Search

Your search keyword '"Angarano, A"' showing total 2,235 results
Start Over Author "Angarano, A"
2,235 results on '"Angarano, A"'

2. GPS-free Autonomous Navigation in Cluttered Tree Rows with Deep Semantic Segmentation

Author

Navone, Alessandro, Martini, Mauro, Ambrosio, Marco, Ostuni, Andrea, Angarano, Simone, and Chiaberge, Marcello

Subjects
Computer Science - Robotics
Abstract

Segmentation-based autonomous navigation has recently been presented as an appealing approach to guiding robotic platforms through crop rows without requiring perfect GPS localization. Nevertheless, current techniques are restricted to situations where the distinct separation between the plants and the sky allows for the identification of the row's center. However, tall, dense vegetation, such as high tree rows and orchards, is the primary cause of GPS signal blockage. In this study, we increase the overall robustness and adaptability of the control algorithm by extending the segmentation-based robotic guiding to those cases where canopies and branches occlude the sky and prevent the utilization of GPS and earlier approaches. An efficient Deep Neural Network architecture has been used to address semantic segmentation, performing the training with synthetic data only. Numerous vineyards and tree fields have undergone extensive testing in both simulation and real-world to show the solution's competitive benefits., Comment: arXiv admin note: text overlap with arXiv:2304.08988

Published
2024

3. Lavender Autonomous Navigation with Semantic Segmentation at the Edge

Author

Navone, Alessandro, Romanelli, Fabrizio, Ambrosio, Marco, Martini, Mauro, Angarano, Simone, and Chiaberge, Marcello

Subjects
Computer Science - Robotics
Abstract

Achieving success in agricultural activities heavily relies on precise navigation in row crop fields. Recently, segmentation-based navigation has emerged as a reliable technique when GPS-based localization is unavailable or higher accuracy is needed due to vegetation or unfavorable weather conditions. It also comes in handy when plants are growing rapidly and require an online adaptation of the navigation algorithm. This work applies a segmentation-based visual agnostic navigation algorithm to lavender fields, considering both simulation and real-world scenarios. The effectiveness of this approach is validated through a wide set of experimental tests, which show the capability of the proposed solution to generalize over different scenarios and provide highly-reliable results.

Published
2023

4. Autonomous Navigation in Rows of Trees and High Crops with Deep Semantic Segmentation

Author

Navone, Alessandro, Martini, Mauro, Ostuni, Andrea, Angarano, Simone, and Chiaberge, Marcello

Subjects
Computer Science - Robotics
Abstract

Segmentation-based autonomous navigation has recently been proposed as a promising methodology to guide robotic platforms through crop rows without requiring precise GPS localization. However, existing methods are limited to scenarios where the centre of the row can be identified thanks to the sharp distinction between the plants and the sky. However, GPS signal obstruction mainly occurs in the case of tall, dense vegetation, such as high tree rows and orchards. In this work, we extend the segmentation-based robotic guidance to those scenarios where canopies and branches occlude the sky and hinder the usage of GPS and previous methods, increasing the overall robustness and adaptability of the control algorithm. Extensive experimentation on several realistic simulated tree fields and vineyards demonstrates the competitive advantages of the proposed solution.

Published
2023
Full Text
View/download PDF

5. Domain Generalization for Crop Segmentation with Standardized Ensemble Knowledge Distillation

Author

Angarano, Simone, Martini, Mauro, Navone, Alessandro, and Chiaberge, Marcello

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

In recent years, precision agriculture has gradually oriented farming closer to automation processes to support all the activities related to field management. Service robotics plays a predominant role in this evolution by deploying autonomous agents that can navigate fields while performing tasks such as monitoring, spraying, and harvesting without human intervention. To execute these precise actions, mobile robots need a real-time perception system that understands their surroundings and identifies their targets in the wild. Existing methods, however, often fall short in generalizing to new crops and environmental conditions. This limit is critical for practical applications where labeled samples are rarely available. In this paper, we investigate the problem of crop segmentation and propose a novel approach to enhance domain generalization using knowledge distillation. In the proposed framework, we transfer knowledge from a standardized ensemble of models individually trained on source domains to a student model that can adapt to unseen realistic scenarios. To support the proposed method, we present a synthetic multi-domain dataset for crop segmentation containing plants of variegate species and covering different terrain styles, weather conditions, and light scenarios for more than 70,000 samples. We demonstrate significant improvements in performance over state-of-the-art methods and superior sim-to-real generalization. Our approach provides a promising solution for domain generalization in crop segmentation and has the potential to enhance a wide variety of agriculture applications.

Published
2023

6. Online Learning of Wheel Odometry Correction for Mobile Robots with Attention-based Neural Network

Author

Navone, Alessandro, Martini, Mauro, Angarano, Simone, and Chiaberge, Marcello

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Modern robotic platforms need a reliable localization system to operate daily beside humans. Simple pose estimation algorithms based on filtered wheel and inertial odometry often fail in the presence of abrupt kinematic changes and wheel slips. Moreover, despite the recent success of visual odometry, service and assistive robotic tasks often present challenging environmental conditions where visual-based solutions fail due to poor lighting or repetitive feature patterns. In this work, we propose an innovative online learning approach for wheel odometry correction, paving the way for a robust multi-source localization system. An efficient attention-based neural network architecture has been studied to combine precise performances with real-time inference. The proposed solution shows remarkable results compared to a standard neural network and filter-based odometry correction algorithms. Nonetheless, the online learning paradigm avoids the time-consuming data collection procedure and can be adopted on a generic robotic platform on-the-fly.

Published
2023
Full Text
View/download PDF

7. Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System

Author

Marchionna, Luca, Pugliese, Giulio, Martini, Mauro, Angarano, Simone, Salvetti, Francesco, and Chiaberge, Marcello

Subjects
Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Systems and Control
Abstract

The game of Jenga represents an inspiring benchmark for developing innovative manipulation solutions for complex tasks. Indeed, it encouraged the study of novel robotics methods to successfully extract blocks from the tower. A Jenga game round undoubtedly embeds many traits of complex industrial or surgical manipulation tasks, requiring a multi-step strategy, the combination of visual and tactile data, and the highly precise motion of the robotic arm to perform a single block extraction. In this work, we propose a novel, cost-effective architecture for playing Jenga with e.Do, a 6-DOF anthropomorphic manipulator manufactured by Comau, a standard depth camera, and an inexpensive monodirectional force sensor. Our solution focuses on a visual-based control strategy to accurately align the end-effector with the desired block, enabling block extraction by pushing. To this aim, we train an instance segmentation deep learning model on a synthetic custom dataset to segment each piece of the Jenga tower, allowing visual tracking of the desired block's pose during the motion of the manipulator. We integrate the visual-based strategy with a 1D force sensor to detect whether the block can be safely removed by identifying a force threshold value. Our experimentation shows that our low-cost solution allows e.DO to precisely reach removable blocks and perform up to 14 consecutive extractions in a row.

Published
2022
Full Text
View/download PDF

10. Ultra-low-power Range Error Mitigation for Ultra-wideband Precise Localization

Author

Angarano, Simone, Salvetti, Francesco, Mazzia, Vittorio, Fantin, Giovanni, Gandini, Dario, and Chiaberge, Marcello

Subjects
Computer Science - Machine Learning, Computer Science - Robotics
Abstract

Precise and accurate localization in outdoor and indoor environments is a challenging problem that currently constitutes a significant limitation for several practical applications. Ultra-wideband (UWB) localization technology represents a valuable low-cost solution to the problem. However, non-line-of-sight (NLOS) conditions and complexity of the specific radio environment can easily introduce a positive bias in the ranging measurement, resulting in highly inaccurate and unsatisfactory position estimation. In the light of this, we leverage the latest advancement in deep neural network optimization techniques and their implementation on ultra-low-power microcontrollers to introduce an effective range error mitigation solution that provides corrections in either NLOS or LOS conditions with a few mW of power. Our extensive experimentation endorses the advantages and improvements of our low-cost and power-efficient methodology.

Published
2022

11. Generative Adversarial Super-Resolution at the Edge with Knowledge Distillation

Author

Angarano, Simone, Salvetti, Francesco, Martini, Mauro, and Chiaberge, Marcello

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Robotics
Abstract

Single-Image Super-Resolution can support robotic tasks in environments where a reliable visual stream is required to monitor the mission, handle teleoperation or study relevant visual details. In this work, we propose an efficient Generative Adversarial Network model for real-time Super-Resolution, called EdgeSRGAN (code available at https://github.com/PIC4SeR/EdgeSRGAN). We adopt a tailored architecture of the original SRGAN and model quantization to boost the execution on CPU and Edge TPU devices, achieving up to 200 fps inference. We further optimize our model by distilling its knowledge to a smaller version of the network and obtain remarkable improvements compared to the standard training approach. Our experiments show that our fast and lightweight model preserves considerably satisfying image quality compared to heavier state-of-the-art models. Finally, we conduct experiments on image transmission with bandwidth degradation to highlight the advantages of the proposed system for mobile robotic applications.

Published
2022

12. Back-to-Bones: Rediscovering the Role of Backbones in Domain Generalization

Author

Angarano, Simone, Martini, Mauro, Salvetti, Francesco, Mazzia, Vittorio, and Chiaberge, Marcello

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Domain Generalization (DG) studies the capability of a deep learning model to generalize to out-of-training distributions. In the last decade, literature has been massively filled with training methodologies that claim to obtain more abstract and robust data representations to tackle domain shifts. Recent research has provided a reproducible benchmark for DG, pointing out the effectiveness of naive empirical risk minimization (ERM) over existing algorithms. Nevertheless, researchers persist in using the same outdated feature extractors, and no attention has been given to the effects of different backbones yet. In this paper, we start back to the backbones proposing a comprehensive analysis of their intrinsic generalization capabilities, which so far have been ignored by the research community. We evaluate a wide variety of feature extractors, from standard residual solutions to transformer-based architectures, finding an evident linear correlation between large-scale single-domain classification accuracy and DG capability. Our extensive experimentation shows that by adopting competitive backbones in conjunction with effective data augmentation, plain ERM outperforms recent DG solutions and achieves state-of-the-art accuracy. Moreover, our additional qualitative studies reveal that novel backbones give more similar representations to same-class samples, separating different domains in the feature space. This boost in generalization capabilities leaves marginal room for DG algorithms. It suggests a new paradigm for investigating the problem, placing backbones in the spotlight and encouraging the development of consistent algorithms on top of them. The code is available at https://github.com/PIC4SeR/Back-to-Bones.

