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- Katsoulis, J, et al.
(författare)
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Impact of sample storage on detection of periodontal bacteria.
- 2005
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Ingår i: Oral Microbiology and Immunology. - 0902-0055 .- 1399-302X. ; 20:2, s. 128-130
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND/AIMS: Information on the impact of sample storage prior to analysis by DNA methods is limited. The aim of this study was to investigate the effect of subgingival sample storage on bacterial detection and enumeration.MATERIAL AND METHODS: Subgingival plaque samples were studied by a) checkerboard DNA-DNA hybridization by immediate processing, b) storage at + 4 degrees C for 6 weeks, c) storage at - 20 degrees C for 6 months or d) storage at - 20 degrees C for 12 months.RESULTS: No differences in total DNA were found between protocol 1 and 2, or between protocol 3 and 4. Protocol 1 yielded 2.4 times more total bacterial DNA than did protocol 3 (P < 0.001). Actinobacillus actinomycetemcomitans and Campylobacter gracilis were detected in 21.1% of the immediately processed samples but only in 6.6% of the samples after 12 months of storage. Similar changes were noticed for Treponema denticola, which was detected in 22.3% and 9.2%, respectively. Streptococci spp., Fusobacterium nucleatum and Tannerella forsythia did not seem to be affected by storage. In contrast, the level of Campylobacter rectus detection frequency changed from 2.6% if processed immediately to 15.8% if samples were stored for 12 months.CONCLUSIONS: In longitudinal clinical studies including microbiological samples and processed with DNA-DNA hybridization methods, samples should be stored for the same period of time before processing to avoid loss of microbiological information.
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- van Toor, Mariëlle L., et al.
(författare)
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Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity
- 2018
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Ingår i: Landscape Ecology. - : Springer. - 0921-2973 .- 1572-9761. ; 33:6, s. 879-893
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Tidskriftsartikel (refereegranskat)abstract
- High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species' potential to link patches or populations are of importance. We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories' plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range. We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species' range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature. Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species. We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.
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