MicroRNAs (miRNAs) have been demonstrated to play crucial roles in the initiation and development of non-small cell lung cancer (NSCLC). However, further investigation of the specific role of miR-126 in NSCLC is still required. An analysis of miR-126 expression in NSCLC was carried out using the Gene Expression Omnibus (GEO) database, and a literature review was also performed. The differentially expressed genes (DEGs) in three mRNA datasets, GSE18842, GSE19804, and GSE101929, from GEO were identified. Following the prediction of hsa-miR-126-5p target genes by TargetScan, the overlap of miR-126 target genes with DEGs in NSCLC was examined. After that, Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed. Finally, an analysis to identify the impact of hub genes on the prognosis of NSCLC was carried out on the basis of a protein-protein interaction (PPI) network constructed using STRING and Cytoscape. The data in the literature review revealed a trend that miR126 was downregulated in NSCLC. The number of both NSCLC-related and miR-126-related DEGs was 187. Dozens of DEGs were significantly enriched in biological regulation, cell membrane binding, and signal receptor binding. In the PPI network analysis, 3 of 10 identified hub genes, namely , and were obviously related to poor prognosis in NSCLC; the survival rate was low among patients with high expression levels of these genes. Furthermore, through network analysis, TPX2, HMMR, and ANLN were identified as recessive miR-126-related genes that may be involved in NSCLC. MiR-126 plays an essential role in the biological processes of NSCLC through binding to target genes and influences the prognosis of patients with the disease. MiR-126 plays an essential role in the biological processes of NSCLC through binding to target genes and influences the prognosis of patients with the disease. Cervical cancer ranks as one of the most prevalent female malignancies globally, and its treatment with new targets has been the focus of current research. The present study set out to investigate the function of microRNA-326 (miR-326) and and to verify the direct targeting of transcription factor 4 (TCF4) by miR-326. The detection of messenger RNA (mRNA) expressing miR-326 and TCF4 in cervical cancer cell lines and tumor samples was conducted using quantitative real-time polymerase chain (qRT-PCR). A dual-luciferase reporter assay was carried out to detect the target relationship of miR-326 with TCF4. A Cell Counting Kit-8 (CCK-8) assay was employed to detect the effect of miR-326 on CasKi cell viability. Flow cytometry and western blotting were employed to examine the effects of miR-326 on cancer stem cell (CSC)-like property. Tumor weight was measured in orthotopic xenograft mouse models. Immunohistochemistry was employed to analyze the protein expression levels of Ki-67, proliferating cell nuclend has potential as a biomarker or therapeutic target for cervical cancer. Breast cancer is the most common malignancy in women. Triple-negative breast cancer (TNBC) refers to a special subtype that is deficient in the expression of estrogen (ER), progesterone (PR), and human epidermal growth factor receptor 2 (HER-2). https://www.selleckchem.com/products/AZD0530.html In this study, a variety of bioinformatics analysis tools were used to screen Hub genes related to the occurrence and development of triple negative breast cancer, and their biological functions were analyzed. Gene Expression Omnibus (GEO) breast cancer microarray data GSE62931 was selected as the research object. The differentially expressed genes (DEGs) were screened and the protein-protein interaction (PPI) network of DEGs was constructed using bioinformatics tools. The Hub genes were also screened. The Gene Ontology (GO) knowledgebase and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for biological enrichment analysis. The Gene Expression Profiling Interactive Analysis (GEPIA) online tool was used to verify the expression of the screened genes ads can effectively analyze the DEGs related to the occurrence and development of breast cancer, and the screening of PLK1 can provide theoretical guidance for further research on the molecular mechanism of breast cancer and the screening of molecular markers. Gene chip combined with bioinformatics methods can effectively analyze the DEGs related to the occurrence and development of breast cancer, and the screening of PLK1 can provide theoretical guidance for further research on the molecular mechanism of breast cancer and the screening of molecular markers. One of the difficulties and hot topics in the field of computer vision and image processing is extraction of the high-level pulmonary trachea from patients' lung CT images. Current, common bronchial extraction methods are limited by the phenomenon of bronchial loss and leakage, and cannot extract the higher-level pulmonary trachea, which does not meet the requirements of guiding lung puncture procedures. Based on the characteristic "tubular structure" (ring or semi-closed ring) of the pulmonary trachea in CT images, an algorithm based on dynamic tubular edge contour is proposed. In axial, coronal and sagittal CT images, the algorithm could extract the skeletal line of the pulmonary trachea and vessel-connecting region, perform elliptical fitting, extract the pulmonary trachea by the ratio of the ellipse's long and short axes, and obtain point cloud data of the pulmonary trachea in three directions. The point cloud data was fused to obtain a complete three-dimensional model of the pulmonary trachea. The algorithm was verified using CT data from "EXACT09", and could extract the pulmonary trachea to the 10-11 level, which effectively solves the problems of leakage and loss of the trachea. We have constructed a novel extraction algorithm of pulmonary trachea that can guide the doctors to decide the puncture path and avoid the large trachea, which has important theoretical and practical significance for reducing puncture complications and the mortality rate. We have constructed a novel extraction algorithm of pulmonary trachea that can guide the doctors to decide the puncture path and avoid the large trachea, which has important theoretical and practical significance for reducing puncture complications and the mortality rate.