Find research datasets worth reusing

Data supporting 'Small molecule and cell contact-inducible systems for controlling expression and differentiation in stem cells'

Data supporting Soliman et al. 2024. Manuscript describes data collection practices and experimental design.

opencc-zeroMar 2024View details →

Ectopical expression of bacterial collagen-like protein supports its role as adhesin in host-parasite coevolution

<div> <div> <div> <div> For a profound understanding of antagonistic coevolution, it is necessary to identify the coevolving genes. The bacterium Pasteuria and its host, the microcrustacean Daphnia, are a well-characterized paradigm for co-evolution, but the underlying genes remain largely unknown. A genome-wide association study suggested a Pasteuria collagen-like protein 7 (Pcl7) as a candidate mediating parasite attachment and driving its coevolution with the host. Since Pasteuria ramosa cannot currently be genetically manipulated, we used Bacillus thuringiensis to express a fusion protein of a Pcl7 carboxy- terminus from P. ramosa and the amino-terminal domain of a B. thuringiensis collagen-like protein (CLP). Mutant B. thuringiensis (Pcl7-Bt) spores but not wild-type B. thuringiensis (WT-Bt) spores, attached to the same site of susceptible hosts as P. ramosa. Furthermore, Pcl7-Bt spores attached readily to susceptible host genotypes, but only slightly to resistant host genotypes. These findings indicated that the fusion protein was properly expressed and folded and demonstrated that indeed the C-terminus of Pcl7 mediates attachment in a host genotype-specific manner. These results provide strong evidence for the involvement of a CLP in the coevolution of Daphnia and P. ramosa and open new avenues for genetic epidemiological studies of host–parasite interactions. </div> </div> </div> </div>

opencc-by-4.0Nov 2023View details →

Atomistic Picture of Electronic Metal Support Interaction and the Role of Water

Synchrotron radiation photoelectron spectroscopy (SRPES), Scanning Tunnelling Microscopy (STM) data, Density Functional Theory (DFT) data

Data supporting "Stimulated emission does not radiate in a pure dipole pattern"

Image data presented in figure 3 (15_9_series_I.h5) and figure 4 (25_10_series_J.h5) of the manuscript Stimulated emission does not radiate in a pure dipole pattern. Each h5 file contains image data as an EArray as well as relevant metadata. It is recommended to open them using the PYthon Microscopy Environment (PYME; https://zenodo.org/doi/10.5281/zenodo.4289803). They were processed using the included iPython notebooks. Please see the readme.txt file if you wish to use these notebooks.

Data to the Supporting Information to "Radiative Heating of High-Level Clouds and its Impacts on Climate"

Author: Kerstin Haslehner kerstin.haslehner@univie.ac.at This archive includes the ICON-ESM output files used to study the radiative heating of high-level clouds. This dataset is related to the manuscript "Radiative Heating of High-Level Clouds and its Impacts on Climate" by Kerstin Haslehner, Blaž Gasparini and Aiko Voigt, which will be submitted to the Journal of Geophysical Research: Atmospheres. The output data was originally created as part of a Master's thesis by Kerstin Haslehner at the Department of Meteorology and Geophysics at University Vienna. This thesis is available here: https://utheses.univie.ac.at/detail/67015/#   Descriptions of names: "clouds off": radiative heating of all clouds turned off "ice-off": radiative heating of when clouds at temperatures colder than -35°C are turned off "ice-off-warmbase": radiative heating of high-level clouds turned off "ice-on": radiative heating of all clouds active, reference run "diagice-cirrus": contains output variables that diagnose the radiative heating of clouds at temperatures colder than -35°C "hl": height levels

opencc-zeroMar 2024View details →

Data from: Advancing transdisciplinary research on grassy biomes to support resilience in tropical ecosystems and livelihoods

