cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.j00052.00035
title: data set of article‘Working memory representation of task-irrelevant emotional face can capture attention：effect of perceptual load’
title: 文章“无关情绪面孔工作记忆表征对注意的捕获—知觉负载的影响”数据集

description: This data set is generated by the Eprime software, which collects 10 people's ratings of materials and 52 people's keystroke data.This data set consists of three parts. The first part is the material score, including the potency and arousal scores of 256 pictures selected by 10 people; The second part is the error rate data, including the search error rate and recognition error rate (percentage) under all conditions of Experiment 1 and Experiment 2. A and B in the table represent emotion type and memory interference face relationship respectively; The third part is the reaction time data, including the reaction time (in milliseconds) of the high and low speed groups in Experiment 1, Experiment 2 and Experiment 1 under all conditions. A and B in the table represent emotion type and memory interference face relationship respectively.
description: This data set is generated by the Eprime software, which collects 10 people's ratings of materials and 52 people's keystroke data.This data set consists of three parts. The first part is the material score, including the potency and arousal scores of 256 pictures selected by 10 people; The second part is the error rate data, including the search error rate and recognition error rate (percentage) under all conditions of Experiment 1 and Experiment 2. A and B in the table represent emotion type and memory interference face relationship respectively; The third part is the reaction time data, including the reaction time (in milliseconds) of the high and low speed groups in Experiment 1, Experiment 2 and Experiment 1 under all conditions. A and B in the table represent emotion type and memory interference face relationship respectively.
DOI: 10.57760/sciencedb.03180
title: Sequencing data on gamma-aminobutyric acid acts as a soil amendment to enhance cadmium phytoextraction by Coreopsis grandiflora
title: Sequencing data on gamma-aminobutyric acid acts as a soil amendment to enhance cadmium phytoextraction by Coreopsis grandiflora

description: The sequencing data were obtained by 16S sequencing after different concentrations of exogenous GABA were added to the cadmium-contaminated soil to extract DNA from the rhizosphere soil of Coreopsis grandiflora, in order to understand how plant rhizosphere soil bacteria respond to changes in soil microenvironment, thus affecting plant growth and uptake of cadmium.
description: The sequencing data were obtained by 16S sequencing after different concentrations of exogenous GABA were added to the cadmium-contaminated soil to extract DNA from the rhizosphere soil of Coreopsis grandiflora, in order to understand how plant rhizosphere soil bacteria respond to changes in soil microenvironment, thus affecting plant growth and uptake of cadmium.
DOI: 10.57760/sciencedb.03186
title: Polarities-Induced Weakening of Molecular Interaction and Formation of Nanocellulose with Different Dimensions
title: Polarities-Induced Weakening of Molecular Interaction and Formation of Nanocellulose with Different Dimensions

description: Additives with different polarities were used in the fabrication of nanocellulose by ball-milling. It was found that the dimension of cellulose nanomaterials could be controlled by the additive polarity. Because there are hydrophilic and hydrophobic crystal planes, additives with different polarities may permeate into the interface between the crystal planes with different additive hydrophilicities. It was suggested that the polar additive molecules could migrate into the interface between the hydrophilic crystalline faces (110 and 11̅0) and weaken the hydrogen bonding interaction during milling, which results in slippage and peeling along the 110 and 11̅0 planes and eventually allows one dimensional cellulose nanofibers. On the other hand, nonpolar and medium-polar additive molecules can only permeate into the interface between the hydrophobic crystalline face (200 plane) and weaken the hydrophobic interaction during milling, which results in the slippage and peeling along 200 planes and the formation of two dimensional cellulose nanosheets. The results of this study may facilitate the regulated and controllable fabrication of micro-/nanocellulose with different morphologies and dimensions.
description: Additives with different polarities were used in the fabrication of nanocellulose by ball-milling. It was found that the dimension of cellulose nanomaterials could be controlled by the additive polarity. Because there are hydrophilic and hydrophobic crystal planes, additives with different polarities may permeate into the interface between the crystal planes with different additive hydrophilicities. It was suggested that the polar additive molecules could migrate into the interface between the hydrophilic crystalline faces (110 and 11̅0) and weaken the hydrogen bonding interaction during milling, which results in slippage and peeling along the 110 and 11̅0 planes and eventually allows one dimensional cellulose nanofibers. On the other hand, nonpolar and medium-polar additive molecules can only permeate into the interface between the hydrophobic crystalline face (200 plane) and weaken the hydrophobic interaction during milling, which results in the slippage and peeling along 200 planes and the formation of two dimensional cellulose nanosheets. The results of this study may facilitate the regulated and controllable fabrication of micro-/nanocellulose with different morphologies and dimensions.
DOI: 10.57760/sciencedb.03194
title: raw data of Predicting Thermodynamic Stability of Magnesium Alloys in Machine Learning
title: raw data of Predicting Thermodynamic Stability of Magnesium Alloys in Machine Learning

