Effect of \u3ci\u3eLactobacillus acidophilus\u3c/i\u3e Strain N P51 on\u3ci\u3e Escherichia coli \u3c/i\u3e0157:H7 Fecal Shedding and Finishing Performance in Beef Feedlot Cattle

A 2-year study was conducted during the summer months (May to September) to test the effectiveness of feeding Lactobacillus acidophilus strain NP51 on the proportion of cattle shedding Escherichia coli 0157:H7 in the feces and evaluate the effect of the treatment on finishing performance. Steers (n = 448) were assigned randomly to pens, and pens of cattle were assigned randomly to NP5 1 supplementation or no supplementation (control). NP5 1 products were mixed with water and applied as the feed was mixed daily in treatment-designated trucks at the rate of l09 CFU per steer. Fecal samples were collected (n = 3,360) from the rectum from each animal every 3 weeks, and E. coli 0157:H7 was isolated by standard procedures, using selective enrichment, immunomagnetic separation, and PCR confirmation. The outcome variable was the recovery of E. coli 0157:H7 from feces, and was modeled using logistic regression accounting for year, repeated measures of pens of cattle, and block. No significant differences were detected for gain, intakes, or feed efficiency of control or NP51-fed steers. The probability for cattle to shed E. coli 0157:H7 varied significantly between 2002 and 2003 (P = 0.004). In 2002 and 2003, the probability for NP5 1-treated steers to shed E. coli 0157:H7 over the test periods was 13 and 21 %, respectively, compared with 21 and 28% among controls. Over the 2 years, NP51-treated steers were 35% less likely to shed E. coli 0157: H7 than were steers in untreated pens (odds ratio = 0.58, P = 0.008). This study is consistent with previous reports that feeding NP51 is effective in reducing E. coli 0157:H7 fecal shedding in feedlot cattle

Prevalence and Level of Enterohemorrhagic \u3ci\u3eEscherichia coli\u3c/i\u3e in Culled Dairy Cows at Harvest

The primary objective of this study was to determine the prevalence and level of enterohemorrhagic Escherichia coli (EHEC) O26, O45, O103, O111, O121, and O145 (collectively EHEC-6) plus EHEC O157 in fecal, hide, and preintervention carcass surface samples from culled dairy cows. Matched samples (n=300) were collected from 100 cows at harvest and tested by a culture-based method and two molecular methods: NeoSEEK STEC (NS) and Atlas STEC EG2 Combo. Both the culture and NS methods can be used to discriminate among the seven EHEC types (EHEC-7), from which the cumulative prevalence was inferred, whereas the Atlas method can discriminate only between EHEC O157 and non-O157 EHEC, without discrimination of the serogroup. The EHEC-7 prevalence in feces, hides, and carcass surfaces was 6.5, 15.6, and 1.0%, respectively, with the culture method and 25.9, 64.9, and 7.0%, respectively, with the NS method. With the Atlas method, the prevalence of non-O157 EHEC was 29.1, 38.3, and 28.0% and that of EHEC O157 was 29.1, 57.0, and 3.0% for feces, hides, and carcasses, respectively. Only two samples (a hide sample and a fecal sample) originating from different cows contained quantifiable EHEC. In both samples, the isolates were identified as EHEC O157, with 4.7 CFU/1,000 cm2 in the hide sample and 3.9 log CFU/g in the fecal sample. Moderate agreement was found between culture and NS results for detection of EHEC O26 (k=0.58,

Reduced cerebral blood flow and impaired visual-spatial function in proximal myotonic myopathy

Objective: To compare brain involvement in myotonic dystrophy (DM) with that of proximal myotonic myopathy (PROMM). Background: PROMM is a multisystem disease with many features in common with DM. Methods: Twenty patients with DM (CTG([500-700])), 20 patients with PROMM, and 20 normal control subjects were studied. Neuropsychological testing was performed in 12 patients with PROMM and in 18 patients with DM; brain MRI was performed in 17 of 20 PROMM patients and 15 of 20 DM patients. Ten patients with PROMM and 11 patients with DM were subjected to H215O PET. Results: Two-thirds of the patients with PROMM and one-half of those with DM were impaired on visual- spatial recall, whereas one-third of the patients with PROMM and less than half of those with DM showed an impairment in visual-spatial construction. Brain MRI was normal, or showed only nonspecific white matter abnormalities in both PROMM and DM patients. PET studies in PROMM patients showed a bilateral decrease in regional cerebral blood flow (rCBF) of the orbitofrontal and medial frontal cortex, whereas DM patients had more widespread hypoperfusion that extended to the dorsolateral frontal cortex and subcortical regions. Conclusions: Impaired visual-spatial function may be present in proximal myotonic myopathy. This correlates best with a reduction in regional cerebral blood flow observed in H215O PET brain scans rather than with specific structural abnormalities observed on brain MRI

