cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24196829.v1
title: Additional file 2 of A glimpse of the paleome in endolithic microbial communities

description: Additional file 2: Supplementary tables: Table S1. Statistics sequence data processing. pwd = powdered sample, pc = rock pieces sample, QC = quality control. Table S2. Identified contaminants for different taxonomic ranks. Freq = frequency, prev = prevalence, p.freq = tail probability at value R, p.prev = tail probability of the chi-square distribution for the respective taxon based on presence/absence in true samples and negative controls, p = p-value from Fisher's exact test, NA = not available. Please see [112] for details regarding the mentioned metrics. Table S3. Phylum-level taxonomic profiles. lib_blk = library blank, ex_blank = extraction blank, pc = rock pieces sample, pwd = powdered sample. Table S4. Basic assembly statistics and results from read recruitment. Table S5. Phylum-level taxonomic profiles of assembled contigs (&gt; 1 kbp). Table S6. Taxonomy and quality information regarding recovered genome bins based on checkm [64] output. Table S7. Functional profile based on KEGG Lvl3 Orthologies. Abundances are given as CoPM. CoPM = copies per million. Table S8. Functional profile based on a subset of KEGG pathways. CoPM = copies per million, logCoPM = log copies per million.
DOI: 10.6084/m9.figshare.21261716.v1
title: Hydrothermal alteration, lithogeochemical marker units and vectors towards mineralisation at the Svärdsjö Zn-Pb-Cu deposit, Bergslagen, Sweden

description: The Svärdsjö Zn-Pb-Cu deposit is situated in the heavily mineralised Bergslagen lithotectonic unit of the Fennoscandian shield, south-central Sweden. Intense hydrothermal alteration followed by a strong overprint by deformation and metamorphism during the Svecokarelian orogeny complicate interpretation of the local geology. Integration of whole-rock lithogeochemical and petrographic methods has allowed the mainly dacitic volcanic host succession and effects of ore-related hydrothermal alteration to be characterised. Mineralisation is hosted by 2–15 m thick, commonly skarn-altered dolomitic marble interbeds. Zones of strong–intense hydrothermal chlorite-sericite alteration envelop the marble units, recording mass gains of Fe and Mg, as well as Na depletion. Minerals such as cordierite, anthophyllite and sillimanite formed in these rocks during regional metamorphism. Mineralisation via sub-seafloor replacement is suggested for the deposit based on alteration zoning and the irregular, stratabound, marble-hosted style of sulphide lenses. It is inferred that mineralisation formed via neutralisation of hot, acidic metalliferous fluids. Geochemically and lithologically distinct units adjacent to the mineralised zones can serve as marker units to aid further exploration in the area. Mass change calculations reveal that Fe and Mg enrichment, as well as Na depletion exhibit detectable changes extending up to 100 m from the mineralised lenses, providing exploration vectors.
DOI: 10.6084/m9.figshare.23849610.v1
title: Additional file 1 of Promoter hypermethylation of neural-related genes is compatible with stemness in solid cancers

description: Additional file 1: The list of significantly differentially methylated probes is provided in the file “significant Limma output per cancer type.xlsx”. A list of all enriched GO terms per cancer type is provided in the file “GO outcome.rar”. A list of neural differentiation-associated genes is provided in the file “Neural differentiation-associated genes.xlsx”.
DOI: 10.6084/m9.figshare.23849610
title: Additional file 1 of Promoter hypermethylation of neural-related genes is compatible with stemness in solid cancers

description: Additional file 1: The list of significantly differentially methylated probes is provided in the file “significant Limma output per cancer type.xlsx”. A list of all enriched GO terms per cancer type is provided in the file “GO outcome.rar”. A list of neural differentiation-associated genes is provided in the file “Neural differentiation-associated genes.xlsx”.
DOI: 10.6084/m9.figshare.24091834.v1
title: Additional file 4 of Factors associated with suicide in people who use drugs: a scoping review

description: Supplementary Material 4: Charting form for included publications
DOI: 10.6084/m9.figshare.23972931.v1
title: Additional file 1 of Platelet-derived circRNAs signature in patients with gastroenteropancreatic neuroendocrine tumors

