cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6634709
title: Pre-ovipositional and ovipositional behaviour of <i>Holaspulus tenuipes</i> (Berlese) (Parasitiformes: Mesostigmata: Parholaspididae) with notes on egg chorion, incubation, and hatching

description: Egg deposition in the soil mite <i>Holaspulus tenuipes</i> (Berlese, 1904) was observed with the use of continuous video-monitoring. The process was found to consist of four distinct phases. In Phase 1, the species performed pre-ovipositional activity prior to the egg being extruded from the genital opening. Phase 1 lasted approximately 7.5 min. Phase 2 involved egg extrusion followed with holding of the egg beneath the gnathosoma and lasted approximately 6.5 min. Egg deposition that occurs in Phase 3 lasted 10 sec. on average. Phase 4 involves covering the egg with substrate particles, the longest part of oviposition which lasted approximately 18 min. The egg possesses lamellar exochorion and two processes, one on each of the egg apexes. The average time of egg incubation was 3 days and 21 h. The hatching lasted 1 min. 43 sec. on average, the egg splitting was longitudinal and larva moved backward during hatch.
DOI: 10.6084/m9.figshare.6634709.v1
title: Pre-ovipositional and ovipositional behaviour of <i>Holaspulus tenuipes</i> (Berlese) (Parasitiformes: Mesostigmata: Parholaspididae) with notes on egg chorion, incubation, and hatching

description: Egg deposition in the soil mite <i>Holaspulus tenuipes</i> (Berlese, 1904) was observed with the use of continuous video-monitoring. The process was found to consist of four distinct phases. In Phase 1, the species performed pre-ovipositional activity prior to the egg being extruded from the genital opening. Phase 1 lasted approximately 7.5 min. Phase 2 involved egg extrusion followed with holding of the egg beneath the gnathosoma and lasted approximately 6.5 min. Egg deposition that occurs in Phase 3 lasted 10 sec. on average. Phase 4 involves covering the egg with substrate particles, the longest part of oviposition which lasted approximately 18 min. The egg possesses lamellar exochorion and two processes, one on each of the egg apexes. The average time of egg incubation was 3 days and 21 h. The hatching lasted 1 min. 43 sec. on average, the egg splitting was longitudinal and larva moved backward during hatch.
DOI: 10.6084/m9.figshare.6634313
title: Supplementary Material for: Abnormal Cochleovestibular Anatomy and Hearing Outcomes: Pediatric Patients with a Questionable Cochleovestibular Nerve Status May Benefit from Cochlear Implantation and/or Hearing Aids

description: <b><i>Objective:</i></b> Imaging characteristics and hearing outcomes in children with cochleovestibular or cochleovestibular nerve (CVN) abnormalities. <b><i>Study Design:</i></b> Retrospective, critical review. <b><i>Setting:</i></b> Tertiary referral academic center. <b><i>Patients:</i></b> Twenty-seven children with CVN abnormalities with magnetic resonance (MRI) and/or computed tomography (CT). <b><i>Study Intervention(s):</i></b> None. <b><i>Main Outcome Measure(s):</i></b> Determine the likely presence or absence of a CNV and auditory stimulation responses. <b><i>Results:</i></b> Two of 27 cases had unilateral hearing loss, and all others had bilateral loss. Eleven (46%) were identified with a disability or additional condition. Twenty-two (42%) ears received a cochlear implant (CI) and 9 ears (17%) experienced no apparent benefit from the device. MRI acquisition protocols were suboptimal for identification of the nerve in 22 (42%) ears. A likely CVN absence was associated with a narrow cochlear aperture and internal auditory canal and cochlear malformation. Thirteen (48%) children with an abnormal nerve exhibited normal cochleae on the same side. Hearing data were available for 30 ears, and 25 ears (83%) exhibited hearing with or without an assistive device. One child achieved closed set speech recognition with a hearing aid, another with a CI. One child achieved open set speech recognition with a CI. <b><i>Conclusions:</i></b> Current imaging cannot accurately characterize the functional status of the CVN or predict an assistive device benefit. Children who would have otherwise been denied a CI exhibited auditory responses after implantation. A CI should be considered in children with abnormal CVN. Furthermore, imaging acquisition protocols need standardization for clear temporal bone imaging.
DOI: 10.6084/m9.figshare.6634313.v1
title: Supplementary Material for: Abnormal Cochleovestibular Anatomy and Hearing Outcomes: Pediatric Patients with a Questionable Cochleovestibular Nerve Status May Benefit from Cochlear Implantation and/or Hearing Aids

