cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48597/bxuk-yc3e
title: Nitrate at Zarra

description: Measurement of Nitrate at Zarra
DOI: 10.48597/by4d-tw4q
title: Nitrogen_monoxide at Cabo de Creus

description: Measurement of Nitrogen_monoxide at Cabo de Creus
DOI: 10.48597/cj7k-8hcp
title: POPs (persistent organic pollutants) at Zingst

description: Measurement of POPs (persistent organic pollutants) at Zingst
DOI: 10.48597/cue9-f5cv
title: PAHs (polycyclic aromatic hydrocarbons, 16) at Niembro

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Niembro
DOI: 10.48597/cvde-s8wk
title: Precipitation_amount at Peyrusse Vieille

description: Measurement of Precipitation_amount at Peyrusse Vieille
DOI: 10.48597/dkg7-rg88
title: Precipitation_amount at Heigham Holmes

description: Measurement of Precipitation_amount at Heigham Holmes
DOI: 10.6084/m9.figshare.8867033
title: Additional file 5: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S2. In 77 species, the number of methylation-related genes, the number of single-copy genes, the number of multi-copy genes, the number of missing genes, and the chromosome ploidy of the sequenced species. (XLSX 58 kb)
DOI: 10.48597/dm6d-yamm
title: Nitrate at Campisabalos

description: Measurement of Nitrate at Campisabalos
DOI: 10.6084/m9.figshare.8867051
title: Additional file 8: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S5. The gene length, exon number, exon length, intron length of methylation-related genes in 18 species. A: Gene length of methylation-related genes in 18 species. B: The number of genes with extreme values in gene length. C: Exon number of methylation-related genes in 18 species. D: The number of genes with extreme values in exon number. E: Gene length of methylation-related genes in 18 species. F: The number of genes with extreme values in exon length. G: Intron length of methylation-related genes in 18 species. H: The number of genes with extreme values in intron length. (XLSX 70 kb)
DOI: 10.6084/m9.figshare.8867033.v1
title: Additional file 5: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S2. In 77 species, the number of methylation-related genes, the number of single-copy genes, the number of multi-copy genes, the number of missing genes, and the chromosome ploidy of the sequenced species. (XLSX 58 kb)
DOI: 10.48597/e7du-btgr
title: Inorganics in air and particle phase at Søgne

description: Measurement of Inorganics in air and particle phase at Søgne
DOI: 10.48597/em9a-bk79
title: Inorganics in air and particle phase at Waldhof

description: Measurement of Inorganics in air and particle phase at Waldhof
DOI: 10.48597/eszd-zav9
title: Inorganics in precipitation and zinc at Langtjern

description: Measurement of Inorganics in precipitation and zinc at Langtjern
DOI: 10.48597/fkne-w26v
title: Pm10_mass at Westerland

description: Measurement of Pm10_mass at Westerland
DOI: 10.48597/g3ak-wth6
title: Sulphur_dioxide at Waldhof

description: Measurement of Sulphur_dioxide at Waldhof
DOI: 10.48597/hg25-vamc
title: VOC (hydrocarbons) at Hohenpeissenberg

description: Measurement of VOC (hydrocarbons) at Hohenpeissenberg
DOI: 10.48597/hp8t-pnyd
title: Nitrate at Els Torms

description: Measurement of Nitrate at Els Torms
DOI: 10.48597/hw3b-umq9
title: Sulphate_corrected at Haukeland

description: Measurement of Sulphate_corrected at Haukeland
DOI: 10.48597/hxz5-jkk7
title: Inorganics in air and particle phase at Waldhof

description: Measurement of Inorganics in air and particle phase at Waldhof
DOI: 10.48597/jcf5-5ynr
title: Propyne at Rigi

description: Measurement of Propyne at Rigi
DOI: 10.48597/js82-xtqv
title: Mercury at Pallas (Matorova)

description: Measurement of Mercury at Pallas (Matorova)
DOI: 10.48597/jvna-kkxj
title: Nitrate at O Saviñao

description: Measurement of Nitrate at O Saviñao
DOI: 10.48597/k33u-ybtq
title: Nitrate at Risco Llamo

