cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7765080
title: Cypherpunks Mailing List (merge 1992-2023/03)

description: Merged dataset with cypherpunks mailing list (From, Date, Subject and Body Data source: https://github.com/cryptoanarchywiki 1992-2000: https://mailing-list-archive.cryptoanarchy.wiki/ / https://cypherpunks.venona.com/raw/ (228 MB| 98807 mails) 2000-2016: https://github.com/cryptoanarchywiki/2000-to-2016-raw-cypherpunks-archive (246,7 MB | /92193 mails) July 2013 to Present/March 2023: https://lists.cpunks.org/pipermail/cypherpunks/ (1206 MB | 65795 mails)
DOI: 10.5281/zenodo.7765079
title: Cypherpunks Mailing List (merge 1992-2023/03)

description: Merged dataset with cypherpunks mailing list Data source: https://github.com/cryptoanarchywiki 1992-2000: https://mailing-list-archive.cryptoanarchy.wiki/ / https://cypherpunks.venona.com/raw/ (228 MB| 98807 mails) 2000-2016: https://github.com/cryptoanarchywiki/2000-to-2016-raw-cypherpunks-archive (246,7 MB | /92193 mails) July 2013 to Present/March 2023: https://lists.cpunks.org/pipermail/cypherpunks/ (1206 MB | 65795 mails) Last version (511.6 MB) with all metadata: from_address = msg['From'] to_address = msg['To'] message_id = msg['Message-ID'] date = msg['Date'] subject = msg['Subject'] in_reply_to = msg['In-Reply-To'] mime_version = msg['MIME-Version'] content_type = msg['Content-Type'] body = msg.get_payload()
DOI: 10.5281/zenodo.7815449
title: Cypherpunks Mailing List (merge 1992-2023/03)

description: Merged dataset with cypherpunks mailing list (From, Date, Subject and Body Data source: https://github.com/cryptoanarchywiki 1992-2000: https://mailing-list-archive.cryptoanarchy.wiki/ / https://cypherpunks.venona.com/raw/ (228 MB| 98807 mails) 2000-2016: https://github.com/cryptoanarchywiki/2000-to-2016-raw-cypherpunks-archive (246,7 MB | /92193 mails) July 2013 to Present/March 2023: https://lists.cpunks.org/pipermail/cypherpunks/ (1206 MB | 65795 mails)
DOI: 10.5281/zenodo.7924881
title: Cypherpunks Mailing List (merge 1992-2023/03)

description: Merged dataset with cypherpunks mailing list Data source: https://github.com/cryptoanarchywiki 1992-2000: https://mailing-list-archive.cryptoanarchy.wiki/ / https://cypherpunks.venona.com/raw/ (228 MB| 98807 mails) 2000-2016: https://github.com/cryptoanarchywiki/2000-to-2016-raw-cypherpunks-archive (246,7 MB | /92193 mails) July 2013 to Present/March 2023: https://lists.cpunks.org/pipermail/cypherpunks/ (1206 MB | 65795 mails) Last version (511.6 MB) with all metadata: from_address = msg['From'] to_address = msg['To'] message_id = msg['Message-ID'] date = msg['Date'] subject = msg['Subject'] in_reply_to = msg['In-Reply-To'] mime_version = msg['MIME-Version'] content_type = msg['Content-Type'] body = msg.get_payload()
DOI: 10.25934/pr00008938
title: Data challenge

