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1,196 results for “Minerals”
Fig. 1 in Alleged cnidarian Sphenothallus in the Late Ordovician of Baltica, its mineral composition and microstructure
Fig. 1. Location of study area (A) and studied sections (B).
New Insights into the Correlation between Bone Mineral Density at Various Sites and Dental Caries: Highlighting the Role of Head Bone Mineral Density
<p> Investigate the relationship between bone mineral density (BMD) at various body sites and dental caries.<br>Materials and methods: Based on the National Health and Nutrition Examination Survey (NHANES) database from 2011-2016, the correlation between BMD at various body sites and the DMFS index among 7044 adults aged 20-59 years was analyzed. Multiple linear regression, restricted cubic splines (RCS), piecewise linear regression, logistic regression, weighted quantile sum regression (WQS) and mediation effects analysis were integrated to explore the relationship between BMD and dental caries.<br>Results: Under the linear assumption, except for arm BMD, the BMDs of all other sites are negatively correlated with the DMFS index of dental caries. RCS analysis indicates a U-shaped relationship between head BMD and the DMFS index (p for nonlinear < 0.0001). WQS analysis indicates that mixed BMD is significantly negatively correlated with the DMFS index for dental caries (estimate, −0.023; 95% CI, −0.025 ~ −0.020), and head BMD has the most significant impact on the DMFS index (weight = 91.4%). Simple mediation analysis of the effect of dental caries on BMD levels mediated by inflammation levels showed negative results, suggesting that dental caries may not influence BMD through inflammation levels.<br>Conclusion: Monitoring BMD should be combined with appropriate oral healthcare and caries management strategies to effectively address these interconnected health issues, and particular attention should be paid to the monitoring of head BMD.</p>
Dataset of concentrations of perfluoalkylated substances (PFAS) in tap an mineral waters in different parts of Spains and the World
<p>Dataset of concentrations of 20 PFAS in drinking water regulated according to Directive 2020/2184/EU.</p> <p>Data is provided in MS Excel (xlsx) and CSV formats and contains details on the concentrations of 20 PFAS in mineral (11 samples) and tap drinking water (23 samples from Spain and 12 samples from other countries) collected in 2022-2023. Concentrations are in ng/L.</p> <p><strong>Further details are provided in the associated publication:</strong></p> <p><em>J. López-Vázquez, R. Montes, R. Rodil, R. Cela, J.A. Martínez-Pontevedra, M.T. Pena, J.B. Quintana. Determination of regulated perfluoroalkyl substances (PFAS)<br>in drinking water according to Directive 2020/2184/EU.</em><em><br>Environmental Science and Pollution Research 2024, DOI: 10.1007/s11356-024-34852-z.<br><a href="https://doi.org/10.1007/s11356-024-34852-z" target="_blank" rel="noopener">https://doi.org/10.1007/s11356-024-34852-z</a><br></em></p> <div>The data is deposited in ZENODO:</div> <div><a href="../doi/10.5281/zenodo.10990801">https://zenodo.org/doi/10.5281/zenodo.10990801</a></div> <div> </div> <div><strong>If you reuse the data, please cite the publication and ZENODO deposit mentioned above</strong></div>
Observed data, predictions and uncertainty associated with the updated distribution of clay minerals in the World Ocean
<p>Sparase observed data for various clay mineral species are .csv file format.</p> <p>Predictions and uncertainty for four seafloor clay mineral species (relative percentages, Kaolinite, Illite, Smectite, Chlorite) are generated via geospatial machine learning (GML). Methodology is outlined in "The updated distribution of clay mineral in the World Ocean"<span>. These files are in net-CDF file format. Files are cell-centered. Further, latitudes and longitudes of grid cells are denoted in the variables of the .nc files.</span></p>
