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Most bacterial genomes encode different secretion systems (such as toxin-antitoxin systems, pump efflux systems and ABC protein exporters), which provide versatile responses and adaptations to environmental changes.
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Stem cell-based therapy is a new strategy in the treatment of acute kidney injury and has potentially more value than single-agent drug therapy due to the highly versatile response of cells to their environment [ 2].
These modifications in the availability and activity of growth factors and cytokines by defined constituents of the ECM contribute to the versatile response of cells to a changing environment.
Macrophages are highly plastic and very versatile in response to microenvironment stimuli, including cues released by neoplastic cells [ 15– 17].
It is known that other organisms will exchange cytochrome C oxidase subunits to remain more metabolically versatile in response to changing redox state [ 33].
The efficiency of light energy capture and conversion, critical for primary production in ecosystems, relies on the rapid expansion of thylakoids and their versatile reorganization in response to light changes.
The expression of CAM phases can be modulated in a versatile way in response to environmental stress.
The expression profiles derived from reverse transcription and quantitative PCR suggested that a large number of VpCDPKs responded to various stimuli on the transcriptional level, indicating their versatile roles in the responses to biotic and abiotic stresses.
All of these binding features, out of which many are exposed in the RNAPII TFIIF complex, enable contacts and distinct (i.e., gene-specific) responses with versatile partners and thereby contribute to the complex signaling mechanism of the Mediator.
They attain their greatest diversity and biomass as epiphytes and hemi-epiphytes growing in moist tropical forests where the high plasticity inherent in CAM performance allows rapid, versatile and readily reversible responses to stressful multi-factor environmental situations.
In this paper we propose a very transparent and versatile method for simulating response and predictor data from a multiple linear regression model which hopefully may serve as a standard tool simulating linear model data.
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