description: Antimicrobial resistance (AMR) is a constantly evolving multiscale phenomenon representing a growing public health issue worldwide, particularly in low- and middle-income countries (LMIC). So far, clinical data are under-exploited, and there is a paucity of surveillance data in LMIC.
Among all the gram-negative pathogens, members of Enterobacteriaceae are among the World Health Organization's priority pathogens with high resistant rates, causing serious infections worldwide. Currently, the AMR dynamics and patterns among the Enterobacteriaceae population from LMIC remain unclear. Moreover, the exact drug-resistant Enterobacteriaceae clones circulating in Africa and their mechanisms of resistance and spread remain to be ascertained. Interestingly, with the advances and availability of clinical and genomic data, it is currently possible to dig deep into certain pathogen-related factors contributing to and mediating AMR.
Firstly, we aim to identify and demystify the temporal and spatial AMR dynamics and patterns among the Enterobacteriaceae population and subpopulation from LMIC over different sampling periods. Thereafter, and more interestingly, we aim to use available genomic data with the help of bioinformatics tools to unravel the prevalence of resistance genes, understand the exact AMR circulating clones in LMIC and also demystify the precise mechanisms of the spread of the clones in this region. We intend to use data from ATLAS databases, Venatorx-GEAR, and publicly available databases.
Overall, our approach is necessary to track AMR trends properly, understand circulating bacterial clones of importance, identify potential outbreak clusters in certain regions, and prevent and control infections in LMIC. In addition, aside from understanding AMR dynamics in LMIC, integrating scalable genomics into routine surveillance programs is a critical task, an area we are highly passionate about. The result of this study is critical for new drug discovery and development strategies. It is also vital to inform public health practice.
DOI: 10.35078/xjkh8n
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Diamantina | Município: São Gonçalo do Rio Preto (antiga Felisberto Caldeira)

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.4121/1aac46fb-7900-4d4c-a099-d2ce354811d2.v2
title: 4D spatio-temporal laser scan dataset of the beach-dune system in Noordwijk, NL

description: From July 2019 to June 2022 a stationary laser scanner, installed on top of the balcony of Grand Hotel Huis ter Duin was used to survey the beach-dune system at the coast in Noordwijk, The Netherlands. The observed area is about 1000 m long and, depending on the tides, about 350 m wide and includes dunes and a sandy beach.A total of 21812 hourly scans were obtained from July 11<sup>th</sup> 2019, 14:00 until June 21<sup>st</sup> 2022, 12:00. Each scan produces a 3D point cloud containing about 4 million points depending on atmospheric conditions and the tide-dependent width of the beach. Additional attributes such as the laser return intensity are available for each individual 3D point record.
DOI: 10.25934/pr00008936
title: Data Challenge

description: Spatiotemporal modelling of antimicrobial resistance in key gram-negative pathogens: Deciphering global patterns using indirect predictors

Antimicrobial resistance (AMR) in gram-negative pathogens is a growing global health threat, particularly in low and middle-income countries (LMICs) [1]. Traditional surveillance methods often face challenges due to limited resources and diagnostic capacity [2]. In light of the growing need for effective surveillance interventions, the use of indirect predictors, such as sociodemographic, healthcare, and environmental indicators, has emerged as a valuable approach for estimating AMR prevalence [3,4]. Our recent study used socio-economic correlations to forecast national AMR trends and devised a prediction model for clinical AMR prevalence in countries without historical data [5]. By harnessing the power of these surrogate markers, robust predictive models can facilitate data-driven prioritisation of surveillance efforts and guide interventions to curb the spread of AMR [5,6].

Our project aims to model global spatiotemporal AMR trends for key gram-negative pathogens (Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa) by combining susceptibility data with sociodemographic, environmental, and health-related covariates. Our methodology includes: 

1.	Model Evaluation: Validate our prediction model (1998-2017) [5] using the new dataset (2018-2021).
2.	Model Development: Optimize our model with additional indirect predictors [7] and advanced techniques, like stacked ensemble models and spatiotemporal Gaussian process regression (ST-GPR).
3.	Model Comparison: Assess the performance of original and optimized AMR prediction models.
4.	Synthesize findings, draw conclusions, and provide strategic recommendations.

We commit to Open Science by publishing in an open-access journal, and our approach can be generalizable to other priority pathogens. Over 3 billion people, especially in LMICs, live in areas with uncertain AMR estimates of resistance. Our advanced modelling techniques offer an efficient method to facilitate data-driven prioritization of surveillance efforts and significantly contribute to the global battle against antimicrobial resistance.

