Associations among sugar sweetened beverage intake, visceral fat, and cortisol awakening response in minority youth.

CONTEXT: Abdominal adiposity has long been associated with excess caloric intake possibly resulting from increased psychosocial stress and associated cortisol dysfunction. However, the relationship of sugar-sweetened beverage (SSB) intake specifically with cortisol variability and visceral adipose tissue (VAT) is unknown. OBJECTIVE: To examine the relationships between SSB intake, VAT, and cortisol response in minority youth. DESIGN: A cross-sectional analysis. SETTING: The University of Southern California. PARTICIPANTS: 60 overweight/obese Non-Hispanic Black and Hispanic adolescents ages 14-18years. MAIN OUTCOME MEASURES: VAT via Magnet Resonance Imaging (MRI), cortisol awakening response (CAR) via multiple salivary samples, and SSB intake via multiple 24-hour diet recalls. SSB intake was divided into the following: low SSB consumers (<1 servings per day), medium SSB consumers (≥1-<2 servings per day), high SSB consumers (≥2 servings per day). Analysis of covariance were run with VAT and CAR as dependent variables and SSB intake categories (independent variable) with the following a priori covariates: sex, Tanner stage, ethnicity, caloric intake, and body mass index. RESULTS: The high SSB intake group exhibited a 7% higher VAT compared to the low SSB intake group (ß=0.25, CI:(0.03, 0.33), p=0.02). CAR was associated with VAT (ß=0.31, CI:(0.01,0.23), p=0.02). The high SSB intake group exhibited 22% higher CAR compared to the low SSB intake group (ß=0.30, CI:(0.02,0.48), p=0.04). CONCLUSION: This is the first study exploring the relationship between SSB, VAT, and CAR. SSB consumption appears to be independently associated greater abdominal adiposity and higher morning cortisol variability in overweight and obese minority youth. This study highlights potential targets for interventions specifically to reduce SSB intake in a minority youth population.

Covariance Partition Priors: A Bayesian Approach to Simultaneous Covariance Estimation for Longitudinal Data.

The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.

Inflammasome-dependent IL-1ß release depends upon membrane permeabilisation.

Interleukin-1ß (IL-1ß) is a critical regulator of the inflammatory response. IL-1ß is not secreted through the conventional ER-Golgi route of protein secretion, and to date its mechanism of release has been unknown. Crucially, its secretion depends upon the processing of a precursor form following the activation of the multimolecular inflammasome complex. Using a novel and reversible pharmacological inhibitor of the IL-1ß release process, in combination with biochemical, biophysical, and real-time single-cell confocal microscopy with macrophage cells expressing Venus-labelled IL-1ß, we have discovered that the secretion of IL-1ß after inflammasome activation requires membrane permeabilisation, and occurs in parallel with the death of the secreting cell. Thus, in macrophages the release of IL-1ß in response to inflammasome activation appears to be a secretory process independent of nonspecific leakage of proteins during cell death. The mechanism of membrane permeabilisation leading to IL-1ß release is distinct from the unconventional secretory mechanism employed by its structural homologues fibroblast growth factor 2 (FGF2) or IL-1α, a process that involves the formation of membrane pores but does not result in cell death. These discoveries reveal key processes at the initiation of an inflammatory response and deliver new insights into the mechanisms of protein release.

Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

Inference on data with missingness can be challenging, particularly if the knowledge that a measurement was unobserved provides information about its distribution. Our work is motivated by the Commit to Quit II study, a smoking cessation trial that measured smoking status and weight change as weekly outcomes. It is expected that dropout in this study was informative and that patients with missed measurements are more likely to be smoking, even after conditioning on their observed smoking and weight history. We jointly model the categorical smoking status and continuous weight change outcomes by assuming normal latent variables for cessation and by extending the usual pattern mixture model to the bivariate case. The model includes a novel approach to sharing information across patterns through a Bayesian shrinkage framework to improve estimation stability for sparsely observed patterns. To accommodate the presumed informativeness of the missing data in a parsimonious manner, we model the unidentified components of the model under a non-future dependence assumption and specify departures from missing at random through sensitivity parameters, whose distributions are elicited from a subject-matter expert.

