cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25204064
title: Data from Quantitative description of the phase separation behavior of the multivalentSLP65-CIN85 complex

description: The dataset contains seven folders:LASSI_run_example - A set of LASSI simulations of the molecules SLP65(1-330) and CIN85-ABC sampling a range of concentration by varying the BOX_SIZE parameter in the param.key file. For prior pair distribution calculation, the interaction between the molecules is omitted by setting the energy terms to zero in the energy.dat file. In this example, the natural linker length is scaled by 1/4 as defined in the structure.prm file.LASSI_templates - Templates with defined parameters to vary BOX_SIZE (param.key), linker length (structure.prm) and interaction energy table (energy.prm) that allows to simulate SLP65 and CIN85 constructs, designed to have different binding affinities. The folder contains three python (Python 3.7.6) scripts: "CalculateGDIP_from_RDF_dat_file.py" to calculate the GDIPs of a set of simulations. "extractPercolation.py", a text parsing script, to simply obtain the percolation values of each cycle of a simulation. "Plot_FigS12.py" to plot the GDIP parameter as shown in Fig. S12.Fluorescence_Images - Fluorescent microscopy images of protein mixtures (SLP65/CIN85 constructs) for calculation of the dispersion index and images with 5x zoom for printed figures. Images are recorded as a z-stack and processed in ImageJ (v1.52a) by applying an intensity threshold of 55. The analyzed image is indicated in the file name, (e.g. im3 for z-stack image number 3).Fluorescence_Images_withSUV - Fluorescent microscopy z-stack images of protein-vesicle mixtures (SLP65/CIN85 constructs + SUV) for calculation of the dispersion index and images with 5x zoom for visualizing figures.Titration_ITC_peptides - VP-ITC MicroCalorimeter raw files of titration of individual SLP65 peptides to individual SH3 domains.Titration_ITC_protein_constructs - VP-ITC MicroCalorimeter raw files of titrations of weak and strong binding protein constructs.Titrations_NMR - Raw files NMR spectra (Topspin 4.06, Bruker) of titrations of SLP65 peptides to individual domains. For analysis, peaklists for 1D CS analysis or processed spectra for 2D lineshape analysis are given.
DOI: 10.6084/m9.figshare.25204064.v1
title: Data from Quantitative description of the phase separation behavior of the multivalentSLP65-CIN85 complex

description: The dataset contains seven folders:LASSI_run_example - A set of LASSI simulations of the molecules SLP65(1-330) and CIN85-ABC sampling a range of concentration by varying the BOX_SIZE parameter in the param.key file. For prior pair distribution calculation, the interaction between the molecules is omitted by setting the energy terms to zero in the energy.dat file. In this example, the natural linker length is scaled by 1/4 as defined in the structure.prm file.LASSI_templates - Templates with defined parameters to vary BOX_SIZE (param.key), linker length (structure.prm) and interaction energy table (energy.prm) that allows to simulate SLP65 and CIN85 constructs, designed to have different binding affinities. The folder contains three python (Python 3.7.6) scripts: "CalculateGDIP_from_RDF_dat_file.py" to calculate the GDIPs of a set of simulations. "extractPercolation.py", a text parsing script, to simply obtain the percolation values of each cycle of a simulation. "Plot_FigS12.py" to plot the GDIP parameter as shown in Fig. S12.Fluorescence_Images - Fluorescent microscopy images of protein mixtures (SLP65/CIN85 constructs) for calculation of the dispersion index and images with 5x zoom for printed figures. Images are recorded as a z-stack and processed in ImageJ (v1.52a) by applying an intensity threshold of 55. The analyzed image is indicated in the file name, (e.g. im3 for z-stack image number 3).Fluorescence_Images_withSUV - Fluorescent microscopy z-stack images of protein-vesicle mixtures (SLP65/CIN85 constructs + SUV) for calculation of the dispersion index and images with 5x zoom for visualizing figures.Titration_ITC_peptides - VP-ITC MicroCalorimeter raw files of titration of individual SLP65 peptides to individual SH3 domains.Titration_ITC_protein_constructs - VP-ITC MicroCalorimeter raw files of titrations of weak and strong binding protein constructs.Titrations_NMR - Raw files NMR spectra (Topspin 4.06, Bruker) of titrations of SLP65 peptides to individual domains. For analysis, peaklists for 1D CS analysis or processed spectra for 2D lineshape analysis are given.
DOI: 10.6084/m9.figshare.14287396.v1
title: Oxidative stress and antioxidant defense in detoxification systems of snake venom-induced toxicity