Published
2022

13. Position-Agnostic Autonomous Navigation in Vineyards with Deep Reinforcement Learning

Author

Martini, Mauro, Cerrato, Simone, Salvetti, Francesco, Angarano, Simone, and Chiaberge, Marcello

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Precision agriculture is rapidly attracting research to efficiently introduce automation and robotics solutions to support agricultural activities. Robotic navigation in vineyards and orchards offers competitive advantages in autonomously monitoring and easily accessing crops for harvesting, spraying and performing time-consuming necessary tasks. Nowadays, autonomous navigation algorithms exploit expensive sensors which also require heavy computational cost for data processing. Nonetheless, vineyard rows represent a challenging outdoor scenario where GPS and Visual Odometry techniques often struggle to provide reliable positioning information. In this work, we combine Edge AI with Deep Reinforcement Learning to propose a cutting-edge lightweight solution to tackle the problem of autonomous vineyard navigation without exploiting precise localization data and overcoming task-tailored algorithms with a flexible learning-based approach. We train an end-to-end sensorimotor agent which directly maps noisy depth images and position-agnostic robot state information to velocity commands and guides the robot to the end of a row, continuously adjusting its heading for a collision-free central trajectory. Our extensive experimentation in realistic simulated vineyards demonstrates the effectiveness of our solution and the generalization capabilities of our agent.

Published
2022
Full Text
View/download PDF

14. Waypoint Generation in Row-based Crops with Deep Learning and Contrastive Clustering

Author

Salvetti, Francesco, Angarano, Simone, Martini, Mauro, Cerrato, Simone, and Chiaberge, Marcello

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

The development of precision agriculture has gradually introduced automation in the agricultural process to support and rationalize all the activities related to field management. In particular, service robotics plays a predominant role in this evolution by deploying autonomous agents able to navigate in fields while executing different tasks without the need for human intervention, such as monitoring, spraying and harvesting. In this context, global path planning is the first necessary step for every robotic mission and ensures that the navigation is performed efficiently and with complete field coverage. In this paper, we propose a learning-based approach to tackle waypoint generation for planning a navigation path for row-based crops, starting from a top-view map of the region-of-interest. We present a novel methodology for waypoint clustering based on a contrastive loss, able to project the points to a separable latent space. The proposed deep neural network can simultaneously predict the waypoint position and cluster assignment with two specialized heads in a single forward pass. The extensive experimentation on simulated and real-world images demonstrates that the proposed approach effectively solves the waypoint generation problem for both straight and curved row-based crops, overcoming the limitations of previous state-of-the-art methodologies., Comment: Accepted at ECML PKDD 2022

Published
2022
Full Text
View/download PDF

17. A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops

Author

Cerrato, Simone, Mazzia, Vittorio, Salvetti, Francesco, Martini, Mauro, Angarano, Simone, Navone, Alessandro, and Chiaberge, Marcello

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Expensive sensors and inefficient algorithmic pipelines significantly affect the overall cost of autonomous machines. However, affordable robotic solutions are essential to practical usage, and their financial impact constitutes a fundamental requirement to employ service robotics in most fields of application. Among all, researchers in the precision agriculture domain strive to devise robust and cost-effective autonomous platforms in order to provide genuinely large-scale competitive solutions. In this article, we present a complete algorithmic pipeline for row-based crops autonomous navigation, specifically designed to cope with low-range sensors and seasonal variations. Firstly, we build on a robust data-driven methodology to generate a viable path for the autonomous machine, covering the full extension of the crop with only the occupancy grid map information of the field. Moreover, our solution leverages on latest advancement of deep learning optimization techniques and synthetic generation of data to provide an affordable solution that efficiently tackles the well-known Global Navigation Satellite System unreliability and degradation due to vegetation growing inside rows. Extensive experimentation and simulations against computer-generated environments and real-world crops demonstrated the robustness and intrinsic generalizability of our methodology that opens the possibility of highly affordable and fully autonomous machines., Comment: Submitted to Robotics and Autonomous Systems (Elsevier)

Published
2021

18. Diagnosis and management of acquired aplastic anemia in childhood. Guidelines from the Marrow Failure Study Group of the Pediatric Haemato-Oncology Italian Association (AIEOP)

Author

Guarina, A., Farruggia, P., Mariani, E., Saracco, P., Barone, A., Onofrillo, D., Cesaro, S., Angarano, R., Barberi, W., Bonanomi, S., Corti, P., Crescenzi, B., Dell'Orso, G., De Matteo, A., Giagnuolo, G., Iori, A.P., Ladogana, S., Lucarelli, A., Lupia, M., Martire, B., Mastrodicasa, E., Massaccesi, E., Arcuri, L., Giarratana, M.C., Menna, G., Miano, M., Notarangelo, L.D., Palazzi, G., Palmisani, E., Pestarino, S., Pierri, F., Pillon, M., Ramenghi, U., Russo, G., Saettini, F., Timeus, F., Verzegnassi, F., Zecca, M., Fioredda, F., and Dufour, C.

Published
2024
Full Text
View/download PDF

19. Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition

Author

Mazzia, Vittorio, Angarano, Simone, Salvetti, Francesco, Angelini, Federico, and Chiaberge, Marcello

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Deep neural networks based purely on attention have been successful across several domains, relying on minimal architectural priors from the designer. In Human Action Recognition (HAR), attention mechanisms have been primarily adopted on top of standard convolutional or recurrent layers, improving the overall generalization capability. In this work, we introduce Action Transformer (AcT), a simple, fully self-attentional architecture that consistently outperforms more elaborated networks that mix convolutional, recurrent and attentive layers. In order to limit computational and energy requests, building on previous human action recognition research, the proposed approach exploits 2D pose representations over small temporal windows, providing a low latency solution for accurate and effective real-time performance. Moreover, we open-source MPOSE2021, a new large-scale dataset, as an attempt to build a formal training and evaluation benchmark for real-time, short-time HAR. The proposed methodology was extensively tested on MPOSE2021 and compared to several state-of-the-art architectures, proving the effectiveness of the AcT model and laying the foundations for future work on HAR., Comment: Published by Pattern Recognition, Elsevier

Published
2021
Full Text
View/download PDF

20. Robust Ultra-wideband Range Error Mitigation with Deep Learning at the Edge

Author

Angarano, Simone, Mazzia, Vittorio, Salvetti, Francesco, Fantin, Giovanni, and Chiaberge, Marcello

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Robotics, Electrical Engineering and Systems Science - Signal Processing
Abstract

Ultra-wideband (UWB) is the state-of-the-art and most popular technology for wireless localization. Nevertheless, precise ranging and localization in non-line-of-sight (NLoS) conditions is still an open research topic. Indeed, multipath effects, reflections, refractions, and complexity of the indoor radio environment can easily introduce a positive bias in the ranging measurement, resulting in highly inaccurate and unsatisfactory position estimation. This article proposes an efficient representation learning methodology that exploits the latest advancement in deep learning and graph optimization techniques to achieve effective ranging error mitigation at the edge. Channel Impulse Response (CIR) signals are directly exploited to extract high semantic features to estimate corrections in either NLoS or LoS conditions. Extensive experimentation with different settings and configurations has proved the effectiveness of our methodology and demonstrated the feasibility of a robust and low computational power UWB range error mitigation., Comment: Submitted to Engineering Applications of Artificial Intelligence

Published
2020
Full Text
View/download PDF

22. Knowledge, attitudes, and practices about HIV and other sexually transmitted infections among High School students in Southern Italy: A cross-sectional survey.

Author

Francesco Di Gennaro, Francesco Vladimiro Segala, Giacomo Guido, Mariacristina Poliseno, Laura De Santis, Alessandra Belati, Carmen Rita Santoro, Irene Francesca Bottalico, Carmen Pellegrino, Roberta Novara, Luisa Frallonardo, Mariangela Cormio, Michele Camporeale, Sergio Cotugno, Vincenzo Giliberti, Stefano Di Gregorio, Valentina Totaro, Nicola Catucci, Anna De Giosa, Roberta Giusto, Ilaria Viviana Lanera, Gioacchino Angarano, Sergio Lo Caputo, and Annalisa Saracino

Subjects
Medicine, Science
Abstract

High School students, recognized as a high-risk group for sexually transmitted infections (STIs), were the focal point of an educational campaign in Southern Italy to share information and good practices about STIs and HIV/AIDS. A baseline survey comprising 76 items was conducted via the REDCap platform to assess students' initial knowledge, attitudes, and practices (KAP) related to STIs and HIV/AIDS. Sociodemographic variables were also investigated. The association between variables and KAP score was assessed by Kruskal-Wallis' or Spearman's test, as appropriate. An ordinal regression model was built to estimate the effect size, reported as odds ratio (OR) with a 95% confidence interval (CI), for achieving higher KAP scores among students features. On a scale of 0 to 29, 1702 participants achieved a median KAP score of 14 points. Higher scores were predominantly reported by students from classical High Schools (OR 3.19, 95% C.I. 1.60-6.33, p

Published
2024
Full Text
View/download PDF

28. Parietal intrahemispheric source connectivity of resting-state electroencephalographic alpha rhythms is abnormal in Naïve HIV patients

Author

Claudio Babiloni, Claudio Del Percio, Roberta Lizio, Susanna Lopez, Alfredo Pennica, Paolo Roma, Valentina Correr, Federica Cucciolla, Ginevra Toma, Andrea Soricelli, Francesco Di Campli, Antonio Aceti, Elisabetta Teti, Loredana Sarmati, Gloria Crocetti, Raffaele Ferri, Ivan Lorenzo, Massimo Galli, Cristina Negri, Gioacchino Angarano, Annalisa Saracino, Luciana Lepore, Massimo Di Pietro, Francesco Maria Fusco, Vincenzo Vullo, Gabriella D’Ettorre, Pasquale Pagliano, Giusy Di Flumeri, Benedetto Maurizio Celesia, Elio Gentilini Cacciola, Giovanni Di Perri, Andrea Calcagno, Fabrizio Stocchi, Stefano Ferracuti, Paolo Onorati, Massimo Andreoni, and Giuseppe Noce

Subjects
Human immunodeficiency virus (HIV), Functional brain connectivity, Resting-state EEG rhythms, Exact Low-resolution brain electromagnetic source tomography (eLORETA), Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Previous evidence showed abnormal parietal sources of resting-state electroencephalographic (EEG) delta (< 4 Hz) and alpha (8–12 Hz) rhythms in treatment-Naïve HIV (Naïve HIV) subjects, as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis that these local abnormalities may be related to functional cortical dysconnectivity as an oscillatory brain network disorder.The present EEG database regarded 128 Naïve HIV and 60 Healthy subjects. The eLORETA freeware estimated lagged linear EEG source connectivity (LLC). The area under receiver operating characteristic (AUROC) curve indexed the accuracy in the classification between Healthy and HIV individuals.Parietal intrahemispheric LLC solutions in alpha sources were abnormally lower in the Naïve HIV than in the control group. Furthermore, those abnormalities were greater in the Naïve HIV subgroup with executive and visuospatial deficits than the Naïve HIV subgroup with normal cognition. AUROC curves of those LLC solutions exhibited moderate/good accuracies (0.75–0.88) in the discrimination between the Naïve HIV individuals with executive and visuospatial deficits vs. Naïve HIV individuals with normal cognition and control individuals.In quiet wakefulness, Naïve HIV subjects showed clinically relevant abnormalities in parietal alpha source connectivity. HIV may alter a parietal “hub” oscillating at the alpha frequency in quiet wakefulness as a brain network disorder.

