Find research datasets worth reusing

opencc-by-4.0Apr 2020View details →

MicroED datasets of peptide crystals (AVAAGA) at different accumulated electron exposures

Continuous rotation data sets in SMV format were collected on a Tecnai F30 (300 kv) equipped with a TVIPS TEM CAM XF416 detector. Datasets were collected from 3 different crystals. To simulate increasing dose each crystal had 4 datasets collected from it with an approximate fluence of 3 e- Å2 per dataset (12 e- Å2 total accumulated exposure per crystal). Datasets at each exposure were indexed with XDS and merged with XSCALE to produce a final set of intensities at each total exposure. Experimental parameters are as follows: Accelerating voltage: 300 kV Wavelength: 0.019687 Cameralength: 1320 mm Exposure time: 3 s Rotation speed: 0.3 degrees s-1 Rotation: +/- 45 degrees  Detector area: 2048 x 2048 (Bin 2) Pixel size: 0.031 mm Spot size: 11 C2 aperture: 20 µm SA aperture: 1 µm Datasets are grouped as follows: Crystal 1 = mov1-4, Crystal 2 = mov5-8, Crystal 3 = mov9-12. An example XDS and XSCALE file are provided. Note: It has been brought to our attention that the zip file does not always unpack in a linux environment. The following workaround was found by T. Nakane using OpenJDK (17.0.1) <code>jar -xvf</code> AVAAGA_dose_series.zip

