Primary outcome measures were uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), contrast sensitivity, and higher order aberrations.\n\nRESULTS: At 6 months, mean values

for UDVA (logMAR) were -0.064 +/- 0.077 and -0.051 +/- 0.070 in the 120-mu m and 90-mu m groups, respectively (n=40, P=.431). Visual acuity of 20/20 was achieved in 98% of eyes with 120-mu m flaps and 95% of eyes with 90-mu m flaps, whereas 20/15 vision was achieved in 50% of eyes with 120-mu m flaps and 45% of eyes with 90-mu m flaps (P >=.454). Both groups had significant increases in total higher order aberrations PF-00299804 mw (P <=.003). Significant differences were not found between groups in contrast sensitivity (P >=.258), CDVA (P >=.726), total higher order aberrations (P >=.477), or patient-reported outcomes (P >=.132). Patients in both groups reported increased quality of life postoperatively (P <=.002).\n\nCONCLUSIONS: Under well-controlled surgical conditions, thin-flap LASIK achieved similar results in visual acuity, contrast sensitivity, and low induction of higher order aberrations in eyes with intended flap thicknesses of either 120 or 90 mu m. [J Refract Surg. see more 2011;27(4):251-259.] doi:10.3928/1081597X-20100624-01″
“Background: Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such

as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity

of tumor progression.\n\nMethods: We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random Nepicastat ic50 permutated datasets.\n\nResults: We show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings.\n\nConclusions: Results suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies.”
“This paper examines three respects in which the study of epileptic absence seizures promises to inform our understanding of consciousness.