Published
2022
Full Text
View/download PDF

34. Clinical features and comorbidity pattern of HCV infected migrants compared to native patients in care in Italy: A real-life evaluation of the PITER cohort

Author

Mazzaro, Cesare, Bertola, Manuela, Schioppa, Ornella, Benedetti, Antonio, Schiadà, Laura, Cucco, Monica, Giacometti, Andrea, Brescini, Laura, Castelletti, Sefora, Fiorentini, Alessandro, Angarano, Gioacchino, Milella, Michele, Di Leo, Alfredo, Rendina, Maria, D'abramo, Fulvio Salvatore, Lillo, Chiara, Iannone, Andrea, Piazzolla, Mariano, Verucchi, Gabriella, Badia, Lorenzo, Piscaglia, Fabio, Benevento, Francesca, Serio, Ilaria, Castelli, Francesco, Zaltron, Serena, Spinetti, Angiola, Odolini, Silvia, Bruno, Raffaele, Mondelli, Mario, Chessa, Luchino, Loi, Martina, Torti, Carlo, Costa, Chiara, Mazzitelli, Maria, Pisani, Vincenzo, Scaglione, Vincenzo, Trecarichi, Enrico Maria, Zignego, Anna Linda, Monti, Monica, Madia, Francesco, Blanc, Pier Luigi, Attala, Letizia, Pierotti, Piera, Salomoni, Elena, Mariabelli, Elisa, Santantonio, Teresa Antonia, Bruno, Serena Rita, Cela, Ester Marina, Bassetti, Matteo, Mazzarello, Giovanni, Alessandrini, Anna Ida, Di Biagio, Antonio, Nicolini, Laura Ambra, Raimondo, Giovanni, Filomia, Roberto, Aghemo, Alessio, Meli, Rossella, Lazzarin, Adriano, Morsica, Giulia, Salpietro, Stefania, Galli, Massimo, Fracanzani, Anna Ludovica, Fatta, Erika, Lombardi, Rosa, Lampertico, Pietro, Borghi, Marta, D'ambrosio, Roberta, Degasperi, Elisabetta, Puoti, Massimo, Baiguera, Chiara, D'amico, Federico, Vinci, Maria, Rumi, Maria Grazia, Zuin, Massimo, Giorgini, Alessia, Zermiani, Paola, Andreone, Pietro, Caraceni, Paolo, Margotti, Marzia, Guarneri, Valeria, Villa, Erica, Bernabucci, Veronica, Bristot, Laura, Paradiso, Maria Luisa, Migliorino, Guglielmo, Beretta, Ilaria, Gambaro, Alessandra, Lapadula, Giuseppe, Spolti, Anna, Soria, Alessandro, Invernizzi, Pietro, Ciaccio, Antonio, LucÀ, Martina, Malinverno, Federica, Ratti, Laura, Coppola, Carmine, Amoruso, Daniela Caterina, Pisano, Federica, Scarano, Ferdinando, Staiano, Laura, Morisco, Filomena, Cossiga, Valentina, Gentile, Ivan, Buonomo, Antonio Riccardo, Foggia, Maria, Zappulo, Emanuela, Federico, Alessandro, Dallio, Marcello, Coppola, Nicola, Sagnelli, Caterina, Martini, Salvatore, Monari, Caterina, Nardone, Gerardo, Sgamato, Costantino, Chemello, Liliana, Cavalletto, Luisa, Sterrantino, Daniela, Russo, Francesco Paolo, Zanetto, Alberto, Zanaga, Paola, Barbaro, Francesco, Brancaccio, Giuseppina, Craxì, Antonio, Petta, Salvatore, Calvaruso, Vincenza, Crapanzano, Luciano, Madonia, Salvatore, Cannizzaro, Marco, Bruno, Erica Maria, Licata, Anna, Amodeo, Simona, Capitano, Adele Rosaria, Ferrari, Carlo, Laccabue, Diletta, Negri, Elisa, Orlandini, Alessandra, Pesci, Marco, Gulminetti, Roberto, Pagnucco, Layla, Parruti, Giustino, Di Stefano, Paola, Brunetto, Maurizia Rossana, Coco, Barbara, Massari, Marco, Corsini, Romina, Garlassi, Elisa, Andreoni, Massimo, Teti, Elisabetta, Cerva, Carlotta, Baiocchi, Lorenzo, Tata, Xhimi, Grassi, Giuseppe, Gasbarrini, Antonio, Pompili, Maurizio, De Siena, Martina, Taliani, Gloria, Biliotti, Elisa, Spaziante, Martina, Persico, Marcello, Masarone, Mario, Aglitti, Andrea, Calvanese, Gemma, Anselmo, Marco, De Leo, Pasqualina, Marturano, Monica, Saracco, Giorgio Maria, Ciancio, Alessia, Ieluzzi, Donatella, Quaranta, Maria Giovanna, Ferrigno, Luigina, D'Angelo, Franca, Saracino, Annalisa, and Kondili, Loeta A.

Published
2021
Full Text
View/download PDF

35. Phytosomes as Innovative Delivery Systems for Phytochemicals: A Comprehensive Review of Literature

Author

Barani M, Sangiovanni E, Angarano M, Rajizadeh MA, Mehrabani M, Piazza S, Gangadharappa HV, Pardakhty A, Mehrbani M, Dell’Agli M, and Nematollahi MH

Subjects
phytochemical, nanomedicine, phytosome, delivery, vesicle, disease, Medicine (General), R5-920
Abstract

Mahmood Barani,1 Enrico Sangiovanni,2 Marco Angarano,2 Mohammad Amin Rajizadeh,3 Mehrnaz Mehrabani,4 Stefano Piazza,2 Hosahalli Veerabhadrappa Gangadharappa,5 Abbas Pardakhty,6 Mehrzad Mehrbani,7 Mario Dell’Agli,2 Mohammad Hadi Nematollahi8 1Medical Mycology and Bacteriology Research Center, Kerman University of Medical Sciences, Kerman, 76169-13555, Iran; 2Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, 20133, Italy; 3Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran; 4Physiology Research Center, Kerman University of Medical Sciences, Kerman, Iran; 5Department of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru, India; 6Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran; 7Department of Traditional Medicine, Faculty of Traditional Medicine, Kerman University of Medical Sciences, Kerman, Iran; 8Herbal and Traditional Medicines Research Center, Kerman University of Medical Sciences, Kerman, IranCorrespondence: Mario Dell’AgliDepartment of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Via Balzaretti 9, Milan, 20133, ItalyEmail mario.dellagli@unimi.itMohammad Hadi NematollahiDepartment of Clinical Biochemistry, Kerman University of Medical Sciences, Kerman, IranEmail mh.nematollahi@yahoo.comAbstract: Nowadays, medicinal herbs and their phytochemicals have emerged as a great therapeutic option for many disorders. However, poor bioavailability and selectivity might limit their clinical application. Therefore, bioavailability is considered a notable challenge to improve bio-efficacy in transporting dietary phytochemicals. Different methods have been proposed for generating effective carrier systems to enhance the bioavailability of phytochemicals. Among them, nano-vesicles have been introduced as promising candidates for the delivery of insoluble phytochemicals. Due to the easy preparation of the bilayer vesicles and their adaptability, they have been widely used and approved by the scientific literature. The first part of the review is focused on introducing phytosome technology as well as its applications, with emphasis on principles of formulations and characterization. The second part provides a wide overview of biological activities of commercial and non-commercial phytosomes, divided by systems and related pathologies. These results confirm the greater effectiveness of phytosomes, both in terms of biological activity or reduced dosage, highlighting curcumin and silymarin as the most formulated compounds. Finally, we describe the promising clinical and experimental findings regarding the applications of phytosomes. The conclusion of this study encourages the researchers to transfer their knowledge from laboratories to market, for a further development of these products.Keywords: phytochemical, nanomedicine, phytosome, delivery, vesicle, disease

Published
2021

41. Dalbavancin Efficacy and Impact on Hospital Length-of-Stay and Treatment Costs in Different Gram-Positive Bacterial Infections

Author

Poliseno, Mariacristina, Bavaro, Davide Fiore, Brindicci, Gaetano, Luzzi, Giovanni, Carretta, Domenico Maria, Spinarelli, Antonio, Messina, Raffaella, Miolla, Maria Paola, Achille, Teresa Immacolata, Dibartolomeo, Maria Rosaria, Dell’Aera, Maria, Saracino, Annalisa, Angarano, Gioacchino, Favale, Stefano, D’Agostino, Carlo, Moretti, Biagio, Signorelli, Francesco, Taglietti, Camilla, and Carbonara, Sergio

Published
2021
Full Text
View/download PDF

47. Rituximab Unveils Hypogammaglobulinemia and Immunodeficiency in Children with Autoimmune Cytopenia

Author

Ottaviano, Giorgio, Marinoni, Maddalena, Graziani, Simona, Sibson, Keith, Barzaghi, Federica, Bertolini, Patrizia, Chini, Loredana, Corti, Paola, Cancrini, Caterina, D'Alba, Irene, Gabelli, Maria, Gallo, Vera, Giancotta, Carmela, Giordano, Paola, Lassandro, Giuseppe, Martire, Baldassare, Angarano, Rosa, Mastrodicasa, Elena, Bava, Cecilia, Miano, Maurizio, Naviglio, Samuele, Verzegnassi, Federico, Saracco, Paola, Trizzino, Antonino, Biondi, Andrea, Pignata, Claudio, and Moschese, Viviana

