BACKGROUND:Mouse nerve growth factor can promote the repair and regeneration of injured nerves, but current experimental research shows that the effects of different treatment methods are stil controversial.
OBJECTIVE:To evaluate the effect of mouse nerve growth factor injection via different ways on the treatment of peripheral nerve injury.
METHODS:Total y 52 patients with peripheral nerve injury were randomly assigned into two groups:experimental group (local injection of mouse nerve growth factor, n=27) and control group (systemic administration of mouse nerve growth factor, n=25). The treatment was performed once a day, and lasted for 4 weeks. Then, the clinical efficacy and recovery of neurological function were compared.
RESULTS AND CONCLUSION:The good and effective rates were 85%(n=23) and 93%(n=25) in the experimental group, while 72%(n=18) and 84%(n=21) in the control group, respectively, which were significantly better in the experimental group than the control group (P<0.05). In the experimental group, 13 cases developed transient pain at injection site, including one case of remission undergoing oral analgesics;in the control group, 12 cases had transient pain at injection site, without any treatment. The results suggest that both local and total body injection of mouse nerve growth factor are safe and effective for treatment of peripheral nerve injury, but local injection is superior to systemic administration.

Genomic studies of cancer cell alterations,such as mutations,copy number variations(CNVs),and translocations,greatly promote our understanding of the genesis and development of cancers.However,the 3D genome architecture of cancers remains less studied due to the complexity of cancer genomes and technical difficulties.To explore the 3D genome structure in clin-ical lung cancer,we performed Hi-C experiments using paired normal and tumor cells harvested from patients with lung cancer,combining with RNA sequenceing analysis.We demonstrated the feasibility of studying 3D genome of clinical lung cancer samples with a small number of cells(1×104),compared the genome architecture between clinical samples and cell lines of lung cancer,and identified conserved and changed spatial chromatin structures between normal and cancer sam-ples.We also showed that Hi-C data can be used to infer CNVs and point mutations in cancer.By integrating those different types of cancer alterations,we showed significant associations between CNVs,3D genome,and gene expression.We propose that 3D genome mediates the effects of cancer genomic alterations on gene expression through altering regulatory chromatin structures.Our study highlights the importance of analyzing 3D genomes of clinical cancer samples in addition to cancer cell lines and provides an integrative genomic analysis pipeline for future larger-scale studies in lung cancer and other cancers.