description: <b><i>Objective:</i></b> Imaging characteristics and hearing outcomes in children with cochleovestibular or cochleovestibular nerve (CVN) abnormalities. <b><i>Study Design:</i></b> Retrospective, critical review. <b><i>Setting:</i></b> Tertiary referral academic center. <b><i>Patients:</i></b> Twenty-seven children with CVN abnormalities with magnetic resonance (MRI) and/or computed tomography (CT). <b><i>Study Intervention(s):</i></b> None. <b><i>Main Outcome Measure(s):</i></b> Determine the likely presence or absence of a CNV and auditory stimulation responses. <b><i>Results:</i></b> Two of 27 cases had unilateral hearing loss, and all others had bilateral loss. Eleven (46%) were identified with a disability or additional condition. Twenty-two (42%) ears received a cochlear implant (CI) and 9 ears (17%) experienced no apparent benefit from the device. MRI acquisition protocols were suboptimal for identification of the nerve in 22 (42%) ears. A likely CVN absence was associated with a narrow cochlear aperture and internal auditory canal and cochlear malformation. Thirteen (48%) children with an abnormal nerve exhibited normal cochleae on the same side. Hearing data were available for 30 ears, and 25 ears (83%) exhibited hearing with or without an assistive device. One child achieved closed set speech recognition with a hearing aid, another with a CI. One child achieved open set speech recognition with a CI. <b><i>Conclusions:</i></b> Current imaging cannot accurately characterize the functional status of the CVN or predict an assistive device benefit. Children who would have otherwise been denied a CI exhibited auditory responses after implantation. A CI should be considered in children with abnormal CVN. Furthermore, imaging acquisition protocols need standardization for clear temporal bone imaging.
DOI: 10.6084/m9.figshare.6634190
title: Supplementary Material for: Association of Platelet Count and Mean Platelet Volume with Overall Survival in Patients with Cirrhosis and Unresectable Hepatocellular Carcinoma

description: <b><i>Background:</i></b> Platelets have been reported to influence tumor biology and may promote metastasis. Traditionally, thrombocytopenia, a hallmark of cirrhosis, was associated with hepatocellular carcinoma (HCC) development. However, the impact of platelet count on outcome in patients with established HCC is not well studied. <b><i>Methods:</i></b> Outcomes of patients with cirrhosis diagnosed with HCC between 1995 and 2013 (derivation cohort) and 2000–2016 (validation cohort) who were not eligible for surgical treatment and did not receive antiplatelet therapy were retrospectively studied. Thrombocytopenia was defined as platelet count &lt; 150 g/L. High mean platelet volume (MPV) was defined as ≥median value of the respective cohort (derivation cohort: ≥11 fL; validation cohort: ≥10.6 fL). <b><i>Results:</i></b> Among 626 patients with unresectable HCC, thrombocytopenia was present in 378 (60.4%) and was associated with favorable baseline tumor characteristics: lower diameter of the largest nodule (5.6 ± 3.2 vs. 7.6 ± 4.2 cm), less extrahepatic spread (9.5 vs. 20.2%, both <i>p</i> &lt; 0.001), less macrovascular invasion (21.2 vs. 31.0%, <i>p</i> = 0.005), and lower BCLC stages (63.0 vs. 73.4% BCLC C/D; <i>p</i> = 0.007) as compared to patients with normal platelet count. On univariate analysis, thrombocytopenia and larger MPV were associated with longer overall survival (OS) (thrombocytopenia: median OS [95% CI], 11.5 [9.3–13.8] vs. 5.5 [3.8–7.1] months; <i>p</i> = 0.001; MPV ≥11 fL: 11.7 [9.1–14.2] vs. 6.0 [4.4–7.6] months; <i>p</i> &lt; 0.001). In multivariate analysis, the combined variable of thrombocytopenia and larger MPV was independently associated with longer OS (HR [95% CI], 0.80 [0.65–0.98]; <i>p</i> = 0.029). These results were confirmed in an independent external validation cohort of 525 patients with cirrhosis and HCC. Again, patients with thrombocytopenia and high MPV had significantly longer OS (15.3 [11.7–18.9] vs. 9.3 [7.4–11.2] months; <i>p</i> &lt; 0.001). <b><i>Conclusions:</i></b> Thrombocytopenia and higher MPV are associated with better outcome in patients with advanced HCC. These findings may prompt further clinical research on additive antiplatelet therapy in the prevention and management of HCC.
DOI: 10.6084/m9.figshare.6634136
title: Supplementary Material for: Development of a PD-L1-Expressing Orthotopic Liver Cancer Model: Implications for Immunotherapy for Hepatocellular Carcinoma