Published
2020
Full Text
View/download PDF

48. Trends in mortality in people with HIV from 1999 to 2020: a multi-cohort collaboration

Author

Tusch, E, Ryom, L, Pelchen-Matthews, A, Mocroft, A, Elbirt, D, Oprea, C, Günthard, H, Staehelin, C, Zangerle, R, Suarez, I, Vehreschild, J, Wit, F, Menozzi, M, d'Arminio Monforte, A, Spagnuolo, V, Pradier, C, Carlander, C, Suanzes, P, Wasmuth, J, Carr, A, Petoumenos, K, Borgans, F, Bonnet, F, De Wit, S, El-Sadr, W, Neesgaard, B, Jaschinski, N, Greenberg, L, Hosein, S, Gallant, J, Vannappagari, V, Young, L, Sabin, C, Lundgren, J, Peters, L, Reekie, J, Calvo, G, Dabis, F, Kirk, O, Law, M, Monforte, A, Morfeldt, L, Reiss, P, Weber, R, Lind-Thomsen, A, Brandt, R, Hillebreght, M, Zaheri, S, Scherrer, A, Schöni-Affolter, F, Rickenbach, M, Tavelli, A, Fanti, I, Leleux, O, Mourali, J, Marec, F, Boerg, E, Thulin, E, Sundström, A, Bartsch, G, Thompsen, G, Necsoi, C, Delforge, M, Fontas, E, Caissotti, C, Dollet, K, Mateu, S, Torres, F, Blance, A, Huang, R, Puhr, R, Laut, K, Kristensen, D, Phillips, A, Kamara, D, Smith, C, Hatleberg, C, Raben, D, Matthews, C, Bojesen, A, Grevsen, A, Powderly, B, Shortman, N, Moecklinghoff, C, Reilly, G, Franquet, X, Smit, C, Ross, M, Fux, C, Morlat, P, Friis-Møller, N, Kowalska, J, Bohlius, J, Bower, M, Fätkenheuer, G, Grulich, A, Sjøl, A, Meidahl, P, Iversen, J, Reiss, C, Hillebregt, M, Prins, J, Kuijpers, T, Scherpbier, H, van der Meer, J, Godfried, M, van der Poll, T, Nellen, F, Geerlings, S, van Vugt, M, Pajkrt, D, Bos, J, Wiersinga, W, van der Valk, M, Goorhuis, A, Hovius, J, van Eden, J, Henderiks, A, van Hes, A, Mutschelknauss, M, Nobel, H, Pijnappel, F, Jurriaans, S, Back, N, Zaaijer, H, Berkhout, B, Cornelissen, M, Schinkel, C, Thomas, X, Ziekenhuis, A, van den Berge, M, Stegeman, A, Baas, S, de Looff, L, Versteeg, D, Ziekenhuis, C, Pronk, M, Ammerlaan, H, De Munnik, E, Jansz, A, Tjhie, J, Wegdam, M, Deiman, B, Scharnhorst, V, van der Plas, A, Weijsenfeld, A, van der Ende, M, De Vries-Sluijs, T, van Gorp, E, Schurink, C, Nouwen, J, Verbon, A, Rijnders, B, Bax, H, van der Feltz, M, Bassant, N, van Beek, J, Vriesde, M, van Zonneveld, L, de Oude-Lubbers, A, van den Berg-Cameron, H, Bruinsma-Broekman, F, de Groot, J, de Man, M, Boucher, C, Koopmans, M, van Kampen, J, Pas, S, Mc–sophia, E, Driessen, G, van Rossum, A, van der Knaap, L, Visser, E, Branger, J, Rijkeboer-Mes, A, de Ven, C, Ziekenhuis, H, Schippers, E, van Nieuwkoop, C, van IJperen, J, Geilings, J, van der Hut, G, Franck, P, van Eeden, A, Brokking, W, Groot, M, Elsenburg, L, Damen, M, Kwa, I, Groeneveld, P, Bouwhuis, J, van den Berg, J, van Hulzen, A, van der Bliek, G, Bor, P, Bloembergen, P, Wolfhagen, M, Ruijs, G, Kroon, F, de Boer, M, Bauer, M, Jolink, H, Vollaard, A, Dorama, W, van Holten, N, Claas, E, Wessels, E, den Hollander, J, Pogany, K, Roukens, A, Kastelijns, M, Smit, J, Smit, E, Struik-Kalkman, D, Tearno, C, Bezemer, M, van Niekerk, T, Pontesilli, O, Lowe, S, Lashof, A, Posthouwer, D, Ackens, R, Schippers, J, Vergoossen, R, Weijenberg-Maes, B, van Loo, I, Havenith, T, Leyten, E, Gelinck, L, van Hartingsveld, A, Meerkerk, C, Wildenbeest, G, Mutsaers, J, Jansen, C, Mulder, J, Vrouenraets, S, Lauw, F, van Broekhuizen, M, Paap, H, Vlasblom, D, Smits, P, Zuiderzee, M, Weijer, S, El Moussaoui, R, Bosma, A, van Vonderen, M, van Houte, D, Kampschreur, L, Dijkstra, K, Faber, S, Weel, J, Kootstra, G, Delsing, C, van der Burg-van de Plas, M, Heins, H, Lucas, E, Kortmann, W, van Twillert, G, Stuart, J, Diederen, B, Pronk, D, van Truijen-Oud, F, van der Reijden, W, Jansen, R, Brinkman, K, van den Berk, G, Blok, W, Frissen, P, Lettinga, K, Schouten, W, Veenstra, J, Brouwer, C, Geerders, G, Hoeksema, K, Kleene, M, van der Meché, I, Spelbrink, M, Sulman, H, Toonen, A, Wijnands, S, Kwa, D, Witte, E, Koopmans, P, Keuter, M, van der Ven, A, ter Hofstede, H, Dofferhoff, A, van Crevel, R, Albers, M, Bosch, M, Grintjes-Huisman, K, Zomer, B, Stelma, F, Rahamat-Langendoen, J, Burger, D, Richter, C, Gisolf, E, Hassing, R, ter Beest, G, van Bentum, P, Langebeek, N, Tiemessen, R, Swanink, C, van Lelyveld, S, Soetekouw, R, Hulshoff, N, van der Prijt, L, van der Swaluw, J, Bermon, N, Herpers, B, Veenendaal, D, Verhagen, D, van Wijk, M, Ziekenhuis, S, van Kasteren, M, Brouwer, A, de Wiel, B, Kuipers, M, Santegoets, R, van der Ven, B, Marcelis, J, Buiting, A, Kabel, P, Bierman, W, Scholvinck, H, Wilting, K, Stienstra, Y, Jonge, H, van der Meulen, P, de Weerd, D, Ludwig-Roukema, J, Niesters, H, Riezebos-Brilman, A, van Leer-Buter, C, Knoester, M, Hoepelman, A, Mudrikova, T, Ellerbroek, P, Oosterheert, J, Arends, J, Barth, R, Wassenberg, M, Schadd, E, van Elst-Laurijssen, D, van Oers-Hazelzet, E, Vervoort, S, van Berkel, M, Schuurman, R, Verduyn-Lunel, F, Wensing, A, Peters, E, van Agtmael, M, Bomers, M, de Vocht, J, Heitmuller, M, Laan, L, Pettersson, A, Vandenbroucke-Grauls, C, Ang, C, Kinderziekenhuis, W, Geelen, S, Wolfs, T, Bont, L, Nauta, N, Bezemer, D, van Sighem, A, Boender, T, de Jong, A, Bergsma, D, Hoekstra, P, de Lang, A, Grivell, S, Jansen, A, Rademaker, M, Raethke, M, Meijering, R, Schnörr, S, de Groot, L, van den Akker, M, Bakker, Y, Claessen, E, El Berkaoui, A, Koops, J, Kruijne, E, Lodewijk, C, Munjishvili, L, Peeck, B, Ree, C, Regtop, R, Ruijs, Y, Rutkens, T, van de Sande, L, Schoorl, M, Timmerman, A, Tuijn, E, Veenenberg, L, van der Vliet, S, Wisse, A, Woudstra, T, Tuk, B, Dupon, M, Gaborieau, V, Lacoste, D, Malvy, D, Mercié, P, Neau, D, Pellegrin, J, Tchamgoué, S, Lazaro, E, Cazanave, C, Vandenhende, M, Vareil, M, Gérard, Y, Blanco, P, Bouchet, S, Breilh, D, Fleury, H, Pellegrin, I, Chêne, G, Thiébaut, R, Wittkop, L, Lawson-Ayayi, S, Gimbert, A, Desjardin, S, Lacaze-Buzy, L, Petrov-Sanchez, V, André, K, Bernard, N, Caubet, O, Caunegre, L, Chossat, I, Courtault, C, Dauchy, F, De Witte, S, Dondia, D, Duffau, P, Dutronc, H, Farbos, S, Faure, I, Ferrand, H, Gerard, Y, Greib, C, Hessamfar, M, Imbert, Y, Lataste, P, Marie, J, Mechain, M, Monlun, E, Ochoa, A, Pistone, T, Raymond, I, Receveur, M, Rispal, P, Sorin, L, Valette, C, Viallard, J, Wille, H, Wirth, G, Lafon, M, Trimoulet, P, Bellecave, P, Tumiotto, C, Haramburu, F, Miremeont-Salamé, G, Blaizeau, M, Decoin, M, Hannapier, C, Lenaud, E, Pougetoux, A, Delveaux, S, D’Ivernois, C, Diarra, F, Uwamaliya-Nziyumvira, B, Palmer, G, Conte, V, Sapparrart, V, Law, C, Moore, R, Edwards, S, Hoy, J, Watson, K, Roth, N, Lau, H, Bloch, M, Baker, D, Cooper, D, O’Sullivan, M, Nolan, D, Guelfi, G, Calvo, C, Domingo, P, Sambeat, M, Gatell, J, Del Cacho, E, Cadafalch, J, Fuster, M, Codina, C, Sirera, G, Vaqué, A, Clumeck, N, Gennotte, A, Gerard, M, Kabeya, K, Konopnicki, D, Libois, A, Martin, C, Payen, M, Semaille, P, Van Laethem, Y, Neaton, C, Krum, E, Thompson, G, Wentworth, D, Luskin-Hawk, R, Telzak, E, Abrams, D, Cohn, D, Markowitz, N, Arduino, R, Mushatt, D, Friedland, G, Perez, G, Tedaldi, E, Fisher, E, Gordin, F, Crane, L, Sampson, J, Baxter, J, Gazzard, B, Horban, A, Karpov, I, Losso, M, Pedersen, C, Ristola, M, Rockstroh, J, Fischer, A, Larsen, J, Podlekareva, D, Cozzi-Lepri, A, Shepherd, L, Schultze, A, Amele, S, Kundro, M, Schmied, B, Wien, P, Vassilenko, A, Mitsura, V, Paduto, D, Florence, E, Vandekerckhove, L, Hadziosmanovic, V, Begovac, J, Machala, L, Jilich, D, Sedlacek, D, Kronborg, G, Benfield, T, Gerstoft, J, Katzenstein, T, Møller, N, Ostergaard, L, Wiese, L, Nielsen, L, Zilmer, K, Smidt, J, Siseklinik, N, Aho, I, Viard, J, Duvivier, C, Schmidt, R, Degen, O, Stellbrink, H, Stefan, C, Goethe, J, Bogner, J, Chkhartishvili, N, Gargalianos, P, Xylomenos, G, Armenis, K, Sambatakou, H, Szlávik, J, Gottfredsson, M, Mulcahy, F, Yust, I, Turner, D, Burke, M, Shahar, E, Hassoun, G, Elinav, H, Haouzi, M, Sthoeger, Z, Esposito, R, Mazeu, I, Mussini, C, Mazzotta, F, Gabbuti, A, Annunziata, O, Vullo, V, Lichtner, M, Zaccarelli, M, Antinori, A, Acinapura, R, Plazzi, M, Lazzarin, A, Castagna, A, Gianotti, N, Galli, M, Ridolfo, A, Rozentale, B, Uzdaviniene, V, Matulionyte, R, Staub, T, Hemmer, R, Ormaasen, V, Maeland, A, Bruun, J, Knysz, B, Gasiorowski, J, Inglot, M, Bakowska, E, Flisiak, R, Grzeszczuk, A, Parczewski, M, Maciejewska, K, Aksak-Was, B, Beniowski, M, Mularska, E, Smiatacz, T, Gensing, M, Jablonowska, E, Malolepsza, E, Wojcik, K, Mozer-Lisewska, I, Caldeira, L, Mansinho, K, Maltez, F, Radoi, R, Panteleev, A, Panteleev, O, Yakovlev, A, Trofimora, T, Khromova, I, Kuzovatova, E, Blokhina, I, Novogrod, N, Borodulina, E, Vdoushkina, E, Jevtovic, D, Tomazic, J, Miró, J, Moreno, S, Rodriguez, J, Clotet, B, Jou, A, Paredes, R, Tural, C, Puig, J, Bravo, I, Gutierrez, M, Mateo, G, Laporte, J, Sonnerborg, A, Brännström, I, Flamholc, L, Cavassini, M, Calmy, A, Furrer, H, Battegay, M, Schmid, P, Kuznetsova, A, Kyselyova, G, Sluzhynska, M, Johnson, A, Simons, E, Johnson, M, Orkin, C, Weber, J, Scullard, G, Clarke, A, Leen, C, Morfeldt, C, Thulin, G, Åkerlund, B, Koppel, K, Karlsson, A, Håkangård, C, Castelli, F, Cauda, R, Perri, G, Iardino, R, Ippolito, G, Marchetti, G, Perno, C, von