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Experiments 1 and 2 represent data derived from INS GFP/w MEL1 hESCs differentiated using a flat culture protocol based on D'Amour et al., whilst experiments 3 and 4 represent data generated from INS GFP/w HES3 hESCs differentiated as described by Nostro et al., 2011.
However, whilst experiments on equine cartilage can provide extremely useful data, equine cartilage can be hard to obtain and standardized and the use of cartilage from a more readily obtainable species, e.g. rat, may be useful in the elucidation of cellular and molecular events that occur with SIL.
However, it has recently been argued that the role of plant genetic variation in structuring arthropod communities has been considerably inflated due to the common methodological flaw that genotypes are collected from diverse and often distant environments, which maximizes genetic variation, whilst experiments are performed in a single common garden where environmental variation is minimized.
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Experiment 1 was conducted on a 1.5-T Siemens Sonata system whilst Experiment 3 used a 3 T Siemens Allegra system.
In terms of total dry matter, however, vegetative growth almost fully compensated for the lack of fruit growth and side shoot growth in experiment RZR1, whilst in experiment RZR2 there was only partial compensation for the restriction of fruit and side shoot growth (Table 1).
Second, whilst placebo control experiments do not show any characteristic sustained trend of oscillator modulation over the period of the experiment, there are clear fluctuations in intrinsic oscillations over the course of the experiment.
Pilots were asked to keep an extra lookout whilst the experiments were taking place.
Whilst our experiments do not identify what this role is they do provide a means to study this phenomenon in vitro.
Furthermore, whilst transcriptomic experiments highlighted genes whose expression was significantly altered during fermentation, these genes are not necessarily required for fermentation reliability.
Whilst our experiments show that rule-based methods produce the best results, our best performing machine-learned classifier (CRF) achieves competitive performance, and alleviates the need for manual rule construction.
Whilst the experiments in Fig 5 are an interesting attempt to address the function of Foxp3 with respect to cytokine dependence, the conclusions are not fully supported by the data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com