description: <b><i>Background:</i></b> Anti-programmed cell death-1(anti-PD1) treatment has shown promising antitumor efficacy in patients with advanced hepatocellular carcinoma (HCC). This study sought to explore the functional significance of programmed death ligand-1 (PD-L1) expression in tumor cells in the tumor microenvironment. <b><i>Methods:</i></b> The mouse liver cancer cell line BNL-MEA was transfected with PD-L1 plasmids and stable clones expressing PD-L1 were selected. An orthotopic HCC model was generated by implanting the cells into the subcapsular space of BALB/c mice. Cell growth features were measured by proliferation assay, colony formation, flow cytometry (in vitro), ultrasonography, and animal survival (in vivo). The changes in T-cell function were examined by cytokine assay, expression of T-cell related genes, and flow cytometry. The efficacy of anti-PD1 therapy was compared between the parental and PD-L1-expressing tumors. <b><i>Results:</i></b> PD-L1 expression did not affect growth characteristics of BNL-MEA cells but downregulated the expression of genes related to T-cell activation in the tumor microenvironment. Co-culture of PD-L1-expressing BNL-MEA cells with CD8+ T cells reduced T-cell proliferation and expression of cytokines IFNγ and TNFα. Tumors with PD-L1 expression showed better response to anti-PD1 therapy and depletion of CD8+ T cells abolished the antitumor effect. The difference in treatment response between parental and PD-L1-expressing tumors disappeared when a combination of anti-PD1 and sorafenib was given. <b><i>Conclusions:</i></b> PD-L1 expression in HCC cells may inhibit T-cell function in the liver tumor microenvironment. Anti-PD1 therapy appeared more effective in PD-L1-expressing than nonexpressing tumors, but the difference was diminished by the addition of sorafenib.
DOI: 10.6084/m9.figshare.6634001
title: Macrophage phenotype in dense collagen

description: Macrophage phenotype in dense collagen.
DOI: 10.6084/m9.figshare.6634001.v1
title: Macrophage phenotype in dense collagen

description: Macrophage phenotype in dense collagen.
DOI: 10.6084/m9.figshare.6633998
title: Macrophage phenotype in fibrillar collagen

description: Macrophage phenotype in fibrillar collagen.
DOI: 10.6084/m9.figshare.6633998.v1
title: Macrophage phenotype in fibrillar collagen

description: Macrophage phenotype in fibrillar collagen.
DOI: 10.6084/m9.figshare.6633983
title: MIProblems: A repository of multiple instance learning datasets

description: This repository contains the multiple instance learning datasets previously stored at miproblems.org. As I am now longer maintaining the website, I moved the datasets to Figshare. A detailed description of the files is found in readme.pdf<br> If you use these datasets, please cite this Figshare resource rather than linking to miproblems.org, which will be offline soon.
DOI: 10.6084/m9.figshare.6633506
title: E. coli predictions

