cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13385168.v1
title: Production of L-carnitine-enriched edible filamentous fungal biomass through submerged cultivation

description: The edible filamentous fungi are hot candidate for future supply of functional food and feed with e.g. protein, essential amino acids, and compounds with immunostimulant activity. L-carnitine that plays a crucial role in energy metabolism represents a functional compound normally produced by Zygomycetes filamentous fungus <i>Rhizopus oligosporus</i> in solid-state fermentation. The present study provides the first insights on production of L-carnitine-enriched edible fungal biomass through submerged cultivation of several Ascomycetes and Zygomycetes including <i>Aspergillus oryzae</i>, <i>Neurospora intermedia</i>, <i>Rhizopus oryzae</i>, and <i>Rhizopus oligosporus</i>. <i>A. oryzae</i> with 3 mg L-carnitine yield per gram of fungal biomass, indicates great potential on production of this bioactive compound which is remarkably higher than the other tested fungi in this work and also previous studies. In addition to fungal strain, other factors such as cultivation time and presence of yeast extract were found to play a role. Further studies on submerged growth optimization of <i>A</i>. <i>oryzae</i> in both high-quality recipes and in medium based on low-value substrates are proposed in order to clarify its potential for production of L-carnitine-enriched fungal biomass.
DOI: 10.6084/m9.figshare.17708087.v1
title: Integrated Analysis of DNA methylation and transcriptome profile to identify key features of age-related macular degeneration

description: Age-related macular degeneration (AMD) is a common vision-threatening disease. The current study sought to integrate DNA methylation with transcriptome profile to explore key features in AMD. Gene expression data were obtained from the Gene Expression Omnibus (GEO, accession ID: GSE135092) and DNA methylation data were obtained from the ArrayExpress repository (E-MTAB-7183). A total of 456 differentially expressed genes (DEGs) and 4827 intragenic differentially methylated CpGs (DMCs) were identified between AMD and controls. DEGs and DMCs were intersected and 19 epigenetically induced (EI) genes and 15 epigenetically suppressed (ES) genes were identified. Immune cell infiltration analysis was performed to estimate the abundance of different types of immune cell in each sample. Enrichment scores of inflammatory response and tumor necrosis factor-alpha (TNFα) signaling via nuclear factor kappa B (NF-κb) were positively correlated with abundance of activated memory CD4 T cells and M1 macrophages. Subsequently, two significant random forest classifiers were constructed based on DNA methylation and transcriptome data. SMAD2 and NGFR were selected as key genes through functional epigenetic modules (FEM) analysis. Expression level of SMAD2, NGFR and their integrating proteins was validated in hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) and TNFα co-treated retinal pigment epithelium (RPE) <i>in vitro</i>. The findings of the current study showed that local inflammation and systemic inflammatory host response play key roles in pathogenesis of AMD. SMAD2 and NGFR provide new insight in understanding the molecular mechanism and are potential therapeutic targets for development of AMD therapy.
DOI: 10.6084/m9.figshare.17708087
title: Integrated Analysis of DNA methylation and transcriptome profile to identify key features of age-related macular degeneration

description: Age-related macular degeneration (AMD) is a common vision-threatening disease. The current study sought to integrate DNA methylation with transcriptome profile to explore key features in AMD. Gene expression data were obtained from the Gene Expression Omnibus (GEO, accession ID: GSE135092) and DNA methylation data were obtained from the ArrayExpress repository (E-MTAB-7183). A total of 456 differentially expressed genes (DEGs) and 4827 intragenic differentially methylated CpGs (DMCs) were identified between AMD and controls. DEGs and DMCs were intersected and 19 epigenetically induced (EI) genes and 15 epigenetically suppressed (ES) genes were identified. Immune cell infiltration analysis was performed to estimate the abundance of different types of immune cell in each sample. Enrichment scores of inflammatory response and tumor necrosis factor-alpha (TNFα) signaling via nuclear factor kappa B (NF-κb) were positively correlated with abundance of activated memory CD4 T cells and M1 macrophages. Subsequently, two significant random forest classifiers were constructed based on DNA methylation and transcriptome data. SMAD2 and NGFR were selected as key genes through functional epigenetic modules (FEM) analysis. Expression level of SMAD2, NGFR and their integrating proteins was validated in hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) and TNFα co-treated retinal pigment epithelium (RPE) <i>in vitro</i>. The findings of the current study showed that local inflammation and systemic inflammatory host response play key roles in pathogenesis of AMD. SMAD2 and NGFR provide new insight in understanding the molecular mechanism and are potential therapeutic targets for development of AMD therapy.
DOI: 10.6084/m9.figshare.13516783
title: Individualized prognostic signature for pancreatic carcinoma validated by integrating immune-related gene pairs (IRGPs)

