cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29571952
title: Antigen presentation-related protein APOL3 promotes anti-tumor T cell immunity and suppresses melanoma cell growth in mice

description: Melanoma is a malignant tumor with limited treatment option in advanced stages. Apolipoprotein L3 (APOL3), a protein implicated in immune regulation, has recently emerged as a potential player in tumor immunity. This research aims to explore the potential efficacy of APOL3 in melanoma. Using data from the Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM), we identified two clusters based on 56 prognostic antigen presentation-related genes. Differential expression analysis revealed 185 genes between these two clusters, which were further narrowed down to 34 genes using univariate analysis and random survival forest dimensionality reduction. Among them, APOL3 was found to be the top-ranked gene. Afterward, the effect of APOL3 on melanoma cells was evaluated using CCK-8, EdU, and Transwell experiment. The results showed that overexpression of APOL3 decreases melanoma cell viability, clonogenicity, proliferation, migration, and invasion. Bioinformatics analysis showed the association of high/low APOL3 expression with genomic mutations characterizing melanoma. APOL3 was also found associated with T-cell infiltration levels, immune checkpoints (CD274, PDCD1, CD247, PDCD1LG2, CTLA4, TNFRSF9, TNFRSF4, and TLR9), and some immune pathways. To validate the role of APOL3 on T cell immunity, we applied B16 melanoma cells to construct the mice tumor models. The model showed that APOL3 overexpression markedly reduces melanoma tumor volume and weight while increasing interferon-γ (IFN-γ), granzyme B production, and CD3<sup>+</sup> T cell infiltration. In conclusion, antigen presentation-related APOL3 promotes anti-tumor T-cell immunity and suppresses melanoma cell growth <i>in-vitro</i> and <i>in-vivo</i> in a murine model. These results suggested that APOL3 may serve as a promising immunotherapeutic target for the treatment of melanoma.
DOI: 10.6084/m9.figshare.29571952.v1
title: Antigen presentation-related protein APOL3 promotes anti-tumor T cell immunity and suppresses melanoma cell growth in mice

description: Melanoma is a malignant tumor with limited treatment option in advanced stages. Apolipoprotein L3 (APOL3), a protein implicated in immune regulation, has recently emerged as a potential player in tumor immunity. This research aims to explore the potential efficacy of APOL3 in melanoma. Using data from the Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM), we identified two clusters based on 56 prognostic antigen presentation-related genes. Differential expression analysis revealed 185 genes between these two clusters, which were further narrowed down to 34 genes using univariate analysis and random survival forest dimensionality reduction. Among them, APOL3 was found to be the top-ranked gene. Afterward, the effect of APOL3 on melanoma cells was evaluated using CCK-8, EdU, and Transwell experiment. The results showed that overexpression of APOL3 decreases melanoma cell viability, clonogenicity, proliferation, migration, and invasion. Bioinformatics analysis showed the association of high/low APOL3 expression with genomic mutations characterizing melanoma. APOL3 was also found associated with T-cell infiltration levels, immune checkpoints (CD274, PDCD1, CD247, PDCD1LG2, CTLA4, TNFRSF9, TNFRSF4, and TLR9), and some immune pathways. To validate the role of APOL3 on T cell immunity, we applied B16 melanoma cells to construct the mice tumor models. The model showed that APOL3 overexpression markedly reduces melanoma tumor volume and weight while increasing interferon-γ (IFN-γ), granzyme B production, and CD3<sup>+</sup> T cell infiltration. In conclusion, antigen presentation-related APOL3 promotes anti-tumor T-cell immunity and suppresses melanoma cell growth <i>in-vitro</i> and <i>in-vivo</i> in a murine model. These results suggested that APOL3 may serve as a promising immunotherapeutic target for the treatment of melanoma.
DOI: 10.13130/rd_unimi/tdflym/oidc9x
title: Novembre_1899_Pagina_075.jpg

