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Annexes to the external scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using MCRA software - Input and output data sets
<p>Retrospective dietary exposure assessments were conducted for two groups of pesticides that have chronic effects on the thyroid: </p> <ol> <li>hypertrophy, hyperplasia and neoplasia of C-cells, i.e. affecting the parafollicular cells or the calcitonin system of the thyroid (CAG-TCP);</li> <li>hypothyroidism, i.e. affecting the follicular cells and/or the hormone system of the thyroid (CAG-TCF).</li> </ol> <p>The pesticides considered in this assessment were identified and characterised in the scientific report on the establishment of cumulative assessment groups of pesticides for their effects on the thyroid (<a href="https://doi.org/10.2903/j.efsa.2019.5801">here</a>).</p> <p>The exposure calculations used monitoring data collected by Member States under their official pesticide monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Regarding the selection of relevant food commodities, the assessment included water, foods for infants and young children and 30 raw primary commodities of plant origin that are widely consumed within Europe.</p> <p>Exposure estimates were obtained with Monte Carlo Risk Assessment (MCRA) software using a 2-dimensional probabilistic method, which is composed of an inner-loop execution and an outer-loop execution. Variability within the population is modelled through the inner-loop execution and is expressed as a percentile of the exposure distribution. The outer-loop execution is used to derive 95% confidence intervals around those percentiles (reflecting the sampling uncertainty of the input data).</p> <p>Furthermore, calculations were carried out according to a tiered approach. While the first-tier calculations (Tier I) use very conservative assumptions for an efficient screening of the exposure with low risk for underestimation, the second-tier assessment (Tier II) includes assumptions that are more refined but still conservative. For each scenario, exposure estimates were obtained for different percentiles of the exposure distribution and the total margin of exposure (MOET, i.e. the ratio of the toxicological reference dose to the estimated exposure) was calculated at each percentile.</p> <p>The input and output data for the exposure assessment are reported in the following annexes:</p> <ul> <li>Annex A.1 – Input data for the exposure assessment of CAG-TCP</li> <li>Annex A.2 – Input data for the exposure assessment of CAG-TCF</li> <li>Annex B.1 – Output data from the Tier II exposure assessment of CAG-TCP</li> <li>Annex B.2 – Output data from the Tier II exposure assessment of CAG-TCF</li> </ul> <p>Further information on the data, methodologies and interpretation of the results are provided in the external scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using MCRA software (<a href="https://doi.org/10.2903/sp.efsa.2019.en-1707">here</a>).</p> <p>The results reported in this assessment only refer to the exposure and are not an estimation of the actual risks. These exposure estimates should therefore be considered as documentation for the final scientific report on the cumulative risk assessment of dietary exposure to pesticides for their effects on the thyroid (<a href="https://www.efsa.europa.eu/en/consultations/call/public-consultation-scientific-report-cumulative">here</a>). The latter combines the hazard assessment and exposure assessment into a consolidated risk characterisation, including all related uncertainties.</p>
Annexes to the scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using SAS® software - Input and output data sets
<p>Retrospective dietary exposure assessments were conducted for two groups of pesticides that have chronic effects on the thyroid: </p> <ol> <li>hypertrophy, hyperplasia and neoplasia of C-cells, i.e. affecting the parafollicular cells or the calcitonin system of the thyroid (CAG-TCP);</li> <li>hypothyroidism, i.e. affecting the follicular cells and/or the hormone system of the thyroid (CAG-TCF).</li> </ol> <p>The pesticides considered in this assessment were identified and characterised in the scientific report on the establishment of cumulative assessment groups of pesticides for their effects on the thyroid (<a href="https://doi.org/10.2903/j.efsa.2019.5801">here</a>).</p> <p>The exposure calculations used monitoring data collected by Member States under their official pesticide monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Regarding the selection of relevant food commodities, the assessment included water, foods for infants and young children and 30 raw primary commodities of plant origin that are widely consumed within Europe.