393 research outputs found
USING NONLINEAR FIXED AND MIXED MODELS WITH SWITCHING FUNCTIONS TO ALLOW FOR HORMESIS IN GROWTH OF ESCHERICHIA COLI
Individual Escherichia coli (E. coli) strains can be characterized by measuring growth rate. Strains better adapted to the environment are expected to grow faster. Classic bacterial growth curves display an increase in optical density over time. In this paper, we use the logistic function to model growth in optical density of E. coli over time. We examine 16 curves for 8 E. coli strains originally isolated from cattle and found many curves have a paradoxical dip at the beginning that is indicative of hormesis (an initial contrarian response showing, stimulation or suppression of growth). We examine several switching functions that allow for the effect of hormesis and compare the ability of nonlinear fixed and mixed models to detect the presence of hormesis
Narrow grass hedge effects on microbial transport following variable applications of beef cattle manure
The effectiveness of a 1.4 m wide grass hedge in reducing microbial transport following manure application was examined in this study. Beef cattle manure was applied to 0.75 m wide by 4.0 m long plots established on an Aksarben silty clay loam located in southeast Nebraska. Manure was added at rates required to meet none or the 1-, 2-, or 4-year nitrogen requirements for corn. The transport of phages, total coliforms, E. coli, and enterococci was measured for three 30 min simulated rainfall events, which were separated by approximately 24 h intervals. The narrow grass hedge reduced total counts of phages, E. coli, and enterococci from 10.8 to 9.01 log PFU ha-1, from 12.4 to 11.9 log CFU ha-1, and from 11.8 to 11.2 log CFU ha-1, respectively. For the plots that received manure, no significant differences in transport of phages or enterococci were found among the three manure application rates. Rainfall simulation run significantly affected measurements of phages, total coliforms, and enterococci, with measurements during the three runs varying from 8.91 to 10.5 log PFU ha-1, from 12.7 to 13.3 log CFU ha-1, and from 11.2 to 11.7 log CFU ha-1, respectively. Counts for phages, total coliforms, and enterococci were significantly less for the first than the second and third rainfall simulation runs. All four of the microbial constituents were significantly correlated to dissolved P, particulate P, total P, and total N. A narrow grass hedge placed on the contour significantly reduced microbial transport following variable applications of beef cattle manure
Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI
Precision medicine for chronic diseases such as multiple sclerosis (MS)
involves choosing a treatment which best balances efficacy and side
effects/preferences for individual patients. Making this choice as early as
possible is important, as delays in finding an effective therapy can lead to
irreversible disability accrual. To this end, we present the first deep neural
network model for individualized treatment decisions from baseline magnetic
resonance imaging (MRI) (with clinical information if available) for MS
patients. Our model (a) predicts future new and enlarging T2 weighted (NE-T2)
lesion counts on follow-up MRI on multiple treatments and (b) estimates the
conditional average treatment effect (CATE), as defined by the predicted future
suppression of NE-T2 lesions, between different treatment options relative to
placebo. Our model is validated on a proprietary federated dataset of 1817
multi-sequence MRIs acquired from MS patients during four multi-centre
randomized clinical trials. Our framework achieves high average precision in
the binarized regression of future NE-T2 lesions on five different treatments,
identifies heterogeneous treatment effects, and provides a personalized
treatment recommendation that accounts for treatment-associated risk (e.g. side
effects, patient preference, administration difficulties).Comment: Accepted to MIDL 202
Association of \u3ci\u3eEscherichia coli\u3c/i\u3e O157:H7 \u3ci\u3etir\u3c/i\u3e polymorphisms with human infection
Background: Emerging molecular, animal model and epidemiologic evidence suggests that Shigatoxigenic Escherichia coli O157:H7 (STEC O157) isolates vary in their capacity to cause human infection and disease. The translocated intimin receptor (tir) and intimin (eae) are virulence factors and bacterial receptor-ligand proteins responsible for tight STEC O157 adherence to intestinal epithelial cells. They represent logical genomic targets to investigate the role of sequence variation in STEC O157 pathogenesis and molecular epidemiology. The purposes of this study were (1) to identify tir and eae polymorphisms in diverse STEC O157 isolates derived from clinically ill humans and healthy cattle (the dominant zoonotic reservoir) and (2) to test any observed tir and eae polymorphisms for association with human (vs bovine) isolate source.
