cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7924/r4cr5zc7v
title: Data and scripts from: Sea level rise drives carbon and habitat loss in the U.S. mid-Atlantic coastal zone

description: Coastal marshes and seagrass beds store millions of tons of carbon in their sediments and sequester carbon at higher per-area rates than most terrestrial ecosystems. There is substantial interest in this “blue carbon” as a carbon mitigation strategy, despite the major threat that sea level rise (SLR) poses to these habitats. Many projections of habitat and carbon change with SLR emphasize the potential for inland marsh migration and increased rates of marsh carbon sequestration, but do not consider carbon fluxes associated with habitat conversion. We integrated existing data and models to develop a spatial model for predicting habitat and carbon changes due to SLR in six mid-Atlantic U.S. states likely to face coastal habitat loss over the next century due to low tidal ranges and sediment supply. Our primary model projection, using an intermediate SLR scenario (1.2 m SLR by 2104), predicts loss of 83% of existing coastal marshes and 3026% of existing seagrasses in the study area. In addition, 270,000 hectares of forest and forested wetlands in low-lying coastal areas will convert to coastal marshes. These SLR-driven habitat changes cause the study area to shift from a carbon sink to a source in our primary model projection. Given the many uncertainties about the habitat and carbon changes represented in our model, we also identified the parameters and assumptions that most strongly affected the model results to inform future research needs.  These included: land availability for inland marsh migration, the baseline extent and location of coastal marshes, proportion of stored carbon emitted from lost habitats (coastal marsh sediments or terrestrial biomass carbon), and methane emissions from freshwater habitats. The study area switched from a net carbon sink to a net carbon source under SLR for all but three model runs; in those runs, net carbon sequestration declined by 58-99%. This research was funded by the United States Climate Alliance Grant Program for Natural and Working Lands Research and administered by American Forests, and Southeast Climate Adaptation Science Center.
DOI: 10.7924/r41n87v9d
title: Data from: GLP-1 receptor blockade reduces stimulated insulin secretion in fasted subjects with low circulating GLP-1

description: Context: Glucagon-like peptide 1 (GLP-1), an insulinotropic peptide released into the circulation from intestinal enteroendocrine cells, is considered a hormonal mediator of insulin secretion. However, the physiological actions of circulating GLP-1 have long been questioned because of the short half-life of the active peptide. Moreover, there is mounting evidence for localized, intra-islet mediation of GLP-1 receptor (GLP-1r) signaling including a role for islet dipeptidyl-peptidase 4 (DPP4).

Objective: To determine whether GLP-1r signaling contributes to insulin secretion in the absence of enteral stimulation and increased plasma levels, and whether this is affected by DPP4.
Setting: Single-site study conducted at an academic medical center.
Participants: 20 nondiabetic subjects and 13 subjects with type 2 diabetes.
Design & Interventions: Cross-over study in which subjects received either a DPP4 inhibitor (DPP4i; sitagliptin) or placebo on two separate days. On each day they received a bolus of intravenous (IV) arginine during sequential 60 minute infusions of the GLP-1r blocker exendin[9-39] (Ex-9) and saline. 

Main Outcome Measures: Arginine-stimulated secretion of C-Peptide (C-PArg) and insulin (InsArg).

Results: Plasma GLP-1 remained at fasting levels throughout the experiments and IV arginine stimulated both - and β-cell secretion in all subjects. Ex-9 infusion reduced C-PArg in both the diabetic and nondiabetic groups by ~14% (p < 0.03 for both groups). Sitagliptin lowered baseline glycemia but did not affect the primary measures of insulin secretion. However, a significant interaction between sitagliptin and Ex-9 suggested a greater effect of GLP-1r activation with DPP4i treatment in diabetic subjects.
Conclusions: GLP-1r activation contributes to β-cell secretion in diabetic and nondiabetic humans during -cell activation, but in the absence of increased circulating GLP-1. These results are compatible with regulation of β-cells by paracrine signals from -cells. This process may be affected by DPP4 inhibition.
DOI: 10.7924/r43t9qf44
title: Data and scripts from: Design and use of monitoring networks: Few-large versus many-small (FLvMS) and multi-scale analysis

