The present study aimed to investigate the expression, biological function and mechanism of action of engrailed homeobox 2 (EN2) in non-small cell lung cancer (NSCLC) at the tissue and cellular level. A total of 42 patients who underwent surgical resection of NSCLC tissues between January 2014 and January 2015 were included in the present study. EN2 mRNA expression levels in explanted NSCLC tissues were determined using reverse-transcription quantitative polymerase chain reaction analysis. Adenocarcinoma human alveolar basal epithelial A549 cells were transfected with negative control plasmids or those containing EN2, enabling its overexpression. To assess the effect of EN2 overexpression in A549 cells, a Cell Counting kit-8 assay was used to analyze cellular proliferation, a Transwell assay was used to evaluate cellular migration and invasion and flow cytometry was used to detect the cell cycle distribution. To measure protein expression of EN2 and β-catenin in A549 cells, western blotting was also conducted. EN2 mRNA expression levels in NSCLC tissues were lower than those in normal tissues, and were associated with metastasis, clinical staging and differentiation degrees of NSCLC. Increased expression of EN2 inhibited the proliferation of A549 cells , and suppressed their migration and invasion. Elevated EN2 expression inhibited the proliferation of A549 cells by regulating the G/S phase transition. β-catenin protein expression levels and nuclear translocation in A549 cells were inhibited by EN2 overexpression. The present study demonstrated that expression of EN2 in NSCLC tissues was downregulated and negatively associated with the degree of disease differentiation, lymphatic metastasis and clinical staging. Overexpression of EN2 inhibits the proliferation, migration and invasion of A549 cells, as well as the expression of β-Catenin and nuclear translocation.

Background/Aims: Currently, scientists attempt to improve outcome of spinal cord injury (SCI) via reducing secondary injury during SCI. Oxidative stress is critical for pathophysiology of secondary damage, thus we mainly focused on the anti-oxidant effects of Lycium barbarum polysaccharides (LBPs) on PC-12 and SH-SY5Y cells as well as the underlying mechanisms. Methods: Oxidative stress was induced by H₂O₂ stimulation. Effects of LBPs on cell viability, apoptosis, and expression of proteins associated with apoptosis and autophagy in H₂O₂-induced cells were assessed by CCK-8 assay, flow cytometry assay and Western blot analysis, respectively. Then, expression of miR-194 was determined by qRT-PCR. Expression of miR-194 was dysregulated, and whether LBPs affected H₂O₂-treated cells through modulating miR-194 was verified. The expression of key kinases in the PI3K/AKT pathway and the intracellular levels of ROS and NO were testified by Western blot analysis and flow cytometry with fluorescent probes. Results: H₂O₂-induced decrease of cell viability and increases of apoptosis and autophagy in PC-12 cells were mitigated by LBPs treatment. Next, we found that miR-194 expression was both down-regulated by LBPs treatment in PC-12 and SH-SY5Y cells. More experiments consolidated that influence of LBPs on H₂O₂-treated cells was reversed by miR-194 overexpression while was augmented by miR-194 inhibition. LBPs elevated the phosphorylated levels of PI3K and AKT and reduced levels of ROS and NO through miR-194. Conclusion: LBPs alleviated H₂O₂-induced decrease of cell viability, and increase of apoptosis and autophagy through down-regulating miR-194. Moreover, LBPs activated the PI3K/AKT pathway and reduced oxidative stress through miR-194.

The early diagnosis and the accurate separation of COVID-19 from non-COVID-19 cases based on pulmonary diffuse airspace opacities is one of the challenges facing researchers. Recently, researchers try to exploit the Deep Learning (DL) method’s capability to assist clinicians and radiologists in diagnosing positive COVID-19 cases from chest X-ray images. In this approach, DL models, especially Deep Convolutional Neural Networks (DCNN), propose real-time, automated effective models to detect COVID-19 cases. However, conventional DCNNs usually use Gradient Descent-based approaches for training fully connected layers. Although GD-based Training (GBT) methods are easy to implement and fast in the process, they demand numerous manual parameter tuning to make them optimal. Besides, the GBT’s procedure is inherently sequential, thereby parallelizing them with Graphics Processing Units is very difficult. Therefore, for the sake of having a real-time COVID-19 detector with parallel implementation capability, this paper proposes the use of the Whale Optimization Algorithm for training fully connected layers. The designed detector is then benchmarked on a verified dataset called COVID-Xray-5k, and the results are verified by a comparative study with classic DCNN, DUICM, and Matched Subspace classifier with Adaptive Dictionaries. The results show that the proposed model with an average accuracy of 99.06% provides 1.87% better performance than the best comparison model. The paper also considers the concept of Class Activation Map to detect the regions potentially infected by the virus. This was found to correlate with clinical results, as confirmed by experts. Although results are auspicious, further investigation is needed on a larger dataset of COVID-19 images to have a more comprehensive evaluation of accuracy rates.

The present study aimed to determine the expression of vascular endothelial growth factor A (VEGFA) and microRNA (miRNA/miR)-27a in hippocampal tissues, and serum from a depression model of rats. In addition, the present study aimed to understand the mechanism of regulation of miR-27a in depression. A total of 40 male rats were selected, and divided into the control and depression model groups. The rats in the model group were subjected to 14 types of stimulations to model depression. By determining the body weight, syrup consumption rate and open field test score, the extent of depression in the rats was evaluated. Quantitative-polymerase chain reaction was used to determine the expression of VEGFA mRNA and miR-27a in hippocampal tissues, and serum. ELISA was used to measure the content of VEGFA protein in serum, while western blotting was employed to determine the expression of VEGFA protein in hippocampal tissues. A dual luciferase assay was carried out to identify the interactions between VEGFA mRNA and miR-27a. The rats in the depression model group showed depression symptoms and the depression model was successfully constructed. Rats with depression had lower VEGFA mRNA and protein expression in the hippocampus, and peripheral blood compared with the control group. Rats in the depression model group had reduced levels of miR-27a in the hippocampus and peripheral blood, which may be associated with the levels of VEGFA. miR-27a was able to bind with the 3′-untranslated region of VEGFA mRNA to regulate its expression. The present study demonstrated that miR-27a expression in hippocampal tissues and blood from rats with depression is upregulated, while the expression of VEGFA mRNA and protein is downregulated. miR-27a may participate in the pathological process of depression in rats by regulating VEGFA.