opencc-by-4.0Dec 2021View details →

Exposure of boreal aapa mires to climate change

This repository contains four zipped data files which contain (i) the spatial distribution of aapa mire complexes (‘aapa mires’) and their wettest flark-dominated parts (‘wet aapa mires’) situated in the aapa mire and palsa mire zones of Finland, as selected for the study by Heikkinen et al. (in review), (ii)  values for the six bioclimatic variables (growing degree days, mean January and July temperature, annual precipitation, and May and July water balance) averaged for the years 1981–2010, and developed for the studied aapa mires and wet aapa mires using a 50 x 50 m lattice system, and (iii) values for the same six bioclimatic variables developed for future climates and the two types of study mires, based on the global climate models for 2040–2069 and two Representative Concentration Pathways (RCP4.5 and RCP8.5), and (iv) values of climate velocity metrics calculated for the six bioclimatic variables and the two types of study mires. These data provide the essential data employed in conducting the analysis in the following work: Risto K. Heikkinen1, Kaisu Aapala1, Niko Leikola1 and Juha Aalto2: Exposure of boreal aapa mires to climate change, in review. 1 Biodiversity Centre, Finnish Environment Institute, Latokartanonkaari 11, FI-00790 Helsinki, Finland 2 Finnish Meteorological Institute, Weather and climate change impact research, Helsinki, Finland The data files are embedded in four compressed zip files (one of them including a geodatabase folder with files) which include several ArcGIS compatible tiff-raster or shape files. The names and contents of the four zipped files are as follows: (1) mires.zip – includes shape files describing the location and spatial configuration of the aapa mires (‘Aapa_mires.shp’) and the wet aapa mires (‘Wet_aapa_mires.shp’) included in the study, and the borders of different mire zones in Finland (‘Mire_zones.shp’); (2) climate_data_aapa_mires.zip – includes 18 tiff raster files showing the values of the six bioclimatic variables in the studied aapa mires within the 50 x 50 m resolution grid. The data in this zipped file include climate data averaged for the years 1981 – 2010 and for the future time slice of 2040–2069 and two Representative Concentration Pathways (RCP4.5 and RCP8.5); (3) climate_data_wet_aapa_mires.zip – includes 18 tiff raster files showing the values of the six bioclimatic variables in the studied wet aapa mires within the 50 x 50 m resolution grid. Similarly as in (2), the data in this zipped file include climate data averaged for the years 1981 – 2010 and for the future time slice of 2040–2069 and two Representative Concentration Pathways (RCP4.5 and RCP8.5); (4) velocity_data_for_mires.zip – includes zipped geodatabase folder velocity_open_mires.gdb which, in turn, includes spatial ArcGIS surfaces for the climate change velocity metric calculated for all the six bioclimatic variables, and the two types of mires and the two RCPs. In the zipped files (2) and (3), first part of the names of the included files refer to one of the six bioclimatic variables as follows: GDD5 – growing degree days, PREC – annual precipitation, TEMP_Jan – mean January temperature, TEMP_July – mean July temperature, WAB_May – May water balance, WAB_July – July water balance; and the remaining part of the name indicates the time period, type of the RCP and that of the mire.   It should be noted that these data are embargoed until the end of the SUMI project for which they were developed, i.e. 1.1.2023. The coordinate system for the data files is: ETRS-TM35FIN (EPSG: 3067) (or YKJ Finland/Finnish Uniform Coordinate System (EPSG: 2393)). Summarization of the key settings of the study is provided below. A detailed treatment is included in the manuscript Heikkinen et al. (in review). Once the manuscript is accepted for publication an updated link will be provided. Study system: Aapa mires are waterlogged, peat-accumulating EU Habitats Directive priority habitats whose ecological conditions and biodiversity values may be jeopardized by climate change. Aapa mires depend on the surface water flows from the surroundings which makes them sensitive to hydrological alterations and falling water tables caused by land use (ditching for peatland drainage) as well as climate change (Gong et al. 2012, Sallinen et al. 2019). This sensitivity of aapa mires and their biodiversity to increasing temperatures and decreasing water balance and precipitation can be of particular concern as they occur in northern hemisphere, in areas where the largest climatic changes are projected to take place (AMAP 2017, Väliranta et al. 2017. Kolari et al. 2021). In the study by Heikkinen et al. (in review), we assess the climate exposure of these habitats by developing velocity metrics for both the aapa mire complexes (‘aapa mires’) and their wettest flark-dominated parts (‘wet aapa mires’) in Finland. Aapa mire data: Occurrences of aapa mires were identified from the CORINE CLC2018 land cover data which is available in Finland as a 20 x 20 m resolution raster data, by focusing on the CORINE category 4121 (‘Peatbogs’) which includes various open mires occurring in aapa mire and palsa mire zones, as well as in raised bogs zones. We excluded open mires occurring in the raised bogs zone but included CORINE Peatbog occurrences both from the aapa mire and palsa mire zones. This opted for this decision because open mires in aapa and palsa mire zones share several matching ecological features, and because palsa mires may provide suitable habitats for aapa mire species under warming climate. The adjacent peatbog 20-m pixels in the aapa and palsa mire zones were merged and converted into contiguous peatland polygons. From these, polygons smaller than 10 ha in size were excluded because typically they show only limited number of ecological elements central to the representative aapa mires. These selected ≥10 ha peatland polygons formed the first study mire dataset, aapa mire complexes, or ‘aapa mires’ in short (i.e., the whole aapa mire ecosystem containing all embedded mire habitats therein). The second study mire dataset was constrained to include only the wettest parts of aapa mire complexes characterized by flarks, i.e., open water pools, referred here simply as ‘wet aapa mires’. These wet aapa mire occurrences are typically smaller than the whole aapa mire complexes and occur more sparsely in the landscape. Thus, the climatic exposure of wet aapa mires can be expected to be greater than that of aapa mire complexes. This will very likely cause elevated climate change adaptation challenges for habitat specialist species that require open water or permanently wet environments. The spatial data for the wet aapa mires were determined with the help of the topographic database developed by the National Land Survey of Finland (NLS), and the land cover class ‘Swamps classified as difficult, dangerous and impossible to cross’ therein. Climate data: In the first phase, monthly average air temperature data for 1981–2010 were constructed at the 50 x 50 m spatial resolution across Finland, as described in Aalto et al. (2017) and Heikkinen et al. (2020, 2021). This was done by modelling the weather station data from 313 Fennoscandian stations together with variables of geographical location, local topography and water cover. Monthly precipitation data were developed by fitting kriging interpolation method to the data on 343 rain gauges, and the data on geographical