Identification and validation of cuproptosis related genes and signature markers in bronchopulmonary dysplasia disease using bioinformatics analysis and machine learning

The cuproptosis-related gene glutaminase promotes alveolar macrophage copper ion accumulation in chronic obstructive pulmonary disease

Cuproptosis, a novel mode of cell death, is strongly associated with a variety of diseases. However, the contribution of cuproptosis to the onset or progression of chronic obstructive pulmonary disease (COPD), the third most common chronic cause of mortality, is not yet clear. To investigate the potential role of cuproptosis in COPD, raw datasets from multiple public clinical COPD databases (including RNA-seq, phenotype, and lung function data) were used. For further validation, mice exposed to cigarette smoke for three months were used as in vivo models, and iBMDMs (immortalized bone marrow-derived macrophages) and RAW264.7 cells stimulated with cigarette smoke extract were used as in vitro models. For the first time, the expression of the cuproptosis-related gene glutaminase (GLS) was found to be decreased in COPD, and the low expression of GLS was significantly associated with the grade of pulmonary function. In vivo experiments confirmed the decreased expression of GLS in COPD, particularly in alveolar macrophages. Furthermore, in vitro studies revealed that copper ions accumulated in alveolar macrophages, leading to a substantially decreased amount of cell activity of macrophages when stimulated with cigarette extract. In summary, we demonstrate the high potential of GLS as an avenue for diagnosis and therapy in COPD.

Transforming neonatal care with artificial intelligence: challenges, ethical consideration, and opportunities

Artificial intelligence (AI) offers tremendous potential to transform neonatology through improved diagnostics, personalized treatments, and earlier prevention of complications. However, there are many challenges to address before AI is ready for clinical practice. This review defines key AI concepts and discusses ethical considerations and implicit biases associated with AI. Next we will review literature examples of AI already being explored in neonatology research and we will suggest future potentials for AI work. Examples discussed in this article include predicting outcomes such as sepsis, optimizing oxygen therapy, and image analysis to detect brain injury and retinopathy of prematurity. Realizing AI's potential necessitates collaboration between diverse stakeholders across the entire process of incorporating AI tools in the NICU to address testability, usability, bias, and transparency. With multi-center and multi-disciplinary collaboration, AI holds tremendous potential to transform the future of neonatology.

Integrated bioinformatics and experiment revealed that cuproptosis is the potential common pathogenesis of three kinds of primary cardiomyopathy

Cuproptosis is a recently reported new mode of programmed cell death which might be a potential co-pathogenesis of three kinds of primary cardiomyopathy. However, no investigation has reported a clear relevance between primary cardiomyopathy and cuproptosis. In this study, the differential cuproptosis-related genes (CRGs) shared by three kinds of primary cardiomyopathy were identified in training sets. As a result, four CRGs shared by three kinds of primary cardiomyopathy were acquired and they were mainly related to biological processes such as cell death and immuno-inflammatory response through differential analysis, correlation analysis, GSEA, GSVA and immune cell infiltration analysis. Then, three key CRGs (K-CRGs) with high diagnostic value were identified by LASSO regression. The results of nomogram, machine learning, ROC analysis, calibration curve and decision curve indicated that the K-CRGs exhibited outstanding performance in the diagnosis of three kinds of primary cardiomyopathy. After that, in each disease, two molecular subtypes clusters were distinguished. There were many differences between different clusters in the biological processes associated with cell death and immunoinflammation and K-CRGs had excellent molecular subtype identification efficacy. Eventually, results from validation datasets and in vitro experiments verified the role of K-CRGs in diagnosis of primary cardiomyopathy, identification of primary cardiomyopathic molecular subtypes and pathogenesis of cuproptosis. In conclusion, this study found that cuproptosis might be the potential common pathogenesis of three kinds of primary cardiomyopathy and K-CRGs might be promising biomarkers for the diagnosis and molecular subtypes identification of primary cardiomyopathy.