Background: Breast cancer is the most prevalent malignancy in women globally, and apoptosis plays an important role in its pathological process. However, studies on the relationship between breast cancer prognosis and apoptosis-related genes are scarce. This study aimed to construct an apoptosis-related specific risk model for breast cancer and preliminarily explore the immunological differences between the high- and low-risk groups of this model to improve the prognosis and treatment of patients with breast cancer.Methods: The Cancer Gene Atlas (TCGA) and Gene Expression Omnibus (GEO) were used to analyze the correlation between apoptosis-related genes and differentially expressed genes. Apoptotic genes associated with prognosis were selected, and a risk model was constructed and validated using univariate and multivariate Cox proportional regression analyses. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO)analyses were used to predict potential mechanical pathways. Tumor lymphocyte infiltration was analyzed between the high- and low-risk groups. The CellMiner database, RNA: RNA-seq expression and Compound activity: DTP NCI-60 were used to assess the drug sensitivity of the model genes. Immunohistochemistry was used to validate the levels of risk model signatures in clinical samples.Results: Seventy-four differentially expressed apoptosis-related genes were screened between breast cancer tissues and adjacent normal tissues. Immune infiltration analysis suggested that CD8-positive T-cells and natural killer cells was considerably higher in the low-risk group than in the high-risk group and that the immune effect was higher in the low-risk group than in the high-risk group. Drug sensitivity analysis showed a positive correlation between the model genes and the sensitivity of multiple drugs, such as vemurafenib, dabrafenib, PD-98059, and palbociclib. Immunohistochemistry results were consistent with the above-mentioned results.Conclusion: Our findings suggest that the developed apoptosis-related specific risk model could be a novel predictive tool for use in patients with breast cancer and can serve as the basis for future breast cancer therapy.

Objective Optical Coherence tomography (OCT) was employed to screen for maculopathy in the senile cataract population, investigate its incidence, and establish a healthy mode of management for maculopathy. Methods A visual examination, slit-lamp microscope examination, direct ophthalmoscopic fundus examination, and a macular OCT examination were performed on 102 people with senile cataracts who were over 60 years in our hospital from January 1, 2019, to July 31, 2019. The demographic characteristics such as sex, age, physical examination mode: organization/individual, and routine physical examination items: presence or absence of hypertension, body mass index (BMI), blood biochemistry, total cholesterol, triglyceride (TG), fasting blood glucose and others. Results Of the 102 subjects in the study, 28 were positive for maculopathy according to the OCT examination. Univariate analysis found that there were statistical differences between sexes and the presence of maculopathy (p<0.05). There were no significant differences in age, visual acuity, hypertension, BMI, fasting blood glucose, TG, total cholesterol, and cataract type ( P >0.05). Multivariate logistic regression analysis, including all factors that might affect maculopathy, indicated that positivity for maculopathy and age (OR =2.549, 95%CI: 1.129–5.756, p<0.05) and gender (OR=3.907, 95%CI: 1.241–12.302, p<0.05) were related. Conclusion The incidence of maculopathy in the senile cataract population was higher than that in the elderly population without cataract disease, and the proportion is 27.45%. Screening for maculopathy in the senile cataract population, especially among the elderly and females, should be improved.

Background: To identify the heterogeneous and homogeneous prognostic factors associated with distant metastases in colorectal cancer (CRC) patients and then construct nomograms to predict prognosis.Methods: CRC patients registered in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016 were included. Cox regression was used to analyse homogeneous and heterogeneous prognostic factors, and Kaplan-Meier analysis was used to estimate overall survival (OS). Predictive nomograms were constructed, and their performance was evaluated with C-indexes and calibration curves.Results: A total of 34933 patients with distant metastases were included. The median survival time of patients with liver metastases, lung metastases, bone metastases, and brain metastases were 12.00 months (95% CI: 11.71-12.29 months), 10.00 months (95% CI: 9.57-10.43 months), 5.00 months (95% CI: 4.47-5.53 months), and 3.00 months (95% CI: 2.31-3.70 months), respectively. Older age and no surgery were identified as homogeneous prognostic factors of the four types of metastases. Male sex, black race, unmarried status, uninsured status, primary CRC site, poor differentiation/grade, advanced N stage, T stage, high carcinoembryonic antigen (CEA) level and metastatic organ were heterogeneously associated with the prognosis of patients with distant metastases. The calibration curves and C-indexes exhibited good performance for predicting the OS of patients with distant metastases.Conclusion: CRC patients with distant metastases exhibited homogeneous and heterogeneous prognostic factors, all of which were associated with poor survival. The nomograms showed good accuracy and can be used as tools for clinicians to predict the prognosis of CRC patients with distant metastases.