In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
One example: Alterations of the architecture of cerebral white matter in the developing human brain can affect cortical development and result in functional disabilities. A line scan diffusion-weighted magnetic resonance imaging (MRI) sequence with diffusion tensor analysis was applied to measure the apparent diffusion coefficient, to calculate relative anisotropy, and to delineate three-dimensional fiber architecture in cerebral white matter in preterm (n = 17) and full-term infants (n = 7). To assess effects of prematurity on cerebral white matter development, early gestation preterm infants (n = 10) were studied a second time at term. In the central white matter the mean apparent diffusion coefficient at 28 wk was high, 1.8 microm2/ms, and decreased toward term to 1.2 microm2/ms. In the posterior limb of the internal capsule, the mean apparent diffusion coefficients at both times were similar (1.2 versus 1.1 microm2/ms). Relative anisotropy was higher the closer birth was to term with greater absolute values in the internal capsule than in the central white matter. Preterm infants at term showed higher mean diffusion coefficients in the central white matter (1.4 +/- 0.24 versus 1.15 +/- 0.09 microm2/ms, p = 0.016) and lower relative anisotropy in both areas compared with full-term infants (white matter, 10.9 +/- 0.6 versus 22.9 +/- 3.0%, p = 0.001; internal capsule, 24.0 +/- 4.44 versus 33.1 +/- 0.6% p = 0.006). Nonmyelinated fibers in the corpus callosum were visible by diffusion tensor MRI as early as 28 wk; full-term and preterm infants at term showed marked differences in white matter fiber organization. The data indicate that quantitative assessment of water diffusion by diffusion tensor MRI provides insight into microstructural development in cerebral white matter in living infants.
Solution is here: Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging.
Explanation: This title is appropriate for the given abstract because the focus of this abstract is cerebral white matter assesment.

Now, solve this: Objective:To assess the relative validity and acceptability of the computerised 24-h recall 'Young Adolescent's Nutrition Assessment on Computer (YANA-C)'.Design:Food and nutrient intakes assessed with YANA-C were compared with food records (study 1) and 24-h dietary recall interviews (study 2).Main outcome measures:Intakes of food groups (fruit, fruit juice, vegetables, potatoes, bread, cereals, milk, cheese, other milk products, soft drinks, diet soft drinks, sugar/sweets, pastry/cookies, savoury snacks, butter/sauces, eggs, fish, meat) and nutrients (energy, carbohydrates, protein, fat, fiber, calcium, vitamin C and iron).Subjects and setting:A total of 237 pupils (1114 y) from two primary and four secondary schools (study 1: n=136; study 2: n=101) in Belgium-Flanders. Results:YANA-C proved to agree well with both standard methods in categorizing subjects in consumers and nonconsumers (study 1=0.480.92; study 2=0.380.90). Spearman's correlations for energy and nutrient intakes ranged between 0.44 and 0.79 for study 1 and between 0.44 and 0.86 for study 2. Nutrient and energy intakes were in general (excluding calcium) significantly higher in YANA-C in comparison with the food record, but not in comparison with the interview (only fiber). Statistics used to investigate whether YANA-C agreed with the other methods in ranking portions/amounts in consumers only were fair to moderate for most of the food groups (weighted study 1=0.110.55; study 2=0.040.73); amounts in consumers only, were significantly lower in YANA-C against both standards for cereals; amounts were significantly higher in YANA-C against the food record for milk, soft drinks, sugar/sweets and savoury snacks and against the interview for potatoes. Only a few pupils evaluated the program negatively. Conclusion:YANA-C is a promising method to collect detailed dietary information from young adolescents with relatively low staff resources, useful in many nutrition research applications.
Solution:
Young adolescents' nutrition assessment on computer (YANA-C)