description: About this dataset: These are the most reliable 40,000 PPI predictions for E. Coli. It is a CSV file.<br>Motivation: Protein-protein interactions (PPIs) play a key role in many cellular processes. Most annotations of PPIs mix experimental and computational data. The mix optimizes coverage, but obfuscates the annotation origin. Some resources excel at focusing on reliable experimental data. Here, we focused on new pairs of interacting proteins for several model organisms based solely on sequence-based prediction methods. <br>Results: We extracted reliable experimental data about which proteins interact (binary) for eight diverse model organisms from public databases, namely from Escherichia coli, Schizosaccharomyces pombe, Plasmodium falciparum, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus, Arabidopsis thaliana, and for the previously used Homo sapiens and Saccharomyces cerevisiae. Those data were the base to develop a PPI prediction method for each model organism. The method used evolutionary information through a profile-kernel Support Vector Machine (SVM). With the resulting eight models, we predicted all possible protein pairs in each organism and made the top predictions available through a web application. Almost all of the PPIs made available were predicted between proteins that have not been observed in any interaction, in particular for less well-studied organisms. Thus, our work complements existing resources and is particularly helpful for designing experiments because of its uniqueness. Experimental annotations and computational predictions are strongly influenced by the fact that some proteins have many partners and others few. To optimize machine learning, the newly methods explicitly ignored such a network-structure. This might be another strength of our approach. The database interface representing our results is accessible from https://rostlab.org/services/ppipair/. <br>Please cite us when you are using this data:<pre>@article{tran2018profppidb, title={ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes}, author={Tran, Linh and Hamp, Tobias and Rost, Burkhard}, journal={bioRxiv}, pages={332510}, year={2018}, publisher={Cold Spring Harbor Laboratory} }</pre>
DOI: 10.6084/m9.figshare.6633494
title: Integrated analysis of lncRNAs and mRNA expression profiles reveals the potential role of lncRNAs in different bovine lactation stages

description: Long non-coding RNAs (lncRNAs) play a critical role in mammary development and breast cancer biology. Despite their important role in the mammary gland, little is known on the roles of lncRNAs in bovine lactation, particularly regarding the molecular processes underlying it. To characterize the role of lncRNAs in bovine lactation, four samples of Holstein cow mammary gland tissue at peak and late lactation stages were examined after biopsy. We then profiled the transcriptome of mammary gland using RNA sequencing technology. Further, functional lncRNA-mRNA co-expression pairs were constructed to infer the function of lncRNAs using a generalized linear model, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Over 1000 putative lncRNAs were identified, 117 of which were differentially expressed between peak and late lactation stages. Bovine lncRNAs were shorter, with fewer exon numbers, and expressed at significantly lower levels than protein-coding genes. Seventy-two differentially expressed lncRNAs (DE-lncRNAs) were co-expressed with 340 different protein-coding genes. The KEGG pathway analysis showed that target mRNAs for DE-lncRNAs were mainly related to lipid and glucose metabolism, including the peroxisome proliferator-activated receptors (PPAR) and 5' adenosine monophosphate-activated protein kinase (AMPK) signaling pathways. Further bioinformatics and integrative analyses revealed that 12 DE-lncRNAs potentially played important roles in bovine lactation. Our findings provide a valuable resource for future bovine transcriptome studies, facilitate the understanding of bovine lactation biology, and offer functional information for cattle lactation.Keywords: Long non-coding RNA, bovine lactation, mammary gland, co-expression, RNA sequencing
DOI: 10.6084/m9.figshare.6633485
title: A. thaliana predictions

description: About this dataset: These are the most reliable 500,000 PPI predictions for A. thaliana. It is a CSV file.<br>Motivation: Protein-protein interactions (PPIs) play a key role in many cellular processes. Most annotations of PPIs mix experimental and computational data. The mix optimizes coverage, but obfuscates the annotation origin. Some resources excel at focusing on reliable experimental data. Here, we focused on new pairs of interacting proteins for several model organisms based solely on sequence-based prediction methods. <br>Results: We extracted reliable experimental data about which proteins interact (binary) for eight diverse model organisms from public databases, namely from Escherichia coli, Schizosaccharomyces pombe, Plasmodium falciparum, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus, Arabidopsis thaliana, and for the previously used Homo sapiens and Saccharomyces cerevisiae. Those data were the base to develop a PPI prediction method for each model organism. The method used evolutionary information through a profile-kernel Support Vector Machine (SVM). With the resulting eight models, we predicted all possible protein pairs in each organism and made the top predictions available through a web application. Almost all of the PPIs made available were predicted between proteins that have not been observed in any interaction, in particular for less well-studied organisms. Thus, our work complements existing resources and is particularly helpful for designing experiments because of its uniqueness. Experimental annotations and computational predictions are strongly influenced by the fact that some proteins have many partners and others few. To optimize machine learning, the newly methods explicitly ignored such a network-structure. This might be another strength of our approach. The database interface representing our results is accessible from https://rostlab.org/services/ppipair/.<br>Please cite us when you are using this data:<pre>@article{tran2018profppidb, title={ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes}, author={Tran, Linh and Hamp, Tobias and Rost, Burkhard}, journal={bioRxiv}, pages={332510}, year={2018}, publisher={Cold Spring Harbor Laboratory} }</pre>
DOI: 10.6084/m9.figshare.6633485.v1
title: A. thaliana predictions