description: Bulletin of 1899/11/19
DOI: 10.3535/ln5-kl9-x5s
title: Aglais urticae (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.6084/m9.figshare.30664105
title: The role of IRF-1 in mediating T-cell immune imbalance in systemic lupus erythematosus and the construction of a diagnostic model

description: Systemic lupus erythematosus (SLE), characterized by immune dysregulation, urgently requires improved diagnostic tools and mechanistic insights. The role of interferon regulatory factor-1 (IRF-1) remains unclear. We integrated single-cell transcriptomes (scRNA-seq; GSE254176), 6 bulk transcriptomic datasets (1079 SLE patients, 137 controls, GSE72326 and GSE61635 were merged as training datasets, including 256 SLE patients and 50 controls), and clinical samples (70 SLE patients and 58 controls). IRF-1 dynamics in T-cell subsets were analyzed via clustering and pseudotemporal trajectory. Diagnostic genes were identified by intersecting single-cell-derived IRF-1–associated markers with SLE differential genes, followed by feature selection. Six machine learning models were trained and validated in four independent cohorts. scRNA-seq revealed significant downregulation of IRF-1 in T-cell subsets (central memory CD8⁺, Th17) during active SLE, with compensatory overexpression in remission—validated clinically. Cross-analysis identified four IRF-1–correlated diagnostic genes: CCR7, CD274, KLRB1, and NRCAM, that are enriched in MAPK signaling and immune receptor activity. Generalized linear model (GLM) and partial least squares (PLS) models achieved superior diagnostic accuracy across validation cohorts. Immune analysis revealed decreased numbers of resting CD4⁺ memory T cells and Tregs (<i>P</i> &lt; 0.01), alongside expanded proinflammatory cells (M1/M2 macrophages, neutrophils; <i>P</i> &lt; 0.01). IRF-1 regulates T-cell differentiation and contributes to SLE immune imbalance. The IRF-1–associated gene–based machine learning model provides a robust, noninvasive diagnostic tool.
DOI: 10.6084/m9.figshare.30664105.v2
title: The role of IRF-1 in mediating T-cell immune imbalance in systemic lupus erythematosus and the construction of a diagnostic model

description: Systemic lupus erythematosus (SLE), characterized by immune dysregulation, urgently requires improved diagnostic tools and mechanistic insights. The role of interferon regulatory factor-1 (IRF-1) remains unclear. We integrated single-cell transcriptomes (scRNA-seq; GSE254176), 6 bulk transcriptomic datasets (1079 SLE patients, 137 controls, GSE72326 and GSE61635 were merged as training datasets, including 256 SLE patients and 50 controls), and clinical samples (70 SLE patients and 58 controls). IRF-1 dynamics in T-cell subsets were analyzed via clustering and pseudotemporal trajectory. Diagnostic genes were identified by intersecting single-cell-derived IRF-1–associated markers with SLE differential genes, followed by feature selection. Six machine learning models were trained and validated in four independent cohorts. scRNA-seq revealed significant downregulation of IRF-1 in T-cell subsets (central memory CD8⁺, Th17) during active SLE, with compensatory overexpression in remission—validated clinically. Cross-analysis identified four IRF-1–correlated diagnostic genes: CCR7, CD274, KLRB1, and NRCAM, that are enriched in MAPK signaling and immune receptor activity. Generalized linear model (GLM) and partial least squares (PLS) models achieved superior diagnostic accuracy across validation cohorts. Immune analysis revealed decreased numbers of resting CD4⁺ memory T cells and Tregs (<i>P</i> &lt; 0.01), alongside expanded proinflammatory cells (M1/M2 macrophages, neutrophils; <i>P</i> &lt; 0.01). IRF-1 regulates T-cell differentiation and contributes to SLE immune imbalance. The IRF-1–associated gene–based machine learning model provides a robust, noninvasive diagnostic tool.
DOI: 10.13130/rd_unimi/tdflym/1cmkzh
title: Novembre_1899_Pagina_077.jpg

description: Bulletin of 1899/11/20
DOI: 10.13130/rd_unimi/tdflym/p3rcbm
title: Novembre_1899_Pagina_076.jpg

description: Bulletin of 1899/11/19
DOI: 10.3535/031-xva-cp4
title: Noctuidae

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/h53-9vz-j0a
title: Agriades Hübner, 1819

