cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25dv8q
title: CCDC 2008343: Experimental Crystal Structure Determination

description: Related Article: Jichuan Zhang, Yongan Feng, Yiyang Bo, Richard J. Staples, Jiaheng Zhang, Jean’ne M. Shreeve|2021|J.Am.Chem.Soc.|143|12665|doi:10.1021/jacs.1c05292
DOI: 10.5517/ccdc.csd.cc26t158
title: CCDC 2049849: Experimental Crystal Structure Determination

description: Related Article: Hong-Hao Zhang, Menghan Tang, Jia-Jia Zhao, Changhua Song, Shouyun Yu|2021|J.Am.Chem.Soc.|143|12836|doi:10.1021/jacs.1c06271
DOI: 10.5517/ccdc.csd.cc275k22
title: CCDC 2060913: Experimental Crystal Structure Determination

description: Related Article: Shu-Xi Jing, Ran Fu, Chun-Huan Li, Ting-Ting Zhou, Yan-Chun Liu, Yan Liu, Shi-Hong Luo, Xiao-Nian Li, Fang Zeng, Sheng-Hong Li|2021|J.Org.Chem.|86|11169|doi:10.1021/acs.joc.1c00374
DOI: 10.5517/ccdc.csd.cc277cyt
title: CCDC 2062676: Experimental Crystal Structure Determination

description: Related Article: Jichuan Zhang, Yongan Feng, Yiyang Bo, Richard J. Staples, Jiaheng Zhang, Jean’ne M. Shreeve|2021|J.Am.Chem.Soc.|143|12665|doi:10.1021/jacs.1c05292
DOI: 10.5517/ccdc.csd.cc27wc0j
title: CCDC 2081867: Experimental Crystal Structure Determination

description: Related Article: Rayhan G. Biswas, Sumit K. Ray, Rajshekhar A. Unhale, Vinod K. Singh|2021|Org.Lett.|23|6504|doi:10.1021/acs.orglett.1c02313
description: Related Article: Rayhan Gafur Biswas, Sumit K. Ray, Rajshekhar A. Unhale, Vinod K. Singh|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc284htr
title: CCDC 2089704: Experimental Crystal Structure Determination

description: Related Article: Sokratis T. Tsantis, Panagiota Danelli, Demetrios I. Tzimopoulos, Catherine P. Raptopoulou, Vassilis Psycharis, Spyros P. Perlepes|2021|Inorg.Chem.|60|11888|doi:10.1021/acs.inorgchem.1c01800
DOI: 10.5517/ccdc.csd.cc284hvs
title: CCDC 2089705: Experimental Crystal Structure Determination

description: Related Article: Sokratis T. Tsantis, Panagiota Danelli, Demetrios I. Tzimopoulos, Catherine P. Raptopoulou, Vassilis Psycharis, Spyros P. Perlepes|2021|Inorg.Chem.|60|11888|doi:10.1021/acs.inorgchem.1c01800
DOI: 10.15121/1148828
title: Hot Pot Contoured Temperature Gradient Map

description: Temperature gradient contours derived from Oski temperature gradient hole program and from earlier published information.
DOI: 10.6084/m9.figshare.16160265
title: SVE-visit-regression_data

description: Data used for the regression assessing the relationship between a pollinator's relative visit frequency and single visit effectiveness (for which r squared values were calculated) and associated data for all studies which reported paired visit frequency and effectiveness data.
DOI: 10.25386/genetics.14529318
title: Supplemental Material for Duerr et al., 2021

description: Supplemental File 1 contains flanking sequence information for <i>cha-1</i> mutations.Supplemental File 2 contains a list of 145 species used to determine amino acid conservation.Supplemental File 3 is an annotated protein sequence alignment of human and <i>C. elegans</i> choline acetyltransferase.Supplemental File 4 is a list of strains and alleles used in the submitted manuscript.<br>
DOI: 10.25386/genetics.14529318.v2
title: Supplemental Material for Duerr et al., 2021

description: Supplemental File 1 contains flanking sequence information for <i>cha-1</i> mutations.Supplemental File 2 contains a list of 145 species used to determine amino acid conservation.Supplemental File 3 is an annotated protein sequence alignment of human and <i>C. elegans</i> choline acetyltransferase.Supplemental File 4 is a list of strains and alleles used in the submitted manuscript.<br>
DOI: 10.25386/genetics.14529318.v1
title: Supplemental Material for Duerr et al., 2021

