cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19135841.v1
title: Additional file 10 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 10: Table S9.106 Common Proteins in "Tumor vs NATs OSCC and HNSCC Cell line Secrotome" vs "salivary proteome healthy vs. OSCC dataset by Chu et al. [8], human salivary proteome by Sivadasan et al. [9] and normal salivary proteome dataset ( https://salivaryproteome.nidcr.nih.gov/ )."
DOI: 10.6084/m9.figshare.19135844
title: Additional file 11 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 11: Table S10. List of 205 differentially expressed up regulated proteins (P &lt; 0.01) of OSCC tumor tissue vs. paired normal adjacent tissue predicted to be secreted, either via classical or non-classical secretion mechanisms and their subcellular localization
DOI: 10.6084/m9.figshare.19135841
title: Additional file 10 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 10: Table S9.106 Common Proteins in "Tumor vs NATs OSCC and HNSCC Cell line Secrotome" vs "salivary proteome healthy vs. OSCC dataset by Chu et al. [8], human salivary proteome by Sivadasan et al. [9] and normal salivary proteome dataset ( https://salivaryproteome.nidcr.nih.gov/ )."
DOI: 10.6084/m9.figshare.19135844.v1
title: Additional file 11 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 11: Table S10. List of 205 differentially expressed up regulated proteins (P &lt; 0.01) of OSCC tumor tissue vs. paired normal adjacent tissue predicted to be secreted, either via classical or non-classical secretion mechanisms and their subcellular localization
DOI: 10.6084/m9.figshare.19135850.v1
title: Additional file 2 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 2: Table S1. List of 5123 identified proteins tumors compared to NAT of OSCC patients
DOI: 10.6084/m9.figshare.19135850
title: Additional file 2 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 2: Table S1. List of 5123 identified proteins tumors compared to NAT of OSCC patients
DOI: 10.6084/m9.figshare.19135853
title: Additional file 3 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 3: Table S2. List of differentially up and down regulated Proteins (P&lt;0.01, 2-fold up/down) in tumors compared to NAT of OSCC patients.
DOI: 10.6084/m9.figshare.19135856
title: Additional file 4 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 4: Table S3. String Interaction of 205 up regulated proteins at FC &gt;+2 and P &lt;0.01 in tumors as compared to NATs.
DOI: 10.6084/m9.figshare.19135856.v1
title: Additional file 4 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 4: Table S3. String Interaction of 205 up regulated proteins at FC &gt;+2 and P &lt;0.01 in tumors as compared to NATs.
DOI: 10.6084/m9.figshare.19135853.v1
title: Additional file 3 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 3: Table S2. List of differentially up and down regulated Proteins (P&lt;0.01, 2-fold up/down) in tumors compared to NAT of OSCC patients.
DOI: 10.6084/m9.figshare.19135862
title: Additional file 6 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 6: Table S5. 1724 secretome proteins were identified (˃5 average counts) in all HNSCC secretome.
DOI: 10.6084/m9.figshare.19135859
title: Additional file 5 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 5: Table S4. List of 4472 identified proteins secretomes of HNSCC cell lines.
DOI: 10.6084/m9.figshare.19135859.v1
title: Additional file 5 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 5: Table S4. List of 4472 identified proteins secretomes of HNSCC cell lines.
DOI: 10.6084/m9.figshare.19135862.v1
title: Additional file 6 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 6: Table S5. 1724 secretome proteins were identified (˃5 average counts) in all HNSCC secretome.
DOI: 10.6084/m9.figshare.19135865
title: Additional file 7 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 7: Table S6. Overlap analysis of these robustly identified secretome proteins with the differential OSCC tissue proteins revealed 132 promising OSCC proteins as candidate non-invasive markers. Underscoring their value as potential OSCC marker, 131 proteins were also cancer-associated in the large-scale proteomics analysis of OSCC tissue recently reported by Huang et al. [7].
DOI: 10.6084/m9.figshare.19135865.v1
title: Additional file 7 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 7: Table S6. Overlap analysis of these robustly identified secretome proteins with the differential OSCC tissue proteins revealed 132 promising OSCC proteins as candidate non-invasive markers. Underscoring their value as potential OSCC marker, 131 proteins were also cancer-associated in the large-scale proteomics analysis of OSCC tissue recently reported by Huang et al. [7].
DOI: 10.6084/m9.figshare.19135868
title: Additional file 8 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 8: Table S7. 132 overlapping OSCC tissue and HNSCC secretome candidates had a predicted signal peptide in their sequence.
DOI: 10.6084/m9.figshare.19135868.v1
title: Additional file 8 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 8: Table S7. 132 overlapping OSCC tissue and HNSCC secretome candidates had a predicted signal peptide in their sequence.
DOI: 10.6084/m9.figshare.19135871
title: Additional file 9 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 9: Table S8.Public proteomics datasets; salivary proteome healthy vs. OSCC dataset by Chu et al. [8], human salivary proteome by Sivadasan et al. [9] and Normal Saliva Proteome database ( https://salivaryproteome.nidcr.nih.gov/)
DOI: 10.6084/m9.figshare.19135871.v1
title: Additional file 9 of Secreted protein markers in oral squamous cell carcinoma (OSCC)