</p> <p>Exposure estimates were obtained with SAS<sup>®</sup> software using a 2-dimensional probabilistic method, which is composed of an inner-loop execution and an outer-loop execution. Variability within the population is modelled through the inner-loop execution and is expressed as a percentile of the exposure distribution. The outer-loop execution is used to derive 95% confidence intervals around those percentiles (reflecting the sampling uncertainty of the input data).</p> <p>Furthermore, calculations were carried out according to a tiered approach. While the first-tier calculations (Tier I) use very conservative assumptions for an efficient screening of the exposure with low risk for underestimation, the second-tier assessment (Tier II) includes assumptions that are more refined but still conservative. For each scenario, exposure estimates were obtained for different percentiles of the exposure distribution and the total margin of exposure (MOET, i.e. the ratio of the toxicological reference dose to the estimated exposure) was calculated at each percentile.</p> <p>The input and output data for the exposure assessment are reported in the following annexes:</p> <ul> <li>Annex A.1 – Input data for the exposure assessment of CAG-TCP</li> <li>Annex A.2 – Input data for the exposure assessment of CAG-TCF</li> <li>Annex B.1 – Output data from the Tier I exposure assessment of CAG-TCP</li> <li>Annex B.2 – Output data from the Tier I exposure assessment of CAG-TCF</li> <li>Annex C.1 – Output data from the Tier II exposure assessment of CAG-TCP</li> <li>Annex C.2 – Output data from the Tier II exposure assessment of CAG-TCF</li> </ul> <p>Further information on the data, methodologies and interpretation of the results are provided in the scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using SAS<sup>®</sup> software (<a href="https://doi.org/10.2903/j.efsa.2019.5763">here</a>).</p> <p>The results reported in this assessment only refer to the exposure and are not an estimation of the actual risks. These exposure estimates should therefore be considered as documentation for the final scientific report on the cumulative risk assessment of dietary exposure to pesticides for their effects on the thyroid (<a href="https://www.efsa.europa.eu/en/consultations/call/public-consultation-scientific-report-cumulative">here</a>). The latter combines the hazard assessment and exposure assessment into a consolidated risk characterisation, including all related uncertainties.</p>
Annexes to the scientific report on the cumulative dietary exposure assessment of pesticides that have acute effects on the nervous system using SAS® software - Input and output data sets
<p>Retrospective dietary exposure assessments were conducted for two groups of pesticides that have acute effects on the nervous system: </p> <ol> <li>brain and/or erythrocyte acetylcholinesterase inhibition (CAG-NAN);</li> <li>functional alterations of the motor division (CAG-NAM).</li> </ol> <p>The pesticides considered in this assessment were identified and characterised in the scientific report on the establishment of cumulative assessment groups of pesticides for their effects on the nervous system (<a href="https://doi.org/10.2903/j.efsa.2019.5800">here</a>).</p> <p>The exposure calculations used monitoring data collected by Member States under their official pesticide monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Regarding the selection of relevant food commodities, the assessment included water, foods for infants and young children and 30 raw primary commodities of plant origin that are widely consumed within Europe.</p> <p>Exposure estimates were obtained with SAS<sup>®</sup> software using a 2-dimensional Monte Carlo simulation, which is composed of an inner-loop execution and an outer-loop execution. Variability within the population is modelled through the inner-loop execution and is expressed as a percentile of the exposure distribution. The outer-loop execution is used to derive 95% confidence intervals around those percentiles (reflecting the sampling uncertainty of the input data).</p> <p>Furthermore, calculations were carried out according to a tiered approach. While the first-tier calculations (Tier I) use very conservative assumptions for an efficient screening of the exposure with low risk for underestimation, the second-tier assessment (Tier II) includes assumptions that are more refined but still conservative. For each scenario, exposure estimates were obtained for different percentiles of the exposure distribution and the total margin of exposure (MOET, i.e. the ratio of the toxicological reference dose to the estimated exposure) was calculated at each percentile.