cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.c5b180h
title: Data from: A risk stratification tool for prehospital triage of patients exposed to a whiplash trauma

description: Objective: Our aim was to develop a risk stratification model to predict
 the presence of a potentially more sinister injury in patients exposed to
 a whiplash trauma. Methods: The study base comprised of 3,115 residents
 who first sought healthcare contact within one week after being exposed to
 a whiplash trauma between 1999-2008, from within a defined geographical
 area, Skaraborg County in south-western Sweden. Information about gender,
 age, time elapsed prior to seeking care, type of health care contact, and
 hospitalization was retrieved. Eighteen potential risk factors were
 identified and evaluated using multivariate logistic regression. Results:
 Of 3,115 patients, 215 (6.9%) required hospital admission so theoretically
 93% could have been initially assessed by primary health care. However,
 only 46% had their first contact in primary health care. All patients had
 symptoms resulting in a diagnosis of whiplash injury. Four risk factors
 were found to be associated with hospital admission: commotio cerebri (OR
 31, 19-51), fracture / luxation (OR 11, 5.1-22), serious injury (OR 41,
 8.0-210), and the patient sought care during the same day as the trauma
 (OR 5.9, 3.7- 9.5). These four risk factors explained 27 % of the
 variation for hospital admission and the area under curve (AUC) was 0.77
 (0.74-0.80). Ninety-six percent of patients (2,985) had only a whiplash
 injury with none of the other four risk factors. These could be split into
 those attending health care the same day as the trauma, 1,737 (56%) with a
 7.1% risk for hospital admission, and those attending health care later,
 1,248 (40%) with a 1.3% risk for hospital admission. Conclusion: Patients
 with no signs of commotio cerebri, no fracture/luxation injury, no serious
 injury, comprising 96% of all patients exposed to a whiplash trauma can
 initially be referred to primary health care for initial assessment.
 However, those contacting the health care the same day as the trauma
 should be referred to a hospital for evaluation if they can’t get an
 appointment with a general practitioner the same day.
description: 2019-03-18
 PONE-D-1812628-PLOSONERaw data in SPSS .sav
 file format2019-03-18
 PONE-D-1812628R1-PLOSONE.sav
DOI: 10.6084/m9.figshare.30393025
title: Global divergent responses of soil heterotrophic respiration to nitrogen deposition

description: Numerous studies have demonstrated that soil heterotrophic respiration (<i>R</i><sub>H</sub>) is significantly influenced by the atmospheric nitrogen (N) deposition. However, the response ratios (Δ<i>R</i><sub>H</sub>) exhibit substantial spatial heterogeneity worldwide. Here, based on a hierarchical meta-analysis of 912 paired observations from global N addition experiments, we show that this heterogeneity in Δ<i>R</i><sub>H</sub> can be explained by the divergences in the ecological characteristics of the sample sites. The mean annual precipitation (MAP) and mean annual temperature (MAT) at the sample sites exhibited linear negative effects on Δ<i>R</i><sub>H</sub>, especially in regions with high MAP (&gt; 700 mm) or MAT (&gt; 17 °C). Δ<i>R</i><sub>H</sub> significantly increased in alkaline soils (pH &gt; 7.5) but decreased in acidic soils (pH &lt; 5.5). Furthermore, Δ<i>R</i><sub>H</sub> significantly increased in soils with high total organic carbon (TOC &gt; 15 g/kg) or low available N contents (NH4+ &lt; 19 mg/kg or NO3− &lt; 15 mg/kg), but decreased in soils with high total N (TN &gt; 11 g/kg). Additionally, N addition altered soil properties, such as soil microbial biomass, pH, TOC, TN, C:N ratio, NH4+, and NO3−. The alternations in soil microbial biomass (ΔBiomass) and pH linearly affected Δ<i>R</i><sub>H</sub> at the global scale, whereas others linearly impacted Δ<i>R</i><sub>H</sub> only under certain threshold levels. Structural equation modeling demonstrated that the ΔBiomass, which directly and ultimately drives the variation in Δ<i>R</i><sub>H</sub>, was simultaneously modulated by climatic conditions, initial soil properties, and their alternations after N addition. Moreover, these factors significantly interacted with each other, and their relative importance to Δ<i>R</i><sub>H</sub> varied across sample sites. Using machine learning, we predicted the global Δ<i>R</i><sub>H</sub> following a 10% increase in atmospheric N deposition and observed significant heterogeneity (–32.3% to +142%). Our findings suggest that when accurately evaluating soil <i>R</i><sub>H</sub> to N deposition, the levels of sample site characteristics and their interactions should be comprehensively considered.
DOI: 10.6084/m9.figshare.30393025.v3
title: Global divergent responses of soil heterotrophic respiration to nitrogen deposition