Table 4 in Influence of Mycorrhizae and Irrigation on Growth and Mineral Uptake by Corn (Zea mays L.) Seedlings in a Calcareous Soil
<p>Table 4. Analysis of variance for micronutrient (Fe, Mn, B, Cu, and Zn) uptake by shoots of corn seedlings. Numbers are P values with F statistics in parentheses. Plants were grown in Guam cobbly clay soil, inoculated or not inoculated with <i>Glomus aggregatum</i> and provided one of four levels of water.</p><table><tbody><tr><th></th><th></th><th></th><th><b>Micronutrients</b></th><th></th><th></th></tr></tbody><tbody><tr><th><b>Source</b></th><td><i>df</i></td><td>Fe</td><td>Mn</td><td>B</td><td>Cu</td><td>Zn</td></tr><tr><th>Water (W) *</th><td>3</td><td>0.75 (0.36)</td><td><0.01 (9.57)</td><td>0.22 (1.67)</td><td>0.12 (0.89)</td><td><0.05 (7.23)</td></tr><tr><th>Inoculation (I)</th><td>1</td><td><0.001 (31.16)</td><td><0.001 (169.46)</td><td><0.001 (69.93)</td><td><0.001 (38.63)</td><td><0.001 (436.02)</td></tr><tr><th>W × I</th><td>3</td><td>0.88 (0.37)</td><td>0.18 (1.83)</td><td>0.65 (0.62)</td><td>0.59 (0.91)</td><td>0.24 (1.29)</td></tr></tbody></table><p>*Water treatment (W) was tested against main-plot error while both inoculation (I) and interaction (W × I) were tested against the sub-plot error.</p>
Table 5 in Influence of Mycorrhizae and Irrigation on Growth and Mineral Uptake by Corn (Zea mays L.) Seedlings in a Calcareous Soil
<p>Table 5. Correlation analysis of plant growth parameters (shoot biomass, root biomass, leaf width, SPAD chlorophyll reading) and uptake of macro- and microelements in leaf tissues.</p><table><tbody><tr><th></th><th></th><th><b>Macroelements</b></th><th><b>plant)</b></th><th></th><th></th><th><b>Microelements</b></th><th><b>plant)</b></th><th></th></tr></tbody><tbody><tr><th><b>Growth parameter</b></th><td>N</td><td>P</td><td>K</td><td>Mg</td><td>Ca</td><td>Fe</td><td>Mn</td><td>B</td><td>Cu</td><td>Zn</td></tr><tr><th>Shoot biomass (g)</th><td>0.8873</td><td>0.9521</td><td>0.9482</td><td>0.9746</td><td>0.9551</td><td>0.7587</td><td>0.9439</td><td>0.8959</td><td>0.8534</td><td>0.9321</td></tr><tr><th>Root biomass (g)</th><td>0.8258</td><td>0.9079</td><td>0.9150</td><td>0.9452</td><td>0.9497</td><td>0.7199</td><td>0.9112</td><td>0.9358</td><td>0.7390</td><td>0.8730</td></tr><tr><th>Leaf width (cm)</th><td>0.8569</td><td>0.9067</td><td>0.9394</td><td>0.9251</td><td>0.8954</td><td>0.8011</td><td>0.8957</td><td>0.8779</td><td>0.8478</td><td>0.9030</td></tr><tr><th>Chlorophyll (SPAD)</th><td>0.852</td><td>0.8211</td><td>0.8664</td><td>0.8104</td><td>0.7893</td><td>0.7284</td><td>0.7616</td><td>0.7377</td><td>0.7400</td><td>0.8377</td></tr></tbody></table><p>All correlations are highly significant at P <, Pearson.</p>
Table 3 in Influence of Mycorrhizae and Irrigation on Growth and Mineral Uptake by Corn (Zea mays L.) Seedlings in a Calcareous Soil
<p>Table 3. Analysis of variance for macronutrient (N, P, K, Mg and Ca) uptake by shoots of corn seedlings. Numbers are P values with F statistics in parentheses. Plants were grown in Guam cobbly clay soil, inoculated or not inoculated with <i>Glomus aggregatum</i>, and provided one of four levels of water.</p><table><tbody><tr><th></th><th></th><th></th><th></th><th><b>Macronutrients</b></th><th></th><th></th></tr></tbody><tbody><tr><th><b>Source</b></th><td><i>df</i></td><td>N</td><td>P</td><td>K</td><td>Mg</td><td>Ca</td></tr><tr><th>Water (W)*</th><td>3</td><td><0.05 (4.19)</td><td><0.05 (6.06)</td><td><0.01 (6.23)</td><td><0.01 (8.03)</td><td><0.01 (6.75)</td></tr><tr><th>Inoculation (I) 1</th><td><0.001 (159.51)</td><td><0.001 (437.94)</td><td><0.001 (816.51)</td><td><0.001 (364.49)</td><td><0.001 (116.39)</td></tr><tr><th>W × I</th><td>3</td><td>0.27 (2.30)</td><td>0.07 (2.70)</td><td>0.37 (0.95)</td><td>0.08 (2.44)</td><td>0.18 (2.27)</td></tr></tbody></table><p>*Water treatment (W) was tested against main-plot error while both inoculation (I) and interaction (W × I) were tested against the sub-plot error.</p>
Table 2 in Influence of Mycorrhizae and Irrigation on Growth and Mineral Uptake by Corn (Zea mays L.) Seedlings in a Calcareous Soil
