In this study, the effectiveness of direct-fed microbials at reducing Escherichia coli O157 and Salmonella in beef cattle was evaluated. Steers (n=240) received one of the following four treatment concentrations: control = lactose carrier only; low = 1 X 10(7) CFU per steer daily Lactobacillus acidophilus NP51; medium = 5 x 10(8) CFU per steer daily L. acidophilus NP51; and high = 1 x 10(9) CFU per steer daily L. acidophilus NP51. Low, medium, and high diets also included 1 x 10(9) CFU per steer Propionibacterium freudenreichii NP24. Feces were collected from each animal at allocation of treatment and found to have no variation (P = 0.54) between cohorts concerning E. coli O157 recovery. Feces and hide swabs were collected at harvest and analyzed for the presence of E. coli O157 by immunomagnetic separation and Salmonella by PCR. No significant dosing effects were detected for E. coli O157 recovery from feces at the medium dose or from hides at the medium and high doses. E. coli O157 was 74% (P < 0.01) and 69% (P < 0.01) less likely to be recovered in feces from animals receiving the high and low diets, respectively, compared with controls. Compared with controls, E. coli O157 was 74% (P = 0.05) less likely to be isolated on hides of cattle receiving the low dose. No significant dosing effects were detected for Salmonella recovery from feces at the medium and low doses or from hides at any doses. Compared with controls, Salmonella was 48% (P = 0.09) less likely to be shed in feces of cattle receiving the high dose. No obvious dose-response of L. acidophilus NP51 on recovery of E. coli O157 or Salmonella was detected in our study.

Although preclinical studies suggested taxane sensitivity was associated with chromosomal stability and wild-type APC, we found that nab-paclitaxel was inactive in CIMP-high metastatic CRC. Nab-paclitaxel may represent a novel therapeutic option for SBA.

Next year will mark 60 years since Dr. Leslie Foulds outlined his hypothesis that cancer is “a dynamic process advancing through stages that are qualitatively different,”1 leading the way to our view of cancer progression as we know it today2. Our understanding of the mechanisms of these stages have been continuously evolving this past half-century and there has always been an active discussion of the roles of both genetic or epigenetic changes in directing this progression. In this review, we will focus on the roles one particular epigenetic mark - DNA methylation - plays in these various “discontinuous” stages of cancer. Understanding these steps not only gives us a better picture of how this fascinating biological process operates, but opens the doors to new prognostic biomarkers and therapies against these malignancies.

Several studies have demonstrated that unmapped reads in next generation sequencing data could be used to identify infectious agents or structural variants, but there has been no intensive effort to analyze and classify all non-human sequences found in individual large data sets. To identify commonality in non-human sequences by infectious agents and putative contamination events, we analyzed non-human sequences in 150 genomic sequencing data files from the 1000 Genomes Project and observed that 0.13% of reads on average showed similarities to non-human genomes. We compared results among different sample groups divided based on ethnicities, sequencing centers and enrichment methods (whole genome sequencing vs. exome sequencing) and found that sequencing centers had specific signatures of contaminating genomes as ‘time stamps’. We also observed many unmapped reads that falsely indicated contamination because of the high similarity of human sequences to sequences in non-human genome assemblies such as mouse and Nicotiana.

Genomic instability at microsatellite loci is a hallmark of many cancers, including breast cancer. However, much of the genomic variation and many of the hereditary components responsible for breast cancer remain undetected. We hypothesized that variation at microsatellites could provide additional genomic markers for breast cancer risk assessment. A total of 1,345 germline and tumor DNA samples from individuals diagnosed with breast cancer, exome sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation. The comparison group for our analysis, representing healthy individuals, consisted of 249 females which were exome sequenced as part of the 1,000 Genomes Project. We applied our microsatellite-based genotyping pipeline to identify 55 microsatellite loci that can distinguish between the germline of individuals diagnosed with breast cancer and healthy individuals with a sensitivity of 88.4 % and a specificity of 77.1 %. Further, we identified additional microsatellite loci that are potentially useful for distinguishing between breast cancer subtypes, revealing a possible fifth subtype. These findings are of clinical interest as possible risk diagnostics and reveal genes that may be of potential therapeutic value, including genes previously not associated with breast cancer.Electronic supplementary materialThe online version of this article (doi:10.1007/s10549-014-2908-8) contains supplementary material, which is available to authorized users.