description: Numerous studies have demonstrated that soil heterotrophic respiration (<i>R</i><sub>H</sub>) is significantly influenced by the atmospheric nitrogen (N) deposition. However, the response ratios (Δ<i>R</i><sub>H</sub>) exhibit substantial spatial heterogeneity worldwide. Here, based on a hierarchical meta-analysis of 912 paired observations from global N addition experiments, we show that this heterogeneity in Δ<i>R</i><sub>H</sub> can be explained by the divergences in the ecological characteristics of the sample sites. The mean annual precipitation (MAP) and mean annual temperature (MAT) at the sample sites exhibited linear negative effects on Δ<i>R</i><sub>H</sub>, especially in regions with high MAP (&gt; 700 mm) or MAT (&gt; 17 °C). Δ<i>R</i><sub>H</sub> significantly increased in alkaline soils (pH &gt; 7.5) but decreased in acidic soils (pH &lt; 5.5). Furthermore, Δ<i>R</i><sub>H</sub> significantly increased in soils with high total organic carbon (TOC &gt; 15 g/kg) or low available N contents (NH4+ &lt; 19 mg/kg or NO3− &lt; 15 mg/kg), but decreased in soils with high total N (TN &gt; 11 g/kg). Additionally, N addition altered soil properties, such as soil microbial biomass, pH, TOC, TN, C:N ratio, NH4+, and NO3−. The alternations in soil microbial biomass (ΔBiomass) and pH linearly affected Δ<i>R</i><sub>H</sub> at the global scale, whereas others linearly impacted Δ<i>R</i><sub>H</sub> only under certain threshold levels. Structural equation modeling demonstrated that the ΔBiomass, which directly and ultimately drives the variation in Δ<i>R</i><sub>H</sub>, was simultaneously modulated by climatic conditions, initial soil properties, and their alternations after N addition. Moreover, these factors significantly interacted with each other, and their relative importance to Δ<i>R</i><sub>H</sub> varied across sample sites. Using machine learning, we predicted the global Δ<i>R</i><sub>H</sub> following a 10% increase in atmospheric N deposition and observed significant heterogeneity (–32.3% to +142%). Our findings suggest that when accurately evaluating soil <i>R</i><sub>H</sub> to N deposition, the levels of sample site characteristics and their interactions should be comprehensively considered.
DOI: 10.5061/dryad.hc218qk
title: Data from: Phylogeography of the Neotropical epiphytic orchid, Brassavola nodosa: evidence for a secondary contact zone in northwestern Costa Rica

description: Spatial patterns of genetic variation can reveal otherwise cryptic
 evolutionary and landscape processes. In northwestern Costa Rica, an
 approximately concordant genetic discontinuity occurs among populations of
 several plant species. We conducted phylogeographic analyses of an
 epiphytic orchid, Brassavola nodosa, to test for genetic discontinuity and
 to explore its underlying causes. We genotyped 18 populations with 19
 nuclear loci and two non-coding chloroplast sequence regions. We estimated
 genetic diversity and structure, relative importance of pollen and seed
 dispersal, and divergence time to understand how genetic diversity was
 spatially partitioned. Nuclear genetic diversity was high with little
 differentiation among populations (GSTn = 0.065). In contrast, chloroplast
 haplotypes were highly structured (GSTc = 0.570) and reveal a
 discontinuity between northwestern and southeastern populations within
 Costa Rica. Haplotype differences suggest two formerly isolated lineages
 that diverged approximately 10,000-100,000 YBP. Haplotype mixing and
 greater genetic diversity occur in an intermediate transition zone.
 Patterns of nuclear and chloroplast data were consistent. Different levels
 of genetic differentiation for the two genomes reflect the relative
 effectiveness of biotic versus abiotic dispersers of pollen and seeds.
 Isolation of the two lineages likely resulted from the complex
 environmental and geophysical history of the region. Our results suggest a
 recent cryptic seed dispersal barrier and/or zone of secondary contact. We
 hypothesize that powerful northeasterly trade winds hinder movement of
 wind-borne seeds between the two regions, while the multi-directional
 dispersal of pollen by strong-flying sphinx moths resulted in lower
 differentiation of nuclear loci.
description: Brassavola nodosa -
 Chloroplast haplotype sequence dataBrassavola nodosa -
 Chloroplast haplotype sequence data. Annotated sequences of 2 regions:
 trnL/rpL32F and 5'trnG/3'trnG (1340 bp)1 Brassavola nodosa -
 Chloroplast haplotype sequence
 data.xlsxBrassavola nodosa -
 Nuclear genetic dataBrassavola nodosa -
 Allozyme data from 19 loci. Codominant nuclear genetic data, where missing
 data is indicated by -9.2 Brassavola nodosa - Allozyme
 data.xls
DOI: 10.6084/m9.figshare.30393025.v2
title: Global divergent responses of soil heterotrophic respiration to nitrogen deposition