Seasonal fluxes of carbon monoxide from an intensively grazed grassland in Scotland

Fluxes of carbon monoxide (CO) were measured using a fast-response quantum cascade laser absorption spectrometer and the eddy covariance method at a long-term intensively grazed grassland in southern Scotland. Measurements lasted 20 months from April 2016 to November 2017, during which normal agricultural activities continued. Observed fluxes followed a regular diurnal cycle, peaking at midday and returning to values near zero during the night, with occasional uptake observed. CO fluxes correlated well with the meteorological variables of solar radiation, soil temperature and soil moisture content. Using a general additive model (GAM) we were able to gap fill CO fluxes and estimate annual fluxes of 0.38 ± 0.046 and 0.35 ± 0.045 g C m−2 y−1g C m−2 y−1 for 2016 and 2017, respectively. If the CO fluxes reported in this study are representative of UK grasslands, then national annual emissions could be expected to be in the order of 61.91 (54.3–69.5) Gg, which equates to 3.8% (3.4–4.3%) of the current national inventory total

Mathematical Manipulative Models: In Defense of Beanbag Biology

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Novel HTS Strategy Identifies TRAIL-Sensitizing Compounds Acting Specifically Through the Caspase-8 Apoptotic Axis

Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand (TRAIL) is potentially a very important therapeutic as it shows selectivity for inducing apoptosis in cancer cells whilst normal cells are refractory. TRAIL binding to its cognate receptors, Death Receptors-4 and -5, leads to recruitment of caspase-8 and classical activation of downstream effector caspases, leading to apoptosis. As with many drugs however, TRAIL's usefulness is limited by resistance, either innate or acquired. We describe here the development of a novel 384-well high-throughput screening (HTS) strategy for identifying potential TRAIL-sensitizing agents that act solely in a caspase-8 dependent manner. By utilizing a TRAIL resistant cell line lacking caspase-8 (NB7) compared to the same cells reconstituted with the wild-type protein, or with a catalytically inactive point mutant of caspase-8, we are able to identify compounds that act specifically through the caspase-8 axis, rather than through general toxicity. In addition, false positive hits can easily be “weeded out” in this assay due to their activity in cells lacking caspase-8-inducible activity. Screening of the library of pharmacologically active compounds (LOPAC) was performed as both proof-of-concept and to discover potential unknown TRAIL sensitizers whose mechanism is caspase-8 mediated. We identified known TRAIL sensitizers from the library and identified new compounds that appear to sensitize specifically through caspase-8. In sum, we demonstrate proof-of-concept and discovery of novel compounds with a screening strategy optimized for the detection of caspase-8 pathway-specific TRAIL sensitizers. This screen was performed in the 384-well format, but could easily be further miniaturized, allows easy identification of artifactual false positives, and is highly scalable to accommodate diverse libraries

Sampling the Solution Space in Genome-Scale Metabolic Networks Reveals Transcriptional Regulation in Key Enzymes

Genome-scale metabolic models are available for an increasing number of organisms and can be used to define the region of feasible metabolic flux distributions. In this work we use as constraints a small set of experimental metabolic fluxes, which reduces the region of feasible metabolic states. Once the region of feasible flux distributions has been defined, a set of possible flux distributions is obtained by random sampling and the averages and standard deviations for each of the metabolic fluxes in the genome-scale model are calculated. These values allow estimation of the significance of change for each reaction rate between different conditions and comparison of it with the significance of change in gene transcription for the corresponding enzymes. The comparison of flux change and gene expression allows identification of enzymes showing a significant correlation between flux change and expression change (transcriptional regulation) as well as reactions whose flux change is likely to be driven only by changes in the metabolite concentrations (metabolic regulation). The changes due to growth on four different carbon sources and as a consequence of five gene deletions were analyzed for Saccharomyces cerevisiae. The enzymes with transcriptional regulation showed enrichment in certain transcription factors. This has not been previously reported. The information provided by the presented method could guide the discovery of new metabolic engineering strategies or the identification of drug targets for treatment of metabolic diseases