description: Additional file 1: Figure S1. Structural and genomic features of circRNAs. Figure S2. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the up-regulated genes for Follow up vs Baseline GEP-NET#1 comparison. Figure S3. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the up-regulated genes for Follow up vs Baseline GEP-NET#4 comparison. Figure S4. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the up-regulated genes for Follow up vs Baseline GEP-NET#5 comparison. Figure S5. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the down-regulated genes for Follow up vs Baseline GEP-NET#1 comparison. Figure S6. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the down-regulated genes for Follow up vs Baseline GEP-NET#4 comparison. Figure S7. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the down-regulated genes for Follow up vs Baseline GEP-NET#5 comparison. Table S1. List of all circRNAs identified in the whole cohort and relative annotations.
DOI: 10.6084/m9.figshare.24070304
title: Additional file 1 of Crush syndrome: a review for prehospital providers and emergency clinicians

description: Additional file 1. Recommended management at each EMT level of classification WHO and ICRC. The progress of CS patients’ care can often depend on appropriate management at each EMT classification level, as well as the proper transfer between levels, and depends on the resources available.
DOI: 10.6084/m9.figshare.23972931
title: Additional file 1 of Platelet-derived circRNAs signature in patients with gastroenteropancreatic neuroendocrine tumors

description: Additional file 1: Figure S1. Structural and genomic features of circRNAs. Figure S2. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the up-regulated genes for Follow up vs Baseline GEP-NET#1 comparison. Figure S3. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the up-regulated genes for Follow up vs Baseline GEP-NET#4 comparison. Figure S4. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the up-regulated genes for Follow up vs Baseline GEP-NET#5 comparison. Figure S5. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the down-regulated genes for Follow up vs Baseline GEP-NET#1 comparison. Figure S6. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the down-regulated genes for Follow up vs Baseline GEP-NET#4 comparison. Figure S7. Tree map of the enriched GO category (Biological Process, Molecular Function and Cellular Component) among the down-regulated genes for Follow up vs Baseline GEP-NET#5 comparison. Table S1. List of all circRNAs identified in the whole cohort and relative annotations.
DOI: 10.6084/m9.figshare.24209121
title: Additional file 9 of Astrocytes of the optic nerve exhibit a region-specific and temporally distinct response to elevated intraocular pressure

description: Additional file 9: Supplementary Table 7. Differentially expressed genes and pathways identified in ONP 30 vs 7 days.
DOI: 10.6084/m9.figshare.24209136.v1
title: Additional file 12 of Astrocytes of the optic nerve exhibit a region-specific and temporally distinct response to elevated intraocular pressure

description: Additional file 12: Supplementary Table 10. Pathways differentiating ONH astrocytes from those in the ONP at 30 days.
DOI: 10.6084/m9.figshare.24209130
title: Additional file 11 of Astrocytes of the optic nerve exhibit a region-specific and temporally distinct response to elevated intraocular pressure

description: Additional file 11: Supplementary Table 9. Differentially expressed genes and pathways identified in ONP 30 vs 0 days.
DOI: 10.6084/m9.figshare.24196829
title: Additional file 2 of A glimpse of the paleome in endolithic microbial communities

description: Additional file 2: Supplementary tables: Table S1. Statistics sequence data processing. pwd = powdered sample, pc = rock pieces sample, QC = quality control. Table S2. Identified contaminants for different taxonomic ranks. Freq = frequency, prev = prevalence, p.freq = tail probability at value R, p.prev = tail probability of the chi-square distribution for the respective taxon based on presence/absence in true samples and negative controls, p = p-value from Fisher's exact test, NA = not available. Please see [112] for details regarding the mentioned metrics. Table S3. Phylum-level taxonomic profiles. lib_blk = library blank, ex_blank = extraction blank, pc = rock pieces sample, pwd = powdered sample. Table S4. Basic assembly statistics and results from read recruitment. Table S5. Phylum-level taxonomic profiles of assembled contigs (&gt; 1 kbp). Table S6. Taxonomy and quality information regarding recovered genome bins based on checkm [64] output. Table S7. Functional profile based on KEGG Lvl3 Orthologies. Abundances are given as CoPM. CoPM = copies per million. Table S8. Functional profile based on a subset of KEGG pathways. CoPM = copies per million, logCoPM = log copies per million.
DOI: 10.6084/m9.figshare.23983470
title: Additional file 1 of The metabolic consequences of HIV/TB co-infection

