, V., Carriero, D., Carrozzo, G., Cartanese, M., Casalena, M., Casarola, M., Caso, C., Casotto, M., Castaldi, F., Castegnaro, R., Castellani, G., Castri, S., Catalano, E., Catinello, N., Caturano, G., Cavallaro, R., Cavallo, A. M., Cavallo, G., Cavion, M. T., Cavirani, G., Cazzaniga, F., Cazzetta, D., Cecconi, V., Cefalo, A., Celebrano, M., Celora, A., Centonze, P., Cerati, D., Cesaretti, D., Checchia, G., Checchin, A., Cherubini, M., Chianese, L., Chiappa, A., Chiappa, M. V., Chiariello, G., Chiavini, G., Chicco, M., Chiumeo, F., Ciacciarelli, A., Ciaci, D., Ciancaglini, R., Cicale, C., Cicale, S., Cipolla, A., Ciruolo, A., Citeri, A. L., Citterio, G., Clerici, M., Coazzoli, E., Collecchia, G., Colletta, F., Colombo, I., Colorio, P., Coluccia, S., Comerio, M., Comoretto, P., Compagni, M., Conte, O., Contri, S., Contrisciani, A., Coppetti, T., Corasaniti, F., Corradi, M. T., Corsano, A., Corsini, A., Corti, N., Costantini, G., Costantino, A., Cotroneo, S., Cozzi, D., Cravello, M. G., Cristiano, E., Cucchi, R., Cusmai, L., D’Errico, G. B., D’Agostino, P., Dal Bianco, L., Dal Mutto, U., Dal Pozzo, G., Dallapiccola, P., Dallatorre, G., Dalle Molle, G., Dalloni, E., D’Aloiso, A., D’Amicis, G., Danese, R., Danieli, D., Danisi, G., D’Anna, M. A., Danti, G., D’Ascanio, S., Davidde, G., De Angeli, D., De Bastiani, R., De Battisti, A., De Bellis, A., De Berardinis, G., De Carlo, F., De Giorgi, D., De Gobbi, R., De Lorenzis, E., De Luca, P., De Martini, G., De Marzi, M., De Matteis, D., De Padova, S., De Polo, P., De Sabato, N., De Stefano, T., De Vita, M. T., De Vito, U., De Zolt, V., Debernardi, F., Del Carlo, A., Del Re, G., Del Zotti, F., D’Elia, R., Della Giovanna, P., Dell’Acqua, L., Dell’Orco, R. L., Demaria, G., Di Benedetto, M. G., Di Chiara, G., Di Corcia, V., Di Domizio, O., Di Donato, P., Di Donato, S., Di Fermo, G., Di Franco, M., Di Giovannantonio, G., Di Lascio, G., Di Lecce, G., Di Lorenzo, N., Di Maro, T., Di Mattia, Q., Di Michele, E., Di Modica, R. S., Di Murro, D., Di Noi, M. C., Di Paoli, V., Di Santi, M., Di Sanzo, A., Di Turi, C., Diazzi, A., Dileo, I., D’Ingianna, A. P., Dolci, A., Donà, G., Donato, C., Donato, P., Donini, A., Donna, M. E., Donvito, T. V., Esposito, L., Esposito, N., Evangelista, M., Faita, G., Falco, M., Falcone, D. A., Falorni, F., Fanciullacci, A., Fanton, L., Fasolo, L., Fassina, R., Fassone, A., Fatarella, P., Fedele, F., Fera, I., Fera, L., Ferioli, S., Ferlini, M. G., Ferlino, R., Ferrante, G., Ferrara, F. N., Ferrarese, M. F., Ferrari, G., Ferrari, O., Ferreri, A., Ferroni, M., Fezzi, G., Figaroli, C., Fina, M. G., Fioretta, A., Fiorucci, C., Firrincieli, R., Fischetti, M., Fischietti, G., Fiume, D. C., Flecchia, G., Forastiere, G., Fossati, B., Franceschi, P. L., Franchi, L., Franzoso, F., Frapporti, G., Frasca, G., Frisotti, A., Fumagalli, G., Fusco, D., Gabriele, P., Gabrieli, A., Gagliano, D., Galimberti, G., Galli, A., Gallicchio, N., Gallio, F., Gallipoli, T., Gallo, P., Galopin, T., Gambarelli, L., Garbin, A., Garozzo, G. M., Gasparri, R., Gastaldo, M., Gatti, E., Gazzaniga, P., Gennachi, N., Gentile, R. V., Germani, P., Gesualdi, F., Gherardi, E., Ghezzi, C., Ghidini, M. G., Ghionda, F., Giacci, L., Gialdini, D., Giampaolo, C., Giancane, R., Giannanti, A., Giannese, S., Giannini, L., Giaretta, M., Giaretta, R., Giavardi, L., Giordano, P., Giordano, E., Giordano, B., Gioria, G. M., Giugliano, R., Grassi, E. A., Greco, A., Greco, L., Grilletti, N., Grimaldi, N., Grisetti, G., Groppelli, G., Gualtieri, L., Guarducci, M., Guastella, G., Guerra, M., Guerrini, F., Guglielmini, A., Guido, A., Gulotta, P., Iacono, E., Iadarola, G., Ianiro, G., Iarussi, V., Ieluzzi, M. L., Ierardi, C., Ingaldi, F., Interlandi, S., Iocca, M., Iorno, A., Ioverno, E., Iurato, R., La Pace, L., La Piscopia, C., La Selva, R., Lafratta, M., Lamparelli, M., Lanaro, G., Lancerotto, R., Larcher, M., Lassandro, M., Lattuada, G., Laurino, P., Lefons, C., Legrottaglie, F., Lemma, A., Leone, D., Leone, F., Leso, A., Leuzzi, G., Levato, G., Libardi, L., Libralesso, N., Licini, P. I., Licursi, G., Lidonnici, F., Lillo, C., Liveri, L., Livio, A., Loiero, R. A., Loison, M., Lombardo, G., Lombardo, T., Lomunno, V., Lomuscio, S., Lonedo, A., Longo, E., Longoni, P., Lora, L., Lotterio, A., Lucatello, L., Luongo, A., Lupoli, M., Macchia, C., Macri, G., Mafessanti, M., Maggialetti, V., Maggioni, A., Magnani, M., Maiellaro, G., Mancuso, A., Maniglio, A. R., Mannari, G. L., Manni, A., Manocchio, B., Mao, M., Maranò, A., Maraone, E., Marascio, D., Marcheselli, P., Marchetto, B., Marchetto, S., Marchi, A., Marchi, G. L., Mariano, C., Marinacci, S., Marinelli, S., Marini, G., Marra, V. C., Marrali, F., Marseglia, C., Martello, G., Martino, C., Martino, G., Martino, M., Marulli, C. F., Maruzzi, G., Marzotti, A., Mascheroni, G., Mascolo, P., Masoch, G., Masone, R., Massa, E., Massa, L., Massafra, M., Massi, M., Massignani, D. M., Matarese, A. M., Matini, G., Mauro, R., Mazzi, M., Mazzillo, A., Mazzocato, E., Mazzoleni, N. S., Mazzone, A., Melacci, A., Mele, E., Meliota, P., Menaspà, S., Meneghello, F., Merola, G., Merone, L., Metrucci, A., Mezzina, V., Micchi, A., Michielon, A., Migliore, N., Minero, G., Minotta, F., Mirandola, C., Mistrorigo, S., Modafferi, L., Moitre, R., Mola, E., Monachese, C., Mongiardini, C., Montagna, F., Montani, M., Montemurno, I., Montolli, R., Montorsi, S., Montresor, M., Monzani, M. G., Morabito, F., Mori, G., Moro, A., Mosca, M. F., Motti, F., Muddolon, L., Mugnai, M., Muscas, F., Naimoli, F., Nanci, G., Nargi, E., Nasorri, R., Nastrini, G., Negossi, M., Negrini, A., Negroni, A., Neola, V., Niccolini, F., Niro, C. M., Nosengo, C., Novella, G., Nuti, C., Obici, F., Olita, C., Oliverio, S. S., Olivieri, I., Oriente, S., Orlando, G., Paci, C., Pagano, G., Pagliara, C., Paita, G., Paladini, G., Paladino, G., Palano, T., Palatella, A., Palermo, P., Palmisano, M., Pando, P., Panessa, P., Panigo, F., Panozzo, G., Panvini, F., Panzieri, F., Panzino, A., Panzitta, F., Paoli, N., Papagna, R., Papaleo, M. G., Papalia, G., Parisi, R., Parotti, N., Parravicini, D., Passarella, P., Pastore, G. A., Patafio, M., Pavone, P., Pedroli, W., Pedroni, M., Pelligra, G., Pellizzari, M., Penati, A., Perlot, M., Perrone, A., Perrone, G., Peruzzi, P., Peselli, C., Petracchini, L., Petrera, L., Petrone, S., Peverelli, C., Pianorsi, F., Piazza, G. P., Piazzolla, G., Picci, A., Pienabarca, G., Pietronigro, T. P., Pignocchino, P., Pilone, R., Pinto, D., Pirovano, E., Pirrotta, D., Pisante, V., Pitotto, P., Pittari, L., Piva, A., Pizzoglio, A., Plantera, O. R., Plebani, W., Plessi, S., Podrecca, D., Poerio, V., Poggiani, F., Pogliani, W., Poli, L., Poloni, F. G., Porcelli, R., Porto, S., Pranzo, L., Prevedello, C., Profeta, C., Profico, D., Punzi, A., Quaglia, G. M., Racano, M., Raccone, A., Radice, F., Raho, C. A., Raimondi, R., Rainò, M., Ramponi, R., Ramunni, A., Ramunni, A. L., Ravasio, F., Ravera, M., Re Sartò, G., Rebustello, G., Regazzoli, S., Restelli, C., Rezzonico, M., Ricchiuto, F., Rigo, S., Rigon, G., Rigon, R., Rinaldi, O. V., Rinaldi, M., Risplendente, P. G., Rispoli, M., Riundi, R., Riva, M. G., Rizzi, A. L., Rizzi, D., Rizzo, L. D., Rocchi, L., Rondinone, B., Rosa, B., Rosati, F., Roselli, F., Rossetti, A., Rossetti, C., Rossi, R., Rossi, P. R., Rossi, A., Rossi, C. L., Rossitto, A., Ruffini, R., Ruffo, A., Ruggio, S., Ruo, M., Russo, B., Russo, L., Russo, R., Russo, S., Russo, U., Russo, V., Ruta, G., Sacchi, F., Sacco Botto, F., Saia, A., Salladini, G., Salmoiraghi, S., Saluzzo, F., Salvatore, C., Salvatori, E., Salvio, G., Sandri, P., Sandrini, T., Sangermano, V., Santoni, N., Saracino, A. D., Saracino, A., Sarasin, P., Sardo Infirri, C., Sarrì, B., Sartori, G., Sartori, N., Sauro, C., Scaglioni, M., Scalfi, C., Scamardella, A. M., Scandale, G., Scandone, L., Scannavini, G., Scarati, R., Scardi, A., Scarpa, F. M., Scazzi, P., Schifone, A., Schiroso, G., Scigliano, G., Scilla, A., Sciortino, M., Scolaro, G., Scollo, E., Scorretti, G., Sellitti, R., Selmo, A., Selvaggio, G., Sempio, A., Seren, F., Serio, L., Serra, C., Serra, L., Siciliano, D., Sideri, A., Sighele, M., Signore, R., Siliberto, F., Silvestro, M., Simioni, G., Simmini, G., Simonato, L., Sinchetto, F., Sizzano