description: raw data of Predicting Thermodynamic Stability of Magnesium Alloys in Machine Learning for submitting to Computational Materials Science.Datasets are VASP output files including energy, coordinate, etc. Datasets have been used for ML training that described in the submitted manuscript.
description: raw data of Predicting Thermodynamic Stability of Magnesium Alloys in Machine Learning for submitting to Computational Materials Science.Datasets are VASP output files including energy, coordinate, etc. Datasets have been used for ML training that described in the submitted manuscript.
DOI: 10.57760/sciencedb.03198
title: Both Strength of Urges to Act and Time Pressure Influence Intentional Inhibition in the Free Two-Choice Oddball Task
title: 冲动倾向和时间压力共同影响自由双选择Oddball任务中的内生意图性抑制

description: Trials with RT &lt; 100 ms were deleted, and data form subjects who made extreme selection (significantly less than 15% or more than 85%) on free choice stimuli were deleted.
description: Trials with RT &lt; 100 ms were deleted, and data form subjects who made extreme selection (significantly less than 15% or more than 85%) on free choice stimuli were deleted.
DOI: 10.57760/sciencedb.03201
title: Mechanical property test and microstructure detection results of 30CrMnSi alloy steel in 2019
title: 2019年30CrMnSi合金钢力学性能测试和微观表征数据集

description: Comparison of mechanical properties and microstructure characterization results of 30CrMnSi alloy steel before and after deep cryogenic treatment in 2019.
description: Comparison of mechanical properties and microstructure characterization results of 30CrMnSi alloy steel before and after deep cryogenic treatment in 2019.
DOI: 10.57760/sciencedb.03203
title: Heterogeneity of subsets in glioblastoma mediated by Smad3 palmitoylation
title: Heterogeneity of subsets in glioblastoma mediated by Smad3 palmitoylation

description: Glioblastoma (GBM) is the most common and deadly of the primary intracranial tumors and is comprised of subsets that show plasticity and marked heterogeneity, contributing to the lack of success in genomic profiling to guide development of precision medicine for these tumors. In this study, a mutation in isocitrate dehydrogenase 1 was found to suppress the transforming growth factor-beta signaling pathway and E2F4 interacted with Smad3 to inhibit expression of mesenchymal markers. However, palmitoylation of Smad3 mediated by palmitoyltransferase ZDHHC19 promoted activation of the transforming growth factor-beta signaling pathway, and its interaction with EP300 promoted expression of mesenchymal markers in the mesenchymal subtype of GBM. Smad3 and hypoxia-inducible factor 1-alpha may be important molecular targets for treatment of glioma because they appear to coordinate the basic aspects of cancer stem cell biology.
description: Glioblastoma (GBM) is the most common and deadly of the primary intracranial tumors and is comprised of subsets that show plasticity and marked heterogeneity, contributing to the lack of success in genomic profiling to guide development of precision medicine for these tumors. In this study, a mutation in isocitrate dehydrogenase 1 was found to suppress the transforming growth factor-beta signaling pathway and E2F4 interacted with Smad3 to inhibit expression of mesenchymal markers. However, palmitoylation of Smad3 mediated by palmitoyltransferase ZDHHC19 promoted activation of the transforming growth factor-beta signaling pathway, and its interaction with EP300 promoted expression of mesenchymal markers in the mesenchymal subtype of GBM. Smad3 and hypoxia-inducible factor 1-alpha may be important molecular targets for treatment of glioma because they appear to coordinate the basic aspects of cancer stem cell biology.
DOI: 10.57760/sciencedb.03204
title: Effects of Anesthesia on Postoperative Recurrence and Metastasis of Malignant Tumors
title: Effects of Anesthesia on Postoperative Recurrence and Metastasis of Malignant Tumors

