267 results on '"Perco P"'
Search Results
2. Association of urinary EGF, FABP3, and VCAM1 levels with the progression of early diabetic kidney disease
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Felix Keller, Sara Denicolò, Johannes Leierer, Maren Kruus, Andreas Heinzel, Michael Kammer, Wenjun Ju, Viji Nair, Frederic Burdet, Mark Ibberson, Rajasree Menon, Edgar Otto, Ye Ji Choi, Laura Pyle, Patricia Ladd, Petter M. Bjornstad, Susanne Eder, Laszlo Rosivall, Patrick Barry Mark, Andrzej Wiecek, Hiddo J. Lamber Heerspink, Matthias Kretzler, Rainer Oberbauer, Gert Mayer, and Paul Perco
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Dermatology ,RL1-803 ,Diseases of the circulatory (Cardiovascular) system ,RC666-701 ,Diseases of the genitourinary system. Urology ,RC870-923 - Abstract
Introduction Diabetic kidney disease (DKD) is a common cause of chronic kidney disease with around 25-40% of patients with diabetes being affected. The course of DKD is variable and estimated glomerular filtration rate (eGFR) and albuminuria, the currently used clinical markers, are not able to accurately predict the individual disease trajectory, in particular in early stages of the disease. The aim of this study was to assess the association of urine levels of selected protein biomarkers with the progression of DKD at an early stage of disease. Methods We measured 22 protein biomarkers using the Mesoscale Discovery platform in 461 urine samples of the PROVALID cohort, an observational study of patients with type 2 diabetes mellitus followed at the primary health care level for a minimum of four years. Odds ratios (OR) were estimated for the effect of marker values above median on fast progression using unadjusted and adjusted logistic regression models. RNA expression at the single cell level in kidney biopsy samples obtained from a cohort of young persons with type 2 diabetes mellitus was in addition determined for markers showing significant associations with disease progression. Results Increased urinary levels of epidermal growth factor (EGF) were linked to lower odds of fast progression (defined as annual eGFR decline greater than 2.58 ml/min per 1.73 m2) with an odds ratio (OR) of 0.60 (95% CI 0.46, 0.78). The association with outcome was even stronger when adjusting for a set of 14 baseline clinical parameters including age, biological sex, eGFR, body mass index, albuminuria, and HbA1c. Elevated urinary levels of fatty acid binding protein 3 (FABP3) and vascular cell adhesion molecule 1 (VCAM1) were each significantly associated with fast progression with an OR of 1.44 (95% CI 1.11, 1.87) and an OR of 1.41 (95% CI 1.08, 1.83), respectively. Enriched expression of EGF and FABP3 was observed in distal convoluted tubular cells and VCAM1 in parietal epithelial cells at single cell level from biopsies of patients with early DKD. Conclusion In summary we show that lower urinary levels of EGF and higher urinary levels of FABP3 and VCAM1 are significantly associated with DKD progression in early-stage disease.
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- 2024
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3. Unveiling Inequality of Atoms in Ultrasmall Pt Clusters: Oxygen Adsorption Limited to the Uppermost Atomic Layer
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Federico Loi, Luca Bignardi, Deborah Perco, Andrea Berti, Paolo Lacovig, Silvano Lizzit, Aras Kartouzian, Ulrich Heiz, Dario Alfè, and Alessandro Baraldi
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clusters ,density functional theories ,graphenes ,platinum ,X‐ray photoelectron spectroscopies ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
The concept of preferential atomic and molecular adsorption site is of primary relevance in heterogeneous catalysis. In the case of ultrasmall size‐selected clusters, distinguishing the role played by each atom in a reaction is extremely challenging due to their reduced size and peculiar structures. Herein, it is revealed how the inequivalent atoms composing graphene‐supported Pt12 and Pt13 clusters behave differently in the photoinduced dissociation of O2, with only those in the uppermost layer of the clusters being involved in the reaction. In this process, the epitaxial graphene support plays a fundamental active role: its corrugation and pinning induced by the presence of the clusters are crucial for defining the preferential adsorption site on the Pt atomic agglomerates, facilitating the lateral diffusion of physisorbed oxygen at a distance that induces its selective adsorption in the topmost layer of the clusters, and inducing an inhomogeneous charge distribution within the clusters which directly affects the O2 adsorption. The inhomogeneous oxidation of the clusters is resolved by means of synchrotron‐based X‐ray photoelectron spectroscopy and supported by ab initio density functional theory calculations. The possibility to identify the active sites on Pt clusters induced by cluster–support interactions has the potential to enhance the experimentally supported design of nanocatalysts.
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- 2024
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4. In-silico human genomics with GeneCards
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Stelzer Gil, Dalah Irina, Stein Tsippi, Satanower Yigeal, Rosen Naomi, Nativ Noam, Oz-Levi Danit, Olender Tsviya, Belinky Frida, Bahir Iris, Krug Hagit, Perco Paul, Mayer Bernd, Kolker Eugene, Safran Marilyn, and Lancet Doron
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GeneCards ,GeneDecks ,Partner Hunter ,Set Distiller ,omics ,genomics ,human genes ,database ,synthetic lethality ,genetic variations ,Medicine ,Genetics ,QH426-470 - Abstract
Abstract Since 1998, the bioinformatics, systems biology, genomics and medical communities have enjoyed a synergistic relationship with the GeneCards database of human genes (http://www.genecards.org). This human gene compendium was created to help to introduce order into the increasing chaos of information flow. As a consequence of viewing details and deep links related to specific genes, users have often requested enhanced capabilities, such that, over time, GeneCards has blossomed into a suite of tools (including GeneDecks, GeneALaCart, GeneLoc, GeneNote and GeneAnnot) for a variety of analyses of both single human genes and sets thereof. In this paper, we focus on inhouse and external research activities which have been enabled, enhanced, complemented and, in some cases, motivated by GeneCards. In turn, such interactions have often inspired and propelled improvements in GeneCards. We describe here the evolution and architecture of this project, including examples of synergistic applications in diverse areas such as synthetic lethality in cancer, the annotation of genetic variations in disease, omics integration in a systems biology approach to kidney disease, and bioinformatics tools.
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- 2011
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5. Identification of endophenotypes supporting outcome prediction in hemodialysis patients based on mechanistic markers of statin treatment
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Johannes Leierer, Madonna Salib, Michail Evgeniou, Patrick Rossignol, Ziad A. Massy, Klaus Kratochwill, Gert Mayer, Bengt Fellström, Nicolas Girerd, Faiez Zannad, and Paul Perco
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Statins ,Gene expression profiling ,Predictive biomarkers ,Patient stratification ,Cox proportional hazards regression models ,Cardiovascular risk ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Background: Statins are widely used to reduce the risk of cardiovascular disease (CVD). Patients with end-stage renal disease (ESRD) on hemodialysis have significantly increased risk of developing CVD. Statin treatment in these patients however did not show a statistically significant benefit in large trials on a patient cohort level. Methods: We generated gene expression profiles for statins to investigate the impact on cellular programs in human renal proximal tubular cells and mesangial cells in-vitro. We subsequently selected biomarkers from key statin-affected molecular pathways and assessed these biomarkers in plasma samples from the AURORA cohort, a double-blind, randomized, multi-center study of patients on hemodialysis or hemofiltration that have been treated with rosuvastatin. Patient clusters (phenotypes) were created based on the identified biomarkers using Latent Class Model clustering and the associations with outcome for the generated phenotypes were assessed using Cox proportional hazards regression models. The multivariable models were adjusted for clinical and biological covariates based on previously published data in AURORA. Results: The impact of statin treatment on mesangial cells was larger as compared with tubular cells with a large overlap of differentially expressed genes identified for atorvastatin and rosuvastatin indicating a predominant drug class effect. Affected molecular pathways included TGFB-, TNF-, and MAPK-signaling and focal adhesion among others. Four patient clusters were identified based on the baseline plasma concentrations of the eight biomarkers. Phenotype 1 was characterized by low to medium levels of the hepatocyte growth factor (HGF) and high levels of interleukin 6 (IL6) or matrix metalloproteinase 2 (MMP2) and it was significantly associated with outcome showing increased risk of developing major adverse cardiovascular events (MACE) or cardiovascular death. Phenotype 2 had high HGF but low Fas cell surface death receptor (FAS) levels and it was associated with significantly better outcome at 1 year. Conclusions: In this translational study, we identified patient subgroups based on mechanistic markers of statin therapy that are associated with disease outcome in patients on hemodialysis.
