Summary:Nerve repair cannot always be achieved by the conventional end-to-end technique. This study evaluated the functional recovery of nerves repaired with end-to-side neurorrhaphy in a rat model. The right peroneal nerves of 80 female rats were transectcd and divided into four groups. In group A, the nerve ends were separated and remained unrepaired; in group €3, the distal peroneal ends were directly sutured to the epineurium of the tibia1 nerves in end-to-side fashion; in group C, the distal ends were sutured through an epineurial window at the repair site in end-to-side fashion; and in group D, the nerve ends were reconnected by the traditional end-to-end technique. Evaluation included gait analysis by calculation of a peroneal functional index, measurement of contractile function of the extensor digitorum longus muscle, wet weight of the extensor digitorum longus, and histological cxamination. The findings of this study suggested the following: (a) end-to-side neurorrhaphy allows effective motor functional recovery, demonstrated by earlier improvement of the peroneal functional index, stronger muscle contractile function, greater muscle weight, and higher density of regenerated axons compared with unrepaired nerves; (b) removal of the epineurium of the donor nerve at the nerve coaptation site increases the cffectiveness of end-to-side neurorrhaphy, but the cpineurium appears to be a partial barrier to axonal regeneration; (c) removal of the epineurium docs not affect the structure and function of the donor nerve; and (d) end-to-end repair achieved the best functional recovery among the four groups; therefore, end-to-side repair should he considered as a potential alternative only when no proximal nerve is available.

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations.