1,806 results on '"Cortesi, P."'
Number of results to display per page
Search Results
102. Purinergic enzymes on extracellular vesicles: immune modulation on the go
- Author
-
Riekje Winzer, Du Hanh Nguyen, Felix Schoppmeier, Filippo Cortesi, Nicola Gagliani, and Eva Tolosa
- Subjects
extracellular vesicles ,purinergic signaling ,CD73 ,adenosine ,immune regulation ,tumor microenvironment ,Immunologic diseases. Allergy ,RC581-607 - Abstract
An increase in the extracellular concentration of ATP as a consequence of cellular stress or cell death results in the activation of immune cells. To prevent inflammation, extracellular ATP is rapidly metabolized to adenosine, which deploys an anti-inflammatory signaling cascade upon binding to P1 receptors on immune cells. The ectonucleotidases necessary for the degradation of ATP and generation of adenosine are present on the cell membrane of many immune cells, and their expression is tightly regulated under conditions of inflammation. The discovery that extracellular vesicles (EVs) carry purinergic enzyme activity has brought forward the concept of EVs as a new player in immune regulation. Adenosine-generating EVs derived from cancer cells suppress the anti-tumor response, while EVs derived from immune or mesenchymal stem cells contribute to the restoration of homeostasis after infection. Here we will review the existing knowledge on EVs containing purinergic enzymes and molecules, and discuss the relevance of these EVs in immune modulation and their potential for therapy.
- Published
- 2024
- Full Text
- View/download PDF
103. An environmental dependence of the physical and structural properties in the Hydra Cluster galaxies
- Author
-
Lima-Dias, Ciria, Monachesi, Antonela, Torres-Flores, Sergio, Cortesi, Arianna, Hernández-Lang, Daniel, Barbosa, Carlos Eduardo, de Oliveira, Claudia Mendes, Olave-Rojas, Daniela, Pallero, Diego, Sampedro, Laura, Molino, Alberto, Herpich, Fabio R., Jaffé, Yara L., Amorín, Ricardo, Chies-Santos, Ana L., Dimauro, Paola, Telles, Eduardo, Lopes, Paulo A. A., Alvarez-Candal, Alvaro, Ferrari, Fabricio, Kanaan, Antonio, Ribeiro, Tiago, and Schoenell, William
- Subjects
Astrophysics - Astrophysics of Galaxies ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The nearby Hydra Cluster ($\sim$50 Mpc) is an ideal laboratory to understand, in detail, the influence of the environment on the morphology and quenching of galaxies in dense environments. We study the Hydra cluster galaxies in the inner regions ($1R_{200}$) of the cluster using data from the Southern Photometric Local Universe Survey (S-PLUS), which uses 12 narrow and broad band filters in the visible region of the spectrum. We analyse structural (S\'ersic index, effective radius) and physical (colours, stellar masses and star formation rates) properties. Based on this analysis, we find that $\sim$88 percent of the Hydra cluster galaxies are quenched. Using the Dressler-Schectman test approach, we also find that the cluster shows possible substructures. Our analysis of the phase-space diagram together with DBSCAN algorithm indicates that Hydra shows an additional substructure that appears to be in front of the cluster centre, which is still falling into it. Our results, thus, suggest that the Hydra Cluster might not be relaxed. We analyse the median S\'ersic index as a function of wavelength and find that for red ($(u-r)\geq$2.3) and early-type galaxies it displays a slight increase towards redder filters (13 and 18 percent, for red and early-type respectively) whereas for blue+green ($(u-r)$<2.3) galaxies it remains constant. Late-type galaxies show a small decrease of the median S\'ersic index toward redder filters. Also, the S\'ersic index of galaxies, and thus their structural properties, do not significantly vary as a function of clustercentric distance and density within the cluster; and this is the case regardless of the filter., Comment: Accepted for publication in MNRAS
- Published
- 2020
- Full Text
- View/download PDF
104. Formation of S0s in extreme environments II: the star-formation histories of bulges, discs and lenses
- Author
-
Johnston, Evelyn J., Aragón-Salamanca, Alfonso, Fraser-McKelvie, Amelia, Merrifield, Michael, Häußler, Boris, Coccato, Lodovico, Jaffé, Yara, Cortesi, Ariana, Chies-Santos, Ana, Del Pino, Bruno Rodríguez, and Sheen, Yun-Kyeong
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
Different processes have been proposed to explain the formation of S0s, including mergers, disc instabilities and quenched spirals. These processes are expected to dominate in different environments, and thus leave characteristic footprints in the kinematics and stellar populations of the individual components within the galaxies. New techniques enable us to cleanly disentangle the kinematics and stellar populations of these components in IFU observations. In this paper, we use buddi to spectroscopically extract the light from the bulge, disc and lens components within a sample of 8 S0 galaxies in extreme environments observed with MUSE. While the spectra of bulges and discs in S0 galaxies have been separated before, this work is the first to isolate the spectra of lenses. Stellar populations analysis revealed that the bulges and lenses have generally similar or higher metallicities than the discs, and the $\alpha$-enhancement of the bulges and discs are correlated, while those of the lenses are completely unconnected to either component. We conclude that the majority of the mass in these galaxies was built up early in the lifetime of the galaxy, with the bulges and discs forming from the same material through dissipational processes at high redshift. The lenses, on the other hand, formed over independent timescales at more random times within the lifetime of the galaxy, possibly from evolved bars. The younger stellar populations and asymmetric features seen in the field S0s may indicate that these galaxies have been affected more by minor mergers than the cluster galaxies., Comment: 25 pages, accepted for publication in MNRAS
- Published
- 2020
- Full Text
- View/download PDF
105. Weather regimes linked to daily precipitation anomalies in Northern Chile
- Author
-
Meseguer-Ruiz, Ó., Cortesi, N., Guijarro, J. A., and Sarricolea, P.
- Subjects
Physics - Atmospheric and Oceanic Physics - Abstract
Northern Chile is one of the most arid regions in the world, with precipitation mainly occurring during austral summer, between December and April 1966-2015. The aim of this study is to classify the main weather regimes derived from sea level pressure, surface wind speed, 500 or 250 hPa geopotential heights, in order to measure their influence on precipitation anomalies and determine if they can be considered sources of predictability of rainfall in this region. Four weather regimes were found to optimally describe atmospheric circulation in the study area and for each of the four levels described above. Using daily precipitation data from a network of 161 meteorological stations across the region, the rainfall anomalies associated with each weather regime were quantified. They are coherent with the direction of flow derived from pressure and geopotential anomalies, bringing humid air masses from the Amazon Basin or the Pacific. The transitions between the different regimes are also coherent, representing transitions to and from similar regimes. A few negative and significant trends in the persistence of different regimes were detected, most likely linked to the absence of anthropogenic warming in the Antarctic as opposed to the Arctic. Finally, two of the regimes derived from surface wind speed exhibit a negative and significant trend in its frequency of occurrence, determining a precipitation decrease in the south of the study area (28-30 S), which can be compared with the Megadrought experienced in central Chile., Comment: 24 pages, 12 figures
- Published
- 2020
- Full Text
- View/download PDF
106. $^{25}$Si $\beta^+$-decay spectroscopy
- Author
-
Sun, L. J., Friedman, M., Budner, T., Pérez-Loureiro, D., Pollacco, E., Wrede, C., Brown, B. A., Cortesi, M., Fry, C., Glassman, B. E., Heideman, J., Janasik, M., Kruskie, A., Magilligan, A., Roosa, M., Stomps, J., Surbrook, J., and Tiwari, P.
- Subjects
Nuclear Experiment - Abstract
$\beta$-decay spectroscopy provides valuable information on exotic nuclei and a stringent test for nuclear theories beyond the stability line. To search for new $\beta$-delayed protons and $\gamma$ rays of $^{25}$Si to investigate the properties of $^{25}$Al excited states. $^{25}$Si $\beta$ decays were measured by using the Gaseous Detector with Germanium Tagging system at the National Superconducting Cyclotron Laboratory. The protons and $\gamma$ rays emitted in the decay were detected simultaneously. A Monte Carlo method was used to model the Doppler broadening of $^{24}$Mg $\gamma$-ray lines caused by nuclear recoil from proton emission. Shell-model calculations using two newly developed universal \textit{sd}-shell Hamiltonians, USDC and USDI, were performed. The most precise $^{25}$Si half-life to date has been determined. A new proton branch at 724(4)~keV and new proton-$\gamma$-ray coincidences have been identified. Three $^{24}$Mg $\gamma$-ray lines and eight $^{25}$Al $\gamma$-ray lines are observed for the first time in $^{25}$Si decay. The first measurement of the $^{25}$Si $\beta$-delayed $\gamma$ ray intensities through the $^{25}$Al unbound states is reported. All the bound states of $^{25}$Al are observed to be populated in the $\beta$ decay of $^{25}$Si. Several inconsistencies between the previous measurements have been resolved, and new information on the $^{25}$Al level scheme is provided. An enhanced decay scheme has been constructed and compared to the mirror decay of $^{25}$Na and the shell-model calculations. The measured excitation energies, $\gamma$-ray and proton branchings, log~$ft$ values, and Gamow-Teller transition strengths for the states of $^{25}$Al populated in the $\beta$ decay of $^{25}$Si are in good agreement with the shell-model calculations, offering gratifyingly consistent insights into the fine nuclear structure of $^{25}$Al.
- Published
- 2020
- Full Text
- View/download PDF
107. J-PAS: Measuring emission lines with artificial neural networks
- Author
-
Martínez-Solaeche, G., Delgado, R. M. González, García-Benito, R., de Amorim, A., Pérez, E., Rodríguez-Martín, J. E., Díaz-García, L. A., Fernandes, R. Cid, López-Sanjuan, C., Bonoli, S., Cenarro, A. J., Dupke, R. A., Marín-Franch, A., Varela, J., Ramió, H. Vázquez, Abramo, L. R., Cristóbal-Hornillo, D., Moles, M., Alcaniz, J., Baqui, P. O., Benitez, N., Carneiro, S., Cortesi, A., Ederoclite, A., Marra, V., de Oliveira, C. Mendes, Sodré Jr., L., Vílchez, J. M., Taylor, K., and collaboration, JPAS
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
Throughout this paper we present a new method to detect and measure emission lines in J-PAS up to $z = 0.35$. J-PAS will observe $8000$~deg$^2$ of the northern sky in the upcoming years with 56 photometric bands. The release of such amount of data brings us the opportunity to employ machine learning methods in order to overcome the difficulties associated with photometric data. We used Artificial Neural Networks (ANNs) trained and tested with synthetic J-PAS photometry from CALIFA, MaNGA, and SDSS spectra. We carry out two tasks: firstly, we cluster galaxies in two groups according to the values of the equivalent width (EW) of $H\alpha$, $H\beta$, $[NII]{\lambda 6584}$, and $ [OIII]{\lambda 5007}$ lines measured in the spectra. Then, we train an ANN to assign to each galaxy a group. We are able to classify them with the uncertainties typical of the photometric redshift measurable in J-PAS. Secondly, we utilize another ANN to determine the values of those EWs. Subsequently, we obtain the $[NII]/H\alpha$, $[OIII]/H\beta$, and \ion{O}{3}\ion{N}{2} ratios recovering the BPT diagram . We study the performance of the ANN in two training samples: one is only composed of synthetic J-PAS photo-spectra (J-spectra) from MaNGA and CALIFA (CALMa set) and the other one is composed of SDSS galaxies. We can reproduce properly the main sequence of star forming galaxies from the determination of the EWs. With the CALMa training set we reach a precision of 0.093 and 0.081 dex for the $[NII]/H\alpha$ and $[OIII]/H\beta$ ratios in the SDSS testing sample. Nevertheless, we find an underestimation of those ratios at high values in galaxies hosting an AGN. We also show the importance of the dataset used for both training and testing the model. ANNs are extremely useful to overcome the limitations previously expected concerning the detection and measurements of the emission lines in surveys like J-PAS., Comment: 19 pages, 14 figures, Accepted to A&A
- Published
- 2020
- Full Text
- View/download PDF
108. Inverted metallicity gradients in two Virgo cluster star-forming dwarf galaxies: evidence of recent merging?
- Author
-
Grossi, M., García-Benito, R., Cortesi, A., Gonçalves, D. R., Gonçalves, T. S., Lopes, P. A. A., Menéndez-Delmestre, K., and Telles, E.
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
We present integral field spectroscopy observations of two star-forming dwarf galaxies in the Virgo cluster (VCC135 and VCC324) obtained with PMAS/PPak at the Calar Alto 3.5 meter telescope. We derive metallicity maps using the N2 empirical calibrator. The galaxies show positive gas metallicity gradients, contrarily to what is usually found in other dwarfs or in spiral galaxies. We measure gradient slopes of 0.20 $\pm$ 0.06 and 0.15 $\pm$ 0.03 dex/$R_e$ for VCC135 and VCC324, respectively. Such a trend has been only observed in few, very isolated galaxies, or at higher redshifts ($z >$ 1). It is thought to be associated with accretion of metal-poor gas from the intergalactic medium, a mechanism that would be less likely to occur in a high-density environment like Virgo. We combine emission line observations with deep optical images to investigate the origin of the peculiar metallicity gradient. The presence of weak underlying substructures in both galaxies and the analysis of morphological diagnostics and of ionised gas kinematics suggest that the inflow of metal-poor gas to the central regions of the dwarfs may be related to a recent merging event with a gas-rich companion., Comment: 13 pages, 9 figures, MNRAS in press. V2: minor figure revisions and minor title changes
- Published
- 2020
- Full Text
- View/download PDF
109. The halo of M105 and its group environment as traced by planetary nebula populations: I. Wide-field photometric survey of planetary nebulae in the Leo I group
- Author
-
Hartke, J., Arnaboldi, M., Gerhard, O., Coccato, L., Pulsoni, C., Freeman, K. C., Merrifield, M., Cortesi, A., and Kuijken, K.
- Subjects
Astrophysics - Astrophysics of Galaxies ,Astrophysics - Solar and Stellar Astrophysics - Abstract
M105 (NGC 3379) is an early-type galaxy in the Leo I group. This group is the nearest group that contains all main galaxy types and can thus be used as a benchmark to study the properties of the intra-group light (IGL) in low-mass groups. We use PNe as discrete stellar tracers of the diffuse light around M105. PNe were identified on the basis of their bright [OIII]5007 AA emission and the absence of a broad-band continuum. We compare the PN number density profile with the galaxy surface-brightness profile decomposed into metallicity components using published HST photometry in two halo fields. We identify 226 PNe candidates within a limiting magnitude of mlim = 28.1 from our Subaru-SuprimeCam imaging, covering 67.6 kpc along the major axis of M105 and the halos of NGC 3384 and NGC 3398. We find an excess of PNe at large radii compared to the stellar surface brightness profile from broad-band surveys. This excess is related to a variation in the luminosity-specific PN number $\alpha$ with radius. The $\alpha$-parameter value of the extended halo is more than 7 times higher than that of the inner halo. We also measure an increase in the slope of the PN luminosity function at fainter magnitudes with radius. We infer that the radial variation of the PN population properties is due to a diffuse population of metal-poor stars ([M/H] < -1.0) following an exponential profile, in addition to the M105 halo. The spatial coincidence between the number density profile of these metal-poor stars and the increase in the $\alpha$-parameter value with radius establishes the missing link between metallicity and the post-AGB phases of stellar evolution. We estimate that the total bolometric luminosity associated with the exponential IGL population is 2.04x10^9 Lsun as a lower limit, corresponding to an IGL fraction of 3.8%. This work sets the stage for kinematic studies of the IGL in low-mass groups., Comment: 22 pages, 18 figures, accepted for publication in Astronomy & Astrophysics. Abridged abstract
- Published
- 2020
- Full Text
- View/download PDF
110. The miniJPAS survey: a preview of the Universe in 56 colours
- Author
-
Bonoli, S., Marín-Franch, A., Varela, J., Ramió, H. Vázquez, Abramo, L. R., Cenarro, A. J., Dupke, R. A., Vílchez, J. M., Cristóbal-Hornillos, D., Delgado, R. M. González, Hernández-Monteagudo, C., López-Sanjuan, C., Muniesa, D. J., Civera, T., Ederoclite, A., Hernán-Caballero, A., Marra, V., Baqui, P. O., Cortesi, A., Cypriano, E. S., Daflon, S., de Amorim, A. L., Díaz-García, L. A., Diego, J. M., Martínez-Solaeche, G., Pérez, E., Placco, V. M., Prada, F., Queiroz, C., Alcaniz, J., Alvarez-Candal, A., Cepa, J., Maroto, A. L., Roig, F., Siffert, B. B., Taylor, K., Benitez, N., Moles, M., Sodré Jr., L., Carneiro, S., de Oliveira, C. Mendes, Abdalla, E., Angulo, R. E., Resco, M. Aparicio, Balaguera-Antolínez, A., Ballesteros, F. J., Brito-Silva, D., Broadhurst, T., Carrasco, E. R., Castro, T., Fernandes, R. Cid, Coelho, P., de Melo, R. B., Doubrawa, L., Fernandez-Soto, A., Ferrari, F., Finoguenov, A., García-Benito, R., Iglesias-Páramo, J., Jiménez-Teja, Y., Kitaura, F. S., Laur, J., Lopes, P. A. A., Lucatelli, G., Martínez, V. J., Maturi, M., Quartin, M., Pigozzo, C., Rodrìguez-Martìn, J. E., Salzano, V., Tamm, A., Tempel, E., Umetsu, K., Valdivielso, L., von Marttens, R., Zitrin, A., Díaz-Martín, M. C., López-Alegre, G., López-Sainz, A., Yanes-Díaz, A., Rueda-Teruel, F., Rueda-Teruel, S., Ibañez, J. Abril, Bravo, J. L Antón, Ferrer, R. Bello, Bielsa, S., Casino, J. M., Castillo, J., Chueca, S., Cuesta, L., Calderaro, J. Garzarán, Iglesias-Marzoa, R., Íniguez, C., Gutierrez, J. L. Lamadrid, Lopez-Martinez, F., Lozano-Pérez, D., Sacristán, N. Maícas, Molina-Ibáñez, E. L., Moreno-Signes, A., Llano, S. Rodríguez, Navarro, M. Royo, Rua, V. Tilve, Andrade, U., Alfaro, E. J., Akras, S., Arnalte-Mur, P., Ascaso, B., Barbosa, C. E., Jiménez, J. Beltrán, Benetti, M., Bengaly, C. A. P., Bernui, A., Blanco-Pillado, J. J., Fernandes, M. Borges, Bregman, J. N., Bruzual, G., Calderone, G., Carvano, J. M., Casarini, L., Chies-Santos, A. L, de Carvalho, G. Coutinho, Dimauro, P., Puertas, S. Duarte, Figueruelo, D., González-Serrano, J. I., Guerrero, M. A., Gurung-López, S., Herranz, D., Huertas-Company, M., Irwin, J. A., Izquierdo-Villalba, D., Kanaan, A., Kehrig, C., Kirkpatrick, C. C., Lim, J., Lopes, A. R., de Oliveira, R. Lopes, Marcos-Caballero, A., Martínez-Delgado, D., Martínez-González, E., Martínez-Somonte, G., Oliveira, N., Orsi, A. A., Overzier, R. A., Penna-Lima, M., Reis, R. R. R., Spinoso, D., Tsujikawa, S., Vielva, P., Vitorelli, A. Z., Xia, J. Q., Yuan, H. B., Arroyo-Polonio, A., Dantas, M. L. L., Galarza, C. A., Gonçalves, D. R., Gonçalves, R. S., Gonzalez, J. E., Gonzalez, A. H., Greisel, N., Landim, R. G., Lazzaro, D., Magris, G., Monteiro-Oliveira, R., Pereira, C. B., Rebouças, M. J., Rodriguez-Espinosa, J. M., da Costa, S. Santos, and Telles, E.
- Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Astrophysics of Galaxies ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will soon start to scan thousands of square degrees of the northern extragalactic sky with a unique set of $56$ optical filters from a dedicated $2.55$m telescope, JST, at the Javalambre Astrophysical Observatory. Before the arrival of the final instrument (a 1.2 Gpixels, 4.2deg$^2$ field-of-view camera), the JST was equipped with an interim camera (JPAS-Pathfinder), composed of one CCD with a 0.3deg$^2$ field-of-view and resolution of 0.23 arcsec pixel$^{-1}$. To demonstrate the scientific potential of J-PAS, with the JPAS-Pathfinder camera we carried out a survey on the AEGIS field (along the Extended Groth Strip), dubbed miniJPAS. We observed a total of $\sim 1$ deg$^2$, with the $56$ J-PAS filters, which include $54$ narrow band (NB, $\rm{FWHM} \sim 145$Angstrom) and two broader filters extending to the UV and the near-infrared, complemented by the $u,g,r,i$ SDSS broad band (BB) filters. In this paper we present the miniJPAS data set, the details of the catalogues and data access, and illustrate the scientific potential of our multi-band data. The data surpass the target depths originally planned for J-PAS, reaching $\rm{mag}_{\rm {AB}}$ between $\sim 22$ and $23.5$ for the NB filters and up to $24$ for the BB filters ($5\sigma$ in a $3$~arcsec aperture). The miniJPAS primary catalogue contains more than $64,000$ sources extracted in the $r$ detection band with forced photometry in all other bands. We estimate the catalogue to be complete up to $r=23.6$ for point-like sources and up to $r=22.7$ for extended sources. Photometric redshifts reach subpercent precision for all sources up to $r=22.5$, and a precision of $\sim 0.3$% for about half of the sample. (Abridged), Comment: The miniJPAS data and associated value added catalogues are publicly accessible via this url: http://archive.cefca.es/catalogues/minijpas-pdr201912
- Published
- 2020
- Full Text
- View/download PDF
111. Twinning automata and regular expressions for string static analysis
- Author
-
Negrini, Luca, Arceri, Vincenzo, Ferrara, Pietro, and Cortesi, Agostino
- Subjects
Computer Science - Software Engineering ,Computer Science - Formal Languages and Automata Theory - Abstract
In this paper we formalize and prove the soundness of Tarsis, a new abstract domain based on the abstract interpretation theory that approximates string values through finite state automata. The main novelty of Tarsis is that it works over an alphabet of strings instead of single characters. On the one hand, such approach requires a more complex and refined definition of the widening operator, and the abstract semantics of string operators. On the other hand, it is in position to obtain strictly more precise results than than state-of-the-art approaches. We implemented a prototype of Tarsis, and we applied it on some case studies taken from some of the most popular Java libraries manipulating string values. The experimental results confirm that Tarsis is in position to obtain strictly more precise results than existing analyses.
- Published
- 2020
112. One hundred SMUDGes in S-PLUS: ultra-diffuse galaxies flourish in the field
- Author
-
Barbosa, C. E., Zaritsky, D., Donnerstein, R., Zhang, H., Dey, A., de Oliveira, C. Mendes, Sampedro, L., Molino, A., Costa-Duarte, M. V., Coelho, P., Cortesi, A., Herpich, F. R., Hernandez-Jimenez, J. A., Santos-Silva, T., Pereira, E., Werle, A., Overzier, R. A., Fernandes, R. Cid, Castelli, A. V. Smith, Ribeiro, T., Schoenell, W., and Kanaan, A.
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
We present the first systematic study of the stellar populations of ultra-diffuse galaxies (UDGs) in the field, integrating the large area search and characterization of UDGs by the SMUDGes survey with the twelve-band optical photometry of the S-PLUS survey. Based on Bayesian modeling of the optical colors of UDGs, we determine the ages, metallicities and stellar masses of 100 UDGs distributed in an area of $\sim 330$ deg$^2$ in the Stripe 82 region. We find that the stellar masses and metallicities of field UDGs are similar to those observed in clusters and follow the trends previously defined in studies of dwarf and giant galaxies. However, field UDGs have younger luminosity-weighted ages than do UDGs in clusters. We interpret this result to mean that field UDGs have more extended star formation histories, including some that continue to form stars at low levels to the present time. Finally, we examine stellar population scaling relations that show that UDGs are, as a population, similar to other low-surface brightness galaxies., Comment: 24 pages, 10 figures, accepted for Publication in ApJS
- Published
- 2020
- Full Text
- View/download PDF
113. First direct measurement of $^{22}$Mg($\alpha$,p)$^{25}$Al and implications for X-ray burst model-observation comparisons
- Author
-
Randhawa, J. S., Ayyad, Y., Mittig, W., Meisel, Z., Ahn, T., Aguilar, S., Alvarez-Pol, H., Bardayan, D. W., Bazin, D., Beceiro-Novo, S., Carpenter, L., Cortesi, M., Cortina-Gil, D., Blankstein, D., Gastis, P., Hall, M., Henderson, S., Kolata, J. J., Mijatovic, T., Ndayisabye, F., Malley, P. O, Pereira, J., Pierre, A., Robert, H., Santamaria, C., Schatz, H., Smith, J., Watwood, N., and Zamora, J. C.
