Effects of mutations involving cell division, recombination, and chromosome dimer resolution on a priA2∷kan mutant

Recombinational repair of replication forks can occur either to a crossover (XO) or noncrossover (non-XO) depending on Holliday junction resolution. Once the fork is repaired by recombination, PriA is important for restarting these forks in Escherichia coli. PriA mutants are Rec− and UV sensitive and have poor viability and 10-fold elevated basal levels of SOS expression. PriA sulB mutant cells and their nucleoids were studied by differential interference contrast and fluorescence microscopy of 4′,6-diamidino-2-phenylindole-stained log phase cells. Two populations of cells were seen. Eighty four percent appeared like wild type, and 16% of the cells were filamented and had poorly partitioned chromosomes (Par−). To probe potential mechanisms leading to the two populations of cells, mutations were added to the priA sulB mutant. Mutating sulA or introducing lexA3 decreased, but did not eliminate filamentation or defects in partitioning. Mutating either recA or recB virtually eliminated the Par− phenotype. Filamentation in the recB mutant decreased to 3%, but increased to 28% in the recA mutant. The ability to resolve and/or branch migrate Holliday junctions also appeared crucial in the priA mutant because removing either recG or ruvC was lethal. Lastly, it was tested whether the ability to resolve chromosome dimers caused by XOs was important in a priA mutant by mutating dif and the C-terminal portion of ftsK. Mutation of dif showed no change in phenotype whereas ftsK1∷cat was lethal with priA2∷kan. A model is proposed where the PriA-independent pathway of replication restart functions at forks that have been repaired to non-XOs.

An O(N log N) algorithm for shape modeling.

We present a shape-recovery technique in two dimensions and three dimensions with specific applications in modeling anatomical shapes from medical images. This algorithm models extremely corrugated structures like the brain, is topologically adaptable, and runs in O(N log N) time, where N is the total number of points in the domain. Our technique is based on a level set shape-recovery scheme recently introduced by the authors and the fast marching method for computing solutions to static Hamilton-Jacobi equations.

Quantitative analysis of senile plaques in Alzheimer disease: observation of log-normal size distribution and molecular epidemiology of differences associated with apolipoprotein E genotype and trisomy 21 (Down syndrome).

The discovery that the epsilon 4 allele of the apolipoprotein E (apoE) gene is a putative risk factor for Alzheimer disease (AD) in the general population has highlighted the role of genetic influences in this extremely common and disabling illness. It has long been recognized that another genetic abnormality, trisomy 21 (Down syndrome), is associated with early and severe development of AD neuropathological lesions. It remains a challenge, however, to understand how these facts relate to the pathological changes in the brains of AD patients. We used computerized image analysis to examine the size distribution of one of the characteristic neuropathological lesions in AD, deposits of A beta peptide in senile plaques (SPs). Surprisingly, we find that a log-normal distribution fits the SP size distribution quite well, motivating a porous model of SP morphogenesis. We then analyzed SP size distribution curves in genotypically defined subgroups of AD patients. The data demonstrate that both apoE epsilon 4/AD and trisomy 21/AD lead to increased amyloid deposition, but by apparently different mechanisms. The size distribution curve is shifted toward larger plaques in trisomy 21/AD, probably reflecting increased A beta production. In apoE epsilon 4/AD, the size distribution is unchanged but the number of SP is increased compared to apoE epsilon 3, suggesting increased probability of SP initiation. These results demonstrate that subgroups of AD patients defined on the basis of molecular characteristics have quantitatively different neuropathological phenotypes.