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38 results for “environmental contamination”
Fig. 1 in Mussels (Perna perna) as bioindicator of environmental contamination by Cryptosporidium species with zoonotic potential
Fig. 1. Map of the studied area in the municipality of Mangaratiba, Rio de Janeiro State, Brazil. Red marker A — Collection site A; Red marker B — Collection site B; Green marker — The river known as "Rio do Saco" which leads to the ocean at collection site B. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).
Figure 4 in Limitations of allometry, morphometry, and fluctuating asymmetry in detecting environmental stress caused by lead soil contamination in aphids under field conditions
Figure 4 Fluctuating asymmetry (mean and error deviation) observed in the antenna and tibia of Brevicoryne brassicae in the presence (Lead (Pb)) and absence (Control) of lead.
Figure 3 in Limitations of allometry, morphometry, and fluctuating asymmetry in detecting environmental stress caused by lead soil contamination in aphids under field conditions
Figure 3 Negative allometry represented by the allometric coefficients of both the antenna and tibia and their confidence intervals; the values are related to the body length ofBrevicoryne brassicae in the presence (Lead (Pb)) and absence (Control) of lead.
Figure 1 in Limitations of allometry, morphometry, and fluctuating asymmetry in detecting environmental stress caused by lead soil contamination in aphids under field conditions
Figure 1 Brevicoryne brassicae placed in a dorsal-ventral position for structure measurement. (a): Total body length (b): antenomer length (c): length of the posterior tibia. Source: the authors.
Figure 2 in Limitations of allometry, morphometry, and fluctuating asymmetry in detecting environmental stress caused by lead soil contamination in aphids under field conditions
Figure 2 Mean length and standard error of the antenna, tibia and body length of Brevicoryne brassicae in the presence (Lead (Pb)) and absence (Control) of lead.
Fig. 4 in Factors that alter the biochemical biomarkers of environmental contamination in Chironomus sancticaroli (Diptera, Chironomidae)
Fig. 4. Effect of sample centrifugation on the activity of acetylcholinesterase (AChE), alpha esterase (EST-α), and beta alpha esterase (EST-β) of Chironomus sancticaroli. The values are expressed as the mean value of enzyme activity ± SD (n = 30 for each condition). Different letters indicate significant differences when p <0.05 (using paired t-test).
Fig. 2 in Factors that alter the biochemical biomarkers of environmental contamination in Chironomus sancticaroli (Diptera, Chironomidae)
Fig. 2. Effect of fasting for 24 h (A); 48 h (B) and 72 h (C) on the activity of acetylcholinesterase (AChE), alpha esterase (EST-α), and beta alpha esterase (EST-β) of Chironomus sancticaroli. The values are expressed as the mean value of enzyme activity ± SD (n = 30 for each condition). Different letters indicate significant differences when p <0.05 (using unpaired t-test).
Fig. 1 in Factors that alter the biochemical biomarkers of environmental contamination in Chironomus sancticaroli (Diptera, Chironomidae)
Fig. 1. Effect of temperature (20, 25 and 30 ◦C) on the activity of acetylcholinesterase (AChE), alpha esterase (EST-α), and beta alpha esterase (EST-β) of Chironomus sancticaroli. The values are expressed as the mean value of enzyme activity ± SD (n = 30 for each condition). Different letters indicate significant differences when p <0.05 (using ANOVA – one way and Tukey contrast).
Figure 1 in Amphibian and fish eye lens used as biomarker of remote and chronic environmental contamination
Figure 1.The main abnormities of the frog lens in the region of the posterior pole. а – back lens suture is normal; b - "starry sky" picture; c – lesion of the back lens suture.
Fig. 2 in Toxoplasma gondii contamination at an animal agriculture facility: Environmental, agricultural animal, and wildlife contamination indicator evaluation
Fig. 2. Soil sampling and animal trapping locations at Little River Animal and Environmental Unit in Walland, Tennessee, United States.
Fig. 1 in Toxoplasma gondii contamination at an animal agriculture facility: Environmental, agricultural animal, and wildlife contamination indicator evaluation
Fig. 1. The geographic location of the study site, Little River Animal and Environmental Unit in Walland, Tennessee, United States.
Long-term changes in pituitary gene expression following developmental exposure to environmental contaminants (BPS, BDE-47, or TBBPA) in male mice.