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.6084/m9.figshare.28776436
title: Unveiling causal pathways in autoimmune diseases: a multi-omics approach

description: Autoimmune diseases (ADs), such as Graves’ disease (GD), Hashimoto’s thyroiditis (HT), psoriasis, systemic lupus erythematosus (SLE), and type 1 diabetes (T1D), involve complex immune and inflammatory responses. This study employed Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data to examine the causal relationships among 91 circulating inflammatory proteins, 41 cytokines, 211 gut microbiota, and 731 immune cell traits in relation to ADs. Additionally, we integrated mediation and bioinformatics analyses, including protein-protein interaction (PPI) networks, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subnetwork discovery and key protein identification were performed using the Molecular Complex Detection (MCODE) plugin, alongside colocalization analysis and drug target exploration to identify potential mechanisms. MR analysis identified significant causal relationships between various circulating inflammatory proteins, cytokines, gut microbiota species, immune cells, and ADs, with certain relationships retaining significance after false discovery rate (FDR) correction. Mediation analysis demonstrated that inflammatory proteins mediate pathogenic pathways linking immune cells to psoriasis and gut microbiota to Hashimoto’s thyroiditis. PPI and bioinformatics analyses highlighted 22 key proteins involved in ADs, while subnetwork analysis identified 15 central proteins. Fms-related tyrosine kinase 3 ligand (FLT3LG) exhibited strong colocalization evidence. Molecular docking confirmed several proteins as viable drug targets. This comprehensive multi-omics study advances our understanding of ADs, identifies novel therapeutic targets, and offers valuable insights for developing new treatment strategies.
DOI: 10.6084/m9.figshare.28776436.v1
title: Unveiling causal pathways in autoimmune diseases: a multi-omics approach

description: Autoimmune diseases (ADs), such as Graves’ disease (GD), Hashimoto’s thyroiditis (HT), psoriasis, systemic lupus erythematosus (SLE), and type 1 diabetes (T1D), involve complex immune and inflammatory responses. This study employed Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data to examine the causal relationships among 91 circulating inflammatory proteins, 41 cytokines, 211 gut microbiota, and 731 immune cell traits in relation to ADs. Additionally, we integrated mediation and bioinformatics analyses, including protein-protein interaction (PPI) networks, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subnetwork discovery and key protein identification were performed using the Molecular Complex Detection (MCODE) plugin, alongside colocalization analysis and drug target exploration to identify potential mechanisms. MR analysis identified significant causal relationships between various circulating inflammatory proteins, cytokines, gut microbiota species, immune cells, and ADs, with certain relationships retaining significance after false discovery rate (FDR) correction. Mediation analysis demonstrated that inflammatory proteins mediate pathogenic pathways linking immune cells to psoriasis and gut microbiota to Hashimoto’s thyroiditis. PPI and bioinformatics analyses highlighted 22 key proteins involved in ADs, while subnetwork analysis identified 15 central proteins. Fms-related tyrosine kinase 3 ligand (FLT3LG) exhibited strong colocalization evidence. Molecular docking confirmed several proteins as viable drug targets. This comprehensive multi-omics study advances our understanding of ADs, identifies novel therapeutic targets, and offers valuable insights for developing new treatment strategies.
DOI: 10.6084/m9.figshare.30664105.v1
title: The role of IRF-1 in mediating T-cell immune imbalance in systemic lupus erythematosus and the construction of a diagnostic model