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- 2024
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6. Urinary peptides provide information about the risk of mortality across a spectrum of diseases and scenarios
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Felix Keller, Joachim Beige, Justyna Siwy, Alexandre Mebazaa, Dewei An, Harald Mischak, Joost P. Schanstra, Marika Mokou, Paul Perco, Jan A. Staessen, Antonia Vlahou, and Agnieszka Latosinska
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Death ,Mass spectrometry ,Peptidomics ,Personalised medicine ,Urinary biomarkers ,Medicine - Abstract
Abstract Background There is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, although the mechanisms causing this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to vulnerabilities that are already present. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides. Methods Urinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated. Results In the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death [adjusted HR 1.2 (95% CI 1.17–1.24)]. The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% [adjusted HR 1.61 (95% CI 1.47–1.76)], consistent with adjusted meta-analytic HR estimate of 1.55 [95% CI 1.39–1.73]. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I (I). Conclusion The COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. This prediction is mainly based on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as a basis for proteomics-guided intervention aiming towards manipulating/ improving collagen turnover, thereby reducing the risk of death.
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- 2023
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7. The highest oxidation state observed in graphene-supported sub-nanometer iron oxide clusters
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Perco, Deborah, Loi, Federico, Bignardi, Luca, Sbuelz, Luca, Lacovig, Paolo, Tosi, Ezequiel, Lizzit, Silvano, Kartouzian, Aras, Heiz, Ueli, and Baraldi, Alessandro
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- 2023
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8. Urinary peptides provide information about the risk of mortality across a spectrum of diseases and scenarios
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Keller, Felix, Beige, Joachim, Siwy, Justyna, Mebazaa, Alexandre, An, Dewei, Mischak, Harald, Schanstra, Joost P., Mokou, Marika, Perco, Paul, Staessen, Jan A., Vlahou, Antonia, and Latosinska, Agnieszka
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- 2023
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9. The highest oxidation state observed in graphene-supported sub-nanometer iron oxide clusters
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Deborah Perco, Federico Loi, Luca Bignardi, Luca Sbuelz, Paolo Lacovig, Ezequiel Tosi, Silvano Lizzit, Aras Kartouzian, Ueli Heiz, and Alessandro Baraldi
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Chemistry ,QD1-999 - Abstract
Iron oxide nanoclusters are of interest for a broad range of applications, but limited experimental information on their oxidation mechanism is available outside of the gas phase. Here, the oxidation of graphene-supported size-selected Fen clusters is studied using high-resolution X-ray Photoelectron Spectroscopy.
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- 2023
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10. Characterization of protein-interaction networks in tumors
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Lukas Arno, Perco Paul, Platzer Alexander, and Mayer Bernd
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be formally represented as graphs, and approximating PINs as undirected graphs allows the network properties to be characterized using well-established graph measures. This paper outlines features of PINs derived from 29 studies on differential gene expression in cancer. For each study the number of differentially regulated genes was determined and used as a basis for PIN construction utilizing the Online Predicted Human Interaction Database. Results Graph measures calculated for the largest subgraph of a PIN for a given differential-gene-expression data set comprised properties reflecting the size, distribution, biological relevance, density, modularity, and cycles. The values of a distinct set of graph measures, namely Closeness Centrality, Graph Diameter, Index of Aggregation, Assortative Mixing Coefficient, Connectivity, Sum of the Wiener Number, modified Vertex Distance Number, and Eigenvalues differed clearly between PINs derived on the basis of differential gene expression data sets characterizing malignant tissue and PINs derived on the basis of randomly selected protein lists. Conclusion Cancer PINs representing differentially regulated genes are larger than those of randomly selected protein lists, indicating functional dependencies among protein lists that can be identified on the basis of transcriptomics experiments. However, the prevalence of hub proteins was not increased in the presence of cancer. Interpretation of such graphs in the context of robustness may yield novel therapies based on synthetic lethality that are more effective than focusing on single-action drugs for cancer treatment.
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- 2007
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11. Large expert-curated database for benchmarking document similarity detection in biomedical literature search
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Brown, Peter, Tan, Aik-Choon, El-Esawi, Mohamed A, Liehr, Thomas, Blanck, Oliver, Gladue, Douglas P, Almeida, Gabriel MF, Cernava, Tomislav, Sorzano, Carlos O, Yeung, Andy WK, Engel, Michael S, Chandrasekaran, Arun Richard, Muth, Thilo, Staege, Martin S, Daulatabad, Swapna V, Widera, Darius, Zhang, Junpeng, Meule, Adrian, Honjo, Ken, Pourret, Olivier, Yin, Cong-Cong, Zhang, Zhongheng, Cascella, Marco, Flegel, Willy A, Goodyear, Carl S, van Raaij, Mark J, Bukowy-Bieryllo, Zuzanna, Campana, Luca G, Kurniawan, Nicholas A, Lalaouna, David, Hüttner, Felix J, Ammerman, Brooke A, Ehret, Felix, Cobine, Paul A, Tan, Ene-Choo, Han, Hyemin, Xia, Wenfeng, McCrum, Christopher, Dings, Ruud PM, Marinello, Francesco, Nilsson, Henrik, Nixon, Brett, Voskarides, Konstantinos, Yang, Long, Costa, Vincent D, Bengtsson-Palme, Johan, Bradshaw, William, Grimm, Dominik G, Kumar, Nitin, Martis, Elvis, Prieto, Daniel, Sabnis, Sandeep C, Amer, Said EDR, Liew, Alan WC, Perco, Paul, Rahimi, Farid, Riva, Giuseppe, Zhang, Chongxing, Devkota, Hari P, Ogami, Koichi, Basharat, Zarrin, Fierz, Walter, Siebers, Robert, Tan, Kok-Hian, Boehme, Karen A, Brenneisen, Peter, Brown, James AL, Dalrymple, Brian P, Harvey, David J, Ng, Grace, Werten, Sebastiaan, Bleackley, Mark, Dai, Zhanwu, Dhariwal, Raman, Gelfer, Yael, Hartmann, Marcus D, Miotla, Pawel, Tamaian, Radu, Govender, Pragashnie, Gurney-Champion, Oliver J, Kauppila, Joonas H, Zhang, Xiaolei, Echeverría, Natalia, Subhash, Santhilal, Sallmon, Hannes, Tofani, Marco, Bae, Taeok, Bosch, Oliver, Cuív, Páraic O, Danchin, Antoine, Diouf, Barthelemy, Eerola, Tuomas, Evangelou, Evangelos, Filipp, Fabian V, Klump, Hannes, Kurgan, Lukasz, Smith, Simon S, Terrier, Olivier, Tuttle, Neil, and Ascher, David B
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Cancer ,Generic health relevance ,RELISH Consortium ,Data Format ,Library and Information Studies - Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.