- Subjects
Nuclear Experiment - Abstract
Type-I X-ray burst (XRB) light curves are sensitive to the model's nuclear input and consequently affects the model-observation comparisons. $^{22}$Mg($\alpha$,p)$^{25}$Al is among the most important reactions which directly impact the XRB light curve. We report the first direct measurement of $^{22}$Mg($\alpha$,p)$^{25}$Al using the Active Target Time Projection Chamber. XRB light curve model-observation comparison for the source $\tt{GS 1826-24}$ using new reaction rate implies a less-compact neutron star than previously inferred. Additionally, our result removes an important uncertainty in XRB model calculations that previously hindered extraction of the neutron star compactness.
- Published
- 2020
- Full Text
- View/download PDF
114. Unraveling the safety of adjuvant radiotherapy in prostate cancer: impact of older age and hypofractionated regimens on acute and late toxicity - a multicenter comprehensive analysis
- Author
-
Milly Buwenge, Gabriella Macchia, Letizia Cavallini, Annalisa Cortesi, Claudio Malizia, Lorenzo Bianchi, Maria Ntreta, Alessandra Arcelli, Ilaria Capocaccia, Elena Natoli, Savino Cilla, Francesco Cellini, Luca Tagliaferri, Lidia Strigari, Silvia Cammelli, Riccardo Schiavina, Eugenio Brunocilla, Alessio Giuseppe Morganti, and Francesco Deodato
- Subjects
prostate neoplasms ,observational study ,toxicity ,predictive factors ,radiotherapy ,adjuvant therapy ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
BackgroundThe objective of this study was to assess the impact of age and other patient and treatment characteristics on toxicity in prostate cancer patients receiving adjuvant radiotherapy (RT).Materials and methodsThis observational study (ICAROS-1) evaluated both acute (RTOG) and late (RTOG/EORTC) toxicity. Patient- (age; Charlson’s comorbidity index) and treatment-related characteristics (nodal irradiation; previous TURP; use, type, and duration of ADT, RT fractionation and technique, image-guidance systems, EQD2 delivered to the prostate bed and pelvic nodes) were recorded and analyzed.ResultsA total of 381 patients were enrolled. The median EQD2 to the prostate bed (α/β=1.5) was 71.4 Gy. The majority of patients (75.4%) were treated with intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT). Acute G3 gastrointestinal (GI) and genitourinary (GU) toxicity rates were 0.5% and 1.3%, respectively. No patients experienced >G3 acute toxicity. The multivariable analysis of acute toxicity (binomial logistic regression) showed a statistically significant association between older age (> 65) and decreased odds of G≥2 GI acute toxicity (OR: 0.569; 95%CI: 0.329-0.973; p: 0.040) and decreased odds of G≥2 GU acute toxicity (OR: 0.956; 95%CI: 0.918-0.996; p: 0.031). The 5-year late toxicity-free survival rates for G≥3 GI and GU toxicity were 98.1% and 94.5%, respectively. The only significant correlation found (Cox’s regression model) was a reduced risk of late GI toxicity in patients undergoing hypofractionation (HR: 0.38; 95% CI: 0.18-0.78; p: 0.008).ConclusionsThe unexpected results of this analysis could be explained by a “response shift bias” concerning the protective effect of older age and by treatment in later periods (using IMRT/VMAT) concerning the favorable effect of hypofractionation. However, overall, the study suggests that age should not be a reason to avoid adjuvant RT and that the latter is well-tolerated even with moderately hypofractionated regimens.
- Published
- 2023
- Full Text
- View/download PDF
115. High-resolution monitoring of landslides with UAS photogrammetry and digital image correlation
- Author
-
Francesco Mugnai, Andrea Masiero, Riccardo Angelini, and Irene Cortesi
- Subjects
digital image correlation (DIC) ,unmanned aircraft system (UAS) ,GNSS ,deformation map ,monitoring ,Oceanography ,GC1-1581 ,Geology ,QE1-996.5 - Abstract
ABSTRACTPeriodically monitoring landslides is a key factor for supporting the realisation of hazard warning systems and risk reduction in the corresponding neighbourhood areas. Although satellite remote sensing solutions can be considered for low spatial resolution monitoring, this approach is still inappropriate for high spatial resolution investigations. Ground-based Radar Interferometry is also a widely used technique that allows for working at a proper spatial resolution, but it can often be an overbudget solution for most applications. Instead, photogrammetric surveys based on Unmanned Aerial System (UAS) imagery appear as a very interesting approach in terms of both spatial resolution and flexibility in temporally repeating the survey. Motivated by this observation, this work investigates the use of multi-temporal UAS surveys for landslide monitoring. To be more precise, Digital Image Correlation (DIC) has been applied to orthomosaics generated from different UAS photogrammetry surveys to compute the area’s deformation map. Compared with a reference GNSS survey, the results obtained using NHAZCA IRIS software and an in-house DIC approach show a deformation estimation accuracy of approximately 0.1 m, a reasonable accuracy for landslides moving at moderate velocity.
- Published
- 2023
- Full Text
- View/download PDF
116. J-PLUS: Tools to identify compact planetary nebulae in the Javalambre and southern photometric local universe surveys
- Author
-
Gutiérrez-Soto, L. A., Gonçalves, D. R., Akras, S., Cortesi, A., López-Sanjuan, C., Guerrero, M. A., Daflon, S., Fernandes, M. Borges, de Oliveira, C. Mendes, Ederoclite, A., Sodré Jr, L., Pereira, C. B., Kanaan, A., Werle, A., Ramió, H. Vázquez, Alcaniz, J. S., Angulo, R. E., Cenarro, A. J., Cristóbal-Hornillos, D., Dupke, R. A., Hernández-Monteagudo, C., Marín-Franch, A., Moles, M., Varela, J., Ribeiro, T., Schoenell, W., Alvarez-Candal, A., Galbany, L., Jiménez-Esteban, F. M., Logroño-García, R., and Sobral, D.
- Subjects
Astrophysics - Astrophysics of Galaxies ,Astrophysics - Solar and Stellar Astrophysics - Abstract
From the approximately $\sim$3,500 planetary nebulae (PNe) discovered in our Galaxy, only 14 are known to be members of the Galactic halo. Nevertheless, a systematic search for halo PNe has never been performed. In this study, we present new photometric diagnostic tools to identify compact PNe in the Galactic halo by making use of the novel 12-filter system projects, J-PLUS (Javalambre Photometric Local Universe Survey) and S-PLUS (Southern-Photometric Local Universe Survey). We reconstructed the IPHAS (Isaac Newton Telescope (INT) Photometric H${\alpha}$ Survey of the Northern Galactic Plane) diagnostic diagram and propose four new ones using i) the J-PLUS and S-PLUS synthetic photometry for a grid of photo-ionisation models of halo PNe, ii) several observed halo PNe, as well as iii) a number of other emission-line objects that resemble PNe. All colour-colour diagnostic diagrams are validated using two known halo PNe observed by J-PLUS during the scientific verification phase and the first data release (DR1) of S-PLUS and the DR1 of J-PLUS. By applying our criteria to the DR1s ($\sim$1,190 deg$^2$), we identified one PN candidate. However, optical follow-up spectroscopy proved it to be a H II region belonging to the UGC 5272 galaxy. Here, we also discuss the PN and two H II galaxies recovered by these selection criteria. Finally, the cross-matching with the most updated PNe catalogue (HASH) helped us to highlight the potential of these surveys, since we recover all the known PNe in the observed area. The tools here proposed to identify PNe and separate them from their emission-line contaminants proved to be very efficient thanks to the combination of many colours, even when applied -like in the present work- to an automatic photometric search that is limited to compact PNe., Comment: 12 pages, 10 figures, accepted for publication at A&A
- Published
- 2019
- Full Text
- View/download PDF
117. Formation of S0s in extreme environments I: clues from kinematics and stellar populations
- Author
-
Coccato, Lodovico, Jaffé, Yara L., Cortesi, Arianna, Merrifield, Michael, Johnston, Evelyn, del Pino, Bruno Rodríguez, Haeussler, Boris, Chies-Santos, Ana L., de Oliveira, Claudia L. Mendes, Sheen, Yun-Kyeong, and Menéndez-Delmestre, Karín
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
Despite numerous efforts, it is still unclear whether lenticular galaxies (S0s) evolve from spirals whose star formation was suppressed, or formed trough mergers or disk instabilities. In this paper we present a pilot study of 21 S0 galaxies in extreme environments (field and cluster), and compare their spatially-resolved kinematics and global stellar populations. Our aim is to identify whether there are different mechanisms that form S0s in different environments. Our results show that the kinematics of S0 galaxies in field and cluster are, indeed, different. Lenticulars in the cluster are more rotationally supported, suggesting that they are formed through processes that involve the rapid consumption or removal of gas (e.g. starvation, ram pressure stripping). In contrast, S0s in the field are more pressure supported, suggesting that minor mergers served mostly to shape their kinematic properties. These results are independent of total mass, luminosity, or disk-to-bulge ratio. On the other hand, the mass-weighted age, metallicity, and star formation time-scale of the galaxies correlate more with mass than with environment, in agreement with known relations from previous work such as the one between mass and metallicity. Overall, our results re-enforce the idea that there are multiple mechanisms that produce S0s, and that both mass $and$ environment play key roles. A larger sample is highly desirable to confirm or refute the results and the interpretation of this pilot study., Comment: 18 pages, 11 figure, accepted for publication in MNRAS
- Published
- 2019
- Full Text
- View/download PDF
118. Development of a novel MPGD-based drift chamber for the NSCL/FRIB S800 spectrometer
- Author
-
Cortesi, M., Pereira, J., Bazin, D., Ayyad, Y., Cerizza, G., Fox, R., and Zegers, R. G. T.
- Subjects
Physics - Instrumentation and Detectors ,High Energy Physics - Experiment ,Nuclear Experiment - Abstract
The performance of a novel tracking detector developed for the focal plane of the NSCL/FRIB S800 magnetic spectrometer is presented. The detector comprises a large-area drift chamber equipped with a hybrid Micro-Pattern Gaseous Detector (MPGD)-based readout. The latter consists of a position-sensitive Micromegas detector preceded by a two-layer M-THGEM multiplier as a pre-amplification stage. The signals from the Micromegas readout are processed by a data acquisition system based on the General Electronics for TPC (GET). The drift chamber has an effective area of around 60x30 cm^2, which matches to the very large acceptance of the S800 spectrometer. This work discusses in detail the results of performance evaluation tests carried out with a low-energy alpha-particles source and with high-energy heavy-ion beams with the detector installed at the S800 focal plane. In this latter case, the detector was irradiated with a 150 MeV/u 78Kr36+ beam as well as a heavy-ion fragmentation cocktail beam produced by the 78Kr36+ beam impinging on a thin beryllium target. Sub-millimeter position resolution is obtained in both dispersive and non-dispersive directions., Comment: 13 pages, 13 figures
- Published
- 2019
- Full Text
- View/download PDF
119. An Overview of PARP Inhibitors for the Treatment of Breast Cancer
- Author
-
Cortesi, Laura, Rugo, Hope S, and Jackisch, Christian
- Subjects
Clinical Research ,Clinical Trials and Supportive Activities ,Genetics ,Breast Cancer ,Cancer ,6.2 Cellular and gene therapies ,5.1 Pharmaceuticals ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Development of treatments and therapeutic interventions ,Good Health and Well Being ,Breast Neoplasms ,Female ,Humans ,Poly(ADP-ribose) Polymerase Inhibitors ,Oncology and Carcinogenesis ,Oncology & Carcinogenesis - Abstract
Loss-of-function mutations in BRCA1 and BRCA2 are detected in at least 5% of unselected patients with breast cancer (BC). These BC susceptibility genes encode proteins critical for DNA homologous recombination repair (HRR). This review provides an update on oral poly(ADP-ribose) polymerase (PARP) inhibitors for the treatment of BC. Olaparib and talazoparib are PARP inhibitors approved as monotherapies for deleterious/suspected deleterious germline BRCA-mutated, HER2-negative BC. Olaparib is approved in the USA for metastatic BC and in Europe for locally advanced/metastatic BC. Talazoparib is approved for locally advanced/metastatic BC in the USA and Europe. In phase 3 trials, olaparib and talazoparib monotherapies demonstrated significant progression-free survival benefits compared with chemotherapy. Common toxicities were effectively managed by supportive treatment and dose interruptions/reductions. Veliparib combined with platinum-based chemotherapy has also shown promise for locally advanced/metastatic BC in a phase 3 trial. Differences in efficacy and safety across PARP inhibitors (olaparib, talazoparib, veliparib, niraparib, rucaparib) may relate to differences in potency of PARP trapping on DNA and cytotoxic specificity. PARP inhibitors are being investigated in early BC, in novel combinations, and in patients without germline BRCA mutations, including those with somatic BRCA mutations and other HRR gene mutations. Ongoing phase 2/3 studies include PARP inhibitors combined with immune checkpoint inhibitors for the treatment of triple-negative BC. Wider access to testing for BRCA and other mutations, and to genetic counseling, are required to identify patients who could benefit from PARP inhibitor therapy. The advent of PARP inhibitors has potential benefits for BC treatment beyond the locally advanced/metastatic setting.
- Published
- 2021
120. A PERFORMANCE COMPARISON BETWEEN SEGNET AND DEEPLABV3+ ON THE SEMANTIC SEGMENTATION OF HERITAGE BUILDINGS
- Author
-
E. Pellis, A. Masiero, I. Cortesi, G. Tucci, M. Betti, and P. Grussenmeyer
- Subjects
Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Applied optics. Photonics ,TA1501-1820 - Abstract
During the last decade, the use of machine and deep learning tools to support 3D semantic segmentation of point clouds remarkably increased and their impressive results have led to the application of such methods to the semantic modeling of heritage buildings. Nevertheless, a standard procedure to deal with such problem is still missing, and several significant challenges, caused by the complexity of heritage building scenario, have still to be faced. This paper aims at comparing the overall performance of two convolutional neural network architectures, named SegNet and Deeplabv3+, for the semantic segmentation of heritage point clouds throughout a multiview approach. More specifically, the two architectures have been tested to obtain 2D segmentation maps of the related photogrammetric images of the buildings, and then the output maps have been projected to the photogrammetric point cloud by means of the interior and exterior camera parameters. Experiments to test the effectiveness of the proposed approach have been conducted on the case study of Spedale del Ceppo in Pistoia, Italy. Despite the results shown a remarkable performance of both the architectures, Deeplabv3+ outperformed SegNet in terms of accuracy, memory consumption and training time.
- Published
- 2023
- Full Text
- View/download PDF
121. ON THE CO-REGISTRATION OF ASYNCHRONOUS MULTI-SPECTRAL AND THERMAL IMAGES
- Author
-
I. Cortesi, A. Masiero, N. Pfeifer, and G. Tucci
- Subjects
Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Applied optics. Photonics ,TA1501-1820 - Abstract
Plastic pollution has a severe impact on the ecosystem, altering its natural equilibrium and causing serious health issues to both flora and fauna. Several actions have already been undertaken in order to reduce the plastic litter dispersion in the environment, both in terms of changing the human behavior, reducing the use of plastics and avoiding their dispersion, and of implementing methods for detecting and collecting the already dispersed ones. This paper focuses on the latter, and, in particular, on plastic litter detection on the fluvial environment. To this aim, an Unmanned Aerial Vehicle, provided with a multi-spectral and a thermal camera, have been used, in order to: (i) allow affordable periodic monitoring of relatively long river reaches, (ii) detect even quite small macro-plastics, based on their spectral signature. More specifically, since the cameras deployed in our data collection campaigns are not synchronized, this work aims at presenting the developed strategy for the co-registration of the acquired imagery, which results to be quite challenging given the few amount of visual features recognizable on the images acquired flying at a limited altitude over a river. The proposed methodology, which is based on the correlation maximization between multi-spectral and thermal images, provided reasonable results on the considered case study. The obtained values of normalized intersection over union of plastic areas are over 80%.
- Published
- 2023
- Full Text
- View/download PDF
122. Books to the Masses! An Investigation of Russian WWI ‘Dime Stories’
- Author
-
Luca Cortesi
- Subjects
Russian literature ,war literature ,WWI ,dime literature ,dime stories ,Literature (General) ,PN1-6790 - Abstract
The impact of WWI on Russian society was immediately disruptive. This effect affected every sphere of social and cultural environs. Although previous research has established that WWI was a major topic of the cultural discourse of that time, the way in which WWI literature, and in particular consumer literature, contributed to the representation of war among the mass population deserves further research. By drawing a parallel with the phenomenon of the American dime novel, this study is grounded on the analysis of the style, content, structure, and even of the ‘mere’ appearance of some 1914–1916 ‘mass’ publications aimed at the broader public. The goal of this article, therefore, is to stimulate a consistent re-evaluation of this strand of ‘consumer’ war literature and to focus on its importance as a culturological tool to have a better understanding of the cultural environment of that time.
- Published
- 2023
- Full Text
- View/download PDF
123. Long term longitudinal follow-up of an AD-HIES cohort: the impact of early diagnosis and enrollment to IPINet centers on the natural history of Job’s syndrome
- Author
-
Maria Carrabba, Rosa Maria Dellepiane, Manuela Cortesi, Lucia Augusta Baselli, Annarosa Soresina, Emilia Cirillo, Giuliana Giardino, Francesca Conti, Laura Dotta, Andrea Finocchi, Caterina Cancrini, Cinzia Milito, Lucia Pacillo, Bianca Laura Cinicola, Fausto Cossu, Rita Consolini, Davide Montin, Isabella Quinti, Andrea Pession, Giovanna Fabio, Claudio Pignata, Maria Cristina Pietrogrande, and Raffaele Badolato
- Subjects
AD-HIES ,Job’s syndrome ,Immunodeficiency ,Inborn errors of immunity ,STAT3 ,Pneumatocele ,Immunologic diseases. Allergy ,RC581-607 - Abstract
Abstract Job’s syndrome, or autosomal dominant hyperimmunoglobulin E syndrome (AD-HIES, STAT3-Dominant Negative), is a rare inborn error of immunity (IEI) with multi-organ involvement and long-life post-infective damage. Longitudinal registries are of primary importance in improving our knowledge of the natural history and management of these rare disorders. This study aimed to describe the natural history of 30 Italian patients with AD-HIES recorded in the Italian network for primary immunodeficiency (IPINet) registry. This study shows the incidence of manifestations present at the time of diagnosis versus those that arose during follow up at a referral center for IEI. The mean time of diagnostic delay was 13.7 years, while the age of disease onset was
- Published
- 2023
- Full Text
- View/download PDF
124. Predictive role of diffusion-weighted MRI in the assessment of response to total neoadjuvant therapy in locally advanced rectal cancer
- Author
-
Iafrate, Franco, Ciccarelli, Fabio, Masci, Giorgio Maria, Grasso, Damiano, Marruzzo, Francesco, De Felice, Francesca, Tombolini, Vincenzo, D’Ambrosio, Giancarlo, Magliocca, Fabio Massimo, Cortesi, Enrico, and Catalano, Carlo
- Published
- 2023
- Full Text
- View/download PDF
125. Validation of the Adult Eating Behavior Questionnaire in an Italian Community Sample
- Author
-
Emanuela S. Gritti, Ludovica Cionti, Federica Cortesi, Alessandro Torelli, Andrea Gambarini, Claudia Hunot-Alexander, and Anna L. Ogliari
- Subjects
eating ,behavior ,appetitive traits ,adult ,validation ,questionnaire ,Nutrition. Foods and food supply ,TX341-641 - Abstract
(1) Background: Appetitive traits in adults can be measured through the Adult Eating Behavior Questionnaire (AEBQ), a questionnaire adapted from the Child Eating Behavior Questionnaire (CEBQ). The AEBQ has been validated in several countries. The aim of the present study was to explore and validate the factor structure of the Italian version of the AEBQ. Furthermore, convergent validity and correlations between factors and BMI were explored to assess its criterion validity. (2) Methods: Participants (N = 624, mean age of 32.08 ± 14.94 years) completed the AEBQ, the Eating Attitude Test (EAT-40), and the Dutch Eating Behavior Questionnaire (DEBQ). They also self-reported demographic and anthropometric data. A Confirmatory Factor Analysis (CFA) was used to test three different alternative models that emerged in previous validations. (3) Results: The CFA revealed a good model fit (RMSEA = 0.0634, TLI = 0.894, CFI = 0.907) for the 7-factor structure, without the Hunger items, showing a valid and reliable (Cronbach’s α > 0.7) structure. Convergent and divergent validity of the AEBQ yielded favorable results, and relationships between the AEBQ and BMI factors revealed that the Food Approach traits were positively associated with BMI. (4) Conclusions: Finally, this study provides initial support for the use of the AEBQ as a valid and reliable tool to measure a wide range of appetitive traits in the adult Italian population.
- Published
- 2024
- Full Text
- View/download PDF
126. Mucosal immune alterations at the early onset of tissue destruction in chronic obstructive pulmonary disease
- Author
-
Charlotte de Fays, Vincent Geudens, Iwein Gyselinck, Pieterjan Kerckhof, Astrid Vermaut, Tinne Goos, Marie Vermant, Hanne Beeckmans, Janne Kaes, Jan Van Slambrouck, Yousry Mohamady, Lynn Willems, Lucia Aversa, Emanuela E. Cortesi, Charlotte Hooft, Gitte Aerts, Celine Aelbrecht, Stephanie Everaerts, John E. McDonough, Laurens J. De Sadeleer, Sophie Gohy, Jerome Ambroise, Wim Janssens, Laurens J. Ceulemans, Dirk Van Raemdonck, Robin Vos, Tillie L. Hackett, James C. Hogg, Naftali Kaminski, Ghislaine Gayan-Ramirez, Charles Pilette, and Bart M. Vanaudenaerde
- Subjects
lung mucosal immunity ,chronic obstructive pulmonary disease ,airway inflammation ,lung tissue destruction ,emphysema severity ,Immunologic diseases. Allergy ,RC581-607 - Abstract
RationaleCOPD is characterized by chronic airway inflammation, small airways changes, with disappearance and obstruction, and also distal/alveolar destruction (emphysema). The chronology by which these three features evolve with altered mucosal immunity remains elusive. This study assessed the mucosal immune defense in human control and end-stage COPD lungs, by detailed microCT and RNA transcriptomic analysis of diversely affected zones.MethodsIn 11 control (non-used donors) and 11 COPD (end-stage) explant frozen lungs, 4 cylinders/cores were processed per lung for microCT and tissue transcriptomics. MicroCT was used to quantify tissue percentage and alveolar surface density to classify the COPD cores in mild, moderate and severe alveolar destruction groups, as well as to quantify terminal bronchioles in each group. Transcriptomics of each core assessed fold changes in innate and adaptive cells and pathway enrichment score between control and COPD cores. Immunostainings of immune cells were performed for validation.ResultsIn mildly affected zones, decreased defensins and increased mucus production were observed, along CD8+ T cell accumulation and activation of the IgA pathway. In more severely affected zones, CD68+ myeloid antigen-presenting cells, CD4+ T cells and B cells, as well as MHCII and IgA pathway genes were upregulated. In contrast, terminal bronchioles were decreased in all COPD cores.ConclusionSpatial investigation of end-stage COPD lungs show that mucosal defense dysregulation with decreased defensins and increased mucus and IgA responses, start concomitantly with CD8+ T-cell accumulation in mild emphysema zones, where terminal bronchioles are already decreased. In contrast, adaptive Th and B cell activation is observed in areas with more advanced tissue destruction. This study suggests that in COPD innate immune alterations occur early in the tissue destruction process, which affects both the alveoli and the terminal bronchioles, before the onset of an adaptive immune response.
- Published
- 2023
- Full Text
- View/download PDF
127. Low-energy $^{23}$Al $\beta$-delayed proton decay and $^{22}$Na destruction in novae
- Author
-
Friedman, M., Budner, T., Pérez-Loureiro, D., Pollacco, E., Wrede, C., José, J., Brown, B. A., Cortesi, M., Fry, C., Glassman, B., Heideman, J., Janasik, M., Roosa, M., Stomps, J., Surbrook, J., and Tiwari, P.