description: Additional file 9: Table S8.Public proteomics datasets; salivary proteome healthy vs. OSCC dataset by Chu et al. [8], human salivary proteome by Sivadasan et al. [9] and Normal Saliva Proteome database ( https://salivaryproteome.nidcr.nih.gov/)
DOI: 10.6084/m9.figshare.19135880
title: Additional file 1 of Genetic testing of dogs predicts problem behaviors in clinical and nonclinical samples

description: Additional file 1: Supplementary Data 1. Paper questionnaire, C-BARQ phenotype and genotype data. Supplementary Data 2. Cumulative frequencies used to define Fixed Thresholds for FTCCM. Supplementary Text. Extended introduction and discussion. Table S1. Cohort breed frequencies. Table S2. Comparison of cohort breeds to US and US cities popularities. Table S3. Study markers list with genome scan traits. Table S4. Descriptive statistics for continuous variables. Figure S1. Duplicate of Fig. 1, but with numerical values (incl. p-values). Figure S2. Correlation table of C-BARQ variables. Figure S3. PCA of C-BARQ traits isolating the following: sex, neuter status, pedigree vs. mixed breed, Pit Bull-type, behavioral diagnosis and non-behavioral ailments. Figure S4. PCA of genetic markers isolating the following: sex, neuter status, pedigree vs. mixed breed, Pit Bull-type, behavioral diagnosis and non-behavioral ailments. Figure S5. PCA of genetic markers separately isolating all retrievers and German Shepherd Dogs. Figure S6. Duplicate of Fig. 3, but with p-values. Figure S7. Duplicate of Fig. 4, but with p-values. Figure S8. Duplicate of Fig. 5, but with p-values. Figures S9–12. Logistic regression with stepwise selection modeling with cases classified by trait severity at 50th, 75th, 90th and 95th percentile, respectively. Figures S13/14. PCA of genetic markers and C-BARQ behavior isolating Wilson et al. 2018 clustering of breeds by C-BARQ behavior.
DOI: 10.6084/m9.figshare.19135880.v1
title: Additional file 1 of Genetic testing of dogs predicts problem behaviors in clinical and nonclinical samples

