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  1. Article ; Online: An immunological glimpse of human virus peptides: Distance from self, MHC class I binding, proteasome cleveage, TAP transport and sequence composition entropy.

    Santoni, Daniele / Felici, Giovanni

    Virus research

    2022  Volume 317, Page(s) 198814

    Abstract: Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the ... ...

    Abstract Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the cell. Predicting if a peptide is exposed is important to shed light on the rules that govern immune response and, thus, identify potential targets and design vaccine and drugs. We focused on peptides exposed on cell surface and made accessible to immune system through the MHC Class I complex. Before this can happen, three successive selection steps have to take place: a) Proteasome cleveage, b) TAP Transport, and c) binding to MHC-class I. Starting from a set of 211 host human reference viruses, we computed the set of unique peptides occurring in the correspondent proteomes. Then, we obtained the probability values of Proteasome Cleveage, TAP Transport and Binding to MHC Class I associated to those peptides through established prediction software tools. Such values were analysed in conjunction with two other features that could play a major role: the distance from self, strictly linked to the concept of nullomers, and the sequence entropy, measuring the complexity of the peptide amino acid composition. The analysis confirmed and extended previous results on a larger, more significant and consistent data set; we showed that the higher the distances from self, the higher the score of TAP Transport and binding to MHC class I; no significant association was instead found between distance from self and Proteasome Cleveage. Additionally, amino acid peptide composition entropy was significantly associated with the other features. In particular, higher entropies were linked with higher scores of Proteasome Cleveage, TAP Transport, Binding to MHC Class I, and higher distance from self. The relationship among the three selection steps provided evidence of a tight inter-correlation, clearly suggesting it could be the product of a co-evolutive process. We believe that these results give new insights on the complex processes that regulate peptide presentation through MHC class I, and unveil the mechanisms the allow the immune system to distinguish self and viral non-self peptides.
    MeSH term(s) ATP-Binding Cassette Transporters/genetics ; Amino Acids ; Antigen Presentation ; Entropy ; Epitopes ; Histocompatibility Antigens Class I/metabolism ; Humans ; Peptides ; Proteasome Endopeptidase Complex/metabolism ; Viruses/metabolism
    Chemical Substances ATP-Binding Cassette Transporters ; Amino Acids ; Epitopes ; Histocompatibility Antigens Class I ; Peptides ; Proteasome Endopeptidase Complex (EC 3.4.25.1)
    Language English
    Publishing date 2022-05-16
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 605780-9
    ISSN 1872-7492 ; 0168-1702
    ISSN (online) 1872-7492
    ISSN 0168-1702
    DOI 10.1016/j.virusres.2022.198814
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: Optimizing accuracy and diversity

    Felici, Giovanni / Sudoso, Antonio M.

    a multi-task approach to forecast combinations

    2023  

    Abstract: Forecast combination involves using multiple forecasts to create a single, more accurate prediction. Recently, feature-based forecasting has been employed to either select the most appropriate forecasting models or to optimize the weights of their ... ...

    Abstract Forecast combination involves using multiple forecasts to create a single, more accurate prediction. Recently, feature-based forecasting has been employed to either select the most appropriate forecasting models or to optimize the weights of their combination. In this paper, we present a multi-task optimization paradigm that focuses on solving both problems simultaneously and enriches current operational research approaches to forecasting. In essence, it incorporates an additional learning and optimization task into the standard feature-based forecasting approach, focusing on the identification of an optimal set of forecasting methods. During the training phase, an optimization model with linear constraints and quadratic objective function is employed to identify accurate and diverse methods for each time series. Moreover, within the training phase, a neural network is used to learn the behavior of that optimization model. Once training is completed the candidate set of methods is identified using the network. The proposed approach elicits the essential role of diversity in feature-based forecasting and highlights the interplay between model combination and model selection when optimizing forecasting ensembles. Experimental results on a large set of series from the M4 competition dataset show that our proposal enhances point forecast accuracy compared to state-of-the-art methods.
    Keywords Computer Science - Machine Learning ; Mathematics - Optimization and Control ; Statistics - Machine Learning
    Subject code 006
    Publishing date 2023-10-31
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Endoscopic third ventriculostomy in an infant with vein of Galen aneurysmal malformation treated by endovascular occlusion: Case report and a review of literature.

