cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4759186
title: DARPA SETA Support FY2010 / FY2015 Database

description: SETA Support DARPA FY2010/FY2015 Data Base contains information on contracts and performers of DARPA in 2010 and 2015 fiscal years. Contains information on 3793 contracts, including: Contract Number, Performer's Name, Performer's Type, Agent Name, Program Type (6.1, 6.2, 6.3, or unknown (X)), Program Name, DARPA Office, Program Manager, Fiscal Year, Obligated, SETA Marker, Ratio (SETA/Total), as well as Whole Program Costs and Whole Program SETA-support Costs. <br>Abbreviations: SETA - systems engineering and technical assistance; DARPA - Defense Advanced Research Projects Agency.
DOI: 10.6084/m9.figshare.4762138.v1
title: Clostridium difficile toxin level

description: These are datasets of patients with Clostridium difficile in whom toxin levels were determined using ELISA
DOI: 10.6084/m9.figshare.4758646
title: OnlineAppendix_Vizentin-Bugoni et al 2017

description: Metadata extracted from 206 studies published on pollination networks in tropical and non-tropical regions. Details on Vizentin-Bugoni J, Maruyama PK, Silveira CS, Ollerton J, Rech AR & Sazima, M (2017). Plant-pollinator interactions in the tropics: a review. In. Dáttilo W & Rico-Gray V. Ecological Networks in the Tropics. Springer.
DOI: 10.6084/m9.figshare.4759354.v1
title: data for uploading.pdf

description: these are datasets for graphs as well as blot images
DOI: 10.6084/m9.figshare.4762180.v2
title: ThrEEBoost: Thresholded Boosting for Variable Selection and Prediction via Estimating Equations

description: Most variable selection techniques for high-dimensional models are designed to be used in settings, where observations are independent and completely observed. At the same time, there is a rich literature on approaches to estimation of low-dimensional parameters in the presence of correlation, missingness, measurement error, selection bias, and other characteristics of real data. In this article, we present ThrEEBoost (<i>Thr</i>esholded <i>EEBoost</i>), a general-purpose variable selection technique which can accommodate such problem characteristics by replacing the gradient of the loss by an estimating function. ThrEEBoost generalizes the previously proposed EEBoost algorithm (Wolfson 2011) by allowing the number of regression coefficients updated at each step to be controlled by a thresholding parameter. Different thresholding parameter values yield different variable selection paths, greatly diversifying the set of models that can be explored; the optimal degree of thresholding can be chosen by cross-validation. ThrEEBoost was evaluated using simulation studies to assess the effects of different threshold values on prediction error, sensitivity, specificity, and the number of iterations to identify minimum prediction error under both sparse and nonsparse true models with correlated continuous outcomes. We show that when the true model is sparse, ThrEEBoost achieves similar prediction error to EEBoost while requiring fewer iterations to locate the set of coefficients yielding the minimum error. When the true model is less sparse, ThrEEBoost has lower prediction error than EEBoost and also finds the point yielding the minimum error more quickly. The technique is illustrated by applying it to the problem of identifying predictors of weight change in a longitudinal nutrition study. Supplementary materials are available online.
DOI: 10.6084/m9.figshare.4758604
title: Serum S100 protein could predict altered consciousness in glyphosate or glufosinate poisoning patients

description: <b>Background:</b> Central nervous system (CNS) complications such as seizures and reduced consciousness are important in glufosinate and may occur in severe glyphosate poisoning. The aim of this study was to assess the possible role of serum S100B protein as a biochemical marker of CNS complications associated with glyphosate or glufosinate poisoning. <b>Methods:</b> The study enrolled 40 patients (23 glyphosate poisoning and 17 glufosinate poisoning). Altered consciousness and seizure were observed during hospitalization. S100B level was measured with fully automated modular analytic E170 system using electrochemoluminometric immunoassay. <b>Results:</b> Among 40 patients, neurologic features were observed in 12 patients with a median time to onset of 21.5 (IQR 8.25–24.75) h. Serum S100B concentrations measured on admission were higher in the group with neurologic features than in the group without neurologic features [0.148 μg/L (IQR 0.128–0.248) vs. 0.072 μg/L (IQR 0.047–0.084), <i>p</i> <b>Conclusions:</b> In our pilot study, S100B was a significant predictor of neurologic complications in patients with glyphosate and glufosinate poisoning. Large prospective cohorts are needed to confirm this finding.
DOI: 10.6084/m9.figshare.4762180.v1
title: ThrEEBoost: Thresholded Boosting for Variable Selection and Prediction via Estimating Equations