location, topography and proximity to the sea. Based on the monthly temperature and precipitation data, six bioclimatic variables describing key ecological winter- and summer-time conditions for aapa mire ecosystems were calculated (cf. Parviainen and Luoto 2007, Ruuhijärvi 1988, Rydin and Jeglum 2006): (1) annual temperature sum above the base temperature of 5 °C (growing degree days, GDD5), (2) mean January temperature, (3) mean July temperature, (4) monthly climatic water balance calculated for May and (5) for July, and (6) annual precipitation sum. The two climatic water balance variables were calculated as the difference between the May - or July - total precipitation sum and the potential evapotranspiration (PET) in the corresponding month following Skov and Svenning (2004). In the second step, the data based on an ensemble of 23 global climate models from the Coupled Model Intercomparison Project (CMIP5) archives (Taylor et al. 2012) were employed to develop future climate surfaces averaged for the years 2040–2069 and the two Representative Concentration Pathways (RCP4.5 and RCP8.5). The monthly air temperature and precipitation data in these climate surfaces were interpolated to match the 50 × 50 m grid, then the change predicted by the GCMs was added to the 1981–2010 climate data, and finally, the values for the six bioclimatic variables were recalculated for the 50-m resolution grid across the whole Finland. In the third step, all the developed climate surface datasets were intersected by the spatial datasets of the two differently delimited aapa mire networks, i.e. ‘aapa mires’ and ‘wet aapa mires’. This allowed calculation of the climate change velocity metrics separately for the two types of aapa mires, namely, for both mire datasets by measuring the distance between climatically similar 50-m grid cells in the present and future climates by considering only locations with either (i) aapa mires, or (ii) wet aapa mires. Thus, matrix areas providing unsuitable habitat for aapa mire biodiversity were excluded and for both types of mires the distance from the present-day mire cell was linked to the nearest corresponding mire cell with similar future climatic conditions. The climate data for the years 1981 – 2010 and the future time slice of 2040–2069 and the two Representative Concentration Pathways (RCP4.5 and RCP8.5), clipped to the networks of the two types of aapa mires for all the six bioclimatic variables are included in the following two zipped files: ‘climate_data_aapa_mires.zip’ and ‘climate_data_wet_aapa_mires.zip’. Climate change velocity metrics: The climate velocities for the six bioclimatic variables, developed separately for the two types of aapa mires and the two RCPs, were calculated with climate-analog method (see Brito-Morales et al. 2018). For these calculations, both the present-day and future climate data from the two RCP scenarios were converted from continuous values into categorical climate surfaces following Hamann et al. (2015). During these conversion processes, following categories and within-class ranges were used: GDD5, within-class range 50 °C; January and July temperatures, within-class range 0.5 °C; water balance of May and July, within-class range 2.5 mm; and annual precipitation, within-class range 25 mm. In the conversion process, the climate surfaces in each of the 50-m grid cells were reclassified into one of the 29 GDD5, 27 January temperature, 22 July temperature, 21 May water balance, 22 July water balance, and 19 annual precipitation categories. Using the reclassified climate surfaces, the minimum distances between mire grid cells with similar present-day and future climates for the six variables were determined with the Euclidean distance function in ArcGIS. In the final step of calculating the velocity metrics, the mire-to-mire distances were divided by the number of years between the two points in time (see Brito-Morales et al., 2018; Heikkinen et al., 2020). The derived velocity metrics for the six bioclimatic variables yielded six individual estimates of climate exposure for the two types of study mires, illustrating the magnitude of climate displacement that the local mire species communities are projected to experience (Hamann et al. 2015, Brito-Morales et al., 2018). In our study, for each contiguous aapa mire and wet aapa mire, the mean velocity value for the climate variables were calculated as the average of the 50-m grid cells included in it. The data on the 50-m resolution velocities for the six bioclimatic variables and the two types of aapa mires and the two RCPs are included in the zip file ‘velocity_data_for_mires.zip’. References Aalto, J., Riihimäki, H., Meineri, E., Hylander, K., Luoto, M. (2017) Revealing topoclimatic heterogeneity using meteorological station data. International Journal of Climatology 37, 544-556. AMAP (2017) Snow, Water, Ice and Permafrost in the Arctic (SWIPA) 2017. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. Brito-Morales, I., García Molinos, J., Schoeman, D.S., Burrows, M.T., Poloczanska, E.S., Brown, C.J., Ferrier, S., Harwood, T.D., Klein, C.J., McDonald-Madden, E., Moore, P.J., Pandolfi, J.M., Watson, J.E.M., Wenger, A.S., Richardson, A.J. (2018) Climate Velocity Can Inform Conservation in a Warming World. Trends in Ecology & Evolution 33, 441-457. Gong, J., Wang, K., Kellomäki, S., Zhang, C., Martikainen, P.J., Shurpali, N. (2012) Modeling water table changes in boreal peatlands of Finland under changing climate conditions. Ecological Modelling 244, 65-78. Hamann, A., Roberts, D.R., Barber, Q.E., Carroll, C., Nielsen, S.E. (2015) Velocity of climate change algorithms for guiding conservation and management. Global Change Biology 21, 997-1004. Heikkinen, R.K., Kartano, L., Leikola, N., Aalto, J., Aapala, K., Kuusela, S., Virkkala, R. (2021) High-latitude EU Habitats Directive species at risk due to climate change and land use. Global Ecology and Conservation 28, e01664. Heikkinen, R.K., Leikola, N., Aalto, J., Aapala, K., Kuusela, S., Luoto, M., Virkkala, R. (2020) Fine-grained climate velocities reveal vulnerability of protected areas to climate change. Scientific Reports 10. Kolari, T.H.M., Sallinen, A., Wolff, F., Kumpula, T., Tolonen, K., Tahvanainen, T. (2021) Ongoing Fen–Bog Transition in a Boreal Aapa Mire Inferred from Repeated Field Sampling, Aerial Images, and Landsat Data. Ecosystems. Parviainen, M., Luoto, M. (2007) Climate envelopes of mire complex types in fennoscandia. Geografiska Annaler: Series A, Physical Geography 89, 137-151. Ruuhijärvi, R., (1988) Mire vegetation. Atlas of Finland 141-143. Biogeography, nature conservation. . National Board of Survey and Geographical Society of Finland, Helsinki, pp. 2-4. Rydin, H., Jeglum, J. (2006) The biology of peatlands. Oxford University Press, Oxford. Sallinen, A., Tuominen, S., Kumpula, T., Tahvanainen, T. (2019) Undrained peatland areas disturbed by surrounding drainage: a large scale GIS analysis in Finland with a special focus on aapa mires. Mires and Peat 24, 1-22. Skov, F., Svenning, J.-C. (2004) Potential impact of climatic change on the distribution of forest herbs in Europe. Ecography 27, 366-380. Taylor, K.E., Stouffer, R.J., Meehl, G.A. (2012) An Overview of CMIP5 and the Experiment Design. Bulletin of the American meteorological Society 93, 485-498. Väliranta, M., Salojärvi, N., Vuorsalo, A., Juutinen, S., Korhola, A., Luoto, M., Tuittila, E.-S. (2017) Holocene fen–bog transitions, current status in Finland and future perspectives. The Holocene 27, 752-764.

