cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/2z5gjnggmy.1
title: Spatiotemporal Visualization of Hyperphosphorylation-induced Tau Conformational Change in Early Stage Tauopathy by FRET-based Biosensor in Living Cells

description: Figure 2. TCCB T1 showed a significant increase in the FRET/ECFP emission ratio from 20min and finally a 1.1-fold change at 160 min in soluble ROI like the TCCB T1-SF, but there is no change of FRET/ECFP emission ratio in MT-associated ROI. This indicates that there is no change in MT-associated tau during 160 minutes of conformational change of soluble tau, which is consistent with previous studies that the conformational change occurred in soluble, flexible tau first.
Figure 3. Mutant sensors showed no change in the FRET/ECFP emission ratio of soluble tau region and MT-associated tau region, like the DMSO-treated control. These consequently suggest that our TCCB T1 can detect conformational changes due to the interaction between amino acids of the N-terminus (5-15) and a group of amino acids spanning the third repeat domain(312-322) of tau when tau is hyperphosphorylated in the early stage of tauopathy.
Figure 4. We identified the approximate time to reach the late stage of tauopathy by checking intensity change after treating Fsk in the cells transfected by Tau-BiFC, one of the aggregation tau sensors. We investigated whether our sensor detects the true early stage compared with Tau-BiFC. These results demonstrate that conformational change of hyperphosphorylated tau occurs at an earlier stage than aggregation in the cell-based tauopathy study.
Figure 5. we expected that MT-associated tau did not change significantly in the beginning, but after detaching, conformational change, aggregation proceeded, and MT-depolymerization would also be induced, thereby accelerating the exacerbation. Therefore, we recognized the need to develop a sensor that can track changes in MT-associated tau, named TCCB T2, which was made by taking advantage of the property that the N-terminus and C-terminus of MT-binding tau have an adjacent structure called “paperclip”.  We performed live imaging for 80 minutes by treating Nocodazole(Noc) and Paclitaxel(PTX) in TCCB T2 transfected MCF-7 cells. We confirmed that the FRET/ECFP emission ratio gradually decreased compared to the control. In contrast, our TCCB T1, which has been proven to detect conformational changes in hyperphosphorylated tau, did not show any change in FRET/ECFP emission ratio even after MT depolymerization. This suggests that we have developed two biosensors with completely distinct roles (TCCB T1, detecting conformational change caused by hyperphosphorylation in an early stage of tauopathy in the cell-based study; TCCB T2, detecting MT-collapse of neurons occurring during tauopathy).
Figure 6. hyperphosphorylation with Fsk showed changes only in the soluble region but did not show in the MT-associated region. To confirm this, TCCB T2 was transfected into MCF-7 cells and live imaging was performed for 160 minutes under the same conditions.
DOI: 10.17632/d9dphh55cj.1
title: Shutoff of host transcription triggers a toxin-antitoxin system to cleave phage RNA and abort infection (Guegler and Laub 2021)

description: Data contains the raw data/original gel images for all cell serial dilution spotting assays, phage spotting assays, gels, and Northern and Western blots shown in Guegler and Laub 2021:
- Figure 1C: toxI rescue of ToxN overexpression
- Figure 1G: T4 spotting on +toxIN, -toxIN, and +toxI-toxN(K55A) cells
- Figure 3J: protein pulse-labeling following T4 infection
- Figure 4B: Northern blots of toxI and Western blots of ToxN following T4 infection and rifampicin treatment
- Figure 4H: T4 spotting assays in +toxIN cells in the presence of exogenous expression of toxI from T4 promoters
- Figure 5G: Northern blot of toxI following T7 infection
- Figure 5H: Northern blots of groL following T7 and T4 infections
- Figure S1C: spotting of various phage on +toxIN, -toxIN, and +toxI-toxN(K55A) cells
- Figure S4A: spotting of T4 on +toxIN, -toxIN, and +toxI-toxN-His6 cells
- Figure S5H: spotting of P1_virulent on E. coli MG1655, E. coli MG1655 delta(mazEF), and E. coli MG1655 delta(10TA)
DOI: 10.17632/vpjnxx3t9m.1
title: Orchid mycorrhizal fungus against rice pathogens