description: In order to learn about broad scale ecological patterns, data from large-scale surveys must allow us to either estimate the correlations between the environment and an outcome of interest and/or accurately predict ecological patterns. An important part of data collection is the sampling effort used to collect observations, which we decompose into two quantities: the number of observations or plots ($n$) and the per-observation/plot effort ($E$) (e.g. area per plot). If we want to understand the relationships between predictors and a response variable, then lower model parameter uncertainty is desirable. If the goal is higher predictive performance, then lower prediction error is preferable. We aim to learn if and when aggregating data can help attain these goals.  

We examine the impacts of aggregating observations for count and continuous data. Through simulations, we generate data and fit models at different degrees (e.g. groups of 10, 60) and types of aggregation, and examine parameter uncertainty as well as prediction error. We compare the findings from simulated data to real data in an application to tree density of selected species from Forest Inventory and Analysis (FIA) data. In particular, we fit models to FIA data that have been aggregated via distance and covariate similarity or US EPA ecoregions.
DOI: 10.7924/r4hq43669
title: Data from: Blue carbon mapping for six mid-Atlantic states

description: Coastal habitats’ ability to store carbon makes them valuable assets in state and community efforts to  support climate mitigation, but sea level rise (SLR) poses a major threat to these habitats and the carbon they store. The Nicholas Institute collaborated with six eastern seaboard states (North Carolina, Virginia, Maryland, Delaware, New Jersey, and New York) to develop a spatial model for predicting habitat and carbon changes due to SLR. These data provide results for each state using state-specific model parameters requested by state partners. A regional scale version of this work that uses consistent model parameters across all states is available in: http://doi.org/10.7924/r4cr5zc7v

This research was funded by the United States Climate Alliance Grant Program for Natural and Working Lands Research and administered by American Forests, and Southeast Climate Adaptation Science Center.
DOI: 10.7924/r4bk1j35s
title: Data from: The cancer microbiome atlas (TCMA): A pan-cancer comparative analysis to distinguish organ-associated microbiota from equiprevalent contaminants

description: Studying the microbial composition of internal organs and their associations with disease remains challenging due to the difficulty of acquiring clinical biopsies. We designed a statistical model to analyze the prevalence of species across sample types from The Cancer Genome Atlas (TCGA), revealing that species equiprevalent across sample types are predominantly contaminants, bearing unique signatures from each TCGA-designated sequencing center. Removing such species mitigated batch effects and isolated the tissue-resident microbiome, which was validated with original TCGA samples. "Mixed-evidence"species can be further distinguished by gene copy and nucleotide variants. We thus present The Cancer Microbiome Atlas (TCMA), a collection of curated, decontaminated microbial compositions of oropharyngeal, esophageal, gastrointestinal, and colorectal tissues. This led to discovery of prognostic species and blood signatures of mucosal barrier injuries, and enabled systematic matched microbe-host multi-omics analyses, which will help guide future studies of the microbiome's role in human health and disease.
DOI: 10.7924/r4gb27w9h
title: Data from: Stimulation of the pelvic nerve increases bladder capacity in the Prostaglandin E2 rat model of overactive bladder

description: This dataset contains data used for the publication: Langdale et al. 2017 (DOI:10.1152/ajprenal.00116.2017). The abstract for that paper is as follows:

Original Paper Abstract:
Overactive bladder (OAB) syndrome is a highly prevalent condition that may lead to medical complications and decreased quality of life. Emerging therapies focusing on selective electrical stimulation of peripheral nerves associated with lower urinary tract (LUT) function may provide improved efficacy and reduced side effects compared to sacral neuromodulation for the treatment of OAB symptoms. Prior studies investigating the effects of pelvic nerve (PelN) stimulation on LUT function were focused on promoting bladder contractions, and it is unclear if selective stimulation of the PelN would be beneficial for the treatment of OAB. Therefore, our motivation was to test the hypothesis that PelN stimulation would increase bladder capacity in the prostaglandin E2 (PGE2) rat model of OAB. The effects of intravesical PGE2 vs. vehicle and PelN stimulation after intravesical PGE2 on cystometric parameters were quantified in 17 urethane-anesthetized female Sprague-Dawley rats. Intravesical infusion of PGE2 resulted in decreased bladder capacity and increased voiding efficiency without a change in bladder contraction area under the curve, maximum contraction pressure, or contraction duration. Bladder capacity was also significantly decreased compared to vehicle confirming that the change in bladder capacity was mediated by PGE2. PelN stimulation reversed the PGE2-induced change in bladder capacity and increased the EUS EMG activity at a specific stimulation condition (1.0T amplitude at 10 Hz). These results confirm that the urodynamic changes reported in conscious rats are also observed under urethane anesthesia and that PelN stimulation is a novel and promising approach for the treatment of the symptoms of OAB.
DOI: 10.7924/r4pv6nm9f
title: Digitized tape recordings of Red colobus and other African forest monkey species vocalizations

description: These tape recordings were made as part of a general study of the behavioral ecology of 10 taxa of red colobus monkeys (Piliocolobus) and 29 other taxa of African monkeys, mainly Cercopithecus but including Colobus, Cercocebus, Lophocebus, and the rare Allochrocebus preussi (referred to as Cercopithecus lhoesti on tape) whoop ooo call, a contagious loud call given by adult males of Cameroon just before sunset. Recordings were made in the following countries and localities: Narangs Forest, Senegal; Tai Forest, Ivory Coast; Korup Forest, Cameroon; Dja Reserve, Cameroon; Idenau Forest, Cameroon; Bioko Island, Equatorial Guinea; Ituri Forest, Democratic Republic of Congo; Virunga National Park (Ruwenzori Mountains foothills), DRC; Kibale Forest, Uganda; Mbizi Forest, Tanzania; Magombero Forest, Tanzania; Jozani Forest, Zanzibar Island, Tanzania; Tana River forests, Kenya. Recordings in this collection were made between 1969 and 1992. All narration on these tapes is in English. 

The original tapes have been digitized into either an mp3 or wav format. Those in the wav format were done by Mr. Matthew Medler of the Macaulay Library at the Cornell Lab of Ornithology.
DOI: 10.7924/r4bp07h15
title: Data from: Capturing the start point of the virus-cell interaction with high-speed 3D single-particle tracking

description: <strong>*Data will be embargoed until publication of related article, or up to no more than 1 year from data upload.*</strong>

The early stages of the virus-cell interaction have long evaded observation by existing microscopy methods due to the rapid diffusion of virions in the extracellular space and the large 3D cellular structures involved. Here we present an active-feedback single-particle tracking method with simultaneous volumetric imaging of the live cell environment to address this knowledge gap to present unprecedented detail to the extracellular phase of the infectious cycle. We report previously unobserved phenomena in the early stages of the virus-cell interaction, including skimming contact events at the millisecond timescale, orders of magnitude change in diffusion coefficient upon binding, and cylindrical and linear diffusion modes along cellular protrusions. Finally, we demonstrate how this new method can move single-particle tracking from simple monolayer culture towards more tissue-like conditions by tracking single virions in tightly packed epithelial cells. This multi-resolution method presents new opportunities for capturing fast, 3D processes in biological systems.
DOI: 10.7924/r46w9hp7v
title: Data from: Assessment of soil carbon sequestration or losses from drained short pocosins located in Hyde County, NC, during the years 2020 and 2021

