Purpose The purpose of this study was to conduct a matched-pair analysis to assess the impact of radiotherapy (RT) on patients with malignant tracheal tumors using the surveillance, epidemiology, and end results database. Additionally, a predictive nomogram was developed for patients with malignant tracheal tumors. Methods Propensity score matching (PSM) was used to minimize bias between the RT and no-RT groups. We utilized both univariate and multivariate Cox proportional hazards regression analyses to identify independent prognostic factors for patients and subgroups. We developed a novel nomogram and evaluated its results using the C-index. Results A total of 648 patients between 1975 and 2019 were included, and 160 patients in RT were 1:1 propensity score-matched with no-RT. The independent prognostic factors for patients with tracheal malignant tumors were surgery, marital status, disease extension, pathology, and age. The independent risk factors for patients without surgery included RT and disease extension. The C-index confirmed that the nomogram accurately predicted the prognosis of patients with tracheal malignant tumors. Conclusions Our findings suggest that RT may provide a survival benefit for tracheal cancer patients who did not undergo surgery. The nomogram can be a useful tool for predicting prognosis in patients with tracheal malignant tumors.

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This paper proposes a novel binary particle swarm optimization (PSO) algorithm using artificial immune system (AIS) for face recognition. Inspired by face recognition ability in human visual system (HVS), this algorithm fuses the information of the holistic and partial facial features. The holistic facial features are extracted by using principal component analysis (PCA), while the partial facial features are extracted by non-negative matrix factorization with sparseness constraints (NMFs). Linear discriminant analysis (LDA) is then applied to enhance adaptability to illumination and expression. The proposed algorithm is used to select the fusion rules by minimizing the Bayesian error cost. The fusion rules are finally applied for face recognition. Experimental results using UMIST and ORL face databases show that the proposed fusion algorithm outperforms individual algorithm based on PCA or NMFs.

The diagnosis and treatment of non-small cell lung cancer (NSCLC) are not ideal. We identified NSCLC-related has_circ_0006423 in database. qRT-PCR was used to measure expression levels of hsa_circ_0006423 and miR-492 in the plasma and tissue samples, and 3 NSCLC cell lines, respectively. We analyzed the relationship between expression levels of hsa_circ_0006423 and clinicopathological factors and miR-492 expression in plasma and tissue samples. Assess the diagnostic value of hsa_circ_0006423 and miR-492 in NSCLC. Cell function vitro experiment to explore the effect of has_circ_0006423 on NSCLC. We found has_circ_0006423 is lower expressed in NSCLC and miR-492 is opposite, has_circ_0006423 and miR-492 has diagnostic value in NSCLC. In A549 and NCI-H1299 cells, hsa_circ_0006423 inhibited the proliferation, migration, and invasion of NSCLC cells by sponging miR-492 and accelerating NSCLC cell apoptosis. This effect may be due to the combination of has_circ_0006423 and miR-492 affecting the progression of NSCLC.