opencc-by-4.0Jan 2022View details →

Supplemental Data for "Embryonic Exposure to Tryptophan Yields Bullying Victimization via Reprogramming the Microbiota-Gut-Brain Axis in a Chicken Model"

This is data set associated with an article "Embryonic Exposure to Tryptophan Yields Bullying Victimization via Reprogramming the Microbiota-Gut-Brain Axis in a Chicken Model" by Xiaohong Huang, Jiaying Hu, Haining Peng, and Heng-wei Cheng, including Supplemental Table S1, S2, S3, S4, S5, S6.

opencc-by-4.0Feb 2022View details →

SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8 T cells

This dataset contains aggregated CellRanger output for six 10x Genomics (5'GEX+abTCR+Feature barcoding) experiments from the study by Minervina, Pogorelyy et al (<a href="https://www.medrxiv.org/content/10.1101/2021.07.12.21260227v3">medrxiv</a>).  The scripts to process it further are available at github (<a href="https://github.com/pogorely/COVID_vax_CD8">repository</a>).  Raw sequencing data is available at SRA (acc. PRJNA744851)

opencc-by-4.0Mar 2022View details →

Influence of a portable air cleaner location on the exposure to exhaled contaminants in hospital rooms

Indoor environments with a deficient mechanical ventilation, could increase exposure to exhaled contaminants. This situation is critical in hospital environments such as hospital rooms. In this situation, a portable air cleaner system based on high efficiency air filters maybe a solution by itself or combined with mechanical ventilation systems to reduce the concentration of aerosols in hospital room environments. In this study the influence of the location of a portable air cleaner based on high efficiency air filters on the exposure to exhaled contaminants of a health worker close to a patient lying on a bed was investigated. The experimental setup consists of a hospital room (40.84 m3) with two breathing thermal manikins, BTM. One BTM was lying on the bed (patient) and the other BTM was stand up near the bed (health worker). Each BTM has its own independent breathing system with the capability of performing different breathing flows. Both BTM inhale and exhale through the mouth with a respiration frequency of 17.90 min-1 (inhalation) and 16.43 min-1 (exhalation). Both has minute volume 9.46 (l/min) and tidal volume 0.55 l. The BTM lying on a bed, simulated the source of exhaled contaminants and exhales particles sized 0.57-0.76 µm. A total air flow rate of 150 m3/h (3.67 ACH) was used in all experimental tests. The total air flow rate was generated only by the air cleaner, only by the ventilation system or using a combination of the air cleaner and the ventilation system. The concentration of particles was measured in the inhalation of the standing BTM close to bed, and in other points of the room to analyse the influence of air cleaner location on the exposure to airborne contaminants. The results suggest that the air diffusion plays an important role in the exposure to exhaled contaminants in a hospital room. In these indoor environments, low values in the exposure to exhaled contaminants can be obtained using a combination of a portable air cleaner located near the source of contaminants and the ventilation system or using only 100% air flow rate in the ventilation system.

opencc-by-4.0Feb 2022View details →

S93 | CECMOUTHING | Chemicals of Emerging Concern (CECs) in children's mouthing exposure

This is the collection associated with list S93 CECMOUTHING | Chemicals of Emerging Concern (CECs) in children's mouthing exposure on the NORMAN Suspect List Exchange. <a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a>   A dataset of 60 Chemicals of Concern (CECs) and their chemical migration rate into saliva due to mouthing exposure in children studied in Aurisano et. al DOI:<a href="https://www.nature.com/articles/s41370-021-00354-0">10.1038/s41370-021-00354-0</a>. This dataset was used to develop a regression model for predicting migration rates for manifold chemical-material combinations to support high-throughput screening.   Structural identifiers and mapping to DTXSID provided by ECI.

openother-openNov 2022View details →

Impacts of wind power on air quality, premature mortality, and exposure disparities in the United States