description: Additional file 1: Supplementary Data 1. Paper questionnaire, C-BARQ phenotype and genotype data. Supplementary Data 2. Cumulative frequencies used to define Fixed Thresholds for FTCCM. Supplementary Text. Extended introduction and discussion. Table S1. Cohort breed frequencies. Table S2. Comparison of cohort breeds to US and US cities popularities. Table S3. Study markers list with genome scan traits. Table S4. Descriptive statistics for continuous variables. Figure S1. Duplicate of Fig. 1, but with numerical values (incl. p-values). Figure S2. Correlation table of C-BARQ variables. Figure S3. PCA of C-BARQ traits isolating the following: sex, neuter status, pedigree vs. mixed breed, Pit Bull-type, behavioral diagnosis and non-behavioral ailments. Figure S4. PCA of genetic markers isolating the following: sex, neuter status, pedigree vs. mixed breed, Pit Bull-type, behavioral diagnosis and non-behavioral ailments. Figure S5. PCA of genetic markers separately isolating all retrievers and German Shepherd Dogs. Figure S6. Duplicate of Fig. 3, but with p-values. Figure S7. Duplicate of Fig. 4, but with p-values. Figure S8. Duplicate of Fig. 5, but with p-values. Figures S9–12. Logistic regression with stepwise selection modeling with cases classified by trait severity at 50th, 75th, 90th and 95th percentile, respectively. Figures S13/14. PCA of genetic markers and C-BARQ behavior isolating Wilson et al. 2018 clustering of breeds by C-BARQ behavior.
DOI: 10.6084/m9.figshare.17305020
title: Additional file 1 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 1: Details of high-throughput sequencing runs and BoRV CH15–specific scaffolds in cases 1 to 7.
DOI: 10.6084/m9.figshare.17305020.v1
title: Additional file 1 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 1: Details of high-throughput sequencing runs and BoRV CH15–specific scaffolds in cases 1 to 7.
DOI: 10.6084/m9.figshare.17305029
title: Additional file 3 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 3: Possible insertions in the long terminal repeats of BoRV CH15 genomes of case 5 and 7.
DOI: 10.6084/m9.figshare.17305029.v1
title: Additional file 3 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 3: Possible insertions in the long terminal repeats of BoRV CH15 genomes of case 5 and 7.
DOI: 10.6084/m9.figshare.17305026
title: Additional file 2 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 2: Read pairs with one mate mapping to the Bos taurus genome and one mapping to BoRV CH15.
DOI: 10.6084/m9.figshare.17305026.v1
title: Additional file 2 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 2: Read pairs with one mate mapping to the Bos taurus genome and one mapping to BoRV CH15.
DOI: 10.6084/m9.figshare.17305041
title: Additional file 6 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 6: Primers used for Sanger sequencing.
DOI: 10.6084/m9.figshare.17305038
title: Additional file 5 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 5: Pairwise identities (%) of BoRV CH15 genome elements.
DOI: 10.6084/m9.figshare.17305038.v1
title: Additional file 5 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 5: Pairwise identities (%) of BoRV CH15 genome elements.
DOI: 10.6084/m9.figshare.17305041.v1
title: Additional file 6 of A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

description: Additional file 6: Primers used for Sanger sequencing.
DOI: 10.6084/m9.figshare.19135942.v1
title: Additional file 1 of Occupation and prostate Cancer risk: results from the epidemiological study of prostate cancer (EPICAP)

description: Additional file 1. The results for associations between all occupations (1 to 3-digits with at least 10 subjects) and PCa can be found in a supplementary document named: Additional file 1 - Occupation and Prostate Cancer risk - results from the Epidemiological study of prostate cancer (EPICAP). Data are presented in a Microsoft Excel Spreadsheet (.xlsx) which contains: Table S1. Associations between occupations and prostate cancer [all cancers] (N = 1693). Table S2. Associations between occupations and prostate cancer aggressiveness (N = 1680).
DOI: 10.6084/m9.figshare.19135942
title: Additional file 1 of Occupation and prostate Cancer risk: results from the epidemiological study of prostate cancer (EPICAP)

description: Additional file 1. The results for associations between all occupations (1 to 3-digits with at least 10 subjects) and PCa can be found in a supplementary document named: Additional file 1 - Occupation and Prostate Cancer risk - results from the Epidemiological study of prostate cancer (EPICAP). Data are presented in a Microsoft Excel Spreadsheet (.xlsx) which contains: Table S1. Associations between occupations and prostate cancer [all cancers] (N = 1693). Table S2. Associations between occupations and prostate cancer aggressiveness (N = 1680).
DOI: 10.6084/m9.figshare.19135979
title: Additional file 1 of Effects of a taped filter mask on peak power, perceived breathlessness, heart rate, blood lactate and oxygen saturation during a graded exercise test in young healthy adults: a randomized controlled trial

description: Additional file 1: Qualitative feedback from mask questionnaire. In this table it listed participants’ feedback on the surgical and taped mask during exercise.
DOI: 10.6084/m9.figshare.19135979.v1
title: Additional file 1 of Effects of a taped filter mask on peak power, perceived breathlessness, heart rate, blood lactate and oxygen saturation during a graded exercise test in young healthy adults: a randomized controlled trial