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- 2019
12. Assessment of Fibrinogen-like 2 (FGL2) in Human Chronic Kidney Disease through Transcriptomics Data Analysis
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Sara Denicolò, Viji Nair, Johannes Leierer, Michael Rudnicki, Matthias Kretzler, Gert Mayer, Wenjun Ju, and Paul Perco
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chronic kidney disease ,renal fibrosis ,FGL2 ,gene expression ,outcome analysis ,Microbiology ,QR1-502 - Abstract
Fibrinogen-like 2 (FGL2) was recently found to be associated with fibrosis in a mouse model of kidney damage and was proposed as a potential therapeutic target in chronic kidney disease (CKD). We assessed the association of renal FGL2 mRNA expression with the disease outcome in two independent CKD cohorts (NEPTUNE and Innsbruck CKD cohort) using Kaplan Meier survival analysis. The regulation of FGL2 in kidney biopsies of CKD patients as compared to healthy controls was further assessed in 13 human CKD transcriptomics datasets. The FGL2 protein expression in human renal tissue sections was determined via immunohistochemistry. The regulators of FGL2 mRNA expression in renal tissue were identified in the co-expression and upstream regulator analysis of FGL2-positive renal cells via the use of single-cell RNA sequencing data from the kidney precision medicine project (KPMP). Higher renal FGL2 mRNA expression was positively associated with kidney fibrosis and negatively associated with eGFR. Renal FGL2 mRNA expression was upregulated in CKD as compared with healthy controls and associated with CKD progression in the Innsbruck CKD cohort (p-value = 0.0036) and NEPTUNE cohort (p-value = 0.0048). The highest abundance of FGL2 protein in renal tissue was detected in the thick ascending limb of the loop of Henle and macula densa, proximal tubular cells, as well as in glomerular endothelial cells. The upstream regulator analysis identified TNF, IL1B, IFNG, NFKB1, and SP1 as factors potentially inducing FGL2-co-expressed genes, whereas factors counterbalancing FGL2-co-expressed genes included GLI1, HNF1B, or PPARGC1A. In conclusion, renal FGL2 mRNA expression is elevated in human CKD, and higher FGL2 levels are associated with fibrosis and worse outcomes.
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- 2022
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13. Using Infodemiology Metrics to Assess Public Interest in Liver Transplantation: Google Trends Analysis
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Maria Effenberger, Andreas Kronbichler, Erica Bettac, Felix Grabherr, Christoph Grander, Timon Erik Adolph, Gert Mayer, Heinz Zoller, Paul Perco, and Herbert Tilg
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundLiver transplantation (LT) is the only curative treatment for end-stage liver disease. Less than 10% of global transplantation needs are met worldwide, and the need for LT is still increasing. The death rates on the waiting list remain too high. ObjectiveIt is, therefore, critical to raise awareness among the public and health care providers and in turn increasingly acquire donors. MethodsWe performed a Google Trends search using the search terms liver transplantation and liver transplant on October 15, 2020. On the basis of the resulting monthly data, the annual average Google Trends indices were calculated for the years 2004 to 2018. We not only investigated the trend worldwide but also used data from the United Network for Organ Sharing (UNOS), Spain, and Eurotransplant. Using pairwise Spearman correlations, Google Trends indices were examined over time and compared with the total number of liver transplants retrieved from the respective official websites of UNOS, the Organización Nacional de Trasplantes, and Eurotransplant. ResultsFrom 2004 to 2018, there was a significant decrease in the worldwide Google Trends index from 78.2 in 2004 to 20.5 in 2018 (–71.2%). This trend was more evident in UNOS than in the Eurotransplant group. In the same period, the number of transplanted livers increased worldwide. The waiting list mortality rate was 31% for Eurotransplant and 29% for UNOS. However, in Spain, where there are excellent awareness programs, the Google Trends index remained stable over the years with comparable, increasing LT numbers but a significantly lower waiting list mortality (15%). ConclusionsPublic awareness in LT has decreased significantly over the past two decades. Therefore, novel awareness programs should be initialized.
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- 2021
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14. Canagliflozin reduces inflammation and fibrosis biomarkers: a potential mechanism of action for beneficial effects of SGLT2 inhibitors in diabetic kidney disease
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Heerspink, Hiddo J. L., Perco, Paul, Mulder, Skander, Leierer, Johannes, Hansen, Michael K., Heinzel, Andreas, and Mayer, Gert
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- 2019
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15. Validation of systems biology derived molecular markers of renal donor organ status associated with long term allograft function
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Paul Perco, Andreas Heinzel, Johannes Leierer, Stefan Schneeberger, Claudia Bösmüller, Rupert Oberhuber, Silvia Wagner, Franziska Engler, and Gert Mayer
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Medicine ,Science - Abstract
Abstract Donor organ quality affects long term outcome after renal transplantation. A variety of prognostic molecular markers is available, yet their validity often remains undetermined. A network-based molecular model reflecting donor kidney status based on transcriptomics data and molecular features reported in scientific literature to be associated with chronic allograft nephropathy was created. Significantly enriched biological processes were identified and representative markers were selected. An independent kidney pre-implantation transcriptomics dataset of 76 organs was used to predict estimated glomerular filtration rate (eGFR) values twelve months after transplantation using available clinical data and marker expression values. The best-performing regression model solely based on the clinical parameters donor age, donor gender, and recipient gender explained 17% of variance in post-transplant eGFR values. The five molecular markers EGF, CD2BP2, RALBP1, SF3B1, and DDX19B representing key molecular processes of the constructed renal donor organ status molecular model in addition to the clinical parameters significantly improved model performance (p-value = 0.0007) explaining around 33% of the variability of eGFR values twelve months after transplantation. Collectively, molecular markers reflecting donor organ status significantly add to prediction of post-transplant renal function when added to the clinical parameters donor age and gender.
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- 2018
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16. Synthetic lethality guiding selection of drug combinations in ovarian cancer.
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Andreas Heinzel, Maximilian Marhold, Paul Mayer, Michael Schwarz, Erwin Tomasich, Arno Lukas, Michael Krainer, and Paul Perco
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Medicine ,Science - Abstract
BACKGROUND:Synthetic lethality describes a relationship between two genes where single loss of either gene does not trigger significant impact on cell viability, but simultaneous loss of both gene functions results in lethality. Targeting synthetic lethal interactions with drug combinations promises increased efficacy in tumor therapy. MATERIALS AND METHODS:We established a set of synthetic lethal interactions using publicly available data from yeast screens which were mapped to their respective human orthologs using information from orthology databases. This set of experimental synthetic lethal interactions was complemented by a set of predicted synthetic lethal interactions based on a set of protein meta-data like e.g. molecular pathway assignment. Based on the combined set, we evaluated drug combinations used in late stage clinical development (clinical phase III and IV trials) or already in clinical use for ovarian cancer with respect to their effect on synthetic lethal interactions. We furthermore identified a set of drug combinations currently not being tested in late stage ovarian cancer clinical trials that however have impact on synthetic lethal interactions thus being worth of further investigations regarding their therapeutic potential in ovarian cancer. RESULTS:Twelve of the tested drug combinations addressed a synthetic lethal interaction with the anti-VEGF inhibitor bevacizumab in combination with paclitaxel being the most studied drug combination addressing the synthetic lethal pair between VEGFA and BCL2. The set of 84 predicted drug combinations for example holds the combination of the PARP inhibitor olaparib and paclitaxel, which showed efficacy in phase II clinical studies. CONCLUSION:A set of drug combinations currently not tested in late stage ovarian cancer clinical trials was identified having impact on synthetic lethal interactions thus being worth of further investigations regarding their therapeutic potential in ovarian cancer.
