Cognitive dysfunction is known to be influenced by circulating sex steroidal hormones. The aim of this study was to examine the protective effect and possible protective mechanism of testosterone (T) on cognitive performance in male rats induced by intrahippocampal injections of beta amyloid 1-42 oligomers (Aβ1-42). Treatment with T as evidenced by the Morris water maze (MWM) test significantly shortened escape latency and reduced path length to reach the platform compared to the control (C). During probe trials, the T group displayed a significantly greater percent of time in the target quadrant and improved the number of platform crossings compared with C, flutamide (F), an antiandrogen, and a combined F and T group. Flutamide markedly inhibited the influence of T on cognitive performance. Following Nissl staining, the number of intact pyramidal cells was significantly elevated in the T group, and the effect of T was blocked by F. Immunohistochemisty and Western blot analysis showed that the protein expression level of Aβ 1-42 was markedly decreased and expression levels of synaptophysin (SYN) significantly increased with T, while F inhibited all T-mediated effects. Our data suggest that the influence of T on cognitive performance was mediated via androgen receptors (AR) to remove beta amyloid, which leads to enhanced synaptic plasticity.
The present study indicated that serum AGE levels were associated with insulin resistance in male nondiabetic patients with OSA. These findings suggest that AGEs may play a role in insulin resistance in OSA and may also be a biomarker for patients with OSA with high risk of developing type 2 diabetes.
Background
Colorectal cancer (CRC) is one of the lethal malignant tumors worldwide. However, the underlying mechanism of CRC and its biomarkers remain unclear. The aim of this study was to identify the key genes associated with CRC and to further explore their prognostic significance.
Methods
Four expression profile datasets (GSE41657, GSE74602, GSE113513, and GSE40967) downloaded from Gene Expression Omnibus (GEO) and one RNAseq dataset of CRC from The Cancer Genome Atlas (TCGA) database were included in our study. The Cox model was utilized for univariate or multivariate survival analysis. GEPIA and HAP database were adopted for verification of DEGs (
ZG16
). The decision curve analysis (DCA) and time-dependent ROC were chosen for evaluating the prognostic effectiveness of biomarkers.
Results
In total, 88 differentially expressed genes (DEGs) were identified, and the GO and KEGG enrichment analyses of DEGs were processed. After, the protein–protein interaction (PPI) network was constructed and 15 hub genes including
ZG16
were identified. The differential expression of
ZG16
between tumor and normal colorectal tissues were further verified in GEPIA and HAP database. Subsequent survival indicated that expression of
ZG16
is negatively correlated with overall survival of OS and is an independent prognostic factor for CRC patients. Furthermore, the construction of a prognostic score containing
ZG16
, TNM stage and age exhibited superior effectiveness for predicting long-term survival of CRC patients. Additionally, our results were verified using the GSE40967 dataset, which indicated an improved performance of combined risk score based on
ZG16
for predicting OS of CRC patients.
Conclusion
ZG16
is a potential parameter for predicting prognosis in CRC. Furthermore, a combination of
ZG16
, TNM stage, and age allows improved prognosis of CRC.
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