description: Abstract Background: Snakebites remain a major life-threatening event worldwide. It is still difficult to make a positive identification of snake species by clinicians in both Western medicine and Chinese medicine. The main reason for this is a shortage of diagnostic biomarkers and lack of knowledge about pathways of venom-induced toxicity. In traditional Chinese medicine, snakebites are considered to be treated with wind, fire, and wind-fire toxin, but additional studies are required. Methods: Cases of snakebite seen at the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine were grouped as follows: fire toxin - including four cases of bites by Agkistrodon acutus and three bites by Trimeresurus stejnegeri - and wind-fire toxin - four cases of bites by vipers and three bites by cobras. Serum protein quantification was performed using LC-MS/MS. Differential abundance proteins (DAPs) were identified from comparison of snakebites of each snake species and healthy controls. The protein interaction network was constructed using STITCH database. Results: Principal component analysis and hierarchical clustering of 474 unique proteins exhibited protein expression profiles of wind-fire toxins that are distinct from that of fire toxins. Ninety-three DAPs were identified in each snakebite subgroup as compared with healthy control, of which 38 proteins were found to have significantly different expression levels and 55 proteins displayed no expression in one subgroup, by subgroup comparison. GO analysis revealed that the DAPs participated in bicarbonate/oxygen transport and hydrogen peroxide catabolic process, and affected carbon-oxygen lyase activity and heme binding. Thirty DAPs directly or indirectly acted on hydrogen peroxide in the interaction network of proteins and drug compounds. The network was clustered into four groups: lipid metabolism and transport; IGF-mediated growth; oxygen transport; and innate immunity. Conclusions: Our results show that the pathways of snake venom-induced toxicity may form a protein network of antioxidant defense by regulating oxidative stress through interaction with hydrogen peroxide.
DOI: 10.6084/m9.figshare.10094345
title: MOESM6 of The long non-coding RNA lncRNA973 is involved in cotton response to salt stress

description: Additional file 6: Table S1. lncRNA973 co-expressed protein-coding genes information. (XLS 3055 kb)
DOI: 10.6084/m9.figshare.10094345.v1
title: MOESM6 of The long non-coding RNA lncRNA973 is involved in cotton response to salt stress

description: Additional file 6: Table S1. lncRNA973 co-expressed protein-coding genes information. (XLS 3055 kb)
DOI: 10.6084/m9.figshare.21103036.v1
title: Deciphering the lncRNA and mRNA profiles of Min pig backfat after acute cold stress

description: Cold stress can promote fat metabolism and reduce fat deposition. The present study compared differentially expressed (DE) lncRNAs and mRNAs in the subcutaneous back fat of Min pigs subjected to 24 h acute cold stress. Transcriptome sequencing was used to identify DE lncRNAs and mRNAs. A lncRNA mRNA co expression network was constructed using the confirmed lncRNAs. GO and KEGG analyses were performed to investigate the biological processes involved in the response to acute cold stress. A total of 166 DE lncRNAs and 269 DE mRNAs were found. Several genes such as ANGPTL4, KLF11 and NUPR1 were related to lipid metabolism. Interferon stimulating genes (ISGS) such as RSAD2, ISG20, ISG15, DDX60, MX2, MX1 and IFI6 were all significantly up-regulated. In addition, genes related to blood flow, respiration, and oxidative stress were also up-regulated. Many terms related to defense response to a virus were found in the GO annotation. A lncRNA mRNA co expression network comprising 46 specific mRNAs and the top 10 up-regulated DE lncRNAs was constructed. According to the results, the interaction between lncRNAs and mRNAs was complex. This study provides genome-wide gene and lncRNA expression profiles in adipose tissue of pigs after acute cold stress.
DOI: 10.6084/m9.figshare.10094351
title: MOESM2 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 2: Table S1. Descriptions of training data used in pTuneos Pre&RecNeo.
DOI: 10.6084/m9.figshare.10094351.v1
title: MOESM2 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 2: Table S1. Descriptions of training data used in pTuneos Pre&RecNeo.
DOI: 10.6084/m9.figshare.10094354
title: MOESM7 of The long non-coding RNA lncRNA973 is involved in cotton response to salt stress