description: Numerous studies have demonstrated that soil heterotrophic respiration (<i>R</i><sub>H</sub>) is significantly influenced by the atmospheric nitrogen (N) deposition. However, the response ratios (Δ<i>R</i><sub>H</sub>) exhibit substantial spatial heterogeneity worldwide. Here, based on a hierarchical meta-analysis of 912 paired observations from global N addition experiments, we show that this heterogeneity in Δ<i>R</i><sub>H</sub> can be explained by the divergences in the ecological characteristics of the sample sites. The mean annual precipitation (MAP) and mean annual temperature (MAT) at the sample sites exhibited linear negative effects on Δ<i>R</i><sub>H</sub>, especially in regions with high MAP (&gt; 700 mm) or MAT (&gt; 17 °C). Δ<i>R</i><sub>H</sub> significantly increased in alkaline soils (pH &gt; 7.5) but decreased in acidic soils (pH &lt; 5.5). Furthermore, Δ<i>R</i><sub>H</sub> significantly increased in soils with high total organic carbon (TOC &gt; 15 g/kg) or low available N contents (NH4+ &lt; 19 mg/kg or NO3− &lt; 15 mg/kg), but decreased in soils with high total N (TN &gt; 11 g/kg). Additionally, N addition altered soil properties, such as soil microbial biomass, pH, TOC, TN, C:N ratio, NH4+, and NO3−. The alternations in soil microbial biomass (ΔBiomass) and pH linearly affected Δ<i>R</i><sub>H</sub> at the global scale, whereas others linearly impacted Δ<i>R</i><sub>H</sub> only under certain threshold levels. Structural equation modeling demonstrated that the ΔBiomass, which directly and ultimately drives the variation in Δ<i>R</i><sub>H</sub>, was simultaneously modulated by climatic conditions, initial soil properties, and their alternations after N addition. Moreover, these factors significantly interacted with each other, and their relative importance to Δ<i>R</i><sub>H</sub> varied across sample sites. Using machine learning, we predicted the global Δ<i>R</i><sub>H</sub> following a 10% increase in atmospheric N deposition and observed significant heterogeneity (–32.3% to +142%). Our findings suggest that when accurately evaluating soil <i>R</i><sub>H</sub> to N deposition, the levels of sample site characteristics and their interactions should be comprehensively considered.
DOI: 10.5061/dryad.5cc26s8
title: Data from: Impact of deleterious mutations, sexually antagonistic selection and mode of recombination suppression on transitions between male and female heterogamety.

description: Deleterious mutations accumulating on non-recombining Y chromosomes can
 drive XY to XY turnovers, as they allow to replace the old mutation-loaded
 Y by a new mutation-free one. The same process is thought to prevent XY to
 ZW turnovers, because the latter requires fixation of the ancestral Y,
 assuming dominance of the emergent feminizing mutation. Using
 individual-based simulations, we explored whether and how an epistatically
 dominant W allele can spread in a young XY system that gradually
 accumulates deleterious mutations. We also investigated how sexually
 antagonistic (SA) polymorphism on the ancestral sex chromosomes and the
 mechanism controlling X-Y recombination suppression affect these
 transitions. In contrast with XY to XY turnovers, XY to ZW turnovers
 cannot be favored by Y chromosome mutation load. If the arrest of X-Y
 recombination depends on genotypic sex, transitions are strongly hindered
 by deleterious mutations, and totally suppressed by very small SA cost,
 because deleterious mutations and female-detrimental SA alleles would have
 to fix with the Y. If, however, the arrest of X-Y recombination depends on
 phenotypic sex, X and Y recombine in XY ZW females, allowing for the purge
 of Y-linked deleterious mutations and loss of the SA polymorphism, causing
 XY to ZW turnovers to occur at the same rate as in the absence of
 deleterious and sex-antagonistic mutations. We generalize our results to
 other types of turnovers (e.g., triggered by non-dominant sex-determining
 mutations) and discuss their empirical relevance.
description: Saunders_2019_quantinemo_simulationsquantinemo_files_Saunders_2019.zip
DOI: 10.5061/dryad.5p26rh4
title: Data from: Expansion history and environmental suitability shape effective population size in a plant invasion