description: Most variable selection techniques for high-dimensional models are designed to be used in settings, where observations are independent and completely observed. At the same time, there is a rich literature on approaches to estimation of low-dimensional parameters in the presence of correlation, missingness, measurement error, selection bias, and other characteristics of real data. In this article, we present ThrEEBoost (<i>Thr</i>esholded <i>EEBoost</i>), a general-purpose variable selection technique which can accommodate such problem characteristics by replacing the gradient of the loss by an estimating function. ThrEEBoost generalizes the previously proposed EEBoost algorithm (Wolfson 2011) by allowing the number of regression coefficients updated at each step to be controlled by a thresholding parameter. Different thresholding parameter values yield different variable selection paths, greatly diversifying the set of models that can be explored; the optimal degree of thresholding can be chosen by cross-validation. ThrEEBoost was evaluated using simulation studies to assess the effects of different threshold values on prediction error, sensitivity, specificity, and the number of iterations to identify minimum prediction error under both sparse and nonsparse true models with correlated continuous outcomes. We show that when the true model is sparse, ThrEEBoost achieves similar prediction error to EEBoost while requiring fewer iterations to locate the set of coefficients yielding the minimum error. When the true model is less sparse, ThrEEBoost has lower prediction error than EEBoost and also finds the point yielding the minimum error more quickly. The technique is illustrated by applying it to the problem of identifying predictors of weight change in a longitudinal nutrition study. Supplementary materials are available online.
DOI: 10.6084/m9.figshare.4758604.v1
title: Serum S100 protein could predict altered consciousness in glyphosate or glufosinate poisoning patients

description: <b>Background:</b> Central nervous system (CNS) complications such as seizures and reduced consciousness are important in glufosinate and may occur in severe glyphosate poisoning. The aim of this study was to assess the possible role of serum S100B protein as a biochemical marker of CNS complications associated with glyphosate or glufosinate poisoning. <b>Methods:</b> The study enrolled 40 patients (23 glyphosate poisoning and 17 glufosinate poisoning). Altered consciousness and seizure were observed during hospitalization. S100B level was measured with fully automated modular analytic E170 system using electrochemoluminometric immunoassay. <b>Results:</b> Among 40 patients, neurologic features were observed in 12 patients with a median time to onset of 21.5 (IQR 8.25–24.75) h. Serum S100B concentrations measured on admission were higher in the group with neurologic features than in the group without neurologic features [0.148 μg/L (IQR 0.128–0.248) vs. 0.072 μg/L (IQR 0.047–0.084), <i>p</i> <b>Conclusions:</b> In our pilot study, S100B was a significant predictor of neurologic complications in patients with glyphosate and glufosinate poisoning. Large prospective cohorts are needed to confirm this finding.
DOI: 10.6084/m9.figshare.4759186.v1
title: SETA Support DARPA FY2010 / FY2015 Data Base

description: SETA Support DARPA FY2010/FY2015 Data Base contains information on contracts and performers of DARPA in 2010 and 2015 fiscal years. Contains information on 3793 contracts, including: Contract Number, Performer's Name, Performer's Type, Agent Name, Program Type (6.1, 6.2, 6.3, or unknown (X)), Program Name, DARPA Office, Program Manager, Fiscal Year, Obligated, SETA Marker, Ratio (SETA/Total), as well as Whole Program Costs and Whole Program SETA-support Costs. <br>Abbreviations: SETA - systems engineering and technical assistance; DARPA - Defense Advanced Research Projects Agency.
DOI: 10.6084/m9.figshare.4758532
title: Costello et al 2017 JCS Datasets

description: Costello et al 2017 JCS Datasets S1 and S2<br>
DOI: 10.6084/m9.figshare.4758511
title: folder_10

description: Honeybee accelerometer data
DOI: 10.6084/m9.figshare.4758424
title: Supplementary Material for: Putative Biomarker Genes for Grading Clear Cell Renal Cell Carcinoma