description: Additional file 7: Table S2. Gene-specific primers and probes used in the research. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.10094354.v1
title: MOESM7 of The long non-coding RNA lncRNA973 is involved in cotton response to salt stress

description: Additional file 7: Table S2. Gene-specific primers and probes used in the research. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.7997204
title: Additional file 1: of Revealing the dominant long noncoding RNAs responding to the infection with Colletotrichum gloeosporioides in Hevea brasiliensis

description: Table S1. Sample information for our datasets and datasets from public databases. Table S2. 115 miRNA of rubber tree used in our study. Table S3. Descriptions of the tools and databases used in the study. Table S4. Functional annotations for identified hub responsive coding genes. (XLS 58 kb)
DOI: 10.6084/m9.figshare.10094357
title: MOESM3 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 3: Table S2. Experimentally confirmed immunogenic and non-immunogenic peptides in melanoma from Carreno et al. (ref. [15]).
DOI: 10.6084/m9.figshare.7997204.v1
title: Additional file 1: of Revealing the dominant long noncoding RNAs responding to the infection with Colletotrichum gloeosporioides in Hevea brasiliensis

description: Table S1. Sample information for our datasets and datasets from public databases. Table S2. 115 miRNA of rubber tree used in our study. Table S3. Descriptions of the tools and databases used in the study. Table S4. Functional annotations for identified hub responsive coding genes. (XLS 58 kb)
DOI: 10.6084/m9.figshare.10094357.v1
title: MOESM3 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 3: Table S2. Experimentally confirmed immunogenic and non-immunogenic peptides in melanoma from Carreno et al. (ref. [15]).
DOI: 10.6084/m9.figshare.10094360
title: MOESM4 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 4: Table S3. A. Clinical information and neoantigen information of stage III/IV stomach adenocarcinoma (n=166). B. Clinical information and neoantigen information of stage III/IV lung adenocarcinoma (n=101). C. Clinical information and neoantigen information of stage III/IV cutaneous melanoma (n=191).
DOI: 10.6084/m9.figshare.10094360.v1
title: MOESM4 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 4: Table S3. A. Clinical information and neoantigen information of stage III/IV stomach adenocarcinoma (n=166). B. Clinical information and neoantigen information of stage III/IV lung adenocarcinoma (n=101). C. Clinical information and neoantigen information of stage III/IV cutaneous melanoma (n=191).
DOI: 10.6084/m9.figshare.18482032.v1
title: Additional file 12 of Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

description: Additional file 12: Original data of inner testing set of SEER.
DOI: 10.6084/m9.figshare.25204145
title: Flower bud fpkm of Chrysanthemum morifolium

description: Flower bud fpkm of Chrysanthemum morifolium
DOI: 10.6084/m9.figshare.25204145.v1
title: Flower bud fpkm of Chrysanthemum morifolium

description: Flower bud fpkm of Chrysanthemum morifolium
DOI: 10.6084/m9.figshare.18482035.v1
title: Additional file 13 of Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

