scispace - formally typeset
Search or ask a question
Institution

University of Córdoba (Spain)

EducationCordova, Spain
About: University of Córdoba (Spain) is a education organization based out in Cordova, Spain. It is known for research contribution in the topics: Population & Catalysis. The organization has 12006 authors who have published 22998 publications receiving 537842 citations. The organization is also known as: University of Córdoba (Spain) & Universidad de Córdoba.


Papers
More filters
Journal ArticleDOI
TL;DR: It is shown that LLR (vs open) for HCC generally yields better short‐term outcomes without compromising long-term outcomes, and that incidences of postoperative ascites and liver failure are decreased with LLR.
Abstract: Liver resection (LR) for patients with hepatocellular carcinoma (HCC) and chronic liver disease (CLD) poses a high risk of serious postoperative complications and multicentric metachronous lesions requiring repeated treatment. The efficacy of laparoscopic LR (LLR) for such patients has yet to be established. The objective of this study is to test the outcomes of LLR for HCC with the aim of considering potential expansion of the indications for LLR. We performed a systematic review of the pertinent English-language literature. Our search yielded four meta-analyses and 23 comparative studies of LLR for HCC. On the basis of the findings from these studies and our newly conducted meta-analysis, the possibility for expanding the indications for LLR to HCC was examined. The studies show that LLR (vs open) for HCC generally yields better short-term outcomes without compromising long-term outcomes, and that incidences of postoperative ascites and liver failure are decreased with LLR. Several studies show the benefits of LLR for patients with severe CLD and for repeat surgery. Reductions of postoperative ascites and liver failure are among the advantages of LLR. These characteristics of LLR may allow us to expand the indications of LLR to HCC with CLD.

143 citations

Journal ArticleDOI
TL;DR: This work presents a generally applicable model that accurately explains the behavior of data obtained using current SIL approaches, including (18)O, iTRAQ, and SILAC labeling, and different MS instruments, and decomposes the total technical variance into the spectral, peptide, and protein variance components.
Abstract: The combination of stable isotope labeling (SIL) with mass spectrometry (MS) allows comparison of the abundance of thousands of proteins in complex mixtures. However, interpretation of the large data sets generated by these techniques remains a challenge because appropriate statistical standards are lacking. Here, we present a generally applicable model that accurately explains the behavior of data obtained using current SIL approaches, including (18)O, iTRAQ, and SILAC labeling, and different MS instruments. The model decomposes the total technical variance into the spectral, peptide, and protein variance components, and its general validity was demonstrated by confronting 48 experimental distributions against 18 different null hypotheses. In addition to its general applicability, the performance of the algorithm was at least similar than that of other existing methods. The model also provides a general framework to integrate quantitative and error information fully, allowing a comparative analysis of the results obtained from different SIL experiments. The model was applied to the global analysis of protein alterations induced by low H₂O₂ concentrations in yeast, demonstrating the increased statistical power that may be achieved by rigorous data integration. Our results highlight the importance of establishing an adequate and validated statistical framework for the analysis of high-throughput data.

143 citations

Journal ArticleDOI
TL;DR: In this article, an economic optimisation model for hydrologic planning in deficit irrigation systems is proposed, which is carried out following an economic efficiency criterion with the aim of maximising the overall economic benefits obtained, allocating available water to each user as a function of the water's profit margin.

143 citations

Journal ArticleDOI
TL;DR: It is concluded that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.
Abstract: Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

143 citations

Journal ArticleDOI
TL;DR: In this paper, an object-based image analysis (OBIA) method was developed for weed seedling mapping with ortho-mosaicked imagery, which successfully classified the sunflower-rows with 100% accuracy in both fields for all flight altitudes and camera types.
Abstract: Site-specific weed management is defined as the application of customised control treatments only where weeds are located within the crop-field by using adequate herbicide according to weed emergence. The aim of the study was to generate georeferenced weed seedling infestation maps in two sunflower fields by analysing overlapping aerial images of the visible and near-infrared spectrum (using visible or multi-spectral cameras) collected by an unmanned aerial vehicle (UAV) flying at 30 and 60 m altitudes. The main tasks focused on the configuration and evaluation of the UAV and its sensors for image acquisition and ortho-mosaicking, as well as the development of an automatic and robust image analysis procedure for weed seedling mapping used to design a site-specific weed management program. The control strategy was based on seven weed thresholds with 2.5 steps of increasing ratio from 0 % (herbicide must be applied just when there is presence or absence of weed) to 15 % (herbicide applied when weed coverage >15 %). As a first step of the imagery analysis, sunflower rows were correctly matched to the ortho-mosaicked imagery, which allowed accurate image analysis using object-based image analysis [object-based-image-analysis (OBIA) methods]. The OBIA algorithm developed for weed seedling mapping with ortho-mosaicked imagery successfully classified the sunflower-rows with 100 % accuracy in both fields for all flight altitudes and camera types, indicating the computational and analytical robustness of OBIA. Regarding weed discrimination, high accuracies were observed using the multi-spectral camera at any flight altitude, with the highest (approximately 100 %) being those recorded for the 15 % weed threshold, although satisfactory results from 2.5 to 5 % thresholds were also observed, with accuracies higher than 85 % for both field 1 and field 2. The lowest accuracies (ranging from 50 to 60 %) were achieved with the visible camera at all flight altitudes and 0 % weed threshold. Herbicide savings were relevant in both fields, although they were higher in field 2 due to less weed infestation. These herbicide savings varied according to the different scenarios studied. For example, in field 2 and at 30 m flight altitude and using the multi-spectral camera, a range of 23–3 % of the field (i.e., 77 and 97 % of area) could be treated for 0–15 % weed thresholds. The OBIA procedure computed multiple data which permitted calculation of herbicide requirements for timely and site-specific post-emergence weed seedling management.

143 citations


Authors

Showing all 12089 results

NameH-indexPapersCitations
Jose M. Ordovas123102470978
Liang Cheng116177965520
Pedro W. Crous11580951925
Munther A. Khamashta10962350205
Luis Serrano10545242515
Raymond Vanholder10384140861
Carlos Dieguez10154536404
David G. Bostwick9940331638
Leon V. Kochian9526631301
Abhay Ashtekar9436637508
Néstor Armesto9336926848
Manuel Hidalgo9253841330
Rafael de Cabo9131735020
Harald Mischak9044527472
Manuel Tena-Sempere8735123100
Network Information
Related Institutions (5)
Complutense University of Madrid
90.2K papers, 2.1M citations

92% related

Autonomous University of Barcelona
80.5K papers, 2.3M citations

92% related

University of Valencia
65.6K papers, 1.7M citations

91% related

Ghent University
111K papers, 3.7M citations

90% related

University of Barcelona
108.5K papers, 3.7M citations

90% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202333
2022133
20211,640
20201,619
20191,517
20181,348