description: Additional file 1: Qualitative feedback from mask questionnaire. In this table it listed participants’ feedback on the surgical and taped mask during exercise.
DOI: 10.6084/m9.figshare.19136006
title: Additional file 1 of Maternal microbiota-derived metabolic profile in fetal murine intestine, brain and placenta

description: Additional file 1.
DOI: 10.6084/m9.figshare.19136006.v1
title: Additional file 1 of Maternal microbiota-derived metabolic profile in fetal murine intestine, brain and placenta

description: Additional file 1.
DOI: 10.6084/m9.figshare.19136009
title: Additional file 2 of Maternal microbiota-derived metabolic profile in fetal murine intestine, brain and placenta

description: Additional file 2.
DOI: 10.6084/m9.figshare.19136009.v1
title: Additional file 2 of Maternal microbiota-derived metabolic profile in fetal murine intestine, brain and placenta

description: Additional file 2.
DOI: 10.5519/qd.mgp0vbph
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (47 records)
DOI: 10.6084/m9.figshare.19136047
title: Additional file 2 of Single-cell isoform analysis in human immune cells

description: Additional file 2. Supplemental tables 3-4. (XLS 169 kb)
DOI: 10.6084/m9.figshare.19136047.v1
title: Additional file 2 of Single-cell isoform analysis in human immune cells

description: Additional file 2. Supplemental tables 3-4. (XLS 169 kb)
DOI: 10.6084/m9.figshare.19136050
title: Additional file 3 of Single-cell isoform analysis in human immune cells

description: Additional file 3. Cell type specific isoforms in psl format.
DOI: 10.6084/m9.figshare.19136050.v1
title: Additional file 3 of Single-cell isoform analysis in human immune cells

description: Additional file 3. Cell type specific isoforms in psl format.
DOI: 10.6084/m9.figshare.17598539
title: Additional file 1 of Efficacy and safety of artemether-lumefantrine and dihydroartemisinin-piperaquine for the treatment of uncomplicated Plasmodium falciparum malaria and prevalence of molecular markers associated with artemisinin and partner drug resistance in Uganda

description: Additional file 1: Table S1. Raw genotyping data.
DOI: 10.6084/m9.figshare.17598539.v1
title: Additional file 1 of Efficacy and safety of artemether-lumefantrine and dihydroartemisinin-piperaquine for the treatment of uncomplicated Plasmodium falciparum malaria and prevalence of molecular markers associated with artemisinin and partner drug resistance in Uganda

description: Additional file 1: Table S1. Raw genotyping data.
DOI: 10.6084/m9.figshare.19136072
title: Additional file 1 of Mating behavior and reproductive morphology predict macroevolution of sex allocation in hermaphroditic flatworms

description: Additional file 1: Table S1. Details on all specimens included in this study. Table S2. Mean species values for all variables. Table S3. Sample size per species for all quantitative traits. Table S4. PGLS analysis of gonadal sex allocation and various indicators of the inferred mating syndrome. Table S5. Heterozygosity estimates. Table S6. Univariate PGLS with GSA as the dependent variable. Table S7. Results from PGLS regression analysis of (A) testis size and ovary size on body size and (B) a covariate model including body size and the inferred mating syndrome. Table S8. PGLS of the residual testis and residual ovary size. Table S9. Multivariate PGLS of gonadal sex allocation using four sexual traits and body size as predictors.
DOI: 10.6084/m9.figshare.19136072.v1
title: Additional file 1 of Mating behavior and reproductive morphology predict macroevolution of sex allocation in hermaphroditic flatworms

description: Additional file 1: Table S1. Details on all specimens included in this study. Table S2. Mean species values for all variables. Table S3. Sample size per species for all quantitative traits. Table S4. PGLS analysis of gonadal sex allocation and various indicators of the inferred mating syndrome. Table S5. Heterozygosity estimates. Table S6. Univariate PGLS with GSA as the dependent variable. Table S7. Results from PGLS regression analysis of (A) testis size and ovary size on body size and (B) a covariate model including body size and the inferred mating syndrome. Table S8. PGLS of the residual testis and residual ovary size. Table S9. Multivariate PGLS of gonadal sex allocation using four sexual traits and body size as predictors.
DOI: 10.6084/m9.figshare.19136128
title: Additional file 2 of Distribution of soil viruses across China and their potential role in phosphorous metabolism

