Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
334
datasets available to search
ShareScore release 0.7.1
Dataset results
334 results for “arsenic”
Tretinoin and Arsenic Trioxide in Treating Patients With Untreated Acute Promyelocytic Leukemia
ClinicalTrials.gov study NCT02339740. IPD Sharing: YES. Countries: 6. Publications: 1.
Microbiome characterization of urbanized lakes impacted by legacy arsenic contamination
Open the record for dataset details and reuse information.
Data from: Littoral sediment arsenic concentrations predict arsenic trophic transfer and human health risk in contaminated lakes
Open the record for dataset details and reuse information.
Data from: Single cell RNA-seq analysis reveals that prenatal arsenic exposure results in long-term, adverse effects on immune gene expression in response to Influenza A infection
Open the record for dataset details and reuse information.
Co-sampled fruticose and foliose epiphytic lichens as spatial biomonitors of airborne mercury and arsenic in a historical "Gold Rush" mining district
Open the record for dataset details and reuse information.
Arsenic (+3 oxidation state) methyltransferase gene polymorphisms and expression on bladder cancer
<p><span><span><span><span>Inorganic arsenic (iAs) is a recognized environment-related factor for bladder cancer (BCa). </span><span><span>Arsenic (+3 oxidation state) methyltransferase (</span></span><i><span><span>AS3MT</span></span></i><span><span>)</span></span><i><span><span> gene</span></span></i><span> might influence BCa by regulating iAs metabolism. </span>The objectives of the present study were to systematically review eligible case-control studies about <i><span>AS3MT</span></i><i> </i>polymorphisms and BCa and to further compare the genotype distribution and allele distribution between BCa patients and controls by meta-analysis for humans. Besides, to clarify the effects of <i><span>AS3MT </span></i>expression on BCa clinical outcomes and survival time, we also conducted a series of analyses based on The Cancer Genome Atlas (TCGA) dataset. <span>Databases were systematically retrieved and we applied Stata software to perform meta-analysis. The registration of this study protocol is at PROSPERO and ID is CRD42019133947. Five articles</span> <span>were recruited and pooled results demonstrated that</span> <span>rs3740393 and rs11191438 polymorphisms were related to BCa risk in overall population (P<0.05)</span> <span>in the overall population.</span><span> In addition, GG and GC genotypes in rs3740393 and GG genotype in rs11191438 might be the susceptibility genotypes for BCa. </span><span>Results based on </span><span>168</span><span> BCa samples from TGCA indicated that patients with higher expression of </span><i><span><span>AS3MT</span></span></i><span> had poor </span><span>overall survival</span><span> time</span><span> and </span><i><span><span>AS3MT</span></span></i><span> expression is an independent indicator</span><span> for BCa </span><span>survival.</span> <span>This study identified that </span><i><span><span>AS3MT</span></span></i><span> polymorphisms could </span><span>affect</span><span> BCa risk and </span><i><span><span>AS3MT</span></span></i><span> expression was pivotal in prognosis of BCa.</span></span></span></span></p>
Data from: Simultaneous removal of fluoride and arsenic in geothermal water in Tibet using modified yak dung biochar as an adsorbent
Fluoride (F) and arsenic (As) are two typical and harmful elements that are found in high concentrations in geothermal water in Tibet. In the present work, yak dung, an abundant source of biomass energy in Tibet, was made into biochars (BC1, BC2 and BC3) by pyrolysis under different conditions, and the better biochar was modified by FeCl2 (Fe-BC3). The adsorption conditions were optimized to adsorb F and As in geothermal water. The results showed that BC3 can remove 90% F- and 20% As(V), which is the best effect of the three initial biochars. Fe-BC3 could remove 94% F- and 99.45% As(V) under the same conditions as BC3, which was an adsorbent dosage 10 g/L, pH 5-6 and temperature of 25 °C. It was also demonstrated that the removal rate did not decrease at 80 °C. A quasi-second-order kinetic model best described the adsorption behavior of ions on the surface of the biochar. The maximum adsorption capacity of F- and As(V) on Fe-BC3 was 3.928 mg/g and 2.926 mg/g, respectively. The features of Fe-BC3 were characterized by X-Ray Diffraction (XRD), Fourier Transform Infrared (FTIR), Brunauer-Emmett-Teller (BET), Energy Dispersive Spectrometer (EDS), and Scanning Electron Microscopy (SEM) to understand the adsorption process.
