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Embryotoxic responses are critically dependent on the timing of exposure during embryo development. Here, we examined the time- dependent developmental effects in rat embryos exposed to flusilazole (FLU), and their link to retinoic acid (RA) mediated pathways. To this end, we assessed the effects of 4 h exposure of rat embryos in vitro to 300 mu M FLU during four developmental time windows (0-4, 4-8, 24-28 and 44-48 h), evaluating morphological parameters, expression and localization of five genes directly or indirectly linked with the RA pathway. These were RA- (Cyp26a1 and Dhrs3), differentiation-(Gbx2 and Cdx1) and sterol biosynthesis- (Cyp51) related genes. Extended exposure for 48 h to 300 mu M FLU resulted in morphological changes, typical for triazoles and RA, while the 4 h exposure times did not. Time dependent significant upregulation of the five selected genes was observed. These results corroborate that the embryotoxic responses to FLU are correlated with the regulation of the RA pathway. Thus, these gene expression markers can be considered early biomarkers of FLU-induced potential developmental toxicity later in the development. (C) 2016 Elsevier Inc. All rights reserved.

Macrophages are key innate immune cells in the tumor microenvironment that regulate primary tumor growth, vascularization, metastatic spread and response to therapies. Macrophages can polarize into two different states (M1 and M2) with distinct phenotypes and functions. To investigate the known tumoricidal effects of M1 macrophages, we obtained RNA expression profiles and clinical data from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA). The proportions of immune cells in tumor samples were assessed using CIBERSORT, and weighted gene co-expression network analysis (WGCNA) was used to identify M1 macrophage-related modules. Univariate Cox analysis and LASSO-Cox regression analysis were performed, and four genes (SPP1, DHRS3, SLC11A1, and CFB) with significant differential expression were selected through GEPIA. These four genes can be considered hub genes. The four-gene risk-scoring model may be an independent prognostic factor for THCA patients. The validation cohort and the entire cohort confirmed the results. Univariate and multivariate Cox analysis was performed to identify independent prognostic factors for THCA. Finally, a prognostic nomogram was built based on the entire cohort, and the nomogram combining the risk score and clinical prognostic factors was superior to the nomogram with individual clinical prognostic factors in predicting overall survival. Time-dependent ROC curves and DCA confirmed that the combined nomogram is useful. Gene set enrichment analysis (GSEA) was used to elucidate the potential molecular functions of the high-risk group. Our study identified four genes associated with M1 macrophages and established a prognostic nomogram that predicts overall survival for patients with THCA, which may help determine clinical treatment options for different patients.