Schloesser, F, Viale, P, Ceccherini-Silberstein, F, Girardi, E, Caputo, S, Puoti, M, Andreoni, M, Ammassari, A, Balotta, C, Bandera, A, Bonfanti, P, Bonora, S, Borderi, M, Calcagno, A, Calza, L, Capobianchi, M, Cingolani, A, Cinque, P, De Luca, A, Biagio, A, Gori, A, Guaraldi, G, Lapadula, G, Madeddu, G, Maggiolo, F, Marcotullio, S, Monno, L, Nozza, S, Roldan, E, Rossotti, R, Rusconi, S, Santoro, M, Saracino, A, Galli, L, Lorenzini, P, Rodano, A, Shanyinde, M, Carletti, F, Carrara, S, Caro, A, Graziano, S, Petrone, F, Prota, G, Quartu, S, Truffa, S, Giacometti, A, Costantini, A, Barocci, V, Angarano, G, Santoro, C, Suardi, C, Donati, V, Verucchi, G, Minardi, C, Quirino, T, Abeli, C, Manconi, P, Piano, P, Cacopardo, B, Celesia, B, Vecchiet, J, Falasca, K, Pan, A, Lorenzotti, S, Sighinolfi, L, Segala, D, Vichi, F, Cassola, G, Viscoli, C, Alessandrini, A, Bobbio, N, Mazzarello, G, Mastroianni, C, Belvisi, V, Caramma, I, Chiodera, A, Milini, P, Rizzardini, G, Moioli, M, Piolini, R, Salpietro, S, Tincati, C, Puzzolante, C, Abrescia, N, Chirianni, A, Borgia, G, Orlando, R, Bonadies, G, Martino, F, Gentile, I, Maddaloni, L, Cattelan, A, Marinello, S, Cascio, A, Colomba, C, Baldelli, F, Schiaroli, E, Parruti, G, Sozio, F, Magnani, G, Ursitti, M, Cristaudo, A, Baldin, G, Capozzi, M, Cicalini, S, Sulekova, L, Iaiani, G, Latini, A, Mastrorosa, I, Savinelli, S, Vergori, A, Cecchetto, M, Viviani, F, Bagella, P, Rossetti, B, Franco, A, Del Vecchio, R, Francisci, D, Giuli, C, Caramello, P, Orofino, G, Sciandra, M, Bassetti, M, Londero, A, Pellizzer, G, Manfrin, V, Starnini, G, Ialungo, A, Central, C, Dellamonica, P, Bernard, E, Courjon, J, Cua, E, De Salvador-Guillouet, F, Durant, J, Etienne, C, Ferrando, S, Mondain-Miton, V, Naqvi, A, Perbost, I, Pillet, S, Prouvost-Keller, B, Pugliese, P, Rio, V, Risso, K, Roger, P, Aubert, V, Bernasconi, E, Böni, J, Braun, D, Bucher, H, Ciuffi, A, Dollenmaier, G, Egger, M, Elzi, L, Fehr, J, Fellay, J, Haerry, D, Hasse, B, Hirsch, H, Hoffmann, M, Hösli, I, Kahlert, C, Kaiser, L, Keiser, O, Klimkait, T, Kouyos, R, Kovari, H, Ledergerber, B, Martinetti, G, de Tejada, B, Marzolini, C, Metzner, K, Müller, N, Nicca, D, Pantaleo, G, Paioni, P, Rauch, A, Rudin, C, Speck, R, Stöckle, M, Tarr, P, Trkola, A, Vernazza, P, Wandeler, G, Yerly, S, Valk, M, Hutchinson, J, Rupasinghe, D, Han, W, Appoyer, H, Vera, J, Broster, B, Barbour, L, Carney, D, Greenland, L, Coughlan, R, Saint-Pierre, C, Stephan, C, Bucht, M, Chokoshvili, O, Borghi, V, Casabona, J, Miro, J, Lampe, F, Burns, F, Chaloner, C, Muccini, C, Lolatto, R, Sönnerborg, A, Nowak, P, Vesterbacka, J, Mattsson, L, Carrick, D, Stigsäter, K, Kusejko, K, Schulze, N, Franke, B, Rooney, J, Mcnicholl, I, Garges, H, Campo, R, Volny-Anne, A, Dedes, N, Williams, E, Bruguera, A, Volny-Anne, R, Mendão, L, Timiryasova, A, Fursa, O, Jakobsen, M, Kraef, C, Gardizi, M, Andersen, K, Kumar, L, Elsing, T, Shahi, S, Valdenmaiier, O, Bansi-Matharu, L, Byonanebye, D, Bannister, W, Roen, A, Null, N, Tusch, Erich, Ryom, Lene, Pelchen-Matthews, Annegret, Mocroft, Amanda, Elbirt, Daniel, Oprea, Cristiana, Günthard, Huldrych F, Staehelin, Cornelia, Zangerle, Robert, Suarez, Isabelle, Vehreschild, Jörg Janne, Wit, Ferdinand, Menozzi, Marianna, d'Arminio Monforte, Antonella, Spagnuolo, Vincenzo, Pradier, Christian, Carlander, Christina, Suanzes, Paula, Wasmuth, Jan-Christian, Carr, Andrew, Petoumenos, Kathy, Borgans, Frauke, Bonnet, Fabrice, De Wit, Stephane, El-Sadr, Wafaa, Neesgaard, Bastian, Jaschinski, Nadine, Greenberg, Lauren, Hosein, Sean R, Gallant, Joel, Vannappagari, Vani, Young, Lital, Sabin, Caroline, Lundgren, Jens, Peters, Lars, Reekie, Joanne, Monforte, A d’Arminio, Brandt, R Salbøl, Wit, F W N M, Marec, F Le, Laut, K Grønborg, Sabin, C A, Phillips, A N, Kamara, D A, Smith, C J, Hatleberg, C I, Brandt, R S, Grevsen, A L, Lundgren, J D, Fux, C A, Monforte, A d'Arminio, Iversen, J S, Reiss, Central P, Prins, J M, Kuijpers, T W, Scherpbier, H J, van der Meer, J T M, Godfried, M H, Nellen, F J B, Geerlings, S E, Bos, J C, Wiersinga, W J, Hovius, J W, van Hes, A M H, Nobel, H E, Pijnappel, F J J, Back, N K T, Zaaijer, H L, Cornelissen, M T E, Schinkel, C J, Thomas, X V, Ziekenhuis, Admiraal De Ruyter, de Looff, L Hage, Ziekenhuis, Catharina, Pronk, M J H, Ammerlaan, H S M, De Munnik, E S, Jansz, A R, Wegdam, M C A, Weijsenfeld, A M, van der Ende, M E, De Vries-Sluijs, T E M S, van Gorp, E C M, Schurink, C A M, Nouwen, J L, Rijnders, B J A, Bax, H I, van Beek, J E A, van Zonneveld, L M, van den Berg-Cameron, H J, Bruinsma-Broekman, F B, de Man, M de Zeeuw, Boucher, C A B, Koopmans, M P G, van Kampen, J J A, Pas, S D, MC–Sophia, Erasmus, Driessen, G J A, van Rossum, A M C, van der Knaap, L C, de Ven, C J H M Duijf-van, Ziekenhuis, Haga, Schippers, E F, van IJperen, J M, Franck, P F H, Elsenburg, L J M, Kwa, I S, Groeneveld, P H P, Bouwhuis, J W, van den Berg, J F, van Hulzen, A G W, van der Bliek, G L, Bor, P C J, Wolfhagen, M J H M, Ruijs, G J H M, Kroon, F P, de Boer, M G J, Bauer, M P, Vollaard, A M, Claas, E C J, den Hollander, J G, Smit, J V, Lowe, S H, Lashof, A M L Oude, Ackens, R P, van Loo, I H M, Havenith, T R A, Leyten, E M S, Gelinck, L B S, Wildenbeest, G S, Mutsaers, J A E M, Jansen, C L, Mulder, J W, Vrouenraets, S M E, Lauw, F N, van Broekhuizen, M C, Vlasblom, D J, Smits, P H M, Zuiderzee, M C, Bosma, A S, van Vonderen, M G A, van Houte, D P F, Kampschreur, L M, Kootstra, G J, Delsing, C E, Stuart, J W T Cohen, Diederen, B M W, van Truijen-Oud, F A, van der Reijden, W A, van den Berk, G E L, Blok, W L, Frissen, P H J, Lettinga, K D, Schouten, W E M, Brouwer, C J, Geerders, G F, Kleene, M J, van der Meché, I B, Toonen, A J M, Koopmans, P P, van der Ven, A J A M, ter Hofstede, H J M, Dofferhoff, A S M, Bosch, M E W, Grintjes-Huisman, K J T, Zomer, B J, Stelma, F F, Gisolf, E H, Hassing, R J, van Bentum, P H M, Swanink, C M A, van Lelyveld, S F L, van der Prijt, L M M, Herpers, B L, Verhagen, D W M, Ziekenhuis, St Elisabeth, van Kasteren, M E E, Brouwer, A E, de Wiel, B A F M de Kruijf-van, Santegoets, R M W J, Marcelis, J H, Buiting, A G M, Kabel, P J, Bierman, W F W, Wilting, K R, Jonge, H de Groot-de, van der Meulen, P A, de Weerd, D A, Niesters, H G M, van Leer-Buter, C C, Hoepelman, A I M, Ellerbroek, P M, Oosterheert, J J, Arends, J E, Barth, R E, Wassenberg, M W M, Schadd, E M, van Elst-Laurijssen, D H M, van Oers-Hazelzet, E E B, Wensing, A M J, Peters, E J G, van Agtmael, M A, Laan, L M, Pettersson, A M, Vandenbroucke-Grauls, C M J E, Ang, C W, Kinderziekenhuis, Wilhelmina, Geelen, S P M, Wolfs, T F W, Bont, L J, Bezemer, D O, van Sighem, A I, Boender, T S, Rademaker, M J, Pellegrin, J L, Vareil, M O, Dauchy, F A, Receveur, M C, Vandenhende, M A, Viallard, J F, Lafon, Me, Blaizeau, M J, Boerg, Eloïse, Law, Central M, Calvo, Central G, Sambeat, M A, Gennotte, A F, Payen, M C, Neaton, Central J, El-Sadr, W M, Abrams, D I, Crane, L R, Fischer, A H, Larsen, J F, Wien, Pulmologisches Zentrum der Stadt, Mitsura, V M, Møller, N F, Nielsen, L N, Smidt, Jelena, Siseklinik, Nakkusosakond, Viard, J-P, Stellbrink, H J, Goethe, J W, Sthoeger, Z M, Monforte, A D’Arminio, Annunziata, Ospedale S Maria, Blokhina, I N, Novogrod, Nizhny, Gatell, J M, Miró, J M, Rodriguez, J M, Laporte, J M, Johnson, A M, Johnson, M A, Morfeldt, Central L, Perri, G Di, Marchetti, G C, Perno, C F, Caputo, S Lo, Capobianchi, M R, Biagio, A Di, Roldan, E Quiros, Santoro, M M, Caro, A Di, Manconi, P E, Moioli, M C, Ridolfo, A L, Martino, F Di, Cattelan, A M, Ursitti, M A, Sulekova, L Fontanelli, Plazzi, M M, Del Vecchio, R Fontana, Giuli, C Di, Orofino, G C, Roger, P M, Braun, D L, Bucher, H C, Günthard, H F, Hirsch, H H, Kouyos, R D, de Tejada, B Martinez, Metzner, K J, Scherrer, A U, Valk, Marc vd, Han, W Min, Saint-Pierre, C H U, Miro, J M, Wasmuth, J C, Vehreschild, J J, McNicholl, I, Williams, E D, Volny-Anne, R Campo