The supplementary information page contains references and extended methodology description.
DOI: 10.11583/dtu.22739759
title: Rødby - nearshore PM vertical profiles

description: Vertical profiles up to 120 m of PM1, PM2.5 and PM10 using a multi-rotor uncrewed aerial system (UAS) and an optical particle counter (OPC). <br> Files named "baro" are exports of the UAS autopilot. baro_1 and baro_2 correspond to the first two flights, and baro_3-4 combines flights 3-4. From there, columns of importance are: timestamp: Datetime in epochtime [ns] Alt: Altitude [m] Press: Air pressure [Pa]. <br> Four OPC output files are included stating the sensor used and the time of the measurements, with the following name convention: sensor_name_datetime <br> From the data file, the following columns are of importance: Date: Date and time of each measurement Bin0 - Bin23: OPC size channels SFR: Sampling flow rate [100 ml s-1] Sampling Period: The sampling time for each measurement [100 s] PM1, PM2.5, PM10: PM concentrations [μg m-3]
DOI: 10.11583/dtu.22739759.v1
title: Rødby - nearshore PM vertical profiles

description: Vertical profiles up to 120 m of PM1, PM2.5 and PM10 using a multi-rotor uncrewed aerial system (UAS) and an optical particle counter (OPC). <br> Files named "baro" are exports of the UAS autopilot. baro_1 and baro_2 correspond to the first two flights, and baro_3-4 combines flights 3-4. From there, columns of importance are: timestamp: Datetime in epochtime [ns] Alt: Altitude [m] Press: Air pressure [Pa]. <br> Four OPC output files are included stating the sensor used and the time of the measurements, with the following name convention: sensor_name_datetime <br> From the data file, the following columns are of importance: Date: Date and time of each measurement Bin0 - Bin23: OPC size channels SFR: Sampling flow rate [100 ml s-1] Sampling Period: The sampling time for each measurement [100 s] PM1, PM2.5, PM10: PM concentrations [μg m-3]
DOI: 10.25444/nhlbi.22782665
title: Dataset for Reorganization of Mitochondria-Organelle Interactions during Postnatal Development in Skeletal Muscle

description: Prism files including data tables, statistical analyses, and data graphs for all figures in Reorganization of Mitochondria-Organelle Interactions during Postnatal Development in Skeletal Muscle .
DOI: 10.25444/nhlbi.22782665.v1
title: Dataset for Reorganization of Mitochondria-Organelle Interactions during Postnatal Development in Skeletal Muscle

description: Prism files including data tables, statistical analyses, and data graphs for all figures in Reorganization of Mitochondria-Organelle Interactions during Postnatal Development in Skeletal Muscle .
DOI: 10.5281/zenodo.7924287
title: Datasets for " Evaluation of the TOF-ACSM-CV for PM1.0 and PM2.5 measurements during the RITA-2021 field campaign"

description: For the description of the dataset, please see the readme file included in the compressed file.
DOI: 10.7910/dvn/qh4zui
title: Synthetic Vectors for Activating the Driving Axis of Ferroptosis