description: Additional file 1: Table S1. Detailed clinical data for HIV-positive cohorts. Table S2. Fisher’s exact tests for categorical variables. Table S3. Stratification based on CD4 count. Table S4. Untreated co-infected group as used for analyses. Table S5. t-Test. Figure S1. Dendogram of the healthy controls versus untreated HIV/TB co-infected samples, after exclusion of the co-infected samples with high CD4 T-cell counts but before exclusion of any healthy controls. This figure shows that the 5 healthy controls indicated in red cluster with the diseased samples, and were subsequently excluded. Table S6. Fold Change. Table S7. t-Test. Table S8. Fold Change. Table S9. t-Test and FC. Table S10. PLS-DA. Figure S2. The validation results for the PLS-DA analysis of the healthy controls versus all the untreated patient samples. A: Leave-one-out cross-validation results, indicating that PLS-DA with one component is most applicable to these data, B: Permutation testing (frequency = 2000), indicating that the model is not random (significant p-value, &lt;0.05). Table S11. Results of the ANOVA including all groups (with exclusions of HIV+/TB+/Tn- samples with CD4 T cell count&gt;600 and selected healthy controls). Table S12. A count of the compounds significant in the ANOVA post-hoc analysis per compound class. Table S13. Results of the ANOVA including all groups (with exclusions of HIV+/TB+/Tn- samples with CD4 T cell count&gt;600) and selected healthy controls, organized by compound class, and then by significance as per ANOVA post-hoc analysis. Table S14. The effect of untreated HIV/TB on the metabolome (untreated HIV/TB versus healthy controls). Table S15. The effect of HIV on TB (untreated TB vs untreated HIV/TB). Table S16. The effect of ART on HIV/TB (untreated HIV/TB versus treated HIV/TB). Table S17. Pearson's r correlation results for 3,4-DHBA and all other metabolites (from ANOVA). Figure S3. PLS-DA validation results for the comparison of all groups.
DOI: 10.6084/m9.figshare.23983470.v1
title: Additional file 1 of The metabolic consequences of HIV/TB co-infection

description: Additional file 1: Table S1. Detailed clinical data for HIV-positive cohorts. Table S2. Fisher’s exact tests for categorical variables. Table S3. Stratification based on CD4 count. Table S4. Untreated co-infected group as used for analyses. Table S5. t-Test. Figure S1. Dendogram of the healthy controls versus untreated HIV/TB co-infected samples, after exclusion of the co-infected samples with high CD4 T-cell counts but before exclusion of any healthy controls. This figure shows that the 5 healthy controls indicated in red cluster with the diseased samples, and were subsequently excluded. Table S6. Fold Change. Table S7. t-Test. Table S8. Fold Change. Table S9. t-Test and FC. Table S10. PLS-DA. Figure S2. The validation results for the PLS-DA analysis of the healthy controls versus all the untreated patient samples. A: Leave-one-out cross-validation results, indicating that PLS-DA with one component is most applicable to these data, B: Permutation testing (frequency = 2000), indicating that the model is not random (significant p-value, &lt;0.05). Table S11. Results of the ANOVA including all groups (with exclusions of HIV+/TB+/Tn- samples with CD4 T cell count&gt;600 and selected healthy controls). Table S12. A count of the compounds significant in the ANOVA post-hoc analysis per compound class. Table S13. Results of the ANOVA including all groups (with exclusions of HIV+/TB+/Tn- samples with CD4 T cell count&gt;600) and selected healthy controls, organized by compound class, and then by significance as per ANOVA post-hoc analysis. Table S14. The effect of untreated HIV/TB on the metabolome (untreated HIV/TB versus healthy controls). Table S15. The effect of HIV on TB (untreated TB vs untreated HIV/TB). Table S16. The effect of ART on HIV/TB (untreated HIV/TB versus treated HIV/TB). Table S17. Pearson's r correlation results for 3,4-DHBA and all other metabolites (from ANOVA). Figure S3. PLS-DA validation results for the comparison of all groups.
DOI: 10.4227/05/56d79d59c41d3
title: Weeds on Western Australia's Islands: A historical database with records spanning from 1913 to 2014

description: The island weeds database we created contains weed records for 697 islands and 1995 plant species. Data sources cited span between 1913 and 2014. To compound the value of the database, original species identifications were verified by Parks and Wildlife botanists and species names were updated to current taxonomy using the WA census data housed within MAX Version 3.0 (Woodman and Gioia 2016). We do not present any interpretation of the data with this data submission. GPS coordinates for weeds were largely unavailable, so most coordinates provided within the database are island centroids.