description: Systemic lupus erythematosus (SLE), characterized by immune dysregulation, urgently requires improved diagnostic tools and mechanistic insights. The role of interferon regulatory factor-1 (IRF-1) remains unclear. We integrated single-cell transcriptomes (scRNA-seq; GSE254176), 6 bulk transcriptomic datasets (1079 SLE patients, 137 controls, GSE72326 and GSE61635 were merged as training datasets, including 256 SLE patients and 50 controls), and clinical samples (70 SLE patients and 58 controls). IRF-1 dynamics in T-cell subsets were analyzed via clustering and pseudotemporal trajectory. Diagnostic genes were identified by intersecting single-cell-derived IRF-1–associated markers with SLE differential genes, followed by feature selection. Six machine learning models were trained and validated in four independent cohorts. scRNA-seq revealed significant downregulation of IRF-1 in T-cell subsets (central memory CD8⁺, Th17) during active SLE, with compensatory overexpression in remission—validated clinically. Cross-analysis identified four IRF-1–correlated diagnostic genes: CCR7, CD274, KLRB1, and NRCAM, that are enriched in MAPK signaling and immune receptor activity. Generalized linear model (GLM) and partial least squares (PLS) models achieved superior diagnostic accuracy across validation cohorts. Immune analysis revealed decreased numbers of resting CD4⁺ memory T cells and Tregs (<i>P</i> &lt; 0.01), alongside expanded proinflammatory cells (M1/M2 macrophages, neutrophils; <i>P</i> &lt; 0.01). IRF-1 regulates T-cell differentiation and contributes to SLE immune imbalance. The IRF-1–associated gene–based machine learning model provides a robust, noninvasive diagnostic tool.
DOI: 10.13130/rd_unimi/tdflym/8jifk1
title: Novembre_1899_Pagina_078.jpg

description: Bulletin of 1899/11/20
DOI: 10.3535/3mj-lyt-8zt
title: Amphipoea fucosa Freyer, 1830

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.6084/m9.figshare.29657152
title: CPN2 alleviates cryptorchidism by inhibiting the NF-κB pathway and regulating immune responses

description: Cryptorchidism, a common male reproductive disorder characterized by undescended testes, is associated with infertility and increased cancer risk. While its etiology remains incompletely understood, accumulating evidence suggests that immune-inflammatory responses contribute to disease progression. This study investigated the role of carboxypeptidase N subunit 2 (CPN2) in modulating immune activation and testicular pathology via the NF-κB signaling pathway. Key regulatory genes were identified through transcriptomic analysis, weighted gene co-expression network analysis (WGCNA), and machine learning approaches. A di-n-butyl phthalate (DBP)-induced rat model of cryptorchidism and CRISPR/Cas9-mediated CPN2 knockout rats were employed, alongside histological, immunohistochemical, Western blotting, and co-culture assays to explore immune activation and spermatogonial cell fate. CPN2 was identified as a pivotal factor that suppresses NF-κB activation and plasma cell infiltration. Its overexpression alleviated inflammatory cytokine production, preserved spermatogonial stem cell proliferation, and reduced apoptosis in both in vivo and in vitro models. These effects were reversed upon NF-κB activation, confirming the regulatory role of the CPN2/NF-κB axis. Our findings reveal that CPN2 mitigates cryptorchidism progression by modulating immune-inflammatory responses, highlighting it as a promising molecular target for non-surgical intervention in this condition.
DOI: 10.6084/m9.figshare.29657152.v1
title: CPN2 alleviates cryptorchidism by inhibiting the NF-κB pathway and regulating immune responses

description: Cryptorchidism, a common male reproductive disorder characterized by undescended testes, is associated with infertility and increased cancer risk. While its etiology remains incompletely understood, accumulating evidence suggests that immune-inflammatory responses contribute to disease progression. This study investigated the role of carboxypeptidase N subunit 2 (CPN2) in modulating immune activation and testicular pathology via the NF-κB signaling pathway. Key regulatory genes were identified through transcriptomic analysis, weighted gene co-expression network analysis (WGCNA), and machine learning approaches. A di-n-butyl phthalate (DBP)-induced rat model of cryptorchidism and CRISPR/Cas9-mediated CPN2 knockout rats were employed, alongside histological, immunohistochemical, Western blotting, and co-culture assays to explore immune activation and spermatogonial cell fate. CPN2 was identified as a pivotal factor that suppresses NF-κB activation and plasma cell infiltration. Its overexpression alleviated inflammatory cytokine production, preserved spermatogonial stem cell proliferation, and reduced apoptosis in both in vivo and in vitro models. These effects were reversed upon NF-κB activation, confirming the regulatory role of the CPN2/NF-κB axis. Our findings reveal that CPN2 mitigates cryptorchidism progression by modulating immune-inflammatory responses, highlighting it as a promising molecular target for non-surgical intervention in this condition.
DOI: 10.13130/rd_unimi/tdflym/auwa7k
title: Novembre_1899_Pagina_079.jpg