description: The margins of an expanding range are predicted to be challenging
 environments for adaptation. Marginal populations should often experience
 low effective population sizes (Ne) where genetic drift is high due to
 demographic expansion and/or census population size is low due to
 unfavorable environmental conditions. Nevertheless, invasive species
 demonstrate increasing evidence of rapid evolution and potential
 adaptation to novel environments encountered during colonization, calling
 into question whether significant reductions in Ne are realized during
 range expansions in nature. Here we report one of the first empirical
 tests of the joint effects of expansion dynamics and environment on
 effective population size variation during invasive range expansion. We
 estimate contemporary values of Ne using rates of linkage disequilibrium
 among genome-wide markers within introduced populations of the highly
 invasive plant Centaurea solstitialis (yellow starthistle) in North
 America (California, USA), and within native Eurasian populations. As
 predicted, we find that Ne within the invaded range is positively
 correlated with both expansion history (time since founding) and habitat
 quality (abiotic climate). History and climate had independent additive
 effects with similar effect sizes, indicating an important role for both
 factors in this invasion. These results support theoretical expectations
 for the population genetics of range expansion, though whether these
 processes can ultimately arrest the spread of an invasive species remains
 an unanswered question.
description: Ne.environment.dataEffective population size, climate, and age data for California and European populations of yellow starthistle.
DOI: 10.15468/bxh5v4
title: First report of the genus Swammerdamella Enderlein, 1912 (Diptera: Scatopsidae) in China, with descriptions of nine new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Xiao, Yishen, Hong, Dawei, Li, Zhu, Yang, Ding (2025): First report of the genus Swammerdamella Enderlein, 1912 (Diptera: Scatopsidae) in China, with descriptions of nine new species. Zootaxa 5723 (1): 49-70, DOI: 10.11646/zootaxa.5723.1.2, URL: https://doi.org/10.11646/zootaxa.5723.1.2AbstractThe genus Swammerdamella Enderlein, 1912 is first reported in China with nine new species described in this paper: S. flexuosa sp. nov., S. globus sp. nov., S. gracilis sp. nov., S. latilobata sp. nov., S. papillata sp. nov., S. planus sp. nov., S. ramulosa sp. nov., S. tricuspis sp. nov., S. venusta sp. nov. A key to known Swammerdamella species in China is also provided.
DOI: 10.5061/dryad.62n8p0q
title: Data from: Mie scattering and microparticle based characterization of heavy metal ions and classification by statistical inference methods

description: A straightforward method for classifying heavy metal ions in water is
 proposed using statistical classification and clustering techniques from
 non-specific microparticle scattering data. A set of carboxylated
 polystyrene microparticles of sizes 0.91 μm, 0.75 μm, and 0.40 μm were
 mixed with the solutions of nine heavy metal ions and two control cations
 and scattering measurements were collected at two angles optimized for
 scattering from non-aggregated and aggregated particles. Classification of
 these observations was conducted and compared among several machine
 learning techniques, including linear discriminant analysis, support
 vector machine analysis, K-means clustering, and K-medians clustering.
 This study found the highest classification accuracy using the linear
 discriminant and support vector machine analysis, each reporting high
 classification rates for heavy metal ions with respect to the model. This
 may be attributed to moderate correlation between detection angle and
 particle size. These classification models provide reasonable
 discrimination between most ion species, with the highest distinction seen
 for Pb(II), Cd(II), Ni(II), and Co(II), followed by Fe(II) and Fe(III),
 potentially due to its known sorption with carboxyl groups. The support
 vector machine analysis was also applied to three different mixture
 solutions representing leaching from pipes and mine tailings, and showed
 good correlation with single species data, specifically with Pb(II) and
 Ni(II). With more expansive training data and further processing, this
 method shows promise for low-cost and portable heavy metal identification
 and sensing.
description: Raw scattering
 dataSTATA functions for
 LDAR code for
 SVM
DOI: 10.5061/dryad.2n054k4
title: Data from: Higher insulin resistance & adiposity in post-menopausal women with breast cancer treated with aromatase inhibitors