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- 2019
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17. Computational drug repositioning of clopidogrel as a novel therapeutic option for focal segmental glomerulosclerosis.
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Gebeshuber, Christoph A., Daniel-Fischer, Lisa, Regele, Heinz, Schachner, Helga, Aufricht, Christoph, Kornauth, Christoph, Ley, Matthias, Alper, Seth L., Herzog, Rebecca, Kratochwill, Klaus, and Perco, Paul
- Abstract
Focal segmental glomerulosclerosis (FSGS) is a glomerular lesion often associated with nephrotic syndrome. It is also associated with a high risk of progression to end-stage kidney disease. Current treatment of FSGS is limited to systemic corticosteroids or calcineurin inhibition, along with inhibitors of the renin-angiotensin-aldosterone system. FSGS is heterogeneous in etiology, and novel therapies targeting specific, dysregulated molecular pathways represent a major unmet medical need. We have generated a network-based molecular model of FSGS pathophysiology using previously established systems biology workflows to allow computational evaluation of compounds for their predicted interference with molecular processes contributing to FSGS. We identified the anti-platelet drug clopidogrel as a therapeutic option to counterbalance dysregulated FSGS pathways. This prediction of our computational screen was validated by testing clopidogrel in the adriamycin FSGS mouse model. Clopidogrel improved key FSGS outcome parameters and significantly reduced urinary albumin to creatinine ratio (P < 0.01) and weight loss (P < 0.01), and ameliorated histopathological damage (P < 0.05). Clopidogrel is used to treat several cardiovascular diseases linked to chronic kidney disease. Clopidogrel's favorable safety profile and its efficacy in the adriamycin mouse FSGS model thus recommend it as an attractive drug repositioning candidate for clinical trial in FSGS. [ABSTRACT FROM AUTHOR]
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- 2023
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18. A panel of novel biomarkers representing different disease pathways improves prediction of renal function decline in type 2 diabetes.
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Michelle J Pena, Andreas Heinzel, Georg Heinze, Alaa Alkhalaf, Stephan J L Bakker, Tri Q Nguyen, Roel Goldschmeding, Henk J G Bilo, Paul Perco, Bernd Mayer, Dick de Zeeuw, and Hiddo J Lambers Heerspink
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Medicine ,Science - Abstract
ObjectiveWe aimed to identify a novel panel of biomarkers predicting renal function decline in type 2 diabetes, using biomarkers representing different disease pathways speculated to contribute to the progression of diabetic nephropathy.Research design and methodsA systematic data integration approach was used to select biomarkers representing different disease pathways. Twenty-eight biomarkers were measured in 82 patients seen at an outpatient diabetes center in The Netherlands. Median follow-up was 4.0 years. We compared the cross-validated explained variation (R2) of two models to predict eGFR decline, one including only established risk markers, the other adding a novel panel of biomarkers. Least absolute shrinkage and selection operator (LASSO) was used for model estimation. The C-index was calculated to assess improvement in prediction of accelerated eGFR decline defined as ResultsPatients' average age was 63.5 years and baseline eGFR was 77.9 mL/min/1.73m2. The average rate of eGFR decline was -2.0 ± 4.7 mL/min/1.73m2/year. When modeled on top of established risk markers, the biomarker panel including matrix metallopeptidases, tyrosine kinase, podocin, CTGF, TNF-receptor-1, sclerostin, CCL2, YKL-40, and NT-proCNP improved the explained variability of eGFR decline (R2 increase from 37.7% to 54.6%; p=0.018) and improved prediction of accelerated eGFR decline (C-index increase from 0.835 to 0.896; p=0.008).ConclusionsA novel panel of biomarkers representing different pathways of renal disease progression including inflammation, fibrosis, angiogenesis, and endothelial function improved prediction of eGFR decline on top of established risk markers in type 2 diabetes. These results need to be confirmed in a large prospective cohort.
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- 2015
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19. Large expert-curated database for benchmarking document similarity detection in biomedical literature search
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Brown, P, Zhou, Y, Tan, A, El-Esawi, M, Liehr, T, Blanck, O, Gladue, D, Almeida, G, Cernava, T, Sorzano, C, Yeung, A, Engel, M, Chandrasekaran, A, Muth, T, Staege, M, Daulatabad, S, Widera, D, Zhang, J, Meule, A, Honjo, K, Pourret, O, Yin, C, Zhang, Z, Cascella, M, Flegel, W, Goodyear, C, van Raaij, M, Bukowy-Bieryllo, Z, Campana, L, Kurniawan, N, Lalaouna, D, Huttner, F, Ammerman, B, Ehret, F, Cobine, P, Tan, E, Han, H, Xia, W, Mccrum, C, Dings, R, Marinello, F, Nilsson, H, Nixon, B, Voskarides, K, Yang, L, Costa, V, Bengtsson-Palme, J, Bradshaw, W, Grimm, D, Kumar, N, Martis, E, Prieto, D, Sabnis, S, Amer, S, Liew, A, Perco, P, Rahimi, F, Riva, G, Zhang, C, Devkota, H, Ogami, K, Basharat, Z, Fierz, W, Siebers, R, Tan, K, Boehme, K, Brenneisen, P, Brown, J, Dalrymple, B, Harvey, D, Ng, G, Werten, S, Bleackley, M, Dai, Z, Dhariwal, R, Gelfer, Y, Hartmann, M, Miotla, P, Tamaian, R, Govender, P, Gurney-Champion, O, Kauppila, J, Zhang, X, Echeverria, N, Subhash, S, Sallmon, H, Tofani, M, 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- Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.
- Published
- 2019
20. microRNA-182-5p Regulates Post-Transplant Acute Kidney Injury.: Abstract# A505
- Author
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Wilflingseder, J., Sunzenauer, J., Toronyi, E., Heinzel, A., Kainz, A., Perco, P., Mayer, B., Langer, R., and Oberbauer, R.
- Published
- 2014
21. Evaluation of the Zucker diabetic fatty (ZDF) rat as a model for human disease based on urinary peptidomic profiles.
- Author
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Justyna Siwy, Carlamaria Zoja, Julie Klein, Ariela Benigni, Wiliam Mullen, Bernd Mayer, Harald Mischak, Joachim Jankowski, Robert Stevens, Antonia Vlahou, Sophia Kossida, Paul Perco, and Ferdinand H Bahlmann
- Subjects
Medicine ,Science - Abstract
Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level.
- Published
- 2012
- Full Text
- View/download PDF
22. Renal Allograft Rejection and Delayed Graft Funciton Regulated by miRNAs.: Abstract# 1447 Poster Board #-Session: P9-IV
- Author
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Wilflingseder, J., Regele, H., Kainz, A., Perco, P., Soleiman, A., Mühlbacher, F., Mayer, B., and Oberbauer, R.