Sparsity Inducing Prior Distributions for Correlation Matrices of Longitudinal Data.

For longitudinal data, the modeling of a correlation matrix R can be a difficult statistical task due to both the positive definite and the unit diagonal constraints. Because the number of parameters increases quadratically in the dimension, it is often useful to consider a sparse parameterization. We introduce a pair of prior distributions on the set of correlation matrices for longitudinal data through the partial autocorrelations (PACs), each of which vary independently over [-1,1]. The first prior shrinks each of the PACs toward zero with increasingly aggressive shrinkage in lag. The second prior (a selection prior) is a mixture of a zero point mass and a continuous component for each PAC, allowing for a sparse representation. The structure implied under our priors is readily interpretable for time-ordered responses because each zero PAC implies a conditional independence relationship in the distribution of the data. Selection priors on the PACs provide a computationally attractive alternative to selection on the elements of R or R-1 for ordered data. These priors allow for data-dependent shrinkage/selection under an intuitive parameterization in an unconstrained setting. The proposed priors are compared to standard methods through a simulation study and a multivariate probit data example. Supplemental materials for this article (appendix, data, and R code) are available online.

Computationally efficient banding of large covariance matrices for ordered data and connections to banding the inverse Cholesky factor.

In this article, we propose a computationally efficient approach to estimate (large) p-dimensional covariance matrices of ordered (or longitudinal) data based on an independent sample of size n. To do this, we construct the estimator based on a k-band partial autocorrelation matrix with the number of bands chosen using an exact multiple hypothesis testing procedure. This approach is considerably faster than many existing methods and only requires inversion of (k + 1)-dimensional covariance matrices. The resulting estimator is positive definite as long as k < n (where p can be larger than n). We make connections between this approach and banding the Cholesky factor of the modified Cholesky decomposition of the inverse covariance matrix (Wu and Pourahmadi, 2003) and show that the maximum likelihood estimator of the k-band partial autocorrelation matrix is the same as the k-band inverse Cholesky factor. We evaluate our estimator via extensive simulations and illustrate the approach using high-dimensional sonar data.

Fully Bayesian inference under ignorable missingness in the presence of auxiliary covariates.

In order to make a missing at random (MAR) or ignorability assumption realistic, auxiliary covariates are often required. However, the auxiliary covariates are not desired in the model for inference. Typical multiple imputation approaches do not assume that the imputation model marginalizes to the inference model. This has been termed "uncongenial" [Meng (1994, Statistical Science 9, 538-558)]. In order to make the two models congenial (or compatible), we would rather not assume a parametric model for the marginal distribution of the auxiliary covariates, but we typically do not have enough data to estimate the joint distribution well non-parametrically. In addition, when the imputation model uses a non-linear link function (e.g., the logistic link for a binary response), the marginalization over the auxiliary covariates to derive the inference model typically results in a difficult to interpret form for the effect of covariates. In this article, we propose a fully Bayesian approach to ensure that the models are compatible for incomplete longitudinal data by embedding an interpretable inference model within an imputation model and that also addresses the two complications described above. We evaluate the approach via simulations and implement it on a recent clinical trial.

Longitudinal measurements of MRI-T2 in boys with Duchenne muscular dystrophy: effects of age and disease progression.

Duchenne muscular dystrophy (DMD) is characterized by an increased muscle damage and progressive replacement of muscle by noncontractile tissue. Both of these pathological changes can lengthen the MRI transverse proton relaxation time (T2). The current study measured longitudinal changes in T2 and its distribution in the lower leg of 16 boys with DMD (5-13years, 15 ambulatory) and 15 healthy controls (5-13years). These muscles were chosen to allow extended longitudinal monitoring, due to their slow progression compared with proximal muscles in DMD. In the soleus muscle of boys with DMD, T2 and the percentage of pixels with an elevated T2 (⩾2SD above control mean T2) increased significantly over 1year and 2years, while the width of the T2 histogram increased over 2years. Changes in soleus T2 variables were significantly greater in 9-13years old compared with 5-8years old boys with DMD. Significant correlations between the change in all soleus T2 variables over 2years and the change in functional measures over 2years were found. MRI measurement of muscle T2 in boys with DMD is sensitive to disease progression and shows promise as a clinical outcome measure.

