RESUMEN
Superatoms are crucial in the assembly of functional and optoelectronic materials. This study investigates the endohedral metallo-boron nitride [boron nitride (BN)] fullerenes U@B12N12, Cm@B12N12, and U@B16N16 in theory. Our findings confirm that U@B12N12, Cm@B12N12, and U@B16N16 are superatoms and their electronic configurations are 1P61S21D101F142P62S22D102F123P6, 1P61S21D101F141G161H162S22P62D102F12, and 1P61S21D101F142P62S22D102F14, respectively. Notably, the orbital energy levels in these superatoms exhibit a flipping phenomenon, deviating from those of previous superatom studies. Further, the orbital composition analyses reveal that superatomic orbitals 1S, 1P, 1D, and 1F mainly originate from BN cages, whereas the 2S, 2P, 2D, 2F, and 3P superatomic orbitals arise from hybridizations between BN cage orbitals and the 7s, 7p, 6d, and 5f orbitals of actinide atoms. And the energy gap of endohedral metallo-BN fullerene superatoms is reduced by introducing actinide atoms. Additionally, the analyses of ionization potentials and electron affinities show that U@B12N12, Cm@B12N12, and U@B16N16 have lower ionization potentials and higher electron affinities, suggesting decreased stability compared to that of pure BN cages. This instability may be linked to the observed flipping of the superatomic orbital energy levels. These insights introduce new members to the superatom family and offer new building blocks for the design of nanoscale materials with tailored properties.
RESUMEN
Background: Multiple myeloma (MM), an incurable plasma cell malignancy. The significance of the relationship between natural killer (NK) cell-related genes and clinical factors in MM remains unclear. Methods: Initially, we extracted NK cell-related genes from peripheral blood mononuclear cells (PBMC) of healthy donors and MM samples by employing single-cell transcriptome data analysis in TISCH2. Subsequently, we screened NK cell-related genes with prognostic significance through univariate Cox regression analysis and protein-protein interaction (PPI) network analysis. Following the initial analyses, we developed potential subtypes and prognostic models for MM using consensus clustering and lasso regression analysis. Additionally, we conducted a correlation analysis to explore the relationship between clinical features and risk scores. Finally, we constructed a weighted gene co-expression network analysis (WGCNA) and identified differentially expressed genes (DEGs) within the MM cohort. Results: We discovered that 153 NK cell-related genes were significantly associated with the prognosisof MM patients (P <0.05). Patients in NK cluster A exhibited poorer survival outcomes compared to those in cluster B. Furthermore, our NK cell-related genes risk model revealed that patients with a high risk score had significantly worse prognoses (P <0.05). Patients with a high risk score were more likely to exhibit adverse clinical markers. Additionally, the nomogram based on NK cell-related genes demonstrated strong prognostic performance. The enrichment analysis indicated that immune-related pathways were significantly correlated with both the NK subtypes and the NK cell-related genes risk model. Ultimately, through the combined use of WGCNA and DEGs analysis, and by employing Venn diagrams, we determined that ITM2C is an independent prognostic marker for MM patients. Conclusion: In this study, we developed a novel model based on NK cell-related genes to stratify the prognosis of MM patients. Notably, higher expression levels of ITM2C were associated with more favorable survival outcomes in these patients.