</p> <p>The input and output data for the exposure assessment are reported in the following annexes:</p> <ul> <li>Annex A.1 – Input data for the exposure assessment of CAG-NAN</li> <li>Annex A.2 – Input data for the exposure assessment of CAG-NAM</li> <li>Annex B.1 – Output data from the Tier I exposure assessment of CAG-NAN</li> <li>Annex B.2 – Output data from the Tier I exposure assessment of CAG-NAM</li> <li>Annex C.1 – Output data from the Tier II exposure assessment of CAG-NAN</li> <li>Annex C.2 – Output data from the Tier II exposure assessment of CAG-NAM</li> </ul> <p>Further information on the data, methodologies and interpretation of the results are provided in the scientific report on the cumulative dietary exposure assessment of pesticides that have acute effects on the nervous system using SAS<sup>®</sup> software (<a href="https://doi.org/10.2903/j.efsa.2019.5764">here</a>).</p> <p>The results reported in this assessment only refer to the exposure and are not an estimation of the actual risks. These exposure estimates should therefore be considered as documentation for the final scientific report on the cumulative risk assessment of dietary exposure to pesticides for their effects on the nervous system (<a href="https://www.efsa.europa.eu/en/consultations/call/public-consultation-scientific-report-cumulative">here</a>). The latter combines the hazard assessment and exposure assessment into a consolidated risk characterisation, including all related uncertainties.</p>
ENERGISE Living Lab country report - Ireland
<p>ENERGISE Living Labs (ELLs) employ practice-based approaches to reduce energy use in households while co-creating knowledge on why energy-intensive practices are performed and how they depend on the context in which they are performed. Altogether 16 living labs were implemented in eight European countries in 2018.</p> <p>The Irish ELLs were led by the ENERGISE team from the National University of Ireland Galway (NUIG). The ENERGISE Living Labs were implemented in one county (Tipperary) in the midlands of Ireland, approximately 150 kilometres from Galway City.</p>
Supplementary material to Republic of Moldova project report Free University Berlin
<p>This is supplementary material for the project of the Freie Universität Berlin with the title: <strong>Anwendung geoarchäoogischer Methoden zum Verständnis anthropogener Spuren der Poineşti-Lucaşeuca Kultur in Ivancea-Sub Pădure, Republik Moldau. </strong>The project was carried out by students during the module Projekt I at the Freien Universität Berlin. Fieldwork was conducted 16th - 23rd September 2018in the vicinity of Ivancea (central Moldova), about 30km north of the capital Chisinau. </p>
HY+_HSVA‐06_UNIS - Data Storage Report
<p>Data Storage Report<br>Bending rheology of floating saline ice and wave damping – Waves in Ice; BRWD-Waves in Ice<br>Large Ice Model Basin (LIMB), Hamburg Ship Model Basin</p>
HY+_HSVA-02_UCL - Data Storage Report
<p>Hydralab+ Data Storage Report<br>Sea Ice Dynamics: The Role of Ice Rubble in Multi-Scale Deformation<br>Hy+_HSVA-02-UCL<br>HSVA ARCTECLAB – Large Ice Model Basin (LIMB)<br>Author: Sally Scourfield, Institute for Risk and Disaster Reduction, University College London</p>
HY+_HSVA‐08_UNI ST.ANDREWS - Data Storage Report and Data Set
<p>Data from the internal waves project according to data storage report</p>
ENERGISE LIVING LAB COUNTRY REPORT – GERMANY
<p>The German ENERGISE living labs were rolled out by the LMU ENERGISE team to 40 participant households over the course of eight months from August 2018 to April 2019 in the Oberland region of Bavaria. During that time, over the course of a number of interviews and surveys households in and around the towns of Weilheim (ELL1) and Murnau (ELL2) were asked to do a thorough examination of their practices in the areas of heating and laundry with a specific focus on trying to encourage households to reduce the energy use associated with those practices by means of finding sufficiency focused strategies to enable them to heat less and launder less.</p>
4onse stations monthly reports
<p>This dataset contains monthly climatological reports (NOAA style) of all the 4onse stations installed in the Deduru Oya basin in Sri Lanka.</p>
Figure 2 in First report of Spodoptera frugiperda (Lepidoptera: Noctuidae) on Onion (Allium cepa L.) in South Kivu, Eastern DR Congo
Figure 2 Mean (±S.E) incidence of Spodoptera frugiperda in onion as a function of season and cropping system. 24 plots were considered in each cropping system. A and B represents the incidence in 2019 and 2020 respectively.
