cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.8074361
title: Supplementary Material for: CT-Quantified Adipose Tissue Distribution: Risk or Protective Factor for Complications after Rectal Cancer Surgery?

description: <b><i>Purpose:</i></b> Obesity is associated with increased incidence and mortality in rectal cancer (RC). However, an obesity paradox in the sense of a protective effect of obesity is discussed controversially. We evaluated whether adipose tissue distribution has an impact on medical (MC) and surgical complications (SC) after RC surgery. <b><i>Methods:</i></b> A total of 296 RC patients underwent oncological surgery and multidetector CT with quantification of total (TAT), visceral (VAT), and subcutaneous adipose tissue (SAT). Logistic regressions on SC (anastomotic leakage [<i>n</i> = 26], wound infection [<i>n</i> = 58], bleeding [<i>n</i> = 12], abscess [<i>n</i> = 32], bladder dysfunction [<i>n</i> = 24], burst abdomen [<i>n</i> = 10]), and MC (pulmonary [<i>n</i> = 22], cardiac [<i>n</i> = 18], urinary tract infection [<i>n</i> = 9], sepsis [<i>n</i> = 5]) were performed. <b><i>Results:</i></b> High pelvic<sub></sub>VAT was associated with reduced risk for overall SC (OR = 0.915, <i>p</i> = 0.012) and anastomotic leakage (OR = 0.587, <i>p</i> = 0.024, CI: 0.369/0.934). In contrast, CT-quantified obesity was associated with increased risk for wound infection, bladder dysfunction, burst abdomen, overall MC, and cardiac complications (ORs up to 1.423). BMI was not associated with any SC or MC. <b><i>Conclusion:</i></b> An obesity paradox with a protective effect of CT-quantified adipose tissue was confirmed for anastomotic leakage and overall SC. In contrast, high adipose tissue was associated with higher risk for other SC and MC. These results show a more complex influence of body composition on MC and SC. CT-quantified obesity is able to provide deeper insights to explain the obesity paradox beyond BMI.
DOI: 10.6084/m9.figshare.8074373.v1
title: Overseas Study Zhihu Corpus

description: Chinese language corpus containing 621 questions and 10,416 answers posted to Zhihu.com. Questions relate to undertaking overseas study in Australia.Includes R scripts used to extract data. Data extracted in April 2019. Files are questions (Q), answers (A) and question topics (T). The naming convention is the URL of the webpage: For questions: https://www.zhihu.com/question/[<i>question number</i>] For answers: https://www.zhihu.com/question/[<i>question number</i>]/answer/[<i>answer number</i>]<br>Answers are organised by author category: "male", "female", "undisclosed gender", "anonymous", "organisation" using information from the user's profile where publicly accessible.
DOI: 10.6084/m9.figshare.8074352
title: Supplementary Material for: Potential of Parameters of Iron Metabolism for the Diagnosis of Anemia of Inflammation in the Critically Ill

description: <b><i>Background:</i></b> Anemia of inflammation (AI) is the most common cause of anemia in the critically ill, but its diagnosis is a challenge. New therapies specific to AI are in development, and they require accurate detection of AI. This study explores the potential of parameters of iron metabolism for the diagnosis of AI during an ICU stay. <b><i>Methods:</i></b> In a nested case-control study, 30 patients developing AI were matched to 60 controls. The iron parameters were determined in plasma samples during an ICU stay. Receiver operating characteristic curves were used to determine the iron parameter threshold with the highest sensitivity and specificity to predict AI. Likelihood ratios as well as positive and negative predictive values were calculated as well. <b><i>Results:</i></b> The sensitivity of iron parameters for diagnosing AI ranges between 62 and 76%, and the specificity between 57 and 72%. Iron and transferrin show the greatest area under the curve. Iron shows the highest sensitivity, and transferrin and transferrin saturation display the highest specificity. Hepcidin and ferritin show the lowest specificity. At an actual anemia prevalence of 53%, the diagnostic accuracy of iron, transferrin, and transferrin saturation was fair, with a positive predictive value between 71 and 73%. Combining iron, transferrin, transferrin saturation, hepcidin, and/or ferritin levels did not increase the accuracy of the AI diagnosis. <b><i>Conclusions:</i></b> In this explorative study on the use of different parameters of iron metabolism for diagnosing AI during an ICU stay, low levels of commonly measured markers such as plasma iron, transferrin, and transferrin saturation have the highest sensitivity and specificity and outperform ferritin and hepcidin.
DOI: 10.6084/m9.figshare.8074340
title: The in vitro effect of antirheumatic drugs on platelet function