, E., Smajato, G., Smaldone, M., Sola, G., Sordillo, L., Sovran, C. S., Spagnul, P., Spanò, F., Sproviero, S., Squintani, A., Stella, L., Stilo, V., Stocchiero, B., Stornello, M. C., Stracka, G., Strada, S., Stranieri, G., Stucci, N., Stufano, N., Suppa, A., Susca, V. G., Sutti, M., Taddei, M., Tagliabue, E., Tagliente, G., Talato, F., Talerico, P., Talia, R., Taranto, R., Tartaglia, M., Tauro, N., Tedesco, A., Tieri, P., Tirelli, M., Tocci, L., Todesco, P., Tognolo, M., Tomba, A., Tonello, P., Tonon, R., Toscano, L., Tosi, A., Tosi, G., Toso, S., Travaglio, P., Tremul, L., Tresso, C., Triacchini, P., Triggiano, L., Trigilio, A., Trimeloni, J., Tripicchio, G., Tritto, G. S., Trono, F., Trotta, E., Trotta, G., Tubertini, A., Turri, C., Turri, L., Tuttolani, M. P., Urago, M., Ursini, G., Valcanover, F., Valente, L., Valenti, M., Valentini, F., Vallone, G., Valz, P., Valzano, L., Vanin, V., Vatteroni, M., Vegetti, L., Vendrame, D., Veramonti, I., Veronelli, G., Vesco, A., Vicariotto, G., Vignale, G., Villa, P. L., Vinciguerra, R., Visco, A., Visentin, G., Visonà, E., Vitali, E., Vitali, S., Vitti, F., Volpone, D. A., Zambon, N., Zammarrelli, A., Zanaboni, A., Zane, D., Zanetti, B., Zanibellato, R., Zappetti, M., Zappone, P., Zerilli, G., Zirino, V., Zoccali, R., Zuin, F., Altomonte, M., Anelli, N., Angiò, F., Annale, P., Antonacci, S., Anzilotta, R., Bano, F., Basadonna, O., Beduschi, L., Becagli, P., Bellotti, G., Blotta, C., Bruno, G., Cappuccini, A., Caramatti, S., Cariolato, M. P., Castellana, M., Castellani, L., Catania, R., Chielli, A., Chinellato, A., Ciaccia, A., Clerici, E., Cocci, A., Costanzo, G., D’Ercole, F., De Stefano, G., Decè, F., Di Cicco, N., Di Marco, A., Donati Sarti, C., Draghi, E., Dusi, G., Esposito, V., Ferraro, L., Ferretti, A., Ferri, E., Foggetti, L., Foglia, A., Fonzi, E., Frau, G., Fuoco, M. R., Furci, G., Gallo, L., Garra, V., Giannini, A., Gris, A., Iacovino, R., Interrigi, R., Joppi, R., Laner, B., La Fortezza, G., La Padula, A., Lista, M. R., Lupi, G., Maffei, D., Maggioni, G., Magnani, L., Marrazzo, E., Marcon, L., Marinò, V., Maroni, A., Martinelli, C., Mastandrea, E., Mastropierro, F., Meo, A. T., Mero, P., Minesso, E., Moschetta, V., Mosele, E., Nanni, C., Negretti, A., Nisticò, C., Orsini, A., Osti, M., Pacilli, M. C., Pennestre, C., Picerno, G., Piol, K., Pivano, L., Pizzuti, E., Poggi, L., Poidomani, I., Pozzetto, M., Presti, M. L., Ravani, R., Recalenda, V., Romagnuolo, F., Rossignoli, S., Rossin, E., Sabatella, C., Sacco, F., Sanità, F., Sansone, E., Servadei, F., Sisto, M. T., Sorio, A., Sorrentino, A., Spinelli, E., Spolaor, A., Squillacioti, A., Stella, P., Talerico, A., Todisco, C., Vadino, M., Zuliani, C., and Risk & Prevention Collaborative Group