description: Additional file 2. Table S1. Soil sampling information and physicochemical properties. Table S2. The amino acid sequences of phoH genes f.rom different environmental samples. Table S3. Overview of 19 virome data. Table S4. The vOTU table. Table S5. The abundance of viral reads identified by Kraken 2 (Family level).
DOI: 10.6084/m9.figshare.19136128.v1
title: Additional file 2 of Distribution of soil viruses across China and their potential role in phosphorous metabolism

description: Additional file 2. Table S1. Soil sampling information and physicochemical properties. Table S2. The amino acid sequences of phoH genes f.rom different environmental samples. Table S3. Overview of 19 virome data. Table S4. The vOTU table. Table S5. The abundance of viral reads identified by Kraken 2 (Family level).
DOI: 10.6084/m9.figshare.19136131.v1
title: Additional file 1 of High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

description: Additional file 1.
DOI: 10.6084/m9.figshare.19136131
title: Additional file 1 of High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

description: Additional file 1.
DOI: 10.6084/m9.figshare.19136134.v1
title: Additional file 2 of High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

description: Additional file 2.
DOI: 10.6084/m9.figshare.19136143.v1
title: Additional file 4 of High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

description: Additional file 4.
DOI: 10.6084/m9.figshare.19136134
title: Additional file 2 of High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

description: Additional file 2.
DOI: 10.6084/m9.figshare.19136143
title: Additional file 4 of High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

description: Additional file 4.
DOI: 10.25345/c53p1q
title: MassIVE MSV000088797 - Identification of enriched O-GlcNAc proteins in hypertrophic mouse hearts
title: We used C57/Bl6 mice subjected to sham or transverse aortic constriction (TAC) to create pressure-overload hypertrophy (POH). From the hearts, we stabilized and labelled the O-GlcNAc moiety with tetramethylrhodamine azide (TAMRA) before enriching by TAMRA immunoprecipitation (files with "TAMRAIP"). Global proteomics were performed on the non-enriched matching samples (files with "GlobalDigest"). Sham sample IDs: 529, 545, 547, 551, 552. TAC sample IDs: 524, 528, 562, 563, 564. O-GlcNAc proteins were labeled with a click chemistry kit with TAMRA tag (ThermoFisher Scientific), then the labeled proteins were enriched with TAMRA antibody for proteomics experiments. Data was searched against the UniProt mouse database using PEAKS Studio for label free quantitation. Protein abundances were log2 transformed, normalized to median, and missing values imputed using Perseus.
DOI: 10.5281/zenodo.6000683
title: Private or shared room? A nationwide questionnaire survey on bereaved family members' perceptions of where patients spend their last days

description: Background: Where patients receive end-of-life care influences their quality of life. Objectives: To clarify the effects of staying in a private or shared room in inpatient hospices. Design: A part of a Japanese multicenter survey to evaluate the quality of end-of-life care. Setting/participants: 779 bereaved families whose relatives who died from cancer in inpatient hospices. Measurements: The primary outcome was family-perceived need for improvement in environment-related professional care. Secondary end-points included: family satisfaction, environment-related family perception, and quality of death and dying (Good Death Inventory: GDI). Results: 574 responded (73.7%). 300 patients were in a private room from admission to discharge, 47 were in a shared room less than 50% of the time, and the remaining 85 were in a shared room 50% or more. There were significant differences in the need for improvement in shared (vs. private) rooms, and in favor of private rooms for: “privacy was protected,” “easy for visitors to visit,” “could discuss sensitive issues with medical staff without concern,” and “could visit at night.”, as well as “living in calm circumstances” and “spending enough time with family” of the GDI. Contrarily, significant differences were found in favor of shared rooms for: “the patient could interact with other patients.” There was no significant difference in family satisfaction and total score of GDI. Conclusion: There are the advantages and disadvantages of spending one’s final days in a private or shared room, and adjusting rooms according to patients and their families’ values is necessary.