description: Several antirheumatic drugs lower the cardiovascular risk among rheumatoid arthritis patients. It is, however, unknown whether inhibition of platelet function contributes to this risk reduction. Only few studies have investigated the potential role of platelets as a target of antirheumatic drugs. In this study, platelet function was tested in vitro in samples from 24 healthy individuals spiked with antirheumatic drugs in clinically relevant concentrations or vehicle. Platelet aggregation was tested with 96-well light transmission aggregometry (LTA), and when an effect ≥20% compared to vehicle was observed, flow cytometric platelet aggregation and activation were evaluated and closure time was measured by Platelet Function Analyzer (PFA-200). When evaluated by LTA, teriflunomide (the active metabolite of leflunomide), tocilizumab, and prednisolone reduced ADP- and collagen-induced platelet aggregation ≥20%, while adalimumab increased TRAP-induced platelet aggregation ≥20%. Using flow cytometry, agonist-induced platelet aggregation with teriflunomide or vehicle was mean ± standard deviation (SD); 30.7% ± 5.8 vs. 41.7% ± 6.5, p = 0.02 using ADP, and 34.7% ± 13.9 vs. 55.8% ± 3.9, p = 0.01 using collagen. Results indicate that teriflunomide, prednisolone, and tocilizumab inhibit, and adalimumab increases platelet aggregation. The study suggests that the majority of antirheumatic drugs mainly reduced cardiovascular risk through indirect effects (e.g., reducing inflammation).
DOI: 10.6084/m9.figshare.8074352.v1
title: Supplementary Material for: Potential of Parameters of Iron Metabolism for the Diagnosis of Anemia of Inflammation in the Critically Ill

description: <b><i>Background:</i></b> Anemia of inflammation (AI) is the most common cause of anemia in the critically ill, but its diagnosis is a challenge. New therapies specific to AI are in development, and they require accurate detection of AI. This study explores the potential of parameters of iron metabolism for the diagnosis of AI during an ICU stay. <b><i>Methods:</i></b> In a nested case-control study, 30 patients developing AI were matched to 60 controls. The iron parameters were determined in plasma samples during an ICU stay. Receiver operating characteristic curves were used to determine the iron parameter threshold with the highest sensitivity and specificity to predict AI. Likelihood ratios as well as positive and negative predictive values were calculated as well. <b><i>Results:</i></b> The sensitivity of iron parameters for diagnosing AI ranges between 62 and 76%, and the specificity between 57 and 72%. Iron and transferrin show the greatest area under the curve. Iron shows the highest sensitivity, and transferrin and transferrin saturation display the highest specificity. Hepcidin and ferritin show the lowest specificity. At an actual anemia prevalence of 53%, the diagnostic accuracy of iron, transferrin, and transferrin saturation was fair, with a positive predictive value between 71 and 73%. Combining iron, transferrin, transferrin saturation, hepcidin, and/or ferritin levels did not increase the accuracy of the AI diagnosis. <b><i>Conclusions:</i></b> In this explorative study on the use of different parameters of iron metabolism for diagnosing AI during an ICU stay, low levels of commonly measured markers such as plasma iron, transferrin, and transferrin saturation have the highest sensitivity and specificity and outperform ferritin and hepcidin.
DOI: 10.6084/m9.figshare.8074340.v1
title: The in vitro effect of antirheumatic drugs on platelet function