- Subjects
Nuclear Experiment - Abstract
The radionuclide $^{22}$Na is a target of $\gamma$-ray astronomy searches, predicted to be produced during thermonuclear runaways driving classical novae. The $^{22}$Na(p,$\gamma$)$^{23}$Mg reaction is the main destruction channel of $^{22}$Na during a nova, hence, its rate is needed to accurately predict the $^{22}$Na yield. However, experimental determinations of the resonance strengths have led to inconsistent results. In this work, we report a measurement of the branching ratios of the $^{23}$Al $\beta$-delayed protons, as a probe of the key 204--keV (center-of-mass) $^{22}$Na(p,$\gamma$)$^{23}$Mg resonance strength. We report a factor of 5 lower branching ratio compared to the most recent literature value. The variation in $^{22}$Na yield due to nuclear data inconsistencies was assessed using a series of hydrodynamic nova outburst simulations and has increased to a factor of 3.8, corresponding to a factor of $\sim$2 uncertainty in the maximum detectability distance. This is the first reported scientific measurement using the Gaseous Detector with Germanium Tagging (GADGET) system.
- Published
- 2019
- Full Text
- View/download PDF
128. The S-PLUS: a star/galaxy classification based on a Machine Learning approach
- Author
-
Costa-Duarte, M. V., Sampedro, L., Molino, A., Xavier, H. S., Herpich, F. R., Chies-Santos, A. L., Barbosa, C. E., Cortesi, A., Schoenell, W., Kanaan, A., Ribeiro, T., de Oliveira, C. Mendes, Akras, S., Alvarez-Candal, A., Barbosa, C. L., Castellón, J. L. N., Coelho, P., Dantas, M. L. L., Dupke, R., Ederoclite, A., Galarza, A., Gonçalves, T. S., Hernandez-Jimenez, J. A., Jiménez-Teja, Y., Lopes, A., Lopes, P. A. A., de Oliveira, R. Lopes, de Azevedo, J. L. Melo, Nakazono, L. M., Perottoni, H. D., Queiroz, C., Saha, K., Sodré Jr., L., Telles, E., and de Souza, R. C. Thom
- Subjects
Astrophysics - Astrophysics of Galaxies ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
We present a star/galaxy classification for the Southern Photometric Local Universe Survey (S-PLUS), based on a Machine Learning approach: the Random Forest algorithm. We train the algorithm using the S-PLUS optical photometry up to $r$=21, matched to SDSS/DR13, and morphological parameters. The metric of importance is defined as the relative decrease of the initial accuracy when all correlations related to a certain feature is vanished. In general, the broad photometric bands presented higher importance when compared to narrow ones. The influence of the morphological parameters has been evaluated training the RF with and without the inclusion of morphological parameters, presenting accuracy values of 95.0\% and 88.1\%, respectively. Particularly, the morphological parameter {\rm FWHM/PSF} performed the highest importance over all features to distinguish between stars and galaxies, indicating that it is crucial to classify objects into stars and galaxies. We investigate the misclassification of stars and galaxies in the broad-band colour-colour diagram $(g-r)$ versus $(r-i)$. The morphology can notably improve the classification of objects at regions in the diagram where the misclassification was relatively high. Consequently, it provides cleaner samples for statistical studies. The expected contamination rate of red galaxies as a function of the redshift is estimated, providing corrections for red galaxy samples. The classification of QSOs as extragalactic objects is slightly better using photometric-only case. An extragalactic point-source catalogue is provided using the classification without any morphology feature (only the SED information) with additional constraints on photometric redshifts and {\rm FWHM/PSF} values., Comment: 11 pages and 6 figures, submitted to MNRAS
- Published
- 2019
129. Network Reconnaissance and Vulnerability Excavation of Secure DDS Systems
- Author
-
White, Ruffin, Caiazza, Gianluca, Jiang, Chenxu, Ou, Xinyue, Yang, Zhiyue, Cortesi, Agostino, and Christensen, Henrik
- Subjects
Computer Science - Cryptography and Security ,Computer Science - Networking and Internet Architecture - Abstract
Distribution Service (DDS) is a realtime peer-to-peer protocol that serves as a scalable middleware between distributed networked systems found in many Industrial IoT domains such as automotive, medical, energy, and defense. Since the initial ratification of the standard, specifications have introduced a Security Model and Service Plugin Interface (SPI) architecture, facilitating authenticated encryption and data centric access control while preserving interoperable data exchange. However, as Secure DDS v1.1, the default plugin specifications presently exchanges digitally signed capability lists of both participants in the clear during the crypto handshake for permission attestation; thus breaching confidentiality of the context of the connection. In this work, we present an attacker model that makes use of network reconnaissance afforded by this leaked context in conjunction with formal verification and model checking to arbitrarily reason about the underlying topology and reachability of information flow, enabling targeted attacks such as selective denial of service, adversarial partitioning of the data bus, or vulnerability excavation of vendor implementations., Comment: 10 pages, 7 figures, 1 algorithm, 10 sections plus references
- Published
- 2019
130. Development of the TIP-HOLE gas avalanche structure for nuclear physics/astrophysics applications with radioactive isotope beams: preliminary results
- Author
-
Randhawa, Jaspreet Singh, Cortesi, Marco, Mittig, Wolfgang, Wierzbicki, Thomas, and Gomez, Alejandro
- Subjects
Physics - Instrumentation and Detectors - Abstract
We discuss the operational principle and performance of new micro-pattern gaseous detectors based on the multi-layer Thick Gaseous Electron Multiplier (M-THGEM) concept coupled to a needle-like anode. The new gas avalanche structure aims at high-gain operation in nuclear physics and nuclear astrophysics applications with radioactive isotope beams. It is thereafter named TIP-HOLE gas amplifier, and consists of a THGEM or a two-layers M-THGEM mounted in a WELL configuration. The avalanche electrodes are collected by thin conductive needles (with up to a few ten um radius and a height of 100 um), located at the center of the hole and acting as point-like anode. The bottom area of the needle may be surrounded by a cylindrical cathode strip in order to increase the electron collection efficiency. The electric field lines from the drift region above the M-THGEM are focused into the holes, and then forced to converge on the needle tip. An extremely high field is reached at the top of the needle, creating a point-like avalanche process. Stable, high-gain operations in a wide range of pressures may be achieved at relatively low operational voltage, even in pure quencher gas at atmospheric pressure (e.g. pure isobutene). The TIP-HOLE structure may be produced by the innovative scalable additive manufacturing technology for large-area, multiple-layer printed circuit boards, recently developed by the UHV technology company (USA) and discussed for the first time in this work., Comment: 8 pages, 6 figures. submitted to JINST
- Published
- 2019
131. Beam induced space-charge effects in Time Projection Chambers in low-energy nuclear physics experiments
- Author
-
Randhawa, J. S., Cortesi, M., Ayyad, Y., Mittig, W., Ahn, T., Bazin, D., Beceiro-Novo, S., Carpenter, L., Cook, K. J., Dasgupta, M., Henderson, S., Hinde, D. J., Kolata, J. J., Sammut, J., Santamaria, C., Watwood, N., and Yeck, A.
- Subjects
Physics - Instrumentation and Detectors ,Nuclear Experiment - Abstract
Tracking capabilities in Time Projection Chambers (TPCs) are strongly dictated by the homogeneity of the drift field. Ion back-flow in various gas detectors, mainly induced by the secondary ionization processes during amplification, has long been known as a source of drift field distortion. Here, we report on beam-induced space-charge effects from the primary ionization process in the drift region in low-energy nuclear physics experiment with Active Target Time Projection Chamber (AT-TPC). A qualitative explanation of the observed effects is provided using detailed electron transport simulations. As ion mobility is a crucial factor in the space-charge effects, the need for a careful optimization of gas properties is highlighted. The impact of track distortion on tracking algorithm performance is also discussed.
- Published
- 2019
- Full Text
- View/download PDF
132. Assessing the photometric redshift precision of the S-PLUS survey: the Stripe-82 as a test-case
- Author
-
Molino, A., Costa-Duarte, M. V., Sampedro, L., Herpich, F. R., Sodré Jr., L., de Oliveira, C. Mendes, Schoenell, W., Barbosa, C. E., Queiroz, C., Lima, E. V. R., Azanha, L., Muñoz-Elgueta, N., Ribeiro, T., Kanaan, A., Hernandez-Jimenez, J. A., Cortesi, A., Akras, S., de Oliveira, R. Lopes, Torres-Flores, S., Lima-Dias, C., Castellon, J. L. Nilo, Damke, G., Alvarez-Candal, A., Jiménez-Teja, Y., Coelho, P., Pereira, E., Montero-Dorta, A. D., Benítez, N., Gonçalves, T. S., Santana-Silva, L., Werner, S. V., Almeida, L. A., Lopes, P. A. A., Chies-Santos, A. L., Telles, E., de Souza, Thom, C., R., Gonçalves, D. R., de Souza, R. S., Makler, M., Placco, V. M., Nakazono, L. M. I., Saito, R. K., Overzier, R. A., and Abramo, L. R.
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
In this paper we present a thorough discussion about the photometric redshift (photo-z) performance of the Southern Photometric Local Universe Survey (S-PLUS). This survey combines a 7 narrow + 5 broad passband filter system, with a typical photometric-depth of r$\sim$21 AB. For this exercise, we utilize the Data Release 1 (DR1), corresponding to 336 deg$^{2}$ from the Stripe-82 region. We rely on the \texttt{BPZ2} code to compute our estimates, using a new library of SED models, which includes additional templates for quiescent galaxies. When compared to a spectroscopic redshift control sample of $\sim$100k galaxies, we find a precision of $\sigma_{z}<$0.8\%, $<$2.0\% or $<$3.0\% for galaxies with magnitudes r$<$17, $<$19 and $<$21, respectively. A precision of 0.6\% is attained for galaxies with the highest \texttt{Odds} values. These estimates have a negligible bias and a fraction of catastrophic outliers inferior to 1\%. We identify a redshift window (i.e., 0.26$
- Published
- 2019
- Full Text
- View/download PDF
133. The Southern Photometric Local Universe Survey (S-PLUS): improved SEDs, morphologies and redshifts with 12 optical filters
- Author
-
de Oliveira, C. Mendes, Ribeiro, T., Schoenell, W., Kanaan, A., Overzier, R. A., Molino, A., Sampedro, L., Coelho, P., Barbosa, C. E., Cortesi, A., Costa-Duarte, M. V., Herpich, F. R., Hernandez-Jimenez, J. A., Placco, V. M., Xavier, H. S., Abramo, L. R., Saito, R. K., Chies-Santos, A. L., Ederoclite, A., de Oliveira, R. Lopes, Gonçalves, D. R., Akras, S., Almeida, L. A., Almeida-Fernandes, F., Beers, T. C., Bonatto, C., Bonoli, S., Cypriano, E. S., de Lima, Erik V. R., de Souza, R. S., de Souza, G. Fabiano, Ferrari, F., Gonçalves, T. S., Gonzalez, A. H., Gutiérrez-Soto, L. A., Hartmann, E. A., Jaffe, Y., Kerber, L. O., Lima-Dias, C., Lopes, P. A. A., Menendez-Delmestre, K., Nakazono, L. M. I., Novais, P. M., Ortega-Minakata, R. A., Pereira, E. S., Perottoni, H. D., Queiroz, C., Reis, R. R. R., Santos, W. A., Santos-Silva, T., Santucci, R. M., Barbosa, C. L., Siffert, B. B., Sodré Jr., L., Torres-Flores, S., Westera, P., Whitten, D. D., Alcaniz, J. S., Alonso-García, Javier, Alencar, S., Alvarez-Candal, A., Amram, P., Azanha, L., Barbá, R. H., Bernardinelli, P. H., Fernandes, M. Borges, Branco, V., Brito-Silva, D., Buzzo, M. L., Caffer, J., Campillay, A., Cano, Z., Carvano, J. M., Castejon, M., Fernandes, R. Cid, Dantas, M. L. L., Daflon, S., Damke, G., de la Reza, R., de Azevedo, L. J. de Melo, De Paula, D. F., Diem, K. G., Donnerstein, R., Dors, O. L., Dupke, R., Eikenberry, S., Escudero, Carlos G., Faifer, Favio R., Farías, H., Fernandes, B., Fernandes, C., Fontes, S., Galarza, A., Hirata, N. S. T., Katena, L., Gregorio-Hetem, J., Hernández-Fernández, J. D., Izzo, L., Arancibia, M. Jaque, Jatenco-Pereira, V., Jiménez-Teja, Y., Kann, D. A., Krabbe, A. C., Labayru, C., Lazzaro, D., Neto, G. B. Lima, Lopes, Amanda R., Magalhães, R., Makler, M., de Menezes, R., Miralda-Escudé, J., Monteiro-Oliveira, R., Montero-Dorta, A. D., Muñoz-Elgueta, N., Nemmen, R. S., Castellón, J. L. Nilo, Oliveira, A. S., Ortíz, D., Pattaro, E., Pereira, C. B., Quint, B., Riguccini, L., Pinto, H. J. Rocha, Rodrigues, I., Roig, F., Rossi, S., Saha, Kanak, Santos, R., Müller, A. Schnorr, Sesto, Leandro A., Silva, R., Castelli, Analía V. Smith, Teixeira, Ramachrisna, Telles, E., de Souza, R. C. Thom, Thöne, C., Trevisan, M., Postigo, A. de Ugarte, Urrutia-Viscarra, F., Veiga, C. H., Vika, M., Vitorelli, A. Z., Werle, A., Werner, S. V., and Zaritsky, D.
- Subjects
Astrophysics - Astrophysics of Galaxies ,Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Solar and Stellar Astrophysics - Abstract
The Southern Photometric Local Universe Survey (S-PLUS) is imaging ~9300 deg^2 of the celestial sphere in twelve optical bands using a dedicated 0.8 m robotic telescope, the T80-South, at the Cerro Tololo Inter-American Observatory, Chile. The telescope is equipped with a 9.2k by 9.2k e2v detector with 10 um pixels, resulting in a field-of-view of 2 deg^2 with a plate scale of 0.55"/pixel. The survey consists of four main subfields, which include two non-contiguous fields at high Galactic latitudes (8000 deg^2 at |b| > 30 deg) and two areas of the Galactic plane and bulge (for an additional 1300 deg^2). S-PLUS uses the Javalambre 12-band magnitude system, which includes the 5 u, g, r, i, z broad-band filters and 7 narrow-band filters centered on prominent stellar spectral features: the Balmer jump/[OII], Ca H+K, H-delta, G-band, Mg b triplet, H-alpha, and the Ca triplet. S-PLUS delivers accurate photometric redshifts (delta_z/(1+z) = 0.02 or better) for galaxies with r < 20 AB mag and redshift < 0.5, thus producing a 3D map of the local Universe over a volume of more than 1 (Gpc/h)^3. The final S-PLUS catalogue will also enable the study of star formation and stellar populations in and around the Milky Way and nearby galaxies, as well as searches for quasars, variable sources, and low-metallicity stars. In this paper we introduce the main characteristics of the survey, illustrated with science verification data highlighting the unique capabilities of S-PLUS. We also present the first public data release of ~336 deg^2 of the Stripe-82 area, which is available at http://datalab.noao.edu/splus., Comment: Updated to reflect the published version (MNRAS, 489, 241). For a short introductory video of the S-PLUS project, see https://youtu.be/yc5kHrHU9Jk - The S-PLUS Data Release 1 is available at http://datalab.noao.edu/splus
- Published
- 2019
- Full Text
- View/download PDF
134. Direct observation of proton emission in 11Be
- Author
-
Ayyad, Y., Olaizola, B., Mittig, W., Potel, G., Zelevinsky, V., Horoi, M., Beceiro-Novo, S., Alcorta, M., Andreoiu, C., Ahn, T., Anholm, M., Atar, L., Babu, A., Bazin, D., Bernier, N., Bhattacharjee, S. S., Bowry, M., Caballero-Folch, R., Cortesi, M., Dalitz, C., Dunling, E., Garnsworthy, A. B., Holl, M., Kootte, B., Leach, K. G., Randhawa, J. S., Saito, Y., Santamaria, C., Šiuryte, P., Svensson, C. E., Umashankar, R., Watwood, N., and Yates, D.
- Subjects
Nuclear Experiment - Abstract
The elusive $\beta^-\text{p}^+$ decay was observed in $^{11}$Be by directly measuring the emitted protons and their energy distribution for the first time with the prototype Active Target Time Projection Chamber (pAT-TPC) in an experiment performed at ISAC-TRIUMF. The measured $\beta^-\text{p}^+$ branching ratio is orders of magnitude larger than any previous theoretical model predicted. This can be explained by the presence of a narrow resonance in $^{11}$B above the proton separation energy.
- Published
- 2019
- Full Text
- View/download PDF
135. GADGET: A Gas Amplifier Detector with Germanium Tagging
- Author
-
Friedman, Moshe, Pérez-Loureiro, David, Budner, Tamas, Pollacco, Emanuel, Wrede, Chris, Cortesi, Marco, Fry, Cathleen, Glassman, Brent, Harris, Madison, Heideman, Joe, Janasik, Molly, Roeder, Brian T, Roosa, Michael, Saastamoinen, Antti, Stomps, Jordan, Surbrook, Jason, Tiwari, Pranjal, and Yurkon, John
- Subjects
Physics - Instrumentation and Detectors ,Nuclear Experiment - Abstract
The Gas Amplifier Detector with Germanium Tagging (GADGET) is a new detection system devoted to the measurement of weak, low-energy $\beta$-delayed proton decays relevant for nuclear astrophysics studies. It is comprised of a new gaseous Proton Detector equipped with a Micromegas readout for charged particle detection, surrounded by the existing Segmented Germanium Array (SeGA) for the high-resolution detection of the prompt $\gamma$-rays. In this work we describe in detail for the first time the design, construction, and operation of the GADGET system, including performance of the Proton Detector. We present the results of a recent commissioning experiment performed with \textsuperscript{25}Si beam at the National Superconducting Cyclotron Laboratory (NSCL). GADGET provided low-background, low-energy $\beta$-delayed proton detection with efficiency above 95\%, and relatively good efficiency for proton-gamma coincidences (2.7\% at 1.37 MeV).
- Published
- 2019
- Full Text
- View/download PDF
136. First Direct Measurement of Mg22(α,p)Al25 and Implications for X-Ray Burst Model-Observation Comparisons
- Author
-
Randhawa, JS, Ayyad, Y, Mittig, W, Meisel, Z, Ahn, T, Aguilar, S, Alvarez-Pol, H, Bardayan, DW, Bazin, D, Beceiro-Novo, S, Blankstein, D, Carpenter, L, Cortesi, M, Cortina-Gil, D, Gastis, P, Hall, M, Henderson, S, Kolata, JJ, Mijatovic, T, Ndayisabye, F, O’Malley, P, Pereira, J, Pierre, A, Robert, H, Santamaria, C, Schatz, H, Smith, J, Watwood, N, and Zamora, JC
- Subjects
Nuclear and Plasma Physics ,Astronomical Sciences ,Synchrotrons and Accelerators ,Physical Sciences ,Mathematical Sciences ,Engineering ,General Physics ,Mathematical sciences ,Physical sciences - Abstract
Type-I x-ray bursts can reveal the properties of an accreting neutron star system when compared with astrophysics model calculations. However, model results are sensitive to a handful of uncertain nuclear reaction rates, such as ^{22}Mg(α,p). We report the first direct measurement of ^{22}Mg(α,p), performed with the Active Target Time Projection Chamber. The corresponding astrophysical reaction rate is orders of magnitude larger than determined from a previous indirect measurement in a broad temperature range. Our new measurement suggests a less-compact neutron star in the source GS1826-24.
- Published
- 2020
137. Overcoming presynaptic effects of VAMP2 mutations with 4-aminopyridine treatment.
- Author
-
Li, Haiyan, Alten, Baris, Santos, Magda, Jiang, Ruiji, Paul, Brianna, Lalani, Sanam, Cortesi, Audrey, Parks, Kendall, Khandelwal, Nitin, Smith-Packard, Bethany, Phoong, Malay, Chez, Michael, Fisher, Heather, Scheuerle, Angela, Shinawi, Marwan, Hussain, Shaun, Kavalali, Ege, Voglmaier, Susan, Sherr, Elliott, and Simmons, Roxanne
- Subjects
VAMP2 ,aminopyridine ,neurodevelopmental disorder ,synaptic transmission ,synaptic vesicle ,4-Aminopyridine ,Adult ,Electrophysiology ,Exocytosis ,Female ,Humans ,Male ,Mutation ,Synaptic Transmission ,Synaptic Vesicles ,Vesicle-Associated Membrane Protein 2 - Abstract
Clinical and genetic features of five unrelated patients with de novo pathogenic variants in the synaptic vesicle-associated membrane protein 2 (VAMP2) reveal common features of global developmental delay, autistic tendencies, behavioral disturbances, and a higher propensity to develop epilepsy. For one patient, a cognitively impaired adolescent with a de novo stop-gain VAMP2 mutation, we tested a potential treatment strategy, enhancing neurotransmission by prolonging action potentials with the aminopyridine family of potassium channel blockers, 4-aminopyridine and 3,4-diaminopyridine, in vitro and in vivo. Synaptic vesicle recycling and neurotransmission were assayed in neurons expressing three VAMP2 variants by live-cell imaging and electrophysiology. In cellular models, two variants decrease both the rate of exocytosis and the number of synaptic vesicles released from the recycling pool, compared with wild-type. Aminopyridine treatment increases the rate and extent of exocytosis and total synaptic charge transfer and desynchronizes GABA release. The clinical response of the patient to 2 years of off-label aminopyridine treatment includes improved emotional and behavioral regulation by parental report, and objective improvement in standardized cognitive measures. Aminopyridine treatment may extend to patients with pathogenic variants in VAMP2 and other genes influencing presynaptic function or GABAergic tone, and tested in vitro before treatment.
- Published
- 2020
138. First Direct Measurement of ^{22}Mg(α,p)^{25}Al and Implications for X-Ray Burst Model-Observation Comparisons.
- Author
-
Randhawa, JS, Ayyad, Y, Mittig, W, Meisel, Z, Ahn, T, Aguilar, S, Alvarez-Pol, H, Bardayan, DW, Bazin, D, Beceiro-Novo, S, Blankstein, D, Carpenter, L, Cortesi, M, Cortina-Gil, D, Gastis, P, Hall, M, Henderson, S, Kolata, JJ, Mijatovic, T, Ndayisabye, F, O'Malley, P, Pereira, J, Pierre, A, Robert, H, Santamaria, C, Schatz, H, Smith, J, Watwood, N, and Zamora, JC
- Subjects
General Physics ,Mathematical Sciences ,Physical Sciences ,Engineering - Abstract
Type-I x-ray bursts can reveal the properties of an accreting neutron star system when compared with astrophysics model calculations. However, model results are sensitive to a handful of uncertain nuclear reaction rates, such as ^{22}Mg(α,p). We report the first direct measurement of ^{22}Mg(α,p), performed with the Active Target Time Projection Chamber. The corresponding astrophysical reaction rate is orders of magnitude larger than determined from a previous indirect measurement in a broad temperature range. Our new measurement suggests a less-compact neutron star in the source GS1826-24.
- Published
- 2020
139. On the use of Infrared Atmospheric Sounding Interferometer (IASI) spectrally resolved radiances to test the EC-Earth climate model (v3.3.3) in clear-sky conditions
- Author
-
S. Della Fera, F. Fabiano, P. Raspollini, M. Ridolfi, U. Cortesi, F. Barbara, and J. von Hardenberg
- Subjects
Geology ,QE1-996.5 - Abstract
The long-term comparison between simulated and observed spectrally resolved outgoing longwave radiation (OLR) can represent a stringent test for the direct verification and improvement of general circulation models (GCMs), which are regularly tuned by adjusting parameters related to subgrid processes not explicitly represented in the model to constrain the integrated OLR energy fluxes to observed values. However, a good agreement between simulated and observed integrated OLR fluxes may be obtained from the cancellation of opposite-in-sign systematic errors localized in specific spectral ranges. Since the mid-2000s, stable hyperspectral observations of the mid-infrared region (667 to 2750 cm−1) of the Earth emission spectrum have been provided by different sensors (e.g. AIRS, IASI and CrIS). Furthermore, the FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) mission, selected to be the ninth ESA Earth Explorer, will measure, starting from 2027, the terrestrial radiation emitted to space at the top of the atmosphere (TOA) from 100 to 1600 cm−1, filling the observational gap in the far-infrared (FIR) region, from 100 to 667 cm−1. In this work, in anticipation of FORUM measurements, we compare Infrared Atmospheric Sounding Interferometer (IASI) Metop-A observations to radiances simulated on the basis of the atmospheric fields predicted by the EC-Earth Global Climate Model (version 3.3.3) in clear-sky conditions. To simulate spectra based on the atmospheric and surface state provided by the climate model, the radiative transfer model σ-IASI has been integrated in the Cloud Feedback Model Intercomparison Project (COSP) package. Therefore, online simulations, provided by the EC-Earth model equipped with the new COSP–σ-IASI module, have been performed in clear-sky conditions with prescribed sea surface temperature and sea ice concentration, every 6 h, over a time frame consistent with the availability of IASI data. Systematic comparisons between observed and simulated brightness temperature (BT) have been performed in 10 cm−1 spectral intervals, on a global scale over the ocean, with a specific focus on the latitudinal belt between 30∘ S and 30∘ N. The analysis has shown a warm BT bias of about 3.5 K in the core of the CO2 absorption band and a cold BT bias of approximately 1 K in the wing of the CO2 band, due to a positive temperature bias in the stratosphere and a negative temperature bias in the middle troposphere of the climate model, respectively. Finally, considering a warm BT bias in the rotational–vibrational water vapour band, we have highlighted a dry bias of the water vapour concentration in the upper troposphere of the model.