- Published
- 2012
23. miRNA-Regulation bei akuter Nierentransplantatabstoβung und akutem Nierentransplantatversagen: 005
- Author
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Wilflingseder, J., Regele, H., Kainz, A., Perco, P., Mayer, B., and Oberbauer, R.
- Published
- 2010
24. Biocompatibility of haemodialysis membranes determined by gene expression of human leucocytes: a crossover study
- Author
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Wilflingseder, J., Perco, P., Kainz, A., Korbély, R., Mayer, B., and Oberbauer, R.
- Published
- 2008
25. Large expert-curated database for benchmarking document similarity detection in biomedical literature search
- Author
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Zaritsky, A. Zhang, Y. Zhao, H. Zuckerman, H. Lyu, R. Pullan, W. RELISH Consortium
- Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press.
- Published
- 2019
26. Large expert-curated database for benchmarking document similarity detection in biomedical literature search
- Author
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Brown, P., Zhou, Y., Tan, A.C., El-Esawi, M.A., Liehr, T., Blanck, O., Gladue, D.P., Almeida, G.M.F., Cernava, T., Sorzano, C.O., Yeung, A.W.K., Engel, M.S., Chandrasekaran, A.R., Muth, T., Staege, M.S., Daulatabad, S.V., Widera, D., Zhang, J., Meule, A., Honjo, K., Pourret, O., Yin, C.C., Zhang, Z., Cascella, M., Flegel, W.A., Goodyear, C.S., van Raaij, M.J., Bukowy-Bieryllo, Z., Campana, L.G., Kurniawan, N.A., Lalaouna, D., Hüttner, F.J., Ammerman, B.A., Ehret, F., Cobine, P.A., Tan, E.C., Han, H., Xia, W., McCrum, C., Dings, R.P.M., Marinello, F., Nilsson, H., Nixon, B., Voskarides, K., Yang, L., Costa, V.D., Bengtsson-Palme, J., Bradshaw, W., Grimm, D.G., Kumar, N., Martis, E., Prieto, D., Sabnis, S.C., Amer, S.E.D.R., Liew, A.W.C., Perco, P., Rahimi, F., Riva, G., Zhang, C., Devkota, H.P., Ogami, K., Basharat, Z., Fierz, W., Siebers, R., Tan, K.H., Boehme, K.A., Brenneisen, P., Brown, J.A.L., Dalrymple, B.P., Harvey, D.J., Ng, G., Werten, S., Bleackley, M., Dai, Z., Dhariwal, R., Gelfer, Y., Hartmann, M.D., Miotla, P., Tamaian, R., Govender, P., Gurney-Champion, O.J., Kauppila, J.H., Zhang, X., Echeverría, N., Subhash, S., Sallmon, H., Tofani, M., Bae, T., Bosch, O., Cuív, P.O., Danchin, A., Diouf, B., Eerola, T., Evangelou, E., Filipp, F., Klump, H., Kurgan, L., Smith, S.S., Terrier, O., Tuttle, N., and Wiener, J.M.
- Abstract
© The Author(s) 2019. Published by Oxford University Press. Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.
- Published
- 2019
27. In vitro-transcriptional response of polymorphonuclear leukocytes following contact with different antigens
- Author
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Hochegger, K., Perco, P., Enrich, J., Mayer, B., Mayer, G., Rosenkranz, A. R., and Rudnicki, M.
- Published
- 2007
28. Gene expression profiles of human proximal tubular epithelial cells in proteinuric nephropathies
- Author
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Rudnicki, M, Eder, S, Perco, P, Enrich, J, Scheiber, K, Koppelstätter, C, Schratzberger, G, Mayer, B, Oberbauer, R, Meyer, T W, and Mayer, G
- Published
- 2007
29. Protein biomarkers associated with acute renal failure and chronic kidney disease
- Author
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Perco, P., Pleban, C., Kainz, A., Lukas, A., Mayer, G., Mayer, B., and Oberbauer, R.
- Published
- 2006
30. Situazione attuale del gatto selvatico Felis silvestris silvestris e della lince Lynx lynx nell’area delle Alpi sud-orientali
- Author
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Ragni, Bernardino, Lapini, Luca, and Perco, Franco
- Published
- 1989
31. L’Avifauna delle province di Trieste e Gorizia, fino all’Isonzo
- Author
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Perco, Fabio and Utmar, Paolo
- Published
- 1989
32. RHD sequencing: a new tool for decision making on transfusion therapy and provision of Rh prophylaxis
- Author
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Legler, T. J., Maas, J. H., Köhler, M., Wagner, T., Daniels, G. L., Perco, P., and Panzer, S.
- Published
- 2001
33. The kidney—more than the sum of its cellular parts
- Author
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Perco, Paul and Mayer, Gert
- Abstract
The kidney is a complex organ composed of a plethora of highly specialized cells that talk to each other. The tubuloglomerular feedback is a prototypical example of cell–cell interactions adapting glomerular filtration rate. With the advent of single-cell sequencing techniques, spatial transcriptomics, and bioinformatical cell–cell interaction analyses, we are now able to much better decipher the complex physiology and pathophysiology of these crosstalks, and identify new biomarkers as well as novel treatment options.
- Published
- 2022
- Full Text
- View/download PDF
34. Extracellular matrix protein signature of recurrent spontaneous cervical artery dissection.
- Author
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Mayer, Lukas, Pechlaner, Raimund, Barallobre-Barreiro, Javier, Boehme, Christian, Toell, Thomas, Lynch, Marc, Yin, Xiaoke, Willeit, Johann, Gizewski, Elke R., Perco, Paul, Ratzinger, Gudrun, Kiechl, Stefan, Mayr, Manuel, Knoflach, Michael, and Mayer-Suess, Lukas
- Published
- 2020
- Full Text
- View/download PDF
35. Baseline urinary metabolites predict albuminuria response to spironolactone in type 2 diabetes.
- Author
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Mulder, Skander, Perco, Paul, Oxlund, Christina, Mehdi, Uzma F., Hankemeier, Thomas, Jacobsen, Ib A., Toto, Robert, Heerspink, Hiddo J.L., and Pena, Michelle J.