Woodman, S. U 0026 Gioia, P. (2016) Max Version 3. Department of Parks and Wildlife, Perth. Available from: http://www.dpaw.wa.gov.au/max.
DOI: 10.4227/05/54beee248d22b
title: Biological and physical data from river sites across a gradient of catchment area under grazing in northern Tasmania

description: River sites were sampled during the summers of 2008/09 and 2009/10  in a survey designed to  identify correlations between commonly used river condition variables and grazing land-use. Potential stream sites in northern Tasmania were screened by catchment size, northing and slope, and according to attributes aimed at minimising confounding variables, maintaining broad consistency in landscape and geomorphological context, and promoting independence among sites. A set of 27 survey sites was selected across a gradient from low to high proportion of land under grazing in their upstream catchments. Catchment sizes varied from 20-120 km2 and proportion grazing from 0-80%. Macroinvertebrates were sampled using  Surber sampler.  All macroinvertebrates within a 20% sub-sample identified to family and counted, with individuals from the insect orders Ephemeroptera, Plecoptera and Trichoptera identified to genus/species (by Laurie Cook, UTAS). Algal abundance was estimated at each site as the proportion of algal cover and as areal density of benthic chlorophyll a. Physical data variables collected were:  water temperature, conductivity, turbidity, pH, total alkalinity, nitrate nitrate, dissolved reactive phosphorus, total nitrogen,  total phosphorus, overhead shading, the proportion of fine sediments within the sampled riffle zone, accumulated abstraction index and accumulated regulation index.

For more infomration see: See Magierowski RH, Read SM, Carter SJB, Warfe DM, Cook LS, Lefroy EC and Davies PE (under review). Inferring landscape-scale land-use impacts on rivers using data from mesocosm experiments and artificial neural networks. PLOS ONE.

Data licence: Australian Creative Commons Attribution Licence - see link for more information https://creativecommons.org/licenses/by/3.0/au/
DOI: 10.4227/05/56f077b3054e9
title: FosSahul database

description: FosSahul is the first database compiling the ages of nonhuman vertebrate fossils from the Middle Pleistocene to the present in the Sahul region. It includes comprehensive metadata with ratings of reliability allocated to each fossil age. Because ecological and evolutionary phenomena are time-dependent, the entire range of archaeological and palaeontological research disciplines benefit from the availability of this data.
DOI: 10.6084/m9.figshare.23949883
title: Additional file 2 of Recipient-independent, high-accuracy FMT-response prediction and optimization in mice and humans

description: Additional file 2.
DOI: 10.6084/m9.figshare.23949883.v1
title: Additional file 2 of Recipient-independent, high-accuracy FMT-response prediction and optimization in mice and humans

description: Additional file 2.
DOI: 10.4227/05/5567a97e4b364
title: AusPlots Woodlands Protocols Field Trial Data 2015 v1

description: The dataset includes two main components: (1) Tree survey - data on the species, diameter and height of individual trees, along with a count of seedlings and saplings; and (2) Coarse woody debris - data on the size and decay class of downed coarse woody debris encountered in the plots.
DOI: 10.4227/05/57354015127b8
title: Australian Individual Tree Biomass Library- v2

description: Individual tree and shrub above-ground biomass (dry weight), stem diameter, height, and associated auxiliary information about the sites from which the trees or shrubs were sampled.
DOI: 10.6084/m9.figshare.24604965
title: HostNet: Improved Sequence Representation in Deep Neural Network for Virus-Host Prediction

