Identification of immune-related molecular markers in intracranial aneurysm (IA) based on machine learning and cytoscape-cytohubba plug-in

Identification of Angiogenesis-Related Gene Signatures and Prediction of Potential Therapeutic Targets in Ulcerative Colitis Using Integrated Bioinformatics

Objective

This study aims to clarify angiogenesis mechanisms in ulcerative colitis and identify potential therapeutic targets.

Methods

The Gene Expression Omnibus (GEO) database was used to obtain expression profiles and clinical data for UC and healthy colon tissues. Angiogenesis-related gene sets were acquired from GeneCards. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) identified UC-associated hub genes. The CIBERSORT algorithm assessed immune cell infiltration. Analyses of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to determine biological mechanisms. External datasets were utilized to validate and characterize the angiogenesis-related genes in relation to biological agents. Additionally, an ulcerative colitis mouse model was constructed to verify the key genes' expression using real-time quantitative PCR. To predict potential therapeutic agents, we used the DGIdb database. Molecular docking modeled small molecule binding conformations to key gene targets.

Results

This study identified 1,247 DEGs enriched in inflammatory/immune pathways from UC and healthy colon samples. WGCNA indicated the black and light cyan modules were most relevant. Intersecting these with 89 angiogenesis genes revealed 5 UC-associated hub genes (pdgfrb, vegfc, angpt2, tnc, hgf). Validation via ROC analysis, differential expression, and a mouse model confirmed upregulation, supporting their potential as UC diagnostic biomarkers. Bioinformatics approaches like protein-protein interaction, enrichment analysis, and GSEA revealed involvement in PDGFR and PI3K-Akt signaling pathways. CIBERSORT analysis of immune cell infiltration showed positive correlations between the key genes and various immune cells, especially neutrophils, highlighting angiogenesis-inflammation interplay in UC. A ceRNA network was constructed. Drug prediction and molecular docking revealed potential UC therapies like sunitinib and imatinib targeting angiogenesis.

Conclusion

This study identified and validated five angiogenesis-related genes (pdgfrb, vegfc, angpt2, tnc, hgf) that may serve as diagnostic biomarkers and drug targets for UC.

Molecular mechanism underlying the protective effects of ischemic preconditioning in total knee arthroplasty

PROPOSE

To investigate the molecular mechanisms underlying the protective effects of ischemic preconditioning (IPC) in patients undergoing total knee arthroplasty.

METHODS

GSE21164 was extracted from an online database, followed by an investigation of differentially expressed genes (DEGs) between IPC treatment samples at 2 time points (T0T and T1T). Function and pathway enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed to identify hub genes according to 5 different algorithms, followed by enrichment analysis. In addition, long noncoding RNAs (lncRNAs) were identified between the T0T and T1T samples. Furthermore, a competing endogenous RNA network was predicted based on the identified lncRNA-messenger RNA (mRNA), lncRNA-microRNA (miRNA), and mRNA-miRNA relationships revealed in this study. Finally, a drug-gene network was investigated. Statistical analyses were performed using GraphPad Prism 8.0. Differences between groups were determined using an unpaired t-test. p < 0.05 was considered significant.

RESULTS

A total of 343 DEGs at T0 and 10 DEGs at T1 were identified and compared with their respective control groups, followed by 100 DEGs between T0T and T1T. Based on these 100 DEGs, protein-protein interaction network analysis revealed 9 hub genes, mainly with mitochondria-related functions and the carbon metabolism pathway. Six differentially expressed lncRNAs were investigated between T0T and T1T. A competing endogenous RNA network was constructed using 259 lncRNA-miRNA-mRNA interactions, including alpha-2-macroglobulin antisense RNA 1-miR-7161-5p-iron-sulfur cluster scaffold. Finally, 13 chemical drugs associated with the hub genes were explored.

CONCLUSION

Iron-sulfur cluster scaffold may promote IPC-induced ischemic tolerance mediated by alpha-2-macroglobulin antisense RNA 1-miR-7161-5p axis. Moreover, IPC may induce a protective response after total knee arthroplasty via mitochondria-related functions and the carbon metabolism pathway, which should be further validated in the near future.