description: Increasingly attention is being given to immune molecules in pancreatic cancer. The purpose of this study was to understand the potential clinical application of immune-regulated genes (IRGs) in the stratification of prognosis and to facilitate the development of personalized prognostic information for pancreatic cancer patients. We systematically used public data to comprehensively analyze immune-regulated gene pair (IRGP) expression profiles and clinical data. In our study, IRGP signature was identified to predict the overall survival (OS) of pancreatic cancer patients. We suggested that immune genes are enriched in different risk groups. In the high-risk group, M1 macrophages and resting NK cells were significantly enriched, while the percentages of naïve B cells, resting dendritic cells, CD8 T cells and regulatory T cells (Tregs) were significantly higher in the low-risk group, and we verified these results with immunohistochemical experiments. Gene ontology (GO) analysis confirmed that the IRGP index (IRGPI) signature genes in the cohort were mostly party to sensory perception of a chemical stimulus and the adaptive immune response. The identification of these pathways provides a basis for studying the molecular mechanisms of IRGPI signaling to predict the prognosis of pancreatic cancer. Our study effectively constructed a robust IRGP signature with prognostic value for pancreatic cancer, presenting a conceivable method for deciding on a preoperative treatment.
DOI: 10.6084/m9.figshare.13516783.v1
title: Individualized prognostic signature for pancreatic carcinoma validated by integrating immune-related gene pairs (IRGPs)

description: Increasingly attention is being given to immune molecules in pancreatic cancer. The purpose of this study was to understand the potential clinical application of immune-regulated genes (IRGs) in the stratification of prognosis and to facilitate the development of personalized prognostic information for pancreatic cancer patients. We systematically used public data to comprehensively analyze immune-regulated gene pair (IRGP) expression profiles and clinical data. In our study, IRGP signature was identified to predict the overall survival (OS) of pancreatic cancer patients. We suggested that immune genes are enriched in different risk groups. In the high-risk group, M1 macrophages and resting NK cells were significantly enriched, while the percentages of naïve B cells, resting dendritic cells, CD8 T cells and regulatory T cells (Tregs) were significantly higher in the low-risk group, and we verified these results with immunohistochemical experiments. Gene ontology (GO) analysis confirmed that the IRGP index (IRGPI) signature genes in the cohort were mostly party to sensory perception of a chemical stimulus and the adaptive immune response. The identification of these pathways provides a basis for studying the molecular mechanisms of IRGPI signaling to predict the prognosis of pancreatic cancer. Our study effectively constructed a robust IRGP signature with prognostic value for pancreatic cancer, presenting a conceivable method for deciding on a preoperative treatment.
DOI: 10.6084/m9.figshare.13506959
title: The importance of cell culture parameter standardization: an assessment of the robustness of the 2102Ep reference cell line

description: Work undertaken using the embryonic carcinoma 2102Ep line, highlighted the requirement for robust, well-characterized and standardized protocols. A systematic approach utilizing ‘quick hit’ experiments demonstrated variability introduced into culture systems resulting from slight changes to culture conditions (route A). This formed the basis for longitudinal experiments investigating long-term effects of culture parameters including seeding density and feeding regime (route B).Results demonstrated that specific growth rates (SGR) of passage 59 (P59) cells seeded at 20,000 cells/cm<sup>2</sup> and subjected to medium exchange after 48h prior to reseeding at 72h (route B2) on average was marginally higher than, P55 cells cultured under equivalent conditions (route A1); whereby SGR values were (0.021±0.004) and (0.019±0.004). Viability was higher in route B2 over 10 passages with average viability reported as (86.3%±8.1) compared to route A1 (83.3±8.8). The metabolite data demonstrated both culture route B1 (P57 cells seeded at 66,667 cells/cm<sup>2</sup>) and B2 had consistent-specific metabolite rates (SMR) for glucose, but SMR values of route B1 was consistently lower than route B2 (0.00001 mmol, cell-1.d-1 and 0.000025).Results revealed interactions between phenotype, SMR and feeding regime that may not be accurately reflected by growth rate or observed morphology. This implies that current schemes of protocol control do not adequately account for variability, since key cell characteristics, including phenotype and SMR, change regardless of standardized seeding densities. This highlights the need to control culture parameters through defined protocols, for processes that involve culture for therapeutic use, biologics production, and reference lines.
DOI: 10.6084/m9.figshare.13506959.v2
title: The importance of cell culture parameter standardization: an assessment of the robustness of the 2102Ep reference cell line