Published
2017
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31. Using accounting dataset for agricultural sustainability assessment through a multi‐criteria approach: an Italian case study.

Author

Boggia, A., Fagioli, F. F., Paolotti, L., Ruiz, F., Cabello, J.M., and Rocchi, L.

Subjects
AGRICULTURE, SUSTAINABLE agriculture, AGRICULTURAL extension work, SUSTAINABILITY, FARM income, AGRICULTURAL laborers
Abstract

Sustainability has become a key issue for agricultural systems. In this context, sustainability assessment implies considering different aspects of agricultural activities, including environmental, economic and social issues, and it is usually based on practice‐based indicators. However, proposed methods and applications are still rare due to the difficulty to build a strong general framework and to find appropriate data. The present work develops a performance indicator framework using farm accounting data from the Italian Agricultural Accounting Information Network and proposes a multi‐criteria approach based on the multiple reference point weak‐strong composite indicators (MRP‐WSCI) method to assess the degree of sustainability at the farm level. This method, widely applied to sustainability assessment, calculates the relative rankings including the weak and strong approaches to sustainability and facilitates an understanding of the different indices used, but it is still unused in the agricultural sector. The proposed evaluation framework shows that MRP‐WSCI can handle a holistic set of indicators and rank the farms according to their level of sustainability, making it suitable for the agricultural farm sustainability assessment. Our results show that none of the farms in the case study sample can be classified as "good," according to some of the indices produced, that is, the strong–strong and strong–weak index, while just two of them are good for the weak–weak index. Although the size of the sample used is small, the methodological approach proposed can be straightforwardly extended to larger samples. This methodology can provide information regarding the sustainability of farms to regional and/or national agricultural offices, agricultural extension workers, and farmers themselves, helping in understanding issues in specific dimensions. [ABSTRACT FROM AUTHOR]

Published
2023
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33. Voluntary Inhibitory Control of Chorea: A Case Series

Author

Bonomo, R, Latorre, A, Balint, B, Smilowska, K, Rocchi, L, Rothwell, J, Zappia, M, Bhatia, K, Bonomo R., Latorre A., Balint B., Smilowska K., Rocchi L., Rothwell J. C., Zappia M., Bhatia K. P., Bonomo, R, Latorre, A, Balint, B, Smilowska, K, Rocchi, L, Rothwell, J, Zappia, M, Bhatia, K, Bonomo R., Latorre A., Balint B., Smilowska K., Rocchi L., Rothwell J. C., Zappia M., and Bhatia K. P.

Abstract

Background: Volitional control of involuntary movements has so far been considered a hallmark of tic disorders. However, modulation of involuntary movements can also be observed in other hyperkinesias. Cases: Here, we present 6 patients with chorea able to suppress their involuntary movements, on demand. In 3 of them, surface electromyography was used to quantify degree of suppression and confirmed a reduction of muscle activity up to 68%, during volitional control. Conclusion: This observation represents a first step toward a description of a new clinical feature in choreic syndromes and an opportunity to redefine the role of volitional inhibition in hyperkinetic movement disorders.

Published
2020

34. A Critical Investigation of Cerebellar Associative Learning in Isolated Dystonia

Author

Sadnicka, A., Rocchi, L., Latorre, A., Antelmi, E., Teo, J., Pareés, I., Hoffland, B.S., Brock, K., Kornysheva, K., Edwards, Mark J., Bhatia, K.P., Rothwell, J.C., Sadnicka, A., Rocchi, L., Latorre, A., Antelmi, E., Teo, J., Pareés, I., Hoffland, B.S., Brock, K., Kornysheva, K., Edwards, Mark J., Bhatia, K.P., and Rothwell, J.C.