This repo includes supporting material for the publication: Qiu, M., Zigler, C. M., & Selin, N. E. (2022). Impacts of wind power on air quality, premature mortality, and exposure disparities in the United States. Science Advances, 8(48), eabn8762. Please download and unzip the file "<a href="https://zenodo.org/api/files/bef77248-ca65-4ae6-9a92-ad00fc068665/mhqiu/wind_pollution_EJ-v1.0.zip?versionId=a9b5b8e9-273c-4431-a101-4f9a4c331675">mhqiu/wind_pollution_EJ-v1.0.zip</a>". Please see README for a full description of the sample data included in this repo.  README 1. Regression results:  EGU_regression_scenario_results.xlsx  It includes regression results for each EGU in our sample (1264 EGUs in total).  2. Air quality simulation results: 2.1 GEOS-Chem simulation GC_daily_pm25_o3_scenarios.nc  It contains surface level annual mean PM2.5 and MDA8 O3 concentration under different emission scenarios. We include four scenarios in total: - baseline scenario: air quality **without** the amount of wind power associated with 2014 RPS targets  - expost scenario:  air quality with the wind power associated with 2014 RPS targets under the current dispatch decisions - health damage minimizing scenario: air quality with the wind power associated with 2014 RPS targets under a hypothetical dispatch scenario that minimizes the health damage - CO2 minimizing scenario: air quality with the wind power associated with 2014 RPS targets under a hypothetical dispatch scenario that minimizes the CO2 emissions Therefore, to calculate the air quality impacts of wind power under different dispatch decisions:   current (ex post) = ex post - baseline.   health damage minimizing =  health damage minimizing - baseline.   CO2 minimizing scenario = CO2 minimizing - baseline.   2.2 InMAP simulations InMAP/xx.shp   The shapefiles contain annual mean PM2.5 concentration simulated with InMAP under different emission scenarios.   baseline.shp: baseline scenario   ex post.shp: ex post scenario   health_damage_minimizing.shp: health damage minimizing scenario   co2_minimizing.shp: CO2 minimizing scenario Descriptions of the four scenarios are the same as above for GEOS-Chem. 3. County-level air quality change for different demographic groups (GEOS-Chem) county_pm_o3_changes_by_groups_GEOS_CHEM.xlsx   This file contains changes in county-level simulated PM2.5 and O3 concentrations due to wind power under different scenarios. It also includes the total population at the county level and the population for each subgroup. This data can be used to calculate the distributional effects of air quality benefits across different population groups.

opencc-zeroApr 2022View details →

Data: Interactive effects of drought and edge exposure on old-growth forest understory species

Context: Both climatic extremes and land-use change constitute severe threats to biodiversity, but their interactive effects remain poorly understood. In forest ecosystems, the effects of climatic extremes can be exacerbated at forest edges. Objectives: We explore the hypothesis that an extreme summer drought reduced the richness and coverage of old-growth forest species, particularly in forest patches with high edge exposure. Methods: Using a high-resolution spatially explicit precipitation dataset, we could detect variability in drought intensity during the summer drought of 2018. We selected 60 old-growth boreal forest patches in central Sweden that differed in their level of drought intensity and amount of edge exposure. The year after the drought, we surveyed red-listed and old-growth forest indicator species of vascular plants, lichens and bryophytes. We assessed if species richness, composition, and coverage were related to drought intensity, edge exposure, and their interaction. Results: Species richness was negatively related to drought intensity in forest patches with a high edge exposure, but not in patches with less edge exposure. Patterns differed among organism groups and were strongest for cyanolichens, epiphytes associated with high-pH bark, and species occurring on convex substrates such as trees and logs. Conclusions: Our results show that the effects of an extreme climatic event on forest species can vary strongly across a landscape. Edge exposed old-growth forest patches are more at risk under extreme climatic events than those in continuous forests. This suggest that maintaining buffer zones around forest patches with high conservation values should be an important conservation measure.

opencc-by-4.0Apr 2022View details →

Response of Plutella xylostella to the sublethal exposure of fluxametamide under laboratory conditions

Data set generated during the laboratory experiments on toxicity of fluxametamide against diamondback moth Plutella xylostella, and its sublethal effects on life table parameters of this pest. Fluxametamide exhibited an exceptional insecticidal activities against the larval stages of Plutella xylostella. This is a raw data set with the replication for each treatments.