    Lomachinsky, V / Taborsky, J / Felici, G / Charvat, F / Benes Iii, V / Liby, P

    Neuro-Chirurgie

    2022  Volume 68, Issue 5, Page(s) 540–543

    Abstract: Introduction: Vein of Galen aneurysmal malformations (VGAMs) can, through multiple mechanisms, complicate with hydrocephalus (HCP). It is generally agreed that management strategies in this scenario should focus on endovascular embolizations. Treatment ... ...

    Abstract Introduction: Vein of Galen aneurysmal malformations (VGAMs) can, through multiple mechanisms, complicate with hydrocephalus (HCP). It is generally agreed that management strategies in this scenario should focus on endovascular embolizations. Treatment options for non-responders, however, have been only scarcely reported upon.
    Case presentation: We present a nine-month-old boy with a mural type VGAM complicated by HCP. Despite endovascular occlusion of the sole feeder, the child exhibited hydrocephalus progression prompting an Endoscopic Third Ventriculostomy (ETV). This procedure restored a cerebrospinal fluid (CSF) circulation otherwise impaired by aqueduct obstruction. Later, a new feeder arose and a second embolization was ultimately needed in order to achieve VGAM regression. Throughout four years of follow up, the child attained all developmental marks.
    Discussion/conclusion: VGAMs are prone to hydrocephalus development as there is both an underlying venous congestion and a mechanical, obstructive component. Although there is a rationale for addressing both components, the underlying AV shunts and subsequent venous pressure elevations usually determine failure of traditional CSF shunting strategies. It is therefore challenging to manage HCP in patients who failed to improve following endovascular embolizations. For such cases, ETV stands as an elegant minimal invasive alternative with potential to provide a more physiologic drainage route and thus better allow for neurological development.
    MeSH term(s) Cerebral Veins/abnormalities ; Cerebral Veins/surgery ; Humans ; Hydrocephalus/etiology ; Hydrocephalus/surgery ; Infant ; Male ; Third Ventricle/surgery ; Vein of Galen Malformations/complications ; Vein of Galen Malformations/diagnosis ; Vein of Galen Malformations/surgery ; Ventriculostomy/methods
    Language English
    Publishing date 2022-01-14
    Publishing country France
    Document type Case Reports ; Journal Article ; Review
    ZDB-ID 207146-0
    ISSN 1773-0619 ; 0028-3770 ; 0150-9586
    ISSN (online) 1773-0619
    ISSN 0028-3770 ; 0150-9586
    DOI 10.1016/j.neuchi.2021.12.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A readout system for highly sensitive diamond detectors for FLASH dosimetry.

    Pettinato, Sara / Felici, Giuseppe / Galluzzo, Lorenzo / Rossi, Maria Cristina / Girolami, Marco / Salvatori, Stefano

    Physics and imaging in radiation oncology

    2024  Volume 29, Page(s) 100538

    Abstract: Accurate dosimetry of ultra-high dose-rate beams using diamond detectors remains challenging, primarily due to the elevated photocurrent peaks exceeding the input dynamics of precision electrometers. This work aimed at demonstrating the effectiveness of ... ...

    Abstract Accurate dosimetry of ultra-high dose-rate beams using diamond detectors remains challenging, primarily due to the elevated photocurrent peaks exceeding the input dynamics of precision electrometers. This work aimed at demonstrating the effectiveness of compact gated-integration electronics in conditioning the current peaks (>20 mA) generated by a highly sensitive (
    Language English
    Publishing date 2024-01-19
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2405-6316
    ISSN (online) 2405-6316
    DOI 10.1016/j.phro.2024.100538
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: MIP-BOOST: Efficient and Effective

    Kenney, Ana / Chiaromonte, Francesca / Felici, Giovanni

    Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America

    2021  Volume 30, Issue 3, Page(s) 566–577

    Abstract: Recent advances in mathematical programming have made Mixed Integer Optimization a competitive alternative to popular regularization methods for selecting features in regression problems. The approach exhibits unquestionable foundational appeal and ... ...