- Published
- 2023
- Full Text
- View/download PDF
140. Supercritical Carbon Dioxide Extraction of Lyophilized Aristotelia chilensis (Mol.) Stuntz Berries as Pre-treatment for Enhanced Anthocyanin Recovery
- Author
-
A. Cortesi, N. de Zordi, S. Dall’Acqua, A. Calabretti, and E. Neau
- Subjects
supercritical carbon dioxide extraction ,aristotelia chilensis (mol.) stuntz ,fatty acids ,anthocyanin ,central composite design ,Chemical engineering ,TP155-156 - Abstract
The supercritical carbon dioxide extraction of lyophilized berries of Aristotelia chilensis (Mol.) Stuntz was studied as possible pre-treatment for enhanced anthocyanin recovery. Effect of pressure, temperature, and process time on the extracted oil yields and on the anthocyanins recovery in the pre-treated fractions were considered. The operating parameters were optimized using the central composite design, and extractions were run in the pressure, temperature, and time ranges of 99.6 to 200.4 bar, 36.6 to 53.4 °C, and 0.7–2.3 h. The successive multiple regression analysis indicated pressure and time as major influencing parameters on the extraction yield. Those parameters induced no clear changes in the fatty acid composition of almost all the extracted oils, obtaining an average linoleic acid amount between 35–44 % weight in the lipophilic fractions. Standardized methanol extractions demonstrated the influence of the different conditions in the SCO2 pre-treatment processes, resulting in extracted anthocyanin increments ranging from 9 to 26 %.
- Published
- 2023
- Full Text
- View/download PDF
141. MINI UAV-BASED LITTER DETECTION ON RIVER BANKS
- Author
-
I. Cortesi, F. Mugnai, R. Angelini, and A. Masiero
- Subjects
Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Applied optics. Photonics ,TA1501-1820 - Abstract
Most of the anthropic pollution arriving to seas and oceans is carried by rivers, leading to a dramatic impact on the aquatic flora and fauna. Hence, several strategies have already been considered to reduce the use of plastic (and non biodegradable) objects, fostering recycling, detect litter in the environment, and catch it. This work aims at implementing a litter detection approach usable also in urban areas, hence considering a mini-UAV (Unmanned Aerial Vehicle) in order to reduce the issues related to flight restrictions. The implemented strategy exploits a high resolution map of the area of interest, a properly trained deep learning litter object detector, and a vision based localization system, which allows to remarkably reduce the positioning error of the UAV navigation system, in order to provide estimates of the litter object positions with an accuracy at decimeter level for objects not too far from locations recognizable in the map.
- Published
- 2023
- Full Text
- View/download PDF
142. PARP-inhibitors for BRCA1/2-related advanced HER2-negative breast cancer: A meta-analysis and GRADE recommendations by the Italian Association of Medical Oncology
- Author
-
Federica Miglietta, Michela Cinquini, Maria Vittoria Dieci, Laura Cortesi, Carmen Criscitiello, Filippo Montemurro, Lucia Del Mastro, Alberto Zambelli, Laura Biganzoli, Alessia Levaggi, Chiara Delle Piane, Caterina Marchiò, Massimo Calabrese, Lucio Fortunato, Pierfrancesco Franco, Bruno Meduri, Veronica Andrea Fittipaldo, and Stefania Gori
- Subjects
BRCA germline mutations ,Breast cancer ,HER2-negative ,PARP-Inhibitors ,GRADE methodology ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Background: Approximately 5–10% of unselected breast cancer (BC) patients retain a hereditary predisposition related to a germline mutation in BRCA1/2 genes. The poly-ADP ribose polymerase (PARP)-inhibitors olaparib and talazoparib have been granted marketing authorization by both FDA and EMA for adults with BRCA1/2 germline mutations and HER2-negative (HER2-) advanced BC based on the results from the phase III OlympiAd and EMBRACA trials. Methods: The panel of the Italian Association of Medical Oncology (AIOM) Clinical Practice Guidelines on Breast Cancer addressed two critical clinical questions, adopting the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach and the Evidence to Decision framework (EtD), to develop recommendations on the use of PARP-inhibitors, with respect to single-agent chemotherapy, in patients with BRCA-related triple-negative (clinical question 1) and hormone receptor-positive (HR+)/HER2- (clinical question 2) advanced BC. Results: Two studies were eligible (OlympiAd and EMBRACA). For both clinical questions, the Panel judged the benefit/harm balance probably in favor of the intervention, given the favorable impact in terms of PFS, ORR, and QoL at an acceptable cost in terms of toxicity; the overall certainty of the evidence was low. The panel's final recommendations were conditional in favor of PARP-inhibitors over single-agent chemotherapy in both HR+/HER2-and triple-negative BC. Finally, the Panel identified and discussed areas of uncertainty calling for further exploration. Conclusions: The Panel of AIOM BC Clinical Practice Guideline provided clinical recommendations on the use of PARP-inhibitors, with respect to single-agent chemotherapy, in patients with BRCA-related HER2-advanced BC by adopting the GRADE methodology.
- Published
- 2022
- Full Text
- View/download PDF
143. The psychosocial impact of haemophilia from patients’ and caregivers’ point of view: The results of an Italian survey
- Author
-
Fornari, A, Antonazzo, I, Rocino, A, Preti, D, Fragomeno, A, Cucuzza, F, Ceresi, N, Santoro, C, Ferretti, A, Facchetti, R, Cozzolino, P, Biasoli, C, Cassone, C, Coppola, A, Cortesi, P, Mantovani, L, Fornari A., Antonazzo I. C., Rocino A., Preti D., Fragomeno A., Cucuzza F., Ceresi N., Santoro C., Ferretti A., Facchetti R., Cozzolino P., Biasoli C., Cassone C., Coppola A., Cortesi P. A., Mantovani L. G., Fornari, A, Antonazzo, I, Rocino, A, Preti, D, Fragomeno, A, Cucuzza, F, Ceresi, N, Santoro, C, Ferretti, A, Facchetti, R, Cozzolino, P, Biasoli, C, Cassone, C, Coppola, A, Cortesi, P, Mantovani, L, Fornari A., Antonazzo I. C., Rocino A., Preti D., Fragomeno A., Cucuzza F., Ceresi N., Santoro C., Ferretti A., Facchetti R., Cozzolino P., Biasoli C., Cassone C., Coppola A., Cortesi P. A., and Mantovani L. G.
- Abstract
Backgroud: A huge amount of data about psychosocial issues of people with haemophilia (PwH) are available; however, these materials are fragmentary and largely outdated, failing to reflect the impact of current treatment strategies. Aim: Describing the influence of illness on psychosocial aspects of adult PwH (≥18 years) and caregivers of children with haemophilia (CPwH) without inhibitors, in Italy. Methods: Surveys (for adult PwH, CPwH and haemophilia specialists) were developed by a multidisciplinary working group and conducted from November 2019 to June 2020. Results: A total of 120 PwH without inhibitors and 79 CPwH completed the survey. Adult patients reported a significant impairment in many psychosocial aspects, including working activities, relations with family members and social relations. Caregivers generally reported better scores in all aspects of the survey. Mobility, Pain and Mental health domains of EQ-5D were the most frequently impaired in both patients and caregivers, reducing the perceived quality of life. Genetic counselling was an important issue, 53% of CPwH declaring unawareness of their carrier status, as well as the psychological support offered by the reference center, 67.0% of respondents reporting that no psychological support was provided at the time of diagnosis communication. Conclusion: This study provides information about PwH's and CPwH's point of view in the current scenario of continuous innovations in haemophilia treatment and management furthermore, updated insights on psychosocial problems faced by patients and caregivers are reported.
- Published
- 2024
144. Personalized Prophylaxis with myPKFiTCE: A Real-World Cost-Effectiveness Analysis in Haemophilia A Patients
- Author
-
Antonazzo, I, Cortesi, P, Zanon, E, Pasca, S, Morfini, M, Santoro, C, De Cristofaro, R, Di Minno, G, Cozzolino, P, Mantovani, L, Antonazzo I. C., Cortesi P. A., Zanon E., Pasca S., Morfini M., Santoro C., De Cristofaro R., Di Minno G., Cozzolino P., Mantovani L. G., Antonazzo, I, Cortesi, P, Zanon, E, Pasca, S, Morfini, M, Santoro, C, De Cristofaro, R, Di Minno, G, Cozzolino, P, Mantovani, L, Antonazzo I. C., Cortesi P. A., Zanon E., Pasca S., Morfini M., Santoro C., De Cristofaro R., Di Minno G., Cozzolino P., and Mantovani L. G.
- Abstract
Background and Objectives: This study aimed to assess the effectiveness and costs associated with pharmacokinetics-driven (PK) prophylaxis based on the myPKFiT® device in patients affected by hemophilia A (HA) in Italy. Materials and Methods: An observational retrospective study was conducted in three Italian hemophilia centers. All patients with moderate or severe HA, aged ≥ 18 years, capable of having PK estimated using the myPKFiT device, and who had had a clinical visit between 1 November 2019 and 31 March 2022 were included. Differences in clinical, treatment, health resources, and cost data were assessed comparing post-PK prophylaxis with pre-PK. The incremental cost-effectiveness ratio (ICER) was estimated as cost (EUR) per bleed avoided. Results: The study enrolled 13 patients with HA. The mean annual bleeding rate decreased by −1.45 (−63.80%, p = 0.0055) after the use of myPKFiT®. Overall, the consumption of FVIII IU increased by 1.73% during follow-up compared to the period prior the use of the myPKFiT. Prophylaxis based on the myPKFiT resulted in an ICER of EUR 5099.89 per bleed avoided. Conclusions: The results of our study support the idea that the use of PK data in clinical practice can be associated with an improvement in the management of patients, as well as clinical outcomes, with a reasonable increase in costs.
- Published
- 2024
145. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
- Author
-
Steinmetz, J, Seeher, K, Schiess, N, Nichols, E, Cao, B, Servili, C, Cavallera, V, Cousin, E, Hagins, H, Moberg, M, Mehlman, M, Abate, Y, Abbas, J, Abbasi, M, Abbasian, M, Abbastabar, H, Abdelmasseh, M, Abdollahi, M, Abdollahifar, M, Abd-Rabu, R, Abdulah, D, Abdullahi, A, Abedi, A, Abedi, V, Abeldano Zuniga, R, Abidi, H, Abiodun, O, Aboagye, R, Abolhassani, H, Aboyans, V, Abrha, W, Abualhasan, A, Abu-Gharbieh, E, Aburuz, S, Adamu, L, Addo, I, Adebayo, O, Adekanmbi, V, Adekiya, T, Adikusuma, W, Adnani, Q, Adra, S, Afework, T, Afolabi, A, Afraz, A, Afzal, S, Aghamiri, S, Agodi, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, S, Ahmadzade, A, Ahmed, A, Ahmed, H, Ahmed, J, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Aji, B, Ajumobi, O, Akade, S, Akbari, M, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemi, R, Akonde, M, Al Hasan, S, Alahdab, F, Al-Ahdal, T, Al-Amer, R, Albashtawy, M, Albataineh, M, Aldawsari, K, Alemi, H, Alemi, S, Algammal, A, Al-Gheethi, A, Alhalaiqa, F, Alhassan, R, Ali, A, Ali, E, Ali, L, Ali, M, Ali, R, Ali, S, Shujait Ali, S, Ali, Z, Alif, S, Alimohamadi, Y, Aliyi, A, Aljofan, M, Aljunid, S, Alladi, S, Almazan, J, Almustanyir, S, Al-Omari, B, Alqahtani, J, Alqasmi, I, Alqutaibi, A, Al-Shahi Salman, R, Altaany, Z, Al-Tawfiq, J, Altirkawi, K, Alvis-Guzman, N, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Amani, R, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, M, Amu, H, Amugsi, D, Amusa, G, Amzat, J, Ancuceanu, R, Anderlini, D, Anderson, D, Andrei, C, Androudi, S, Angappan, D, Angesom, T, Anil, A, Ansari-Moghaddam, A, Anwer, R, Arafat, M, Aravkin, A, Areda, D, Ariffin, H, Arifin, H, Arkew, M, Arnlov, J, Arooj, M, Artamonov, A, Artanti, K, Aruleba, R, Asadi-Pooya, A, Asena, T, Asghari-Jafarabadi, M, Ashraf, M, Ashraf, T, Atalell, K, Athari, S, Atinafu, B, Atorkey, P, Atout, M, Atreya, A, Aujayeb, A, Avan, A, Ayala Quintanilla, B, Ayatollahi, H, Ayinde, O, Mohammad Ayyoubzadeh, S, Azadnajafabad, S, Azizi, Z, Azizian, K, Azzam, A, Babaei, M, Badar, M, Badiye, A, Baghdadi, S, Bagherieh, S, Bai, R, Baig, A, Balakrishnan, S, Balalla, S, Baltatu, O, Banach, M, Bandyopadhyay, S, Banerjee, I, Baran, M, Barboza, M, Barchitta, M, Bardhan, M, Barker-Collo, S, Barnighausen, T, Barrow, A, Bashash, D, Bashiri, H, Bashiru, H, Basiru, A, Basso, J, Basu, S, Batiha, A, Batra, K, Baune, B, Bedi, N, Begde, A, Begum, T, Behnam, B, Behnoush, A, Beiranvand, M, Bejot, Y, Bekele, A, Belete, M, Belgaumi, U, Bemanalizadeh, M, Bender, R, Benfor, B, Bennett, D, Bensenor, I, Berice, B, Bettencourt, P, Beyene, K, Bhadra, A, Bhagat, D, Bhangdia, K, Bhardwaj, N, Bhardwaj, P, Bhargava, A, Bhaskar, S, Bhat, A, Bhat, V, Bhatti, G, Bhatti, J, Bhatti, R, Bijani, A, Bikbov, B, Bilalaga, M, Biswas, A, Bitaraf, S, Bitra, V, Bjorge, T, Bodolica, V, Bodunrin, A, Boloor, A, Braithwaite, D, Brayne, C, Brenner, H, Briko, A, Bringas Vega, M, Brown, J, Budke, C, Buonsenso, D, Burkart, K, Burns, R, Bustanji, Y, Butt, M, Butt, N, Butt, Z, Cabral, L, dos Santos, F, Calina, D, Campos-Nonato, I, Cao, C, Carabin, H, Cardenas, R, Carreras, G, Carvalho, A, Castaneda-Orjuela, C, Casulli, A, Catala-Lopez, F, Catapano, A, Caye, A, Cegolon, L, Cenderadewi, M, Cerin, E, Chacon-Uscamaita, P, Chan, J, Chanie, G, Charan, J, Chattu, V, Chekol Abebe, E, Chen, H, Chen, J, Chi, G, Chichagi, F, Chidambaram, S, Chimoriya, R, Ching, P, Chitheer, A, Chong, Y, Chopra, H, Choudhari, S, Chowdhury, E, Chowdhury, R, Christensen, H, Chu, D, Chukwu, I, Chung, E, Coberly, K, Columbus, A, Comachio, J, Conde, J, Cortesi, P, Costa, V, Couto, R, Criqui, M, Cruz-Martins, N, Dabbagh Ohadi, M, Dadana, S, Dadras, O, Dai, X, Dai, Z, D'Amico, E, Danawi, H, Dandona, L, Dandona, R, Darwish, A, Das, S, Dascalu, A, Dash, N, Dashti, M, De la Hoz, F, de la Torre-Luque, A, De Leo, D, Dean, F, Dehghan, A, Dejene, H, Demant, D, Demetriades, A, Demissie, S, Deng, X, Desai, H, Devanbu, V, Dhama, K, Dharmaratne, S, Dhimal, M, Dias da Silva, D, Diaz, D, Dibas, M, Ding, D, Dinu, M, Dirac, M, Diress, M, Do, T, Doan, K, Dodangeh, M, Doheim, M, Dokova, K, Dongarwar, D, Dsouza, H, Dube, J, Duraisamy, S, Durojaiye, O, Dutta, S, Dziedzic, A, Edinur, H, Eissazade, N, Ekholuenetale, M, Ekundayo, T, El Nahas, N, El Sayed, I, Elahi Najafi, M, Elbarazi, I, Elemam, N, Elgar, F, Elgendy, I, Elhabashy, H, Elhadi, M, Elilo, L, Ellenbogen, R, Elmeligy, O, Elmonem, M, Elshaer, M, Elsohaby, I, Emamverdi, M, Emeto, T, Endres, M, Esezobor, C, Eskandarieh, S, Fadaei, A, Fagbamigbe, A, Fahim, A, Faramarzi, A, Fares, J, Farjoud Kouhanjani, M, Faro, A, Farzadfar, F, Fatehizadeh, A, Fathi, M, Fathi, S, Fatima, S, Feizkhah, A, Fereshtehnejad, S, Ferrari, A, Ferreira, N, Fetensa, G, Firouraghi, N, Fischer, F, Fonseca, A, Force, L, Fornari, A, Foroutan, B, Fukumoto, T, Gadanya, M, Gaidhane, A, Galali, Y, Galehdar, N, Gan, Q, Gandhi, A, Ganesan, B, Gardner, W, Garg, N, Gau, S, Gautam, R, Gebre, T, Gebrehiwot, M, Gebremeskel, G, Gebreslassie, H, Getacher, L, Ghaderi Yazdi, B, Ghadirian, F, Ghaffarpasand, F, Ghanbari, R, Ghasemi, M, Ghazy, R, Ghimire, S, Gholami, A, Gholamrezanezhad, A, Ghotbi, E, Ghozy, S, Gialluisi, A, Gill, P, Glasstetter, L, Gnedovskaya, E, Golchin, A, Golechha, M, Goleij, P, Golinelli, D, Gomes-Neto, M, Goulart, A, Goyal, A, Gray, R, Grivna, M, Guadie, H, Guan, B, Guarducci, G, Guicciardi, S, Gunawardane, D, Guo, H, Gupta, B, Gupta, R, Gupta, S, Gupta, V, Gutierrez, R, Habibzadeh, F, Hachinski, V, Haddadi, R, Hadei, M, Hadi, N, Haep, N, Haile, T, Haj-Mirzaian, A, Hall, B, Halwani, R, Hameed, S, Hamiduzzaman, M, Hammoud, A, Han, H, Hanifi, N, Hankey, G, Hannan, M, Hao, J, Harapan, H, Hareru, H, Hargono, A, Harlianto, N, Haro, J, Hartman, N, Hasaballah, A, Hasan, F, Hasani, H, Hasanian, M, Hassan, A, Hassan, S, Hassanipour, S, Hassankhani, H, Hassen, M, Haubold, J, Hay, S, Hayat, K, Hegazy, M, Heidari, G, Heidari, M, Heidari-Soureshjani, R, Hesami, H, Hezam, K, Hiraike, Y, Hoffman, H, Holla, R, Hopf, K, Horita, N, Hossain, M, Hossain, S, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, S, Hu, C, Huang, J, Huda, M, Hussain, J, Hussein, N, Huynh, H, Hwang, B, Ibitoye, S, Ilaghi, M, Ilesanmi, O, Ilic, I, Ilic, M, Immurana, M, Iravanpour, F, Islam, S, Ismail, F, Iso, H, Isola, G, Iwagami, M, Iwu, C, Iyer, M, Jaan, A, Jacob, L, Jadidi-Niaragh, F, Jafari, M, Jafarinia, M, Jafarzadeh, A, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jaiswal, A, Jakovljevic, M, Jamora, R, Jana, S, Javadi, N, Javed, S, Javeed, S, Jayapal, S, Jayaram, S, Jiang, H, Johnson, C, Johnson, W, Jokar, M, Jonas, J, Joseph, A, Joseph, N, Joshua, C, Jurisson, M, Kabir, A, Kabir, Z, Kabito, G, Kadashetti, V, Kafi, F, Kalani, R, Kalantar, F, Kaliyadan, F, Kamath, A, Kamath, S, Kanchan, T, Kandel, A, Kandel, H, Kanmodi, K, Karajizadeh, M, Karami, J, Karanth, S, Karaye, I, Karch, A, Karimi, A, Karimi, H, Karimi Behnagh, A, Kasraei, H, Kassebaum, N, Kauppila, J, Kaur, H, Kaur, N, Kayode, G, Kazemi, F, Keikavoosi-Arani, L, Keller, C, Keykhaei, M, Khadembashiri, M, Khader, Y, Khafaie, M, Khajuria, H, Khalaji, A, Khamesipour, F, Khammarnia, M, Khan, M, Khan, Y, Suheb, M, Khanmohammadi, S, Khanna, T, Khatab, K, Khatatbeh, H, Khatatbeh, M, Khateri, S, Khatib, M, Khayat Kashani, H, Khonji, M, Khorashadizadeh, F, Khormali, M, Khubchandani, J, Kian, S, Kim, G, Kim, J, Kim, M, Kim, Y, Kimokoti, R, Kisa, A, Kisa, S, Kivimaki, M, Kochhar, S, Kolahi, A, Koly, K, Kompani, F, Koroshetz, W, Kosen, S, Kourosh Arami, M, Koyanagi, A, Kravchenko, M, Krishan, K, Krishnamoorthy, V, Defo, B, Kuddus, M, Kumar, A, Kumar, G, Kumar, M, Kumar, N, Kumsa, N, Kundu, S, Kurniasari, M, Kusuma, D, Kuttikkattu, A, Kyu, H, La Vecchia, C, Ladan, M, Lahariya, C, Laksono, T, Lal, D, Lallukka, T, Lam, J, Lami, F, Landires, I, Langguth, B, Lasrado, S, Latief, K, Latifinaibin, K, Lau, K, Laurens, M, Lawal, B, Le, L, Le, T, Ledda, C, Lee, M, Lee, S, Lee, W, Lee, Y, Leonardi, M, Lerango, T, Li, M, Li, W, Ligade, V, Lim, S, Linehan, C, Liu, C, Liu, J, Liu, W, Lo, C, Lo, W, Lobo, S, Logroscino, G, Lopes, G, Lopukhov, P, Lorenzovici, L, Lorkowski, S, Loureiro, J, Lubinda, J, Lucchetti, G, Saute, R, Ma, Z, Mabrok, M, Machoy, M, Madadizadeh, F, El Razek, M, Maghazachi, A, Maghbouli, N, Mahjoub, S, Mahmoudi, M, Majeed, A, Malagon-Rojas, J, Malakan