description: Data refer to mycelial growth inhibition by En07 against rice pathogens, conidial germination and appressorium formation, leaf blast of rice plants treated by En07, and enzymatic activity by En07 on cell wall of rice pathogens and co-culture.
DOI: 10.17632/2pyfv3tjp9.1
title: RawData_NTA_EVs

description: Nanoparticle Tracking Analysis (NTA) data are obtained from EVs isolated from 120 human plasma samples, n=30 Alzheimer’s disease (AD), n=30 Lewy body dementia (LBD), n=30 sporadic frontotemporal dementia (FTD) patients and n=30 elderly subjects with normal cognitive function, as control group (CTRL). Moreover, a negative control was included in the analysis (ctrl_neg). Samples were analyzed with Nano-Sight NS300 Instrument (Malvern, Worchestershire, UK). For each sample, 5 video of 60 seconds duration were recorded and data were processed using NanoSight NTA Software 3.2 (Malvern, Worchestershire, UK). Correspondence_RawData table shows sample code, category as diagnostic group, age, sex and the corresponding raw file name. Raw data of each sample analyzed consists of .csv file generated by Nano-Sight NS300 Instrument. File contains information about EVs concentration (particles/ml, particles/frame), size (mean, mode, SD) and size distribution (D10, D50 and D90).
DOI: 10.5281/zenodo.6047984
title: PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions

description: Training, test datasets of the paper "PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions".
DOI: 10.5281/zenodo.6047983
title: PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions

description: Training, test datasets of the paper "PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions".
DOI: 10.5281/zenodo.545780
title: Supplementary Materials for "On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective"

description: Supplementary materials with all used benchmark scripts, plot scripts, benchmark results and PIConGPU example data for the submission to "The 1st International Workshop on Data Reduction for Big Scientific Data (DRBSD-1)" held in conjunction with ISC 2017 in Frankfurt, Germany.
description: This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 654220. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
description: {"references": ["Axel Huebl, Ren\u00e9 Widera, Felix Schmitt, Alexander Matthes, Norbert Podhorszki, Jong Youl Choi, Scott Klasky, and Michael Bussmann (2017). On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective, DOI:10.1007/978-3-319-67630-2_2"]}
DOI: 10.6084/m9.figshare.19158421.v8
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.19158421.v9
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.19158421.v10
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.19163384
title: simHC+

description: Assembly, binning and binning refining for simHC+ dataset
DOI: 10.6084/m9.figshare.19161674
title: Zymo

description: Assembly, binning, binning refining and gold standard for Zymo mock metagenome
DOI: 10.6084/m9.figshare.19161674.v2
title: Zymo

description: Assembly, binning, binning refining and gold standard for Zymo mock metagenome
DOI: 10.6084/m9.figshare.19161674.v1
title: Zymo

description: Assembly, binning, binning refining and gold standard for Zymo mock metagenome
DOI: 10.6084/m9.figshare.19161659
title: MBARC26

description: Assembly, binning, binning refining and gold standard for MBARC26 dataset
DOI: 10.6084/m9.figshare.19161659.v1
title: MBARC26

description: Assembly, binning, binning refining and gold standard for MBARC26 dataset
DOI: 10.6084/m9.figshare.19161656
title: magsim-MGE

description: Assembly, binning, binning results and gold standard
DOI: 10.6084/m9.figshare.19161656.v2
title: magsim-MGE

description: Assembly, binning, binning results and gold standard
DOI: 10.6084/m9.figshare.19161656.v1
title: magsim-MGE

description: Assembly, binning, binning results and gold standard
DOI: 10.6084/m9.figshare.19161647
title: BMock12