description: <br>Abstract: Background: The escalation of viruses over the past decade has brought about the need to determine their respective hosts, particularly for emergent viruses that present a potential menace to the welfare of human and animal life. Yet, the traditional means of ascertaining the host range of viruses, which involves field surveillance and laboratory experiments, is laborious and demanding. Thus, there is a pressing demand for computational tools that can predict virus-host associations with a high degree of accuracy, given the intricate nature of viral-host prediction, which grapples with issues of data imbalance and deficiency. Results: To overcome the challenges of virus-host prediction, we presentHostNet, a deep learning framework that utilizes a Transformer-CNN-BiGRUarchitecture and two enhanced sequence representation modules. The first module, K2V, constructs a background vector representation of k-mers from a broad range of virus sequences to address the issue of data deficiency. This second module, an adaptive sliding window (ASW), truncates virus sequences of various lengths to create a uniform number of informative and distinct samples for each sequence. We assess HostNet’s performance on a benchmark dataset of“Rabies lyssavirus” and an in-house dataset of “Flavivirus.” Our results show that HostNet surpasses the state-of-the-art deep learning-based host prediction method in host-prediction accuracies and F1 score. Our proposed sequence representation modules significantly enhance the deep neural network’s training generalization, performance in challenging classes, and stability on imbalanced data. Conclusions: HostNet is a promising framework for predicting virus hosts from genomic sequences, addressing challenges posed by sparse and varying-length virus sequence data. Our results demonstrate its potential as a valuable tool for viral host prediction in various biological contexts.<i>Flavivirus</i>. We built a nucleotide sequence dataset of virus genus flavivirus for invertebrate host prediction and collected their invertebrate host labels from NCBI GenBank. A total of 9626 sequences from 94 flaviviruses grouped by three invertebrate hosts, two were mosquitos: culex and Aedes, and one tick: Ixodes were selected. In the dataset, the hosts of 73 viruses were mosquitos, 18 viruses were Ixodes, and three viruses had both mosquito and tick as hosts. There were 2424, 6829, and 373 sequences for Culex, Aedes, and Ixodes, respectively. <i>Vir61</i>. For pertaining, namely, training the k-mer to vector representation model, we built a large-scale, wide-ranging, and comprehensive viral gene dataset named Vir61. The sources of virus genomes in the Vir61 dataset include virus genomes that have been published in Genbank. The Vir61 dataset contains 103,466 viral genomes for 1377 viruses belonging to 61 viral families, including Rhabdoviridae, Togaviridae, Ascoviridae, Flaviviridae, etc.
DOI: 10.4227/05/5878480a91885
title: Revegetation rewilds the soil bacterial microbiome of an old field- Part 1: OTU raw data matrix

description: We analysed a total of 3,002,411 quality-filtered bacterial 16S rRNA gene sequences in the 48 technical replicates across the 8 revegetation chronosequence sites, consisting of 3,316 OTUs. Nine bacterial phyla dominated our dataset, including Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Gemmatimonadetes, Planctomycetes, Proteobacteria and Verrucomicrobia.
DOI: 10.34740/kaggle/dsv/7024013
title: 📒 Meta Kaggle ported to MS SQL SERVER 2022 DB
DOI: 10.4227/05/548541119d331
title: Bird response to the size and isolation of unburnt residuals at Pinkawillinie CP, South Australia

description: The data-set describes the occurrence of bird species at sites within a burnt woodland. These sites comprise the following design: 5 replicate block. each with 2 large patch sites, 2 small patch sites and 2 matrix sites. One site of each pair was relatively more isolated than the other (surrounded by a higher proportion of unburnt vegetation). In addition, there are also 6 sites located beyond the extent of the fire. The data-set also lists vegetation attributes at each of these sites.
DOI: 10.4227/05/54c1b45a4cf2f
title: TERN AusPlots - Ausplots Rangelands Survey Program biodiversity mapping supplement dataset

description: This dataset contains records of vascular plant species from selected TERN AusPlots in South Australia. Preparation from raw data involved extraction of all vouchered species from the plots, the removal of intraspecific taxa (only genus and species used to define individual taxa) and removal of duplicate records and those not determined to species.
DOI: 10.4227/05/54c4e38139b4b
title: Pollen diversity matters: revealing the neglected effect of pollen diversity on fitness in fragmented landscapes

description: Mating system and fitness data for families of Eucalyptus socialis grown in common garden experiments. Families collected across a fragmentation gradient. Open-pollinated progeny arrays were collected and reared in the common garden experiments. These open-pollinated progeny arrays were also genotyped at microsatellite loci to generate the mating system data. Data showed association between fragmentation on mating system, which in turn impacted fitness.

Please contact owner prior to use.