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: Kras mutation is a common phenomenon in many human neoplasms. We aimed to assess the Kras mutational status along the histological continuum from normal ovaries to the development of benign, borderline and malignant ovarian mucinous neoplasms. We analyzed 41 cases of malignant, 10 cases of borderline, 7 cases of benign mucinous ovarian tumors and 7 cases of normal ovarian tissue. The prevalence of Kras mutations in the normal ovary was 0.00% (n=0/7), while the prevalence in benign, borderline and malignant mucinous neoplasms was 57.14% (n=4/7), 90.00% (n=9/10) and 75.61% (n=31/41), respectively. Multiple Kras mutations were detected in 6 cases of mucinous carcinoma, including 5 double mutations with G13D/V14I (n=1), G12V/G13S (n=1), G12D/G13S (n=3) and one triple mutation with A11V/G13N/V14I (n=1). We identified six cases with 3 novel Kras mutations not previously described in the COSMIC database, which included A11V (n=3) and V14I (n=2) in mucinous carcinomas, and A11T (n=1) in a mucinous borderline tumor. In conclusion, Kras mutation appears to be one of the imperative events in the ovarian mucinous adenoma-borderline tumor-carcinoma sequence, as increased numbers of Kras mutations have been shown to be the strongest predictor of unequivocal malignancy in ovarian mucinous neoplasms.
Solution:
Multipoint Kras oncogene mutations potentially indicate mucinous carcinoma on the entire spectrum of mucinous ovarian neoplasms