description: Assembly, binning, binning refining and gold standard for BMock12 dataset
DOI: 10.6084/m9.figshare.19161647.v1
title: BMock12

description: Assembly, binning, binning refining and gold standard for BMock12 dataset
DOI: 10.6084/m9.figshare.19158421.v11
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.5281/zenodo.5646574
title: Lakh Pianoroll Dataset

description: The Lakh Pianoroll Dataset (LPD) is a collection of 174,154 multitrack pianorolls derived from the Lakh MIDI Dataset (LMD). For more information, please visit our project homepage.
description: For more information, please visit our project website (https://salu133445.github.io/lakh-pianoroll-dataset/).
description: {"references": ["Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, and Yi-Hsuan Yang, \"MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment,\" in Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018."]}
DOI: 10.5281/zenodo.5646573
title: Lakh Pianoroll Dataset

description: The Lakh Pianoroll Dataset (LPD) is a collection of 174,154 multitrack pianorolls derived from the Lakh MIDI Dataset (LMD). For more information, please visit our project homepage.
description: For more information, please visit our project website (https://salu133445.github.io/lakh-pianoroll-dataset/).
description: {"references": ["Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, and Yi-Hsuan Yang, \"MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment,\" in Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018."]}
DOI: 10.5517/ccdc.csd.cc294r18
title: CCDC 2119719: Experimental Crystal Structure Determination

description: Related Article: Atsushi Ueda, Yui Makura, Sana Kakazu, Takuma Kato, Tomohiro Umeno, Kazuhiro Hirayama, Mitsunobu Doi, Makoto Oba, Masakazu Tanaka|2022|Org.Lett.|24|1049|doi:10.1021/acs.orglett.1c04256
DOI: 10.5517/ccdc.csd.cc29811p
title: CCDC 2122881: Experimental Crystal Structure Determination

description: Related Article: Si-Chao Ji, Tianxiang Zhao, Zhuangzhuang Wei, Lingyi Meng, Xiao-Dong Tao, Mingxue Yang, Xu-Lin Chen, Can-Zhong Lu|2022|Chem.Eng.Journal|435|134868|doi:10.1016/j.cej.2022.134868
DOI: 10.5517/ccdc.csd.cc2980yk
title: CCDC 2122878: Experimental Crystal Structure Determination

description: Related Article: Si-Chao Ji, Tianxiang Zhao, Zhuangzhuang Wei, Lingyi Meng, Xiao-Dong Tao, Mingxue Yang, Xu-Lin Chen, Can-Zhong Lu|2022|Chem.Eng.Journal|435|134868|doi:10.1016/j.cej.2022.134868
DOI: 10.5517/ccdc.csd.cc2931k1
title: CCDC 2118092: Experimental Crystal Structure Determination

description: Related Article: bholanath garai|2021|CSD Communication|||
DOI: 10.6084/m9.figshare.16863241
title: DST Scrum simulation survey data

description: This is the DST Scrum simulation survey data.
DOI: 10.6084/m9.figshare.16863241.v1
title: DST Scrum simulation survey data

description: This is the DST Scrum simulation survey data.
DOI: 10.6073/pasta/7ec8a89997863f2864b98e62b6535bde
title: Mangrove Forest Growth from the Shark River Slough, Everglades National Park (FCE), South Florida from January 1995 to Present

description: All mangrove trees having a diameter at breast high (DBH) greater than 2.5 cm were tagged in two 20 x 20 m plot in stations SRS4-6 and TS/Ph-8. Measurements in PLot Num1 began in 1995; measurements in Plot Num 2 began in 2001. Plot Num1 in TS/Ph-8 was established in 2001. DBH has been measured in the period 1995-2004. Mangrove species include Rhizophora mangle, Laguncularia racemosa, Avicennia germinans, Conacarpus erectus.
DOI: 10.6084/m9.figshare.18142718
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.18142718.v17
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.18142718.v16
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.19158421.v12
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.5281/zenodo.5951148
title: Wallops SuperDARN data in netCDF format (2021-Mar)