Madagascar-wide metadata relating to Malagasy Grassy Biomes. The understanding of vegetation dynamics in tropical grassy biomes is severely limited across spatio-temporal scales, limiting effective management and support for livelihoods and biodiversity. Despite their extent, utility, and central importance to people and ecosystem function, grassy biomes are often uncritically regarded as degraded, valueless landscapes that result primarily from destructive anthropogenic forces. Moreover, this characterization is often presented without investigation of their history, biodiversity, or ecological complexity. Iconically, Madagascar's grassy biomes cover approximately 80% of the island's land surface today and exemplify core challenges to understanding tropical grassy ecosystems and their interactions with anthropogenic activities across spatio-temporal scales. Intersections between human history and environmental change have sparked debates about the role of land use in shaping grassy biomes (e.g., pastoralism, cultivation, fire use), echoing land use debates globally, and highlighting obstacles to ecosystem and livelihood resilience. Like many tropical biodiversity hotspots, Madagascar faces converging challenges that can be aided by an improved understanding of grassy ecosystems and the livelihoods they support, including food and health insecurity, economic inequities, biodiversity loss, climate change, land conversion, and limited resource access. Centered on improved understanding and management of grassy biomes, we present a framework to guide transdisciplinary research across the tropics by: (1) establishing a common terminology; (2) summarising data contributions and knowledge gaps that reflect those in other tropical regions; (3) identifying priority research questions; and (4) highlighting transdisciplinary and inclusive approaches to resolve knowledge gaps and co-benefit ecosystems and livelihoods.

Supporting material for: Geostratigraphic mapping of the intrusive Valentine Domes on the Moon

This dataset is the supporting information for the article called: Geostratigraphic mapping of the intrusive Valentine Domes on the Moon. It contains a QGIS project, the vector data, and the rastar data used to create the geostratigraphic maps of the zone.

Supporting data for "Electrochemical Removal of HF from Carbonate-based LiPF6-containing Li-ion Battery Electrolytes"

This is the dataset of electrochemical experiments and BET analysis for our publication "Electrochemical Removal of HF from Carbonate-based LiPF6-containing Li-ion Battery Electrolytes" (DOI: <a href="https://doi.org/10.1149/1945-7111/ad30d3">https://doi.org/10.1149/1945-7111/ad30d3</a>). This archive contains the raw data and Python Jupyter Notebook computer code to process, analyze, and generate the plots in this manuscript and its Supporting Information.   Abstract for the manuscript:   Due to the hydrolytic instability of LiPF6 in carbonate-based solvents, HF is a typical impurity in Li-ion battery electrolytes. HF significantly influences the performance of Li-ion batteries, for example by impacting the formation of the solid electrolyte interphase at the anode and by affecting transition metal dissolution at the cathode. Additionally, HF complicates studying fundamental interfacial electrochemistry of Li-ion battery electrolytes, such as direct anion reduction, because it is electrocatalytically relatively unstable, resulting in a LiF passivation layer. Methods to selectively remove ppm levels of HF from LiPF6-containing carbonate-based electrolytes are limited. We introduce and benchmark a simple yet efficient electrochemical method to selectively remove ppm amounts of HF from LiPF6-containing carbonate-based electrolytes. The basic idea is the application of a suitable potential to a high surface-area metallic electrode upon which only HF reacts (electrocatalytically) while all other electrolyte components are unaffected under the respective conditions.

Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta: supporting data - high water levels

This dataset contains modelled high water levels in the Guayas delta supporting the paper 'Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta' published in HESS 2024. The dataset is organised through two folders: <ul> <li>mangroves: all data from the scenarios with mangroves included in the domain</li> <li>no_mangroves: all data from the scenarios without mangroves included in the domain</li> </ul> Each folder is further divided along 6 subfolders: <ul> <li>I: El Niño Ocean & river</li> <li>II: El Niño Ocean</li> <li>III: El Niño river</li> <li>IV: Neutral</li> <li>I_50per: 50 % increase in seaward El Niño anomalies</li> <li>I_150per: 150 % increase in seaward El Niño anomalies</li> </ul> Each folder contains two files: <ul> <li>vars.csv - each row represents a mesh node and there are three columns: <ul> <li>X: x value of the model mesh node [m]</li> <li>Y: y value of the model mesh node [m]</li> <li>HIGH_WATER: high water level [m]</li> </ul> </li> </ul>

opencc-zeroMar 2024View details →

Sites dominated by common fiddleneck (Amsinckia menziesii var. intermedia) support diverse plant-pollinator interactions