Rad, E, Malhotra, K, Malik, A, Malik, I, Mallhi, T, Malta, D, Manilal, A, Mansouri, V, Mansournia, M, Marasini, B, Marateb, H, Maroufi, S, Martinez-Raga, J, Martini, S, Martins-Melo, F, Martorell, M, Marz, W, Marzo, R, Massano, J, Mathangasinghe, Y, Mathews, E, Maude, R, Maugeri, A, Maulik, P, Mayeli, M, Mazaheri, M, Mcalinden, C, Mcgrath, J, Meena, J, Mehndiratta, M, Mendez-Lopez, M, Mendoza, W, Mendoza-Cano, O, Menezes, R, Merati, M, Meretoja, A, Merkin, A, Mersha, A, Mestrovic, T, Mi, T, Miazgowski, T, Michalek, I, Mihretie, E, Minh, L, Mirfakhraie, R, Mirica, A, Mirrakhimov, E, Mirzaei, M, Misganaw, A, Misra, S, Mithra, P, Mizana, B, Mohamadkhani, A, Mohamed, N, Mohammadi, E, Mohammadi, H, Mohammadi, S, Mohammadshahi, M, Mohammed, M, Mohammed, S, Mohan, S, Mojiri-Forushani, H, Moka, N, Mokdad, A, Molinaro, S, Moller, H, Monasta, L, Moniruzzaman, M, Montazeri, F, Moradi, M, Moradi, Y, Moradi-Lakeh, M, Moraga, P, Morovatdar, N, Morrison, S, Mosapour, A, Mosser, J, Mossialos, E, Motaghinejad, M, Mousavi, P, Ehsan Mousavi, S, Mubarik, S, Muccioli, L, Mughal, F, Mukoro, G, Mulita, A, Mulita, F, Musaigwa, F, Mustafa, A, Mustafa, G, Muthu, S, Nagarajan, A, Naghavi, P, Naik, G, Nainu, F, Nair, T, Najmuldeen, H, Nakhostin Ansari, N, Nambi, G, Namdar Areshtanab, H, Nargus, S, Nascimento, B, Naser, A, Nashwan, A, Nasoori, H, Nasreldein, A, Natto, Z, Nauman, J, Nayak, B, Nazri-Panjaki, A, Negaresh, M, Negash, H, Negoi, I, Negoi, R, Negru, S, Nejadghaderi, S, Nematollahi, M, Nesbit, O, Newton, C, Nguyen, D, Nguyen, H, Nguyen, N, Nguyen, P, Nguyen, V, Niazi, R, Nikolouzakis, T, Niranjan, V, Nnyanzi, L, Noman, E, Noroozi, N, Norrving, B, Noubiap, J, Nri-Ezedi, C, Ntaios, G, Nunez-Samudio, V, Nurrika, D, Oancea, B, Odetokun, I, O'Donnell, M, Ogunsakin, R, Oguta, J, Oh, I, Okati-Aliabad, H, Okeke, S, Okekunle, A, Okonji, O, Okwute, P, Olagunju, A, Olaiya, M, Olana, M, Olatubi, M, Oliveira, G, Olufadewa, I, Olusanya, B, Bali, A, Ong, S, Onwujekwe, O, Ordak, M, Orji, A, Ortega-Altamirano, D, Osuagwu, U, Otstavnov, N, Otstavnov, S, Ouyahia, A, Owolabi, M, Mahesh Padukudru, P, Pacheco-Barrios, K, Padubidri, J, Pal, P, Palange, P, Palladino, C, Palladino, R, Palma-Alvarez, R, Pan, F, Panagiotakos, D, Panda-Jonas, S, Pandey, A, Pandian, J, Pangaribuan, H, Pantazopoulos, I, Pardhan, S, Parija, P, Parikh, R, Park, S, Parthasarathi, A, Pashaei, A, Patel, J, Patil, S, Patoulias, D, Pawar, S, Pedersini, P, Pensato, U, Pereira, D, Pereira, J, Pereira, M, Peres, M, Perico, N, Perna, S, Petcu, I, Petermann-Rocha, F, Pham, H, Phillips, M, Pinilla-Monsalve, G, Piradov, M, Plotnikov, E, Poddighe, D, Polat, B, Poluru, R, Pond, C, Poudel, G, Pouramini, A, Pourbagher-Shahri, A, Pourfridoni, M, Pourtaheri, N, Prakash, P, Prakash, S, Prakash, V, Prates, E, Pritchett, N, Purnobasuki, H, Qasim, N, Qattea, I, Qian, G, Radhakrishnan, V, Raee, P, Shahraki, H, Rafique, I, Raggi, A, Raghav, P, Rahati, M, Rahim, F, Rahimi, Z, Rahimifard, M, Rahman, M, Rahmani, A, Rahmani, S, Youshanlouei, H, Rahmati, M, Raj Moolambally, S, Rajabpour-Sanati, A, Ramadan, H, Ramasamy, S, Ramasubramani, P, Ramazanu, S, Rancic, N, Rao, I, Rao, S, Rapaka, D, Rashedi, V, Rashid, A, Rashidi, M, Rashidi Alavijeh, M, Rasouli-Saravani, A, Rawaf, S, Razo, C, Redwan, E, Bana, A, Remuzzi, G, Rezaei, N, Rezaeian, M, Rhee, T, Riad, A, Robinson, S, Rodrigues, M, Rodriguez, J, Roever, L, Rogowski, E, Romoli, M, Ronfani, L, Roy, P, Pramanik, K, Rubagotti, E, Ruiz, M, Russ, T, Sunnerhagen, K, Saad, A, Saadatian, Z, Saber, K, Saberikamarposhti, M, Sacco, S, Saddik, B, Sadeghi, E, Sadeghian, S, Saeed, U, Safdarian, M, Safi, S, Sagar, R, Sagoe, D, Saheb Sharif-Askari, F, Saheb Sharif-Askari, N, Sahebkar, A, Sahoo, S, Sahraian, M, Sajedi, S, Sakshaug, J, Saleh, M, Salehi Omran, H, Salem, M, Salimi, S, Samadi Kafil, H, Samadzadeh, S, Samargandy, S, Samodra, Y, Samuel, V, Samy, A, Sanadgol, N, Sanjeev, R, Sanmarchi, F, Santomauro, D, Santri, I, Santric-Milicevic, M, Saravanan, A, Sarveazad, A, Satpathy, M, Saylan, M, Sayyah, M, Scarmeas, N, Schlaich, M, Schuermans, A, Schwarzinger, M, Schwebel, D, Selvaraj, S, Sendekie, A, Sengupta, P, Senthilkumaran, S, Serban, D, Sergindo, M, Sethi, Y, Seyedalinaghi, S, Seylani, A, Shabani, M, Shabany, M, Shafie, M, Shahabi, S, Shahbandi, A, Shahid, S, Shahraki-Sanavi, F, Shahsavari, H, Shahwan, M, Shaikh, M, Shaji, K, Sham, S, Shama, A, Shamim, M, Shams-Beyranvand, M, Shamsi, M, Shanawaz, M, Sharath, M, Sharfaei, S, Sharifan, A, Sharma, M, Sharma, R, Shashamo, B, Shayan, M, Sheikhi, R, Shekhar, S, Shen, J, Shenoy, S, Shetty, P, Shiferaw, D, Shigematsu, M, Shiri, R, Shittu, A, Shivakumar, K, Shokri, F, Shool, S, Shorofi, S, Shrestha, S, Siankam Tankwanchi, A, Siddig, E, Sigfusdottir, I, Silva, J, Silva, L, Sinaei, E, Singh, B, Singh, G, Singh, P, Singh, S, Sirota, S, Sivakumar, S, Sohag, A, Solanki, R, Soleimani, H, Solikhah, S, Solomon, Y, Song, S, Song, Y, Sotoudeh, H, Spartalis, M, Stark, B, Starnes, J, Starodubova, A, Stein, D, Steiner, T, Stovner, L, Suleman, M, Abdulkader, R, Sultana, A, Sun, J, Sunkersing, D, Sunny, A, Susianti, H, Swain, C, Szeto, M, Tabares-Seisdedos, R, Tabatabaei, S, Tabatabai, S, Tabish, M, Taheri, M, Tahvildari, A, Tajbakhsh, A, Tampa, M, Lukenze Tamuzi, J, Tan, K, Tang, H, Tareke, M, Tarigan, I, Tat, N, Tat, V, Tavakoli Oliaee, R, Tavangar, S, Tavasol, A, Tefera, Y, Tehrani-Banihashemi, A, Temesgen, W, Temsah, M, Teramoto, M, Tesfaye, A, Tesfaye, E, Tesler, R, Thakali, O, Thangaraju, P, Thapa, R, Thapar, R, Thomas, N, Thrift, A, Ticoalu, J, Tillawi, T, Toghroli, R, Tonelli, M, Tovani-Palone, M, Traini, E, Tran, N, Van Tran, P, Tromans, S, Truelsen, T, Truyen, T, Tsatsakis, A, Tsegay, G, Tsermpini, E, Tualeka, A, Tufa, D, Ubah, C, Udoakang, A, Ulhaq, I, Umair, M, Umakanthan, S, Umapathi, K, Unim, B, Unnikrishnan, B, Vaithinathan, A, Vakilian, A, Tahbaz, S, Valizadeh, R, Van den Eynde, J, Vart, P, Varthya, S, Vasankari, T, Vaziri, S, Vellingiri, B, Venketasubramanian, N, Verras, G, Vervoort, D, Villafane, J, Villani, L, Veloz, A, Viskadourou, M, Vladimirov, S, Vlassov, V, Volovat, S, Vu, L, Vujcic, I, Wagaye, B, Waheed, Y, Wahood, W, Walde, M, Wang, F, Wang, S, Wang, Y, Waqas, M, Waris, A, Weerakoon, K, Weintraub, R, Weldemariam, A, Westerman, R, Whisnant, J, Wickramasinghe, D, Wickramasinghe, N, Willekens, B, Wilner, L, Winkler, A, Wolfe, C, Wu, A, Wulf Hanson, S, Xu, S, Xu, X, Yadollahpour, A, Yaghoubi, S, Yahya, G, Yamagishi, K, Yang, L, Yano, Y, Yao, Y, Yehualashet, S, Yeshaneh, A, Yesiltepe, M, Yi, S, Yigit, A, Yigit, V, Yon, D, Yonemoto, N, You, Y, Younis, M, Yu, C, Yusuf, H, Zadey, S, Zahedi, M, Zakham, F, Zaki, N, Zali, A, Zamagni, G, Zand, R, Zandieh, G, Zangiabadian, M, Zarghami, A, Zastrozhin, M, Zeariya, M, Zegeye, Z, Zeukeng, F, Zhai, C, Zhang, C, Zhang, H, Zhang, Y, Zhang, Z, Zhao, H, Zhao, Y, Zheng, P, Zhou, H, Zhu, B, Zhumagaliuly, A, Zielinska, M, Zikarg, Y, Zoladl, M, Murray, C, Ong, K, Feigin, V, Vos, T, Dua, T, Steinmetz J. D., Seeher K. M., Schiess N., Nichols E., Cao B., Servili C., Cavallera V., Cousin E., Hagins H., Moberg M. E., Mehlman M. L., Abate Y. H., Abbas J., Abbasi M. A., Abbasian M., Abbastabar H., Abdelmasseh M., Abdollahi M., Abdollahifar M. -A., Abd-Rabu R., Abdulah D. M., Abdullahi A., Abedi A., Abedi V., Abeldano Zuniga R. A., Abidi H., Abiodun O., Aboagye R. G., Abolhassani H., Aboyans V., Abrha W. A., Abualhasan A., Abu-Gharbieh E., Aburuz S., Adamu L. H., Addo I. Y., Adebayo O. M., Adekanmbi V., Adekiya T. A., Adikusuma W., Adnani Q. E. S., Adra S., Afework T., Afolabi A. A., Afraz A., Afzal S., Aghamiri S., Agodi A., Agyemang-Duah W., Ahinkorah B. O., Ahmad A., Ahmad D., Ahmad S., Ahmadzade A. M., Ahmed A., Ahmed H., Ahmed J. Q., Ahmed L. A., Ahmed M. B., Ahmed S. A., Ajami M., Aji B., Ajumobi O., Akade S., Akbari M., Akbarialiabad H., Akhlaghi S., Akinosoglou K., Akinyemi R. O., Akonde M., Al Hasan S. M., Alahdab F., Al-Ahdal T. M. A., Al-Amer R. M., Albashtawy M., AlBataineh M. T., Aldawsari K. A., Alemi H., Alemi S., Algammal A. M., Al-Gheethi A. A. S., Alhalaiqa F. A. N., Alhassan R. K., Ali A., Ali E. A., Ali L., Ali M. U., Ali M. M., Ali R., Ali S., Shujait Ali S. S., Ali Z., Alif S. M., Alimohamadi Y., Aliyi A. A., Aljofan M., Aljunid S. M., Alladi S., Almazan J. U., Almustanyir S., Al-Omari B., Alqahtani J. S., Alqasmi I., Alqutaibi A. Y., Al-Shahi Salman R., Altaany Z., Al-Tawfiq J. A., Altirkawi K. A., Alvis-Guzman N., Al-Worafi Y. M., Aly H., Aly S., Alzoubi K. H., Amani R., Amindarolzarbi A., Amiri S., Amirzade-Iranaq M. H., Amu H., Amugsi D. A., Amusa G. A., Amzat J., Ancuceanu R., Anderlini D., Anderson D. B., Andrei C. L., Androudi S., Angappan D., Angesom T. W., Anil A., Ansari-Moghaddam A., Anwer R., Arafat M., Aravkin A. Y., Areda D., Ariffin H., Arifin H., Arkew M., Arnlov J., Arooj M., Artamonov A. A., Artanti K. D., Aruleba R. T., Asadi-Pooya A. A., Asena T. F., Asghari-Jafarabadi M., Ashraf M., Ashraf T., Atalell K. A., Athari S. S., Atinafu B. T. T., Atorkey P., Atout M. M. W., Atreya A., Aujayeb A., Avan A., Ayala Quintanilla B. P. A., Ayatollahi H., Ayinde O. O., Mohammad Ayyoubzadeh S., Azadnajafabad S., Azizi Z., Azizian K., Azzam A. Y., Babaei M., Badar M., Badiye A. D., Baghdadi S., Bagherieh S., Bai R., Baig A. A., Balakrishnan S., Balalla S., Baltatu O. C., Banach M., Bandyopadhyay S., Banerjee I., Baran M. F., Barboza M. A., Barchitta M., Bardhan M., Barker-Collo S. L., Barnighausen T. W., Barrow A., Bashash D., Bashiri H., Bashiru H. A., Basiru A., Basso J., Basu S., Batiha A. M. M., Batra K., Baune B. T., Bedi N., Begde A., Begum T., Behnam B., Behnoush A. H., Beiranvand M., Bejot Y., Bekele A., Belete M. A., Belgaumi U. I., Bemanalizadeh M., Bender R. G., Benfor B., Bennett D. A., Bensenor I. M., Berice B., Bettencourt P. J. G., Beyene K. A., Bhadra A., Bhagat D. S., Bhangdia K., Bhardwaj N., Bhardwaj P., Bhargava A., Bhaskar S., Bhat A. N., Bhat V., Bhatti G. K., Bhatti J. S., Bhatti R., Bijani A., Bikbov B., Bilalaga M. M., Biswas A., Bitaraf S., Bitra V. R., Bjorge T., Bodolica V., Bodunrin A. O., Boloor A., Braithwaite D., Brayne C., Brenner H., Briko A., Bringas Vega M. L., Brown J., Budke C. M., Buonsenso D., Burkart K., Burns R. A., Bustanji Y., Butt M. H., Butt N. S., Butt Z. A., Cabral L. S., dos Santos F. L. C., Calina D., Campos-Nonato I. R., Cao C., Carabin H., Cardenas R., Carreras G., Carvalho A. F., Castaneda-Orjuela C. A., Casulli A., Catala-Lopez F., Catapano A. L., Caye A., Cegolon L., Cenderadewi M., Cerin E., Chacon-Uscamaita P. R. U., Chan J. S. K., Chanie G. S., Charan J., Chattu V. K., Chekol Abebe E., Chen H., Chen J., Chi G., Chichagi F., Chidambaram S. B., Chimoriya R., Ching P. R., Chitheer A., Chong Y. Y., Chopra H., Choudhari S. G., Chowdhury E. K., Chowdhury R., Christensen H., Chu D. -T., Chukwu I. S., Chung E., Coberly K., Columbus A., Comachio J., Conde J., Cortesi P. A., Costa V. M., Couto R. A. S., Criqui M. H., Cruz-Martins N., Dabbagh Ohadi M. A., Dadana S., Dadras O., Dai X., Dai Z., D'Amico E., Danawi H. A., Dandona L., Dandona R., Darwish A. H., Das S., Dascalu A. M., Dash N. R., Dashti M., De la Hoz F. P., de la Torre-Luque A., De Leo D., Dean F. E., Dehghan A., Dejene H., Demant D., Demetriades A. K., Demissie S., Deng X., Desai H. D., Devanbu V. G. C., Dhama K., Dharmaratne S. D., Dhimal M., Dias da Silva D., Diaz D., Dibas M., Ding D. D., Dinu M., Dirac M. A., Diress M., Do T. C., Do T. H. P., Doan K. D. K., Dodangeh M., Doheim M. F., Dokova K. G., Dongarwar D., Dsouza H. L., Dube J., Duraisamy S., Durojaiye O. C., Dutta S., Dziedzic A. M., Edinur H. A., Eissazade N., Ekholuenetale M., Ekundayo T. C., El Nahas N., El Sayed I. E., Elahi Najafi M. A. E., Elbarazi I., Elemam N. M., Elgar F. J., Elgendy I. Y., Elhabashy H. R., Elhadi M., Elilo L. T., Ellenbogen R. G., Elmeligy O. A. A., Elmonem M. A., Elshaer M., Elsohaby I., Emamverdi M., Emeto T. I., Endres M., Esezobor C. I., Eskandarieh S., Fadaei A., Fagbamigbe A. F., Fahim A., Faramarzi A., Fares J., Farjoud Kouhanjani M., Faro A., Farzadfar F., Fatehizadeh A., Fathi M., Fathi S., Fatima S. A. F., Feizkhah A., Fereshtehnejad S. -M., Ferrari A. J., Ferreira N., Fetensa G., Firouraghi N., Fischer F., Fonseca A. C., Force L. M., Fornari A., Foroutan B., Fukumoto T., Gadanya M. A., Gaidhane A. M., Galali Y., Galehdar N., Gan Q., Gandhi A. P., Ganesan B., Gardner W. M., Garg N., Gau S. -Y., Gautam R. K., Gebre T., Gebrehiwot M., Gebremeskel G. G., Gebreslassie H. G., Getacher L., Ghaderi Yazdi B., Ghadirian F., Ghaffarpasand F., Ghanbari R., Ghasemi M., Ghazy R. M., Ghimire S., Gholami A., Gholamrezanezhad A., Ghotbi E., Ghozy S., Gialluisi A., Gill P. S., Glasstetter L. M., Gnedovskaya E. V., Golchin A., Golechha M., Goleij P., Golinelli D., Gomes-Neto M., Goulart A. C., Goyal A., Gray R. J., Grivna M., Guadie H. A., Guan B., Guarducci G., Guicciardi S., Gunawardane D. A., Guo H., Gupta B., Gupta R., Gupta S., Gupta V. B., Gupta V. K., Gutierrez R. A., Habibzadeh F., Hachinski V., Haddadi R., Hadei M., Hadi N. R., Haep N., Haile T. G., Haj-Mirzaian A., Hall B. J., Halwani R., Hameed S., Hamiduzzaman M., Hammoud A., Han H., Hanifi N., Hankey G. J., Hannan M. A., Hao J., Harapan H., Hareru H. E., Hargono A., Harlianto N. I., Haro J. M., Hartman N. N., Hasaballah A. I., Hasan F., Hasani H., Hasanian M., Hassan A., Hassan S., Hassanipour S., Hassankhani H., Hassen M. B., Haubold J., Hay S. I., Hayat K., Hegazy M. I., Heidari G., Heidari M., Heidari-Soureshjani R., Hesami H., Hezam K., Hiraike Y., Hoffman H. J., Holla R., Hopf K. P., Horita N., Hossain M. M., Hossain M. B., Hossain S., Hosseinzadeh H., Hosseinzadeh M., Hostiuc S., Hu C., Huang J., Huda M. N., Hussain J., Hussein N. R., Huynh H. -H., Hwang B. -F., Ibitoye S. E., Ilaghi M., Ilesanmi O. S., Ilic I. M., Ilic M. D., Immurana M., Iravanpour F., Islam S. M. S., Ismail F., Iso H., Isola G., Iwagami M., Iwu C. C. D., Iyer M., Jaan A., Jacob L., Jadidi-Niaragh F., Jafari M., Jafarinia M., Jafarzadeh A., Jahankhani K., Jahanmehr N., Jahrami H., Jaiswal A., Jakovljevic M., Jamora R. D. G., Jana S., Javadi N., Javed S., Javeed S., Jayapal S. K., Jayaram S., Jiang H., Johnson C. O., Johnson W. D., Jokar M., Jonas J. B., Joseph A., Joseph N., Joshua C. E., Jurisson M., Kabir A., Kabir Z., Kabito G. G., Kadashetti V., Kafi F., Kalani R., Kalantar F., Kaliyadan F., Kamath A., Kamath S., Kanchan T., Kandel A., Kandel H., Kanmodi K. K., Karajizadeh M., Karami J., Karanth S. D., Karaye I. M., Karch A., Karimi A., Karimi H., Karimi Behnagh A., Kasraei H., Kassebaum N. J., Kauppila J. H., Kaur H., Kaur N., Kayode G. A., Kazemi F., Keikavoosi-Arani L., Keller C., Keykhaei M., Khadembashiri M. A., Khader Y. S., Khafaie M. A., Khajuria H., Khalaji A., Khamesipour F., Khammarnia M., Khan M., Khan M. A. B., Khan Y. H., Suheb M. Z. K., Khanmohammadi S., Khanna T., Khatab K., Khatatbeh H., Khatatbeh M. M., Khateri S., Khatib M. N., Khayat Kashani H. R., Khonji M. S., Khorashadizadeh F., Khormali M., Khubchandani J., Kian S., Kim G., Kim J., Kim M. S., Kim Y. J., Kimokoti R. W., Kisa A., Kisa S., Kivimaki M., Kochhar S., Kolahi A. -A., Koly K. N., Kompani F., Koroshetz W. J., Kosen S., Kourosh Arami M., Koyanagi A., Kravchenko M. A., Krishan K., Krishnamoorthy V., Defo B. K., Kuddus M. A., Kumar A., Kumar G. A., Kumar M., Kumar N., Kumsa N. B., Kundu S., Kurniasari M. D., Kusuma D., Kuttikkattu A., Kyu H. H., La Vecchia C., Ladan M. A., Lahariya C., Laksono T., Lal D. K., Lallukka T., Lam J., Lami F. H., Landires I., Langguth B., Lasrado S., Latief K., Latifinaibin K., Lau K. M. -M., Laurens M. B., Lawal B. K., Le L. K. D., Le T. T. T., Ledda C., Lee M., Lee S. -W., Lee S. W., Lee W. -C., Lee Y. H., Leonardi M., Lerango T. L., Li M. -C., Li W., Ligade V. S., Lim S. S., Linehan C., Liu C., Liu J., Liu W., Lo C. -H., Lo W. D., Lobo S. W., Logroscino G., Lopes G., Lopukhov P. D., Lorenzovici L., Lorkowski S., Loureiro J. A., Lubinda J., Lucchetti G., Saute R. L., Ma Z. F., Mabrok M., Machoy M., Madadizadeh F., El Razek M. M. A., Maghazachi A. A., Maghbouli N., Mahjoub S., Mahmoudi M., Majeed A., Malagon-Rojas J. N., Malakan Rad E., Malhotra K., Malik A. A., Malik I., Mallhi T. H., Malta D. C., Manilal A., Mansouri V., Mansournia M. A., Marasini B. P., Marateb H. R., Maroufi S. F., Martinez-Raga J., Martini S., Martins-Melo F. R., Martorell M., Marz W., Marzo R. R., Massano J., Mathangasinghe Y., Mathews E., Maude R. J., Maugeri A., Maulik P. K., Mayeli M., Mazaheri M., McAlinden C., McGrath J. J., Meena J. K., Mehndiratta M. M., Mendez-Lopez M. A. M., Mendoza W., Mendoza-Cano O., Menezes R. G., Merati M., Meretoja A., Merkin A., Mersha A. M., Mestrovic T., Mi T., Miazgowski T., Michalek I. M., Mihretie E. T., Minh L. H. N., Mirfakhraie R., Mirica A., Mirrakhimov E. M., Mirzaei M., Misganaw A., Misra S., Mithra P., Mizana B. A., Mohamadkhani A., Mohamed N. S., Mohammadi E., Mohammadi H., Mohammadi S., Mohammadshahi M., Mohammed M., Mohammed S., Mohan S., Mojiri-Forushani H., Moka N., Mokdad A. H., Molinaro S., Moller H., Monasta L., Moniruzzaman M., Montazeri F., Moradi M., Moradi Y., Moradi-Lakeh M., Moraga P., Morovatdar N., Morrison S. D., Mosapour A., Mosser J. F., Mossialos E., Motaghinejad M., Mousavi P., Ehsan Mousavi S., Mubarik S., Muccioli L., Mughal F., Mukoro G. D., Mulita A., Mulita F., Musaigwa F., Mustafa A., Mustafa G., Muthu S., Nagarajan A. J., Naghavi P., Naik G. R., Nainu F., Nair T. S., Najmuldeen H. H. R., Nakhostin Ansari N., Nambi G., Namdar Areshtanab H., Nargus S., Nascimento B. R., Naser A. Y., Nashwan A. J. J., Nasoori H., Nasreldein A., Natto Z. S., Nauman J., Nayak B. P., Nazri-Panjaki A., Negaresh M., Negash H., Negoi I., Negoi R. I., Negru S. M., Nejadghaderi S. A., Nematollahi M. H., Nesbit O. D., Newton C. R. J., Nguyen D. H., Nguyen H. T. H., Nguyen H. Q., Nguyen N. -T. T., Nguyen P. T., Nguyen V. T., Niazi R. K., Nikolouzakis T. K., Niranjan V., Nnyanzi L. A., Noman E. A., Noroozi N., Norrving B., Noubiap J. J., Nri-Ezedi C. A., Ntaios G., Nunez-Samudio V., Nurrika D., Oancea B., Odetokun I. A., O'Donnell M. J., Ogunsakin R. E., Oguta J. O., Oh I. -H., Okati-Aliabad H., Okeke S. R., Okekunle A. P., Okonji O. C., Okwute P. G., Olagunju A. T., Olaiya M. T., Olana M. D., Olatubi M. I., Oliveira G. M. M., Olufadewa I. I., Olusanya B. O., Bali A. O., Ong S., Onwujekwe O. E., Ordak M., Orji A. U., Ortega-Altamirano D. V., Osuagwu U. L., Otstavnov N., Otstavnov S. S., Ouyahia A., Owolabi M. O., Mahesh Padukudru P. A., Pacheco-Barrios K., Padubidri J. R., Pal P. K., Palange P. N., Palladino C., Palladino R., Palma-Alvarez R. F., Pan F., Panagiotakos D., Panda-Jonas S., Pandey A., Pandian J. D., Pangaribuan H. U., Pantazopoulos I., Pardhan S., Parija P. P., Parikh R. R., Park S., Parthasarathi A., Pashaei A., Patel J., Patil S., Patoulias D., Pawar S., Pedersini P., Pensato U., Pereira D. M., Pereira J., Pereira M. O., Peres M. F. P., Perico