Deciphering Immunotoxicity in Animal-Derived Biomaterials: A Genomic and Bioinformatics Approach

Immunotoxicity evaluation has been crucial in preclinical testing for implantable animal-derived biomaterials due to their prolonged contact with the human body, which requires stringent safety assessments. By creating experimental models with varying levels of immunotoxicity, this study reveals the decisive role of decellularization treatment in diminishing the immunogenicity of materials, thus ensuring clinical safety. Employing cutting-edge differential gene expression analysis, the research not only accurately quantifies gene expression alterations in immune responses but also, through pathway enrichment analysis, identifies gene networks associated with oncogenesis. This offers novel insights into the mechanisms of immune responses following biomaterial implantation. Additionally, the study highlights the importance of developing highly sensitive immunotoxicity testing methods and validates the efficacy of high-throughput sequencing and bioinformatics tools in assessing biomaterial safety, providing robust scientific support for future preclinical evaluations.

Biomimetic biphasic microsphere preparation based on the thermodynamic incompatibility of glycosaminoglycan with gelatin methacrylate for hair regeneration

Hair follicle (HF) tissue engineering is promising for hair loss treatment especially for androgenetic alopecia. Physiologically, the initiation of HF morphogenesis relies on the interactions between hair germ mesenchymal and epithelial layers. To simulate this intricate process, in this study, a co-flowing microfluidic-assisted technology was developed to produce dual aqueous microdroplets capturing growth factors and double-layer cells for subsequent use in hair regeneration. Microspheres, called G/HAD, were generated using glycosaminoglycan-based photo-crosslinkable biological macromolecule (HAD) shells and gelatin methacrylate (GelMA) cores to enclose mesenchymal cells (MSCs) and mouse epidermal cells (EPCs). The findings indicated that the glycosaminoglycan-based HAD shells display thermodynamic incompatibility with GelMA cores, resulting in the aqueous phase separation of G/HAD cell spheres. These G/HAD microspheres exhibited favorable characteristics, including sustained growth factor release and wet adhesion properties. After transplantation into the dorsal skin of BALB/c nude mice, G/HAD cell microspheres efficiently induced the regeneration of HFs. This approach enables the mass production of approximately 250 dual-layer microspheres per minute. Thus, this dual-layer microsphere fabrication method holds great potential in improving current hair regeneration techniques and can also be combined with other tissue engineering techniques for various regenerative purposes.

Identification of hub genes and key pathways in arsenic-treated rice (Oryza sativa L.) based on 9 topological analysis methods of CytoHubba

BACKGROUND

Arsenic is a toxic metalloid that can cause acute and chronic adverse health problems. Unfortunately, rice, the primary staple food for more than half of the world's population, is generally regarded as a typical arsenic-accumulating crop plant. Evidence indicates that arsenic stress can influence the growth and development of the rice plant, and lead to high concentrations of arsenic in rice grain. But the underlying mechanisms remain unclear.

METHODS

In the present research, the possible molecules and pathways involved in rice roots in response to arsenic stress were explored using bioinformatics methods. Datasets that involving arsenic-treated rice root and the "study type" that was restricted to "Expression profiling by array" were selected and downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between the arsenic-treated group and the control group were obtained using the online web tool GEO2R. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to investigate the functions of DEGs. The protein-protein interactions (PPI) network and the molecular complex detection algorithm (MCODE) of DEGs were analyzed using STRING and Cystoscope, respectively. Important nodes and hub genes in the PPI network were predicted and explored using the Cytoscape-cytoHubba plug-in.

RESULTS

Two datasets, GSE25206 and GSE71492, were downloaded from Gene Expression Omnibus (GEO) database. Eighty common DEGs from the two datasets, including sixty-three up-regulated and seventeen down-regulated genes, were then selected. After functional enrichment analysis, these common DEGs were enriched mainly in 10 GO items, including glutathione transferase activity, glutathione metabolic process, toxin catabolic process, and 7 KEGG pathways related to metabolism. After PPI network and MCODE analysis, 49 nodes from the DEGs PPI network were identified, filtering two significant modules. Next, the Cytoscape-cytoHubba plug-in was used to predict important nodes and hub genes. Finally, five genes [Os01g0644000, PRDX6 (Os07g0638400), PRX112 (Os07g0677300), ENO1(Os06g0136600), LOGL9 (Os09g0547500)] were verified and could serve as the best candidates associated with rice root in response to arsenic stress.

CONCLUSIONS

In summary, we elucidated the potential pathways and genes in rice root in response to arsenic stress through a comprehensive bioinformatics analysis.