Results: Five polymorphisms were identified in a 1,627-bp segment of tir. Alleles of two tir polymorphisms, tir 255 T\u3eA and repeat region 1-repeat unit 3 (RR1-RU3, presence or absence) had dissimilar distributions among human and bovine isolates. More than 99% of 108 human isolates possessed the tir 255 T\u3eA T allele and lacked RR1-RU3. In contrast, the tir 255 T\u3eA T allele and RR1-RU3 absence were found in 55% and 57%, respectively, of 77 bovine isolates. Both polymorphisms associated strongly with isolate source (p \u3c 0.0001), but not by pulsed field gel electrophoresis type or by stx1 and stx2 status (as determined by PCR). Two eae polymorphisms were identified in a 2,755-bp segment of 44 human and bovine isolates; 42 isolates had identical eae sequences. The eae polymorphisms did not associate with isolate source.
Conclusion: Polymorphisms in tir but not eae predict the propensity of STEC O157 isolates to cause human clinical disease. The over-representation of the tir 255 T\u3eA T allele in human-derived isolates vs the tir 255 T\u3eA A allele suggests that these isolates have a higher propensity to cause disease. The high frequency of bovine isolates with the A allele suggests a possible bovine ecological niche for this STEC O157 subset
Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models
Image-based precision medicine aims to personalize treatment decisions based
on an individual's unique imaging features so as to improve their clinical
outcome. Machine learning frameworks that integrate uncertainty estimation as
part of their treatment recommendations would be safer and more reliable.
However, little work has been done in adapting uncertainty estimation
techniques and validation metrics for precision medicine. In this paper, we use
Bayesian deep learning for estimating the posterior distribution over factual
and counterfactual outcomes on several treatments. This allows for estimating
the uncertainty for each treatment option and for the individual treatment
effects (ITE) between any two treatments. We train and evaluate this model to
predict future new and enlarging T2 lesion counts on a large, multi-center
dataset of MR brain images of patients with multiple sclerosis, exposed to
several treatments during randomized controlled trials. We evaluate the
correlation of the uncertainty estimate with the factual error, and, given the
lack of ground truth counterfactual outcomes, demonstrate how uncertainty for
the ITE prediction relates to bounds on the ITE error. Lastly, we demonstrate
how knowledge of uncertainty could modify clinical decision-making to improve
individual patient and clinical trial outcomes
Microbial transport as affected by residue cover and manure application rate
Manure is applied to cropland areas with varying surface cover to meet single- or multiple-year crop nutrient requirements. The objectives of this field study were to (1) examine microbial transport following land application of manure to sites with and without wheat residue, (2) compare microbial loads following land application to meet the 0, 1, 2, 4, and 8-year P-based requirements for corn, and (3) evaluate the effects of rainfall simulation run on microbial transport. Manure was added and incorporated by disking plots that were 0.75 m wide by 2.0 m long. Three 30 min simulated rainfall events, separated by 24 h intervals, were then applied at an intensity of 70 mm h-1. Plots containing wheat residue had a total coliform load of 12.6 log CFU ha-1, which was significantly greater than the 12.4 log CFU ha-1 measured on the plots without wheat residue. The plots with and without wheat residue had transport rates of E. coli and enterococci that were not significantly different. The plots on which manure was added at rates varying from 5.4 to 42.8 Mg ha-1 had counts of total coliforms and enterococci that were not significantly different. Rainfall simulation run did not significantly affect measurements of phages, total coliforms, or enterococci. Transport of selected microbes was found to be significantly affected by residue cover, manure application rate, and rainfall simulation run
N N bar,Delta bar N, Delta N bar excitation for the pion propagator in nuclear matter
The particle-hole and Delta -hole excitations are well-known elementary
excitation modes for the pion propagator in nuclear matter. But, the excitation
also involves antiparticles, namely, nucleon-antinucleon, anti-Delta-nucleon
and Delta-antinucleon excitations. These are important for high-energy momentum
as well, and have not been studied before, to our knowledge. In this paper, we
give both the formulas and the numerical calculations for the real and the
imaginary parts of these excitations.Comment: Latex, 3 eps file
Combined Analysis of Near-Threshold Production of omega and phi Mesons in Nucleon-Nucleon Collisions within an Effective Meson-Nucleon Model
Vector meson () production in near-threshold elementary
nucleon-nucleon collisions , and is studied
within an effective meson-nucleon theory. It is shown that a set of effective
parameters can be established to describe fairly well the available
experimental data of angular distributions and the energy dependence of the
total cross sections without explicit implementation of the Okubo-Zweig-Iisuka
rule violation. Isospin effects are considered in detail and compared with
experimental data whenever available
Di-electrons from meson Dalitz decay in proton-proton collisions
The reaction is discussed within a
covariant effective meson-nucleon theory. The model is adjusted to data of the
subreaction . Our focus is on di-electrons from Dalitz decays
of mesons, , and the role of
the corresponding transition form factor . Numerical
results are presented for the intermediate energy kinematics of HADES
experiments
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