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Open access

Lian Fei Cao, Huo Qing Zheng, Qi Yan Shu, Fu Liang Hu and Zi Wei Xu

Abstract

China is the largest producer and exporter of royal jelly in the world. The high production of royal jelly in China is mainly attributed to a high royal jelly-producing lineage of honeybees (Apis mellifera) (HRJB). However, few studies have been conducted on the genetic characterization of HRJB. In this study, the mitochondrial DNA intergenic region between cytochrome oxidase I and II (COI-COII) and the mitochondrial NADH dehydrogenase subunit 2 sequences (ND2) were determined for 90 HRJB colonies, collected from the regions of China where HRJB originated, and 25 unimproved A. m. ligustica colonies from China. COI-COII sequence analysis revealed two mitotypes (C1 and C2d) in HRJB colonies and one mitotype (C1) in unimproved A. m. ligustica colonies. The main mitotype (C1) in HRJB accounted for 93% of the colonies. Based on ND2 sequences, four and two mitotypes were found in HRJB and unimproved A. m. ligustica colonies, respectively. Sequence alignment showed that nucleotides in three positions of the ND2 sequence were different between the main mitotype of HRJB and that of unimproved A. m. ligustica. Our study suggested that HRJB was bred from A. m. ligustica and possibly had genetic characteristics different from unimproved A. m. ligustica.

Open access

Guoqiang Liang, Haiyan Hou, Zhigang Hu, Fu Huang, Yajie Wang and Shanshan Zhang

Abstract

Purpose

Research fronts build on recent work, but using times cited as a traditional indicator to detect research fronts will inevitably result in a certain time lag. This study attempts to explore the effects of usage count as a new indicator to detect research fronts in shortening the time lag of classic indicators in research fronts detection.

Design/methodology/approach

An exploratory study was conducted where the new indicator “usage count” was compared to the traditional citation count, “times cited,” in detecting research fronts of the regenerative medicine domain. An initial topic search of the term “regenerative medicine” returned 10,553 records published between 2000 and 2015 in the Web of Science (WoS). We first ranked these records with usage count and times cited, respectively, and selected the top 2,000 records for each. We then performed a co-citation analysis in order to obtain the citing papers of the co-citation clusters as the research fronts. Finally, we compared the average publication year of the citing papers as well as the mean cited year of the co-citation clusters.

Findings

The citing articles detected by usage count tend to be published more recently compared with times cited within the same research front. Moreover, research fronts detected by usage count tend to be within the last two years, which presents a higher immediacy and real-time feature compared to times cited. There is approximately a three-year time span among the mean cited years (known as “intellectual base”) of all clusters generated by usage count and this figure is about four years in the network of times cited. In comparison to times cited, usage count is a dynamic and instant indicator.

Research limitations

We are trying to find the cutting-edge research fronts, but those generated based on co-citations may refer to the hot research fronts. The usage count of older highly cited papers was not taken into consideration, because the usage count indicator released by WoS only reflects usage logs after February 2013.

Practical implications

The article provides a new perspective on using usage count as a new indicator to detect research fronts.

Originality/value

Usage count can greatly shorten the time lag in research fronts detection, which would be a promising complementary indicator in detection of the latest research fronts.