<p>Table 2. Analysis of variance for shoot biomass, root biomass, leaf width, and SPAD chlorophyll reading of corn seedlings. Numbers are P values with F statistics in parentheses. Plants were grown in Guam cobbly clay soil, inoculated or not inoculated with <i>Glomus aggregatum</i>, and provided one of four water treatments.</p><table><tbody><tr><th></th><th></th><th></th><th><b>Growth parameters</b></th><th></th></tr></tbody><tbody><tr><th></th><td></td><td>Shoot biomass</td><td>Root biomass</td><td>Leaf width</td><td>SPAD chlorophyll</td></tr><tr><th><b>Source</b></th><td><i>df</i></td><td>(g/plant)</td><td>(g/plant)</td><td>(cm)</td><td>reading</td></tr><tr><th>Water (W)*</th><td>3</td><td><0.01 (12.52)</td><td><0.01 (11.73)</td><td><0.01 (10.19)</td><td>0.62 (3.77)</td></tr><tr><th>Inoculation (I)</th><td>1</td><td><0.001 (406.63)</td><td><0.001 (272.41)</td><td><0.001 (195.20)</td><td><0.001 (234.03)</td></tr><tr><th>W × I</th><td>3</td><td><0.01 (6.06)</td><td><0.05 (4.09)</td><td>0.44 (0.97)</td><td><0.01 (1.68)</td></tr></tbody></table><p>*Water treatment (W) was tested against main-plot error while both inoculation (I) and interaction (W × I)</p><p>were tested against the sub-plot error.</p>
Table 1 in Influence of Mycorrhizae and Irrigation on Growth and Mineral Uptake by Corn (Zea mays L.) Seedlings in a Calcareous Soil
<p>Table 1. Chemical characteristics of Guam cobbly clay soil used in the experiment.</p><table><tbody><tr><th><b>Parameter</b></th><th><b>Unit</b></th><th><b>Value</b></th></tr></tbody><tbody><tr><th>pH</th><td></td><td>7.0</td></tr><tr><th>Organic Matter</th><td>g kg-1</td><td>6.4</td></tr><tr><th>P</th><td>mg kg-1</td><td>25</td></tr><tr><th>K</th><td>mg kg-1</td><td>56</td></tr><tr><th>Ca</th><td>mg kg-1</td><td>5678</td></tr><tr><th>Mg</th><td>mg kg-1</td><td>123</td></tr><tr><th>Mn</th><td>mg kg-1</td><td>5.6</td></tr><tr><th>Fe</th><td>mg kg-1</td><td>63</td></tr><tr><th>Zn</th><td>mg kg-1</td><td>0.9</td></tr><tr><th>Cu</th><td>mg kg-1</td><td>0.7</td></tr></tbody></table>
PollyXT and COSMO-MUSCAT data for "Investigating the link between mineral dust hematite content and intensive optical properties by means of lidar measurements and aerosol modelling"
<p>The dataset contains 4 different files: </p> <ul> <li>For the single case example on the 24 August 2021 between 2:45 to 5:27 UTC in Mndelo, Cabo Verde: <ul> <li>-Mindelo-PollyXT_CPV-20210824_0245-0527-77smooth-info.txt : contains the information of the vertically retrieved optical properties from PollyXT lidar measurements. The information contained refers to the chosen retrieval times, vertical smoothing, and reference heights</li> <li>-Mindelo-PollyXT_CPV-20210824_0245-0527-77smooth.txt : vertically retrieved optical properties per height.</li> <li>-Mindelo-model_24aug.csv : COSMO-MUSCAT vertical results of dust and mineral mass concentrations per height. The columns that end with "int mass" correspond to the integrated mass per dust layer and columns that end with numbers correspond to different size bins. For reference to the size bins see Table 1 in Gómez Maqueo Anaya et al., 2024</li> </ul> </li> <li>Mutiple case studies: <ul> <li>-Mindelo-lidar-uvvisdiff_model.csv : Twenty-two case studies with the following order: first, the mean values of the lidar-derived optical properties, along with their corresponding retrieval times and heights that define the dust plume. This is followed by the POLIPHON (Mamouri and Ansmann, 2014, 2017) data. The mean values from dust and mineral mass concentrations from the model start with the model heights where the dust plumes were calculated. At the end of the dataset rows, the times from which the modeled mean values are calculated can be found.</li> </ul> </li> </ul>
Datasets: Evolution of the mineral concentration and bioaccumulation of the black soldier fly, Hermetia illucens, feeding on two different larval media
Open the record for dataset details and reuse information.