Lipidomics and metabolomics datasets for "Adverse effects of arsenic uptake in rice metabolome and lipidome revealed by untargeted liquid chromatography coupled to mass spectrometry (LC-MS) and regions of interest multivariate curve resolution"
<p><strong>Files description</strong></p> <p>Raw files for lipidomics and metabolics studies on the impact of arsenic exposure on rice growth.</p> <p>File details on the worksheets lipids_files.xlsx and metabolomics_files.xlsx</p> <p>Files have been organized as follows:</p> <p><strong>Lipidomics</strong></p> <blockquote> <p>1) Control samples: lip_controls.rar<br> 2) Watering low As exposure: lip_water_1.rar<br> 3) Watering high As exposure: lip_water_1000.rar<br> 4) Soil low As exposure: lip_soil_5.rar<br> 5) Soil high As exposure: lip_soil_50.rar<br> 6) QC samples: lip_qcs.rar</p> </blockquote> <p><strong>Metabolomics (positive ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_pos_controls.rar<br> 2) Watering low As exposure: met_pos_water_1.rar<br> 3) Watering high As exposure: met_pos_water_1000.rar<br> 4) Soil low As exposure: met_pos_soil_5.rar<br> 5) Soil high As exposure: met_pos_soil_50.rar<br> 6) QC samples: met_pos_qcs.rar</p> </blockquote> <p><strong>Metabolomics (negative ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_neg_controls.rar<br> 2) Watering low As exposure: met_neg_water_1.rar<br> 3) Watering high As exposure: met_neg_water_1000.rar<br> 4) Soil low As exposure: met_neg_soil_5.rar<br> 5) Soil high As exposure: met_neg_soil_50.rar<br> 6) QC samples: met_neg_qcs.rar<br> </p> </blockquote> <p> </p> <p><strong>Experimental details</strong></p> <blockquote> <p><strong>Arsenic Exposure</strong></p> <p>Arsenic was supplied through two main routes: watering with contaminated water or soil containing arsenic. In addition, this new study includes metabolomic as well as lipidomic analysis, in order to have a more global overview of arsenic exposure.</p> <p>For the watering treatment, during the first 11 days, rice was irrigated with Milli-Q water. From that day until harvesting, plants were watered with 1 and 1000 μM of As (V) for the two concentration levels of exposure, and with Milli-Q water for control samples. The lowest concentration was established at 1 μM as it is the limit of the acceptable arsenic concentration in water by European legislation. The upper concentration was set at 1000 μM, a threshold established to ensure that the experiment was performed under sub-lethal arsenic concentration for the plant, based on previous studies.</p> <p>For the soil treatment, two containers were prepared with 1 kg of soil two days before planting. Soil from the container was exposed to two arsenic concentration levels (5 and 50 mg L<sup>-1</sup>). Once sowing, rice was irrigated the whole growth period with a solution containing 0.001 μM of As (V). The lowest arsenic limit in this treatment was set at 5 mg L<sup>-1</sup> as a maximum value of common arsenic leaches without toxic characteristics, although background soil content of arsenic varies between one and 40 ppm according to the US food and drug administration (FDA) report. The highest arsenic limit was established to 50 mg L<sup>-1</sup>, as a considerably high arsenic content in the soil, slightly above the maximum frequently encountered levels.</p> <p><strong>Lipidomic Analysis</strong></p> <p>The lipidomic analysis was performed using a Waters Acquity UPLC system (Waters Corporation, MA, USA), connected to a Waters LCT Premier orthogonal accelerated time of flight mass spectrometer (Waters), operated in both positive and negative electrospray (ESI) ionization modes. Full scan spectra were acquired from 50 to 1500 Da.</p> <p>The chromatographic column employed was a Kinetex C8 (100 x 2.1 mm, 1.7 μm) (Phenomenex) under the following conditions (already used in [47]): temperature at 30˚C, injection volume at 10 μL, and flow rate at 0.3 mL min<sup>-1</sup>. Mobile phases selected were (A) MeOH 1mM ammonium formate, and (B) H<sub>2</sub>O 2mM ammonium formate, both at 0.2% formic acid. The gradient started at 80% A, increased to 90% A in 3 min, from 3 to 6 min remained at 90% A, changed to 99 % A until minute 15, remained constant 1 min, and returned to initial conditions until minute 20.</p> <p><strong>Metabolomic analysis</strong></p> <p>The metabolomic analysis was performed using a Waters Acquity UPLC system connected to a Q-Exactive (Thermo Fisher Scientific, Hemel Hempstead, UK) equipped with a quadrupole-Orbitrap mass analyzer. Electrospray (ESI) was used as an ionization source in both positive and negative ion modes. Full scan mass range was set from <em>m/z</em> 90 to 1000, and all ion fragmentation (AIF) was performed with normalized collision energy (NCE) of 35 eV.