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.

Example input: 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.
Example output: Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging.
Example explanation: This title is appropriate for the given abstract because the focus of this abstract is cerebral white matter assesment.
Q: Little is known about the inter-individual variation of cytokine responses to different pathogens in healthy individuals. To systematically describe cytokine responses elicited by distinct pathogens and to determine the effect of genetic variation on cytokine production, we profiled cytokines produced by peripheral blood mononuclear cells from 197 individuals of European origin from the 200 Functional Genomics (200FG) cohort in the Human Functional Genomics Project (http://www.humanfunctionalgenomics.org), obtained over three different years. We compared bacteria- and fungi-induced cytokine profiles and found that most cytokine responses were organized around a physiological response to specific pathogens, rather than around a particular immune pathway or cytokine. We then correlated genome-wide single-nucleotide polymorphism (SNP) genotypes with cytokine abundance and identified six cytokine quantitative trait loci (QTLs). Among them, a cytokine QTL at the NAA35-GOLM1 locus markedly modulated interleukin (IL)-6 production in response to multiple pathogens and was associated with susceptibility to candidemia. Furthermore, the cytokine QTLs that we identified were enriched among SNPs previously associated with infectious diseases and heart diseases. These data reveal and begin to explain the variability in cytokine production by human immune cells in response to pathogens.
A:
Inter-individual variability and genetic influences on cytokine responses to bacteria and fungi