description: Peatlands drained for agriculture or forestry are susceptible to the rapid release of greenhouse gases (GHG) through enhanced microbial decomposition and increased frequency of deep peat fires. We present evidence that rewetting drained subtropical wooded peatlands (STWPs) along the southeastern USA coast, primarily pocosin bogs, could prevent significant carbon (C) losses. To quantify GHG emissions and storage from drained and rewetted pocosin we used eddy covariance techniques, the first such estimates that have been applied to this major bog type, on a private drained (PD) site supplemented by static chamber measurements at PD and Pocosin Lakes National Wildlife Refuge. Net ecosystem exchange (NEE) measurements showed loss was 21.2 Mg CO2 ha−1 yr−1 (1 Mg = 106 g) in the drained pocosin. Under a rewetted scenario, where the annual mean water table depth (WTD) decreased from 60 cm to 30 cm, the C loss was projected to fall to 2 Mg CO2 ha−1 yr−1, a 94% reduction. If the WTD was 20 cm, the peatlands became a net carbon sink (−3.3 Mg CO2 ha−1 yr−1). Hence, net C reductions could reach 24.5 Mg CO2 ha−1 yr−1, and when scaled up to the 4,000-ha PD site nearly 100,000 Mg CO2 yr−1 of creditable C could be amassed. We conservatively estimate among the 0.75 million ha of southeastern STWPs, between 450 and 770 km2 could be rewet, reducing annual GHG emissions by 0.96 to 1.6 Tg (1 Tg = 1012 g) of CO2, through suppressed microbial decomposition and 1.7 to 2.8 Tg via fire prevention, respectively. Despite covering <0.01% of USA land area, rewetting drained pocosin can potentially provide 2.4% of the annual CO2 nationwide reduction target of 0.18 Pg (1 Pg = 1015 g). Suggesting pocosin restoration can contribute disproportionately to the USA goal of achieving net-zero emission by 2050.
DOI: 10.7924/r47m0fd7k
title: Data from: Clinical knowledge among health care providers of essential maternal and child health services in Kenya: A cross-sectional survey

description: We conducted a cross-sectional survey of providers at health facilities in western Kenya providing inpatient maternity services. Providers estimated facility capacity through perceived availability of both general and specialized supplies. Providers reported training on maternal-child health (MCH) topics (post-abortion care, pre-eclampsia, postpartum hemorrhage, neonatal resuscitation) and completed case-based questions to assess clinical knowledge. Our aim was to determine provider knowledge of MCH topics and determine factors associated with clinical knowledge. Our secondary aim was to pilot a case-based questionnaire on post-abortion care.
DOI: 10.7924/r4wd41f7d
title: Data from: Optimized Monophasic Pulses with Equivalent Electric Field for Rapid-Rate Transcranial Magnetic Stimulation

description: Objective. Transcranial magnetic stimulation (TMS) with monophasic pulses achieves greater changes in neuronal excitability but requires higher energy and generates more coil heating than TMS with biphasic pulses, and this limits the use of monophasic pulses in rapid-rate protocols. We sought to design a stimulation waveform that retains the characteristics of monophasic TMS but significantly reduces coil heating, thereby enabling higher pulse rates and increased neuromodulation effectiveness.

Approach. A two-step optimization method was developed that uses the temporal relationship between the electric field (E-field) and coil current waveforms. The optimization step reduced the ohmic losses of the coil current and constrained the error of the E-field waveform compared to a template monophasic TMS pulse, with pulse duration as a second constraint. The second, amplitude adjustment step scaled the candidate waveforms based on simulated neural activation to account for differences in stimulation thresholds. The optimized waveforms were implemented to validate the changes in coil heating.

Main results. Depending on the pulse duration and E-field matching constraints, the optimized waveforms produced 12% to 75% less heating than the original monophasic pulse. The results were robust across a range of neural models. The changes in the measured ohmic losses of the optimized pulses compared to the original pulse agreed with numeric predictions.

