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Antibiotics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 892
Author(s):  
Federico Scali ◽  
Giovanni Santucci ◽  
Antonio M. Maisano ◽  
Francesca Giudici ◽  
Federica Guadagno ◽  
...  

Data on antimicrobial use (AMU) in heavy pig production (>150 kg) are limited. The aim of this study was to investigate the AMU in this production. Data from 2015 were collected for 143 fattening farms. The AMU was estimated through a treatment index per 100 days (TI100) using the defined daily dose animal for Italy (DDDAit). When possible, a comparison with the European Medicines Agency’s defined daily doses for animals (DDDvet) was performed. The median TI100 was 10.7 (range, 0.2–49.5). Group treatments represented 94.6% of overall consumption. The AMU calculated using DDDAit and DDDvet were strongly correlated (ρ = 0.976; p < 0.001). The AMU was negatively correlated with injectables use (ρ = −0.46, p < 0.001) and positively correlated with oral products (ρ = 0.21, p = 0.014), premixes (ρ = 0.26, p = 0.002), and mortality (ρ = 0.18; p = 0.027). Farm size was negatively correlated with AMU (ρ = −0.29, p < 0.001). Smaller farms were more frequently above the median TI100 (odds ratio = 2.3, 95% confidence interval = 1.2–4.7), suggesting that they may have lower biosecurity and management standards. The results of this study should provide useful insights for the development of an Italian monitoring system.


Meat Science ◽  
2020 ◽  
Vol 163 ◽  
pp. 108057 ◽  
Author(s):  
Martina Zappaterra ◽  
Gennaro Catillo ◽  
Anna Maria Belmonte ◽  
Domenico Pietro Lo Fiego ◽  
Paolo Zambonelli ◽  
...  

2018 ◽  
Author(s):  
Samuele Bovo ◽  
Alessio Di Luca ◽  
Giuliano Galimberti ◽  
Stefania Dall’Olio ◽  
Luca Fontanesi

AbstractLiver is a complex organ governing several physiological processes that define biological mechanisms affecting growth, feed efficiency and performance traits in all livestock species, including the pig. Proteomics may contribute to better understand the relationship between liver functions and complex production traits in pigs and to characterize this specie as biomedical model. This study applied, for the first time, a label-free liquid chromatography-mass spectrometry (LC-MS) proteomic approach to compare the liver proteome profiles of two important heavy pig breeds, Italian Duroc (IDU) and Italian Large White (ILW). Liver specimens were collected (after slaughtering) from performance tested pigs of these two breeds, raised in standard conditions. The label-free LC-MS method captured a total of 501 proteins of which 200 were subsequently considered in the between breeds comparison. A statistical pipeline based on the sparse Partial Least Squares Discriminant Analysis (sPLS-DA), coupled with stability and significance tests, was applied for the identification of up or down regulated proteins between breeds. Analyses revealed a total of 25 proteins clearly separating IDU and ILW pigs. Among the top proteins differentiating the two breeds ACAA2 and CES3 were up-regulated in ILW and HIST2H2BF and KHK were up-regulated in IDU. FASN, involved in fatty acid metabolism and encoded by a gene located in a QTL region for fatty acid composition, was up-regulated in ILW. Protein interaction analysis showed that 16 of these proteins were connected in one big module. Functional analyses indicated that differentially expressed proteins were involved in several biological processes related to the metabolism of lipids, amino-acids, carbohydrates, cofactors and antibiotics/drugs, supporting that these functions might distinguish IDU and ILW pigs. This comparative proteomic analysis of the porcine liver highlighted several biological factors that could determine the peculiar production potentials of these two heavy pig breeds, derived by their different genetic backgrounds.


2018 ◽  
pp. 154-169
Author(s):  
Jonathan Soto Hernández ◽  
Carlos Villamar Monsarrate ◽  
Jorge Luis Vinueza Martínez ◽  
Alexandra Astudillo Cobos ◽  
Mirella Correa Peralta

Este trabajo fue un estudio documental de la identidad de la tecnología en el desarrollo productivo sostenible de los gremios artesanales en la base de datos SCOPUS, abordando desde el punto de vista de las variables: desarrollo productivo y tecnología como un análisis general de los estudios realizados por varios autores. La metodología fue 2 consultas relacionadas al desarrollo productivo TITLE-ABS-KEY ( desarrollo  AND productivo ) y productive AND  development  AND  craft  AND  guild  AND  ( LIMIT-TO ( PUBYEAR ,  2016 )  OR  LIMIT-TO ( PUBYEAR ,  2015 )  OR  LIMIT-TO ( PUBYEAR ,  2014 )  OR  LIMIT-TO ( PUBYEAR ,  2013 )  OR  LIMIT-TO ( PUBYEAR ,  2012 ) )  AND  ( LIMIT-TO ( DOCTYPE ,  "ar" ) ) en 2 fases: 1. Obtener información. 2. Analizar y evaluar información validando autores, artículos y fuentes obtenidas. Este estudioo cuantitativo permitió concluir la asociación de 10 autores del artículo Replacing soybean for winter peas in heavy-pig diets: Productive impact of the level of protease inhibitors en la revista ITEA Informacion Tecnica Economica Agraria, revista del cuartil Q3; en el caso de las revistas Cadernos de Saude Publica  de Brasil cuenta con el 35% de participación Latinoamericana, y el artículo Precocious albion: A new interpretation of the British Industrial revolution, publicada en Annual Review of Economics  del 2014 resalta la influencia del desarrollo productivo, importancia del capital humano y calidad del trabajo asociadas con el alto nivel de nutrición, mejores instituciones y el alto nivel de aprendizaje.   Palabras claves: estudio bibliométrico, tecnología, base de datos, producción, publicaciones


2018 ◽  
Vol 19 (4) ◽  
pp. 852-857
Author(s):  
Marco Berton ◽  
Luigi Gallo ◽  
Giuseppe Carcò ◽  
Stefano Schiavon ◽  
Enrico Sturaro

2017 ◽  
Vol 140 ◽  
pp. 685-691 ◽  
Author(s):  
Luciana Bava ◽  
Maddalena Zucali ◽  
Anna Sandrucci ◽  
Alberto Tamburini

Meat Science ◽  
2016 ◽  
Vol 122 ◽  
pp. 132-138 ◽  
Author(s):  
Domenico Pietro Lo Fiego ◽  
Giovanna Minelli ◽  
Luisa Antonella Volpelli ◽  
Alessandro Ulrici ◽  
Paolo Macchioni

2016 ◽  
Vol 565 ◽  
pp. 576-585 ◽  
Author(s):  
G. Pirlo ◽  
S. Carè ◽  
G. Della Casa ◽  
R. Marchetti ◽  
G. Ponzoni ◽  
...  

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