description: Measurement of Nitrate at Risco Llamo
DOI: 10.48597/m3xb-nz76
title: Inorganics in precipitation at Valentia Observatory

description: Measurement of Inorganics in precipitation at Valentia Observatory
DOI: 10.48597/n92p-rqhg
title: Inorganics in air and particle phase at Niembro

description: Measurement of Inorganics in air and particle phase at Niembro
DOI: 10.48597/nbt8-9gt8
title: PCB_28+16 at Zeppelin mountain (Ny-Ålesund)

description: Measurement of PCB_28+16 at Zeppelin mountain (Ny-Ålesund)
DOI: 10.21227/ebbx-5q84
title: IEEEXtreme 15: Training Plan

description: This dataset contains a total of 1195 submissions, with 5% correct solutions and 41% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/training-plan/ See the included PDF document for details about the original challenge.
DOI: 10.6084/m9.figshare.8867060.v1
title: Additional file 9: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S6. Summary of 77 sequenced genomes used for identification of methylation-related genes. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.8867051.v1
title: Additional file 8: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S5. The gene length, exon number, exon length, intron length of methylation-related genes in 18 species. A: Gene length of methylation-related genes in 18 species. B: The number of genes with extreme values in gene length. C: Exon number of methylation-related genes in 18 species. D: The number of genes with extreme values in exon number. E: Gene length of methylation-related genes in 18 species. F: The number of genes with extreme values in exon length. G: Intron length of methylation-related genes in 18 species. H: The number of genes with extreme values in intron length. (XLSX 70 kb)
DOI: 10.6084/m9.figshare.8867036
title: Additional file 6: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S3. In six polyploid plants, the normalized number of methylation-related genes, the normalized number of single-copy genes, the normalized number of multi-copy genes, the normalized number of missing genes, and the chromosome ploidy of the sequenced species. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.8867036.v1
title: Additional file 6: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S3. In six polyploid plants, the normalized number of methylation-related genes, the normalized number of single-copy genes, the normalized number of multi-copy genes, the normalized number of missing genes, and the chromosome ploidy of the sequenced species. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.8867060
title: Additional file 9: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S6. Summary of 77 sequenced genomes used for identification of methylation-related genes. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.14634147
title: Additional file 1 of Very long intergenic non-coding (vlinc) RNAs directly regulate multiple genes in cis and trans

description: Additional file 1: Table S1. Drugs used in SMS and Illumina RNAseq analyses. Table S2. DE mRNAs or vlincRNAs found in each drug treatment in the SMS RNAseq analysis. Table S3. Summary of the validation of the DE vlincRNAs by real-time PCR. Table S4. Numbers of mRNAs found to be co-expressed with each vlincRNA using either SMS or Illumina RNAseq. Table S5. Analysis of the concordancy of the two biological replicas (B1 and B2) of the RAT experiments. Table S6. Comparison of the aggregated RAT signal of different types of genes based on single-sided Wilcoxson Rank Sum Test. Table S7. The overlap between co-expression and the chromatin interaction datasets for top and botton half of expressed mRNAs. Table S8. Significance of the overlap between the co-expression and vlincRNA-chromatin interaction datasets with increasing RAT signal thresholds. Table S9. Overlap between the co-expression networks obtained after the separation based on the expression level and the chromatin interaction dataset for the SMS RNAseq platform. Table S10. Relative fold changes of the co-expressed transcripts in response to vlincRNA knockdown. Table S11. Genes in common between the co-expression and chromatin interaction datasets for each vlincRNA tend to be found consistently in drug and DMSO treatments. Table S12. The overlap between the co-expression and chromatin interaction datasets limited to the genes located on the same chromosomes based on top 50% and bottom 50% expressed mRNAs. Table S13. The top 100 GO terms enriched in the genes either negatively (Table S13.1) or positively (Table S13.2) co-expressed with the vlincRNAs. Table S14. Ratios of the normalized counts of each targeting gRNA vs the cognate non-targeting gRNA control in the mixed CRISPR/Cas13 cell lines subjected to various treatments. Table S15. Overlap between the co-expression networks and the chromatin interaction dataset for the Illumina RNAseq platform. Table S16. Overlap between the co-expression and the chromatin interaction datasets based on merged data for SMS and Illumina RNAseq platform. Table S17. The effect of vlincRNA knockdown on Illumina-based co-expression networks. Table S18. Coordinates of vlincRNAs and sequences of gRNAs used in the RAT and Cas13 knockdown cell lines.
DOI: 10.6084/m9.figshare.14634147.v1
title: Additional file 1 of Very long intergenic non-coding (vlinc) RNAs directly regulate multiple genes in cis and trans