description: <i>Objective:</i> The initial objective of this renal cancer study was to identify gene sets in clear cell renal cell carcinoma (ccRCC) to support grading of ccRCC histopathology. <i>Materials and Methods:</i> Preselected ccRCC tumor tissues of grade 1 (G1, n = 14) and grade 3 (G3, n = 15) as well es 14 normal kidney tissues thereof were subjected to microarray expression analysis using Human Genome U133 Plus 2.0 Array. Event ratio scoring, hierarchical clustering and principal component analysis were used to determine gene sets that distinguish expression profiles from normal kidney tissue, G1 and G3 tumor tissues. <i>Results:</i> An initial set of 73 genes provided seven gene subclusters (SC01 to SC07) that distinguish RNA expression profiles from G1, G3 tumor and normal kidney tissues. A ranked list of 24 genes was determined that separated G1 from G3 tumors in high concordance with histopathological grading confirmed by immunohistochemical analysis of ceruloplasmin protein expression. <i>Conclusion:</i> A final set of 24 genes has been determined awaiting further validation on the RNA as well as on the protein level by studying an additional cohort of ccRCC patients. A reliable separation of G1 and G3 tumor grades will be instrumental to foster and direct the administration of upcoming targeted therapeutics of ccRCC tumors in a more predictive and reliable manner.
DOI: 10.6084/m9.figshare.4758451
title: Supplementary_Information.zip

description: This zip contains CAD files from 3D printers to print custom-made holders for stepper motors, objectives and optical posts as well as an Ardunio algorithm to run a stepper motor. Furthermore, a Matlab program to calculate the speckle contrast can be downloaded. <br>This files are supplementary information to our paper "A step-by-step guide to reduce spatial coherence of laser light using a rotating ground glass diffuser".
DOI: 10.6084/m9.figshare.4758424.v1
title: Supplementary Material for: Putative Biomarker Genes for Grading Clear Cell Renal Cell Carcinoma

description: <i>Objective:</i> The initial objective of this renal cancer study was to identify gene sets in clear cell renal cell carcinoma (ccRCC) to support grading of ccRCC histopathology. <i>Materials and Methods:</i> Preselected ccRCC tumor tissues of grade 1 (G1, n = 14) and grade 3 (G3, n = 15) as well es 14 normal kidney tissues thereof were subjected to microarray expression analysis using Human Genome U133 Plus 2.0 Array. Event ratio scoring, hierarchical clustering and principal component analysis were used to determine gene sets that distinguish expression profiles from normal kidney tissue, G1 and G3 tumor tissues. <i>Results:</i> An initial set of 73 genes provided seven gene subclusters (SC01 to SC07) that distinguish RNA expression profiles from G1, G3 tumor and normal kidney tissues. A ranked list of 24 genes was determined that separated G1 from G3 tumors in high concordance with histopathological grading confirmed by immunohistochemical analysis of ceruloplasmin protein expression. <i>Conclusion:</i> A final set of 24 genes has been determined awaiting further validation on the RNA as well as on the protein level by studying an additional cohort of ccRCC patients. A reliable separation of G1 and G3 tumor grades will be instrumental to foster and direct the administration of upcoming targeted therapeutics of ccRCC tumors in a more predictive and reliable manner.
DOI: 10.6084/m9.figshare.4758379
title: Supplementary Material for: High-Fat Diet in the Absence of Obesity Does Not Aggravate Surgically Induced Lymphoedema in Mice

