cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12464231.v1
title: Supplementary Material for: Adult Ocular Myasthenia Gravis Conversion: A Single-Center Retrospective Analysis in China

description: <b><i>Introduction:</i></b> The conversion rate from ocular myasthenia gravis (OMG) to generalized myasthenia gravis (GMG) was reported to be much lower in Asian population since most OMG patients are juvenile onset. However, the exact conversion rate for adult-onset OMG to GMG is still unknown. <b><i>Objective:</i></b> We aimed to delineate the conversion rate and risk factors for adult patients with ocular onset to GMG. <b><i>Methods:</i></b> Adult myasthenia gravis (MG) patients with ocular onset (age &gt; 18 years) were retrospectively reviewed. Patients with confined ocular involvement lasting more than 2 years (pure OMG group) and those who converted into GMG (converted OMG group) were enrolled for subsequent analysis. We then analyzed 5 clinical variables, including onset age, sex, onset symptoms, anti-acetylcholine receptor antibody (AChR Ab), and thymus CT. Survival analysis was applied to all enrolled patients to explore risk factors associated with conversion. <b><i>Results:</i></b> In a total number of 249 ocular-onset MG patients initially enrolled, we excluded 122 patients with OMG lasting less than 2 years. The remaining 127 patients were enrolled, including 106 converted OMG and 21 pure OMG patients. Converted OMG patients had an older onset age (threshold: 43 years) and higher anti-AChR Ab titer (threshold: 6.13 nmol/L). The estimated conversion rate was 70.64%. Moreover, 67% of conversion occurred within 2 years after onset. Cox regression of survival analysis revealed that higher anti-AChR Ab titer and bilateral ptosis were associated with a higher conversion rate. <b><i>Conclusions:</i></b> The conversion of adult OMG was associated with anti-AChR Ab titer, onset age, and bilateral ptosis. The estimated conversion rate of Chinese adult OMG patients was 70%.
DOI: 10.6084/m9.figshare.12464174
title: Supplementary tables

description: Supplementary tables
DOI: 10.6084/m9.figshare.12463955
title: Supplementary Material for: Characteristics of Children with Acute Rheumatic Carditis from a High-Incidence Region: Importance of Unexplained Worsening of Functional Class

description: <b><i>Background:</i></b> Acute rheumatic fever (ARF) and acute rheumatic carditis (ARC) continue to be a major public health problem in developing countries. <b><i>Objective:</i></b> To study the characteristics of children with ARC being treated at a tertiary centre. <b><i>Methods and Results:</i></b> We studied 126 children (mean age 10.4 ± 2.3 years, range 5–15 years, 60% males) diagnosed with ARC by treating cardiologists. Most had lower socio-economic status. Fifty of 126 (40%) presented with a first episode of ARC. Joint symptoms were present in 29% and fever in 25%. Only 2.4% had subcutaneous nodules and none had erythema marginatum or chorea. Fifty-one percent presented in NYHA class II and 29% in NYHA class III or IV. Tachycardia and heart failure were present in 53% and 21%, respectively. Recent worsening of NYHA class (dyspnoea) was the commonest feature (48%). Laboratory investigations showed raised antistreptolysin O titres (&gt;333 units) in only 36.7% of patients. Raised C-reactive protein (CRP) was present in 70%, while raised erythrocyte sedimentation rate was found in only 37% of patients. On the basis of above findings, the modified Jones criteria (2015) for the diagnosis of ARF were satisfied only in 46% of children. Echocardiography showed mitral valve thickening in 77% and small nodules on the tip of the leaflets in 43% (27 and 8%, respectively for aortic valve). Left ventricular ejection fraction was &lt;50% in only 3 patients. The dominant valve lesion was mitral regurgitation (MR) (present in 95% of patients; severe in 78%, moderate in 15%), while aortic regurgitation was present in 44% (severe in 14%). <b><i>Conclusions:</i></b> The criteria are often not satisfied by patients being treated for ARC. Recent unexplained worsening of dyspnoea, young age, significant MR, echocardiographic nodules, and elevated CRP are important indicators.
DOI: 10.6084/m9.figshare.12463964
title: OMVs- Dietzia.xlsx

description: Protein profiles of outer membrane vesicles from Dietzia sp. DQ12-45-1b, from iron limited and iron rich conditons.
DOI: 10.6084/m9.figshare.12463985
title: Supplementary Material for: Age-Related Differences in the Uncanny Valley Effect