Exposure to 3, 3', 4, 4', 5-pentachlorobiphenyl (PCB 126) causes widespread DNA hypomethylation in adult zebrafish testis

Exposure to environmental toxicants during preconception have been shown to affect offspring health and epigenetic mechanisms such as DNA methylation are hypothesized to be involved in adverse outcomes. However, studies addressing the effects of exposure to environmental toxicants during preconception on epigenetic changes in gametes are limited. The objective of this study is to determine the effect of preconceptional exposure to a dioxin-like PCB (PCB126) on DNA methylation and gene expression in testis. Adult zebrafish were exposed to 3 and 10 nM PCB126 for 24 hours and testis tissue was sampled at 7 days post-exposure for histology, DNA methylation and gene expression profiling. Reduced Representation Bisulfite Sequencing revealed 37 and 92 differentially methylated regions (DMRs) in response to 3 and 10nM PCB126 exposures, respectively. Among them 19 DMRs were found to be common between both PCB126 treatment groups. Gene ontology (GO) analysis of DMRs revealed that enrichment of terms such as RNA processing, iron-sulfur cluster assembly and gluconeogenesis. Gene expression profiling showed differential expression of 40 and 1621 genes in response to 3 and 10nM PCB126 exposures, respectively. GO analysis revealed differential expression of genes related to xenobiotic metabolism, oxidative stress and immune function. There is no overlap in the GO terms or individual genes between DNA methylation and RNAseq results, but functionally many of the altered pathways have been shown to cause spermatogenic defects. Our results indicate that exposure to dioxin-like PCBs during preconception could affect testicular function by altering DNA methylation patterns, with significant implications for reproductive health.

Effects of acute exposure to polystyrene nanoplastics on the channel catfish larvae: Insights from energy metabolism and transcriptomic analysis

Microplastics (nanoplastics) pollution has been a major ecological issue threatening global aquatic ecosystems. However, knowledge of the adverse effects of nanoplastics and the effects on freshwater ecosystems is still limited. To understand the impacts of nanoplastics on freshwater ecosystems, it is essential to reveal the physiological changes caused by nanoplastics in freshwater organisms, especially at their early life-history stages. In the present study, the larval channel catfish Ietalurus punetaus were exposed to gradient concentrations (0, 5, 10, 25 and 50 mg/L) of 75-nm polystyrene nanoplastics (PS-NPs) for 24 h or 48 h, and changes in contents of energy metabolites, metabolic enzyme activities and transcriptome were assessed. The results showed glucose and triglyceride contents increased after 24 h of exposure to 10 or 25 mg/L of PS-NPs but decreased with increased concentrations or prolonged exposure duration. Activities of most metabolic enzymes analyzed decreased in the larvae after 48 h of exposure, especially in 25 or 50 mg/L of PS-NPs. These suggested that PS-NPs caused huge energy consumption and disturbed the energy metabolism in larval fish. Transcriptomic analysis showed that 48 h of exposure to 50 mg/L PS-NPs affected the expression of genes involved in protein digestion and induced response of proteasomes or heat shock proteins in the larval I. punetaus. The genes involved in peroxisome proliferator-activated receptors (PPAR) pathway and biosynthesis of amino acids were activated after the exposure. PS-NPs also depressed the expression of the genes involved in gonad development or muscle contraction in the larval I. punetaus. Overall, acute exposure to 75-nm PS-NPs disrupted the energy metabolism by consuming the energy reserves, and affected a series of molecular pathways which may further affect the development and survival of fish. This study provided the information about adverse effects of nanoplastics on the fish larvae and revealed the molecular pathways for the potential adverse outcomes.

Single-cell phenotypic characteristics of tolerance under recurring antibiotic exposure in Escherichia coli

Non-heritable drug resistance, such as tolerance and persistence towards antibiotics, is little characterized compared to genetic resistance. Tolerance and persistence allow cells to survive application of antibiotics that are bactericidal to non-tolerant cells. Non-heritable drug resistance challenges antibiotic treatment, particularly of recurrent infections, and have implications towards heritable resistance evolution. Tolerant cells have commonly been characterized as growth arrested cells prior and during antibiotic application that quickly resume growth post-application. Here, we explore characteristic of tolerant and susceptible E. coli single bacteria cells to different levels of recurrent antibiotic exposure and quantify their occurrence. In using a high throughput single-cell microfluidic device, we find that tolerant cells reduce their growth rate by about 50%, but contrary to previous findings do not go into growth arrest or near growth arrest. The growth reduction is induced by antibiotic exposure and not caused by a stochastic switch or predetermined state as previously described. Cells exhibiting constant intermediate growth survived best under antibiotic exposure and selection did not primarily act on fast growing cells, as expected for a β-lactam antibiotic. Control experiments on population cultures confirmed and challenged scaling of single cell findings to population level processes. Our findings suggest a prevalent type of tolerance that differs from previously described tolerance and persister characteristics. Our described characteristics and its high frequency of occurrence supports acclaims of an underappreciated role of tolerant cells towards resistance evolution.