description: Work undertaken using the embryonic carcinoma 2102Ep line, highlighted the requirement for robust, well-characterized and standardized protocols. A systematic approach utilizing ‘quick hit’ experiments demonstrated variability introduced into culture systems resulting from slight changes to culture conditions (route A). This formed the basis for longitudinal experiments investigating long-term effects of culture parameters including seeding density and feeding regime (route B).Results demonstrated that specific growth rates (SGR) of passage 59 (P59) cells seeded at 20,000 cells/cm<sup>2</sup> and subjected to medium exchange after 48h prior to reseeding at 72h (route B2) on average was marginally higher than, P55 cells cultured under equivalent conditions (route A1); whereby SGR values were (0.021±0.004) and (0.019±0.004). Viability was higher in route B2 over 10 passages with average viability reported as (86.3%±8.1) compared to route A1 (83.3±8.8). The metabolite data demonstrated both culture route B1 (P57 cells seeded at 66,667 cells/cm<sup>2</sup>) and B2 had consistent-specific metabolite rates (SMR) for glucose, but SMR values of route B1 was consistently lower than route B2 (0.00001 mmol, cell-1.d-1 and 0.000025).Results revealed interactions between phenotype, SMR and feeding regime that may not be accurately reflected by growth rate or observed morphology. This implies that current schemes of protocol control do not adequately account for variability, since key cell characteristics, including phenotype and SMR, change regardless of standardized seeding densities. This highlights the need to control culture parameters through defined protocols, for processes that involve culture for therapeutic use, biologics production, and reference lines.
DOI: 10.6084/m9.figshare.14963763
title: Data mining-based study of collagen type III alpha 1 (COL3A1) prognostic value and immune exploration in pan-cancer

description: The extracellular matrix (ECM) shows an essential effect during the occurrence and procession of human cancers. Type III collagen is a crucial component of ECM. Collagen Type III Alpha 1(COL3A1) is aberrantly expressed in a variety of cancers. Nevertheless, the role of COL3A1 in pan-cancer stays unidentified. In this study, we explored public databases, including Cancer Genome Atlas (TCGA), GTEx, GEPIA, cBioPortal, Oncommine, TIMER and GENEMANIA databases to identify the differential expression of COL3A1 in human cancer tissues and normal samples, followed by its prognostic value for patient survival. In addition, we explore the association between COL3A1 expression and immune infiltration. Further, we used the GeneMANIA database and Gene Set Enrichment Analysis (GSEA) to investigate Protein–Protein Interaction (PPI) and gene functional enrichment. Results show that COL3A1 expressed higher in tumor samples than in normal samples. Upregulation of COL3A1 is associated with a worse prognosis and a more advanced cancer stage. COL3A1 expression shows significant positive correlations with tumor-infiltrating immune cells (TIICs), including neutrophils, macrophages, CD8 + T cells, CD4 + T cells, dendritic cells, and B cells. Markers of TIICs demonstrated distinct patterns of COL3A1-related immune infiltration. COL3A1 expression was associated with ECM receptor interaction, regulation of actin cytoskeleton and focal adhesion pathways via GSEA analysis. In conclusion, COL3A1 may be a molecular biomarker for prognosis and immune infiltration in pan-cancer. It might act as a potential target for a new insight of human cancers management.
DOI: 10.6084/m9.figshare.14963763.v1
title: Data mining-based study of collagen type III alpha 1 (COL3A1) prognostic value and immune exploration in pan-cancer