    Abstract Recent advances in mathematical programming have made Mixed Integer Optimization a competitive alternative to popular regularization methods for selecting features in regression problems. The approach exhibits unquestionable foundational appeal and versatility, but also poses important challenges. Here we propose MIP-BOOST, a revision of standard Mixed Integer Programming feature selection that reduces the computational burden of tuning the critical sparsity bound parameter and improves performance in the presence of feature collinearity and of signals that vary in nature and strength. The final outcome is a more efficient and effective
    Language English
    Publishing date 2021-01-04
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2014382-5
    ISSN 1537-2715 ; 1061-8600
    ISSN (online) 1537-2715
    ISSN 1061-8600
    DOI 10.1080/10618600.2020.1845184
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Simultaneous feature selection and outlier detection with optimality guarantees.

    Insolia, Luca / Kenney, Ana / Chiaromonte, Francesca / Felici, Giovanni

    Biometrics

    2021  Volume 78, Issue 4, Page(s) 1592–1603

    Abstract: Biomedical research is increasingly data rich, with studies comprising ever growing numbers of features. The larger a study, the higher the likelihood that a substantial portion of the features may be redundant and/or contain contamination (outlying ... ...

    Abstract Biomedical research is increasingly data rich, with studies comprising ever growing numbers of features. The larger a study, the higher the likelihood that a substantial portion of the features may be redundant and/or contain contamination (outlying values). This poses serious challenges, which are exacerbated in cases where the sample sizes are relatively small. Effective and efficient approaches to perform sparse estimation in the presence of outliers are critical for these studies, and have received considerable attention in the last decade. We contribute to this area considering high-dimensional regressions contaminated by multiple mean-shift outliers affecting both the response and the design matrix. We develop a general framework and use mixed-integer programming to simultaneously perform feature selection and outlier detection with provably optimal guarantees. We prove theoretical properties for our approach, that is, a necessary and sufficient condition for the robustly strong oracle property, where the number of features can increase exponentially with the sample size; the optimal estimation of parameters; and the breakdown point of the resulting estimates. Moreover, we provide computationally efficient procedures to tune integer constraints and warm-start the algorithm. We show the superior performance of our proposal compared to existing heuristic methods through simulations and use it to study the relationships between childhood obesity and the human microbiome.
    MeSH term(s) Child ; Humans ; Pediatric Obesity ; Algorithms ; Sample Size ; Probability
    Language English
    Publishing date 2021-09-20
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 213543-7
    ISSN 1541-0420 ; 0099-4987 ; 0006-341X
    ISSN (online) 1541-0420
    ISSN 0099-4987 ; 0006-341X
    DOI 10.1111/biom.13553
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: A novel method and software for automatically classifying Alzheimer's disease patients by magnetic resonance imaging analysis.

    Previtali, F / Bertolazzi, P / Felici, G / Weitschek, E

    Computer methods and programs in biomedicine

    2017  Volume 143, Page(s) 89–95

    Abstract: Background and objective: The cause of the Alzheimer's disease is poorly understood and to date no treatment to stop or reverse its progression has been discovered. In developed countries, the Alzheimer's disease is one of the most financially costly ... ...