description: About this dataset: These are the most reliable 500,000 PPI predictions for A. thaliana. It is a CSV file.<br>Motivation: Protein-protein interactions (PPIs) play a key role in many cellular processes. Most annotations of PPIs mix experimental and computational data. The mix optimizes coverage, but obfuscates the annotation origin. Some resources excel at focusing on reliable experimental data. Here, we focused on new pairs of interacting proteins for several model organisms based solely on sequence-based prediction methods. <br>Results: We extracted reliable experimental data about which proteins interact (binary) for eight diverse model organisms from public databases, namely from Escherichia coli, Schizosaccharomyces pombe, Plasmodium falciparum, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus, Arabidopsis thaliana, and for the previously used Homo sapiens and Saccharomyces cerevisiae. Those data were the base to develop a PPI prediction method for each model organism. The method used evolutionary information through a profile-kernel Support Vector Machine (SVM). With the resulting eight models, we predicted all possible protein pairs in each organism and made the top predictions available through a web application. Almost all of the PPIs made available were predicted between proteins that have not been observed in any interaction, in particular for less well-studied organisms. Thus, our work complements existing resources and is particularly helpful for designing experiments because of its uniqueness. Experimental annotations and computational predictions are strongly influenced by the fact that some proteins have many partners and others few. To optimize machine learning, the newly methods explicitly ignored such a network-structure. This might be another strength of our approach. The database interface representing our results is accessible from https://rostlab.org/services/ppipair/.<br>Please cite us when you are using this data:<pre>@article{tran2018profppidb, title={ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes}, author={Tran, Linh and Hamp, Tobias and Rost, Burkhard}, journal={bioRxiv}, pages={332510}, year={2018}, publisher={Cold Spring Harbor Laboratory} }</pre>
DOI: 10.6084/m9.figshare.6633452
title: C. elegans predictions

description: About this dataset: These are the most reliable 200,000 PPI predictions for C. elegans. It is a CSV file.<br>Motivation: Protein-protein interactions (PPIs) play a key role in many cellular processes. Most annotations of PPIs mix experimental and computational data. The mix optimizes coverage, but obfuscates the annotation origin. Some resources excel at focusing on reliable experimental data. Here, we focused on new pairs of interacting proteins for several model organisms based solely on sequence-based prediction methods. <br>Results: We extracted reliable experimental data about which proteins interact (binary) for eight diverse model organisms from public databases, namely from Escherichia coli, Schizosaccharomyces pombe, Plasmodium falciparum, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus, Arabidopsis thaliana, and for the previously used Homo sapiens and Saccharomyces cerevisiae. Those data were the base to develop a PPI prediction method for each model organism. The method used evolutionary information through a profile-kernel Support Vector Machine (SVM). With the resulting eight models, we predicted all possible protein pairs in each organism and made the top predictions available through a web application. Almost all of the PPIs made available were predicted between proteins that have not been observed in any interaction, in particular for less well-studied organisms. Thus, our work complements existing resources and is particularly helpful for designing experiments because of its uniqueness. Experimental annotations and computational predictions are strongly influenced by the fact that some proteins have many partners and others few. To optimize machine learning, the newly methods explicitly ignored such a network-structure. This might be another strength of our approach. The database interface representing our results is accessible from https://rostlab.org/services/ppipair/.<br>Please cite us when you are using this data:<pre>@article{tran2018profppidb, title={ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes}, author={Tran, Linh and Hamp, Tobias and Rost, Burkhard}, journal={bioRxiv}, pages={332510}, year={2018}, publisher={Cold Spring Harbor Laboratory} }</pre>