description: 2021-Mar Wallops SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.5951152
title: Wallops SuperDARN data in netCDF format (2021-Feb)

description: 2021-Feb Wallops SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.5951147
title: Wallops SuperDARN data in netCDF format (2021-Mar)

description: 2021-Mar Wallops SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.5951151
title: Wallops SuperDARN data in netCDF format (2021-Feb)

description: 2021-Feb Wallops SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.6084/m9.figshare.19161686
title: Kuruvilla-Mathew et al

description: EEG data files, younger and older adult groups.
DOI: 10.6084/m9.figshare.19161686.v1
title: Kuruvilla-Mathew et al

description: EEG data files, younger and older adult groups.
DOI: 10.5281/zenodo.6050245
title: Bach Violin Dataset

description: The Bach Violin Dataset is a collection of high-quality public recordings of Bach's sonatas and partitas for solo violin (BWV 1001–1006). The dataset consists of 6.5 hours of professional recordings from 17 violinists recorded in various recording setups. It also provides the reference scores and estimated alignments between the recordings and scores. For more information, please visit our project homepage.
description: {"references": ["Hao-Wen Dong, Cong Zhou, Taylor Berg-Kirkpatrick, and Julian McAuley, \"Deep Performer: Score-to-Audio Music Performance Synthesis,\" Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022."]}
DOI: 10.5281/zenodo.6050244
title: Bach Violin Dataset

description: The Bach Violin Dataset is a collection of high-quality public recordings of Bach's sonatas and partitas for solo violin (BWV 1001–1006). The dataset consists of 6.5 hours of professional recordings from 17 violinists recorded in various recording setups. It also provides the reference scores and estimated alignments between the recordings and scores. For more information, please visit our project homepage.
description: {"references": ["Hao-Wen Dong, Cong Zhou, Taylor Berg-Kirkpatrick, and Julian McAuley, \"Deep Performer: Score-to-Audio Music Performance Synthesis,\" Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022."]}
DOI: 10.5281/zenodo.6043896
title: Analytical data for Combining nickel and squaramide catalysis for the stereodivergent α-propargylation of oxindoles

description: NMR data in a mnova file format and HPLC traces for Combining nickel and squaramide catalysis for the stereodivergent α-propargylation of oxindoles. NMR data are available as .mnova files
DOI: 10.5281/zenodo.6043895
title: Analytical data for Combining nickel and squaramide catalysis for the stereodivergent α-propargylation of oxindoles

description: NMR data in a mnova file format and HPLC traces for Combining nickel and squaramide catalysis for the stereodivergent α-propargylation of oxindoles. NMR data are available as .mnova files
DOI: 10.48366/r165794
title: Comparison of different scholarly communication infrastructures

description: This comparisons highlights the functionalities of different scholarly communication infrastructures
DOI: 10.6084/m9.figshare.19158421.v13
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.15784/601520
title: EAGER: Refining glacial lake history in Taylor Valley, East Antarctica with alternative geochronometers: Infrared Stimulated Luminescence data

description: Location and metadata of samples collected from perched delta deposits along modern stream channels in lower Taylor Valley. Sample collection used equipment and followed procedures from the Desert Research Institute Luminescence Laboratory in Reno, NV.
DOI: 10.15784/601521
title: EAGER: Refining glacial lake history in Taylor Valley, East Antarctica with alternative geochronometers: in situ 14C data

description: Location and metadata of C-14 samples from Taylor Valley, East Antarctica
DOI: 10.6084/m9.figshare.19158421
title: gene-2

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.19158421.v15
title: gene-2

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.
DOI: 10.6084/m9.figshare.19158421.v14
title: gene

description: Transcriptomics was employed to analyze and compare gene expression levels of different groups. It showed that the expressions of genes (Cyp1a1, Noct, and TUBB6) related to liver injury were regulated by SBS.