</p> <p>The column employed was an HILIC TSK gel amide-80 column (250 x 2.0 mm i.d., 5 μm) provided by Tosoh Bioscience (Tokyo, Japan), under the following experimental conditions (already employed in [45]): flow rate at 0.15 mL min<sup>-1</sup>, at room temperature, and 5 μL injection volume. Mobile phases were (A) AcN, and (B) 5 mM ammonium acetate, adjusted at pH 5.5 with acetic acid. The gradient employed was: starting conditions at 25% B, then increased until 30% B in 8 min; a 60% B was reached at 10 min, held for 2 min more and then back to 25% B until minute 14 min; lastly, a re-equilibration step was added and from 14 to 20 min at 25% B.</p> </blockquote> <p> </p> <p><strong>Funding:</strong> This research was funded by the Spanish Ministry of Science and Innovation (MCI, Grant CTQ2017-82598-P) and Severo Ochoa Project CEX2018-000794-S (funded by MCIN/AEI/ 10.13039/501100011033), and supported from the Catalan Agency for Management of University and Research Grants (AGAUR, Grant 2017SGR753). MPC was funded by a predoctoral FPU 16/02640 scholarship from the Spanish Ministry of Education and Vocational Training (MEFP). </p> <p> </p>
Arsenic immobilization and greenhouse gas emission depend on quantity and frequency of nitrogen fertilization in paddy soil
<p><span>Nitrogen (N) fertilization in paddy soils decreases arsenic mobility and methane emissions. However, it is unknown how quantity and frequency of N fertilization affects the interlinked redox reactions of iron(II)-driven denitrification, iron mineral (trans-)formation with subsequent arsenic (im-)mobilization, methane and nitrous oxide emissions, and how this links to microbiome composition. Thus, we incubated paddy soil from Vercelli, Italy, over 129 days and applied nitrate fertilizer at different concentrations (control: 0, low: ~35, medium: ~100, high: ~200 mg N kg<sup>-1 </sup>soil<sup>-1</sup>) once at the beginning and after 49 days. In the high N treatment, nitrate reduction was coupled to oxidation of dissolved and solid-phase iron(II), while naturally occurring arsenic was retained on iron minerals due to suppression of reductive iron(III) mineral dissolution. In the low N treatment, 40 µg L<sup>-1</sup> of arsenic was mobilized into solution after nitrate depletion, with 69% being immobilized after a second nitrate application. In the non-fertilized control, concentrations of dissolved arsenic were as high as 76 µg L<sup>-1</sup>, driven by mobilization of 36% of the initial mineral-bound arsenic. Generally, N fertilization led to 1.5-fold higher total GHG emissions (sum of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O as CO<sub>2</sub> equivalents), 158-fold higher </span><span>N<sub>2</sub>O</span><span>, and 7.5-fold lower CH<sub>4</sub> emissions compared to non-fertilization. On day 37, <em>Gallionellaceae</em>, <em>Comamonadaceae</em> and <em>Rhodospirillales</em> were more abundant in the high N treatment compared to the non-fertilized control, indicating their potential role as key players in nitrate reduction coupled to iron(II) oxidation. The findings underscore the dual effect of N fertilization, immobilizing arsenic in the short-term (low/medium N) or long-term (high N), while simultaneously increasing N<sub>2</sub>O and lowering CH<sub>4</sub> emissions. This highlights the significance of both the quantity and frequency of N fertilizer application in paddy soils. </span></p>
Arsenic(III)-Oxide Intercalates with Potassium Chloride: Water-Induced Varieties and New Synthesis Methods. Raw diffraction data.
<p>Diffraction data for CSD 2055421-2055423.</p>
Arsenic Trioxide in Treating Patients With Stage IV Prostate Cancer That Has Not Responded to Previous Hormone Therapy
ClinicalTrials.gov study NCT00004149. IPD Sharing: Not stated. Countries: 1. Publications: 0.
High-selenium Lentils Versus Arsenic Toxicity
ClinicalTrials.gov study NCT02429921. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Decitabine,Cytarabine and Arsenic Trioxide for Acute Myeloid Leukemia With p53 Mutations
ClinicalTrials.gov study NCT03381781. IPD Sharing: UNDECIDED. Countries: 1. Publications: 6.
The Effect of Arsenic Trioxide on Eliminating HIV-1 Reservoir Combined With cART
ClinicalTrials.gov study NCT03980665. IPD Sharing: NO. Countries: 1. Publications: 18.
Study of Association of Arsenic Trioxide (ATO) and Ascorbic Acid in Myelodysplastic Syndromes
ClinicalTrials.gov study NCT00803530. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Nutrition, Arsenic and Cognitive Function in Children
ClinicalTrials.gov study NCT03384862. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Arsenic Trioxide in Treating Patients With Myelodysplastic Syndromes
ClinicalTrials.gov study NCT00020969. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Arsenic Trioxide in Treating Young Patients With Refractory Leukemia or Lymphoma
ClinicalTrials.gov study NCT00020111. IPD Sharing: Not stated. Countries: 3. Publications: 1.
Scalability of a Home Health Navigator Program to Reduce Arsenic, Nitrate, and Lead in Private Well Water
ClinicalTrials.gov study NCT05395663. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Arsenic Trioxide in Recurrent and Metastatic Ovarian Cancer and Endometrial Cancer With P53 Mutation
ClinicalTrials.gov study NCT04489706. IPD Sharing: NO. Countries: 1. Publications: 12.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.