description: Several antirheumatic drugs lower the cardiovascular risk among rheumatoid arthritis patients. It is, however, unknown whether inhibition of platelet function contributes to this risk reduction. Only few studies have investigated the potential role of platelets as a target of antirheumatic drugs. In this study, platelet function was tested in vitro in samples from 24 healthy individuals spiked with antirheumatic drugs in clinically relevant concentrations or vehicle. Platelet aggregation was tested with 96-well light transmission aggregometry (LTA), and when an effect ≥20% compared to vehicle was observed, flow cytometric platelet aggregation and activation were evaluated and closure time was measured by Platelet Function Analyzer (PFA-200). When evaluated by LTA, teriflunomide (the active metabolite of leflunomide), tocilizumab, and prednisolone reduced ADP- and collagen-induced platelet aggregation ≥20%, while adalimumab increased TRAP-induced platelet aggregation ≥20%. Using flow cytometry, agonist-induced platelet aggregation with teriflunomide or vehicle was mean ± standard deviation (SD); 30.7% ± 5.8 vs. 41.7% ± 6.5, p = 0.02 using ADP, and 34.7% ± 13.9 vs. 55.8% ± 3.9, p = 0.01 using collagen. Results indicate that teriflunomide, prednisolone, and tocilizumab inhibit, and adalimumab increases platelet aggregation. The study suggests that the majority of antirheumatic drugs mainly reduced cardiovascular risk through indirect effects (e.g., reducing inflammation).
DOI: 10.6084/m9.figshare.8073800
title: MOESM1 of Old World cutaneous leishmaniasis treatment response varies depending on parasite species, geographical location and development of secondary infection

description: Additional file 1: Table S1. Cohort characteristics and relevant clinical features.
DOI: 10.6084/m9.figshare.8073803
title: Additional file 1: of Scrutinizing the drug resistance mechanism of multi- and extensively-drug resistant Mycobacterium tuberculosis: mutations versus efflux pumps

description: Table S1. Differential expression of efflux pump genes under RIF, INH, VP+RIF and VP + INH stress in MDR M tuberculosis isolates. Table S2. Differential expression of efflux pump genes under RIF, INH, EMB, VP + RIF, VP + INH, and VP + EMB stress in mono-resistant M tuberculosis isolates. (XLS 84 kb)
DOI: 10.6084/m9.figshare.8073800.v1
title: MOESM1 of Old World cutaneous leishmaniasis treatment response varies depending on parasite species, geographical location and development of secondary infection

description: Additional file 1: Table S1. Cohort characteristics and relevant clinical features.
DOI: 10.6084/m9.figshare.8073803.v1
title: Additional file 1: of Scrutinizing the drug resistance mechanism of multi- and extensively-drug resistant Mycobacterium tuberculosis: mutations versus efflux pumps