description: Bulletin of 1899/11/20
DOI: 10.13130/rd_unimi/tdflym/uzbbmk
title: Novembre_1899_Pagina_080.jpg

description: Bulletin of 1899/11/20
DOI: 10.3535/h58-hs4-nwb
title: Cucullia gnaphalii (Hübner, 1813)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/qey-mqq-a0m
title: Eudonia lacustrata Panzer, 1804

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.6084/m9.figshare.30891149
title: Exploring the mechanism of autophagy and inflammation in osteoarthritis through bioinformatics and experimental verification

description: Osteoarthritis (OA) is a chronic joint disorder characterized by cartilage degradation and accompanied by inflammatory processes. Inflammation and autophagy dysfunction have been associated with the pathogenesis of OA. However, the interplay between autophagy- and inflammation-related genes in the development of OA remains poorly understood. RNA sequencing data of OA samples and autophagy-related genes (ARGs) were obtained from public databases, while inflammation-related genes were extracted from published literature. Differentially expressed genes (DEGs) in the OA dataset were identified using the limma R package. Using WGCNA, we identified autophagy-related gene modules (WGCNA-ARGs), and differential expression analysis was conducted to detect differentially expressed inflammation-related genes (IDEGs). Subsequently, candidate genes were identified by intersecting DEGs, WGCNA-ARGs, and IDEGs. Four machine learning algorithms-LASSO, SVM, RF, and XGBoost-were employed to screen for biomarkers, with diagnostic performance evaluated by ROC curve analysis. The biological functions and therapeutic potential of the biomarkers were further explored through multiple approaches: enrichment analysis, immune infiltration analysis, chromosomal localization, regulatory network construction, and drug prediction. Finally, the expression levels of the biomarkers were validated in clinical samples using RT-qPCR.
DOI: 10.6084/m9.figshare.30891149.v1
title: Exploring the mechanism of autophagy and inflammation in osteoarthritis through bioinformatics and experimental verification

description: Osteoarthritis (OA) is a chronic joint disorder characterized by cartilage degradation and accompanied by inflammatory processes. Inflammation and autophagy dysfunction have been associated with the pathogenesis of OA. However, the interplay between autophagy- and inflammation-related genes in the development of OA remains poorly understood. RNA sequencing data of OA samples and autophagy-related genes (ARGs) were obtained from public databases, while inflammation-related genes were extracted from published literature. Differentially expressed genes (DEGs) in the OA dataset were identified using the limma R package. Using WGCNA, we identified autophagy-related gene modules (WGCNA-ARGs), and differential expression analysis was conducted to detect differentially expressed inflammation-related genes (IDEGs). Subsequently, candidate genes were identified by intersecting DEGs, WGCNA-ARGs, and IDEGs. Four machine learning algorithms-LASSO, SVM, RF, and XGBoost-were employed to screen for biomarkers, with diagnostic performance evaluated by ROC curve analysis. The biological functions and therapeutic potential of the biomarkers were further explored through multiple approaches: enrichment analysis, immune infiltration analysis, chromosomal localization, regulatory network construction, and drug prediction. Finally, the expression levels of the biomarkers were validated in clinical samples using RT-qPCR.
DOI: 10.13130/rd_unimi/tdflym/yqivcp
title: Novembre_1899_Pagina_081.jpg

description: Bulletin of 1899/11/21
DOI: 10.3535/0b7-m4g-sxt
title: Phycitodes albatella Ragonot, 1887

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.