Figure 1 in First report of Spodoptera frugiperda (Lepidoptera: Noctuidae) on Onion (Allium cepa L.) in South Kivu, Eastern DR Congo
Figure 1 Spodoptera frugiperda larvae occurring in the onion crop at the experimental site. A: lesions induced on onion leaf epidermis; B: sixth instar larvae found inside onion leaves; C: severity of damage and faecal pellets in whorl of the onion plant; D: fifth instar larva found on the onion plant.
Figure 4 in First report of Spodoptera frugiperda (Lepidoptera: Noctuidae) on Onion (Allium cepa L.) in South Kivu, Eastern DR Congo
Figure 4 Rates of attack severity of Spodoptera frugiperda according the kind of onion crops. A and B: severity in 2019 and in 2020 respectively. 0: no visible leaf damage; 1: small lesions on leaf epidermis; 2: Small elongated (rectangular shaped) lesions (5) of up to 1.3 cm in length on leaf epidermis; 3: Several small to mid-sized 1.3 to 2.5 cm in length elongated lesions (5-10) on several leaves; 4: Several large elongated lesions (˃10), greater than 2.5 cm in length present on several leaves; 5: leaves almost completely destroyed.
Figs. 1–7 in First report of two species of scarab beetles (Coleoptera, Scarabaeidae) inside nests of Azteca cf. chartifex Forel (Hymenoptera, Formicidae) in Brazilian Amazonian Rainforest
Figs. 1–7. Azteca cf. chartifex nest and its associated myrmecophile beetles. 1, Nest, sectioned at its third lower part, which was searched for myrmecophiles. 2, Upclose view of upper nest part, with no sight of large galleries. 3, Large gallery on the collected nest piece, in which one beetle was found. 4, Phileurus carinatus declivis, dorsal view. 5, Phileurus carinatus declivis, ventral view. 6, Cyclidius elongatus, dorsal view. 7, Cyclidius elongatus, ventral view.
Fig. 4 in First Report of a Case of Prostatitis Due to Acanthamoeba in a Dog
Fig. 4. Phylogenetical analysis of the DF3 sequence of the Acanthamoeba strain isolated from the prostate revealed that the strain belonged to genotype T4.
Figure 2 in First report of some parasites from Mediterranean mussel, Mytilus galloprovincialis Lamarck, 1819, collected from the Black Sea coast at Sinop
Figure 2. Parasites of M. galloprovincialis: A. Nematopsis legeri, B. Peniculistoma mytili, C. Urastoma cyprinae, D. Parvatrema duboisi, E. Polydora ciliata, F. burrow (Λ) on the inner side of mussel shell.
Figure 1 in First Report of African Fig Fly, Zaprionus indianus Gupta (Diptera: Drosophilidae), on the Island of Maui, Hawaii, USA, in 2017 and Potential Impacts to the Hawaiian Entomofauna
Figure 1. Thorax (a) and front tibia (b) of Zaprionus indianus collected on Maui. The lack of a white spot on the scutellum, and the presence of tibial spines, separates this species from Zaprionus ghesquierei.
Figure 4. Xylosandrus compactus boring coffee berries around the blossom area. X. compactus boring a in First Report of Exploitation of Coffee Beans by Black Twig Borer (Xylosandrus Compactus) and Tropical Nut Borer (Hypothenemus obscurus) (Coleoptera; Curculionidae: Scolytinae) in Hawaii
Figure 4. Xylosandrus compactus boring coffee berries around the blossom area. X. compactus boring a coffee berry (A, left), hole made by X. compactus on the endosperm (B, right); galleries or immature stages were not found.
Figure 2 in First Report of Exploitation of Coffee Beans by Black Twig Borer (Xylosandrus Compactus) and Tropical Nut Borer (Hypothenemus obscurus) (Coleoptera; Curculionidae: Scolytinae) in Hawaii
Figure 2. Gallery of Xylosandrus compactus in coffee branches. Xylosandrus compactus female adults (left) and immature stages (right).
Figure 3 in First Report of Exploitation of Coffee Beans by Black Twig Borer (Xylosandrus Compactus) and Tropical Nut Borer (Hypothenemus obscurus) (Coleoptera; Curculionidae: Scolytinae) in Hawaii
Figure 3. Damage symptoms of X. compactus in coffee branches. First leaves turn light green (A, left), then the wilted leaves and bark beyond the affected area turn brown or black (B, right).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.