description: Additional file 1: Table S1. Drugs used in SMS and Illumina RNAseq analyses. Table S2. DE mRNAs or vlincRNAs found in each drug treatment in the SMS RNAseq analysis. Table S3. Summary of the validation of the DE vlincRNAs by real-time PCR. Table S4. Numbers of mRNAs found to be co-expressed with each vlincRNA using either SMS or Illumina RNAseq. Table S5. Analysis of the concordancy of the two biological replicas (B1 and B2) of the RAT experiments. Table S6. Comparison of the aggregated RAT signal of different types of genes based on single-sided Wilcoxson Rank Sum Test. Table S7. The overlap between co-expression and the chromatin interaction datasets for top and botton half of expressed mRNAs. Table S8. Significance of the overlap between the co-expression and vlincRNA-chromatin interaction datasets with increasing RAT signal thresholds. Table S9. Overlap between the co-expression networks obtained after the separation based on the expression level and the chromatin interaction dataset for the SMS RNAseq platform. Table S10. Relative fold changes of the co-expressed transcripts in response to vlincRNA knockdown. Table S11. Genes in common between the co-expression and chromatin interaction datasets for each vlincRNA tend to be found consistently in drug and DMSO treatments. Table S12. The overlap between the co-expression and chromatin interaction datasets limited to the genes located on the same chromosomes based on top 50% and bottom 50% expressed mRNAs. Table S13. The top 100 GO terms enriched in the genes either negatively (Table S13.1) or positively (Table S13.2) co-expressed with the vlincRNAs. Table S14. Ratios of the normalized counts of each targeting gRNA vs the cognate non-targeting gRNA control in the mixed CRISPR/Cas13 cell lines subjected to various treatments. Table S15. Overlap between the co-expression networks and the chromatin interaction dataset for the Illumina RNAseq platform. Table S16. Overlap between the co-expression and the chromatin interaction datasets based on merged data for SMS and Illumina RNAseq platform. Table S17. The effect of vlincRNA knockdown on Illumina-based co-expression networks. Table S18. Coordinates of vlincRNAs and sequences of gRNAs used in the RAT and Cas13 knockdown cell lines.
DOI: 10.6084/m9.figshare.8867045
title: Additional file 7: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S4. A summary of the duplication models of some methylation-related genes in five species. (XLSX 44 kb)
DOI: 10.6084/m9.figshare.8867045.v1
title: Additional file 7: of Tracing the origin and evolution history of methylation-related genes in plants

description: Table S4. A summary of the duplication models of some methylation-related genes in five species. (XLSX 44 kb)
DOI: 10.6084/m9.figshare.23641765
title: Clinical and electrocardiographic factors associated with adverse cardiovascular events in bupropion exposures