description: It is difficult to control the recurrence and metastasis of malignant tumors; furthermore, anesthesia is considered one of the main influencing factors. There has been increasing clinical attention on the effects of anesthetic drugs and methods on postoperative tumor growth and metastasis. We reviewed the effects of anesthesia on tumor recurrence and metastasis; specifically, the effects of anesthetic agents, anesthesia methods, and related factors during the perioperative period on the tumor growth and metastasis were analyzed. This study can provide reference standards for rational anesthesia formulations and cancer-related pain analgesia protocols for surgical procedures in patients with malignant tumors. Moreover, it contributes toward an experimental basis for the improvement and development of novel anesthetic agents and methods.
description: It is difficult to control the recurrence and metastasis of malignant tumors; furthermore, anesthesia is considered one of the main influencing factors. There has been increasing clinical attention on the effects of anesthetic drugs and methods on postoperative tumor growth and metastasis. We reviewed the effects of anesthesia on tumor recurrence and metastasis; specifically, the effects of anesthetic agents, anesthesia methods, and related factors during the perioperative period on the tumor growth and metastasis were analyzed. This study can provide reference standards for rational anesthesia formulations and cancer-related pain analgesia protocols for surgical procedures in patients with malignant tumors. Moreover, it contributes toward an experimental basis for the improvement and development of novel anesthetic agents and methods.
DOI: 10.57760/sciencedb.03207
title: Protein Palmitoylation Regulates Cell Survival by Modulating XBP1 Activity in Glioblastoma Multiforme
title: Protein Palmitoylation Regulates Cell Survival by Modulating XBP1 Activity in Glioblastoma Multiforme

description: Glioblastoma multiforme (GBM) almost invariably acquires an invasive phenotype, resulting in limited therapeutic options. Protein palmitoylation markedly affects tumorigenesis and malignant progression in GBM. The role of protein palmitoylation in GBM, however, has not been systematically reported. This study aimed to investigate the effect of protein palmitoylation on GBM cell survival and the cell cycle. In this study, most palmitoyltransferases were upregulated in GBM and its cell lines, and protein palmitoylation participated in signaling pathways controlling cell survival and the GBM cell cycle. Inhibition of protein palmitoylation with substrate-analog inhibitors, that is, 2-bromopalmitate, cerulenin, and tunicamycin, induced G2 cell cycle arrest and cell death in GBM cells through enhanced endoplasmic reticulum (ER) stress. These effects are primarily attributed to the palmitoylation inhibitors activating pro-apoptotic pathways and ER stress signals. Further analysis revealed was the accumulation of SUMOylated XBP1 (X-box binding protein 1) and its transcriptional repression, along with a reduction in XBP1 palmitoylation. Taken together, the present results indicate that protein palmitoylation plays an important role in the survival of GBM cells, further providing a potential therapeutic strategy for GBM.
description: Glioblastoma multiforme (GBM) almost invariably acquires an invasive phenotype, resulting in limited therapeutic options. Protein palmitoylation markedly affects tumorigenesis and malignant progression in GBM. The role of protein palmitoylation in GBM, however, has not been systematically reported. This study aimed to investigate the effect of protein palmitoylation on GBM cell survival and the cell cycle. In this study, most palmitoyltransferases were upregulated in GBM and its cell lines, and protein palmitoylation participated in signaling pathways controlling cell survival and the GBM cell cycle. Inhibition of protein palmitoylation with substrate-analog inhibitors, that is, 2-bromopalmitate, cerulenin, and tunicamycin, induced G2 cell cycle arrest and cell death in GBM cells through enhanced endoplasmic reticulum (ER) stress. These effects are primarily attributed to the palmitoylation inhibitors activating pro-apoptotic pathways and ER stress signals. Further analysis revealed was the accumulation of SUMOylated XBP1 (X-box binding protein 1) and its transcriptional repression, along with a reduction in XBP1 palmitoylation. Taken together, the present results indicate that protein palmitoylation plays an important role in the survival of GBM cells, further providing a potential therapeutic strategy for GBM.
DOI: 10.57760/sciencedb.03208
title: Molecular subtyping of glioblastoma based on immune-related genes for prognosis
title: Molecular subtyping of glioblastoma based on immune-related genes for prognosis

