Myopia is the most common type of refractive errors characterized by excessive elongation of the ocular globe. With the increasing prevalence of myopia, improved knowledge of factors involved in myopia development is of particular importance. There are growing evidence suggesting that the choroid plays an important role in the regulation of eye growth and the development of myopia. Studies have demonstrated that thinning choroid is a structural feature of myopia, with a negative correlation between choroidal thickness and axial length, suggesting that the change in choroidal thickness may be a predictive biomarker for long‐term changes in ocular elongation. Given the fact that the choroid is primarily a vascular structure capable of rapidly changing blood flow, variations of choroidal thickness might be primarily caused by changes in choroidal blood flow. Considering that hypoxia is associated with myopia and choroidal blood flow is the main source of oxygen and nourishment supply, apart from the effect on myopia possibly by changing choroidal thickness, decreasing choroidal blood flow may contribute to scleral ischaemia and hypoxia, resulting in alterations in the scleral structure and thus leading to myopia. This review aims to provide an overview of recent work exploring the influence of the choroid on myopia from perspectives of choroidal thickness and blood flow, which may present new predictive indicators for the onset of myopia and new targets for the development of novel therapeutic approaches for myopia.

Background Blood urea nitrogen to albumin ratio (BAR) has been implicated in predicting outcomes of various inflammatory-related diseases. However, the predictive value of BAR in long-term mortality in patients with acute myocardial infarction (AMI) has not yet been evaluated. Methods In this retrospective cohort study, the patients were recruited from the Medical Information Mart for Intensive Care III (MIMIC III) database and categorized into two groups by a cutoff value of BAR. Kaplan–Meier (K-M) analysis and Cox proportional hazard model were performed to determine the predictive value of BAR in long-term mortality following AMI. In order to adjust the baseline differences, a 1:1 propensity score matching (PSM) was carried out and the results were further validated. Results A total of 1827 eligible patients were enrolled. The optimal cutoff value of BAR for four-year mortality was 7.83 mg/g. Patients in the high BAR group tended to have a longer intensive care unit (ICU) stay and a higher rate of one-, two-, three- and four-year mortality (all p<0.001) compared with those in the low BAR group. K-M curves indicated a significant difference in four-year survival (p<0.001) between low and high BAR groups. The Cox proportional hazards model showed that higher BAR (>7.83) was independently associated with increased four-year mortality in the entire cohort, with a hazard ratio (HR) of 1.478 [95% CI (1.254–1.740), p<0.001]. After PSM, the baseline characteristics of 312 pairs of patients in the high and low BAR groups were well balanced, and similar results were observed in K-M curve (p=0.003). Conclusion A higher BAR (>7.83) was associated with four-year mortality in patients with AMI. As an easily available biomarker, BAR can predict the long-term mortality in AMI patients independently.

Background Hypoplastic left heart syndrome (HLHS) is one of the most complex congenital cardiac malformations, and the molecular mechanism of heart failure (HF) in HLHS is still elusive. Methods Integrative bioinformatics analysis was performed to unravel the underlying genes and mechanisms involved in HF in HLHS. Microarray dataset GSE23959 was screened out for the differentially expressed genes (DEGs), after which the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were carried out using the Metascape. The protein–protein interaction (PPI) network was generated, and the modules and hub genes were identified with the Cytoscape-plugin. And the integrated network of transcription factor (TF)-DEGs and miRNA-DEGs was constructed, respectively. Results A total of 210 DEGs were identified, including 135 up-regulated and 75 down-regulated genes. The functional enrichment analysis of DEGs pointed towards the mitochondrial-related biological processes, cellular components, molecular functions and signaling pathways. A PPI network was constructed including 155 nodes as well as 363 edges. And 15 hub genes, such as NDUFB6, UQCRQ, SDHD, ATP5H , were identified based on three topological analysis methods and mitochondrial components and functions were the most relevant. Furthermore, by integrating network interaction construction, 23 TFs (NFKB1, RELA, HIF1A, VHL, GATA1, PPAR-γ, etc.) as well as several miRNAs (hsa-miR-155-5p, hsa-miR-191-5p, hsa-mir-124-3p, hsa-miR-1-3p, etc.) were detected and indicated the possible involvement of NF-κB signaling pathways in mitochondrial dysfunction in HLHS. Conclusion The present study applied the integrative bioinformatics analysis and revealed the mitochondrial-related key genes, regulatory pathways, TFs and miRNAs underlying the HF in HLHS, which improved the understanding of disease mechanisms and the development of novel therapeutic targets.