description: Bupropion toxicity can cause cardiogenic shock, ventricular dysrhythmias, and death. Clinical and electrocardiographic factors associated with adverse cardiovascular events in bupropion toxicity have not been well-studied. This study aimed to identify factors associated with adverse cardiovascular events in adult patients with isolated bupropion exposures. This retrospective cohort study queried the National Poison Data System from 2019 through 2020. We included patients 20 years or older with acute or acute-on-chronic single-agent bupropion exposures evaluated in a healthcare facility. Exclusion criteria were confirmed non-exposure, withdrawal as a reason for exposure, lack of follow-up, documentation that exposure was probably not responsible for the effects, and missing data. The primary outcome was adverse cardiovascular events, defined as the presence of any of the following: vasopressor use, ventricular dysrhythmia, myocardial injury, or cardiac arrest. Independent variables were age, the intentionality of exposure, seizures, tachycardia, QRS widening, and QTc prolongation. Multivariable logistic regression was performed to test for independent associations between independent variables and adverse cardiovascular events. Of 4,640 patients included in the final analysis (56.7% female, 56.5% suspected suicidal intent), 68 (1.47%) experienced an adverse cardiovascular event. Age (odds ratio 1.03; 95% confidence intervals 1.02–1.05), single seizure (odds ratio 9.18; 95% confidence intervals 4.24–19.9) and complicated seizures (odds ratio 38.9; 95% confidence intervals 19.3–78.1), QRS widening (odds ratio 3.01; 95% confidence intervals 1.62–5.59), and QTc prolongation (odds ratio 1.76; 95% confidence intervals 1.00–3.10) were independently associated with adverse cardiovascular events. No patients with unintentional exposure experienced adverse cardiovascular events, prohibiting intentionality from inclusion in the regression model. In the post hoc subgroup analysis of intentional exposures, age, single and complicated seizures, and QRS widening remained independently associated with adverse cardiovascular events. Increasing age, seizures, QRS widening, and QTc prolongation were associated with adverse cardiovascular events in bupropion exposures. Adverse cardiovascular events did not occur in unintentional exposures. Further research is needed to develop screening tools and treatments for bupropion cardiotoxicity.
DOI: 10.6084/m9.figshare.23684865
title: Analytically confirmed illicit and novel psychoactive drug use in Western Australian emergency departments: initial results from the Emerging Drugs Network of Australia (EDNA)

description: The burden of acute illicit drug use in Australia is largely unknown. Establishing a prospective drug surveillance system in emergency departments using analytical confirmation may facilitate the early identification of emerging drugs. We describe demographic data and acute toxicity patterns, stratified by analytical confirmation of illicit drugs and novel psychoactive substances, to emergency departments in Western Australia. Patients presenting with severe and/or unusual clinical features consistent with recreational drug toxicity were identified across five Western Australian emergency departments participating in the Emerging Drugs Network of Australia between April 2020 and December 2021. Demographic and toxicology patterns in patients with and without analytically confirmed illicit drugs/novel psychoactive substances from blood samples were collected during the emergency department presentation. The cohort included 434 severe and/or unusual toxicology presentations; median age 33 years (first and third quartiles 25–40 years), 268 (61.8%) males. Any substance (illicit, novel psychoactive substance, pharmaceutical) was detected in 405 (93.3%) presentations. Illicit drugs/novel psychoactive substances were detected in 257 (59.2%) presentations, including 73 (28.3%) with more than one confirmed illicit drug/novel psychoactive substance. Frequent illicit drugs identified were metamfetamine (<i>n</i> = 201, 77.9%) and gamma-hydroxybutyrate (<i>n</i> = 30, 11.6%). Forty-eight novel psychoactive substances were detected within 43 (16.7%) presentations. Novel benzodiazepines were most frequently detected (<i>n</i> = 29, 60.4%). Frequent pharmaceuticals detected included diazepam (<i>n</i> = 100, 26.1%) and clonazepam (<i>n</i> = 40, 10.4%). One hundred and fifty-five (35.7%) presentations were discharged home and 56 (12.9%) were admitted to intensive care. Presentations with detected illicit drugs/novel psychoactive substances had a lower median intensive care length of stay compared to presentations without detected illicit drugs/novel psychoactive substances (32.6 h versus 50.8 h respectively, <i>P</i> &lt; 0.001). Integration of clinical and analytic data in patients with severe and/or unusual toxicology presentations <i>via</i> the Emerging Drugs Network of Australia provides insight into illicit drug/novel psychoactive substance use responsible for acute harm across Western Australian emergency departments.
DOI: 10.6084/m9.figshare.23684865.v1
title: Analytically confirmed illicit and novel psychoactive drug use in Western Australian emergency departments: initial results from the Emerging Drugs Network of Australia (EDNA)