Alain, Dedes, Nikos, Mendão, Luis, Jakobsen, M L, Kumar, L Ramesh, Elsing, T W, null, null, Tusch, E, Ryom, L, Pelchen-Matthews, A, Mocroft, A, Elbirt, D, Oprea, C, Günthard, H, Staehelin, C, Zangerle, R, Suarez, I, Vehreschild, J, Wit, F, Menozzi, M, d'Arminio Monforte, A, Spagnuolo, V, Pradier, C, Carlander, C, Suanzes, P, Wasmuth, J, Carr, A, Petoumenos, K, Borgans, F, Bonnet, F, De Wit, S, El-Sadr, W, Neesgaard, B, Jaschinski, N, Greenberg, L, Hosein, S, Gallant, J, Vannappagari, V, Young, L, Sabin, C, Lundgren, J, Peters, L, Reekie, J, Calvo, G, Dabis, F, Kirk, O, Law, M, Monforte, A, Morfeldt, L, Reiss, P, Weber, R, Lind-Thomsen, A, Brandt, R, Hillebreght, M, Zaheri, S, Scherrer, A, Schöni-Affolter, F, Rickenbach, M, Tavelli, A, Fanti, I, Leleux, O, Mourali, J, Marec, F, Boerg, E, Thulin, E, Sundström, A, Bartsch, G, Thompsen, G, Necsoi, C, Delforge, M, Fontas, E, Caissotti, C, Dollet, K, Mateu, S, Torres, F, Blance, A, Huang, R, Puhr, R, Laut, K, Kristensen, D, Phillips, A, Kamara, D, Smith, C, Hatleberg, C, Raben, D, Matthews, C, Bojesen, A, Grevsen, A, Powderly, B, Shortman, N, Moecklinghoff, C, Reilly, G, Franquet, X, Smit, C, Ross, M, Fux, C, Morlat, P, Friis-Møller, N, Kowalska, J, Bohlius, J, Bower, M, Fätkenheuer, G, Grulich, A, Sjøl, A, Meidahl, P, Iversen, J, Reiss, C, Hillebregt, M, Prins, J, Kuijpers, T, Scherpbier, H, van der Meer, J, Godfried, M, van der Poll, T, Nellen, F, Geerlings, S, van Vugt, M, Pajkrt, D, Bos, J, Wiersinga, W, van der Valk, M, Goorhuis, A, Hovius, J, van Eden, J, Henderiks, A, van Hes, A, Mutschelknauss, M, Nobel, H, Pijnappel, F, Jurriaans, S, Back, N, Zaaijer, H, Berkhout, B, Cornelissen, M, Schinkel, C, Thomas, X, Ziekenhuis, A, van den Berge, M, Stegeman, A, Baas, S, de Looff, L, Versteeg, D, Ziekenhuis, C, Pronk, M, Ammerlaan, H, De Munnik, E, Jansz, A, Tjhie, J, Wegdam, M, Deiman, B, Scharnhorst, V, van der Plas, A, Weijsenfeld, A, van der Ende, M, De Vries-Sluijs, T, van Gorp, E, Schurink, C, Nouwen, J, Verbon, A, Rijnders, B, Bax, H, van der Feltz, M, Bassant, N, van Beek, J, Vriesde, M, van Zonneveld, L, de Oude-Lubbers, A, van den Berg-Cameron, H, Bruinsma-Broekman, F, de Groot, J, de Man, M, Boucher, C, Koopmans, M, van Kampen, J, Pas, S, Mc–sophia, E, Driessen, G, van Rossum, A, van der Knaap, L, Visser, E, Branger, J, Rijkeboer-Mes, A, de Ven, C, Ziekenhuis, H, Schippers, E, van Nieuwkoop, C, van IJperen, J, Geilings, J, van der Hut, G, Franck, P, van Eeden, A, Brokking, W, Groot, M, Elsenburg, L, Damen, M, Kwa, I, Groeneveld, P, Bouwhuis, J, van den Berg, J, van Hulzen, A, van der Bliek, G, Bor, P, Bloembergen, P, Wolfhagen, M, Ruijs, G, Kroon, F, de Boer, M, Bauer, M, Jolink, H, Vollaard, A, Dorama, W, van Holten, N, Claas, E, Wessels, E, den Hollander, J, Pogany, K, Roukens, A, Kastelijns, M, Smit, J, Smit, E, Struik-Kalkman, D, Tearno, C, Bezemer, M, van Niekerk, T, Pontesilli, O, Lowe, S, Lashof, A, Posthouwer, D, Ackens, R, Schippers, J, Vergoossen, R, Weijenberg-Maes, B, van Loo, I, Havenith, T, Leyten, E, Gelinck, L, van Hartingsveld, A, Meerkerk, C, Wildenbeest, G, Mutsaers, J, Jansen, C, Mulder, J, Vrouenraets, S, Lauw, F, van Broekhuizen, M, Paap, H, Vlasblom, D, Smits, P, Zuiderzee, M, Weijer, S, El Moussaoui, R, Bosma, A, van Vonderen, M, van Houte, D, Kampschreur, L, Dijkstra, K, Faber, S, Weel, J, Kootstra, G, Delsing, C, van der Burg-van de Plas, M, Heins, H, Lucas, E, Kortmann, W, van Twillert, G, Stuart, J, Diederen, B, Pronk, D, van Truijen-Oud, F, van der Reijden, W, Jansen, R, Brinkman, K, van den Berk, G, Blok, W, Frissen, P, Lettinga, K, Schouten, W, Veenstra, J, Brouwer, C, Geerders, G, Hoeksema, K, Kleene, M, van der Meché, I, Spelbrink, M, Sulman, H, Toonen, A, Wijnands, S, Kwa, D, Witte, E, Koopmans, P, Keuter, M, van der Ven, A, ter Hofstede, H, Dofferhoff, A, van Crevel, R, Albers, M, Bosch, M, Grintjes-Huisman, K, Zomer, B, Stelma, F, Rahamat-Langendoen, J, Burger, D, Richter, C, Gisolf, E, Hassing, R, ter Beest, G, van Bentum, P, Langebeek, N, Tiemessen, R, Swanink, C, van Lelyveld, S, Soetekouw, R, Hulshoff, N, van der Prijt, L, van der Swaluw, J, Bermon, N, Herpers, B, Veenendaal, D, Verhagen, D, van Wijk, M, Ziekenhuis, S, van Kasteren, M, Brouwer, A, de Wiel, B, Kuipers, M, Santegoets, R, van der Ven, B, Marcelis, J, Buiting, A, Kabel, P, Bierman, W, Scholvinck, H, Wilting, K, Stienstra, Y, Jonge, H, van der Meulen, P, de Weerd, D, Ludwig-Roukema, J, Niesters, H, Riezebos-Brilman, A, van Leer-Buter, C, Knoester, M, Hoepelman, A, Mudrikova, T, Ellerbroek, P, Oosterheert, J, Arends, J, Barth, R, Wassenberg, M, Schadd, E, van Elst-Laurijssen, D, van Oers-Hazelzet, E, Vervoort, S, van Berkel, M, Schuurman, R, Verduyn-Lunel, F, Wensing, A, Peters, E, van Agtmael, M, Bomers, M, de Vocht, J, Heitmuller, M, Laan, L, Pettersson, A, Vandenbroucke-Grauls, C, Ang, C, Kinderziekenhuis, W, Geelen, S, Wolfs, T, Bont, L, Nauta, N, Bezemer, D, van Sighem, A, Boender, T, de Jong, A, Bergsma, D, Hoekstra, P, de Lang, A, Grivell, S, Jansen, A, Rademaker, M, Raethke, M, Meijering, R, Schnörr, S, de Groot, L, van den Akker, M, Bakker, Y, Claessen, E, El Berkaoui, A, Koops, J, Kruijne, E, Lodewijk, C, Munjishvili, L, Peeck, B, Ree, C, Regtop, R, Ruijs, Y, Rutkens, T, van de Sande, L, Schoorl, M, Timmerman, A, Tuijn, E, Veenenberg, L, van der Vliet, S, Wisse, A, Woudstra, T, Tuk, B, Dupon, M, Gaborieau, V, Lacoste, D, Malvy, D, Mercié, P, Neau, D, Pellegrin, J, Tchamgoué, S, Lazaro, E, Cazanave, C, Vandenhende, M, Vareil, M, Gérard, Y, Blanco, P, Bouchet, S, Breilh, D, Fleury, H, Pellegrin, I, Chêne, G, Thiébaut, R, Wittkop, L, Lawson-Ayayi, S, Gimbert, A, Desjardin, S, Lacaze-Buzy, L, Petrov-Sanchez, V, André, K, Bernard, N, Caubet, O, Caunegre, L, Chossat, I, Courtault, C, Dauchy, F, De Witte, S, Dondia, D, Duffau, P, Dutronc, H, Farbos, S, Faure, I, Ferrand, H, Gerard, Y, Greib, C, Hessamfar, M, Imbert, Y, Lataste, P, Marie, J, Mechain, M, Monlun, E, Ochoa, A, Pistone, T, Raymond, I, Receveur, M, Rispal, P, Sorin, L, Valette, C, Viallard, J, Wille, H, Wirth, G, Lafon, M, Trimoulet, P, Bellecave, P, Tumiotto, C, Haramburu, F, Miremeont-Salamé, G, Blaizeau, M, Decoin, M, Hannapier, C, Lenaud, E, Pougetoux, A, Delveaux, S, D’Ivernois, C, Diarra, F, Uwamaliya-Nziyumvira, B, Palmer, G, Conte, V, Sapparrart, V, Law, C, Moore, R, Edwards, S, Hoy, J, Watson, K, Roth, N, Lau, H, Bloch, M, Baker, D, Cooper, D, O’Sullivan, M, Nolan, D, Guelfi, G, Calvo, C, Domingo, P, Sambeat, M, Gatell, J, Del Cacho, E, Cadafalch, J, Fuster, M, Codina, C, Sirera, G, Vaqué, A, Clumeck, N, Gennotte, A, Gerard, M, Kabeya, K, Konopnicki, D, Libois, A, Martin, C, Payen, M, Semaille, P, Van Laethem, Y, Neaton, C, Krum, E, Thompson, G, Wentworth, D, Luskin-Hawk, R, Telzak, E, Abrams, D, Cohn, D, Markowitz, N, Arduino, R, Mushatt, D, Friedland, G, Perez, G, Tedaldi, E, Fisher, E, Gordin, F, Crane, L, Sampson, J, Baxter, J, Gazzard, B, Horban, A, Karpov, I, Losso, M, Pedersen, C, Ristola, M, Rockstroh, J, Fischer, A, Larsen, J, Podlekareva, D, Cozzi-Lepri, A, Shepherd, L, Schultze, A, Amele, S, Kundro, M, Schmied, B, Wien, P, Vassilenko, A, Mitsura, V, Paduto, D, Florence, E, Vandekerckhove, L, Hadziosmanovic, V, Begovac, J, Machala, L, Jilich, D, Sedlacek, D, Kronborg, G, Benfield, T, Gerstoft, J, Katzenstein, T, Møller, N, Ostergaard, L, Wiese, L, Nielsen, L, Zilmer, K, Smidt, J, Siseklinik, N, Aho, I, Viard, J, Duvivier, C, Schmidt, R, Degen, O, Stellbrink, H, Stefan, C, Goethe, J, Bogner, J, Chkhartishvili, N, Gargalianos, P, Xylomenos, G, Armenis, K, Sambatakou, H, Szlávik, J, Gottfredsson, M, Mulcahy, F, Yust, I, Turner, D, Burke, M, Shahar, E, Hassoun, G, Elinav, H, Haouzi, M, Sthoeger, Z, Esposito, R, Mazeu, I, Mussini, C, Mazzotta, F, Gabbuti, A, Annunziata, O, Vullo, V, Lichtner, M, Zaccarelli, M, Antinori, A, Acinapura, R, Plazzi, M, Lazzarin, A, Castagna, A, Gianotti, N, Galli, M, Ridolfo, A, Rozentale, B, Uzdaviniene, V, Matulionyte, R, Staub, T, Hemmer, R, Ormaasen, V, Maeland, A, Bruun, J, Knysz, B, Gasiorowski, J, Inglot, M, Bakowska, E, Flisiak, R, Grzeszczuk, A, Parczewski, M, Maciejewska, K, Aksak-Was, B, Beniowski, M, Mularska, E, Smiatacz, T, Gensing, M, Jablonowska, E, Malolepsza, E, Wojcik, K, Mozer-Lisewska, I, Caldeira, L, Mansinho, K, Maltez, F, Radoi, R, Panteleev, A, Panteleev, O, Yakovlev, A, Trofimora, T, Khromova, I, Kuzovatova, E, Blokhina, I, Novogrod, N, Borodulina, E, Vdoushkina, E, Jevtovic, D, Tomazic, J, Miró, J, Moreno, S, Rodriguez, J, Clotet, B, Jou, A, Paredes, R, Tural, C, Puig, J, Bravo, I, Gutierrez, M, Mateo, G, Laporte, J, Sonnerborg, A, Brännström, I, Flamholc, L, Cavassini, M, Calmy, A, Furrer, H, Battegay, M, Schmid, P, Kuznetsova, A, Kyselyova, G, Sluzhynska, M, Johnson, A, Simons, E, Johnson, M, Orkin, C, Weber, J, Scullard, G, Clarke, A, Leen, C, Morfeldt, C, Thulin, G, Åkerlund, B, Koppel, K, Karlsson, A, Håkangård, C, Castelli, F, Cauda, R, Perri, G, Iardino, R, Ippolito, G, Marchetti, G, Perno, C, von