description: The extracellular matrix (ECM) shows an essential effect during the occurrence and procession of human cancers. Type III collagen is a crucial component of ECM. Collagen Type III Alpha 1(COL3A1) is aberrantly expressed in a variety of cancers. Nevertheless, the role of COL3A1 in pan-cancer stays unidentified. In this study, we explored public databases, including Cancer Genome Atlas (TCGA), GTEx, GEPIA, cBioPortal, Oncommine, TIMER and GENEMANIA databases to identify the differential expression of COL3A1 in human cancer tissues and normal samples, followed by its prognostic value for patient survival. In addition, we explore the association between COL3A1 expression and immune infiltration. Further, we used the GeneMANIA database and Gene Set Enrichment Analysis (GSEA) to investigate Protein–Protein Interaction (PPI) and gene functional enrichment. Results show that COL3A1 expressed higher in tumor samples than in normal samples. Upregulation of COL3A1 is associated with a worse prognosis and a more advanced cancer stage. COL3A1 expression shows significant positive correlations with tumor-infiltrating immune cells (TIICs), including neutrophils, macrophages, CD8 + T cells, CD4 + T cells, dendritic cells, and B cells. Markers of TIICs demonstrated distinct patterns of COL3A1-related immune infiltration. COL3A1 expression was associated with ECM receptor interaction, regulation of actin cytoskeleton and focal adhesion pathways via GSEA analysis. In conclusion, COL3A1 may be a molecular biomarker for prognosis and immune infiltration in pan-cancer. It might act as a potential target for a new insight of human cancers management.
DOI: 10.6084/m9.figshare.16606362.v1
title: Argon inhibits reactive oxygen species oxidative stress via the miR-21-mediated PDCD4/PTEN pathway to prevent myocardial ischemia/reperfusion injury

description: The objective of this study was to explore the effect of argon preconditioning on myocardial ischemia reperfusion (MI/R) injury and its mechanism. Cardiomyocytes H2C9 were pre-treated with 50% argon, and a cell model of oxygen-glucose deprivation (OGD) was established. CCK-8 and cytotoxicity detection kits were used to detect cell viability and lactate dehydrogenase (LDH) release. The miR-21 expression was detected using quantitative real-time polymerase chain reaction. Western blot analysis was performed to detect the expression of programmed cell death protein 4 (PDCD4) and homologous phosphatase and tensin homolog (PTEN) proteins. The levels of inflammatory factors (IL-1β, IL-6, and IL-8) and oxidative stress factors (reactive oxygen species ROS], malondialdehyde [MDA], and superoxide dismutase [SOD]) were measured using an enzyme-linked immunosorbent assay. The effect of argon on cell apoptosis was detected using flow cytometry. Argon increased the proliferation of cardiomyocytes induced by OGD, decreased the release of LDH in cell culture medium, increased miR-21 expression in cells, decreased the expression of miR-21 target proteins PDCD4 and PTEN, decreased the levels of inflammatory factors (interleukin-1β [IL-1β], interleukin-6 [IL-6], and interleukin-8 [IL-8]) and oxidative stress factors (ROS and MDA), increased the SOD content, and decreased the cell apoptosis rate. Our results suggest that argon preconditioning inhibited the PDCD4/PTEN pathway via miR-21, thereby inhibiting ROS oxidative stress and preventing MI/R injury.
DOI: 10.6084/m9.figshare.14912718
title: The integration of differentially expressed genes based on multiple microarray datasets for prediction of the prognosis in oral squamous cell carcinoma

description: Oral squamous cell carcinoma (OSCC) is a common human malignancy. However, its pathogenesis and prognostic information are poorly elucidated. In the present study, we aimed to probe the most significant differentially expressed genes (DEGs) and their prognostic performance in OSCC. Multiple microarray datasets from the Gene Expression Omnibus (GEO) database were aggregated to identify DEGs between OSCC tissue and control tissue. Least absolute shrinkage and selection operator (LASSO) Cox model was constructed to determine the prognostic performance of the aggregated DEGs based on The Cancer Genome Atlas (TCGA) OSCC cohort. Ten datasets with 341 OSCC samples and 283 control samples were included. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that the integrated DEGs were enriched in the IL-17 signaling pathway, viral protein interactions with cytokines and cytokine receptors, and amoebiasis, among others. Our LASSO Cox model was able to discriminate two groups with different overall survival in the training cohort and test cohort (p &lt; 0.001). The time-dependent receiver operating characteristic (ROC) curve revealed that the area under the curve (AUC) values at one year, three years, and five years were 0.831, 0.898, and 0.887, respectively. In the testing cohort, the time-dependent ROC curve showed that the AUC values at one year, three years, and five years were 0.696, 0.693, and 0.860, respectively. Our study showed that the integrated DEGs of OSCC might be applicable in the evaluation of prognosis in OSCC. However, further research should be performed to validate our findings.
DOI: 10.6084/m9.figshare.14912718.v1
title: The integration of differentially expressed genes based on multiple microarray datasets for prediction of the prognosis in oral squamous cell carcinoma

