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Last year, Science reported on a NICHD workshop where planning began for a Human Placenta Project that would aim to monitor the placenta during a woman's pregnancy, using new imaging approaches, tests for fetal molecules shed into a mother's blood, and other tools.
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With several technological advances, the options for treatment must be carefully weighed and novel approaches tested for safety and efficacy.
Transfer learning approaches tested for this experiment include the approach by Pan [87], Gong [42], and Si [109].
Many different approaches tested for treating this disease failed to improve survival [ 1].
Table 3 shows the statistical approaches tested for each set of available training data.
Accordingly, in approaches testing for statistically significant evolution of phenotype by natural selection, gross phenotypic difference has historically been precisely the signal assessed (Lande 1976, 1977; Lande and Arnold, 1983; Lynch 1990; Turelli et al. 1988; Charlesworth 1984).
The multivariate approach tests for general changes; when this is significant, univariate approach tests for CpG site punctual effects.
This 'discovery' approach tests for differences between patients and controls in the connectivity of every pair of brain voxels at a whole-brain level.
Structural equation modeling (a model-based approach) tests for a change in the magnitude of factor loadings on a common latent variable over time [ 30, 31].
This approach tests for the cumulative effect across many genes, which enables the detection of effects at the biological pathway level.
Here, we validate this approach, testing for differential uterine horn hyperglycemic exposure using positron emission tomography (PET) imaging and glucose metabolic tracers to define the temporal and spatial disposition of locally infused glucose.
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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