description: Glioblastoma (GBM) is associated with an increasing mortality and morbidity and is considered as an aggressive brain tumor. Recently, extensive studies have been carried out to examine the molecular biology of GBM, and the progression of GBM has been suggested to be correlated with the tumor immunophenotype in a variety of studies. Samples in the current study were extracted from the ImmPort and TCGA databases to identify immune-related genes affecting GBM prognosis. A total of 92 immune-related genes displaying a significant correlation with prognosis were mined, and a shrinkage estimate was conducted on them. Among them, the 14 most representative genes showed a marked correlation with patient prognosis, and LASSO and stepwise regression analysis was carried out to further identify the genes for the construction of a predictive GBM prognosis model. Then, samples in training and test cohorts were incorporated into the model and divided to evaluate the efficiency, stability, and accuracy of the model to predict and classify the prognosis of patients and to identify the relevant immune features according to the median value of RiskScore (namely, Risk-H and Risk-L). In addition, the constructed model was able to instruct clinicians in diagnosis and prognosis prediction for various immunophenotypes.
description: Glioblastoma (GBM) is associated with an increasing mortality and morbidity and is considered as an aggressive brain tumor. Recently, extensive studies have been carried out to examine the molecular biology of GBM, and the progression of GBM has been suggested to be correlated with the tumor immunophenotype in a variety of studies. Samples in the current study were extracted from the ImmPort and TCGA databases to identify immune-related genes affecting GBM prognosis. A total of 92 immune-related genes displaying a significant correlation with prognosis were mined, and a shrinkage estimate was conducted on them. Among them, the 14 most representative genes showed a marked correlation with patient prognosis, and LASSO and stepwise regression analysis was carried out to further identify the genes for the construction of a predictive GBM prognosis model. Then, samples in training and test cohorts were incorporated into the model and divided to evaluate the efficiency, stability, and accuracy of the model to predict and classify the prognosis of patients and to identify the relevant immune features according to the median value of RiskScore (namely, Risk-H and Risk-L). In addition, the constructed model was able to instruct clinicians in diagnosis and prognosis prediction for various immunophenotypes.
DOI: 10.57760/sciencedb.03209
title: Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns
title: Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns

description: DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.
description: DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.
DOI: 10.57760/sciencedb.03210
title: Systematic Profiling of Alternative mRNA Splicing Signature for Predicting Glioblastoma Prognosis
title: Systematic Profiling of Alternative mRNA Splicing Signature for Predicting Glioblastoma Prognosis

description: Emerging evidence suggests that alternative splicing (AS) is modified in cancer and is associated with cancer progression. Systematic analysis of AS signature in glioblastoma (GBM) is lacking and is greatly needed. We profiled genome-wide AS events in 498 GBM patients in TCGA using RNA-seq data, and splicing network and prognostic predictor were built by integrated bioinformatics analysis. Among 45,610 AS events in 10,434 genes, we detected 1,829 AS events in 1,311 genes, and 1,667 AS events in 1,146 genes that were significantly associated with overall survival and disease-free survival of GBM patients, respectively. Five potential feature genes, S100A4, ECE2, CAST, ASPH, and LY6K, were discovered after network mining as well as correlation analysis between AS and gene expression, most of which were related to carcinogenesis and development. Multivariate survival model analysis indicated that these five feature genes could classify the prognosis at AS event and gene expression level. This report opens up a new avenue for exploration of the pathogenesis of GBM through AS, thus more precisely guiding clinical treatment and prognosis judgment.
description: Emerging evidence suggests that alternative splicing (AS) is modified in cancer and is associated with cancer progression. Systematic analysis of AS signature in glioblastoma (GBM) is lacking and is greatly needed. We profiled genome-wide AS events in 498 GBM patients in TCGA using RNA-seq data, and splicing network and prognostic predictor were built by integrated bioinformatics analysis. Among 45,610 AS events in 10,434 genes, we detected 1,829 AS events in 1,311 genes, and 1,667 AS events in 1,146 genes that were significantly associated with overall survival and disease-free survival of GBM patients, respectively. Five potential feature genes, S100A4, ECE2, CAST, ASPH, and LY6K, were discovered after network mining as well as correlation analysis between AS and gene expression, most of which were related to carcinogenesis and development. Multivariate survival model analysis indicated that these five feature genes could classify the prognosis at AS event and gene expression level. This report opens up a new avenue for exploration of the pathogenesis of GBM through AS, thus more precisely guiding clinical treatment and prognosis judgment.