22 research outputs found
Effector XopQ-induced stromule formation in Nicotiana benthamiana depends on ETI signaling components ADR1 and NRG1
Principles and application of LIMS in mouse clinics.
Large-scale systemic mouse phenotyping, as performed by mouse clinics for more than a decade, requires thousands of mice from a multitude of different mutant lines to be bred, individually tracked and subjected to phenotyping procedures according to a standardised schedule. All these efforts are typically organised in overlapping projects, running in parallel. In terms of logistics, data capture, data analysis, result visualisation and reporting, new challenges have emerged from such projects. These challenges could hardly be met with traditional methods such as pen & paper colony management, spreadsheet-based data management and manual data analysis. Hence, different Laboratory Information Management Systems (LIMS) have been developed in mouse clinics to facilitate or even enable mouse and data management in the described order of magnitude. This review shows that general principles of LIMS can be empirically deduced from LIMS used by different mouse clinics, although these have evolved differently. Supported by LIMS descriptions and lessons learned from seven mouse clinics, this review also shows that the unique LIMS environment in a particular facility strongly influences strategic LIMS decisions and LIMS development. As a major conclusion, this review states that there is no universal LIMS for the mouse research domain that fits all requirements. Still, empirically deduced general LIMS principles can serve as a master decision support template, which is provided as a hands-on tool for mouse research facilities looking for a LIMS
Table 1: Mass spectrometry imaging data sets. AP-MALDI-Atmospheric pressure matrix assisted laser desorption/ionization, DESI-Desorption electrospray ionization, LAESI-Laser ablation/electrospray ionization, LTP-Low-temperature plasma, Res.-lateral resolution, Tol.-mass tolerance. References: Oetjen et al. (2015), Zheng, Bartels & Svatoš (2020), Maldonado-Torres et al. (2014), Maldonado-Torres et al. (2017), Römpp et al. (2010), Römpp et al. (2014).
Association of nerve growth factor and vascular endothelial growth factor A with psychometric measurements of opiate dependence: results of a pilot study in patients participating in a structured diamorphine maintenance program
Preclinical study results suggest that neurotrophic peptides like nerve growth factor (NGF) and vascular endothelial growth factor A (VEGF-A) may be associated with symptoms of addictive behavior like withdrawal symptoms and rewarding effects. We investigated alterations in NGF and VEGF-A serum levels in opiate-dependent patients (25 male patients), who received diamorphine (DAM, heroin) treatment within a structured opiate maintenance program, and compared the results with the NGF and VEGF-A serum levels of healthy controls (23 male controls). NGF and VEGF-A serum levels were assessed before and after DAM administration twice a day (in the morning (16 h after last application--t1) and in the afternoon (7 h after last application--t3)) in order to detect a possible immediate or summative (in the afternoon) heroin effect on these two neuropeptides. Moreover, we investigated possible associations between the serum levels of these neurotrophic growth factors and psychometric dimensions of addictive behavior, e.g. craving, withdrawal, depression. Whereas there was no direct effect of DAM application on the serum levels of both neurotrophic growth factors neither in the morning nor in the afternoon, the NGF serum levels of the patient group were found to be significantly increased at all four time points of investigation compared with the healthy controls. In contrast, VEGF-A serum levels did not differ significantly in the patient and control groups. We found a significant positive association between the NGF serum levels and several items of the short opiate withdrawal scale as well as a negative association between self-reported mood (measured by visual analogue scale) and mood before heroin application (in the morning as in the afternoon). Moreover, we found a significant positive association between the NGF serum levels (t1 and t3) and the self-reported craving for methadone. In contrast, we found a negative association between the VEGF-A serum levels and avoidance, anxiety, suicide intentions of the SCL-90 as well as a positive association between the VEGF-A serum levels and the subscales of the heroin craving questionnaire measuring the rewarding effects of heroin. In conclusion, the results of this pilot study show that there might be an association between symptoms of opiate dependence and withdrawal and serum levels of VEGF-A and NGF
Identifiers for the 21st century:How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data.
In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines
Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data.
In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines