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5,510 results for “Foods”
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Bulgaria
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Risk Assessment Center on Food Chain</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Malta
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Ministry for Agriculture, Fisheries and Animal Rights</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Hungary
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: National Food Chain Safety Office</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Belgium
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection SCIENSANO</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – France
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: French Agency for Food, Environmental and Occupational Health & Safety</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Austria
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Austrian Agency for Health and Food Safety</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Lithuania
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: National Food and Veterinary Risk Assessment Institute</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Romania
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Institute of Hygiene and Veterinary Public Heath and Institute for Diagnosis and Animal Health</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Germany
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods, as well as the voluntary reporting of and Whole Genome Sequencing (WGS) data are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Federal Institute for Risk Assessment</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Estonia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Veterinary and Food Board</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Finland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods, as well as the voluntary reporting of and Whole Genome Sequencing (WGS) data are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Finnish Food Authority</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Luxembourg
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2021 AMR data collection: Administration des services vétérinaires</p>
Data from: Thermoregulatory costs of the innate immune response are modulated by winter food availability in a small passerine
<p>1. In winter, a challenge to the immune system could pose a major energetic trade-off for small endotherms, whereby increasing body temperature (<em>T</em><sub>b</sub>; i.e. eliciting fever) may be beneficial to fight off invading pathogens yet incur a cost for vital energy-saving mechanisms.</p> <p>2. Having previously shown that the availability and acquisition of energy, through manipulation of food predictability, influence the depth of rest-phase hypothermia in a wild bird in winter, we expected that the nocturnal thermoregulatory component of the acute-phase immune response would also be modulated by food availability.</p> <p>3. By manipulating winter food availability in the wild for great tits, <em>Parus major</em>, we created an area offering a "predictable" and constant supply of food at feeding stations, while an unmanipulated area was subject to naturally "unpredictable" food. Birds were subject to an immune challenge shortly after dusk, and the thermoregulatory response was quantified via continuous recording of nocturnal <em>T</em><sub>b</sub>, using subcutaneous thermo-sensitive transponders.</p> <p>4. In response to immune challenge, all birds increased <em>T</em><sub>b</sub> above the level maintained prior to immune challenge (i.e. baseline). However, birds experiencing a naturally unpredictable food supply elevated <em>T</em><sub>b</sub> more than birds with access to predictable food resources, during the period of expected peak response and for the duration of the night. Furthermore, "unpredictable-food" females took longer to return to baseline <em>T</em><sub>b</sub>. Assuming baseline nocturnal <em>T</em><sub>b</sub> reflects an individual's optimum, based on their available energy budget, the metabolic cost of eliciting an acute-phase response for "unpredictable-food" birds was more than double that of "predictable-food" birds. The absence of differences in absolute <em>T</em><sub>b</sub> during the peak response could support the idea of an optimal <em>T</em><sub>b</sub> for immune system activation. Alternatively, "predictable-food" birds could have acquired tolerance to endotoxin as a result of using feeding stations, thus affording them reduced costs associated with a smaller <em>T</em><sub>b</sub> increase.</p> <p>5. These findings shed new light on the trade-offs associated with food acquisition, thermoregulation and immune function in small-bodied endotherms. This knowledge is of increasing importance, given the predicted elevated pathogen risks associated with changes in climate and anthropogenic activities.</p>
Microhabitat humidity rather than food availability drives thermo-hydroregulation responses to drought in a terrestrial lizard
<p>The content of this archive includes raw data and metadata for the paper "Microhabitat humidity rather than food availability drives thermo-hydroregulation responses to drought in a terrestrial lizard" by Bodineau et al. In this experimental study, we investigated how microclimate conditions and food availability influence thermo-hydroregulation strategies and body condition of lizards (Zootoca vivipara) during a simulated drought. We found that water restriction and food deprivation caused physiological alterations such as muscle catabolism and mobilization of caudal energy reserves. Lizards developed behavioural strategy to counteract water and food deprivation like decreased thermoregulation effort, higher shelter use and increased eye closure behaviours. Hydric quality of the shelter rather than food availability was the main modulator of trade-offs between thermoregulatory and hydroregulatory activities and an important buffer against the deleterious effects of water restriction. These original findings challenge the assumptions of mechanistic models of ectotherms, which are currently calibrated on the thermal biology of ectotherms. They demonstrate the urgent need to take into account the dual effect of warming and drought events, behavioural interactions between thermoregulation and hydroregulation and the buffering role of microclimatic conditions.</p>
Data for: Negative but antagonistic effects of neonicotinoid insecticides and ectoparasitic mites Varroa destructor on Apis mellifera honey bee food glands
