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Tables and figures complementing the European Union OneHealth 2020 Zoonoses Report

All summary tables and figures produced for the European Union One Health 2020 Zoonoses Report are provided as archives  containing Excel files for tables, and as PDF or PNG files for figures. All country data connected to this Report are published SEPARATELY on Knowledge Junction - see related identifiers. This is because DATA OWNERSHIP for country data stays with the organisation(s) of the country submitting the data - for further reference see doi:10.2903/sp.efsa.2019.EN-1544.

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Norway

This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Luxembourg

Animal disease data complementing the European Union One Health 2020 Zoonoses Report

This dataset contains the mandatory annual data reported for bovine tuberculosis and for bovine and ovine and caprine brucellosis based on Directive 2003/99 that cites in Recital 7 the Council Directives 64/432/EEC and 91/68/EEC. The relevant Commission Decisions relating to the officially free (OF) MS and MS' regions and related reporting are: Decision 2003/467/EC for bovine tuberculosis and bovine brucellosis, and Decision 93/52/EC for sheep and goat brucellosis (B. melitensis). REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: Disease_status_data_2020_20211109: >>

Prevalence data complementing the European Union One Health 2020 Zoonoses Report

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - the United kingdom

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Finland

Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Sweden

opencc-by-4.0Jan 2022View details →

Dataset related to article "Complement activation promoted by the lectin pathway mediates C3aR-dependent sarcoma progression and immunosuppression"

This record contains raw data related to article “Complement activation promoted by the lectin pathway mediates C3aR-dependent sarcoma progression and immunosuppression" Complement has emerged as a component of tumor promoting inflammation. We conducted a systematic assessment of the role of complement activation and effector pathways in sarcomas. C3 -/-, MBL1/2 -/- and C4 -/- mice showed reduced susceptibility to 3-methylcholanthrene sarcomagenesis and transplanted sarcomas, whereas C1q and factor B deficiency had marginal effects. Complement 3a receptor (C3aR), but not C5aR1 and C5aR2, deficiency mirrored the phenotype of C3 -/- mice. C3 and C3aR deficiency were associated with reduced accumulation and functional skewing of tumor-associated macrophages, increased T cell activation and response to anti-PD-1 therapy. Transcriptional profiling of sarcoma infiltrating macrophages and monocytes revealed the enrichment of MHC II-dependent antigen presentation pathway in C3-deficient cells. In patients, C3aR expression correlated with a macrophage population signature and C3 deficiency-associated signatures predicted better clinical outcome. These results suggest that the lectin pathway and C3a/C3aR axis are key components of complement and macrophage-mediated sarcoma promotion and immunosuppression.

opencc-by-4.0Apr 2022View details →

Datasets and R-codes complementing the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen"

These datasets complement the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen". They contain: i) data on concentration of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO2) in commercially available sunscreens, ii) data on amount sunscreen used, and iii) data on dermal absorption of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO2). The data are used in the probabilistic exposure estimations in the Opinion. The data were retrieved from open sources. In addition, the R-codes used to perform the exposure estimation, are included.

opencc-by-4.0Jun 2022View details →

Data complementing the Avian influenza overview March – June 2022

Annex A –     Characteristics of the HPAI A(H5Nx)-positive poultry establishments The Annex contains table with the characteristics of the HPAI A(H5Nx)-positive poultry establishments by affected EU Member State from 4 March to 1 June 2022. Annex B –     Applied prevention and control measures on avian influenza The Annex contains an overview of specific prevention and control measures applied in Albania, Belgium, Bulgaria, Czechia,  France, Hungary, Iceland, Italy, Moldova, Kosovo, The Netherlands, Poland, Romania, Slovakia, Spain from 1 December 2021 to 4 March 2022 in relation to HPAI outbreaks in poultry and in wild birds. Annex C –     Data on wild birds The Annex contains tables and plots on HPAI notifications in wild birds in Europe.

dryad40/100

Data from: Different taxonomic and functional indices complement the understanding of herb-layer community assembly patterns in a southern-limit temperate forest