description: Table S1. Differential expression of efflux pump genes under RIF, INH, VP+RIF and VP + INH stress in MDR M tuberculosis isolates. Table S2. Differential expression of efflux pump genes under RIF, INH, EMB, VP + RIF, VP + INH, and VP + EMB stress in mono-resistant M tuberculosis isolates. (XLS 84 kb)
DOI: 10.6084/m9.figshare.8073776
title: Additional file 8: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Genotyping panel. The 1416 Pyrus accessions genotyped with the Axiom™ 70 K Pear Genotyping Array. For each sample the table shows the accession’s Plant Introduction (PI) number, the inventory lot identifier, the assigned taxon and common plant name, the origin, the group to which the species belongs (as in Challice and Westwood [60]), the source of the sample, if it failed or passed and the reason for failure, and the ploidy. (XLSX 94 kb)
DOI: 10.6084/m9.figshare.8073773
title: MOESM8 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 8. Correspondence of row numbers between Additional file 1 and Additional file 5 for maternal effects.
DOI: 10.6084/m9.figshare.8073764
title: Additional file 6: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Concordance Check results for the samples of the screening panel. Pairwise concordance values 97% are reported, for a total of 19 groups of duplicated samples (three ‘Bartlett’ pairwise concordances count as one group). Putative sampling errors were verified by SSR analysis. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.8073767
title: MOESM7 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 7. Correspondence of row numbers between Additional file 1 and Additional file 5 for animal effects (i.e., breeding values).
DOI: 10.6084/m9.figshare.8073776.v1
title: Additional file 8: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Genotyping panel. The 1416 Pyrus accessions genotyped with the Axiom™ 70 K Pear Genotyping Array. For each sample the table shows the accession’s Plant Introduction (PI) number, the inventory lot identifier, the assigned taxon and common plant name, the origin, the group to which the species belongs (as in Challice and Westwood [60]), the source of the sample, if it failed or passed and the reason for failure, and the ploidy. (XLSX 94 kb)
DOI: 10.6084/m9.figshare.8073761
title: MOESM6 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 6. Reproduction farm numbers. The order of animals is same as in in Additional file 1.
DOI: 10.6084/m9.figshare.8073764.v1
title: Additional file 6: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Concordance Check results for the samples of the screening panel. Pairwise concordance values 97% are reported, for a total of 19 groups of duplicated samples (three ‘Bartlett’ pairwise concordances count as one group). Putative sampling errors were verified by SSR analysis. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.8073773.v1
title: MOESM8 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 8. Correspondence of row numbers between Additional file 1 and Additional file 5 for maternal effects.
DOI: 10.6084/m9.figshare.8073752
title: MOESM4 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 4. Design matrix for fixed effects on growth curve parameters. The first row is name of effects. The order of animals is the same as in Additional file 1.
DOI: 10.6084/m9.figshare.8073767.v1
title: MOESM7 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 7. Correspondence of row numbers between Additional file 1 and Additional file 5 for animal effects (i.e., breeding values).
DOI: 10.6084/m9.figshare.8073749
title: Additional file 4: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: List of trios used for Mendelian check. A total of 22 trios (two parents, P01 and P02, and one offspring, Off) were included in the screening panel and were used for the Mendelian test on the PolyHighResolution SNPs of the Axiom™ 700 K Pear Genotyping Array. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.8073755
title: MOESM5 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 5. Inverse of $${\mathbf{A}}$$ A matrix. Only non-zero elements are presented as [RowNumber ColumnNumber Value].
DOI: 10.6084/m9.figshare.8073746
title: MOESM3 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 3. Design matrix for fixed effects on weight at entry. The first row is name of effects. The order of animals is the same as in in Additional file 1.
DOI: 10.6084/m9.figshare.8073752.v1
title: MOESM4 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 4. Design matrix for fixed effects on growth curve parameters. The first row is name of effects. The order of animals is the same as in Additional file 1.
DOI: 10.6084/m9.figshare.8073761.v1
title: MOESM6 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 6. Reproduction farm numbers. The order of animals is same as in in Additional file 1.
DOI: 10.6084/m9.figshare.8073743
title: Additional file 3: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Screening panel. The 288 Pyrus accessions screened with the Axiom™ 700 K Pear Genotyping Array. For each sample, the Table shows the accession’s Plant Introduction (PI) number, the inventory lot identifier, the assigned taxon and common plant name, the origin, the group to which the species belongs (as in Challice and Westwood [60]), the source of the sample, if it failed or passed quality check and the reason for failure. (XLSX 28 kb)
