Gene expression microarrays have provided many insights into changes in gene expression patterns between different tissue types, developmental stages, and disease states.
However, in biomedical media, changes in the refractive index can occur between different tissue types.
Remarkably, dysregulated metabolic and cardiac profiles were not driven by disruption of the molecular clockwork, nor by a loss of phase synchrony between different tissue oscillators (internal desynchrony).
Microarray assays, qRT-PCR and high-throughput sequencing have all been used to identify differentially expressed miRNAs in disease states, between different tissues and during development (Davidson et al., 2010; Liang et al., 2013; Wu et al., 2012a).
This may well be due to differences in methodology, but the effect of septic plasma on mitochondrial respiration is still not fully described and may well vary between different tissues or the (patho- physiological state of the individual tissues.
However, cell size and metabolic state varies between different tissues and plant species and the total number of cells is difficult to estimate because the number of partially cut cells contained in thin cryosections depends on the section thickness.
Reference gene stability may vary between different tissues, and between the same tissue in different disease states.
Efficiency also varies between different tissues or organs.
Statistical tests were performed to compare the expression between different tissues and groups of tissues for each aquaporin group.
While initially plant models were unicellular representations of metabolism, not distinguishing between different tissues, recent efforts tend to refine these models and generate multi-tissue representations32.