- Abstract
The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in subjects with diabetic kidney disease, albeit with a large variability between individuals. Identifying novel biomarkers that predict response to therapy may help to tailor spironolactone therapy. We aimed to identify a set of metabolites for prediction of albuminuria response to spironolactone in subjects with type 2 diabetes. Systems biology molecular process analysis was performed a priori to identify metabolites linked to molecular disease processes and drug mechanism of action. Individual subject data and urine samples were used from 2 randomized placebo controlled double blind clinical trials (NCT01062763, NCT00381134). A urinary metabolite score was developed to predict albuminuria response to spironolactone therapy using penalized ridge regression with leave-one-out cross validation. Bioinformatic analysis identified a set of 18 metabolites linked to a diabetic kidney disease molecular model and potentially affected by spironolactone mechanism of action. Spironolactone reduced UACR relative to placebo by median -42% (25th to 75% percentile -65 to 6) and -29% (25th to 75% percentile -37 to -1) in the test and replication cohorts, respectively. In the test cohort, UACR reduction was higher in the lowest tertile of the baseline urinary metabolite score compared with middle and upper tertiles -58% (25th to 75% percentile -78 to 33), -28% (25th to 75% percentile -46 to 8), -40% (25th to 75% percentile -52% to 31), respectively, P = 0.001 for trend). In the replication cohort, UACR reduction was -54% (25th to 75% percentile -65 to -50), -41 (25th to 75% percentile -46% to 30), and -17% (25th to 75% percentile -36 to 5), respectively, P = 0.010 for trend). We identified a set of 18 urinary metabolites through systems biology to predict albuminuria response to spironolactone in type 2 diabetes. These data suggest that urinary metabolites may be used as a tool to tailor optimal therapy and move in the direction of personalized medicine. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
36. Proteomic-Biostatistic Integrated Approach for Finding the Underlying Molecular Determinants of Hypertension in Human Plasma
- Author
-
Gajjala, P, Jankowski, V, Heinze, G, Bilo, G, Zanchetti, A, Noels, H, Liehn, E, Perco, P, Schulz, A, Delles, C, Kork, F, Biessen, E, Narkiewicz, K, Kawecka Jaszcz, K, Floege, J, Soranna, D, Zidek, W, Jankowski, J, Jankowski, J., BILO, GRZEGORZ, SORANNA, DAVIDE, Gajjala, P, Jankowski, V, Heinze, G, Bilo, G, Zanchetti, A, Noels, H, Liehn, E, Perco, P, Schulz, A, Delles, C, Kork, F, Biessen, E, Narkiewicz, K, Kawecka Jaszcz, K, Floege, J, Soranna, D, Zidek, W, Jankowski, J, Jankowski, J., BILO, GRZEGORZ, and SORANNA, DAVIDE
- Abstract
Despite advancements in lowering blood pressure, the best approach to lower it remains controversial because of the lack of information on the molecular basis of hypertension. We, therefore, performed plasma proteomics of plasma from patients with hypertension to identify molecular determinants detectable in these subjects but not in controls and vice versa. Plasma samples from hypertensive subjects (cases; n=118) and controls (n=85) from the InGenious HyperCare cohort were used for this study and performed mass spectrometric analysis. Using biostatistical methods, plasma peptides specific for hypertension were identified, and a model was developed using least absolute shrinkage and selection operator logistic regression. The underlying peptides were identified and sequenced off-line using matrix-assisted laser desorption ionization orbitrap mass spectrometry. By comparison of the molecular composition of the plasma samples, 27 molecular determinants were identified differently expressed in cases from controls. Seventy percent of the molecular determinants selected were found to occur less likely in hypertensive patients. In cross-validation, the overall R 2 was 0.434, and the area under the curve was 0.891 with 95% confidence interval 0.8482 to 0.9349, P<0.0001. The mean values of the cross-validated proteomic score of normotensive and hypertensive patients were found to be -2.007±0.3568 and 3.383±0.2643, respectively, P<0.0001. The molecular determinants were successfully identified, and the proteomic model developed shows an excellent discriminatory ability between hypertensives and normotensives. The identified molecular determinants may be the starting point for further studies to clarify the molecular causes of hypertension
- Published
- 2017
37. Disease map-based biomarker selection and pre-validation for bladder cancer invasiveness and recurrence prediction
- Author
-
De Paoli, M., Perco, P., Mühlberger, I., Lukas, A., Pandha, H., Morgan, R., Feng, G., Marquette, C.A, AXO Science (Axo S), Génie Enzymatique, Membrane Biomimétique et Assemblages Supramoléculaires (GEMBAS), Institut de Chimie et Biochimie Moléculaires et Supramoléculaires (ICBMS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut de Chimie du CNRS (INC)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut de Chimie du CNRS (INC)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)
- Subjects
recurrence ,[CHIM.ORGA]Chemical Sciences/Organic chemistry ,invasiveness ,bladder cancer ,[SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biochemistry [q-bio.BM] ,Biomarkers - Abstract
International audience; CONTEXT:Urinary biomarkers are promising as simple alternatives to cystoscopy for the diagnosis of de novo and recurrent bladder cancer.OBJECTIVE:To identify a highly sensitive and specific biomarker candidate set with potential clinical utility in bladder cancer.MATERIALS AND METHODS:Urinary biomarker concentrations were determined by ELISA. The performance of individual markers and marker combinations was assessed using ROC analysis.RESULTS:A five-biomarker panel (IL8, MMP9, VEGFA, PTGS2 and EN2) was defined from the candidate set.DISCUSSION AND CONCLUSION:This panel showed a better overall performance than the best individual marker. Further validation studies are needed to evaluate its clinical utility in bladder cancer.
- Published
- 2015
- Full Text
- View/download PDF
38. Barriere di sicurezza - L’urto più probabile
- Author
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Marchionna, Aurelio, Perco, P., Marchionna, Aurelio, and Perco, P.
- Published
- 2009
39. POTENZIALITA' OFFERTE DAL DIAGRAMMA DELLE VELOCITA' OPERATIVE NELLA DEFINIZIONE DEGLI INERVENTI DI ADEGUAMENTO DELLE STRADE ESISTENTI
- Author
-
Marchionna, Aurelio, Perco, P., Marchionna, Aurelio, and Perco, P.
- Published
- 2006
40. Italian Operating Speed Prediction Model for Two Lane Rural Road
- Author
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Crisman, Bruno, Marchionna, A, Perco, P, Roberti, Roberto, Robba, A., Crisman, Bruno, Marchionna, A, Perco, P, Roberti, Roberto, and Robba, A.
- Published
- 2005
41. Influence of spiral length on path of vehicle entering a curve
- Author
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PERCO P, CRISMAN, BRUNO, Perco, P, and Crisman, Bruno
- Published
- 2004
42. Considerazioni critiche sull'inserimetno delle curve di raccordo nei tracciati stradali
- Author
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CRISMAN, BRUNO, MARCHIONNA A, PERCO P, ROBERTI, ROBERTO, Crisman, Bruno, Marchionna, A, Perco, P, and Roberti, Roberto
- Published
- 2002
43. Integrative analysis of prognostic biomarkers derived from multiomics panels helps discrimination of chronic kidney disease trajectories in people with type 2 diabetes
- Author
-
Kammer, Michael, Heinzel, Andreas, Willency, Jill A., Duffin, Kevin L., Mayer, Gert, Simons, Kai, Gerl, Mathias J., Klose, Christian, Heinze, Georg, Reindl-Schwaighofer, Roman, Hu, Karin, Perco, Paul, Eder, Susanne, Rosivall, Laszlo, Mark, Patrick B., Ju, Wenjun, Kretzler, Matthias, McCarthy, Mark I., Heerspink, Hiddo L., Wiecek, Andrzej, Gomez, Maria F., and Oberbauer, Rainer
- Abstract
Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73 m2, urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor.
- Published
- 2019
- Full Text
- View/download PDF
44. Photogrammetric Surveys for the Definition of a Model for a Passing Sight Distance Computation
- Author
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Marchionna, Aurelio, Crisman, Bruno, Perco, P., Marchionna, Aurelio, Crisman, Bruno, and Perco, P.