<p>Collaborative brood care by workers is essential for the functionality of eusocial honey bee, <em>Apis</em> <em>mellifera</em>, colonies. The hypopharyngeal food glands of workers play a crucial role in this context. Even though there is consensus that ubiquitous ectoparasitic mites <em>Varroa</em> <em>destructor</em> and widespread insecticides, such as neonicotinoids, are major stressors for honey bee health, their impact alone and in combination on the feeding glands of workers is poorly understood. Here, we show that both <em>V. destructor</em> and neonicotinoids reduce hypopharyngeal gland size, thereby potentially compromising collaborative brood care in colonies. In a fully-crossed laboratory experiment, the impact of mites and the neonicotinoids thiamethoxam and clothianidin alone and in combination on workers were evaluated. While the neonicotinoids did not impact survival and emergence body mass, the data confirm that <em>V. destructor</em> reduces both. Even though the interactions between both stressors were antagonistic and neutral, the clear detrimental effects of both stressors alone and in combination on worker longevity and food glands are remarkable. Besides reduced worker longevity, impaired brood care provided by workers exposed to <em>V. destructor</em> and neonicotinoids could be detrimental for honey bee colony functionality. Our findings highlight a mechanism to explain honey bee colonies losses globally.</p>
Data for: "Land-use intensity influences European tetrapod food-webs"
<p>These .Rdata files enable to reproduce results from our article " Signatures of land use intensity on european tetrapod food-web architectures" along with the R code provided at: https://github.com/ChrisBotella/foodwebs_vs_land_use</p> <p>- raw_data : Raw data including GBIF and iNaturalist occurrences and IUCN enveloppes used to select sites and generate species presence/absence. We provide this file for transparency and reproducibility of our methodology.</p> <p>- preprocessed_data: preprocessed data (obtained from raw_data) used to generate our article Figures along with the next file.</p> <p>- TrophicNetworksList : .Rdata containing a list of igraph objects, each igraph is a foodweb associated to a site identify by the list element name. </p> <p>- MultiRegMatrices: .Rdata containing especially the pre-computed matrix Y of cells (rows) by food web metrics (columns) and the covariate design matrix X (for the linear regressions) in order to facilitate and accelerate the reproduction of the analyses.</p>
Data and Code for "A planetary health innovation for disease, food, and water challenges in Africa"
<p>Data and R code for both economic and non-economic analysis for the paper titled, "A planetary health innovation for disease, food, and water challenges in Africa"</p>
Draft Genome Sequences of Two Bacteriocin-Producing Enterococcus faecium Strains Isolated from Nonfermented Animal Foods in Spain
<p>Raw sequences of two bacteriocin-producing Enterococcus faecium.</p> <p> </p>
Data from: Long-term grazing intensity by reindeer alters the response of the soil micro-food web to simulated climate change in subarctic tundra
<p><span>Top-down control by nematodes over soil microorganisms – considered stronger over bacteria than fungi - may dampen microbial responses to global changes in tundra. To test whether large grazers alter the responses of belowground trophic networks to global changes, we employed factorial warming and nitrogen fertilization treatments in adjacent sites with different reindeer grazing intensities for the past 50 years. Lightly grazed tundra is dominated by dwarf shrubs and a more fungal-based microbial community, while in heavily grazed tundra, high reindeer densities during autumn migration have induced shift into graminoids and more bacterial-based microbial community. We analysed the soil micro-food web, <em>i.e.</em>, the nematode density, trophic structure, and species composition as well as fungal, bacterial and total phospholipid fatty acids (PLFAs) after four growing seasons of warming and fertilization both before and during reindeer migration. We predicted that bacterivore densities are higher and fungivore densities lower under heavy than light grazing (<em>i.e.</em>, nematode populations before migration reflect grazing effects via the base of food web), whereas reindeer migration induces negative impact on nematode densities under heavy grazing (<em>i.e</em>., disturbance by trampling is the driving factor). We further predicted that nematodes negate treatment effects on microbial biomass to a stronger extent in the bacterial-based heavily grazed than the fungal-based lightly grazed tundra. Fungivore densities were higher under light than heavy grazing, but nematodes did not respond to trampling. Warming increased fungivores and the fungal PLFAs irrespective of grazing and timing, but under heavy grazing, increased bacterivores while the bacterial PLFAs remained steady. Fertilization increased carnivores and influenced nematode species composition, diversity and maturity interactively with warming. Our data suggest that large grazers affect tundra soil nematodes via bottom-up effects through microbial community composition and biomass, which in turn may alter the strength of their top-down control soil bacteria under climate warming. </span></p>
Data for: Passive and active parental food allocation in a songbird
<p><span>Parent-offspring conflict over food allocation can be modeled using two theoretical frameworks: passive (scramble competition) and active choice (signaling) resolution models. However, differentiating between these models empirically can be challenging. One possibility involves investigating details of decision-making by feeding parents. Different nestling traits, related to competitive prowess or signalling cryptic condition, may interact additively or non-additively as predictors of parental feeding responses. To explore this, we experimentally created even-sized, small broods of pied flycatchers and manipulated nestling cryptic quality, independently of size, by vitamin E supplementation. We explored how interactions between nestling cryptic condition, size, signals, and spatial location predicted food allocation and prey-testing by parents. Parents created the potential for spatial scramble competition between nestlings by feeding from and to a narrow range of nest locations. Heavier supplemented nestlings grew faster and were more likely to access profitable nest locations. However, the most profitable locations were not more contested, and nestling turnover did not vary in relation to spatial predictability or food supply. Postural begging was only predicted by nestling hunger and body mass, but parents did not favor heavier nestlings. This suggests that size-mediated and spatial competition in experimental broods was mild. Pied flycatcher fathers allocated food in response to nestling position and begging order, while mothers seemingly followed an active choice mechanism involving assessment of more complex traits, including postural intensity interacting with order, position, and treatment, and perhaps other stimuli when performing prey-testings. Differences in time constraints may underlie sex differences in food allocation rules.</span></p>
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Allen Brain Atlas
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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
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