Research community detection from multi-relation researcher network based on structure/attribute similarities

Purpose: This paper aims to provide a method to detect research communities based on research interest in researcher network, which combines the topological structure and vertex attributes in a unified manner.Design/methodology/approach: A heterogeneous researcher network has been constructed by combining multiple relations of academic researchers. Vertex attributes and their similarities were considered and calculated. An approach has been proposed and tested to detect research community in research organizations based on this multi-relation researcher network.Findings: Detection of topologically well-connected, semantically coherent and meaningful research community was achieved.Research limitations: The sample size of evaluation experiments was relatively small. In the present study, a limited number of 72 researchers were analyzed for constructing researcher network and detecting research community. Therefore, a large sample size is required to give more information and reliable results.Practical implications: The proposed multi-relation researcher network and approaches for discovering research communities of similar research interests will contribute to collective innovation behavior such as brainstorming and to promote interdisciplinary cooperation.Originality/value: Recent researches on community detection devote most efforts to singlerelation researcher networks and put the main focus on the topological structure of networks.In reality, there exist multi-relation social networks. Vertex attribute also plays an important role in community detection. The present study combined multiple single-relational researcher networks into a multi-relational network and proposed a structure-attribute clustering method for detecting research community in research organizations.

Deciphering the regulatory and catalytic mechanisms of an unusual SAM-dependent enzyme

S-adenosyl-1-methionine(SAM)-dependent enzymes regulate various disease-related behaviors in all organisms.Recently,the leporin biosynthesis enzyme LepI,a SAM-dependent enzyme,was reported to catalyze pericyclic reactions in leporin biosynthesis;however,the mechanisms underlying LepI activation and catalysis remain unclear.This study aimed to investigate the molecular mechanisms of LepI.Here,we reported crystal structures of LepI bound to SAM/5′-deoxy-5′-(methylthio)adenosine(MTA),S-adenosyl-homocysteine(SAH),and SAM/substrate states.Structural and biochemical analysis revealed that MTA or SAH inhibited the enzyme activities,whereas SAM activated the enzyme.The analysis of the substrate-bound structure of LepI demonstrated that this enzymatic retro-Claisen rearrangement was primarily driven by three critical polar residues His133,Arg197,Arg295 around the active site and assisted by SAM with unclear mechanism.The present studies indicate that the unique mechanisms underlying regulatory and catalysis of the unusual SAM-dependent enzyme LepI,not only strengthening current understanding of the fundamentally biochemical catalysis,but also providing novel insights into the design of SAM-dependent enzyme-specific small molecules.

A booster with SARS-CoV-2 vaccines:protection against Omicron infection

Recently,Wang et al.published a study in Nature that examined whether sera from individuals who received two or three doses of the inactivated vaccine could neutralize Omicron.1 Broad-spectrum and potent neutralizing antibodies were isolated from three-dose recipients,which could effectively neutralize strain pseudoviruses and authentic viruses of SARS-CoV-2 of concern(VOCs),including Omicron.In addition,the cryo-EM structures of the Omicron spike were elucidated,revealing a new critical immune evasion site and mechanism for the Omicron strain.