Flower plantings support wild bee reproduction and may also mitigate pesticide exposure effects

1. Sustainable agriculture relies on pollinators, and wild bees benefit yield of multiple crops. However, the combined exposure to pesticides and loss of flower resources, driven by agricultural intensification, contribute to declining diversity and abundance of many bee taxa. Flower plantings along the margins of agricultural fields offer diverse food resources not directly treated with pesticides. 2. To investigate the potential of flower plantings to mitigate bee pesticide exposure effects and support bee reproduction, we selected replicated sites in intensively farmed landscapes where half contained flower plantings. We assessed solitary bee Osmia lignaria and bumble bee Bombus vosnesenskii nesting and reproduction throughout the season in these landscapes. We also quantified local and landscape flower resources and used bee-collected pollen to determine forage resource use and pesticide exposure and risk. 3. Flower plantings, and their local flower resources, increased O. lignaria nesting probability. Bombus vosnesenskii reproduction was more strongly related to landscape than local flower resources. 4. Bees at sites with and without flower plantings experienced similar pesticide risk, and the local flowers, alongside flowers in the landscape, were sources of pesticide exposure particularly for O. lignaria. However, local flower resources mitigated negative pesticide effects on B. vosnesenskii reproduction. 5. Synthesis and applications. Bees in agricultural landscapes are threatened by pesticide exposure and loss of flower resources through agricultural intensification. Therefore, finding solutions to mitigate negative effects of pesticide use and flower deficiency is urgent. Our findings point towards flower plantings as a potential solution to support bee populations by mitigating pesticide exposure effects and providing key forage. Further investigation of the balance between forage benefits and added pesticide risk is needed to reveal contexts where net benefits occur.

opencc-by-4.0May 2022View details →

Supplemental data and code for Climate change will amplify the inequitable exposure to compound heatwave and ozone pollution

Supplemental data and code for Climate change will amplify the inequitable exposure to compound heatwave and ozone pollution

opencc-by-4.0Jul 2022View details →

Soil ecotoxicology needs robust biomarkers – a meta-analysis approach to test the robustness of gene expression-based biomarkers for measuring chemical exposure effects in soil invertebrates

Gene expression-based biomarkers are regularly proposed  as rapid, sensitive and mechanistically informative tools to identify whether soil invertebrates are experiencing adverse effects due to chemical exposure. However, before biomarkers could be deployed within diagnostic studies, systematic evidence of the robustness of such biomarkers to detect effects  is needed. Here, we present an approach for conducting a systematic meta-analysis of the robustness of gene expression-based biomarkers in soil invertebrates. The approach was developed and trialled for two measurements of gene expression commonly proposed as biomarkers in soil ecotoxicology: metallothionein (MT) gene expression in earthworms for metals and heat shock protein 70 (HSP70) gene expression in earthworms for organic chemicals. From a systematic analysis of the published literature, we collected 294 unique gene expression data points and used linear mixed-effect models to assess concentration, exposure duration and species effects on the quantified response. This database provided contains gene-expression data from publications that have used gene expression-based biomakers to study effects of chemical pollutants on soil invertebrates. R scripts are provided that were used to study the patterns of gene expression as reported in accompanying publication.  We encourage colleagues in the field to apply this approach to other biomarkers, as such quantitative assessment is a prerequisite to ensuring that the suitability and limitations of proposed biomarkers are known and stated.

opencc-zeroJun 2022View details →

Exposure to a fungal pathogen increases the critical thermal minimum of two frog species Datasets

This dataset contains data from a laboratory experiment described in the paper: Siddons, S. R., and Searle, C. L. (Accepted). Exposure to a fungal pathogen increases the critical thermal minimum of two frog species. Ecology and Evolution. The experiment examined how exposure to a virulent fungal pathogen, Batrachochytrium dendrobatidis (Bd), affected the critical thermal minimum (CTmin) of two frog species, Hyla versicolor (gray treefrog) and Lithobates palustris (pickerel frog). The CTmin is the minimum thermal performance point of an organism, which we estimated via righting response trials. For both frog species, the frogs were held in a beaker partially submerged in a circulating water at 15°C. At each 1-degree temperature decrease every 2.5 minutes, the frog was gently flipped onto their back and observed for how quickly they were able to right themselves ("Decreasing" trial). Frogs were considered unable to right themselves when they did not do so within 10 seconds. Another trial was conducted for each frog ("Constant" trial ), in which they were flipped onto their backs every 2.5 minutes while keeping the temperature at a constant 15°C. Main results of the experiment are that, for both species, the CTmin was higher for Bd-exposed frogs than unexposed frogs, and the CTmin of H. versicolor was higher than L. palustris. We also found that Bd-exposed frogs of both species righted themselves significantly fewer times in both decreasing and constant temperature trials. Finally, we observed higher mortality in Bd-exposed individuals throughout the experiment after Bd exposure for both species compared to unexposed individuals, with no difference between species.