N., Perna S., Petcu I. -R., Petermann-Rocha F. E., Pham H. T., Phillips M. R., Pinilla-Monsalve G. D., Piradov M. A., Plotnikov E., Poddighe D., Polat B., Poluru R., Pond C. D., Poudel G. R., Pouramini A., Pourbagher-Shahri A. M., Pourfridoni M., Pourtaheri N., Prakash P. Y., Prakash S., Prakash V., Prates E. J. S., Pritchett N., Purnobasuki H., Qasim N. H., Qattea I., Qian G., Radhakrishnan V., Raee P., Shahraki H. R., Rafique I., Raggi A., Raghav P. R., Rahati M. M., Rahim F., Rahimi Z., Rahimifard M., Rahman M. O., Rahman M. H. U., Rahman M., Rahman M. A., Rahmani A. M., Rahmani S., Youshanlouei H. R., Rahmati M., Raj Moolambally S., Rajabpour-Sanati A., Ramadan H., Ramasamy S. K., Ramasubramani P., Ramazanu S., Rancic N., Rao I. R., Rao S. J., Rapaka D., Rashedi V., Rashid A. M., Rashidi M. -M., Rashidi Alavijeh M., Rasouli-Saravani A., Rawaf S., Razo C., Redwan E. M. M., Bana A. R., Remuzzi G., Rezaei N., Rezaeian M., Rhee T. G., Riad A., Robinson S. R., Rodrigues M., Rodriguez J. A. B., Roever L., Rogowski E. L. B., Romoli M., Ronfani L., Roy P., Pramanik K. R., Rubagotti E., Ruiz M. A., Russ T. C., Sunnerhagen K. S., Saad A. M. A., Saadatian Z., Saber K., SaberiKamarposhti M., Sacco S., Saddik B., Sadeghi E., Sadeghian S., Saeed U., Safdarian M., Safi S. Z., Sagar R., Sagoe D., Saheb Sharif-Askari F. S., Saheb Sharif-Askari N., Sahebkar A., Sahoo S. S., Sahraian M. A., Sajedi S. A., Sakshaug J. W., Saleh M. A., Salehi Omran H., Salem M. R., Salimi S., Samadi Kafil H., Samadzadeh S., Samargandy S., Samodra Y. L., Samuel V. P., Samy A. M., Sanadgol N., Sanjeev R. K., Sanmarchi F., Santomauro D. F., Santri I. N., Santric-Milicevic M. M., Saravanan A., Sarveazad A., Satpathy M., Saylan M., Sayyah M., Scarmeas N., Schlaich M. P., Schuermans A., Schwarzinger M., Schwebel D. C., Selvaraj S., Sendekie A. K., Sengupta P., Senthilkumaran S., Serban D., Sergindo M. T., Sethi Y., SeyedAlinaghi S., Seylani A., Shabani M., Shabany M., Shafie M., Shahabi S., Shahbandi A., Shahid S., Shahraki-Sanavi F., Shahsavari H. R., Shahwan M. J., Shaikh M. A., Shaji K. S., Sham S., Shama A. T. T., Shamim M. A., Shams-Beyranvand M., Shamsi M. A., Shanawaz M., Sharath M., Sharfaei S., Sharifan A., Sharma M., Sharma R., Shashamo B. B., Shayan M., Sheikhi R. A., Shekhar S., Shen J., Shenoy S. M., Shetty P. H., Shiferaw D. S., Shigematsu M., Shiri R., Shittu A., Shivakumar K. M., Shokri F., Shool S., Shorofi S. A., Shrestha S., Siankam Tankwanchi A. B., Siddig E. E., Sigfusdottir I. D., Silva J. P., Silva L. M. L. R., Sinaei E., Singh B. B., Singh G., Singh P., Singh S., Sirota S. B., Sivakumar S., Sohag A. A. M., Solanki R., Soleimani H., Solikhah S., Solomon Y., Song S., Song Y., Sotoudeh H., Spartalis M., Stark B. A., Starnes J. R., Starodubova A. V., Stein D. J., Steiner T. J., Stovner L. J., Suleman M., Abdulkader R. S., Sultana A., Sun J., Sunkersing D., Sunny A., Susianti H., Swain C. K., Szeto M. D., Tabares-Seisdedos R., Tabatabaei S. M., Tabatabai S., Tabish M., Taheri M., Tahvildari A., Tajbakhsh A., Tampa M., Lukenze Tamuzi J. J. L., Tan K. -K., Tang H., Tareke M., Tarigan I. U., Tat N. Y., Tat V. Y., Tavakoli Oliaee R., Tavangar S. M., Tavasol A., Tefera Y. M., Tehrani-Banihashemi A., Temesgen W. A., Temsah M. -H., Teramoto M., Tesfaye A. H., Tesfaye E. G., Tesler R., Thakali O., Thangaraju P., Thapa R., Thapar R., Thomas N. K., Thrift A. G., Ticoalu J. H. V., Tillawi T., Toghroli R., Tonelli M., Tovani-Palone M. R., Traini E., Tran N. M., Tran N. -H., Van Tran P., Tromans S. J., Truelsen T. C., Truyen T. T. T. T., Tsatsakis A., Tsegay G. M., Tsermpini E. E., Tualeka A. R., Tufa D. G., Ubah C. S., Udoakang A. J., Ulhaq I., Umair M., Umakanthan S., Umapathi K. K., Unim B., Unnikrishnan B., Vaithinathan A. G., Vakilian A., Tahbaz S. V., Valizadeh R., Van den Eynde J., Vart P., Varthya S. B., Vasankari T. J., Vaziri S., Vellingiri B., Venketasubramanian N., Verras G. -I., Vervoort D., Villafane J. H., Villani L., Veloz A. F. V., Viskadourou M., Vladimirov S. K., Vlassov V., Volovat S. R., Vu L. T., Vujcic I. S., Wagaye B., Waheed Y., Wahood W., Walde M. T., Wang F., Wang S., Wang Y., Wang Y. -P., Waqas M., Waris A., Weerakoon K. G., Weintraub R. G., Weldemariam A. H., Westerman R., Whisnant J. L., Wickramasinghe D. P., Wickramasinghe N. D., Willekens B., Wilner L. B., Winkler A. S., Wolfe C. D. A., Wu A. -M., Wulf Hanson S., Xu S., Xu X., Yadollahpour A., Yaghoubi S., Yahya G., Yamagishi K., Yang L., Yano Y., Yao Y., Yehualashet S. S., Yeshaneh A., Yesiltepe M., Yi S., Yigit A., Yigit V., Yon D. K., Yonemoto N., You Y., Younis M. Z., Yu C., Yusuf H., Zadey S., Zahedi M., Zakham F., Zaki N., Zali A., Zamagni G., Zand R., Zandieh G. G. Z., Zangiabadian M., Zarghami A., Zastrozhin M. S., Zeariya M. G. M., Zegeye Z. B., Zeukeng F., Zhai C., Zhang C., Zhang H., Zhang Y., Zhang Z. -J., Zhao H., Zhao Y., Zheng P., Zhou H., Zhu B., Zhumagaliuly A., Zielinska M., Zikarg Y. T., Zoladl M., Murray C. J. L., Ong K. L., Feigin V. L., Vos T., Dua T., Steinmetz, J, Seeher, K, Schiess, N, Nichols, E, Cao, B, Servili, C, Cavallera, V, Cousin, E, Hagins, H, Moberg, M, Mehlman, M, Abate, Y, Abbas, J, Abbasi, M, Abbasian, M, Abbastabar, H, Abdelmasseh, M, Abdollahi, M, Abdollahifar, M, Abd-Rabu, R, Abdulah, D, Abdullahi, A, Abedi, A, Abedi, V, Abeldano Zuniga, R, Abidi, H, Abiodun, O, Aboagye, R, Abolhassani, H, Aboyans, V, Abrha, W, Abualhasan, A, Abu-Gharbieh, E, Aburuz, S, Adamu, L, Addo, I, Adebayo, O, Adekanmbi, V, Adekiya, T, Adikusuma, W, Adnani, Q, Adra, S, Afework, T, Afolabi, A, Afraz, A, Afzal, S, Aghamiri, S, Agodi, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, S, Ahmadzade, A, Ahmed, A, Ahmed, H, Ahmed, J, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Aji, B, Ajumobi, O, Akade, S, Akbari, M, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemi, R, Akonde, M, Al Hasan, S, Alahdab, F, Al-Ahdal, T, Al-Amer, R, Albashtawy, M, Albataineh, M, Aldawsari, K, Alemi, H, Alemi, S, Algammal, A, Al-Gheethi, A, Alhalaiqa, F, Alhassan, R, Ali, A, Ali, E, Ali, L, Ali, M, Ali, R, Ali, S, Shujait Ali, S, Ali, Z, Alif, S, Alimohamadi, Y, Aliyi, A, Aljofan, M, Aljunid, S, Alladi, S, Almazan, J, Almustanyir, S, Al-Omari, B, Alqahtani, J, Alqasmi, I, Alqutaibi, A, Al-Shahi Salman, R, Altaany, Z, Al-Tawfiq, J, Altirkawi, K, Alvis-Guzman, N, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Amani, R, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, M, Amu, H, Amugsi, D, Amusa, G, Amzat, J, Ancuceanu, R, Anderlini, D, Anderson, D, Andrei, C, Androudi, S, Angappan, D, Angesom, T, Anil, A, Ansari-Moghaddam, A, Anwer, R, Arafat, M, Aravkin, A, Areda, D, Ariffin, H, Arifin, H, Arkew, M, Arnlov, J, Arooj, M, Artamonov, A, Artanti, K, Aruleba, R, Asadi-Pooya, A, Asena, T, Asghari-Jafarabadi, M, Ashraf, M, Ashraf, T, Atalell, K, Athari, S, Atinafu, B, Atorkey, P, Atout, M, Atreya, A, Aujayeb, A, Avan, A, Ayala Quintanilla, B, Ayatollahi, H, Ayinde, O, Mohammad Ayyoubzadeh, S, Azadnajafabad, S, Azizi, Z, Azizian, K, Azzam, A, Babaei, M, Badar, M, Badiye, A, Baghdadi, S, Bagherieh, S, Bai, R, Baig, A, Balakrishnan, S, Balalla, S, Baltatu, O, Banach, M, Bandyopadhyay, S, Banerjee, I, Baran, M, Barboza, M, Barchitta, M, Bardhan, M, Barker-Collo, S, Barnighausen, T, Barrow, A, Bashash, D, Bashiri, H, Bashiru, H, Basiru, A, Basso, J, Basu, S, Batiha, A, Batra, K, Baune, B, Bedi, N, Begde, A, Begum, T, Behnam, B, Behnoush, A, Beiranvand, M, Bejot, Y, Bekele, A, Belete, M, Belgaumi, U, Bemanalizadeh, M, Bender, R, Benfor, B, Bennett, D, Bensenor, I, Berice, B, Bettencourt, P, Beyene, K, Bhadra, A, Bhagat, D, Bhangdia, K, Bhardwaj, N, Bhardwaj, P, Bhargava, A, Bhaskar, S, Bhat, A, Bhat, V, Bhatti, G, Bhatti, J, Bhatti, R, Bijani, A, Bikbov, B, Bilalaga, M, Biswas, A, Bitaraf, S, Bitra, V, Bjorge, T, Bodolica, V, Bodunrin, A, Boloor, A, Braithwaite, D, Brayne, C, Brenner, H, Briko, A, Bringas Vega, M, Brown, J, Budke, C, Buonsenso, D, Burkart, K, Burns, R, Bustanji, Y, Butt, M, Butt, N, Butt, Z, Cabral, L, dos Santos, F, Calina, D, Campos-Nonato, I, Cao, C, Carabin, H, Cardenas, R, Carreras, G, Carvalho, A, Castaneda-Orjuela, C, Casulli, A, Catala-Lopez, F, Catapano, A, Caye, A, Cegolon, L, Cenderadewi, M, Cerin, E, Chacon-Uscamaita, P, Chan, J, Chanie, G, Charan, J, Chattu, V, Chekol Abebe, E, Chen, H, Chen, J, Chi, G, Chichagi, F, Chidambaram, S, Chimoriya, R, Ching, P, Chitheer, A, Chong, Y, Chopra, H, Choudhari, S, Chowdhury, E, Chowdhury, R, Christensen, H, Chu, D, Chukwu, I, Chung, E, Coberly, K, Columbus, A, Comachio, J, Conde, J, Cortesi, P, Costa, V, Couto, R, Criqui, M, Cruz-Martins, N, Dabbagh Ohadi, M, Dadana, S, Dadras, O, Dai, X, Dai, Z, D'Amico, E, Danawi, H, Dandona, L, Dandona, R, Darwish, A, Das, S, Dascalu, A, Dash, N, Dashti, M, De la Hoz, F, de la Torre-Luque, A, De Leo, D, Dean, F, Dehghan, A, Dejene, H, Demant, D, Demetriades, A, Demissie, S, Deng, X, Desai, H, Devanbu, V, Dhama, K, Dharmaratne, S, Dhimal, M, Dias da Silva, D, Diaz, D, Dibas, M, Ding, D, Dinu, M, Dirac, M, Diress, M, Do, T, Doan, K, Dodangeh, M, Doheim, M, Dokova, K, Dongarwar, D, Dsouza, H, Dube, J, Duraisamy, S, Durojaiye, O, Dutta, S, Dziedzic, A, Edinur, H, Eissazade, N, Ekholuenetale, M, Ekundayo, T, El Nahas, N, El Sayed, I, Elahi Najafi, M, Elbarazi, I, Elemam, N, Elgar, F, Elgendy, I, Elhabashy, H, Elhadi, M, Elilo, L, Ellenbogen, R, Elmeligy, O, Elmonem, M, Elshaer, M, Elsohaby, I, Emamverdi, M, Emeto, T, Endres, M, Esezobor, C, Eskandarieh, S, Fadaei, A, Fagbamigbe, A, Fahim, A, Faramarzi, A, Fares, J, Farjoud Kouhanjani, M, Faro, A, Farzadfar, F, Fatehizadeh, A, Fathi, M, Fathi, S, Fatima, S, Feizkhah, A, Fereshtehnejad, S, Ferrari, A, Ferreira, N, Fetensa, G, Firouraghi, N, Fischer, F, Fonseca, A, Force, L, Fornari, A, Foroutan, B, Fukumoto, T, Gadanya, M, Gaidhane, A, Galali, Y, Galehdar, N, Gan, Q, Gandhi, A, Ganesan, B, Gardner, W, Garg, N, Gau, S, Gautam, R, Gebre, T, Gebrehiwot, M, Gebremeskel, G, Gebreslassie, H, Getacher, L, Ghaderi Yazdi, B, Ghadirian, F, Ghaffarpasand, F, Ghanbari, R, Ghasemi, M, Ghazy, R, Ghimire, S, Gholami, A, Gholamrezanezhad, A, Ghotbi, E, Ghozy, S, Gialluisi, A, Gill, P, Glasstetter, L, Gnedovskaya, E, Golchin, A, Golechha, M, Goleij, P, Golinelli, D, Gomes-Neto, M, Goulart, A, Goyal, A, Gray, R, Grivna, M, Guadie, H, Guan, B, Guarducci, G, Guicciardi, S, Gunawardane, D, Guo, H, Gupta, B, Gupta, R, Gupta, S, Gupta, V, Gutierrez, R, Habibzadeh, F, Hachinski, V, Haddadi, R, Hadei, M, Hadi, N, Haep, N, Haile, T, Haj-Mirzaian, A, Hall, B, Halwani, R, Hameed, S, Hamiduzzaman, M, Hammoud, A, Han, H, Hanifi, N, Hankey, G, Hannan, M, Hao, J, Harapan, H, Hareru, H, Hargono, A, Harlianto, N, Haro, J, Hartman, N, Hasaballah, A, Hasan, F, Hasani, H, Hasanian, M, Hassan, A, Hassan, S, Hassanipour, S, Hassankhani, H, Hassen, M, Haubold, J, Hay, S, Hayat, K, Hegazy, M, Heidari, G, Heidari, M, Heidari-Soureshjani, R, Hesami, H, Hezam, K, Hiraike, Y, Hoffman, H, Holla, R, Hopf, K, Horita, N, Hossain, M, Hossain, S, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, S, Hu, C, Huang, J, Huda, M, Hussain, J, Hussein, N, Huynh, H, Hwang, B, Ibitoye, S, Ilaghi, M, Ilesanmi, O, Ilic, I, Ilic, M, Immurana, M, Iravanpour, F, Islam, S, Ismail, F, Iso, H, Isola, G, Iwagami, M, Iwu, C, Iyer, M, Jaan, A, Jacob, L, Jadidi-Niaragh, F, Jafari, M, Jafarinia, M, Jafarzadeh, A, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jaiswal, A, Jakovljevic, M, Jamora, R, Jana, S, Javadi, N, Javed, S, Javeed, S, Jayapal, S, Jayaram, S, Jiang, H, Johnson, C, Johnson, W, Jokar, M, Jonas, J, Joseph, A, Joseph, N, Joshua, C, Jurisson, M, Kabir, A, Kabir, Z, Kabito, G, Kadashetti, V, Kafi, F, Kalani, R, Kalantar, F, Kaliyadan, F, Kamath, A, Kamath, S, Kanchan, T, Kandel, A, Kandel, H, Kanmodi, K, Karajizadeh, M, Karami, J, Karanth, S, Karaye, I, Karch, A, Karimi, A, Karimi, H, Karimi Behnagh, A, Kasraei, H, Kassebaum, N, Kauppila, J, Kaur, H, Kaur, N, Kayode, G, Kazemi, F, Keikavoosi-Arani, L, Keller, C, Keykhaei, M, Khadembashiri, M, Khader, Y, Khafaie, M, Khajuria, H, Khalaji, A, Khamesipour, F, Khammarnia, M, Khan, M, Khan, Y, Suheb, M, Khanmohammadi, S, Khanna, T, Khatab, K, Khatatbeh, H, Khatatbeh, M, Khateri, S, Khatib, M, Khayat Kashani, H, Khonji, M, Khorashadizadeh, F, Khormali, M, Khubchandani, J, Kian, S, Kim, G, Kim, J, Kim, M, Kim, Y, Kimokoti, R, Kisa, A, Kisa, S, Kivimaki, M, Kochhar, S, Kolahi, A, Koly, K, Kompani, F, Koroshetz, W, Kosen, S, Kourosh Arami, M, Koyanagi, A, Kravchenko, M, Krishan, K, Krishnamoorthy, V, Defo, B, Kuddus, M, Kumar, A, Kumar, G, Kumar, M, Kumar, N, Kumsa, N, Kundu, S, Kurniasari, M, Kusuma, D, Kuttikkattu, A, Kyu, H, La Vecchia, C, Ladan, M, Lahariya, C, Laksono, T, Lal, D, Lallukka, T, Lam, J, Lami, F, Landires, I, Langguth, B, Lasrado, S, Latief, K, Latifinaibin, K, Lau, K, Laurens, M, Lawal, B, Le, L, Le, T, Ledda, C, Lee, M, Lee, S, Lee, W, Lee, Y, Leonardi, M, Lerango, T, Li, M, Li, W, Ligade, V, Lim, S, Linehan, C, Liu, C, Liu, J, Liu, W, Lo, C, Lo, W, Lobo, S, Logroscino, G, Lopes, G, Lopukhov, P, Lorenzovici, L, Lorkowski, S, Loureiro, J, Lubinda, J, Lucchetti, G, Saute, R, Ma, Z, Mabrok, M, Machoy, M, Madadizadeh, F, El Razek, M, Maghazachi, A, Maghbouli, N, Mahjoub, S, Mahmoudi, M, Majeed, A, Malagon-Rojas, J, Malakan Rad, E, Malhotra, K, Malik, A, Malik, I, Mallhi, T, Malta, D, Manilal, A, Mansouri, V, Mansournia, M, Marasini, B, Marateb, H, Maroufi, S, Martinez-Raga, J, Martini, S, Martins-Melo, F, Martorell, M, Marz, W, Marzo, R, Massano, J, Mathangasinghe, Y, Mathews, E, Maude, R, Maugeri, A, Maulik, P, Mayeli, M, Mazaheri, M, Mcalinden, C, Mcgrath, J, Meena, J, Mehndiratta, M, Mendez-Lopez, M, Mendoza, W, Mendoza-Cano, O, Menezes, R, Merati, M, Meretoja, A, Merkin, A, Mersha, A, Mestrovic, T, Mi, T, Miazgowski, T, Michalek, I, Mihretie, E, Minh, L, Mirfakhraie, R, Mirica, A, Mirrakhimov, E, Mirzaei, M, Misganaw, A, Misra, S, Mithra, P, Mizana, B, Mohamadkhani, A, Mohamed, N, Mohammadi, E, Mohammadi, H, Mohammadi, S, Mohammadshahi, M, Mohammed, M, Mohammed, S, Mohan, S, Mojiri-Forushani, H, Moka, N, Mokdad, A, Molinaro, S, Moller, H, Monasta, L, Moniruzzaman, M, Montazeri, F, Moradi, M, Moradi, Y, Moradi-Lakeh, M, Moraga, P, Morovatdar, N, Morrison, S, Mosapour, A, Mosser, J, Mossialos, E, Motaghinejad, M, Mousavi, P, Ehsan Mousavi, S, Mubarik, S, Muccioli, L, Mughal, F, Mukoro, G, Mulita, A, Mulita, F, Musaigwa, F, Mustafa, A, Mustafa, G, Muthu, S, Nagarajan, A, Naghavi, P, Naik, G, Nainu, F, Nair, T, Najmuldeen, H, Nakhostin Ansari, N, Nambi, G, Namdar Areshtanab, H, Nargus, S, Nascimento, B, Naser, A, Nashwan, A, Nasoori, H, Nasreldein, A, Natto, Z, Nauman, J, Nayak, B, Nazri-Panjaki, A, Negaresh, M, Negash, H, Negoi, I, Negoi, R, Negru, S, Nejadghaderi, S, Nematollahi, M, Nesbit, O, Newton, C, Nguyen, D, Nguyen, H, Nguyen, N, Nguyen, P, Nguyen, V, Niazi, R, Nikolouzakis, T, Niranjan, V, Nnyanzi, L, Noman, E, Noroozi, N, Norrving, B, Noubiap, J, Nri-Ezedi, C, Ntaios, G, Nunez-Samudio, V, Nurrika, D, Oancea, B, Odetokun, I, O'Donnell, M, Ogunsakin, R, Oguta, J, Oh, I, Okati-Aliabad, H, Okeke, S, Okekunle, A, Okonji, O, Okwute, P, Olagunju, A, Olaiya, M, Olana, M, Olatubi, M, Oliveira, G, Olufadewa, I, Olusanya, B, Bali, A, Ong, S, Onwujekwe, O, Ordak, M, Orji, A, Ortega-Altamirano, D, Osuagwu, U, Otstavnov, N, Otstavnov, S, Ouyahia, A, Owolabi, M, Mahesh Padukudru, P, Pacheco-Barrios, K, Padubidri, J, Pal, P, Palange, P, Palladino, C, Palladino, R, Palma-Alvarez, R, Pan, F, Panagiotakos, D, Panda-Jonas, S, Pandey, A, Pandian, J, Pangaribuan, H, Pantazopoulos, I, Pardhan, S, Parija, P, Parikh, R, Park, S, Parthasarathi, A, Pashaei, A, Patel, J, Patil, S, Patoulias, D, Pawar, S, Pedersini, P, Pensato, U, Pereira, D, Pereira, J, Pereira, M, Peres, M, Perico, N, Perna, S, Petcu, I, Petermann-Rocha, F, Pham, H, Phillips, M, Pinilla-Monsalve, G, Piradov, M, Plotnikov, E, Poddighe, D, Polat, B, Poluru, R, Pond, C, Poudel, G, Pouramini, A, Pourbagher-Shahri, A, Pourfridoni, M, Pourtaheri, N, Prakash, P, Prakash, S, Prakash, V, Prates, E, Pritchett, N, Purnobasuki, H, Qasim, N, Qattea, I, Qian, G, Radhakrishnan, V, Raee, P, Shahraki, H, Rafique, I, Raggi, A, Raghav, P, Rahati, M, Rahim, F, Rahimi, Z, Rahimifard, M, Rahman, M, Rahmani, A, Rahmani, S, Youshanlouei, H, Rahmati, M, Raj Moolambally, S, Rajabpour-Sanati, A, Ramadan, H, Ramasamy, S, Ramasubramani, P, Ramazanu, S, Rancic, N, Rao, I, Rao, S, Rapaka, D, Rashedi, V, Rashid, A, Rashidi, M, Rashidi Alavijeh, M, Rasouli-Saravani, A, Rawaf, S, Razo, C, Redwan, E, Bana, A, Remuzzi, G, Rezaei, N, Rezaeian, M, Rhee, T, Riad, A, Robinson, S, Rodrigues, M, Rodriguez, J, Roever, L, Rogowski, E, Romoli, M, Ronfani, L, Roy, P, Pramanik, K, Rubagotti, E, Ruiz, M, Russ, T, Sunnerhagen, K, Saad, A, Saadatian, Z, Saber, K, Saberikamarposhti, M, Sacco, S, Saddik, B, Sadeghi, E, Sadeghian, S, Saeed, U, Safdarian, M, Safi, S, Sagar, R, Sagoe, D, Saheb Sharif-Askari, F, Saheb Sharif-Askari, N, Sahebkar, A, Sahoo, S, Sahraian, M, Sajedi, S, Sakshaug, J, Saleh, M, Salehi Omran, H, Salem, M, Salimi, S, Samadi Kafil, H, Samadzadeh, S, Samargandy, S, Samodra, Y, Samuel, V, Samy, A, Sanadgol, N, Sanjeev, R, Sanmarchi, F, Santomauro, D, Santri, I, Santric-Milicevic, M, Saravanan, A, Sarveazad, A, Satpathy, M, Saylan, M, Sayyah, M, Scarmeas, N, Schlaich, M, Schuermans, A, Schwarzinger, M, Schwebel, D, Selvaraj, S, Sendekie, A, Sengupta, P, Senthilkumaran, S, Serban, D, Sergindo, M, Sethi, Y, Seyedalinaghi, S, Seylani, A, Shabani, M, Shabany, M, Shafie, M, Shahabi, S, Shahbandi, A, Shahid, S, Shahraki-Sanavi, F, Shahsavari, H, Shahwan, M, Shaikh, M, Shaji, K, Sham, S, Shama, A, Shamim, M, Shams-Beyranvand, M, Shamsi, M, Shanawaz, M, Sharath, M, Sharfaei, S, Sharifan, A, Sharma, M, Sharma, R, Shashamo, B, Shayan, M, Sheikhi, R, Shekhar, S, Shen, J, Shenoy, S, Shetty, P, Shiferaw, D, Shigematsu, M, Shiri, R, Shittu, A, Shivakumar, K, Shokri, F, Shool, S, Shorofi, S, Shrestha, S, Siankam Tankwanchi, A, Siddig, E, Sigfusdottir, I, Silva, J, Silva, L, Sinaei, E, Singh, B, Singh, G, Singh, P, Singh, S, Sirota, S, Sivakumar, S, Sohag, A, Solanki, R, Soleimani, H, Solikhah, S, Solomon, Y, Song, S, Song, Y, Sotoudeh, H, Spartalis, M, Stark, B, Starnes, J, Starodubova, A, Stein, D, Steiner, T, Stovner, L, Suleman, M, Abdulkader, R, Sultana, A, Sun, J, Sunkersing, D, Sunny, A, Susianti, H, Swain, C, Szeto, M, Tabares-Seisdedos, R, Tabatabaei, S, Tabatabai, S, Tabish, M, Taheri, M, Tahvildari, A, Tajbakhsh, A, Tampa, M, Lukenze Tamuzi, J, Tan, K, Tang, H, Tareke, M, Tarigan, I, Tat, N, Tat, V, Tavakoli