<p><strong>Experimental Design</strong></p><p>In this study we evaluate the long-term gene expression changes in pituitary in male mice exposed developmentally to one of three known endocrine disrupting chemicals: bisphenol-S (BPS), 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), and 3,3',5,5'-tetrabromobisphenol A (TBBPA). Male mice were exposed to chemical treatment through their mothers' during pregnancy (umbilical blood flow) and nursing, from pregnancy day 8 through weaning at postnatal day 21 (PND21). Each chemical exposure was calculated to equal 0.2mg/kg bw/day. The details of exposure protocol are described elsewhere (Kim<i> et al</i>, 2015). The male pups were allowed to grow untreated until adulthood at PND140. At PND140, male mice were euthanized, then their pituitaries removed, snap frozen in liquid nitrogen, and then stored at -80°C. </p><p>The data-files described below represent major steps of our analysis:</p><p><strong>1. FASTQ files for mouse pituitary RNA-seq data.</strong></p><p>Male mouse pituitary RNA was isolated using a Trizol protocol, checked for purity and concentration and then processed for mRNA sequencing using the Illumina TruSeq kit and protocol (TruSeq Stranded mRNA LP, Cat # 20020594 and TruSeq RNA Sg Idx SetB, Cat # 20020493, Illumina, San Diego, CA) following the manufacturer's recommended procedures. High throughput sequencing was conducted using the NextSeq500 sequencing system. cDNA libraries were single-end sequenced in 76 cycles using a NSQ 500/550 Hi Output KT v2.5 (Cat #20024906 Illumina, San-Diego, CA) in one multiplex run (N=3/exposure group). Read filtering, trimming, and de-multiplexing were performed using the BaseSpace cloud service by Illumina (<a href="https://basespace.illumina.com/home/index">https://basespace.illumina.com/home/index</a>, RRID:SCR_011881). Processed reads were mapped to the mouse reference genome (MM10) using the RNA-Seq Alignment v. 1.1.1. software with Bowtie 2. Each FASTQ file is a compressed file representing data from one sequencing flow cell lane for each sample (4 files per sample). Sample identifiers are coded for treatment: X = Vehicle control, R = TBBPA, C = BDE-47, E = BPS. </p><p><strong>2. Differential expression data.</strong></p><p>Aligned reads were used to assemble transcripts and analyze differential expression using Cufflinks Assembly & DE v. 2.1.0. package. Reads aligned to known annotated regions for both control and exposed groups were used to calculate log2 FPKM ratios. Differentially expressed genes were identified as genes altered with false discovery rate significance ≤ 0.05 (FDR, q ≤ 0.05). Data on all exposure groups are shown in different sheets of the same file - Differential_expression.xlsx.</p><p><strong>3. Enrichment of biological categories associated with DEGs induced by chemical exposures. </strong></p><p>All differentially expressed genes were uploaded to Metascape for the analysis of enriched biological categories using default settings. Results of Metascape analysis are shown in two MS Excel files per exposure group, one showing negatively enriched categories and one positively enriched categories. The title of each file consists of three parts connected via underscore sign: the name of the chemical, the direction of enrichment, and the name of analysis - metascape (e.g., BDE-47_negative_metascape.xlsx).</p><p><strong>4. Pathway analysis for chemical exposures.</strong></p><p>All differentially expressed genes were uploaded to Ingenuity Pathway Analysis and enriched canonical pathways were identified using default settings . Altered molecular or disease pathways, their p-values, and associated differentially expressed genes are provided for each exposure. Data for all exposure groups are shown in different sheets of the same file - IPA_pathway_analysis.xlsx.</p><p><strong>References:</strong></p><p>Kim B, Colon E, Chawla S, Vandenberg LN, Suvorov A. Endocrine disruptors alter social behaviors and indirectly influence social hierarchies via changes in body weight. Environ Health. 2015 Aug 5;14:64. doi: 10.1186/s12940-015-0051-6. PMID: 26242739; PMCID: PMC4524022.</p>
No evidence that the widespread environmental contaminant caffeine alters energy balance or stress responses in fish
<p>Anthropogenic sources of environmental pollution are ever-increasing as urban areas expand and more chemical compounds are used in daily life. The stimulant caffeine is one of the most consumed chemical compounds worldwide, and as a result, has been detected as an environmental contaminant in all types of major water sources on all continents. Exposure of wildlife to environmental pollutants can disrupt the energy balance of these organisms, as restoration of homeostasis is prioritised. In turn, energy allocated to other key biological processes such as growth or reproduction may be affected, consequently reducing the overall fitness of an individual. Therefore, we aimed to investigate if long-term exposure to environmentally relevant concentrations of caffeine had any energetic consequences on wildlife. Specifically, we exposed wild eastern mosquitofish (<em>Gambusia holbrooki</em>) to one of three nominal concentrations of caffeine (0, 100, and 10,000 ng/L) and assayed individuals for metabolic rate, general activity, antipredator and foraging behaviour, and body size as measures of energy expenditure or energy intake. We found no differences in any measured traits between any of the given exposure treatments, indicating that exposure to caffeine at current environmental levels may not adversely affect the energy balance and fitness of vulnerable freshwater fish.</p>
No evidence that the widespread environmental contaminant caffeine alters energy balance or stress responses in fish
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IronRefs database of bibliographic data on remediation of contaminated environmental materials using zerovalent metals such as iron (ZVI)
<p>Database of bibliographic data for publications (journal articles, reports, patents, presentation abstracts, etc.) on the use of zerovalent metals (ZVMs)—especially zerovalent iron (ZVI)—for remediation or treatment of contaminated environmental materials (mainly groundwater, but also wastewater, soil, and sediment).</p> <p>The data were compiled and curated between 1996 and 2011 by members of the research group of Professor Paul G. Tratnyek at the Oregon Graduate Institute in Beaverton, Oregon, USA. At the beginning, the field was very small and most new work appeared first in gray-literature, so manual curation of the database made it a uniquely-valuable resource for the community.</p> <p>The original list of references was replaced with a searchable online database in 1998, which was named the “IronRefs” database and made available to all at <a href="http://cgr.ebs.ogi.edu/ironrefs/">http://cgr.ebs.ogi.edu/ironrefs/</a>. The database was updated periodically until 2011, by which time the field had grown so large that it was no longer practical to keep up with all of the new publications.</p> <p>The early development and impact of the IronRefs database was documented when it reached 500 records (Tratnyek, 2002) and when it reached 1000 records (Schneider et al., 2008). The former was published as an article in Groundwater Monitoring and Remediation (DOI: 10.1111/j.1745-6592.2002.tb00757.x) and the latter was given as a poster at the 6th International Conference on Chlorinated and Recalcitrant Compounds, Monterey, CA (PDF included here).</p> <p>In 2019, the server containing IronRefs was retired, so this unique resource became unavailable. In place of IronRefs, we provide here all of the data (2000+ records) in two tagged-field formats that are compatible with most bibliographic data management software: an EndNote compressed library (.enlx) and an RIS file (.ris). We also exported the data to a tab-delimited text file and provide that in .csv and .txt formats.</p> <p>Note that no new records were added to the IronRefs database after about mid-2011, so the value of the dataset provided here is largely historical. There are many newer publications that are relevant, and the literature on this topic continues to grow rapidly as of 2020.</p>
Environmental Contaminants and Infant Development
ClinicalTrials.gov study NCT00013858. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Environmental Exposure to Heavy Metals, Nanoparticles, and Emergent Contaminants and Risk of Allergic Diseases
ClinicalTrials.gov study NCT06529913. IPD Sharing: NO. Countries: 1. Publications: 9.
Data from: Multiple stressors in a top predator seabird: potential ecological consequences of environmental contaminants, population health and breeding conditions
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Accumulation of airborne, eukaryotic environmental DNA contamination: Raw sequencing data and demultiplexing info
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Early life exposure to environmental contaminants (BDE-47, TBBPA, and BPS) produced persistent gut dysbiosis in adult male mice
<p><span>The gut microbiome is a pivotal player in toxicological responses. We investigated the effects of maternal exposure to 3 human health-relevant toxicants (BDE-47, TBBPA, and BPS) on the composition and metabolite levels (bile acids [BAs] and short chain fatty acids [SCFAs]) of the gut microbiome in adult pups. CD-1 mouse dams were orally exposed to vehicle (corn oil, 10ml/kg), BDE-47 (0.2 mg/kg), TBBPA (0.2 mg/kg), or BPS (0.2 mg/kg) once daily from gestational day 8 to the end of lactation (postnatal day 21). 16S rRNA sequencing and targeted metabolomics were performed in fecal DNA of 12-week-old adult male pups (n=14-23/group). BPS had the most prominent effect on the beta-diversity of the fecal microbiome compared to TBPPA and BDE-47 (QIIME). Seventy-three taxa were persistently altered by at least 1 chemical, and 12 taxa were commonly regulated by all chemicals (most of which were from the <i>Clostridia</i> class and were decreased). The most distinct microbial biomarkers were <i>S24-7</i> for BDE-47,<i> Rikenellaceae </i>for TBPPA, and <i>Lactobacillus</i> for BPS (LefSe). The community-wide contributions to the shift in microbial pathways were predicted using FishTaco. Fecal BA output was persistently increased by all chemicals (LC-MS). TBBPA increased propionic acid and succinate, whereas BPS decreased acetic acid (GC-MS. In conclusion, maternal exposure to these toxicants persistently modified fecal microbiome and metabolites later in life, and dysbiosis may contribute to the mechanisms of developmental origins of adult-onset of toxic outcomes. </span></p>
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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.