Biodiversity is declining at unprecedented rates worldwide due largely to land use change and abnormal disturbance events. The high species diversity and endemicity found in California's coastal sage scrub (CSS) are especially at risk from urban development and ongoing disturbance. However, several CSS plant species have disturbance adaptations which may allow them to serve as vital resources for insect pollinators when native plant diversity is threatened. Common fiddleneck (Amsinckia menziesii var. intermedia) is one of the first annual forbs to germinate in CSS and as a result, it occurs in high density patches in early spring which temporarily creates a near monoculture. Although fiddleneck is a prominent CSS plant, particularly in areas that have experienced a disturbance event, its larger ecological role is not well explored. Therefore, we monitored ten sites across a disturbance gradient for two spring seasons to assess the composition of plant-pollinator networks in fiddleneck-dominated plots. We found fiddleneck supported a diverse pollinator community with 68% of recorded taxa visiting fiddleneck. The plants most frequently visited included two native annual forbs (common fiddleneck and Phacelia distans) and two invasive annual forbs (Erodium cicutarium and Brassica tournefortii). Plant and pollinator abundances increased with increased mean precipitation. Additionally, plant-pollinator networks changed over time; the number of links per species increased throughout the season but did not differ amongst disturbance types. Despite the numerical dominance of fiddleneck, CSS supported a diversity of pollinator taxa and exhibited complex plant-pollinator networks across the disturbance gradient.

Dataset for: Advancing projections of Crown-of-Thorns Starfish to support management interventions