description: <b><i>Background:</i></b> Due to declining birthrates and an increasing aging population, shortage of the caregiving labor force has become a global issue. Among various efforts toward the solution, introducing robotic products for assistance could provide an effective way to help older adults in their daily lives. As previous studies have indicated that older adults’ acceptance of robots is lower than that of younger adults, enhancing older adults’ acceptance of robots is imperative. Because older adults’ first impressions based on a robot’s appearance might affect their acceptance of the robot, we investigated the uncanny valley effect (UVE) here. The UVE refers to the phenomenon that people rate robots more positively as robots become more humanlike, but only up to a certain point; as robots approach a near-perfect similarity to human appearance, likeability drops and forms the uncanny valley. Nevertheless, evidence for the UVE came mainly from younger adults. <b><i>Objective:</i></b> The present study aimed to examine whether the UVE varies across different age groups and whether a robot’s appearance would affect participants’ acceptance of the robot’s service or companionship. <b><i>Methods:</i></b> An online questionnaire study was conducted with 255 participants, including younger (<i>n</i> = 77, age 18–39 years), middle-aged (<i>n</i> = 87, age 40–59 years), and older (<i>n</i> = 91, age 60–87 years) adults. Participants were asked to view each picture in a set selected from a total of 83 robot pictures and evaluate their impressions of each robot and the intention of use regarding robot function as a service provider or a companion. <b><i>Results:</i></b> The UVE was found in younger and middle-aged adults; however, older adults did not show the UVE. Older adults preferred humanlike over non-humanlike robots, regardless of robot function. <b><i>Conclusion:</i></b> The design of assistive robots should take the UVE into consideration by customizing robot appearance based on the age group of the intended user.
DOI: 10.6084/m9.figshare.12464174.v2
title: Supplementary tables

description: Supplementary tables
DOI: 10.6084/m9.figshare.12463964.v1
title: OMVs- Dietzia.xlsx

description: Protein profiles of outer membrane vesicles from Dietzia sp. DQ12-45-1b, from iron limited and iron rich conditons.
DOI: 10.6084/m9.figshare.12464174.v1
title: Supplementary tables

description: Supplementary tables
DOI: 10.6084/m9.figshare.12463874
title: Expression of vitamin D 1α-hydroxylase in human gingival fibroblasts in vivo

description: The raw data of the manuscirpt with the title "Expression of vitamin D 1α-hydroxylase in human gingival fibroblasts in vivo". All the files can be used with SPSS.
DOI: 10.6084/m9.figshare.12463934
title: Supplementary_Tables.pdf

description: Supplement tables of the research article entitled "Difference in mortality according to metformin use in diabetic patients with metabolic syndrome with or without cancer".
DOI: 10.6084/m9.figshare.12463559
title: Supplemental_File_3_Primers.xlsx

description: Primer sequences for cloning and qRT-PCR of Bremia lactucae WY effectors.
DOI: 10.6084/m9.figshare.12463874.v1
title: Expression of vitamin D 1α-hydroxylase in human gingival fibroblasts in vivo

description: The raw data of the manuscirpt with the title "Expression of vitamin D 1α-hydroxylase in human gingival fibroblasts in vivo". All the files can be used with SPSS.
DOI: 10.6084/m9.figshare.12463934.v1
title: Supplementary_Tables.pdf

description: Supplement tables of the research article entitled "Difference in mortality according to metformin use in diabetic patients with metabolic syndrome with or without cancer".
DOI: 10.6084/m9.figshare.12463529
title: Tables for Enormous lithium isotopic variations of abyssal peridotite

description: This is a full dataset of the submitted manuscript 'Enormous lithium isotopic variations of abyssal peridotite reveal fast cooling and melt/fluid-rock interactions'
DOI: 10.6084/m9.figshare.12463559.v1
title: Supplemental_File_3_Primers.xlsx

description: Primer sequences for cloning and qRT-PCR of Bremia lactucae WY effectors.
DOI: 10.6084/m9.figshare.12463331
title: Supplemental_File_1_Bremia_WY_Sequences.xlsx

description: Description and sequences for the 59 WY domain containing proteins in the Bremia lactucae genome.
DOI: 10.6084/m9.figshare.12463415
title: PTNM-3

description: replication
DOI: 10.6084/m9.figshare.12463526
title: Supplemental_File_2_Lettuce_Genotypes.xlsx

description: Lettuce accessions tested for recognition of 21 Bremia lactucae WY effectors
DOI: 10.6084/m9.figshare.12463529.v1
title: Tables for Enormous lithium isotopic variations of abyssal peridotite

description: This is a full dataset of the submitted manuscript 'Enormous lithium isotopic variations of abyssal peridotite reveal fast cooling and melt/fluid-rock interactions'
DOI: 10.6084/m9.figshare.12463415.v1
title: PTNM-3

description: replication
DOI: 10.6084/m9.figshare.12463331.v1
title: Supplemental_File_1_Bremia_WY_Sequences.xlsx

description: Description and sequences for the 59 WY domain containing proteins in the Bremia lactucae genome.
DOI: 10.6084/m9.figshare.12463526.v1
title: Supplemental_File_2_Lettuce_Genotypes.xlsx

description: Lettuce accessions tested for recognition of 21 Bremia lactucae WY effectors
DOI: 10.6084/m9.figshare.12463127
title: Additional file 4 of Genomic analysis of Escherichia coli strains isolated from diseased chicken in the Czech Republic

description: Additional file 4: Table 4. Statistics.
DOI: 10.6084/m9.figshare.12463127.v1
title: Additional file 4 of Genomic analysis of Escherichia coli strains isolated from diseased chicken in the Czech Republic

description: Additional file 4: Table 4. Statistics.
DOI: 10.6084/m9.figshare.12463115
title: Additional file 2 of Genomic analysis of Escherichia coli strains isolated from diseased chicken in the Czech Republic

description: Additional file 2: Table 2. Overview of virulence-associated genes detected by whole-genome sequencing. Table 4. The origin of isolates.
DOI: 10.6084/m9.figshare.12463115.v1
title: Additional file 2 of Genomic analysis of Escherichia coli strains isolated from diseased chicken in the Czech Republic

description: Additional file 2: Table 2. Overview of virulence-associated genes detected by whole-genome sequencing. Table 4. The origin of isolates.
DOI: 10.6084/m9.figshare.12463058
title: Additional file 1 of Neuroprotective effect of paricalcitol in a rat model of transient global cerebral ischemia

description: Additional file 1. Supplemental table. Rat’s daily status during follow-up
DOI: 10.6084/m9.figshare.12463058.v1
title: Additional file 1 of Neuroprotective effect of paricalcitol in a rat model of transient global cerebral ischemia

description: Additional file 1. Supplemental table. Rat’s daily status during follow-up
DOI: 10.6084/m9.figshare.12463031
title: Additional file 6 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 6: Table S4.Aedes aegypti Aag-2 cell proteins with modulated abundance over the different infection time points and classification by GO terms for cellular component and biological process, obtained using the software Blast2Go corresponding to Fig. 5.
DOI: 10.6084/m9.figshare.12463025
title: Additional file 5 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 5: Table S3.Aedes aegypti Aag-2 cell and Mayaro virus proteins identified over the different infection time points.
DOI: 10.6084/m9.figshare.12463031.v1
title: Additional file 6 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 6: Table S4.Aedes aegypti Aag-2 cell proteins with modulated abundance over the different infection time points and classification by GO terms for cellular component and biological process, obtained using the software Blast2Go corresponding to Fig. 5.
DOI: 10.6084/m9.figshare.12463019
title: Additional file 4 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 4: Table S2. All peptides from the three different infection time points (0 as control, 12 hpi and 48 hpi), providing protein identification. Parameters used: FDR criterion of 1% and at least two unique peptides.
DOI: 10.6084/m9.figshare.12463025.v1
title: Additional file 5 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 5: Table S3.Aedes aegypti Aag-2 cell and Mayaro virus proteins identified over the different infection time points.
DOI: 10.6084/m9.figshare.12463007
title: Additional file 2 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 2: Table S1. Protein accession numbers of the 4 clusters identified through the VSClust algorithm corresponding to Fig. 3a.
DOI: 10.6084/m9.figshare.12463019.v1
title: Additional file 4 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 4: Table S2. All peptides from the three different infection time points (0 as control, 12 hpi and 48 hpi), providing protein identification. Parameters used: FDR criterion of 1% and at least two unique peptides.
DOI: 10.6084/m9.figshare.12463007.v1
title: Additional file 2 of Dynamic proteomic analysis of Aedes aegypti Aag-2 cells infected with Mayaro virus

description: Additional file 2: Table S1. Protein accession numbers of the 4 clusters identified through the VSClust algorithm corresponding to Fig. 3a.
DOI: 10.6084/m9.figshare.12462944
title: Additional file 9 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 9: Table S9. Normalized data used to test the neural network machine learning classifier.
DOI: 10.6084/m9.figshare.12462950
title: Additional file 1 of A comprehensive custom panel evaluation for routine hereditary cancer testing: improving the yield of germline mutation detection

description: Additional file 1.Table S1. CADD score of the different VUS identified in the genetic analysis.
DOI: 10.6084/m9.figshare.12462938
title: Additional file 7 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 7: Table S7. Unparsed HMM table output from VOG annotations used to generate VOG v-scores.
DOI: 10.6084/m9.figshare.12462944.v1
title: Additional file 9 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 9: Table S9. Normalized data used to test the neural network machine learning classifier.
DOI: 10.6084/m9.figshare.12462950.v1
title: Additional file 1 of A comprehensive custom panel evaluation for routine hereditary cancer testing: improving the yield of germline mutation detection