description: Supplemental File 1 contains flanking sequence information for <i>cha-1</i> mutations.Supplemental File 2 contains a list of 145 species used to determine amino acid conservation.Supplemental File 3 is an annotated protein sequence alignment of human and <i>C. elegans</i> choline acetyltransferase.Supplemental File 4 is a list of strains and alleles used in the submitted manuscript.<br>
DOI: 10.6084/m9.figshare.16166931
title: Wind speed

description: Gridded wind speed (at 2 meters) dataset at 0.01° for Perú. Mean value during 1981-2016.
DOI: 10.6084/m9.figshare.13477077
title: Feng_CheCastaldo_2021_S1Data.zip

description: eBird data from the eBird Basic Dataset (May 2019 Update) and 50-stop data from the North American Breeding Bird Survey Dataset (BBS, version 2018.0) filtered to the US state of Massachusetts during the breeding seasons of 2005-2018. R-script covers the modeling methods and comparative analysis of four indices of annual relative abundance derived from these BBS and eBird datasets.
DOI: 10.6084/m9.figshare.13477077.v4
title: Feng_CheCastaldo_2021_S1Data.zip

description: eBird data from the eBird Basic Dataset (May 2019 Update) and 50-stop data from the North American Breeding Bird Survey Dataset (BBS, version 2018.0) filtered to the US state of Massachusetts during the breeding seasons of 2005-2018. R-script covers the modeling methods and comparative analysis of four indices of annual relative abundance derived from these BBS and eBird datasets.
DOI: 10.5281/zenodo.5230160
title: Forbesichthys agassizzi UTTC_649 SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5230159
title: Forbesichthys agassizzi UTTC_649 SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.15144285.v1
title: Southern Gorgonum Chaos - ArcGis.zip

description: This is the ArcGis project with all datasets on which the mapping in the paper "Geological history of southeastern Gorgonum Chaos" is based. Because of the size of the HiRISE data used, they are not included. However, their IDs are listed in the article and can be downloaded from www.uahirise.org.
DOI: 10.6084/m9.figshare.15144285
title: Southern Gorgonum Chaos - ArcGis.zip

description: This is the ArcGis project with all datasets on which the mapping in the paper "Geological history of southeastern Gorgonum Chaos" is based. Because of the size of the HiRISE data used, they are not included. However, their IDs are listed in the article and can be downloaded from www.uahirise.org.
DOI: 10.5281/zenodo.5230308
title: LA-ICP-MS U-Pb and Lu-Hf data for Bighorn Basin bentonite zircon

description: This table contains the U-Pb composition, calculated ages, and Lu-Hf composition for 697 individual zircon analyses from a suite of bentonite deposits collected from the Bighorn Basin, Wyoming, and southwestern South Dakota. All data was acquired using LA-ICP-Ms at the Laserchron Center at the University of Arizona.
DOI: 10.5281/zenodo.5114313
title: LA-ICP-MS U-Pb and Lu-Hf data for Bighorn Basin bentonite zircon

description: This table contains the U-Pb composition, calculated ages, and Lu-Hf composition for 697 individual zircon analyses from a suite of bentonite deposits collected from the Bighorn Basin, Wyoming, and southwestern South Dakota. All data was acquired using LA-ICP-Ms at the Laserchron Center at the University of Arizona.
DOI: 10.5281/zenodo.5216959
title: Movement data from a Malayan krait (Bungarus candidus) tracked in the Sakaerat Biosphere Reserve, Nakhon Ratchasima province, Thailand