description: Additional file 13: Original data of inner training set of SEER.
DOI: 10.6084/m9.figshare.10094366
title: MOESM5 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 5: Table S4. A list of 13-gene MHC II signature which associated with immune signature.
DOI: 10.6084/m9.figshare.10094366.v1
title: MOESM5 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 5: Table S4. A list of 13-gene MHC II signature which associated with immune signature.
DOI: 10.6084/m9.figshare.10094372
title: MOESM6 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 6: Table S5. A. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_21. B. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_38. C. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_218. D. Candidate neoepitopes identified using MuPeXI from MEL_21 (only retain neoantigen priority score&gt;0). E. Candidate neoepitopes identified using MuPeXI from MEL_38 (only retain neoantigen priority score&gt;0). F. Candidate neoepitopes identified using MuPeXI from MEL_218 (only retain neoantigen priority score&gt;0). G. Candidate neoepitopes identified using neopepsee from MEL_21 (only retain neoantigen predition level is high or medium). H. Candidate neoepitopes identified using neopepsee from MEL_38 (only retain neoantigen predition level is high or medium). I. Candidate neoepitopes identified using neopepsee from MEL_218 (only retain neoantigen predition level is high or medium).
DOI: 10.6084/m9.figshare.10094372.v1
title: MOESM6 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 6: Table S5. A. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_21. B. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_38. C. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_218. D. Candidate neoepitopes identified using MuPeXI from MEL_21 (only retain neoantigen priority score&gt;0). E. Candidate neoepitopes identified using MuPeXI from MEL_38 (only retain neoantigen priority score&gt;0). F. Candidate neoepitopes identified using MuPeXI from MEL_218 (only retain neoantigen priority score&gt;0). G. Candidate neoepitopes identified using neopepsee from MEL_21 (only retain neoantigen predition level is high or medium). H. Candidate neoepitopes identified using neopepsee from MEL_38 (only retain neoantigen predition level is high or medium). I. Candidate neoepitopes identified using neopepsee from MEL_218 (only retain neoantigen predition level is high or medium).
DOI: 10.6084/m9.figshare.10094381
title: MOESM7 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 7: Table S6. A. Refined neoepitope rank obtained by pTuneos RefinedNeo of MEL_38. B. Refined neoepitope rank obtained by pTuneos RefinedNeo of MEL_218.
DOI: 10.6084/m9.figshare.10094381.v1
title: MOESM7 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 7: Table S6. A. Refined neoepitope rank obtained by pTuneos RefinedNeo of MEL_38. B. Refined neoepitope rank obtained by pTuneos RefinedNeo of MEL_218.
DOI: 10.6084/m9.figshare.14287626
title: Knowledge of and attitudes toward COVID-19 among parents of child dental patients during the outbreak

description: Abstract: The aim of this study was to evaluate the knowledge of and attitudes toward coronavirus disease 2019 (COVID-19) among the parents of child dental patients in Shenzhen during the outbreak. A structured questionnaire containing 10 questions was used, and each question had 2 or 3 possible answers. The parents of children (aged 0-14 years) who visited the dental department of our hospital last year were eligible to participate in this study. A total of 148 parents were interviewed by telephone in February 2020 by research staff. A total of 94.59% of the parents said they paid high attention to COVID-19 and explained it to their children; 66.22% thought the dental department environment was more dangerous than other public places; 91.89% believed the dental department had a higher risk of virus infection; and 83.78% said they would take their children to a dental department if the children had a severe toothache. Approximately 81.08% of the parents expressed confidence after we informed them about the preventive measures taken in the dental department to ensure safe treatment for their children. In conclusion, all parents were concerned about COVID-19, and most of them had talked about it with their children often. In addition, a considerable percentage of them would not take their children to the dental department even if they had severe dental pain and thought that the dental environment could be more dangerous than other environments. More information about this topic should be delivered to this population.
DOI: 10.6084/m9.figshare.10094390
title: MOESM8 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 8: Table S7. Experimentally confirmed immunogenic and non-immunogenic peptides in Zacharakis et al., Tran et al. and Gros et al.
DOI: 10.6084/m9.figshare.10094390.v1
title: MOESM8 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 8: Table S7. Experimentally confirmed immunogenic and non-immunogenic peptides in Zacharakis et al., Tran et al. and Gros et al.
DOI: 10.6084/m9.figshare.14287626.v1
title: Knowledge of and attitudes toward COVID-19 among parents of child dental patients during the outbreak