description: Additional file 1.Table S1. CADD score of the different VUS identified in the genetic analysis.
DOI: 10.6084/m9.figshare.12462935
title: Additional file 6 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 6: Table S6. Unparsed HMM table output from Pfam annotations used to generate Pfam v-scores.
DOI: 10.6084/m9.figshare.12462938.v1
title: Additional file 7 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 7: Table S7. Unparsed HMM table output from VOG annotations used to generate VOG v-scores.
DOI: 10.6084/m9.figshare.12462941
title: Additional file 8 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 8: Table S8. Normalized data used to train the neural network machine learning classifier.
DOI: 10.6084/m9.figshare.12462932
title: Additional file 5 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 5: Table S5. Unparsed HMM table output from KEGG annotations used to generate KEGG v-scores.
DOI: 10.6084/m9.figshare.12462941.v1
title: Additional file 8 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 8: Table S8. Normalized data used to train the neural network machine learning classifier.
DOI: 10.6084/m9.figshare.12462926
title: Additional file 4 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 4: Table S4. List of all KEGG, Pfam and VOG annotation names and associated v-scores (if greater than zero).
DOI: 10.6084/m9.figshare.12462932.v1
title: Additional file 5 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 5: Table S5. Unparsed HMM table output from KEGG annotations used to generate KEGG v-scores.
DOI: 10.6084/m9.figshare.12462935.v1
title: Additional file 6 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 6: Table S6. Unparsed HMM table output from Pfam annotations used to generate Pfam v-scores.
DOI: 10.6084/m9.figshare.12462917
title: Additional file 2 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 2: Table S2. Number and sizes of sequence fragments used to train and test VIBRANT for viruses, plasmids, and bacteria and archaea.
DOI: 10.6084/m9.figshare.12462923
title: Additional file 3 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 3: Table S3. List of all HMM names used by VIBRANT.
DOI: 10.6084/m9.figshare.12462926.v1
title: Additional file 4 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 4: Table S4. List of all KEGG, Pfam and VOG annotation names and associated v-scores (if greater than zero).
DOI: 10.6084/m9.figshare.12462911
title: Additional file 20 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 20: Table S19. List of datasets used from He et al., Ijaz et al. and Gevers et al.
DOI: 10.6084/m9.figshare.12462923.v1
title: Additional file 3 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 3: Table S3. List of all HMM names used by VIBRANT.
DOI: 10.6084/m9.figshare.12462911.v1
title: Additional file 20 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 20: Table S19. List of datasets used from He et al., Ijaz et al. and Gevers et al.
DOI: 10.6084/m9.figshare.12462914
title: Additional file 21 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 21: Table S20. VIBRANT runtimes and resource requirements for datasets of various sizes and compositions.
DOI: 10.6084/m9.figshare.12462917.v1
title: Additional file 2 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 2: Table S2. Number and sizes of sequence fragments used to train and test VIBRANT for viruses, plasmids, and bacteria and archaea.
DOI: 10.6084/m9.figshare.12462905
title: Additional file 1 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 1: Table S1. List of NCBI accession numbers for bacterial and archaeal genomes, plasmids, and viral genomes used in this study.
DOI: 10.6084/m9.figshare.12462899
title: Additional file 18 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 18: Table S17. Validation of the greater abundance of viral DAGs in individuals with Crohn’s Disease compared to healthy individuals.
DOI: 10.6084/m9.figshare.12462902
title: Additional file 19 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 19: Table S18. Description of set cutoffs implemented before neural network machine learning analysis for KEGG and Pfam annotations.
DOI: 10.6084/m9.figshare.12462905.v1
title: Additional file 1 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 1: Table S1. List of NCBI accession numbers for bacterial and archaeal genomes, plasmids, and viral genomes used in this study.
DOI: 10.6084/m9.figshare.12462893
title: Additional file 17 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 17: Table S16. Number of Caudovirales genomes and genomic fragments identified per quality estimation category, exact rules used to estimate genome quality and the interpretation of quality estimations.
DOI: 10.6084/m9.figshare.12462899.v1
title: Additional file 18 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 18: Table S17. Validation of the greater abundance of viral DAGs in individuals with Crohn’s Disease compared to healthy individuals.
DOI: 10.6084/m9.figshare.12462902.v1
title: Additional file 19 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 19: Table S18. Description of set cutoffs implemented before neural network machine learning analysis for KEGG and Pfam annotations.
DOI: 10.6084/m9.figshare.12462914.v1
title: Additional file 21 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 21: Table S20. VIBRANT runtimes and resource requirements for datasets of various sizes and compositions.
DOI: 10.6084/m9.figshare.12462884
title: Additional file 15 of VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

description: Additional File 15: Table S15. Complete VIBRANT-derived annotations of validated viral scaffolds that encode putative DAGs, respective of Table 2.