- Published
- 2000
45. PP.28.24
- Author
-
Robinson, S., primary, Perco, P., additional, Husi, H., additional, Köck, T., additional, Mischak, H., additional, Jennings, A., additional, Monleon, D., additional, Ravassa, S., additional, Leenders, J., additional, Jankowski, J., additional, Chatzikyrkou, C., additional, Pieske, B., additional, Staessen, J.A., additional, Padmanabhan, S., additional, Zanchetti, A., additional, Dominiczak, A.F., additional, Delles, C., additional, and Consortium, Eu-Mascara, additional
- Published
- 2015
- Full Text
- View/download PDF
46. Country Report: Update on geometric Design Activities in Italy
- Author
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Cafiso, Salvatore, Lamberti, R., Marchionna, A., and Perco, P.
- Published
- 2010
47. Deceleration model for two-lane rural roads
- Author
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Crisman, B., Perco, P., Robba, A., ROBERTO ROBERTI, Crisman, Bruno, Perco, Paolo, A., Robba, and Roberti, Roberto
- Subjects
deceleration model ,Road safety ,operating speed - Abstract
The operating speed-profile is an important tool for the safety evaluations of new and existing roads. In particular, the operating speed-profile is useful to evaluate the consistency of an alignment identifying the excessive speed differential and to calculate the correct sight distance necessary along the road. Several models have been developed to predict the operating speed on curves and on tangents of two-lane rural roads. However, to trace an operating speed-profile close to the real speed-profile, it is necessary to join these speeds on successive elements using deceleration and acceleration rates that represent the real rates experienced by drivers. Therefore, to develop a deceleration model that could be effectively used in the operating speed-profile models, driver speed reduction behaviour and its dependence on the geometric characteristics of the road were investigated on 18 horizontal curves of two-lane rural roads. The results show that a single constant deceleration rate does not effectively describe the observed speed reduction behaviour. Therefore, its use in a speed-profile model results in a wrong estimation of the real distance used to decelerate before a curve. In fact, the deceleration rate observed varies significantly between the various curves. The data analysis revealed that the deceleration rate is correlated to the radius, the curve length, the approaching speed and the speed reduction. Therefore, two deceleration models were developed. The first one estimates the deceleration rate as a function of the radius of the impending curve and the second one as a function of the approaching speed and of the speed reduction. These models can be effectively used for the construction of the operating speed-profile because they predict deceleration rates consistent with the speed reduction behaviour observed and, consequently, deceleration lengths closer to the real distance travelled during the speed reduction.
- Published
- 2007
48. Proteomic-Biostatistic Integrated Approach for Finding the Underlying Molecular Determinants of Hypertension in Human Plasma.
- Author
-
Jankowski, Vera, Noels, Heidi, Liehn, Elisa, Kork, Felix, Gajjala, Prathibha R., Biessen, Erik, Jankowski, Joachim, Narkiewicz, Krzysztof, Kawecka-Jaszcz, Kalina, Floege, Juergen, Soranna, Davide, Heinze, Georg, Bilo, Grzegorz, Zanchetti, Alberto, Perco, Paul, Schulz, Anna, Zidek, Walter, and Delles, Christian
- Abstract
Despite advancements in lowering blood pressure, the best approach to lower it remains controversial because of the lack of information on the molecular basis of hypertension. We, therefore, performed plasma proteomics of plasma from patients with hypertension to identify molecular determinants detectable in these subjects but not in controls and vice versa. Plasma samples from hypertensive subjects (cases; n=118) and controls (n=85) from the InGenious HyperCare cohort were used for this study and performed mass spectrometric analysis. Using biostatistical methods, plasma peptides specific for hypertension were identified, and a model was developed using least absolute shrinkage and selection operator logistic regression. The underlying peptides were identified and sequenced off-line using matrix-assisted laser desorption ionization orbitrap mass spectrometry. By comparison of the molecular composition of the plasma samples, 27 molecular determinants were identified differently expressed in cases from controls. Seventy percent of the molecular determinants selected were found to occur less likely in hypertensive patients. In cross-validation, the overall R2 was 0.434, and the area under the curve was 0.891 with 95% confidence interval 0.8482 to 0.9349, P<0.0001. The mean values of the cross-validated proteomic score of normotensive and hypertensive patients were found to be -2.007±0.3568 and 3.383±0.2643, respectively, P<0.0001. The molecular determinants were successfully identified, and the proteomic model developed shows an excellent discriminatory ability between hypertensives and normotensives. The identified molecular determinants may be the starting point for further studies to clarify the molecular causes of hypertension. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
49. microRNA-182-5p Regulates Post-Transplant Acute Kidney Injury.
- Author
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Wilflingseder, J., primary, Sunzenauer, J., additional, Toronyi, E., additional, Heinzel, A., additional, Kainz, A., additional, Perco, P., additional, Mayer, B., additional, Langer, R., additional, and Oberbauer, R., additional
- Published
- 2014
- Full Text
- View/download PDF
50. AKI - human studies
- Author
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Kutlay, S., primary, Kurultak, I., additional, Nergizoglu, G., additional, Erturk, S., additional, Karatan, O., additional, Azevedo, P., additional, Pinto, C. T., additional, Pereira, C. M., additional, Marinho, A., additional, Vanmassenhove, J., additional, Hoste, E., additional, Glorieux, G., additional, Dhondt, A., additional, Vanholder, R., additional, Van Biesen, W., additional, Rei, S., additional, Aleksandrova, I., additional, Kiselev, V., additional, Ilynskiy, M., additional, Berdnikov, G., additional, Marchenkova, L., additional, Daher, E. F., additional, Vieira, A. P. F., additional, Souza, J. B., additional, Falcao, F. S., additional, Costa, C. R., additional, Fernandes, A. A. C. S., additional, Mota, R. M. S., additional, Lima, R. S. A., additional, Silva Junior, G. B., additional, Ulusal Okyay, G., additional, Erten, Y., additional, Er, R., additional, Aybar, M., additional, Inal, S., additional, Tekbudak, M., additional, Aygencel, G., additional, Onec, K., additional, Bali, M., additional, Sindel, S., additional, Soto, K., additional, Fidalgo, P., additional, Papoila, A. L., additional, Lentini, P., additional, Zanoli, L., additional, Granata, A., additional, Contestabile, A., additional, Basso, A., additional, Berlingo, G., additional, de Cal, M., additional, Pellanda, V., additional, Dell'Aquila, R., additional, Fortrie, G., additional, Stads, S., additional, van Bommel, J., additional, Zietse, R., additional, Betjes, M. G., additional, Berrada, A., additional, Arias, C., additional, Riera, M., additional, Orfila, M. A., additional, Rodriguez, E., additional, Barrios, C., additional, Peruzzi, L., additional, Chiale, F., additional, Camilla, R., additional, Martano, C., additional, Cresi, F., additional, Bertino, E., additional, Coppo, R., additional, Klimenko, A., additional, Villevalde, S., additional, Efremovtseva, M., additional, Kobalava, Z., additional, Pipili, C., additional, Ioannidou, S., additional, Kokkoris, S., additional, Poulaki, S., additional, Tripodaki, E.