description: Movement data gained through radio-telemetry of a single adult male Malayan krait (<em>Bungarus candidus</em>) among a protected forest of the Sakaerat Biosphere Reserve in Nakhon Ratchasima province, Thailand for a period of 103 days (with 90 location fixes/datapoints). BUCA40_movement_data.csv file column headings: track_ID: number corresponding to the location check datapoint animal_ID: <em>B. candidus</em> identifier number from the Sakaerat tracking project datetime: Date and time when the snake was located (mm/dd/yyyy hh:mm) easting: UTM easting (UTM Zone 47N; Datum WGS84) northing: UTM northing (UTM Zone 47N; Datum WGS84) utm_zone: Universal Transverse Mercator zone (47N World Geodetic System 84) GPS_accuracy: GPS location accuracy in meters (m) behavior: The animal’s behavior observed during the location check (e.g. sheltering, foraging, moving, or feeding) shelter_type: Identified selected shelter type habitat_type: Land-use type where the snake was located
description: This project was supported by the Thailand Institute of Science and Technological Research (TISTR), The National Research Council of Thailand (NRCT), the Sakaerat Environmental Research Station, and Suranaree University of Technology. We had ethical approval from the Suranaree University of Technology Ethics Committee, and all work was permitted by the National Research Council of Thailand (0002/27; 0402/4367).
DOI: 10.6084/m9.figshare.22601644
title: Additional file 3 of The prediction of in-hospital mortality in chronic kidney disease patients with coronary artery disease using machine learning models

description: Additional file 3: Table S1 Baseline characteristics of CKD patients with CAD in the external validation set (eICU-CRD).
DOI: 10.6084/m9.figshare.10022309
title: MOESM1 of Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods

description: Additional file 1. Table S1. simulated 50 base PE read fusion predictions; Table S2. simulated 101 base PE read predictions; Table S3. known experimentally validated fusions; Table S4. fusion predictions on cancer cell lines; Table S5. Centrifuge-based viral and microbial source predictions for Trinity-assembled transcripts; Table S6. Viral assignments of Trinity-UC assembled transcripts via blastn; Table S7. Fusion prediction software commands; Table S8. sources of RNA-seq data for modeling simulated RNA-seq; Table S9. Cancer cell lines targeted for fusion discovery.
DOI: 10.6084/m9.figshare.10022309.v1
title: MOESM1 of Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods

description: Additional file 1. Table S1. simulated 50 base PE read fusion predictions; Table S2. simulated 101 base PE read predictions; Table S3. known experimentally validated fusions; Table S4. fusion predictions on cancer cell lines; Table S5. Centrifuge-based viral and microbial source predictions for Trinity-assembled transcripts; Table S6. Viral assignments of Trinity-UC assembled transcripts via blastn; Table S7. Fusion prediction software commands; Table S8. sources of RNA-seq data for modeling simulated RNA-seq; Table S9. Cancer cell lines targeted for fusion discovery.
DOI: 10.6084/m9.figshare.25162031.v1
title: Supplementary Material for: Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) binds with spike protein and inhibits the entry of SARS-CoV-2 into host cells

description: Introduction: Coronavirus disease 2019 (COVID-19) caused by coronavirus-2 (SARS-CoV-2) has emerged as an aggressive viral pandemic. Health care providers confront a challenging task for rapid development of effective strategies to combat this and its long term after effects. Virus entry into host cells involves interaction between receptor-binding domain (RBD) of Spike (S) protein S1 subunit with angiotensin converting enzyme (ACE) present on host cells. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a moonlighting enzyme involved in cellular glycolytic energy metabolism and micronutrient homeostasis. It is deployed in various cellular compartments and the extra cellular milieu. Though it is known to moonlight as a component of mammalian innate immune defense machinery, till date its role in viral restriction remains unknown.
 Method: Recombinant S protein, the receptor binding domain (RBD) and human GAPDH protein were used for solid phase binding assays and Biolayer interferometry (BLI). Pseudo virus particles expressing four different strain variants of S protein all harboring ZsGreen gene as marker of infection were used for Flow cytometry-based infectivity assays.
 Results: Pseudo-virus entry into target cells in culture was significantly inhibited by addition of human GAPDH into the extracellular medium. Binding assays demonstrated that human GAPDH binds to S protein and RBD domain of SARS-CoV-2 with nano molar affinity.
Conclusions: Our investigations suggest that this interaction of GAPDH interferes in the viral docking with hACE2 receptors, thereby affecting viral ingress into mammalian cells.
DOI: 10.6084/m9.figshare.24420916.v1
title: Development of a Web-Based Algorithm for Understanding the Intraocular Lens-Based Surgery in Stable and Progressing Keratoconus for Non-Specialist Ophthalmologists