Schloesser, F, Viale, P, Ceccherini-Silberstein, F, Girardi, E, Caputo, S, Puoti, M, Andreoni, M, Ammassari, A, Balotta, C, Bandera, A, Bonfanti, P, Bonora, S, Borderi, M, Calcagno, A, Calza, L, Capobianchi, M, Cingolani, A, Cinque, P, De Luca, A, Biagio, A, Gori, A, Guaraldi, G, Lapadula, G, Madeddu, G, Maggiolo, F, Marcotullio, S, Monno, L, Nozza, S, Roldan, E, Rossotti, R, Rusconi, S, Santoro, M, Saracino, A, Galli, L, Lorenzini, P, Rodano, A, Shanyinde, M, Carletti, F, Carrara, S, Caro, A, Graziano, S, Petrone, F, Prota, G, Quartu, S, Truffa, S, Giacometti, A, Costantini, A, Barocci, V, Angarano, G, Santoro, C, Suardi, C, Donati, V, Verucchi, G, Minardi, C, Quirino, T, Abeli, C, Manconi, P, Piano, P, Cacopardo, B, Celesia, B, Vecchiet, J, Falasca, K, Pan, A, Lorenzotti, S, Sighinolfi, L, Segala, D, Vichi, F, Cassola, G, Viscoli, C, Alessandrini, A, Bobbio, N, Mazzarello, G, Mastroianni, C, Belvisi, V, Caramma, I, Chiodera, A, Milini, P, Rizzardini, G, Moioli, M, Piolini, R, Salpietro, S, Tincati, C, Puzzolante, C, Abrescia, N, Chirianni, A, Borgia, G, Orlando, R, Bonadies, G, Martino, F, Gentile, I, Maddaloni, L, Cattelan, A, Marinello, S, Cascio, A, Colomba, C, Baldelli, F, Schiaroli, E, Parruti, G, Sozio, F, Magnani, G, Ursitti, M, Cristaudo, A, Baldin, G, Capozzi, M, Cicalini, S, Sulekova, L, Iaiani, G, Latini, A, Mastrorosa, I, Savinelli, S, Vergori, A, Cecchetto, M, Viviani, F, Bagella, P, Rossetti, B, Franco, A, Del Vecchio, R, Francisci, D, Giuli, C, Caramello, P, Orofino, G, Sciandra, M, Bassetti, M, Londero, A, Pellizzer, G, Manfrin, V, Starnini, G, Ialungo, A, Central, C, Dellamonica, P, Bernard, E, Courjon, J, Cua, E, De Salvador-Guillouet, F, Durant, J, Etienne, C, Ferrando, S, Mondain-Miton, V, Naqvi, A, Perbost, I, Pillet, S, Prouvost-Keller, B, Pugliese, P, Rio, V, Risso, K, Roger, P, Aubert, V, Bernasconi, E, Böni, J, Braun, D, Bucher, H, Ciuffi, A, Dollenmaier, G, Egger, M, Elzi, L, Fehr, J, Fellay, J, Haerry, D, Hasse, B, Hirsch, H, Hoffmann, M, Hösli, I, Kahlert, C, Kaiser, L, Keiser, O, Klimkait, T, Kouyos, R, Kovari, H, Ledergerber, B, Martinetti, G, de Tejada, B, Marzolini, C, Metzner, K, Müller, N, Nicca, D, Pantaleo, G, Paioni, P, Rauch, A, Rudin, C, Speck, R, Stöckle, M, Tarr, P, Trkola, A, Vernazza, P, Wandeler, G, Yerly, S, Valk, M, Hutchinson, J, Rupasinghe, D, Han, W, Appoyer, H, Vera, J, Broster, B, Barbour, L, Carney, D, Greenland, L, Coughlan, R, Saint-Pierre, C, Stephan, C, Bucht, M, Chokoshvili, O, Borghi, V, Casabona, J, Miro, J, Lampe, F, Burns, F, Chaloner, C, Muccini, C, Lolatto, R, Sönnerborg, A, Nowak, P, Vesterbacka, J, Mattsson, L, Carrick, D, Stigsäter, K, Kusejko, K, Schulze, N, Franke, B, Rooney, J, Mcnicholl, I, Garges, H, Campo, R, Volny-Anne, A, Dedes, N, Williams, E, Bruguera, A, Volny-Anne, R, Mendão, L, Timiryasova, A, Fursa, O, Jakobsen, M, Kraef, C, Gardizi, M, Andersen, K, Kumar, L, Elsing, T, Shahi, S, Valdenmaiier, O, Bansi-Matharu, L, Byonanebye, D, Bannister, W, Roen, A, Null, N, Tusch, Erich, Ryom, Lene, Pelchen-Matthews, Annegret, Mocroft, Amanda, Elbirt, Daniel, Oprea, Cristiana, Günthard, Huldrych F, Staehelin, Cornelia, Zangerle, Robert, Suarez, Isabelle, Vehreschild, Jörg Janne, Wit, Ferdinand, Menozzi, Marianna, d'Arminio Monforte, Antonella, Spagnuolo, Vincenzo, Pradier, Christian, Carlander, Christina, Suanzes, Paula, Wasmuth, Jan-Christian, Carr, Andrew, Petoumenos, Kathy, Borgans, Frauke, Bonnet, Fabrice, De Wit, Stephane, El-Sadr, Wafaa, Neesgaard, Bastian, Jaschinski, Nadine, Greenberg, Lauren, Hosein, Sean R, Gallant, Joel, Vannappagari, Vani, Young, Lital, Sabin, Caroline, Lundgren, Jens, Peters, Lars, Reekie, Joanne, Monforte, A d’Arminio, Brandt, R Salbøl, Wit, F W N M, Marec, F Le, Laut, K Grønborg, Sabin, C A, Phillips, A N, Kamara, D A, Smith, C J, Hatleberg, C I, Brandt, R S, Grevsen, A L, Lundgren, J D, Fux, C A, Monforte, A d'Arminio, Iversen, J S, Reiss, Central P, Prins, J M, Kuijpers, T W, Scherpbier, H J, van der Meer, J T M, Godfried, M H, Nellen, F J B, Geerlings, S E, Bos, J C, Wiersinga, W J, Hovius, J W, van Hes, A M H, Nobel, H E, Pijnappel, F J J, Back, N K T, Zaaijer, H L, Cornelissen, M T E, Schinkel, C J, Thomas, X V, Ziekenhuis, Admiraal De Ruyter, de Looff, L Hage, Ziekenhuis, Catharina, Pronk, M J H, Ammerlaan, H S M, De Munnik, E S, Jansz, A R, Wegdam, M C A, Weijsenfeld, A M, van der Ende, M E, De Vries-Sluijs, T E M S, van Gorp, E C M, Schurink, C A M, Nouwen, J L, Rijnders, B J A, Bax, H I, van Beek, J E A, van Zonneveld, L M, van den Berg-Cameron, H J, Bruinsma-Broekman, F B, de Man, M de Zeeuw, Boucher, C A B, Koopmans, M P G, van Kampen, J J A, Pas, S D, MC–Sophia, Erasmus, Driessen, G J A, van Rossum, A M C, van der Knaap, L C, de Ven, C J H M Duijf-van, Ziekenhuis, Haga, Schippers, E F, van IJperen, J M, Franck, P F H, Elsenburg, L J M, Kwa, I S, Groeneveld, P H P, Bouwhuis, J W, van den Berg, J F, van Hulzen, A G W, van der Bliek, G L, Bor, P C J, Wolfhagen, M J H M, Ruijs, G J H M, Kroon, F P, de Boer, M G J, Bauer, M P, Vollaard, A M, Claas, E C J, den Hollander, J G, Smit, J V, Lowe, S H, Lashof, A M L Oude, Ackens, R P, van Loo, I H M, Havenith, T R A, Leyten, E M S, Gelinck, L B S, Wildenbeest, G S, Mutsaers, J A E M, Jansen, C L, Mulder, J W, Vrouenraets, S M E, Lauw, F N, van Broekhuizen, M C, Vlasblom, D J, Smits, P H M, Zuiderzee, M C, Bosma, A S, van Vonderen, M G A, van Houte, D P F, Kampschreur, L M, Kootstra, G J, Delsing, C E, Stuart, J W T Cohen, Diederen, B M W, van Truijen-Oud, F A, van der Reijden, W A, van den Berk, G E L, Blok, W L, Frissen, P H J, Lettinga, K D, Schouten, W E M, Brouwer, C J, Geerders, G F, Kleene, M J, van der Meché, I B, Toonen, A J M, Koopmans, P P, van der Ven, A J A M, ter Hofstede, H J M, Dofferhoff, A S M, Bosch, M E W, Grintjes-Huisman, K J T, Zomer, B J, Stelma, F F, Gisolf, E H, Hassing, R J, van Bentum, P H M, Swanink, C M A, van Lelyveld, S F L, van der Prijt, L M M, Herpers, B L, Verhagen, D W M, Ziekenhuis, St Elisabeth, van Kasteren, M E E, Brouwer, A E, de Wiel, B A F M de Kruijf-van, Santegoets, R M W J, Marcelis, J H, Buiting, A G M, Kabel, P J, Bierman, W F W, Wilting, K R, Jonge, H de Groot-de, van der Meulen, P A, de Weerd, D A, Niesters, H G M, van Leer-Buter, C C, Hoepelman, A I M, Ellerbroek, P M, Oosterheert, J J, Arends, J E, Barth, R E, Wassenberg, M W M, Schadd, E M, van Elst-Laurijssen, D H M, van Oers-Hazelzet, E E B, Wensing, A M J, Peters, E J G, van Agtmael, M A, Laan, L M, Pettersson, A M, Vandenbroucke-Grauls, C M J E, Ang, C W, Kinderziekenhuis, Wilhelmina, Geelen, S P M, Wolfs, T F W, Bont, L J, Bezemer, D O, van Sighem, A I, Boender, T S, Rademaker, M J, Pellegrin, J L, Vareil, M O, Dauchy, F A, Receveur, M C, Vandenhende, M A, Viallard, J F, Lafon, Me, Blaizeau, M J, Boerg, Eloïse, Law, Central M, Calvo, Central G, Sambeat, M A, Gennotte, A F, Payen, M C, Neaton, Central J, El-Sadr, W M, Abrams, D I, Crane, L R, Fischer, A H, Larsen, J F, Wien, Pulmologisches Zentrum der Stadt, Mitsura, V M, Møller, N F, Nielsen, L N, Smidt, Jelena, Siseklinik, Nakkusosakond, Viard, J-P, Stellbrink, H J, Goethe, J W, Sthoeger, Z M, Monforte, A D’Arminio, Annunziata, Ospedale S Maria, Blokhina, I N, Novogrod, Nizhny, Gatell, J M, Miró, J M, Rodriguez, J M, Laporte, J M, Johnson, A M, Johnson, M A, Morfeldt, Central L, Perri, G Di, Marchetti, G C, Perno, C F, Caputo, S Lo, Capobianchi, M R, Biagio, A Di, Roldan, E Quiros, Santoro, M M, Caro, A Di, Manconi, P E, Moioli, M C, Ridolfo, A L, Martino, F Di, Cattelan, A M, Ursitti, M A, Sulekova, L Fontanelli, Plazzi, M M, Del Vecchio, R Fontana, Giuli, C Di, Orofino, G C, Roger, P M, Braun, D L, Bucher, H C, Günthard, H F, Hirsch, H H, Kouyos, R D, de Tejada, B Martinez, Metzner, K J, Scherrer, A U, Valk, Marc vd, Han, W Min, Saint-Pierre, C H U, Miro, J M, Wasmuth, J C, Vehreschild, J J, McNicholl, I, Williams, E D, Volny-Anne, R Campo Alain, Dedes, Nikos, Mendão, Luis, Jakobsen, M L, Kumar, L Ramesh, Elsing, T W, and null, null