-S., additional, Parisi, M., additional, Papastylianou, A., additional, Nanas, S., additional, Wang, Y.-n., additional, Cheng, H., additional, Chen, Y.-p., additional, Wen, Z., additional, Li, X., additional, Shen, P., additional, Zou, Y., additional, Lu, Y., additional, Ma, X., additional, Chen, Y., additional, Ren, H., additional, Chen, X., additional, Chen, N., additional, Yue, T., additional, Elmamoun, S., additional, Wodeyar, H., additional, Goldsmith, C., additional, Abraham, A., additional, Wootton, A., additional, Ahmed, S., additional, Hill, C., additional, Curtis, S., additional, Miller, A., additional, Hine, T., additional, Stevens, K. K., additional, Patel, R. K., additional, Mark, P. B., additional, Delles, C., additional, Jardine, A. G., additional, Wilflingseder, J., additional, Heinzel, A., additional, Mayer, P., additional, Perco, P., additional, Kainz, A., additional, Mayer, B., additional, Oberbauer, R., additional, Huang, T.-M., additional, Wu, V.-C., additional, Park, D. J., additional, Bae, E. J., additional, Kang, Y.-J., additional, Cho, H. S., additional, Chang, S.-h., additional, Stramana, R., additional, Cognolato, D., additional, Baiocchi, M., additional, Chiella, B. M., additional, Pilla, C., additional, Balbinotto, A., additional, Antunes, V. H., additional, Heglert, A., additional, Collares, F. M., additional, Thome, F. S., additional, Gjyzari, A., additional, Thereska, N., additional, Xhango, O., additional, Xue, J., additional, Chen, M. C., additional, Wang, L., additional, Chen, Y. J., additional, Sun, X. Z., additional, An, W. S., additional, Kim, E. S., additional, Son, Y. K., additional, Kim, S. E., additional, Kim, K. H., additional, Oh, Y. J., additional, Tsai, H.-B., additional, Ko, W.-J., additional, Chao, C.-T., additional, Aarnoudse, A.-J. L., additional, Peride, I., additional, Radulescu, D., additional, Niculae, A., additional, Ciocalteu, A., additional, Checherita, A.-I., additional, Kao, C.-C., additional, Wang, C.-Y., additional, Lai, C.-F., additional, Chen, H.-H., additional, Wu, K.-D., additional, Klaus, F., additional, Goldani, J. C., additional, Cantisani, G., additional, Zanotelli, M. L., additional, Carvalho, L., additional, Klaus, D., additional, Garcia, V. D., additional, Keitel, E., additional, Hussaini, S. M., additional, Rao, P. N., additional, Kul, A., additional, Ye, N., additional, Zhang, Y., additional, Baines, R., additional, Westacott, R., additional, Trew, J., additional, Kirtley, J., additional, Selby, N., additional, Carr, S., additional, Xu, G., additional, Steffgen, J., additional, Blaschke, S., additional, Brun-Schulte-Wissing, N., additional, Pagel, P., additional, Huber, F., additional, Mapes, J., additional, Jaehnige, A., additional, Pestel, S., additional, Deray, G., additional, Rouviere, O., additional, Bacigalupo, L., additional, Maes, B., additional, Hannedouche, T., additional, Vrtovsnik, F., additional, Rigothier, C., additional, Billiouw, J.-M., additional, Campioni, P., additional, Marti-Bonmati, L., additional, Gao, Y.-m., additional, Li, D., additional, Woo, S., additional, Lee, J., additional, Noh, H., additional, Kwon, S. H., additional, Han, D. C., additional, Hetherington, L., additional, Valluri, A., additional, McQuarrie, E., additional, Fleming, S., additional, Geddes, C., additional, Bell, S., additional, MacKinnon, B., additional, Patton, A., additional, Sneddon, J., additional, Donnan, P., additional, Vadiveloo, T., additional, Marwick, C., additional, Bennie, M., additional, Davey, P., additional, Yasuda, H., additional, Tsuji, N., additional, Tsuji, T., additional, Iwakura, T., additional, Ohashi, N., additional, Kato, A., additional, Fujigaki, Y., additional, Sasaki, S., additional, Kawarazaki, H., additional, Shibagaki, Y., additional, Kimura, K., additional, Lingaraju, U., additional, Rajanna, S., additional, Radhakrishnan, H., additional, Parekh, A., additional, Sreedhar, C. G., additional, Sarvi, R., additional, Rainone, F., additional, Merlino, L., additional, Ritchie, J. P., additional, Kalra, P. A., additional, Jacinto, C. N., additional, Abreu, K. L. S., additional, Neves, M., additional, Baptista, J. P., additional, Rodrigues, L., additional, Pinho, J., additional, Teixeira, L., additional, Pimentel, J., additional, Gonzalez Sanchidrian, S., additional, Rangel Hidalgo, G., additional, Cebrian Andrada, C., additional, Deira Lorenzo, J., additional, Marin Alvarez, J., additional, Garcia-Bernalt Funes, V., additional, Gallego Dominguez, S., additional, Labrador Gomez, P., additional, Castellano Cervino, I., additional, Novillo Santana, R., additional, Gomez-Martino Arroyo, J., additional, Kim, Y., additional, Choi, B. S., additional, Kim, Y. o., additional, Yoon, S. A., additional, Lin, M.-C., additional, Wang, W.-J., additional, Melo, M. J., additional, Lopes, J. A., additional, Raimundo, M., additional, Fragoso, A., additional, Antunes, F., additional, Martin-Moreno, P. L., additional, Varo, N., additional, Restituto, P., additional, Sayon-Orea, C., additional, Garcia-Fernandez, N., additional, Leite Filho, N. C. V., additional, Souza, L. E. O., additional, Cavalcante, R. M., additional, Morais, B. M., additional, Leite, T. T., additional, Silva, S. L., additional, Kubrusly, M., additional, Jung, Y. S., additional, Kim, Y. N., additional, Shin, H. S., additional, Rim, H., additional, Bentall, A., additional, Al-Baaj, F., additional, Williamson, S., additional, Cheshire, S., additional, Jelakovic, M., additional, Ivkovic, V., additional, Laganovic, M., additional, Karanovic, S., additional, Pecin, I., additional, Premuzic, V., additional, Vukovic Lela, I., additional, Vrdoljak, A., additional, Fucek, M., additional, Cvitkovic, A., additional, Juric, D., additional, Bozina, N., additional, Bitunjac, M., additional, Leko, N., additional, Abramovic Baric, M., additional, Matijevic, V., additional, Jelakovic, B., additional, Ullah, A., additional, Exarchou, K., additional, Archer, T., additional, Anijeet, H., additional, Brown, R., additional, Cheng, Y.-p., additional, Rocha, J. C. G., additional, Gushiken da Silva, T., additional, de Castro, P. F., additional, Kioroglo, P. S., additional, Branco Martins, J. P., additional, Tzanno-Martins, C., additional, Biesenbach, P., additional, Luf, F., additional, Fleischmann, E., additional, Grunberger, T., additional, Druml, W., additional, Gaipov, A., additional, Turkmen, K., additional, Toker, A., additional, Solak, Y., additional, Cicekler, H., additional, Ucar, R., additional, Kilicaslan, A., additional, Gormus, N., additional, Tonbul, H. Z., additional, Yeksan, M., additional, Turk, S., additional, Monteburini, T., additional, Cenerelli, S., additional, Santarelli, S., additional, Boggi, R., additional, Tazza, L., additional, Bossola, M., additional, Ferraresi, M., additional, Merlo, I., additional, Giovinazzo, G., additional, Quercia, A. D., additional, Gai, M., additional, Leonardi, G., additional, Anania, P., additional, Guarena, C., additional, Cantaluppi, V., additional, Pacitti, A., additional, Biancone, L., additional, Hissa, P. N. G., additional, Daher, E. D. F., additional, Liborio, A. B., additional, Thereza, B. M. F., additional, Mendes, C. C. P., additional, and Sousa, A. R. O., additional
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