description: The burden of acute illicit drug use in Australia is largely unknown. Establishing a prospective drug surveillance system in emergency departments using analytical confirmation may facilitate the early identification of emerging drugs. We describe demographic data and acute toxicity patterns, stratified by analytical confirmation of illicit drugs and novel psychoactive substances, to emergency departments in Western Australia. Patients presenting with severe and/or unusual clinical features consistent with recreational drug toxicity were identified across five Western Australian emergency departments participating in the Emerging Drugs Network of Australia between April 2020 and December 2021. Demographic and toxicology patterns in patients with and without analytically confirmed illicit drugs/novel psychoactive substances from blood samples were collected during the emergency department presentation. The cohort included 434 severe and/or unusual toxicology presentations; median age 33 years (first and third quartiles 25–40 years), 268 (61.8%) males. Any substance (illicit, novel psychoactive substance, pharmaceutical) was detected in 405 (93.3%) presentations. Illicit drugs/novel psychoactive substances were detected in 257 (59.2%) presentations, including 73 (28.3%) with more than one confirmed illicit drug/novel psychoactive substance. Frequent illicit drugs identified were metamfetamine (<i>n</i> = 201, 77.9%) and gamma-hydroxybutyrate (<i>n</i> = 30, 11.6%). Forty-eight novel psychoactive substances were detected within 43 (16.7%) presentations. Novel benzodiazepines were most frequently detected (<i>n</i> = 29, 60.4%). Frequent pharmaceuticals detected included diazepam (<i>n</i> = 100, 26.1%) and clonazepam (<i>n</i> = 40, 10.4%). One hundred and fifty-five (35.7%) presentations were discharged home and 56 (12.9%) were admitted to intensive care. Presentations with detected illicit drugs/novel psychoactive substances had a lower median intensive care length of stay compared to presentations without detected illicit drugs/novel psychoactive substances (32.6 h versus 50.8 h respectively, <i>P</i> &lt; 0.001). Integration of clinical and analytic data in patients with severe and/or unusual toxicology presentations <i>via</i> the Emerging Drugs Network of Australia provides insight into illicit drug/novel psychoactive substance use responsible for acute harm across Western Australian emergency departments.
DOI: 10.6084/m9.figshare.23653709.v1
title: The Opioid Overdose Resuscitation Education for Addiction Counselors and Trainees (Opioid Overdose REACT) naloxone response education pilot project improved confidence and knowledge among addiction counselors and trainees

description: Community programs to teach nonmedical laypeople how to recognize an opioid overdose and effectively resuscitate the victim using naloxone have proliferated recently as a significant component of harm-reduction efforts. Although many such programs target laypeople like first responders or friends and family members of people who use drugs, there are currently no programs that specifically target addiction counselors, despite their work with a client population at high risk of an opioid overdose. The four-hour curriculum designed by the authors covered opioid agonist and antagonist pharmacology; opioid toxidrome signs; legal implications and indications for using the naloxone kits; and hands-on training. Participants were two cohorts of addiction counselors and addiction counseling trainees at our institution and an affiliated Opioid Treatment Program methadone clinic. Surveys testing participant knowledge and confidence were conducted at baseline, immediately post-training, six months post-training, and 12 months post-training. Overall, opioid and naloxone pharmacology knowledge, as well as the confidence to intervene in an overdose emergency, improved among participants in both cohorts. Knowledge scores at baseline (<i>n</i> = 36, median 5/10) improved significantly immediately post-training (<i>n</i> = 31, median 7/10, <i>P</i> &lt; 0.0001, Wilcoxon signed-rank test) and were sustained six (<i>n</i> = 19) and 12 months (<i>n</i> = 11) later. Two participants reported using their naloxone kits to successfully reverse a client overdose in the 12 months after taking the course. These results from our knowledge translation pilot project suggest that our educational program to train addiction counselors in opioid pharmacology and toxicology, allowing them to recognize and respond to an opioid overdose, is feasible and could be effective. Specific barriers to implementing such educational programs include cost, stigma, and unclear best practice for designing and conducting these programs. Further study of providing opioid pharmacology education and overdose and naloxone training to addiction counselors and counseling trainees appears to be warranted.