opencc-zeroJul 2022View details →

Transcriptional response of mushrooms to artificial sun exposure

Climate change causes increased tree mortality leading to canopy loss and thus sun-exposed forest floors. Sun exposure creates extreme temperatures and radiation, with potentially more drastic effects on forest organisms than the current increase in mean temperature. Such conditions might potentially negatively affect the maturation of mushrooms of forest fungi. A failure of reaching maturation would mean no sexual spore release and, thus, entail a loss of genetic diversity. However, we currently have a limited understanding of the quality and quantity of mushroom-specific molecular responses caused by sun exposure. Thus, to understand the short-term responses towards enhanced sun exposure, we exposed mushrooms of the wood-inhabiting forest species Lentinula edodes, while still attached to their mycelium and substrate, to artificial solar light (ca. 30 °C and 100.000 lux) for 5, 30, and 60 minutes. We found significant differentially expressed genes at 30 and 60 minutes. Eukaryotic Orthologous Groups (KOG) class enrichment pointed to defense mechanisms. The 20 most significant differentially expressed genes showed the expression of heat-shock proteins, an important family of proteins under heat stress. Although preliminary, our results suggest mushroom-specific molecular responses to tolerate enhanced sun exposure as expected under climate change. Whether mushroom-specific molecular responses are able to maintain fungal fitness under opening forest canopies remains to be tested.

opencc-zeroAug 2022View details →

Evolutionary consequences of pesticide exposure include transgenerational plasticity and potential terminal investment transgenerational effects

Transgenerational plasticity, the influence of the environment experienced by parents on the phenotype and fitness of subsequent generations, is being increasingly recognised. Human-altered environments, such as those resulting from the increasing use of pesticides, may be major drivers of such cross-generational influences, which in turn may have profound evolutionary and ecological repercussions. Most of these consequences are, however, unknown. Whether transgenerational plasticity elicited by pesticide exposure is common, and the consequences of its potential carry-over effects on fitness and population dynamics remains to be determined. Here we investigate whether exposure of parents to a common pesticide elicits intra-, inter- and transgenerational responses (in F0, F1 and F2 generations) in life-history (fecundity, longevity, and lifetime reproductive success-LRS-), in an insect model system, the seed beetle Callosobruchus maculatus. We also assessed sex-specificity of the effects. We found sex-specific and hormetic intergenerational and transgenerational effects on longevity and lifetime reproductive success, manifested both in the form of maternal and paternal effects. In addition, the transgenerational effects via mothers detected in this study are consistent with a new concept: terminal investment transgenerational effects. Such effects could underlie cross-generational responses to environmental perturbation. Our results indicate that pesticide exposure leads to unanticipated effects on population dynamics and have far-reaching ecological and evolutionary implications.

opencc-by-4.0Aug 2022View details →

GDP Exposure in Low-Elevation Coastal Zones of China

GDP Exposure in Low-Elevation Coastal Zones of China Feixiang Li1, Liwei Mao2, Qian Chen1, Xuchao Yang1* 1 Ocean College, Zhejiang University, Zhoushan 316021, China. 2 Hangzhou City Planning and Design Academy, Hangzhou 310012, China Recommended citation    Article citation will be added once the article is available Use of the dataset and full description Before using the dataset, please read this document and the article describing the methodology. The article will be referenced here as soon as it is published. Please notify us (yangxuchao@zju.edu.cn) if you use the dataset so that we can keep track of how it is used and take that into consideration when updating and improving the dataset. When using this dataset or one of its updates, please cite the DOI of the precise version of the dataset used and also the data description article which this dataset is supplement to (see above). Support If you encounter possible errors or other things that should be noted or need support in using the dataset or have any other questions regarding the dataset, please contact <a href="mailto:12034034@zju.edu.cn">yangxuchao@zju.edu.cn</a>.  Abstract This dataset provides the GDP exposure of China's coastal areas and Low-elevation coastal zones (LECZs) in 2010 and 2019 based on the random forest algorithm and the integration of multi-source remote sensing data and geospatial big data, with a spatial resolution of 100m. Files included in the dataset The repository comprises several datasets. Each dataset coms in a TIIF file. The file name is constructed from dataset properties as follows: <Country><Source of the GDP><Region><Year> <Country> The “Country” flag indicates the country represented by the data. In this data set, it is China <Source of the GDP> The “Source of the GDP” flag indicates the sector from which GDP comes. GDP1: The primary sector. GDP2: The secondary sector. GDP3: The tertiary sector. GDPall: The total GDP of the region usually includes primary, secondary and tertiary sector. <Region> The “Region” flag indicates the exact area of the country. Coastal: Coastal areas, in this data are the coastal provinces of China including Liaoning, Hebei, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Guangxi and Hainan. Hong Kong, Macau and Taiwan are excluded because of their different political and economic status. LECZ: Low-elevation coastal zones (LECZ), which are areas below 10m above sea level and connected to the ocean <Year> The “Year” flag indicates the Year of data. Data format description Data format: GeoTIFF. Spatial resolution: 100m. Units: million CNY/ha.