description: To propose an algorithm to facilitate lens-based surgery in keratoconus. A literature review was performed to prepare a software algorithm based on cone location, stability, best spectacle-corrected distance visual acuity (BSCVA) level and whether there is a clear or cataractous lens. The software usability was assessed through a 10-question questionnaire and two hypothetical keratoconus case histories (moderately simple and moderately complex) given to 15 trainees. The usability questionnaires were graded on a Likert scale (1 = strongly disagree to 5 = strongly agree) and two case histories (1 = very difficult to 7 = very easy). The algorithm can be found at https://www.sussexeyelaserclinic.co.uk/keratoconus/. Thirteen trainees completed the questionnaire. 91.9% would frequently use it; for 100%, it was easy to use independently without technical support; for 63.7%, it was strongly integrated; for 100%, it was consistent; 100% thought that most people would learn to use it quickly, 91.9% found the system not cumbersome to use, felt very confident to use it and need not learn a lot to use it. The first case was found easy by 63.7% and the second by 45%. We present an algorithm as a guide for lens-based surgery in stable and progressing keratoconus, which is classified based on cone location. This algorithm will help trainee and “non-specialist” ophthalmic surgeons understand the pre-operative planning for the surgery and referral to the “specialist” corneal surgeon, considering factors such as progression, BSCVA, keratometry, topography and apex location of the cone in keratoconus patients.
DOI: 10.6084/m9.figshare.24168312
title: Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes

description: The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD). With The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we used Cox regression analysis to construct a prognostic model, and verified independence of riskscore. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves. Immune analysis was performed by using ssGSEA. Additionally, immune checkpoint blockade therapy was assessed by using immunophenoscore, Tumor Immune Dysfunction and Exclusion score. Based on the cMAP database, effective small molecule compounds were predicted. A prognostic model was established based on 8 MHC-I-related genes, and the predictive capacity of the model was accurate. Immune analysis results revealed that patients classified as high-risk had lower levels of immune cell infiltration and impaired immune function. The low-risk group possessed a better response to immune checkpoint blockade therapy. Theobromine and pravastatin were identified as having great potential in improving the prognosis of LUAD. Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response.
DOI: 10.6084/m9.figshare.24168312.v2
title: Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes

description: The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD). With The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we used Cox regression analysis to construct a prognostic model, and verified independence of riskscore. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves. Immune analysis was performed by using ssGSEA. Additionally, immune checkpoint blockade therapy was assessed by using immunophenoscore, Tumor Immune Dysfunction and Exclusion score. Based on the cMAP database, effective small molecule compounds were predicted. A prognostic model was established based on 8 MHC-I-related genes, and the predictive capacity of the model was accurate. Immune analysis results revealed that patients classified as high-risk had lower levels of immune cell infiltration and impaired immune function. The low-risk group possessed a better response to immune checkpoint blockade therapy. Theobromine and pravastatin were identified as having great potential in improving the prognosis of LUAD. Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response.
DOI: 10.6084/m9.figshare.24495337
title: Randomized Controlled Trial of Patching versus Dichoptic Stimulation Using Virtual Reality for Amblyopia Therapy

description: <b>Purpose:</b> To compare the outcomes of patching to dichoptic stimulation using virtual reality (VR) in moderate and severe amblyopia. <b>Methods:</b> This study was conducted on 86 subjects with unilateral anisometropic and mixed amblyopia. The subjects were randomized to the VR or patching group. The VR group received treatment using the Vivid Vision software (Vivid Vision Inc., San Francisco, USA) with each subject receiving weekly 2 h-sessions for 10 weeks. The patching group was prescribed patching for 10 weeks. Best-corrected visual acuity (BCVA) was measured using a single crowded letter in an ETDRS chart before, after 10 weeks of treatment, and after another 10 weeks of cessation of treatment. Near stereoacuity was measured using the TNO test. <b>Results:</b> Forty-two patients were randomized to the patching group and 44 to the VR group. The median age of the subjects was 12.0 (range 6.0 to 37.0) years. In the VR group, mean amblyopic eye BCVA showed statistically significant improvement by 0.89 line (95% confidence interval {CI}, 0.73 to 1.35 lines; <i>p</i> &lt; 0.001) after 10 weeks of therapy, and after another 10 weeks of follow-up by 1.32 lines from baseline (95% CI, 1.15 to 1.7 lines; <i>p</i> &lt; 0.001). Regarding the patching group, mean BCVA showed statistically significant improvement after 10 weeks by 1.38 lines (95% CI, 0.82 to 1.8 lines; <i>p</i> &lt; 0.001), and after another 10 weeks by 1 line from baseline (95% CI, 0.06–0.147; 0.6 to 1.47 lines; <i>p</i> &lt; 0.001). There was no significant difference between both groups at any time-point (<i>p</i> values &gt;0.05). No serious adverse events were noted. Adults and severe amblyopes in the VR group showed more significant VA improvement than their counterparts in the patching group. <b>Conclusions:</b> Amblyopes treated using VR dichoptic treatment demonstrated statistically significant VA improvement after 10 and 20 weeks of follow-up that is comparable to patching.
DOI: 10.6084/m9.figshare.24420916
title: Development of a Web-Based Algorithm for Understanding the Intraocular Lens-Based Surgery in Stable and Progressing Keratoconus for Non-Specialist Ophthalmologists

