Involvement of regulatory volume decrease in the migration of nasopharyn-geal carcinoma cells

The transwell chamber migration assay and CCD digital camera imaging techniques were used to investigate the relationship between regulatory volume decrease (RVD) and cell migration in nasopharyngeal carcinoma cells (CNE-2Z cells). Both migrated and non-migrated CNE-2Z cells, when swollen by 47% hypotonic solution, exhibited RVD which was inhibited by extracellular application of chloride channel blockers adenosine 5’-triphosphate (ATP), 5-nitro-2-(3- phenylpropylamino) benzoic acid (NPPB) and tamoxifen. However, RVD rate in migrated CNE-2Z cells was bigger than that of non-migrated cells and the sensitivity of migrated cells to NPPB and tamoxifen was higher than that of non- migrated cells. ATP, NPPB and tamoxifen also inhibited migration of CNE-2Z cells. The inhibition of migration was positively correlated to the blockage of RVD, with a correlation coefficient (r) = 0.99, suggesting a functional relation- ship between RVD and cell migration. We conclude that RVD is involved in cell migration and RVD may play an important role in migratory process in CNE-2Z cells.

Xiongzhi Dilong decoction interferes with calcitonin gene-related peptide(CGRP)-induced migraine in rats through the CGRP/iNOS pathway

Objective: To evaluate the effects of Xiongzhi Dilong decoction(XZDLD) and its wind medicine on calcitonin gene-related peptide(CGRP)-induced migraine and explore the mechanism through the CGRP/inducible nitric oxide synthase(iNOS) pathway.Methods: Rats were divided into control, model, XZDLD, XZDLD(external wind), XZDLD(internal wind),and olcegepant groups. CGRP was injected into the dura mater to induce a migraine. The frequency of head scratching, cage climbing, and facial grooming was observed. The pain threshold, the levels of CGRP,pituitary adenylate cyclase activating polypeptide(PACAP), substance P(SP), and the plasma protein extravasation(PPE) ratio were measured. The phosphorylation levels of p38, extracellular signalregulated kinase 1/2(ERK1/2), and expression of iNOS were detected by western blot.Results: Compared with the model group, the three modified XZDLD groups showed reduced frequency of head scratching and cage climbing in the first 30 min(all P <.05). Facial grooming frequency was reduced in XZDLD and XZDLD(external wind) groups(P =.0003 and P =.0131, respectively). External wind medicine played a more important role in increasing mechanical pain threshold than internal wind medicine. Moreover, compared with the model group, the three modified XZDLD groups demonstrated reduced plasma levels of CGRP and PACAP(all P <.05). No difference in the SP level was observed among the six groups. XZDLD reduced PPE ratio. XZDLD and XZDLD(external wind) groups suppressed the CGRP/iNOS pathway by inhibiting the p-p38/p38 ratio and the expression of iNOS. No difference in pERK1/2/ERK1/2 ratio was detected among the six groups.Conclusion: XZDLD increases pain threshold, downregulates the expression of CGRP and PACAP, and reduces PPE ratio by inhibiting the CGRP/iNOS pathway. External wind medicine is more effective than internal one on improving facial grooming and head scratching, increasing the mechanical pain threshold, and inhibiting the expression of iNOS.

Transferable Features from 1D-Convolutional Network for Industrial Malware Classification

With the development of information technology,malware threats to the industrial system have become an emergent issue,since various industrial infrastructures have been deeply integrated into our modern works and lives.To identify and classify new malware variants,different types of deep learning models have been widely explored recently.Generally,sufficient data is usually required to achieve a well-trained deep learning classifier with satisfactory generalization ability.However,in current practical applications,an ample supply of data is absent in most specific industrial malware detection scenarios.Transfer learning as an effective approach can be used to alleviate the influence of the small sample size problem.In addition,it can also reuse the knowledge from pretrained models,which is beneficial to the real-time requirement in industrial malware detection.In this paper,we investigate the transferable features learned by a 1D-convolutional network and evaluate our proposed methods on 6 transfer learning tasks.The experiment results show that 1D-convolutional architecture is effective to learn transferable features for malware classification,and indicate that transferring the first 2 layers of our proposed 1D-convolutional network is the most efficient way to reuse the learned features.