Abstract

Contains fulltext : 252046.pdf (Publisher’s version ) (Open Access), BACKGROUND: Impaired eyeblink conditioning is often cited as evidence for cerebellar dysfunction in isolated dystonia yet the results from individual studies are conflicting and underpowered. OBJECTIVE: To systematically examine the influence of dystonia, dystonia subtype, and clinical features over eyeblink conditioning within a statistical model which controlled for the covariates age and sex. METHODS: Original neurophysiological data from all published studies (until 2019) were shared and compared to an age- and sex-matched control group. Two raters blinded to participant identity rescored all recordings (6732 trials). After higher inter-rater agreement was confirmed, mean conditioning per block across raters was entered into a mixed repetitive measures model. RESULTS: Isolated dystonia (P = 0.517) and the subtypes of isolated dystonia (cervical dystonia, DYT-TOR1A, DYT-THAP1, and focal hand dystonia) had similar levels of eyeblink conditioning relative to controls. The presence of tremor did not significantly influence levels of eyeblink conditioning. A large range of eyeblink conditioning behavior was seen in both health and dystonia and sample size estimates are provided for future studies. CONCLUSIONS: The similarity of eyeblink conditioning behavior in dystonia and controls is against a global cerebellar learning deficit in isolated dystonia. Precise mechanisms for how the cerebellum interplays mechanistically with other key neuroanatomical nodes within the dystonic network remains an open research question. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.

Published
2022

35. Trapeziectomy and suspension ligamentoplasty for surgical revision of trapeziometacarpal joint arthrodesis failure: two cases

Author

Merendi, Gianfranco, Fulchignoni, Camillo, Pietramala, Silvia, Rocchi, Lorenzo, Merendi G., Fulchignoni C., Pietramala S., Rocchi L. (ORCID:0000-0001-9983-3800), Merendi, Gianfranco, Fulchignoni, Camillo, Pietramala, Silvia, Rocchi, Lorenzo, Merendi G., Fulchignoni C., Pietramala S., and Rocchi L. (ORCID:0000-0001-9983-3800)

Abstract

Trapeziometacarpal joint osteoarthritis is a common degenerative disease. Arthrodesis is a widespread historical surgical technique to treat this pathology, providing pain relief and stability and strength of the thumb. Nevertheless, pantrapezial arthritis and non-union are not uncommon complications, leading in some cases to revision surgery. No gold-standard procedure has been described for revision of trapeziometacarpal arthrodesis failure. We describe two cases of failed arthrodesis treated with trapeziectomy and suspension ligamentoplasty, a well-known, biological, low-cost, successful, and easy-to-perform procedure.

Published
2022

36. Matriderm dermal substitute in the treatment of post traumatic hand’s fingertip tissue loss

Author

Fulchignoni, Camillo, Rocchi, Lorenzo, Cauteruccio, M., Merendi, Gianfranco, Fulchignoni C., Rocchi L. (ORCID:0000-0001-9983-3800), Merendi G., Fulchignoni, Camillo, Rocchi, Lorenzo, Cauteruccio, M., Merendi, Gianfranco, Fulchignoni C., Rocchi L. (ORCID:0000-0001-9983-3800), and Merendi G.

Abstract

Introduction: Treatment of fingers tissue loss is particularly challenging as it often necessitates advanced reconstructive techniques such as flaps or grafts, with esthetic and functional results that are not always as good as hoped for, with long healing times. Recently, along with tissue engineering development, numerous types of dermal substitute have been commercialized, with promising possibilities of treatment in finger tissue loss. In the author's unit, Matriderm® is the most commonly used dermal substitute. As described by the manufacturer, this scaffold is designed to be covered with a split-thickness skin graft. In using a two-step procedure, the authors realized that in most cases of fingertips injuries, at three weeks follow-up, the wound appeared in an advanced state of healing, which permitted to avoid grafting. Material And Methods: Between October 2017 and October 2018, 27 fingers have been included in this study. Patients have been divided in two groups: those treated with Matriderm® alone (15 fingers) and those who had a skin graft three weeks after the first surgery (12 fingers). At the 6-month follow-up, authors evaluated the esthetic results with the Vancouver Scar Scale (VSS), the functional results with Quick Disability of the Arm, Shoulder and Hand (qDASH) score, and sensibility by the mean of two-point discrimination test (2-PD). Results: All outcomes were overlapping in patients treated with or without skin graft: mean VSS was 2.3, mean qDASH was 13.3, and mean 2-PD was 7.7 mm. Conclusions: The results obtained allow to consider Matriderm®, used also without skin graft coverage, as a valid solution for treatment of fingertip tissue loss.