description: Context: Aromatase deficiency causes obesity and insulin resistance in
 aromatase knockout mice and humans with rare mutations of the aromatase
 gene (CYP19). Aromatase inhibitors are a commonly prescribed therapy in
 post-menopausal breast cancer. Objective: We hypothesized that aromatase
 inhibitors induce obesity and insulin resistance when used in treatment of
 breast cancer. Design: Case-control study Setting: University teaching
 hospital Participants: 20 post-menopausal breast cancer patients, treated
 with aromatase inhibitor and 20 age-matched controls. Main outcome
 measures: Primary outcome measure was insulin sensitivity index – Matsuda,
 derived from a 75g oral glucose tolerance test. Body composition was
 assessed by DEXA and subcutaneous adipose tissue biopsies obtained for
 assessment of mRNA transcript levels. Data are mean ± SEM (inhibitor vs
 controls). Results: Aromatase inhibitor therapy was associated with
 significantly lower insulin sensitivity (5.15 ± 0.45 vs. 6.80 ± 0.64, P =
 0.041), higher peak insulin concentration following OGTT (693.4 ± 78.6 vs.
 527.6 ± 85.5 pmol/L, P = 0.035), greater percentage body fat (38.4 ± 1.0
 vs. 34.6 ± 1.3 %, P = 0.026), and higher plasma leptin concentration (23.5
 ± 2.8 vs. 15.5 ± 2.3 ng/mL, P = 0.035). Conclusions: Women who received
 aromatase inhibitors for post-menopausal breast cancer have greater
 percentage body fat and insulin resistance compared to controls with no
 history of breast cancer.
description: Supplemental
 materials
DOI: 10.5061/dryad.5649t65
title: Data from: Community disassembly and disease: realistic – but not randomized – biodiversity losses enhance parasite transmission

description: Debates over the relationship between biodiversity and disease dynamics
 underscore the need for a more mechanistic understanding of how changes in
 host community composition influence parasite transmission. Focusing on
 interactions between larval amphibians and trematode parasites, we
 experimentally contrasted the effects of host richness and species
 composition to identify the individual and joint contributions of both
 parameters on the infection levels of three trematode species. By
 combining experimental approaches with field surveys from 147 ponds, we
 further evaluated how richness effects differed between randomized and
 realistic patterns of species loss (i.e., community disassembly). Our
 results indicated that community-level changes in infection levels were
 due to host species composition, rather than richness. However, when
 composition patterns mirrored empirical observations along a natural
 assembly gradient, each added host species reduced infection success by 12
 to 55%. No such effects occurred when assemblages were randomized.
 Mechanistically, these patterns were due to non-random host species
 assembly/disassembly: while highly competent species predominated in low
 diversity systems, less susceptible hosts became progressively more common
 as richness increased. These findings highlight the potential for
 combining information on host traits and assembly patterns to forecast
 diversity-mediated changes in multi-host disease systems.
description: experiment_infection_hosts_UPLOADexperiment_infection_totals_UPLOAD
DOI: 10.5061/dryad.rj0kj10
title: Data from: The effect of neutral recombination variation on genome scans for selection

description: Recently, there has been an increasing interest in identifying the role
 that regions of low recombination or inversion play in adaptation of
 species to local environments. Many examples of groups of adapted genes
 located within inversions are arising in the literature, in part inspired
 by theory that predicts the evolution of these so-called “supergenes.” We
 still, however, have a poor understanding of how genomic heterogeneity,
 such as varying rates of recombination, may confound signals of selection.
 Here, I evaluate the effect of neutral inversions and recombination
 variation on genome scans for selection, including tests for selective
 sweeps, differentiation outlier tests, and association tests. There is
 considerable variation among methods in their performance, with some
 methods being unaffected and some showing elevated false positive signals
 within a neutral inversion or region of low recombination. In some cases
 the false positive signal can be dampened or removed, if it is possible to
 use a quasi-independent set of SNPs to parameterize the model before
 performing the test. These results will be helpful to those seeking to
 understand the importance of regions of low recombination in adaptation.
description: All scripts and
 simulation outputThis zip file contains
 all scripts and simulation outputs from SLiM, including raw tree files.
 See the GitHub repository
 https://github.com/TestTheTests/TTT_RecombinationGenomeScans for more
 information, and filtered vcf files used for all
 analyses.dryad.tar.gz