description: <b><i>Background:</i></b> Lymphoedema represents the cardinal manifestation of lymphatic dysfunction and is associated with expansion of the adipose tissue in the affected limb. In mice, high-fat diet (HFD)-induced obesity was associated with impaired collecting lymphatic vessel function, and adiposity aggravated surgery-induced lymphoedema in a mouse model. The aim of the current study was to investigate whether adiposity is necessary to impair lymphatic function or whether increased lipid exposure alone might be sufficient in a surgical lymphoedema model. <b><i>Methods:</i></b> To investigate the role of increased lipid exposure in lymphoedema development we used a well-established mouse tail lymphoedema model. Female mice were subjected to a short-term (6 weeks) HFD, without development of obesity, before surgical induction of lymphedema. Lymphoedema was followed over a period of 6 weeks measuring oedema, evaluating tissue histology and lymphatic vascular function. <b><i>Results:</i></b> HFD increased baseline angiogenesis and average lymphatic vessel size in comparison to the chow control group. Upon induction of lymphedema, HFD-treated mice did not exhibit aggravated oedema and no morphological differences were observed in the blood and lymphatic vasculature. Importantly, the levels of fibro-adipose tissue deposition were comparable between the 2 groups and lymphatic vessel function was not impaired as a result of the HFD. Although the net immune cell infiltration was comparable, the HFD group displayed an increased infiltration of macrophages, which exhibited an M2 polarization phenotype. <b><i>Conclusions:</i></b> These results indicate that increased adiposity rather than dietary influences determines predisposition to or severity of lymphedema.
DOI: 10.6084/m9.figshare.4758379.v1
title: Supplementary Material for: High-Fat Diet in the Absence of Obesity Does Not Aggravate Surgically Induced Lymphoedema in Mice

description: <b><i>Background:</i></b> Lymphoedema represents the cardinal manifestation of lymphatic dysfunction and is associated with expansion of the adipose tissue in the affected limb. In mice, high-fat diet (HFD)-induced obesity was associated with impaired collecting lymphatic vessel function, and adiposity aggravated surgery-induced lymphoedema in a mouse model. The aim of the current study was to investigate whether adiposity is necessary to impair lymphatic function or whether increased lipid exposure alone might be sufficient in a surgical lymphoedema model. <b><i>Methods:</i></b> To investigate the role of increased lipid exposure in lymphoedema development we used a well-established mouse tail lymphoedema model. Female mice were subjected to a short-term (6 weeks) HFD, without development of obesity, before surgical induction of lymphedema. Lymphoedema was followed over a period of 6 weeks measuring oedema, evaluating tissue histology and lymphatic vascular function. <b><i>Results:</i></b> HFD increased baseline angiogenesis and average lymphatic vessel size in comparison to the chow control group. Upon induction of lymphedema, HFD-treated mice did not exhibit aggravated oedema and no morphological differences were observed in the blood and lymphatic vasculature. Importantly, the levels of fibro-adipose tissue deposition were comparable between the 2 groups and lymphatic vessel function was not impaired as a result of the HFD. Although the net immune cell infiltration was comparable, the HFD group displayed an increased infiltration of macrophages, which exhibited an M2 polarization phenotype. <b><i>Conclusions:</i></b> These results indicate that increased adiposity rather than dietary influences determines predisposition to or severity of lymphedema.
DOI: 10.6084/m9.figshare.4758349
title: Supplementary Material for: Lymph Node Metastases in Papillary and Medullary Thyroid Carcinoma Are Independent of Intratumoral Lymphatic Vessel Density

description: <b><i>Background:</i></b> Blood and lymph vessel invasion are well-recognized markers of tumor aggressiveness, as these are the routes that lead to metastases. Thyroid tumors, depending on the histological variant, tend to have distinctive biological behaviors and use different vascular routes to metastasize, yet the mechanisms underlying the metastatic process are still poorly understood. <b><i>Objectives:</i></b> The aim of this study was to assess how the lymph vessel density (LVD) in different histological types of thyroid tumors, and in their surrounding tissue, correlate with the presence of lymph node metastases (LNM) and tumor pathological features. <b><i>Methods:</i></b> Lymph vessels of papillary thyroid carcinomas (PTC), of the classical (CVPTC, <i>n</i> = 50) and follicular variants (FVPTC, <i>n</i> = 18), and medullary thyroid carcinomas (MTC, <i>n</i> = 34) were immunohistochemically stained against antigen D2-40. The stained area was quantified using a computerized morphometric analysis tool and correlated with the tumor pathological characteristics. <b><i>Results:</i></b> LVD within all analyzed thyroid tumor subtypes was significantly lower than in the surrounding thyroid tissues (<i>p</i> &lt; 0.001). Despite intratumoral LVD being significantly higher in CVPTC than in FVPTC, and peritumoral LVD being significantly higher in MTC than in PTC (<i>p</i> &lt; 0.05), no correlations were found between LVD (either intratumoral or peritumoral) and the presence of lymph node metastasis. <b><i>Conclusions:</i></b> As no LVD differences were found amongst thyroid tumors with or without LNM, dissemination is more likely to depend on the tumor ability to invade the abundant lymph vessel network of the surrounding thyroid tissue than on the ability of the tumor to promote de novo lymphangiogenesis.
DOI: 10.25387/g3.12795887.v1
title: Supplemental Material for Bitarello and Mathieson, 2020