Abstract

Background: Mortality among people with HIV declined with the introduction of combination antiretroviral therapy. We investigated trends over time in all-cause and cause-specific mortality in people with HIV from 1999-2020. Methods: Data were collected from the D:A:D cohort from 1999 through January 2015 and RESPOND from October 2017 through 2020. Age-standardized all-cause and cause-specific mortality rates, classified using Coding Causes of Death in HIV (CoDe), were calculated. Poisson regression models were used to assess mortality trends over time. Results: Among 55716 participants followed for a median of 6 years (IQR 3-11), 5263 participants died (crude mortality rate [MR] 13.7/1000 PYFU; 95%CI 13.4-14.1). Changing patterns of mortality were observed with AIDS as the most common cause of death between 1999- 2009 (n = 952, MR 4.2/1000 PYFU; 95%CI 4.0-4.5) and non-AIDS defining malignancy (NADM) from 2010 -2020 (n = 444, MR 2.8/1000 PYFU; 95%CI 2.5-3.1). In multivariable analysis, all-cause mortality declined over time (adjusted mortality rate ratio [aMRR] 0.97 per year; 95%CI 0.96, 0.98), mostly from 1999 through 2010 (aMRR 0.96 per year; 95%CI 0.95-0.97), and with no decline shown from 2011 through 2020 (aMRR 1·00 per year; 95%CI 0·96-1·05). Mortality due all known causes except NADM also declined over the entire follow-up period. Conclusion: Mortality among people with HIV in the D:A:D and/or RESPOND cohorts decreased between 1999 and 2009 and was stable over the period from 2010 through 2020. The decline in mortality rates was not fully explained by improvements in immunologic-virologic status or other risk factors.

Published
2024

50. Ceftolozane/tazobactam for the treatment of serious Pseudomonas aeruginosa infections: a multicentre nationwide clinical experience

Author

Bassetti, Matteo, Vena, Antonio, Castaldo, Nadia, Pecori, Davide, Righi, Elda, Carnellutti, Alessia, Givone, Filippo, Graziano, Elena, Merelli, Maria, Cadeo, Barbara, Peghin, Maddalena, Cattelan, Annamaria, Cipriani, Ludovica, Coletto, Davide, Mussini, Cristina, Digaetano, Margherita, Tascini, Carlo, Carannante, Novella, Menichetti, Francesco, Verdenelli, Stefano, Fabiani, Silvia, Mastroianni, Claudio Maria, Gianluca, Russo, Oliva, Alessandra, Ciardi, Maria Rosa, Ajassa, Camilla, Tieghi, Tiziana, Tumbarello, Mario, Losito, Angela Raffaella, Raffaelli, Francesca, Grossi, Paolo, Rovelli, Cristina, Artioli, Stefania, Caruana, Giorgia, Luzzati, Roberto, Bontempo, Giulia, Petrosillo, Nicola, Capone, Alessandro, Rizzardini, Giuliano, Coen, Massimo, Passerini, Matteo, Mastroianni, Antonio, Urso, Filippo, Bianco, Maria Francesca, Borgia, Guglielmo, Gentile, Ivan, Maraolo, Alberto Enrico, Crapis, Massimo, Venturini, Sergio, Parruti, Giustino, Trave, Francesca, Angarano, Gioacchino, Carbonara, Sergio, Mariani, Michele Fabiano, Girardis, Massimo, Cascio, Antonio, Gioé, Claudia, Anselmo, Marco, Malfatto, Emanuele, Russo, Alessandro, and Nicolè, Stefano

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results