description: Abstract: The aim of this study was to evaluate the knowledge of and attitudes toward coronavirus disease 2019 (COVID-19) among the parents of child dental patients in Shenzhen during the outbreak. A structured questionnaire containing 10 questions was used, and each question had 2 or 3 possible answers. The parents of children (aged 0-14 years) who visited the dental department of our hospital last year were eligible to participate in this study. A total of 148 parents were interviewed by telephone in February 2020 by research staff. A total of 94.59% of the parents said they paid high attention to COVID-19 and explained it to their children; 66.22% thought the dental department environment was more dangerous than other public places; 91.89% believed the dental department had a higher risk of virus infection; and 83.78% said they would take their children to a dental department if the children had a severe toothache. Approximately 81.08% of the parents expressed confidence after we informed them about the preventive measures taken in the dental department to ensure safe treatment for their children. In conclusion, all parents were concerned about COVID-19, and most of them had talked about it with their children often. In addition, a considerable percentage of them would not take their children to the dental department even if they had severe dental pain and thought that the dental environment could be more dangerous than other environments. More information about this topic should be delivered to this population.
DOI: 10.6084/m9.figshare.18482038
title: Additional file 14 of Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

description: Additional file 14: Original data of outer validation set from Xijing hospital.
DOI: 10.6084/m9.figshare.10094399
title: MOESM9 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 9: Table S8. A. Candidate neoepitopes identified using pTuneos from 7 samples in Zacharakis et al., Tran et al. and Gros et al. B. Candidate neoepitopes identified using MuPeXI from 7 samples in Zacharakis et al., Tran et al. and Gros et al. (only retain neoantigen priority score&gt;0). C. Candidate neoepitopes identified using neopepsee from 7 samples in Zacharakis et al., Tran et al. and Gros et al. (only retain neoantigen predition level is high or medium).
DOI: 10.6084/m9.figshare.10094399.v1
title: MOESM9 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

description: Additional file 9: Table S8. A. Candidate neoepitopes identified using pTuneos from 7 samples in Zacharakis et al., Tran et al. and Gros et al. B. Candidate neoepitopes identified using MuPeXI from 7 samples in Zacharakis et al., Tran et al. and Gros et al. (only retain neoantigen priority score&gt;0). C. Candidate neoepitopes identified using neopepsee from 7 samples in Zacharakis et al., Tran et al. and Gros et al. (only retain neoantigen predition level is high or medium).
DOI: 10.6084/m9.figshare.20054962
title: Outcomes and risk factors of hemorrhagic cystitis in pediatric allogeneic hematopoietic stem cell transplantation recipients using different graft source and condition with severe aplastic anemia

description: Hemorrhagic cystitis (HC) is a severe complication of allo-HSCT, characterized by irritative symptoms of the urinary tract and a higher morbidity rate. The risk factors and prognosis of HC are still unclear. The objective of this study is to identify risk factors and outcomes to improve treatment in pediatric SAA patients undergoing HSCTs in the Children's Hospital of Soochow University. A total of 97 SAA patients as a cohort were enrolled from 2010 to 2019 in the Children's Hospital of Soochow University and a number of factors related to HC and outcomes were analysed. In all transplants (except UCBT), patients received a combination of G-CSF stimulated bone marrow (BM) and peripheral blood stem cell (PBSC). The minimum number of CD34 + cells is 5 × 10<sup>6</sup> cells/kg. Mononuclear cells dose (MNC, cut off: 8.53 × 10<sup>8</sup>/kg) and grade II–IV acute graft versus host disease (aGVHD) were identified as independent risk factors for HC. Patients without HC had better overall survival (OS) than with HC (No HC: 98.6%±1.4% vs HC: 87.4% ± 6.8%, <i>p</i> = 0.03). We concluded that aGVHD and MNC dose in graft might play an important role in the development of HC in pediatric SAA patients undergoing allo-HSCT. HC is also a key complication affecting the prognosis of children with SAA after allo-HSCT.