description: To propose an algorithm to facilitate lens-based surgery in keratoconus. A literature review was performed to prepare a software algorithm based on cone location, stability, best spectacle-corrected distance visual acuity (BSCVA) level and whether there is a clear or cataractous lens. The software usability was assessed through a 10-question questionnaire and two hypothetical keratoconus case histories (moderately simple and moderately complex) given to 15 trainees. The usability questionnaires were graded on a Likert scale (1 = strongly disagree to 5 = strongly agree) and two case histories (1 = very difficult to 7 = very easy). The algorithm can be found at https://www.sussexeyelaserclinic.co.uk/keratoconus/. Thirteen trainees completed the questionnaire. 91.9% would frequently use it; for 100%, it was easy to use independently without technical support; for 63.7%, it was strongly integrated; for 100%, it was consistent; 100% thought that most people would learn to use it quickly, 91.9% found the system not cumbersome to use, felt very confident to use it and need not learn a lot to use it. The first case was found easy by 63.7% and the second by 45%. We present an algorithm as a guide for lens-based surgery in stable and progressing keratoconus, which is classified based on cone location. This algorithm will help trainee and “non-specialist” ophthalmic surgeons understand the pre-operative planning for the surgery and referral to the “specialist” corneal surgeon, considering factors such as progression, BSCVA, keratometry, topography and apex location of the cone in keratoconus patients.
DOI: 10.6084/m9.figshare.22601777.v1
title: Additional file 7 of Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

description: Additional file 7: Dataset 5. Genes dynamically expressed during CD14+ classical monocyte-to-CD14+ intermediate monocyte differentiation, related to Fig. S3M and S3N, in which the top 250 genes based on wald statistics were differentiation driver genes.
DOI: 10.6084/m9.figshare.22601783.v1
title: Additional file 9 of Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

description: Additional file 9: Dataset 7. Genes dynamically expressed during AT2-to-AT1 differentiation, related to Fig. S4D and S4G, in which the top 500 genes based on wald statistics were differentiation driver genes and those pro-inflammatory and/or pro-apoptotic ones were highlighted in red.
DOI: 10.6084/m9.figshare.22601786.v1
title: Additional file 10 of Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

description: Additional file 10: Dataset 8. Lists of markers in 2 sub-clusters of club cells, namely autoimmune-prone sub-cluster of club cells and mix sub-cluster of club cells, related to Fig. 5D and Fig. S5M. The resulting sub-cluster markers were identified by the seurat FindAllMarkers, including the p-value, the average log2(fold change) of the gene in the sub-cluster compared to all other sub-clusters, the percent of cells expressing the gene in the sub-cluster (pct.1), the percent of cells expressing the gene in all other sub-clusters (pct.2), and the adjusted p-value.
DOI: 10.6084/m9.figshare.22601768
title: Additional file 4 of Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

description: Additional file 4: Dataset 2. Results of differential gene expression analysis within each cell type under the conditions of aging, COPD, and smoking, respectively.
DOI: 10.6084/m9.figshare.22601759.v1
title: Additional file 1 of Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

description: Additional file 1. Supplementary Methods.
DOI: 10.6084/m9.figshare.22601777
title: Additional file 7 of Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

description: Additional file 7: Dataset 5. Genes dynamically expressed during CD14+ classical monocyte-to-CD14+ intermediate monocyte differentiation, related to Fig. S3M and S3N, in which the top 250 genes based on wald statistics were differentiation driver genes.