description: Ferroptosis is a promising strategy for cancer therapy, with numerous inhibitors of its braking axes under investigation as potential drugs. However, few studies have explored the potential of activating the driving axes to induce ferroptosis. Herein, phosphatidylcholine peroxide decorating liposomes (LIPPCPO) were developed as a ferroptosis inducer by targeting divalent metal transporter 1 (DMT1). LIPPCPO was found to boost lysosomal Fe2+ efflux by interacting with lysosomal DMT1, resulting in glutathione peroxidase 4 (GPX4) suppression, glutathione depletion and ferroptosis in breast cancer cells and xenografts. Importantly, LIPPCPO induced ferroptotic cell death was independent of acquired resistance to radiation, chemotherapy, or targeted agents in 11 cancer cell lines. Furthermore, a strong synergistic ferroptosis effect was observed between LIPPCPO and an FDA-approved drug, artesunate. The formula of LIPPCPO encapsulating artesunate significantly inhibited tumor growth and metastasis and improved the survival rate of breast cancer-bearing mice. These findings provide a distinct strategy for inducing ferroptosis and highlight the potential of LIPPCPO as a vector to synergize the therapeutic effects of conventional ferroptosis inducers.
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n.1
title: 3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)tetrahydropyran-2-yl]anthracene-2-carboxylic acid
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI descriptor[cheminf_000113]: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1, and canonical SMILES descriptor[cheminf_000007]: OC[C@H]1O[C@H]([C@@H]([C@H]([C@@H]1O)O)O)c1c(O)c2c(c(c1O)O)C(=O)c1c(C2=O)c(C)c(c(c1)O)C(=O)O, and by the IUPAC name[cheminf_000107]: 3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid. The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]: OC[C@H]1O[C@H]([C@@H]([C@H]([C@@H]1O)O)O)c1c(O)c2c(c(c1O)O)C(=O)c1c(C2=O)c(C)c(c(c1)O)C(=O)O The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-29401 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]: Melting point descriptor[CHEMINF_000256]: 165.0 (°C) Boiling point descriptor[CHEMINF_000257]: Refractive index descriptor[CHEMINF_000253]: The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]: CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR) CHMO:0000595 | 13C nuclear magnetic resonance spectroscopy (13C NMR) CHMO:0001150 | 1H--1H correlation spectroscopy (1H-1H COSY) CHMO:0001146 | 1H--13C heteronuclear single quantum coherence (1H-13C HSQC) CHMO:0001148 | 1H--13C heteronuclear multiple bond coherence (13C-1H HMBC) CHMO:0001151 | 1H--1H nuclear Overhauser enhancement spectroscopy (1H-1H NOESY) CHMO:0000292 | ultraviolet-visible spectrophotometry (UV-VIS) CHMO:0000292 | ultraviolet-visible spectrophotometry (UV-VIS) CHMO:0000292 | ultraviolet-visible spectrophotometry (UV-VIS) CHMO:0000323 | circular dichroism spectroscopy (CD spectrometry) CHMO:0000577 | electrospray ionisation tandem mass spectrometry (ESI-MS2) The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: Used ontologies: CHEBI - Chemical Entities of Biological Interest CHEMINF - chemical information ontology (information entities about chemical entities) CHMO - Chemical Methods Ontology OBI - Ontology for Biomedical Investigations
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0000292.2
title: ultraviolet-visible spectrophotometry (UV-VIS) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for ultraviolet-visible spectrophotometry (UV-VIS)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, D2O with a drop of CF3COOH at 50 °C, DDS, ppm) δ = 184.2, 183.8, 169.8, 158.1, 156.7, 152.7, 146.3, 141.7, 134.5, 129.6, 122.3, 119.0, 111.1, 110.7, 104.9, 80.5, 77.8, 73.4, 71.3, 69.8, 61.1, 19.1.
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0001151
title: 1H--1H nuclear Overhauser enhancement spectroscopy (1H-1H NOESY) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for 1H--1H nuclear Overhauser enhancement spectroscopy (1H-1H NOESY)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0000292.1
title: ultraviolet-visible spectrophotometry (UV-VIS) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for ultraviolet-visible spectrophotometry (UV-VIS)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0000323
title: circular dichroism spectroscopy (CD spectrometry) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for circular dichroism spectroscopy (CD spectrometry)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, D2O with a drop of CF3COOD at 50 °C, DSS) δ = 6.60 (s, 1H), 4.71 (d, J = 9.9 Hz, 1H), 4.05–3.81 (m, 3H), 3.63–3.47 (m, 3H), 1.98 (s, 3H). Missing signals (9H due to H/D exchange in D2O).
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0000292
title: ultraviolet-visible spectrophotometry (UV-VIS) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for ultraviolet-visible spectrophotometry (UV-VIS)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0000577
title: electrospray ionisation tandem mass spectrometry (ESI-MS2) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for electrospray ionisation tandem mass spectrometry (ESI-MS2)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0001146
title: 1H--13C heteronuclear single quantum coherence (1H-13C HSQC) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for 1H--13C heteronuclear single quantum coherence (1H-13C HSQC)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0001148
title: 1H--13C heteronuclear multiple bond coherence (13C-1H HMBC) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for 1H--13C heteronuclear multiple bond coherence (13C-1H HMBC)
DOI: 10.14272/dgqlvpjvxfoqev-jnvstxmasa-n/chmo0001150
title: 1H--1H correlation spectroscopy (1H-1H COSY) (3,5,6,8-tetrahydroxy-1-methyl-9,10-dioxo-7-[(2S,3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]anthracene-2-carboxylic acid)
title: InChI=1S/C22H20O13/c1-4-8-5(2-6(24)9(4)22(33)34)13(25)10-11(15(8)27)16(28)12(18(30)17(10)29)21-20(32)19(31)14(26)7(3-23)35-21/h2,7,14,19-21,23-24,26,28-32H,3H2,1H3,(H,33,34)/t7-,14-,19+,20-,21+/m1/s1

description: dataset for 1H--1H correlation spectroscopy (1H-1H COSY)