description: Oral squamous cell carcinoma (OSCC) is a common human malignancy. However, its pathogenesis and prognostic information are poorly elucidated. In the present study, we aimed to probe the most significant differentially expressed genes (DEGs) and their prognostic performance in OSCC. Multiple microarray datasets from the Gene Expression Omnibus (GEO) database were aggregated to identify DEGs between OSCC tissue and control tissue. Least absolute shrinkage and selection operator (LASSO) Cox model was constructed to determine the prognostic performance of the aggregated DEGs based on The Cancer Genome Atlas (TCGA) OSCC cohort. Ten datasets with 341 OSCC samples and 283 control samples were included. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that the integrated DEGs were enriched in the IL-17 signaling pathway, viral protein interactions with cytokines and cytokine receptors, and amoebiasis, among others. Our LASSO Cox model was able to discriminate two groups with different overall survival in the training cohort and test cohort (p &lt; 0.001). The time-dependent receiver operating characteristic (ROC) curve revealed that the area under the curve (AUC) values at one year, three years, and five years were 0.831, 0.898, and 0.887, respectively. In the testing cohort, the time-dependent ROC curve showed that the AUC values at one year, three years, and five years were 0.696, 0.693, and 0.860, respectively. Our study showed that the integrated DEGs of OSCC might be applicable in the evaluation of prognosis in OSCC. However, further research should be performed to validate our findings.
DOI: 10.6084/m9.figshare.14963790
title: MiRNA based tumor mutation burden diagnostic and prognostic prediction models for endometrial cancer

description: Uterus Corpus Endometrial cancer (UCEC) is the sixth most common malignant tumor worldwide. In this research, we identified diagnostic and prognostic biomarkers to reflect patients’ immune microenvironment and prognostic. Various data of UCEC patients from the TCGA database were obtained. Firstly, patients were divided into a high tumor mutation burden (TMB) level group and a low TMB level group according to the level of TMB. Then, differentially expressed miRNAs between the two groups were obtained. LASSO logistic regression analysis was used to construct a diagnostic model to predict the level of TMB. Univariate, multivariate, and LASSO regression analysis were used to construct a prognostic risk signature (PRS) to predict the prognosis of UCEC patients. Twenty-one miRNAs were used to construct a diagnostic model for predicting TMB levels. The AUC values of ROC curves for 21-miRNA-based diagnostic models were 0.911 in the training set, 0.827 in the test set, and 0.878 in the entire set. This diagnostic model showed positive correlation with TMB, PDL1 expression, and the infiltration of immune cells. In addition, three prognostic miRNAs were finally used to construct the PRS. The PRS was related to the expression of multiple immune checkpoints and the infiltration of multiple immune cells. Furthermore, the PRS can also reflect the response to some commonly used chemotherapy regimens. We have established a miRNA-based diagnostic model and a prognostic model that can predict the prognosis of UCEC patients and their response to chemotherapy and immunotherapy, thus providing valuable information on the choice of treatment regimen.
DOI: 10.5519/qd.pc5fsgsv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2735 records)
DOI: 10.6084/m9.figshare.22148078
title: Database_hemocultures_1.xlsx

description: Bloodstream infections (BSI) are a global health problem and are responsible for mortality and morbidity in hospitalized patients. Furthermore, treating BSI is challenging, especially if it is caused by resistant bacteria. The aim of our study was to examine common pathogens and identify the prevalence of antimicrobial resistance (ADR) in blood cultures from a tertiary hospital in Brazil.