Significance. The first step of the optimization approach was model-free and exhibited robust performance by avoiding the highly non-linear behavior of neural responses, while neural simulations were only run once for amplitude scaling in the second step. This significantly reduced computational cost compared to iterative methods using large populations of candidate solutions and reduced the sensitivity to choice of neural model. The reduced coil heating and power losses of the optimized pulses can enable rapid-rate monophasic TMS protocols
DOI: 10.7924/r41j9jn7t
title: Data from: Comparison of 3D structural metrics on oyster reefs using unoccupied aircraft photogrammetry and terrestrial LiDAR across a tidal elevation gradient

description: Physical structures generated from ecosystem engineers can have a cascade of impacts on the ecological community and the surrounding landscape. The Eastern oyster (Crassostrea virginica) can form extensive intertidal reefs, whose three-dimensional structures provide ecosystem services like nursery and foraging habitat for fishes and invertebrates and shoreline stabilization. Measurements of the structural properties of these reefs provide opportunities to quantitatively assess associated services. There is a growing variety of tools available for measuring three-dimensional (3D) properties of intertidal habitats, including two remote sensing methods that capture 3D structural metrics in a number of environments. We surveyed reefs using a terrestrial laser scanner (TLS, LiDAR) and imagery from unoccupied aircraft systems (UAS, or drones) processed through Structure from Motion photogrammetry. Comparisons of digital elevation models from repetitive flights over an oyster reef yielded mean horizontal and vertical root mean square errors (RMSE) of -0.54 ± 0.47 cm and 0.97 ± 1.0 cm (Mean ± SD), respectively, indicating high accuracy among UAS surveys. Compared to TLS products, point cloud densities from UAS-derived products were more consistent across the reef elevation gradient and much denser overall except in the low reef zone, which was proximal to most of the TLS scan locations. Comparisons of structural metrics between UAS and TLS showed similarities in metrics like profile and planform curvatures, yet indicated UAS surveys produced higher values of rugosity and slope. Both methods showed increasing trends of slope and rugosity with reef elevation. Results indicate that UAS photogrammetry can produce robust oyster reef structural metrics that can be highly useful in oyster conservation and restoration.
DOI: 10.7924/r4jw8j211
title: Data from: Ear and hearing care in national health policies, strategies, and plans

description: Ear and hearing-related conditions pose a significant global health burden, yet public health policy surrounding ear and hearing care in low- and middle-income countries is poorly understood. The present study aims to characterize the inclusion of ear and hearing care (EHC) in national health policies by analyzing 124 National Health Policies, Strategies, and Plans in English, French, Spanish, Portuguese, and Arabic. Eight ear and hearing care keywords were searched, including ear, hearing, audiology, otitis media, ototoxic, noise, vertigo, and hearing screening. "HIV/AIDS," "tuberculosis," and "malaria" were included as comparison keywords as these conditions have historically garnered political priority in global health. Of the 194 World Health Organization member states, there were 100 national policies that met inclusion criteria. These documents mentioned EHC keywords significantly less than comparison terms, with mention of hearing in 25%, noise in 11% noise, and ears in 11%. There was mention of HIV/AIDS in 92% of documents, tuberculosis in 88%, and malaria in 70%. Documents in low- and middle-income countries included significantly fewer mentions of ear and hearing care terms than those of high-income countries. We conclude that ear and hearing conditions pose a significant burden of disease but are severely underrepresented in national health policy; EHC should be included in national health policy to avert unnecessary morbidity. Advocacy for EHC policy is particularly urgent in low- and middle-income countries given the high burden of disease and infrequent inclusion in policy.
DOI: 10.48366/r236296
title: Comparison of machine learning classifiers using different satellite images for land use land cover mapping

description: Knowledge of land-use land-cover (LULC) change is essential in a number of fields based on the use of Earth observations. Accurate land use and cover data are essential for effective land-use planning. With the advancement of remote-sensing (RS) techniques satellites provide data at various spatial and temporal scales. Recently, the application of machine-learning algorithms on remotely-sensed images for LULC mapping has been attracting considerable attention. The comparison show a few studies that have been carried out to identify the best suited and accurate algorithm among used machine-learning classifiers for LULC mapping. It has been found that RF generally provide better accuracy for the LULC classification compared to other machine-learning techniques. However, the sensor characteristics (spatial and temporal resolution) processing software, machine-learning model set-up, training samples and input parameters also determine the accuracy of LULC classification.