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The second model therefore enabled us to test for differences in mean activation levels between the pre-manifest Huntington's disease and control groups after controlling for heterogeneity in the pre-manifest Huntington's disease data accounted for by CAG repeat length and probability of manifest disease onset within 5 years.
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The model therefore enables an analysis of return that goes beyond dichotomies of success and failure of return (Cassarino, 2004).
The measurement model therefore enables us to comment on the validity and reliability of the measurement scale used for each construct.
Furthermore, this model therefore enables the effect of drugs to be tested on various human mutant KCNJ10.
The model therefore enables estimates for the total percentage of new infections in different population subgroups to be calculated.
Our mouse models therefore enabled us to study the absence of HDAC4 in a spatially and temporally selective fashion.
The corresponding models therefore enable further exploration of brain-specific metabolic functions and identification of drug targets that specifically kill tumor cells with minimal side effects on normal tissues.
Collectively, these data confirmed the reliability of the prediction model and therefore enabled us to extend the use of this method to multiple strains.
Comparison of the model predictions with the experimental data therefore enabled us to isolate the combined roles of volume fraction and architecture from the role of tissue material properties.
In the study presented here, we used an experimental mouse model that sustained a long-term S. aureus infection and, therefore, enabled us to dissect the mechanisms of the host immune response during the persistent phase of infection.
Reduction modulo branching bisimulation usually results in a much smaller state space and therefore enables model checking of much larger state spaces.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com