Data from: Variation in thyroid hormone levels is associated with elevated blood mercury levels among artisanal small-scale miners in Ghana
Background: Mercury can be very toxic to human health even at low dose of exposure. Artisanal small-scale miners (ASGMs) use mercury in gold production, hence are at risk of mercury-induced organ dysfunction. Aim: We determined the association between mercury exposure, thyroid function and work-related factors among artisanal small-scale gold miners in Bibiani-Ghana. Method: We conveniently recruited 137 consenting male gold miners at their work site in Bibiani-Ghana, in a comparative cross-sectional study. Occupational activities and socio-demographic data of participants were collected using a questionnaire. Blood sample was analysed for total mercury and thyroid hormones. Results: Overall, 58.4% (80/137) of the participants had blood mercury exceeding the occupational exposure threshold (blood mercury ≥5μg/L). T3(P<0.0001) and T4(P<0.0001) were significantly reduced among the exposed group compared to the non-exposed. TSH showed no significant variation between the exposed and non-exposed groups. Longer work duration (≥5years), gold amalgamation, gold smelting and sucking of excess mercury with the mouth were associated with increased odds of mercury exposure. Blood mercury showed negative correlation with T3(r = -0.29, P<0.0001), and T4(r = -0.69, P<0.0001) and positive correlation with work duration (r = 0.88, P<0.001). Even though a positive trend of association between blood mercury and TSH levels was recorded, it was not significant (r = 0.07, P = 0.4121). Conclusion: Small scale miners in Bibiani are exposed to mercury above the occupational threshold which may affect thyroid hormone levels.
Clay minerals control rare earth elements (REE) fractionation in Brazilian mangrove soils
<p>XRD data from different size fractions of Brazilian mangrove soils, supporting the manuscript entitled <strong><em>Clay minerals control rare earth elements (REE) fractionation in Brazilian mangrove soils, </em></strong>submitted to the journal <strong><em>Catena</em>.</strong></p>
Temporal patterns of visitation of birds and mammals at mineral licks in the Peruvian Amazon
<p>Mineral licks are key ecological resources for many species of birds and mammals in Amazonia, providing essential dietary nutrients and clays, yet little is known about which species visit and their behaviors at the mineral licks. Studying visitation and behavior at mineral licks can provide insight into the lives of otherwise secretive and elusive species. We assessed which species visited mineral licks, when they visited, and whether visits and the probability of recording groups at mineral licks were seasonal or related to the lunar cycle. We camera trapped at 52 mineral licks in the northeastern Peruvian Amazon and detected 20 mammal and 13 bird species over 6,255 camera nights. Generalized linear models assessed visitation patterns and records of groups in association with seasonality and the lunar cycle. We report nocturnal curassows (Nothocrax urumutum) visiting mineral licks for the first time. We found seasonal trends in visitation for the black agouti (Dasyprocta fuliginosa), red howler monkey (Alouatta seniculus), blue-throated piping guan (Pipile cumanensis), red brocket deer (Mazama americana), collared peccary (Pecari tajacu) and tapir (Tapirus terrestris). Lunar trends in visitation occurred for the paca (Cuniculus paca), Brazilian porcupine (Coendou prehensilis) and red brocket deer. The probability of recording groups (>1 individual) at mineral licks was seasonal and related to lunar brightness for tapir. Overall, our results provide important context for how elusive species of birds and mammals interact with these key ecological resources on a landscape scale. The ecological importance of mineral licks for these species can provide context to seasonal changes in species occupancy and movement.</p>
Identifying serpentine minerals by their chemical compositions with machine learning (dataset and python code)
<p>The dataset and python code for the manuscript of Identifying serpentine minerals by their chemical compositions with machine learning (submitted to American Geologist)</p>
Magnetic Properties of Lightning-Induced Glass Produced from Five Mineral Phases
<p>The excel sheet contains raw and corrected vibrating sample magnetometry data of five igneous minerals (< 32 µm powders of albite, labradorite, augite, hornblende, and magnetite) before and after high-current impulse experiments conducted at peak currents of 25 and 40 kA.</p>
Biodiversity, biogeography, and connectivity of polychaetes in the world's largest marine minerals exploration frontier