Published
2022

37. Resurfacing Capitate Pyrocarbon Implant for the treatment of advanced wrist arthritis in the elderly: a retrospective study

Author

Rocchi, Lorenzo, De Vitis, Rocco, Pietramala, Silvia, Fulchignoni, Camillo, D'Orio, Marco, Mazzone, Vincent Joseph, Marcuzzi, A., Rocchi L. (ORCID:0000-0001-9983-3800), De Vitis R., Pietramala S., Fulchignoni C., D'Orio M., Mazzone V., Rocchi, Lorenzo, De Vitis, Rocco, Pietramala, Silvia, Fulchignoni, Camillo, D'Orio, Marco, Mazzone, Vincent Joseph, Marcuzzi, A., Rocchi L. (ORCID:0000-0001-9983-3800), De Vitis R., Pietramala S., Fulchignoni C., D'Orio M., and Mazzone V.

Abstract

OBJECTIVE: Advanced forms of wrist osteoarthritis in the elderly are quite common and often under-treated, preferring a conservative management of the condition due to the age of the patient. However, in elderly people who are still active, sporty and physically demanding, surgical management of wrist osteoarthritis should be considered. Proximal Row Carpectomy associated with a Resurfacing Capitate Pyrocarbon Implant (RCPI), allows the management of a wide range of wrist arthrosis, involving both the radio-carpal and the mid-carpal joints. This treatment has been already reported as a solution in younger people affected by degenerative pathologies of the wrist, giving overall good results. Authors aimed at verifying how this technique could be useful in elderly patients, resolving the severe pain often related to this pathology and letting them recover strength and motion. PATIENTS AND METHODS: This is a retrospective analysis involving 7 cases of elderly men (mean age = 68 y.o.), suffering from severe wrist arthritis and treated with RCPI between 2016 and 2021. RESULTS: All patients reported a return to manual activities between 6 and 12 months after surgery, significantly improving pain. Two patients complained moderate pain under strain at follow-up, with residual difficulty in performing manual tasks. In all cases, an increase of strength and improvement in terms of stiffness was registered. No cases of infections or implant mobilization were reported. CONCLUSIONS: RCPI combined with proximal row carpectomy shows satisfying results in all published studies and it has been confirmed in our series as well. Indications for this procedure should be widened to elderly people, as useful alternatives to more aggressive salvage procedures, such as total prosthesis or arthrodesis.

Published
2022

49. Improving Plant Disease Classification by Adaptive Minimal Ensembling

Author

Bruno A., Moroni D., Dainelli R., Rocchi L., Toscano P., Ferrari E., and Martinelli M.

Subjects
Deep Learning, Convolutional Neural Networks, Plant diseases
Abstract

Plant disease diagnosis is a challenging and time consuming process. In recent years, the evolution of neural network technologies has made it possible to improve automatic recognition. In this article, we propose a novel method to improve the state of the art in plant disease classification. Using as baseline EfficientNet, a recent and advanced family of architectures, we have devised and applied specific design choices, namely stratification, refining validation, regularization and minimal ensembling, using specific transfer learning, optimizer and accuracy test. Our method was tested on PlanVillage as baseline, a public reference dataset used to benchmark models' performances in this domain in both its original and augmented versions, with 55,448 and 61,486 images, respectively. We noticeably improved the state of the art of PlantVillage classification by achieving zero errors in both the original and augmented dataset. In addition, the proposed method requires fewer parameters than the previous state of the art. Results shown were obtained using PyTorch to train, test and validate the models; reproducibility is granted by the provision of exhaustive details including hyperparameters used in the experimentation. A Web interface is also made publicly available to test the proposed methods.

Published
2021

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