description: <b>File_S1 </b>is a pdf and contains 14 supplementary figures and their captions.<br><b>Table S1</b> is an excel spreadsheet and one caption sheet and 20 sheets with content, as described below:<br><b>Sheets 1-6:</b> Different SNP sets generated by clumping and their PRS values. Effect sizes from 360K European ancestry individuals from the UK Biobank. Data from genotype arrays. <br><b>Sheets 6-12:</b> Different SNP sets generated by clumping and their PRS values. Effect sizes estimated from ‘White British’ sibling pairs from the UK Biobank. Data from genotype arrays. <br><b>Sheet 13:</b> Different SNP sets generated by clumping and their PRS values. Data from imputed datasets. <br><b>Sheets 14-19: </b>Different SNP sets generated by clumping and their unweighted PRS values. <br><b>Sheet 20:</b> Difference between PRS values for 1000G super-populations (Africa, Europe) for different sets of SNPs.<br>
DOI: 10.6084/m9.figshare.4758349.v1
title: Supplementary Material for: Lymph Node Metastases in Papillary and Medullary Thyroid Carcinoma Are Independent of Intratumoral Lymphatic Vessel Density

description: <b><i>Background:</i></b> Blood and lymph vessel invasion are well-recognized markers of tumor aggressiveness, as these are the routes that lead to metastases. Thyroid tumors, depending on the histological variant, tend to have distinctive biological behaviors and use different vascular routes to metastasize, yet the mechanisms underlying the metastatic process are still poorly understood. <b><i>Objectives:</i></b> The aim of this study was to assess how the lymph vessel density (LVD) in different histological types of thyroid tumors, and in their surrounding tissue, correlate with the presence of lymph node metastases (LNM) and tumor pathological features. <b><i>Methods:</i></b> Lymph vessels of papillary thyroid carcinomas (PTC), of the classical (CVPTC, <i>n</i> = 50) and follicular variants (FVPTC, <i>n</i> = 18), and medullary thyroid carcinomas (MTC, <i>n</i> = 34) were immunohistochemically stained against antigen D2-40. The stained area was quantified using a computerized morphometric analysis tool and correlated with the tumor pathological characteristics. <b><i>Results:</i></b> LVD within all analyzed thyroid tumor subtypes was significantly lower than in the surrounding thyroid tissues (<i>p</i> &lt; 0.001). Despite intratumoral LVD being significantly higher in CVPTC than in FVPTC, and peritumoral LVD being significantly higher in MTC than in PTC (<i>p</i> &lt; 0.05), no correlations were found between LVD (either intratumoral or peritumoral) and the presence of lymph node metastasis. <b><i>Conclusions:</i></b> As no LVD differences were found amongst thyroid tumors with or without LNM, dissemination is more likely to depend on the tumor ability to invade the abundant lymph vessel network of the surrounding thyroid tissue than on the ability of the tumor to promote de novo lymphangiogenesis.
DOI: 10.25387/g3.12795887
title: Supplemental Material for Bitarello and Mathieson, 2020

description: <b>File_S1 </b>is a pdf and contains 14 supplementary figures and their captions.<br><b>Table S1</b> is an excel spreadsheet and one caption sheet and 20 sheets with content, as described below:<br><b>Sheets 1-6:</b> Different SNP sets generated by clumping and their PRS values. Effect sizes from 360K European ancestry individuals from the UK Biobank. Data from genotype arrays. <br><b>Sheets 6-12:</b> Different SNP sets generated by clumping and their PRS values. Effect sizes estimated from ‘White British’ sibling pairs from the UK Biobank. Data from genotype arrays. <br><b>Sheet 13:</b> Different SNP sets generated by clumping and their PRS values. Data from imputed datasets. <br><b>Sheets 14-19: </b>Different SNP sets generated by clumping and their unweighted PRS values. <br><b>Sheet 20:</b> Difference between PRS values for 1000G super-populations (Africa, Europe) for different sets of SNPs.<br>