DOI: 10.6084/m9.figshare.8073755.v1
title: MOESM5 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 5. Inverse of $${\mathbf{A}}$$ A matrix. Only non-zero elements are presented as [RowNumber ColumnNumber Value].
DOI: 10.6084/m9.figshare.8073737
title: MOESM2 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 2. Phenotype (weight) records of 3831 animals after entry to experimental stations. The first row is days after entry to experimental stations. Missing values are 999,999. The order of animals is the same as in Additional file 1.
DOI: 10.6084/m9.figshare.8073740
title: Additional file 2: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Explanation of the SnpEff categories for all annotated variants. The number of variants for each type of predicted impact on the gene and the explanation of the effects are shown, as reported in the SnpEff manual ( http://snpeff.sourceforge.net/SnpEff_manual.html ). (XLSX 10 kb)
DOI: 10.6084/m9.figshare.8073743.v1
title: Additional file 3: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Screening panel. The 288 Pyrus accessions screened with the Axiom™ 700 K Pear Genotyping Array. For each sample, the Table shows the accession’s Plant Introduction (PI) number, the inventory lot identifier, the assigned taxon and common plant name, the origin, the group to which the species belongs (as in Challice and Westwood [60]), the source of the sample, if it failed or passed quality check and the reason for failure. (XLSX 28 kb)
DOI: 10.6084/m9.figshare.8073746.v1
title: MOESM3 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 3. Design matrix for fixed effects on weight at entry. The first row is name of effects. The order of animals is the same as in in Additional file 1.
DOI: 10.6084/m9.figshare.8073731
title: MOESM1 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 1. Phenotype (weight) records of 3831 animals after birth. The first row is days after birth (i.e., age). Missing values are 999,999.
DOI: 10.6084/m9.figshare.8073734
title: Additional file 1: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Polymorphism discovery panel. The 55 Pyrus accessions re-sequenced for variant discovery. For each sample the table shows the accession’s Plant Introduction (PI) number, the inventory lot identifier, the assigned taxon and common plant name, the group to which the species belongs (as in Challice and Westwood [60]), the source of the sample, the total number of trimmed read pairs (original 100 bp paired-end reads were adapter and quality-trimmed), and the average coverage. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.8073737.v1
title: MOESM2 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 2. Phenotype (weight) records of 3831 animals after entry to experimental stations. The first row is days after entry to experimental stations. Missing values are 999,999. The order of animals is the same as in Additional file 1.
DOI: 10.6084/m9.figshare.8073740.v1
title: Additional file 2: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Explanation of the SnpEff categories for all annotated variants. The number of variants for each type of predicted impact on the gene and the explanation of the effects are shown, as reported in the SnpEff manual ( http://snpeff.sourceforge.net/SnpEff_manual.html ). (XLSX 10 kb)
DOI: 10.6084/m9.figshare.8073725
title: Additional file 14: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Number of samples for each species in the screening panel and in the USDA-NCGR collection. The number of samples for each Pyrus species are reported for the screening panel and for the entire USDA National Clonal Germplasm Collection of Corvallis, OR. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.8073731.v1
title: MOESM1 of Development of a structural growth curve model that considers the causal effect of initial phenotypes

description: Additional file 1. Phenotype (weight) records of 3831 animals after birth. The first row is days after birth (i.e., age). Missing values are 999,999.
DOI: 10.6084/m9.figshare.8073725.v1
title: Additional file 14: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Number of samples for each species in the screening panel and in the USDA-NCGR collection. The number of samples for each Pyrus species are reported for the screening panel and for the entire USDA National Clonal Germplasm Collection of Corvallis, OR. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.8073734.v1
title: Additional file 1: of Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

description: Polymorphism discovery panel. The 55 Pyrus accessions re-sequenced for variant discovery. For each sample the table shows the accession’s Plant Introduction (PI) number, the inventory lot identifier, the assigned taxon and common plant name, the group to which the species belongs (as in Challice and Westwood [60]), the source of the sample, the total number of trimmed read pairs (original 100 bp paired-end reads were adapter and quality-trimmed), and the average coverage. (XLSX 16 kb)