    Abstract Background and objective: The cause of the Alzheimer's disease is poorly understood and to date no treatment to stop or reverse its progression has been discovered. In developed countries, the Alzheimer's disease is one of the most financially costly diseases due to the requirement of continuous treatments as well as the need of assistance or supervision with the most cognitively demanding activities as time goes by. The objective of this work is to present an automated approach for classifying the Alzheimer's disease from magnetic resonance imaging (MRI) patient brain scans. The method is fast and reliable for a suitable and straightforward deploy in clinical applications for helping diagnosing and improving the efficacy of medical treatments by recognising the disease state of the patient.
    Methods: Many features can be extracted from magnetic resonance images, but most are not suitable for the classification task. Therefore, we propose a new feature extraction technique from patients' MRI brain scans that is based on a recent computer vision method, called Oriented FAST and Rotated BRIEF. The extracted features are processed with the definition and the combination of two new metrics, i.e., their spatial position and their distribution around the patient's brain, and given as input to a function-based classifier (i.e., Support Vector Machines).
    Results: We report the comparison with recent state-of-the-art approaches on two established medical data sets (ADNI and OASIS). In the case of binary classification (case vs control), our proposed approach outperforms most state-of-the-art techniques, while having comparable results with the others. Specifically, we obtain 100% (97%) of accuracy, 100% (97%) sensitivity and 99% (93%) specificity for the ADNI (OASIS) data set. When dealing with three or four classes (i.e., classification of all subjects) our method is the only one that reaches remarkable performance in terms of classification accuracy, sensitivity and specificity, outperforming the state-of-the-art approaches. In particular, in the ADNI data set we obtain a classification accuracy, sensitivity and specificity of 99% while in the OASIS data set a classification accuracy and sensitivity of 77% and specificity of 79% when dealing with four classes.
    Conclusions: By providing a quantitative comparison on the two established data sets with many state-of-the-art techniques, we demonstrated the effectiveness of our proposed approach in classifying the Alzheimer's disease from MRI patient brain scans.
    MeSH term(s) Aged ; Aged, 80 and over ; Algorithms ; Alzheimer Disease/classification ; Alzheimer Disease/diagnostic imaging ; Brain/diagnostic imaging ; Disease Progression ; Female ; Humans ; Image Interpretation, Computer-Assisted/methods ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/methods ; Male ; Middle Aged ; Models, Statistical ; Pattern Recognition, Automated ; Predictive Value of Tests ; Reproducibility of Results ; Sensitivity and Specificity ; Software ; Support Vector Machine
    Language English
    Publishing date 2017-05
    Publishing country Ireland
    Document type Journal Article
    ZDB-ID 632564-6
    ISSN 1872-7565 ; 0169-2607
    ISSN (online) 1872-7565
    ISSN 0169-2607
    DOI 10.1016/j.cmpb.2017.03.006
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: IOeRT conventional and FLASH treatment planning system implementation exploiting fast GPU Monte Carlo: The case of breast cancer.

    Franciosini, G / Carlotti, D / Cattani, F / De Gregorio, A / De Liso, V / De Rosa, F / Di Francesco, M / Di Martino, F / Felici, G / Pensavalle, J Harold / Leonardi, M C / Marafini, M / Muscato, A / Paiar, F / Patera, V / Poortmans, P / Sciubba, A / Schiavi, A / Toppi, M /
    Traini, G / Trigilio, A / Sarti, A

    Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

    2024  Volume 121, Page(s) 103346

    Abstract: Partial breast irradiation for the treatment of early-stage breast cancer patients can be performed by means of Intra Operative electron Radiation Therapy (IOeRT). One of the main limitations of this technique is the absence of a treatment planning ... ...

    Abstract Partial breast irradiation for the treatment of early-stage breast cancer patients can be performed by means of Intra Operative electron Radiation Therapy (IOeRT). One of the main limitations of this technique is the absence of a treatment planning system (TPS) that could greatly help in ensuring a proper coverage of the target volume during irradiation. An IOeRT TPS has been developed using a fast Monte Carlo (MC) and an ultrasound imaging system to provide the best irradiation strategy (electron beam energy, applicator position and bevel angle) and to facilitate the optimisation of dose prescription and delivery to the target volume while maximising the organs at risk sparing. The study has been performed in silico, exploiting MC simulations of a breast cancer treatment. Ultrasound-based input has been used to compute the absorbed dose maps in different irradiation strategies and a quantitative comparison between the different options was carried out using Dose Volume Histograms. The system was capable of exploring different beam energies and applicator positions in few minutes, identifying the best strategy with an overall computation time that was found to be completely compatible with clinical implementation. The systematic uncertainty related to tissue deformation during treatment delivery with respect to imaging acquisition was taken into account. The potential and feasibility of a GPU based full MC TPS implementation of IOeRT breast cancer treatments has been demonstrated in-silico. This long awaited tool will greatly improve the treatment safety and efficacy, overcoming the limits identified within the clinical trials carried out so far.
    Language English
    Publishing date 2024-04-11
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 1122650-x
    ISSN 1724-191X ; 1120-1797
    ISSN (online) 1724-191X
    ISSN 1120-1797
    DOI 10.1016/j.ejmp.2024.103346
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Complications of extraperitoneal robot-assisted radical prostatectomy in high-risk prostate cancer: A single high-volume center experience.