The efficient conservation of vulnerable ecosystems in the face of global change requires a complete understanding of how plant communities respond to various environmental factors. We aim to demonstrate that a combined use of different approaches, traits, and indices representing each of the taxonomic and functional characteristics of plant communities will give complementary information on the factors driving vegetation assembly patterns. We analyzed variation across an environmental gradient in taxonomic and functional composition, richness, and diversity of the herb-layer of a temperate beech-oak forest that was located in northern Spain. We measured species cover and four functional traits: leaf dry matter content (LDMC), specific leaf area (SLA), leaf size, and plant height. We found that light is the most limiting resource influencing herb-layer vegetation. Taxonomic changes in richness are followed by equivalent functional changes in the diversity of leaf size but by opposite responses in the richness of SLA. Each functional index is related to different environmental factors even within a single trait (particularly for LDMC and leaf size). To conclude, each characteristic of a plant community is influenced by different and even contrasting factors or processes. Combining different approaches, traits, and indices simultaneously will help us understand how plant communities work.

opencc-zeroDec 2021View details →

opencc-by-4.0Sep 2022View details →

Data complementing the Avian influenza overview June – September 2022

Annex A –     Characteristics of the HPAI A(H5Nx)-positive poultry establishments The Annex contains table with the characteristics of the HPAI A(H5Nx)-positive poultry establishments by affected EU Member State from 2 June to  2 September 2022. Annex B –     Applied prevention and control measures on avian influenza The Annex contains an overview of specific prevention and control measures applied in Bulgaria, Croatia, France, Hungary, Germany, Moldova, the Netherlands, Poland, Portugal, Spain from 2 June to 2 September 2022 in relation to HPAI outbreaks in poultry and in wild birds. Annex C –     Data on wild birds The Annex contains tables and plots on HPAI virus notifications in wild birds in Europe.

Figure 7. T in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 7. T. cruzi growth assessment after cisplatin treatment (300 ΜM). (a) Wild type (WT). (b) TcXPC superexpressor (Tc-TcXPC). (c) TevXPC expressor (Tc-TevXPC). The solid lines represent the untreated cells, while the dotted lines represent the cells treated with cisplatin. Statistical student's t test: (*) On that point, cells treated with cisplatin presented a statistically significant lower growth in relation to untreated cells (p <0.05). Representative results of three independent experiments.

Figure 6 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 6. Growth assessment of T. cruzi: wild type (WT), TcXPC superexpressor (Tc-TcXPC) and TevXPC expressor (Tc-TevXPC). Statistical student's t test: (*) On that point, only Tc-TevXPC presented a statistically significant lower growth in relation to WT (p <0.05); (**) On that point, both Tc-TcXPC and Tc-TevXPC presented a significant lower growth in relation to WT (p <0.05). All parasites were at same initial concentration, grown on LIT medium and were counted daily. Representative results of three independent experiments.

Figure 5 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 5. TevXPC amplification by RT-PCR with the cDNA from cell cultures. Lanes: (1) 1Kb DNA Ladder; (2) WT; (3) Tc-TcXPC; (4 and 5) Tc-TevXPC; (6) positive control (DNA from T. evansi); (7) negative control.

Figure 4 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 4. (a) TcXPB-R protein model. (b) TevXPB-R protein model. (c) TcXPB-R (blue) and TevXPB-R (orange) models overlay.

Figure 2 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 2. (a) Alignment between TcXPC and TevXPC proteins (mismatches highlighted) and its domains. Green: RAD4/PNGase transglutaminase-like fold. Blue: RAD4 beta-hairpin domain 1. Red: RAD4 beta-hairpin domain 2. Yellow: RAD4 beta-hairpin domain 3. (b) Candidate sequence motif involved in p62 interaction (highlighted by brown rectangle) found in TcXPC and TevXPC. This sequence is suggested based on the sequence motif described for Human XPC and yeast RAD4: D/E-F/W-E-D/E-V.

Figure 1 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 1. (a) TcXPC protein model. (b) TevXPC protein model. (c) TbXPC protein model (d) Model of TevXPC protein bound to a mismatch DNA. (e) TcXPC (red), TevXPC (blue) and TbXPC (green) models overlay. (f) Crystal structure of Rad4-Rad23 bound to a mismatched DNA performed by Min and Pavletich (2007).

Figure 3 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 3. (a) TcXPB protein model. (b) TevXPB protein model. (c) TcXPB (green) and TevXPB (red) models overlay.