The impact of the COVID-19 pandemic on scientific research in the life sciences

The COVID-19 outbreak has posed an unprecedented challenge to humanity and science. On the one side, public and private incentives have been put in place to promptly allocate resources toward research areas strictly related to the COVID-19 emergency. But on the flip side, research in many fields not directly related to the pandemic has lagged behind. In this paper, we assess the impact of COVID-19 on world scientific production in the life sciences. We investigate how the usage of medical subject headings (MeSH) has changed following the outbreak. We estimate through a difference-in-differences approach the impact of COVID-19 on scientific production through PubMed. We find that COVID-related research topics have risen to prominence, displaced clinical publications, diverted funds away from research areas not directly related to COVID-19 and that the number of publications on clinical trials in unrelated fields has contracted. Our results call for urgent targeted policy interventions to reactivate biomedical research in areas that have been neglected by the COVID-19 emergency

A network approach to expertise retrieval based on path similarity and credit allocation

With the increasing availability of online scholarly databases, publication records can be easily extracted and analysed. Researchers can promptly keep abreast of others' scientific production and, in principle, can select new collaborators and build new research teams. A critical factor one should consider when contemplating new potential collaborations is the possibility of unambiguously defining the expertise of other researchers. While some organisations have established database systems to enable their members to manually produce a profile, maintaining such systems is time-consuming and costly. Therefore, there has been a growing interest in retrieving expertise through automated approaches. Indeed, the identification of researchers' expertise is of great value in many applications, such as identifying qualified experts to supervise new researchers, assigning manuscripts to reviewers, and forming a qualified team. Here, we propose a network-based approach to the construction of authors' expertise profiles. Using the MEDLINE corpus as an example, we show that our method can be applied to a number of widely used data sets and outperforms other methods traditionally used for expertise identification

Stress resistance and C1 metabolism involved in plant colonization of a methanotroph Methylosinus sp. B4S

Methanotrophs are widespread and have been isolated from various environments including the phyllosphere. In this study, we characterized the plant colonization by Methylosinus sp. B4S, an α-proteobacterial methanotroph isolated from plant leaf. The gfp-tagged Methylosinus sp. B4S cells were observed to colonize Arabidopsis leaf surfaces by forming aggregates. We cloned and sequenced the general stress response genes, phyR, nepR and ecfG, from Methylosinus sp. B4S. In vitro analysis showed that the phyR expression level was increased after heat shock challenge, and phyR was shown to be involved in resistance to heat shock and UV light. In the phyllospheric condition, the gene expression level of phyR as well as mmoX and mxaF was found to be relatively high, compared with methane-grown liquid cultures. The phyR-deletion strain as well as the wild-type strain inoculated on Arabidopsis leaves proliferated at the initial phase and then gradually decreased during plant colonization. These results have shed light firstly on the importance of general stress resistance and C1 metabolism in methanotroph living in the phyllosphere