    Paladini, Alessio / Cochetti, Giovanni / Felici, Graziano / Russo, Miriam / Saqer, Eleonora / Cari, Luigi / Bordini, Stefano / Mearini, Ettore

    Frontiers in surgery

    2023  Volume 10, Page(s) 1157528

    Abstract: Introduction: The role of robot-assisted radical prostatectomy (RARP) in high-risk prostate cancer (PCa) has been debated over the years, but it appears safe and effective in selected patients. While the outcomes of transperitoneal RARP for high-risk ... ...

    Abstract Introduction: The role of robot-assisted radical prostatectomy (RARP) in high-risk prostate cancer (PCa) has been debated over the years, but it appears safe and effective in selected patients. While the outcomes of transperitoneal RARP for high-risk PCa have been already widely investigated, data on the extraperitoneal approach are scarcely available. The primary aim of this study is to evaluate intra- and postoperative complications in a series of patients with high-risk PCa treated by extraperitoneal RARP (eRARP) and pelvic lymph node dissection. The secondary aim is to report oncological and functional outcomes.
    Methods: Data of patients who underwent eRARP for high-risk PCa were prospectively collected from January 2013 to September 2021. Intraoperative and postoperative complications were recorded, as also perioperative, functional, and oncological outcomes. Intraoperative and postoperative complications were classified by employing Intraoperative Adverse Incident Classification by the European Association of Urology and the Clavien-Dindo classification, respectively. Univariate and multivariate analyses were performed to evaluate a potential association between clinical and pathological features and the risk of complications.
    Results: A total of 108 patients were included. The mean operative time and estimated blood loss were 183.5 ± 44 min and 115.2 ± 72.4 mL, respectively. Only two intraoperative complications were recorded, both grade 3. Early complications were recorded in 15 patients, of which 14 were of minor grade, and 1 was grade IIIa. Late complications were diagnosed in four patients, all of grade III. Body mass index (BMI) > 30 kg/m
    Conclusions: eRARP with pelvic lymph node dissection in patients with high-risk PCa is a feasible and safe technique, resulting in only a few intra- and postoperative complications, mostly of low grade.
    Language English
    Publishing date 2023-03-30
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2773823-1
    ISSN 2296-875X
    ISSN 2296-875X
    DOI 10.3389/fsurg.2023.1157528
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: A pilot study of occupational exposure to ultrafine particles during 3D printing in research laboratories.

    Felici, Giorgio / Lachowicz, Joanna Izabela / Milia, Simone / Cannizzaro, Emanuele / Cirrincione, Luigi / Congiu, Terenzio / Jaremko, Mariusz / Campagna, Marcello / Lecca, Luigi Isaia

    Frontiers in public health

    2023  Volume 11, Page(s) 1144475

    Abstract: Introduction: 3D printing is increasingly present in research environments, and could pose health risks to users due to air pollution and particulate emissions. We evaluated the nanoparticulate emissions of two different 3D printers, utilizing either ... ...

    Abstract Introduction: 3D printing is increasingly present in research environments, and could pose health risks to users due to air pollution and particulate emissions. We evaluated the nanoparticulate emissions of two different 3D printers, utilizing either fused filament fabrication with polylactic acid, or stereolithography (SLA) with light curing resin.
    Methods: Nanoparticulate emissions were evaluated in two different research environments, both by environmental measurements in the laboratory and by personal sampling.
    Results: The SLA printer had higher nanoparticulate emissions, with an average concentration of 4,091 parts/cm
    Discussion: Our study implies that when considering the health risks of particulate emissions from 3D printing in research laboratories, attention should be given to the materials used and the type of 3D printer.
    MeSH term(s) Particulate Matter ; Pilot Projects ; Laboratories ; Air Pollution, Indoor ; Printing, Three-Dimensional ; Occupational Exposure
    Chemical Substances Particulate Matter
    Language English
    Publishing date 2023-06-02
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2711781-9
    ISSN 2296-2565 ; 2296-2565
    ISSN (online) 2296-2565
    ISSN 2296-2565
    DOI 10.3389/fpubh.2023.1144475
    Database MEDical Literature Analysis and Retrieval System OnLINE

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