<h3>Abstract</h3> <div> Regular outbreaks of corallivorous Crown of Thorns Starfish (Acanthaster spp; CoTS) occur on the Great Barrier Reef (GBR) and are one of the leading drivers of coral mortality. Understanding the disparities between real-world observations and model predictions of CoTS densities is crucial for refining population modelling and developing effective control strategies. Using a spatially explicit ecosystem model of the Great Barrier Reef (ReefMod-GBR), we compare model predictions of CoTS densities to manta tow survey observations. We also incorporate a new zone-specific CoTS mortality rate to account for differences in predation of CoTS between fished and protected reefs. We found high congruence between predicted CoTS densities and observations: ~81% of categorical reef level CoTS densities were either the same density level or only differed by one level, however underpredictions increased as observed densities increased. The zone-specific CoTS mortality rate reduced severe underpredictions from 7.1% to 5.6%. Underpredictions are a key concern for reef managers as they indicate potential missing outbreaks where targeted culling efforts are necessary and may lead to an underestimation of the coral loss attributed to CoTS outbreaks. Reef protection status was an important driver of prediction accuracy, suggesting it plays a role in determining CoTS densities, emphasising the importance of further research on in situ CoTS mortality rates. The location of a reef inside or outside the “initiation box”, a speculative area of primary outbreaks on the GBR, was also important, with exact predictions more likely to occur outside the box. Accurately modelling initiation box dynamics is challenging owing to limitations of empirical data on CoTS outbreaks, but this highlights the need for focussed research on these dynamics to enhance overall predictive accuracy. Other spatial factors, such as region and shelf position, also contributed to the variance between observations and predictions, underscoring the importance of the spatial-temporal context of each observation. In conclusion, this study validates our CoTS population modelling efforts, showcasing a high congruence between CoTS density predictions and real-world observations. CoTS observations can help refine predictions and guide targeted control against CoTS populations and outbreaks, contributing to effective ecosystem management for long-term resilience of the GBR. </div> <h3>Methods</h3> <div> Data are mean CoTS density (per manta tow) observations and predictions for individual reefs and years on the Great Barrer Reef. Observations come from several sources (CCP, LTMP, FMP) and predictions come from a spatially explicit ecosystem model of the Great Barrier Reef (ReefMod-GBR).  </div> <h3>Subject keywords</h3> Earth and related environmental sciences, adaptive management, coral reef, Great Barrier Reef, individual-based model, Marine Invertebrate, pest management, spatial simulations <h3>Funding</h3> <div> CoTS Control Innovation Program </div> <div> <h2>README: Dataset for: Advancing projections of Crown-of-Thorns Starfish to support management interventions</h2> <a href="https://doi.org/10.5061/dryad.31zcrjdtq">https://doi.org/10.5061/dryad.31zcrjdtq</a> This dataset is for a paper that compares CoTS density observations to predictions for individual reefs on the Great Barrier Reef in individual years. CoTS manta tow observations derive from the CoTS Control Program (CP), Field Management Program (FMP), and the AIMS Long Term Monitoring Program (LTMP). Where multiple observations exist from the same observation source, they are averaged at the reef-level in that year. If multiple observations exist from different sources, they are kept separate. Predictions are generated by a spatially explicit ecosystem model of the Great Barrier Reef (ReefMod-GBR). <h3>Description of the data and file structure</h3> Observed and predicted CoTS densities are compared to determine prediction accuracy of the ecosystem model. Both observed and predicted CoTS per tow values were categorised as follows: 0 = None (Level 1); ≤ 0.1 = No Outbreak (Level 2); 0.11 - 0.22 = Potential Outbreak (Level 3); 0.22 - 1.0 = Established Outbreak (Level 4); 1.0 - 3.0 = Severe Outbreak (Level 5); > 3.0 = Extreme Outbreak (Level 6). The level of each observation was then compared to the level of each prediction and the difference calculated to determine prediction accuracy. Different variables were extracted as potential predictors of CoTS prediction accuracy. As such, the dataset includes the following for each observation/prediction comparison: 1) RM_ID = an individual ID for each of the 3806 reefs that we model in our ecosystem model. 2) YEAR = year as an integer. 3) LAT and LON = the latitude and longitude of the reef. 4) GBRMPAID and GBR_NAME = identifiers for each reef from the Great Barrier Reef Marine Park Authority. 5) REGION: 1 = North, 2 = Central, 3 = South 6) SHELF: 1 = Inner, 2 = Middle, 3 = Outer 7) GZ = Whether a reef is protected (i.e., in a green zone = 1) or not (i.e., in a blue zone = 0). 8) IB = Whether a reef is inside the CoTS initiation box (1) or not (0). 9) GEOM_CH_KM2 = the area (km2) of coral habitat for that reef 10) OBS_SOURCE = the source of the CoTS observation (1 = LTMP, 2 = FMP, 3 = CP) 11) OBS_n = the number of observations that went into calculating the reef-level mean CoTS per tow for that year 12) OBS_COTS_CAT = observed CoTS density as a categorical level from GBRMPA 13) OBS_COTS = mean CoTS per tow, and OBS_COTS_1YB = mean COTS per tow at that reef in the preceding year 14) OBS_CC, OBS_CC_1YB = mean coral cover at that reef from that OBS_SOURCE, and OBS_CC_1YB = in the year preceding it. 15) PRED_COTS_CAT = predicted CoTS density as a categorical level from GBRMPA 16) PRED_COTS, PRED_COTS_1YB, PRED_COTS_2YB, PRED_COTS_3YB = predicted CoTS per tow densities at the current year, and in the one, two, and three years preceding it. 17) PRED_CC, PRED_CC_1YB, PRED_CC_2YB, PRED_CC_3YB = predicted coral cover (%) at the current year, and in the one, two, and three years preceding it. 18) PRED_ACRO, PRED_ACRO_1YB, PRED_ACRO_2YB, PRED_ACRO_3YB = predicted Acropora cover (%) at the current year, and in the one, two, and three years preceding it. Acropora is the preferred food of CoTS. 19) PRED_INSTR, PRED_INSTR_CUMU = incoming strength of CoTS larvae calculated as the CoTS larval input multipled by the size of the reef area. PRED_INSTR_CUMU is the sum of this value over the three years previous to the current year. 20) TOTAL_OBS = where data exist, the CoTS model ReefMod is forced with manta tow survey observations from the CP, FMP, and LTMP which override model predictions at individual reefs/years. This shows the total number of observations that have been used to force the CoTS predictions for this reef in all preceding years. 21) TIME_SINCE_OBS = similar to TOTAL_OBS, but gives the number of years since an observation last forced the CoTS prediction for this reef. 22) PRED_ERR_COTS = the difference in categorical CoTS density levels between observations and predictions. 23) PRED_ERR_CC = observed and predicted coral cover was categorised into AIMS coral cover categories: 0 = 0%, 1 = 0 - 10%, 2 = 10 - 30%, 3 = 30 - 50%, 4 = 50 - 75%, 5 = 75 - 100%. The difference in coral cover category between observations and predictions was then compared. 24) DIFF_CC = the difference in the % coral cover between the observations and predictions. 25) DIFF_CC_CUMU, DIFF_CC_CUMU_N = same as DIFF_CC except the cumulative % difference over the three preceding years, and the number of observations that went into calculating the %. </div>