Oliaee, R, Tavangar, S, Tavasol, A, Tefera, Y, Tehrani-Banihashemi, A, Temesgen, W, Temsah, M, Teramoto, M, Tesfaye, A, Tesfaye, E, Tesler, R, Thakali, O, Thangaraju, P, Thapa, R, Thapar, R, Thomas, N, Thrift, A, Ticoalu, J, Tillawi, T, Toghroli, R, Tonelli, M, Tovani-Palone, M, Traini, E, Tran, N, Van Tran, P, Tromans, S, Truelsen, T, Truyen, T, Tsatsakis, A, Tsegay, G, Tsermpini, E, Tualeka, A, Tufa, D, Ubah, C, Udoakang, A, Ulhaq, I, Umair, M, Umakanthan, S, Umapathi, K, Unim, B, Unnikrishnan, B, Vaithinathan, A, Vakilian, A, Tahbaz, S, Valizadeh, R, Van den Eynde, J, Vart, P, Varthya, S, Vasankari, T, Vaziri, S, Vellingiri, B, Venketasubramanian, N, Verras, G, Vervoort, D, Villafane, J, Villani, L, Veloz, A, Viskadourou, M, Vladimirov, S, Vlassov, V, Volovat, S, Vu, L, Vujcic, I, Wagaye, B, Waheed, Y, Wahood, W, Walde, M, Wang, F, Wang, S, Wang, Y, Waqas, M, Waris, A, Weerakoon, K, Weintraub, R, Weldemariam, A, Westerman, R, Whisnant, J, Wickramasinghe, D, Wickramasinghe, N, Willekens, B, Wilner, L, Winkler, A, Wolfe, C, Wu, A, Wulf Hanson, S, Xu, S, Xu, X, Yadollahpour, A, Yaghoubi, S, Yahya, G, Yamagishi, K, Yang, L, Yano, Y, Yao, Y, Yehualashet, S, Yeshaneh, A, Yesiltepe, M, Yi, S, Yigit, A, Yigit, V, Yon, D, Yonemoto, N, You, Y, Younis, M, Yu, C, Yusuf, H, Zadey, S, Zahedi, M, Zakham, F, Zaki, N, Zali, A, Zamagni, G, Zand, R, Zandieh, G, Zangiabadian, M, Zarghami, A, Zastrozhin, M, Zeariya, M, Zegeye, Z, Zeukeng, F, Zhai, C, Zhang, C, Zhang, H, Zhang, Y, Zhang, Z, Zhao, H, Zhao, Y, Zheng, P, Zhou, H, Zhu, B, Zhumagaliuly, A, Zielinska, M, Zikarg, Y, Zoladl, M, Murray, C, Ong, K, Feigin, V, Vos, T, Dua, T, Steinmetz J. D., Seeher K. M., Schiess N., Nichols E., Cao B., Servili C., Cavallera V., Cousin E., Hagins H., Moberg M. E., Mehlman M. L., Abate Y. H., Abbas J., Abbasi M. A., Abbasian M., Abbastabar H., Abdelmasseh M., Abdollahi M., Abdollahifar M. -A., Abd-Rabu R., Abdulah D. M., Abdullahi A., Abedi A., Abedi V., Abeldano Zuniga R. A., Abidi H., Abiodun O., Aboagye R. G., Abolhassani H., Aboyans V., Abrha W. A., Abualhasan A., Abu-Gharbieh E., Aburuz S., Adamu L. H., Addo I. Y., Adebayo O. M., Adekanmbi V., Adekiya T. A., Adikusuma W., Adnani Q. E. S., Adra S., Afework T., Afolabi A. A., Afraz A., Afzal S., Aghamiri S., Agodi A., Agyemang-Duah W., Ahinkorah B. O., Ahmad A., Ahmad D., Ahmad S., Ahmadzade A. M., Ahmed A., Ahmed H., Ahmed J. Q., Ahmed L. A., Ahmed M. B., Ahmed S. A., Ajami M., Aji B., Ajumobi O., Akade S., Akbari M., Akbarialiabad H., Akhlaghi S., Akinosoglou K., Akinyemi R. O., Akonde M., Al Hasan S. M., Alahdab F., Al-Ahdal T. M. A., Al-Amer R. M., Albashtawy M., AlBataineh M. T., Aldawsari K. A., Alemi H., Alemi S., Algammal A. M., Al-Gheethi A. A. S., Alhalaiqa F. A. N., Alhassan R. K., Ali A., Ali E. A., Ali L., Ali M. U., Ali M. M., Ali R., Ali S., Shujait Ali S. S., Ali Z., Alif S. M., Alimohamadi Y., Aliyi A. A., Aljofan M., Aljunid S. M., Alladi S., Almazan J. U., Almustanyir S., Al-Omari B., Alqahtani J. S., Alqasmi I., Alqutaibi A. Y., Al-Shahi Salman R., Altaany Z., Al-Tawfiq J. A., Altirkawi K. A., Alvis-Guzman N., Al-Worafi Y. M., Aly H., Aly S., Alzoubi K. H., Amani R., Amindarolzarbi A., Amiri S., Amirzade-Iranaq M. H., Amu H., Amugsi D. A., Amusa G. A., Amzat J., Ancuceanu R., Anderlini D., Anderson D. B., Andrei C. L., Androudi S., Angappan D., Angesom T. W., Anil A., Ansari-Moghaddam A., Anwer R., Arafat M., Aravkin A. Y., Areda D., Ariffin H., Arifin H., Arkew M., Arnlov J., Arooj M., Artamonov A. A., Artanti K. D., Aruleba R. T., Asadi-Pooya A. A., Asena T. F., Asghari-Jafarabadi M., Ashraf M., Ashraf T., Atalell K. A., Athari S. S., Atinafu B. T. T., Atorkey P., Atout M. M. W., Atreya A., Aujayeb A., Avan A., Ayala Quintanilla B. P. A., Ayatollahi H., Ayinde O. O., Mohammad Ayyoubzadeh S., Azadnajafabad S., Azizi Z., Azizian K., Azzam A. Y., Babaei M., Badar M., Badiye A. D., Baghdadi S., Bagherieh S., Bai R., Baig A. A., Balakrishnan S., Balalla S., Baltatu O. C., Banach M., Bandyopadhyay S., Banerjee I., Baran M. F., Barboza M. A., Barchitta M., Bardhan M., Barker-Collo S. L., Barnighausen T. W., Barrow A., Bashash D., Bashiri H., Bashiru H. A., Basiru A., Basso J., Basu S., Batiha A. M. M., Batra K., Baune B. T., Bedi N., Begde A., Begum T., Behnam B., Behnoush A. H., Beiranvand M., Bejot Y., Bekele A., Belete M. A., Belgaumi U. I., Bemanalizadeh M., Bender R. G., Benfor B., Bennett D. A., Bensenor I. M., Berice B., Bettencourt P. J. G., Beyene K. A., Bhadra A., Bhagat D. S., Bhangdia K., Bhardwaj N., Bhardwaj P., Bhargava A., Bhaskar S., Bhat A. N., Bhat V., Bhatti G. K., Bhatti J. S., Bhatti R., Bijani A., Bikbov B., Bilalaga M. M., Biswas A., Bitaraf S., Bitra V. R., Bjorge T., Bodolica V., Bodunrin A. O., Boloor A., Braithwaite D., Brayne C., Brenner H., Briko A., Bringas Vega M. L., Brown J., Budke C. M., Buonsenso D., Burkart K., Burns R. A., Bustanji Y., Butt M. H., Butt N. S., Butt Z. A., Cabral L. S., dos Santos F. L. C., Calina D., Campos-Nonato I. R., Cao C., Carabin H., Cardenas R., Carreras G., Carvalho A. F., Castaneda-Orjuela C. A., Casulli A., Catala-Lopez F., Catapano A. L., Caye A., Cegolon L., Cenderadewi M., Cerin E., Chacon-Uscamaita P. R. U., Chan J. S. K., Chanie G. S., Charan J., Chattu V. K., Chekol Abebe E., Chen H., Chen J., Chi G., Chichagi F., Chidambaram S. B., Chimoriya R., Ching P. R., Chitheer A., Chong Y. Y., Chopra H., Choudhari S. G., Chowdhury E. K., Chowdhury R., Christensen H., Chu D. -T., Chukwu I. S., Chung E., Coberly K., Columbus A., Comachio J., Conde J., Cortesi P. A., Costa V. M., Couto R. A. S., Criqui M. H., Cruz-Martins N., Dabbagh Ohadi M. A., Dadana S., Dadras O., Dai X., Dai Z., D'Amico E., Danawi H. A., Dandona L., Dandona R., Darwish A. H., Das S., Dascalu A. M., Dash N. R., Dashti M., De la Hoz F. P., de la Torre-Luque A., De Leo D., Dean F. E., Dehghan A., Dejene H., Demant D., Demetriades A. K., Demissie S., Deng X., Desai H. D., Devanbu V. G. C., Dhama K., Dharmaratne S. D., Dhimal M., Dias da Silva D., Diaz D., Dibas M., Ding D. D., Dinu M., Dirac M. A., Diress M., Do T. C., Do T. H. P., Doan K. D. K., Dodangeh M., Doheim M. F., Dokova K. G., Dongarwar D., Dsouza H. L., Dube J., Duraisamy S., Durojaiye O. C., Dutta S., Dziedzic A. M., Edinur H. A., Eissazade N., Ekholuenetale M., Ekundayo T. C., El Nahas N., El Sayed I. E., Elahi Najafi M. A. E., Elbarazi I., Elemam N. M., Elgar F. J., Elgendy I. Y., Elhabashy H. R., Elhadi M., Elilo L. T., Ellenbogen R. G., Elmeligy O. A. A., Elmonem M. A., Elshaer M., Elsohaby I., Emamverdi M., Emeto T. I., Endres M., Esezobor C. I., Eskandarieh S., Fadaei A., Fagbamigbe A. F., Fahim A., Faramarzi A., Fares J., Farjoud Kouhanjani M., Faro A., Farzadfar F., Fatehizadeh A., Fathi M., Fathi S., Fatima S. A. F., Feizkhah A., Fereshtehnejad S. -M., Ferrari A. J., Ferreira N., Fetensa G., Firouraghi N., Fischer F., Fonseca A. C., Force L. M., Fornari A., Foroutan B., Fukumoto T., Gadanya M. A., Gaidhane A. M., Galali Y., Galehdar N., Gan Q., Gandhi A. P., Ganesan B., Gardner W. M., Garg N., Gau S. -Y., Gautam R. K., Gebre T., Gebrehiwot M., Gebremeskel G. G., Gebreslassie H. G., Getacher L., Ghaderi Yazdi B., Ghadirian F., Ghaffarpasand F., Ghanbari R., Ghasemi M., Ghazy R. M., Ghimire S., Gholami A., Gholamrezanezhad A., Ghotbi E., Ghozy S., Gialluisi A., Gill P. S., Glasstetter L. M., Gnedovskaya E. V., Golchin A., Golechha M., Goleij P., Golinelli D., Gomes-Neto M., Goulart A. C., Goyal A., Gray R. J., Grivna M., Guadie H. A., Guan B., Guarducci G., Guicciardi S., Gunawardane D. A., Guo H., Gupta B., Gupta R., Gupta S., Gupta V. B., Gupta V. K., Gutierrez R. A., Habibzadeh F., Hachinski V., Haddadi R., Hadei M., Hadi N. R., Haep N., Haile T. G., Haj-Mirzaian A., Hall B. J., Halwani R., Hameed S., Hamiduzzaman M., Hammoud A., Han H., Hanifi N., Hankey G. J., Hannan M. A., Hao J., Harapan H., Hareru H. E., Hargono A., Harlianto N. I., Haro J. M., Hartman N. N., Hasaballah A. I., Hasan F., Hasani H., Hasanian M., Hassan A., Hassan S., Hassanipour S., Hassankhani H., Hassen M. B., Haubold J., Hay S. I., Hayat K., Hegazy M. I., Heidari G., Heidari M., Heidari-Soureshjani R., Hesami H., Hezam K., Hiraike Y., Hoffman H. J., Holla R., Hopf K. P., Horita N., Hossain M. M., Hossain M. B., Hossain S., Hosseinzadeh H., Hosseinzadeh M., Hostiuc S., Hu C., Huang J., Huda M. N., Hussain J., Hussein N. R., Huynh H. -H., Hwang B. -F., Ibitoye S. E., Ilaghi M., Ilesanmi O. S., Ilic I. M., Ilic M. D., Immurana M., Iravanpour F., Islam S. M. S., Ismail F., Iso H., Isola G., Iwagami M., Iwu C. C. D., Iyer M., Jaan A., Jacob L., Jadidi-Niaragh F., Jafari M., Jafarinia M., Jafarzadeh A., Jahankhani K., Jahanmehr N., Jahrami H., Jaiswal A., Jakovljevic M., Jamora R. D. G., Jana S., Javadi N., Javed S., Javeed S., Jayapal S. K., Jayaram S., Jiang H., Johnson C. O., Johnson W. D., Jokar M., Jonas J. B., Joseph A., Joseph N., Joshua C. E., Jurisson M., Kabir A., Kabir Z., Kabito G. G., Kadashetti V., Kafi F., Kalani R., Kalantar F., Kaliyadan F., Kamath A., Kamath S., Kanchan T., Kandel A., Kandel H., Kanmodi K. K., Karajizadeh M., Karami J., Karanth S. D., Karaye I. M., Karch A., Karimi A., Karimi H., Karimi Behnagh A., Kasraei H., Kassebaum N. J., Kauppila J. H., Kaur H., Kaur N., Kayode G. A., Kazemi F., Keikavoosi-Arani L., Keller C., Keykhaei M., Khadembashiri M. A., Khader Y. S., Khafaie M. A., Khajuria H., Khalaji A., Khamesipour F., Khammarnia M., Khan M., Khan M. A. B., Khan Y. H., Suheb M. Z. K., Khanmohammadi S., Khanna T., Khatab K., Khatatbeh H., Khatatbeh M. M., Khateri S., Khatib M. N., Khayat Kashani H. R., Khonji M. S., Khorashadizadeh F., Khormali M., Khubchandani J., Kian S., Kim G., Kim J., Kim M. S., Kim Y. J., Kimokoti R. W., Kisa A., Kisa S., Kivimaki M., Kochhar S., Kolahi A. -A., Koly K. N., Kompani F., Koroshetz W. J., Kosen S., Kourosh Arami M., Koyanagi A., Kravchenko M. A., Krishan K., Krishnamoorthy V., Defo B. K., Kuddus M. A., Kumar A., Kumar G. A., Kumar M., Kumar N., Kumsa N. B., Kundu S., Kurniasari M. D., Kusuma D., Kuttikkattu A., Kyu H. H., La Vecchia C., Ladan M. A., Lahariya C., Laksono T., Lal D. K., Lallukka T., Lam J., Lami F. H., Landires I., Langguth B., Lasrado S., Latief K., Latifinaibin K., Lau K. M. -M., Laurens M. B., Lawal B. K., Le L. K. D., Le T. T. T., Ledda C., Lee M., Lee S. -W., Lee S. W., Lee W. -C., Lee Y. H., Leonardi M., Lerango T. L., Li M. -C., Li W., Ligade V. S., Lim S. S., Linehan C., Liu C., Liu J., Liu W., Lo C. -H., Lo W. D., Lobo S. W., Logroscino G., Lopes G., Lopukhov P. D., Lorenzovici L., Lorkowski S., Loureiro J. A., Lubinda J., Lucchetti G., Saute R. L., Ma Z. F., Mabrok M., Machoy M., Madadizadeh F., El Razek M. M. A., Maghazachi A. A., Maghbouli N., Mahjoub S., Mahmoudi M., Majeed A., Malagon-Rojas J. N., Malakan Rad E., Malhotra K., Malik A. A., Malik I., Mallhi T. H., Malta D. C., Manilal A., Mansouri V., Mansournia M. A., Marasini B. P., Marateb H. R., Maroufi S. F., Martinez-Raga J., Martini S., Martins-Melo F. R., Martorell M., Marz W., Marzo R. R., Massano J., Mathangasinghe Y., Mathews E., Maude R. J., Maugeri A., Maulik P. K., Mayeli M., Mazaheri M., McAlinden C., McGrath J. J., Meena J. K., Mehndiratta M. M., Mendez-Lopez M. A. M., Mendoza W., Mendoza-Cano O., Menezes R. G., Merati M., Meretoja A., Merkin A., Mersha A. M., Mestrovic T., Mi T., Miazgowski T., Michalek I. M., Mihretie E. T., Minh L. H. N., Mirfakhraie R., Mirica A., Mirrakhimov E. M., Mirzaei M., Misganaw A., Misra S., Mithra P., Mizana B. A., Mohamadkhani A., Mohamed N. S., Mohammadi E., Mohammadi H., Mohammadi S., Mohammadshahi M., Mohammed M., Mohammed S., Mohan S., Mojiri-Forushani H., Moka N., Mokdad A. H., Molinaro S., Moller H., Monasta L., Moniruzzaman M., Montazeri F., Moradi M., Moradi Y., Moradi-Lakeh M., Moraga P., Morovatdar N., Morrison S. D., Mosapour A., Mosser J. F., Mossialos E., Motaghinejad M., Mousavi P., Ehsan Mousavi S., Mubarik S., Muccioli L., Mughal F., Mukoro G. D., Mulita A., Mulita F., Musaigwa F., Mustafa A., Mustafa G., Muthu S., Nagarajan A. J., Naghavi P., Naik G. R., Nainu F., Nair T. S., Najmuldeen H. H. R., Nakhostin Ansari N., Nambi G., Namdar Areshtanab H., Nargus S., Nascimento B. R., Naser A. Y., Nashwan A. J. J., Nasoori H., Nasreldein A., Natto Z. S., Nauman J., Nayak B. P., Nazri-Panjaki A., Negaresh M., Negash H., Negoi I., Negoi R. I., Negru S. M., Nejadghaderi S. A., Nematollahi M. H., Nesbit O. D., Newton C. R. J., Nguyen D. H., Nguyen H. T. H., Nguyen H. Q., Nguyen N. -T. T., Nguyen P. T., Nguyen V. T., Niazi R. K., Nikolouzakis T. K., Niranjan V., Nnyanzi L. A., Noman E. A., Noroozi N., Norrving B., Noubiap J. J., Nri-Ezedi C. A., Ntaios G., Nunez-Samudio V., Nurrika D., Oancea B., Odetokun I. A., O'Donnell M. J., Ogunsakin R. E., Oguta J. O., Oh I. -H., Okati-Aliabad H., Okeke S. R., Okekunle A. P., Okonji O. C., Okwute P. G., Olagunju A. T., Olaiya M. T., Olana M. D., Olatubi M. I., Oliveira G. M. M., Olufadewa I. I., Olusanya B. O., Bali A. O., Ong S., Onwujekwe O. E., Ordak M., Orji A. U., Ortega-Altamirano D. V., Osuagwu U. L., Otstavnov N., Otstavnov S. S., Ouyahia A., Owolabi M. O., Mahesh Padukudru P. A., Pacheco-Barrios K., Padubidri J. R., Pal P. K., Palange P. N., Palladino C., Palladino R., Palma-Alvarez R. F., Pan F., Panagiotakos D., Panda-Jonas S., Pandey A., Pandian J. D., Pangaribuan H. U., Pantazopoulos I., Pardhan S., Parija P. P., Parikh R. R., Park S., Parthasarathi A., Pashaei A., Patel J., Patil S., Patoulias D., Pawar S., Pedersini P., Pensato U., Pereira D. M., Pereira J., Pereira M. O., Peres M. F. P., Perico N., Perna S., Petcu I. -R., Petermann-Rocha F. E., Pham H. T., Phillips M. R., Pinilla-Monsalve G. D., Piradov M. A., Plotnikov E., Poddighe D., Polat B., Poluru R., Pond C. D., Poudel G. R., Pouramini A., Pourbagher-Shahri A. M., Pourfridoni M., Pourtaheri N., Prakash P. Y., Prakash S., Prakash V., Prates E. J. S., Pritchett N., Purnobasuki H., Qasim N. H., Qattea I., Qian G., Radhakrishnan V., Raee P., Shahraki H. R., Rafique I., Raggi A., Raghav P. R., Rahati M. M., Rahim F., Rahimi Z., Rahimifard M., Rahman M. O., Rahman M. H. U., Rahman M., Rahman M. A., Rahmani A. M., Rahmani S., Youshanlouei H. R., Rahmati M., Raj Moolambally S., Rajabpour-Sanati A., Ramadan H., Ramasamy S. K., Ramasubramani P., Ramazanu S., Rancic N., Rao I. R., Rao S. J., Rapaka D., Rashedi V., Rashid A. M., Rashidi M. -M., Rashidi Alavijeh M., Rasouli-Saravani A., Rawaf S., Razo C., Redwan E. M. M., Bana A. R., Remuzzi G., Rezaei N., Rezaeian M., Rhee T. G., Riad A., Robinson S. R., Rodrigues M., Rodriguez J. A. B., Roever L., Rogowski E. L. B., Romoli M., Ronfani L., Roy P., Pramanik K. R., Rubagotti E., Ruiz M. A., Russ T. C., Sunnerhagen K. S., Saad A. M. A., Saadatian Z., Saber K., SaberiKamarposhti M., Sacco S., Saddik B., Sadeghi E., Sadeghian S., Saeed U., Safdarian M., Safi S. Z., Sagar R., Sagoe D., Saheb Sharif-Askari F. S., Saheb Sharif-Askari N., Sahebkar A., Sahoo S. S., Sahraian M. A., Sajedi S. A., Sakshaug J. W., Saleh M. A., Salehi Omran H., Salem M. R., Salimi S., Samadi Kafil H., Samadzadeh S., Samargandy S., Samodra Y. L., Samuel V. P., Samy A. M., Sanadgol N., Sanjeev R. K., Sanmarchi F., Santomauro D. F., Santri I. N., Santric-Milicevic M. M., Saravanan A., Sarveazad A., Satpathy M., Saylan M., Sayyah M., Scarmeas N., Schlaich M. P., Schuermans A., Schwarzinger M., Schwebel D. C., Selvaraj S., Sendekie A. K., Sengupta P., Senthilkumaran S., Serban D., Sergindo M. T., Sethi Y., SeyedAlinaghi S., Seylani A., Shabani M., Shabany M., Shafie M., Shahabi S., Shahbandi A., Shahid S., Shahraki-Sanavi F., Shahsavari H. R., Shahwan M. J., Shaikh M. A., Shaji K. S., Sham S., Shama A. T. T., Shamim M. A., Shams-Beyranvand M., Shamsi M. A., Shanawaz M., Sharath M., Sharfaei S., Sharifan A., Sharma M., Sharma R., Shashamo B. B., Shayan M., Sheikhi R. A., Shekhar S., Shen J., Shenoy S. M., Shetty P. H., Shiferaw D. S., Shigematsu M., Shiri R., Shittu A., Shivakumar K. M., Shokri F., Shool S., Shorofi S. A., Shrestha S., Siankam Tankwanchi A. B., Siddig E. E., Sigfusdottir I. D., Silva J. P., Silva L. M. L. R., Sinaei E., Singh B. B., Singh G., Singh P., Singh S., Sirota S. B., Sivakumar S., Sohag A. A. M., Solanki R., Soleimani H., Solikhah S., Solomon Y., Song S., Song Y., Sotoudeh H., Spartalis M., Stark B. A., Starnes J. R., Starodubova A. V., Stein D. J., Steiner T. J., Stovner L. J., Suleman M., Abdulkader R. S., Sultana A., Sun J., Sunkersing D., Sunny A., Susianti H., Swain C. K., Szeto M. D., Tabares-Seisdedos R., Tabatabaei S. M., Tabatabai S., Tabish M., Taheri M., Tahvildari A., Tajbakhsh A., Tampa M., Lukenze Tamuzi J. J. L., Tan K. -K., Tang H., Tareke M., Tarigan I. U., Tat N. Y., Tat V. Y., Tavakoli Oliaee R., Tavangar S. M., Tavasol A., Tefera Y. M., Tehrani-Banihashemi A., Temesgen W. A., Temsah M. -H., Teramoto M., Tesfaye A. H., Tesfaye E. G., Tesler R., Thakali O., Thangaraju P., Thapa R., Thapar R., Thomas N. K., Thrift A. G., Ticoalu J. H. V., Tillawi T., Toghroli R., Tonelli M., Tovani-Palone M. R., Traini E., Tran N. M., Tran N. -H., Van Tran P., Tromans S. J., Truelsen T. C., Truyen T. T. T. T., Tsatsakis A., Tsegay G. M., Tsermpini E. E., Tualeka A. R., Tufa D. G., Ubah C. S., Udoakang A. J., Ulhaq I., Umair M., Umakanthan S., Umapathi K. K., Unim B., Unnikrishnan B., Vaithinathan A. G., Vakilian A., Tahbaz S. V., Valizadeh R., Van den Eynde J., Vart P., Varthya S. B., Vasankari T. J., Vaziri S., Vellingiri B., Venketasubramanian N., Verras G. -I., Vervoort D., Villafane J. H., Villani L., Veloz A. F. V., Viskadourou M., Vladimirov S. K., Vlassov V., Volovat S. R., Vu L. T., Vujcic I. S., Wagaye B., Waheed Y., Wahood W., Walde M. T., Wang F., Wang S., Wang Y., Wang Y. -P., Waqas M., Waris A., Weerakoon K. G., Weintraub R. G., Weldemariam A. H., Westerman R., Whisnant J. L., Wickramasinghe D. P., Wickramasinghe N. D., Willekens B., Wilner L. B., Winkler A. S., Wolfe C. D. A., Wu A. -M., Wulf Hanson S., Xu S., Xu X., Yadollahpour A., Yaghoubi S., Yahya G., Yamagishi K., Yang L., Yano Y., Yao Y., Yehualashet S. S., Yeshaneh A., Yesiltepe M., Yi S., Yigit A., Yigit V., Yon D. K., Yonemoto N., You Y., Younis M. Z., Yu C., Yusuf H., Zadey S., Zahedi M., Zakham F., Zaki N., Zali A., Zamagni G., Zand R., Zandieh G. G. Z., Zangiabadian M., Zarghami A., Zastrozhin M. S., Zeariya M. G. M., Zegeye Z. B., Zeukeng F., Zhai C., Zhang C., Zhang H., Zhang Y., Zhang Z. -J., Zhao H., Zhao Y., Zheng P., Zhou H., Zhu B., Zhumagaliuly A., Zielinska M., Zikarg Y. T., Zoladl M., Murray C. J. L., Ong K. L., Feigin V. L., Vos T., and Dua T.
