Costunolide (CE) and dehydrocostuslactone (DE) are derived from many species of medicinal plants, such as Saussurea lappa Decne and Laurus nobilis L. They have been reported for their wide spectrum of biological effects, including anti-inflammatory, anticancer, antiviral, antimicrobial, antifungal, antioxidant, antidiabetic, antiulcer, and anthelmintic activities. In recent years, they have caused extensive interest in researchers due to their potential anti-cancer activities for various types of cancer, and their anti-cancer mechanisms, including causing cell cycle arrest, inducing apoptosis and differentiation, promoting the aggregation of microtubule protein, inhibiting the activity of telomerase, inhibiting metastasis and invasion, reversing multidrug resistance, restraining angiogenesis has been studied. This review will summarize anti-cancer activities and associated molecular mechanisms of these two compounds for the purpose of promoting their research and application.

Much evidence suggested that cholesterol, eicosanoid and phospholipid metabolism plays crucial roles in inflammation, atherosclerosis, carcinogenesis, etc. Therefore, fast and accurate quantification of the metabolites in these metabolic pathways is necessary for discovering the molecular mechanisms and biomarkers of related diseases. In this assay, ultra-high performance liquid chromatography combined with triple quadrupole mass spectrometry platform (UPLC-QqQ-MS) based protocols were developed to simultaneously quantify a total of 104 key metabolites including 32 phospholipids (PLs), 44 eicosanoids (EAs), 28 oxysterols and bile acids (BAs), within 15 minutes. Validation results showed that this method is stable, sensitive and accurate for analyzing different matrix samples. Next, this method was used to characterize the metabolic phenotype of a CCl₄-induced liver injury model. The results showed that polyunsaturated fatty acids (PUFA) and PUFA acyl-phospholipids (PFA-PLs) were down-regulated and the levels of saturated fatty acyl-phospholipids (SFA-PLs) and EAs were up-regulated in both the liver tissue and plasma of the CCl₄-injury group. BAs were up-regulated in plasma, but down-regulated in the liver tissue of the CCl₄-injury group. Immunohistochemistry assay demonstrated that the expression levels of cytosolic phospholipase A2 (cPLA2), phosphorylated cytosolic phospholipase A2 (p-cPLA2), secreted phospholipase A2-IIA (sPLA2-IIA) and lysophosphatidylcholine acyltransferase 1 (LPCAT1) were all up-regulated. According to our results, we drew a diagram of the CCl₄-induced acute liver injury molecular mechanism. Moreover, we found that the area under the receiver operating characteristic curve (AUC) of 7α-hydroxycholesterol and 7β-hydroxycholesterol was 1.0, which indicates that the two metabolites have significant potential for the diagnosis of acute liver injury. The outstanding performance of this analytical method proves its further usefulness for mechanism studies and biomarker screening of related diseases.

Background: Survivin and octamer-binding transcription factor 4 (OCT4) are reportedly up-regulated in esophageal cancer (EC) and have been correlated with high tumor proliferative activity and poor prognosis. Oncolytic viruses encoding specific transgenes have been considered as therapeutic methods to increase therapeutic efficacy in a variety of solid tumors. Methods: In this study, an oncolytic adenovirus carrying short hairpin RNA (shRNA) of survivin (shSRVN) and OCT4 (shOCT4) was constructed to achieve dual knockdown of survivin and OCT4 and to explore the potential effect of the oncolytic adenovirus in EC. Results: The oncolytic adenovirus replicated abundantly in human EC cells, with the replication multiplying by up to 192,085 and 620,055 times in esophageal carcinoma (Eca)-109 cells transfected with purified and completed recombinant adenoviruses called AdSProE1a-dual shRNA (shSRVN + shOCT4) and TE1 cells transfected with AdSProE1a-survivin shRNA (shSRVN) 96 hours after infection, respectively. The shRNAs targeting survivin and OCT4 significantly downregulated the expression levels of survivin and OCT4 in cells, thereby inhibiting the proliferative activity of cancer cells. Furthermore, E-cadherin and vimentin, which are both considered epithelial mesenchymal transition (EMT) markers, were found to be upregulated and downregulated, respectively, in cancer cells after exposure to the viral infection. The interference of survivin and OCT4 also contributed to cell cycle arrest and apoptosis, the half maximal inhibitory concentrations (IC50s) of oncolytic adenovirus loaded with AdSProE1a-shSRVN + shOCT4 in the Eca109 cells and the TE1 cells were 0.7271 and 0.1032 pfu/mL, respectively. Xenograft experiments in vivo showed that oncolytic adenovirus-mediated dual knockdown of survivin and OCT4 effectively inhibited the growth of xenografts and induced cancer cell apoptosis. We concluded that therapies targeting survivin and OCT4 have great potential for improving the therapeutic efficacy in EC. Conclusions: The dual target design strategy ensured the efficacy and safety of the treatment system and provided a novel and effective adjuvant target therapy for EC.

Super-resolution reconstruction has attracted increasing research interest in mass spectrometry imaging (MSI), but it remains a challenging ill-posed problem. In the present study, we proposed a Deep learning based SUper-REsolution model called DeepSURE, where the hematoxylin and eosin (H&E) stain microscopy image is used to pose constrains in the process of super-resolution reconstruction to alleviate the ill-poseness. A novel model architecture is designed to achieve multi-task optimization by incorporating multi-modal image registration and fusion in a mutual reinforced framework. The present results demonstrated that the DeepSURE method is able to produce super-resolution reconstruction image with rich chemical information and detailed structure both on visual inspection and quantitative evaluation. In addition, the method was found able to improve the delimitation of boundary between cancerous and para-cancerous regions in MSI image. Furthermore, the reconstruction of low-resolution spatial transcriptomics data demonstrates that the developed DeepSURE method may find wider applications in biomedical fields.