opencc-zeroApr 2024View details →

Supplementary material: CYB561 supports the neuroendocrine phenotype in castration-resistant prostate cancer

Castration-resistant prostate cancer (CRPC) is associated with resistance to androgen deprivation therapy, and an increase in the population of neuroendocrine (NE) differentiated cells. It is hypothesized that NE differentiated cells secrete neuropeptides that support androgen-independent tumor growth and induce aggressiveness of adjacent proliferating tumor cells through a paracrine mechanism. The cytochrome b561 (CYB561) gene, which codes for a secretory vesicle transmembrane protein, is constitutively expressed in NE cells and highly expressed in CRPC. CYB561 is involved in the α-amidation-dependent activation of neuropeptides and contributes to regulating iron metabolism which is often dysregulated in cancer. These findings led us to hypothesize that CYB561 may be a key player in the NE differentiation process that drives the progression and maintenance of the highly aggressive NE phenotype in CRPC. In our study, we found that CYB561 expression is upregulated in metastatic and NE prostate cancer (NEPC) tumors and cell lines compared to normal prostate epithelia and that its expression is independent of androgen regulation. Knockdown of CYB561 in androgen-deprived LNCaP cells dampened NE differentiation potential and transdifferentiation-induced increase in iron levels. In NEPC PC-3 cells, depletion of CYB561 reduced the secretion of growth-promoting factors, lowered intracellular ferrous iron concentration, and mitigated the highly aggressive nature of these cells in complementary assays for cancer hallmarks. These findings demonstrate the role of CYB561 in facilitating transdifferentiation and maintenance of NE phenotype in CRPC through its involvement in neuropeptide biosynthesis and iron metabolism pathways.

MSU OA Author Fund supported papers 2014-2023

This is a record of open access publications funded by the Montana State Univeristy Library between 2014 and 2023 through both a dedicated fund from the library collections budget and several Read and Pubish agreements. At a minimum, one author must be MSU affiliated to recieve funding.

opencc-zeroApr 2024View details →

The role of health sciences libraries in supporting medical image consent standards survey documentation

Objective: To determine if health sciences library workers were familiar with best practices regarding informed consent for the publication of medical images and if they incorporate the recommendations into their professional work. Methods: A survey was developed by the authors and distributed to library listservs in the United States. The results of the survey were tabulated in R. Results: A total of 90 respondents were included in the data analysis with all respondents reporting multiple responsibilities in their professional role. While the majority of library workers (59%) were familiar with the best practices, few incorporated the recommendations into their everyday professional work. Conclusions: The professional work of health sciences library workers does not appear to include a significant inclusion of the best practices for the informed consent for the publication of medical images. There is a need for future research to better understand how library workers can better incorporate their knowledge of medical image publication consent standards into their work.