<p>The abyssal Clarion-Clipperton Zone (CCZ), Pacific Ocean, is an area of commercial importance owing to the growing interest in mining high-grade polymetallic nodules at the seafloor for battery metals. Research into the spatial patterns of faunal diversity, composition, and population connectivity is needed to better understand the ecological impacts of potential resource extraction. Here, a DNA taxonomy approach is used to investigate regional-scale patterns of taxonomic and phylogenetic alpha and beta diversity, and genetic connectivity, of the dominant macrofaunal group (annelids) across a 6 million km<sup>2</sup> region of the abyssal seafloor. We used a combination of new and published barcode data to study 1866 polychaete specimens using molecular species delimitation. Both phylogenetic and taxonomic alpha and beta diversity metrics were used to analyse spatial patterns of biodiversity. Connectivity analyses were based on haplotype distributions for a subset of the studied taxa. DNA taxonomy identified 291–314 polychaete species from the COI and 16S datasets respectively. Taxonomic and phylogenetic beta diversity between sites were relatively high and mostly explained by lineage turnover. Over half of pairwise comparisons were more phylogenetically distinct than expected based on their taxonomic diversity. Connectivity analyses in abundant, broadly distributed taxa suggest an absence of genetic structuring driven by geographical location. Species diversity in abyssal Pacific polychaetes is high relative to other deep-sea regions. Results suggest that environmental filtering, where the environment selects against certain species, may play a significant role in regulating spatial patterns of biodiversity in the CCZ. A core group of widespread species have diverse haplotypes but are well connected over broad distances. Our data suggest that the high environmental and faunal heterogeneity of the CCZ should be considered in policy decisions such as designating protected areas.</p>
The contribution of Fe(III) reduction to soil carbon mineralization in montane meadows depends on soil chemistry, not parent material or microbial community
<p>The long-term stability of soil carbon (C) is strongly influenced by organo-mineral interactions. Iron (Fe)-oxides can both inhibit microbial decomposition by providing physicochemical protection for organic molecules and enhance rates of C mineralization by serving as a terminal electron acceptor, depending on redox conditions. Restoration of floodplain hydrology in montane meadows has been proposed as a method of sequestering C for climate change mitigation. However, dissimilatory microbial reduction of Fe(III) could lead to C losses under increased reducing conditions. In this study, we explored variations in Fe-C interactions over a range of redox conditions and in soils derived from two distinct parent materials to elucidate biochemical and microbial controls on soil C cycling in Sierra Nevada montane meadows. Differences in parent material were associated with different rates of Fe(III) reduction at increasing soil moisture levels, but not with differences in soil C mineralization. Known Fe(III)-reducing taxa were present in all samples but neither the relative abundance nor richness of Fe(III) reducers corresponded with measured rates of Fe(III) reduction. Under reducing conditions, our results suggest that Fe(III) reduction contributes to C mineralization only when Fe-bound C is present. However, Fe-bound C was not present in all of our soils and was below theoretical limits for C sorption onto Fe-oxides where it was found. Overall, our results suggest that meadow-specific soil chemistry drives Fe-C interactions and that the impact of Fe on C cycling in montane meadows may be smaller than in other ecosystems.</p>
Dataset of manuscript "No detectable upper limit of mineral associated carbon in temperate agricultural soils"
<p>Dataset of carbon fractions (mineral associated organic carbon and particulate organic carbon) detected in a subset of topsoil samples of the first German Agricultural Soil Inventory.</p>
Data from Comparing organic carbon bound to different minerals in wetland and upland soils
<p>Here is the data and drawing code for "comparing organic carbon bound to different minerals in wetland and upland soils". Mineral binding of organic carbon (OC) is vital for soil organic carbon (SOC) persistence. However, the relative importance of two main types of soil minerals - metal oxides and silicate clay - in SOC protection remains unclear, hampering our ability to predict and protect this important pool of persistent SOC. Here, using sequential dissolution by dithionite and hydrofluoric acid, we quantified OC bound to metal oxides versus silicate clay in soils from contrasting environments (i.e., wetlands and uplands). We find that metal oxides override silicate clay in SOC protection in both wetlands and uplands, and OC bound to soil minerals (especially metal oxides) constitutes a higher fraction of SOC in wetlands than uplands, suggesting an underappreciated role of mineral protection in wetland SOC preservation. Furthermore, using lignin phenol analysis in tandem, we find that silicate clay dissolution may release an addition of ~23% lignin phenols from soils, potentially providing a means to assess ‘hidden’ lignin in mineral matrices. These findings highlight the important role of different soil minerals in the protection of SOC and its components in contrasting terrestrial environments, and advance our understanding of predicting and protecting this important pool of persistent SOC.</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.