- Abstract
Background: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous s
- Published
- 2024
146. Burden of Stroke in Europe: An Analysis of the Global Burden of Disease Study Findings from 2010 to 2019
- Author
-
Prendes, C, Rantner, B, Hamwi, T, Stana, J, Feigin, V, Stavroulakis, K, Tsilimparis, N, Fernandez Prendes, C, Aboyans, P, Olusola Akinyemi, R, Al-Shahi Salman, R, Artamonov, A, Aujayeb, A, Baldereschi, M, Basu, S, Bejot, Y, Belo, L, Bennett, D, Srikanth Bhagavathula, A, Bikbov, B, Brenner, H, Dos Santos, F, Carrero, J, Carvalho, F, Catapano, A, Charalampous, P, Christensen, H, Chung, S, Angelo Cortesi, P, Marisa Costa, V, Cyganska, M, D'Amico, E, Davletov, K, Georgieva Dokova, K, Douiri, A, Francis Fagbamigbe, A, Fischer, F, Ghith, N, Giampaoli, S, Singh Gill, P, Gnedovskaya, E, Havmoeller, R, Hostiuc, S, Iavicoli, I, Ilic, M, Isola, G, Jerzy Jozwiak, J, Jurisson, M, Kayode, G, Khan, M, Khatab, K, Kisa, A, Kivimaki, M, Koyanagi, A, Kulimbet, M, Kusuma, D, La Vecchia, C, Lacey, B, Lallukka, T, Lorkowski, S, Majeed, P, Giovanni Mantovani, L, Mazzaglia, G, Mentis, A, Meretoja, A, Miao Jonasson, J, Mirica, A, Mirrakhimov, E, Mohammed, S, Molokhia, M, Monasta, L, Mons, U, Morze, J, Irina Negoi, R, Norrving, B, Oancea, B, O'Caoimh, R, Orru, H, Padron-Monedero, A, Pedersini, P, Perico, N, Polibin, R, Polinder, S, Raggi, A, Rawaf, S, Remuzzi, G, Romoli, M, Sacco, P, Reza Saeb, P, Vasco Santos, J, Santric-Milicevic, M, Aleksandrovna Skryabina, A, Smith, L, Starodubova, A, Stevanovic, A, Stranges, P, Teuschl, Y, Topor-Madry, R, Touvier, M, Tovani-Palone, M, Unim, B, Juhani Vasankari, T, Volovici, V, Wafa, H, Wang, Y, Westerman, R, Wolfe, P, Yesiltepe, M, Zanghi, A, Sergeevich Zastrozhin, M, Prendes C. F., Rantner B., Hamwi T., Stana J., Feigin V. L., Stavroulakis K., Tsilimparis N., Fernandez Prendes C., Aboyans P. V., Olusola Akinyemi R., Al-Shahi Salman R., Artamonov A. A., Aujayeb A., Baldereschi M., Basu S., Bejot Y., Belo L., Bennett D. A., Srikanth Bhagavathula A., Bikbov B., Brenner H., Dos Santos F., Carrero J. J., Carvalho F., Catapano A. L., Charalampous P., Christensen H., Chung S. -C., Angelo Cortesi P., Marisa Costa V., Cyganska M., D'Amico E., Davletov K., Georgieva Dokova K., Douiri A., Francis Fagbamigbe A., Fischer F., Ghith N., Giampaoli S., Singh Gill P., Gnedovskaya E. V., Havmoeller R. J., Hostiuc S., Iavicoli I., Ilic M. D., Isola G., Jerzy Jozwiak J., Jurisson M., Kayode G. A., Khan M. A. B., Khatab K., Kisa A., Kivimaki M., Koyanagi A., Kulimbet M., Kusuma D., La Vecchia C., Lacey B., Lallukka T., Lorkowski S., Majeed P. A., Giovanni Mantovani L., Mazzaglia G., Mentis A. -F. A., Meretoja A., Miao Jonasson J., Mirica A., Mirrakhimov E. M., Mohammed S., Molokhia M., Monasta L., Mons U., Morze J., Irina Negoi R., Norrving B., Oancea B., O'Caoimh R., Orru H., Padron-Monedero A., Pedersini P., Perico N., Polibin R. V., Polinder S., Raggi A., Rawaf S., Remuzzi G., Romoli M., Sacco P. S., Reza Saeb P. M., Vasco Santos J., Santric-Milicevic M. M., Aleksandrovna Skryabina A., Smith L., Starodubova A. V., Stevanovic A., Stranges P. S., Teuschl Y., Topor-Madry R., Touvier M., Tovani-Palone M. R., Unim B., Juhani Vasankari T., Volovici V., Wafa H. A., Wang Y., Westerman R., Wolfe P. C. D. A., Yesiltepe M., Zanghi A., Sergeevich Zastrozhin M., Prendes, C, Rantner, B, Hamwi, T, Stana, J, Feigin, V, Stavroulakis, K, Tsilimparis, N, Fernandez Prendes, C, Aboyans, P, Olusola Akinyemi, R, Al-Shahi Salman, R, Artamonov, A, Aujayeb, A, Baldereschi, M, Basu, S, Bejot, Y, Belo, L, Bennett, D, Srikanth Bhagavathula, A, Bikbov, B, Brenner, H, Dos Santos, F, Carrero, J, Carvalho, F, Catapano, A, Charalampous, P, Christensen, H, Chung, S, Angelo Cortesi, P, Marisa Costa, V, Cyganska, M, D'Amico, E, Davletov, K, Georgieva Dokova, K, Douiri, A, Francis Fagbamigbe, A, Fischer, F, Ghith, N, Giampaoli, S, Singh Gill, P, Gnedovskaya, E, Havmoeller, R, Hostiuc, S, Iavicoli, I, Ilic, M, Isola, G, Jerzy Jozwiak, J, Jurisson, M, Kayode, G, Khan, M, Khatab, K, Kisa, A, Kivimaki, M, Koyanagi, A, Kulimbet, M, Kusuma, D, La Vecchia, C, Lacey, B, Lallukka, T, Lorkowski, S, Majeed, P, Giovanni Mantovani, L, Mazzaglia, G, Mentis, A, Meretoja, A, Miao Jonasson, J, Mirica, A, Mirrakhimov, E, Mohammed, S, Molokhia, M, Monasta, L, Mons, U, Morze, J, Irina Negoi, R, Norrving, B, Oancea, B, O'Caoimh, R, Orru, H, Padron-Monedero, A, Pedersini, P, Perico, N, Polibin, R, Polinder, S, Raggi, A, Rawaf, S, Remuzzi, G, Romoli, M, Sacco, P, Reza Saeb, P, Vasco Santos, J, Santric-Milicevic, M, Aleksandrovna Skryabina, A, Smith, L, Starodubova, A, Stevanovic, A, Stranges, P, Teuschl, Y, Topor-Madry, R, Touvier, M, Tovani-Palone, M, Unim, B, Juhani Vasankari, T, Volovici, V, Wafa, H, Wang, Y, Westerman, R, Wolfe, P, Yesiltepe, M, Zanghi, A, Sergeevich Zastrozhin, M, Prendes C. F., Rantner B., Hamwi T., Stana J., Feigin V. L., Stavroulakis K., Tsilimparis N., Fernandez Prendes C., Aboyans P. V., Olusola Akinyemi R., Al-Shahi Salman R., Artamonov A. A., Aujayeb A., Baldereschi M., Basu S., Bejot Y., Belo L., Bennett D. A., Srikanth Bhagavathula A., Bikbov B., Brenner H., Dos Santos F., Carrero J. J., Carvalho F., Catapano A. L., Charalampous P., Christensen H., Chung S. -C., Angelo Cortesi P., Marisa Costa V., Cyganska M., D'Amico E., Davletov K., Georgieva Dokova K., Douiri A., Francis Fagbamigbe A., Fischer F., Ghith N., Giampaoli S., Singh Gill P., Gnedovskaya E. V., Havmoeller R. J., Hostiuc S., Iavicoli I., Ilic M. D., Isola G., Jerzy Jozwiak J., Jurisson M., Kayode G. A., Khan M. A. B., Khatab K., Kisa A., Kivimaki M., Koyanagi A., Kulimbet M., Kusuma D., La Vecchia C., Lacey B., Lallukka T., Lorkowski S., Majeed P. A., Giovanni Mantovani L., Mazzaglia G., Mentis A. -F. A., Meretoja A., Miao Jonasson J., Mirica A., Mirrakhimov E. M., Mohammed S., Molokhia M., Monasta L., Mons U., Morze J., Irina Negoi R., Norrving B., Oancea B., O'Caoimh R., Orru H., Padron-Monedero A., Pedersini P., Perico N., Polibin R. V., Polinder S., Raggi A., Rawaf S., Remuzzi G., Romoli M., Sacco P. S., Reza Saeb P. M., Vasco Santos J., Santric-Milicevic M. M., Aleksandrovna Skryabina A., Smith L., Starodubova A. V., Stevanovic A., Stranges P. S., Teuschl Y., Topor-Madry R., Touvier M., Tovani-Palone M. R., Unim B., Juhani Vasankari T., Volovici V., Wafa H. A., Wang Y., Westerman R., Wolfe P. C. D. A., Yesiltepe M., Zanghi A., and Sergeevich Zastrozhin M.
- Abstract
BACKGROUND: While most European Regions perform well in global comparisons, large discrepancies within stroke epidemiological parameters exist across Europe. The objective of this analysis was to evaluate the stroke burden across European regions and countries in 2019 and its difference to 2010. METHODS: The GBD 2019 analytical tools were used to evaluate regional and country-specific estimates of incidence, prevalence, deaths, and disability-adjusted life years of stroke for the European Region as defined by the World Health Organization, with its 53 member countries (EU-53) and for European Union as defined in 2019, with its 28 member countries (EU-28), between 2010 and 2019. Results were analyzed at a regional, subregional, and country level. RESULTS: In EU-53, the absolute number of incident and prevalent strokes increased by 2% (uncertainty interval [UI], 0%-4%), from 1 767 280 to 1 802 559 new cases, and by 4% (UI, 3%-5%) between 2010 and 2019, respectively. In EU-28, the absolute number of prevalent strokes and stroke-related deaths increased by 4% (UI, 2%-5%) and by 6% (UI, 1%-10%), respectively. All-stroke age-standardized mortality rates, however, decreased by 18% (UI, -22% to -14%), from 82 to 67 per 100 000 people in the EU-53, and by 15% (UI, -18% to -11%), from 49.3 to 42.0 per 100 000 people in EU-28. Despite most countries presenting reductions in age-adjusted incidence, prevalence, mortality, and disability-adjusted life year rates, these rates remained 1.4×, 1.2×, 1.6×, and 1.7× higher in EU-53 in comparison to the EU-28. CONCLUSIONS: EU-53 showed a 2% increase in incident strokes, while they remained stable in EU-28. Age-standardized rates were consistently lower for all-stroke burden parameters in EU-28 in comparison to EU-53, and huge discrepancies in incidence, prevalence, mortality, and disability-adjusted life-year rates were observed between individual countries.
- Published
- 2024
147. Synergistic retrieval and complete data fusion methods applied to simulated FORUM and IASI-NG measurements
- Author
-
M. Ridolfi, C. Tirelli, S. Ceccherini, C. Belotti, U. Cortesi, and L. Palchetti
- Subjects
Environmental engineering ,TA170-171 ,Earthwork. Foundations ,TA715-787 - Abstract
In the frame of Earth observation remote-sensing data analysis, synergistic retrieval (SR) and complete data fusion (CDF) are techniques used to exploit the complementarity of the information carried by different measurements sounding the same air mass and/or ground pixel. While more difficult to implement due to the required simultaneous access to measurements originating from different instruments, the SR method is sometimes preferred over the CDF method as the latter relies on a linear approximation of the retrieved states as functions of the true atmospheric and/or surface state. In this work, we study the performance of the SR and CDF techniques when applied to simulated measurements of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) and the Infrared Atmospheric Sounding Interferometer – New Generation (IASI-NG) missions that will be operational in a few years, from two polar-orbiting satellites. The study is based on synthetic measurements generated for the two missions in clear-sky atmospheres. The target parameters of the inversion are the vertical profiles of temperature, water vapor and ozone mixing ratios, surface temperature, and spectral emissivity. We find that for exact matching of the measurements, the results of the SR and CDF techniques differ by less than 1/10 of their errors estimated through the propagation of measurement noise. For measurements with a realistic mismatch in space and time, the two methods provide more different results. Still in this case, however, the differences between the results are within the error bars due to measurement noise. We conclude that, when applied to FORUM and IASI-NG missions, the two methods are equivalent from an accuracy point of view.
- Published
- 2022
- Full Text
- View/download PDF
148. Azithromycin use and outcomes in patients with COVID-19: an observational real-world study
- Author
-
Ippazio Cosimo Antonazzo, Carla Fornari, Davide Rozza, Sara Conti, Raffaella di Pasquale, Paolo Cortesi, Shaniko Kaleci, Pietro Ferrara, Alberto Zucchi, Giovanni Maifredi, Andrea Silenzi, Giancarlo Cesana, Lorenzo Giovanni Mantovani, and Giampiero Mazzaglia
- Subjects
Azithromycin ,COVID-19 ,Hospitalization ,Intensive care unit access ,Mechanical ventilation ,Mortality ,Infectious and parasitic diseases ,RC109-216 - Abstract
Objectives: Previous studies ruled out the benefits of azithromycin for treatment of patients with COVID-19 who are hospitalized. However, the effects of azithromycin for treatment of patients with positive SARS-CoV-2 test results in the community remains a matter of debate. This study aimed to assess whether azithromycin, when used in subjects with positive test results for SARS-CoV-2, is associated with a reduced risk of hospitalization, in-hospital COVID-19 outcomes, and death. Methods: Two study cohorts were selected. Cohort A included subjects with positive test results for SARS-CoV-2 between February 20, 2020 and December 10, 2020; cohort B included subjects infected with SARS-CoV-2 and hospitalized between February 20, 2020 and December 31, 2020. We compared the risk of hospitalization, intensive care unit access, need for mechanical ventilation, and death in azithromycin users versus nonusers. A clustered Fine-Gray analysis was employed to assess the risk of hospitalization; logistic and Cox regressions were performed to assess the risk of intensive care unit access, mechanical ventilation, and death. Results: In cohort A, among 4861 azithromycin users and 4861 propensity-matched nonusers, azithromycin use was associated with higher risk of hospitalization (hazard ratio [HR] 1.59, 95% confidence interval [CI] 1.45-1.75) compared with nonuse. In cohort B, among 997 subjects selected in both groups, azithromycin use was not significantly associated with intensive care unit access (odds ratio [OR] 1.22, 95% CI 0.93-1.56), mechanical ventilation (OR 1.30, 95% CI 0.99-1.70), 14-day mortality (HR0.88, 95% CI 0.74-1.05), or 30-day mortality (HR 0.89, 95% CI 0.77-1.03). Conclusion: Our findings confirm the lack of benefits of azithromycin treatment among community patients infected with SARS-CoV-2, raising concern on potential risks associated with its inappropriate use.
- Published
- 2022
- Full Text
- View/download PDF
149. Prognostic significance of germline BRCA mutations in patients with HER2-POSITIVE breast cancer
- Author
-
A. Viansone, B. Pellegrino, C. Omarini, M. Pistelli, D. Boggiani, A. Sikokis, V. Uliana, D. Zanoni, C. Tommasi, B. Bortesi, F. Bonatti, F. Piacentini, L. Cortesi, R. Camisa, P. Sgargi, M. Michiara, and A. Musolino
- Subjects
BRCA ,HER2 ,Prognosis ,Germline mutation ,Breast cancer ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Background: HER2-positive breast cancers are rare amongst BRCA mutation carriers. No data exist regarding clinicopathological characteristics and prognosis of this subgroup of patients. Materials and methods: Using a retrospective matched cohort design, we collected data from 700 women who were diagnosed with operable invasive breast cancer from January 2006 to December 2016 and were screened for germline BRCA mutations. Clinicopathological features and survival rates were analyzed by BRCA and HER2 status. Results: One hundred and fifteen HER2-positive/BRCA mutated cases were evaluated in comparison to the three control groups: HER2-positive/BRCA wild type (n = 129), HER2-negative/BRCA mutated (n = 222), HER2-negative/BRCA wild type (n = 234). HER2-positive breast cancers were more likely to have high histologic grade and high proliferation rate than HER2-negative neoplasms, regardless of BRCA mutation status. An interaction between BRCA mutations and HER2-positive status was found to correlate with worse survival after adjusting for prognostic variables (HR = 3.4; 95% CI: 1.3–16.7). Conclusions: Co-occurrence of BRCA mutations and HER2-positive status is a poor prognostic factor in patients with early or locally advanced breast cancer. This finding may be a proof of concept that a combined pharmacological intervention directed to these targets could be synergistic.
- Published
- 2022
- Full Text
- View/download PDF
150. Management of PALB2‐associated breast cancer: A literature review and case report
- Author
-
Angela Toss, Ornella Ponzoni, Beatrice Riccò, Claudia Piombino, Luca Moscetti, Francesca Combi, Enza Palma, Simona Papi, Elena Tenedini, Giovanni Tazzioli, Massimo Dominici, and Laura Cortesi
- Subjects
breast cancer ,immunotherapy ,PALB2 ,PARP inhibitor ,Medicine ,Medicine (General) ,R5-920 - Abstract
Key Clinical Message Germline pathogenic variants (PV) of the PALB2 tumor suppressor gene are associated with an increased risk of breast, pancreatic, and ovarian cancer. In previous research, PALB2‐associated breast cancer showed aggressive clinicopathological phenotypes, particularly triple‐negative subtype, and higher mortality regardless of tumor stage, type of chemotherapy nor hormone receptor status. The identification of this germline alteration may have an impact on clinical management of breast cancer (BC) from the surgical approach to the systemic treatment choice. We herein report the case of a patient with a germline PV of PALB2, diagnosed with locally advanced PD‐L1 positive triple‐negative BC, who progressed after an immune checkpoint inhibitor (ICI)‐containing regimen and then experienced a pathologic complete response after platinum‐based chemotherapy. This case report hints a major role of the germline PALB2 alteration compared to the PD‐L1 expression as cancer driver and gives us the opportunity to extensively review and discuss the available literature on the optimal management of PALB2‐associated BC. Overall, our case report and review of the literature provide additional evidence that the germline analysis of PALB2 gene should be included in routine genetic testing for predictive purposes and to refine treatment algorithms.
- Published
- 2023
- Full Text
- View/download PDF
Catalog
Books, media, physical & digital resources
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.