Miocene construction of the High Andes recorded by exhumation of the Frontal Cordillera, La Ramada Massif of western Argentina (31°S) (Supporting Information)

Supporting datasets for Howlett et al., "Miocene construction of the High Andes recorded by exhumation of the Frontal Cordillera, La Ramada Massif of western Argentina (31°S)" in review at Earth and Planetary Science Letters (EPSL) as of April 3, 2024.

Supporting Data: Exploring Canyons Beneath Devon Ice Cap

These data are associated with the paper "Exploring Canyons Beneath Devon Ice Cap for Sub-Glacial Drainage Using Radar and Thermodynamic Modeling". This repository contains 3 data sets: <ul> <li>RES simulations - returned power radargrams (Matlab .mat format) from 4 simulated scenarios over Canyon B at DEV3_PER0a_Y86a. These include 2 frozen bed scenarios (0.2m and 0.35m roughness) and 2 scenarios with a 10m canal (0.2m and 0.35m roughness).</li> <li>Temp simulations - the folder for each location simulated contains the following files: <ul> <li>xx.csv - all x locations (in m) for the 2-D grid modeled</li> <li>zz.csv - all z locations (in m) for the 2-D grid modeled</li> <li>6 temperature grids (in degrees C) corresponding to the x and y positions in xx.csv and zz.csv. The filename indicates the basal boundary condition ("Lachenbruch" or "Constant") and accumulation rate ("b=<>") used. </li> </ul> </li> </ul>

Supporting Data for "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change"

Code and netcdf files of processed X-SHiELD and CMIP6 simulations to reproduce the figures of Timothy M. Merlis, Kai-Yuan Cheng, Ilai Guendelman, Lucas Harris, Christopher S. Bretherton, Maximilien Bolot, Linjiong Zhou, Alex Kaltenbaugh, Spencer K. Clark, Gabriel A. Vecchi, and Stephan Fueglistaler (2024): "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change".

Data to support plankton model construction

This work provides a database of references supportive of modelling targeted at developing plankton digital twins. The database, containing over 120 entries, can be explored using multi-level sort functions.  Additional contributions are welcome, and the published database will be re-published to make such additions available on open access.

Supporting dataset for manuscript "Role of metabolism, resistance, and/or antagonism as drivers of endomicrobiomes assemblage in Origanum heracleoticum L." by Giulia Semenzato et al. 2024

Raw data used for the analysis presented in the manuscript "Role of metabolism, resistance, and/or antagonism as drivers of endomicrobiomes assemblage in Origanum heracleoticum L." by authors Giulia Semenzato, Francesco Vitali, Arcangela Frascella, Ludovica Lollini, Stefano Mocali, Alessio Papini, Renato Fania, and Giovanni Emiliani  <ul> <li>phenome_combined_normalized_R.csv = activity values (AV) obtained after DuctApe elaboration of phenotype microarray data for carbon sources analysis. Control well signal was substracted.</li> <li>phenome_combined_nonNormalized_R.csv = activity values (AV) obtained after DuctApe elaboration of phenotype microarray data for resistance/sensibility sources analysis. Control well were signal not substracted.</li> <li>Rawdata_cross_streaking.csv = raw data obtained from cross-streaking experiment.</li> <li>Rawdata_MIC.csv = raw data obtained from MIC experiment.</li> <li>Raw_data_BIOLOG.zip = raw data from phenotype microarray readings.</li> </ul>