Bayesian modeling of the dependence in longitudinal data via partial autocorrelations and marginal variances.

Many parameters and positive-definiteness are two major obstacles in estimating and modelling a correlation matrix for longitudinal data. In addition, when longitudinal data is incomplete, incorrectly modelling the correlation matrix often results in bias in estimating mean regression parameters. In this paper, we introduce a flexible and parsimonious class of regression models for a covariance matrix parameterized using marginal variances and partial autocorrelations. The partial autocorrelations can freely vary in the interval (-1, 1) while maintaining positive definiteness of the correlation matrix so the regression parameters in these models will have no constraints. We propose a class of priors for the regression coefficients and examine the importance of correctly modeling the correlation structure on estimation of longitudinal (mean) trajectories and the performance of the DIC in choosing the correct correlation model via simulations. The regression approach is illustrated on data from a longitudinal clinical trial.

Effect of prenatal stress on subsequent response to mixing stress and a lipopolysaccharide challenge in pigs.

Sows subjected to prenatal stress have been found to produce offspring that have altered responses to stress. Our objective was to determine if exposing a sow to stress would alter the response of the offspring to lipopolysaccharide (LPS) at 2 mo of age or their response to mixing stress at 4 mo of age. Sow treatments consisted of intravenous injections of ACTH (1 IU/kg of BW), exposure to rough handling for a 10-min duration (rough), or no treatment (control) once per week from d 42 to 77 of gestation. At 2 mo of age, pigs from each treatment, 1 per litter (n = 21, 17, and 15 for the ACTH, rough, and control treatments, respectively), were challenged with 2 µg of LPS/kg of BW or saline, or served as a noninjected control. Their behavioral response to a human approach test and salivary cortisol were measured. At 4 mo of age, 1 pig from each treatment (n = 14, 14, and 15 for the ACTH, rough, and control treatments, respectively) was taken from its home pen and placed in a pen of unfamiliar pigs. At this time, a punch biopsy wound (6 × 6 mm) was created to measure the ability of the pig to heal the wound. At this same time, each pig received a 1-mL intramuscular injection of 20% ovine red blood cells (oRBC), and then a second injection of oRBC at 21 d postmixing. Blood samples were collected 3 times per week for 2 wk and then once a week for 4 more weeks. Blood samples were analyzed for cortisol, porcine corticosteroid-binding globulin, antibody response to oRBC, and nitric oxide production by macrophages. Behavior was recorded during the first 5 d after mixing. All pigs in the LPS challenge responded with characteristic sickness behavior; however, pigs in the rough treatment showed less sickness behavior than those in the other 2 treatments (P < 0.05). Maternal stress treatment did not affect (P < 0.43) salivary cortisol. Pigs from all treatments responded similarly to mixing stress with regard to cortisol, porcine corticosteroid-binding globulin, antibody titers, nitric oxide production, and hematology measures, and all pigs experienced the same amount of aggression in response to mixing. Without altering peripheral measures of stress responsivity, prenatal stress enhanced the ability of pigs to cope with a simulated immune challenge, which could prove to be an adaptation to challenging environments.

A mitotic function for the high-mobility group protein HMG20b regulated by its interaction with the BRC repeats of the BRCA2 tumor suppressor.

The inactivation of BRCA2, a suppressor of breast, ovarian and other epithelial cancers, triggers instability in chromosome structure and number, which are thought to arise from defects in DNA recombination and mitotic cell division, respectively. Human BRCA2 controls DNA recombination via eight BRC repeats, evolutionarily conserved motifs of ∼35 residues, that interact directly with the recombinase RAD51. How BRCA2 controls mitotic cell division is debated. Several studies by different groups report that BRCA2 deficiency affects cytokinesis. Moreover, its interaction with HMG20b, a protein of uncertain function containing a promiscuous DNA-binding domain and kinesin-like coiled coils, has been implicated in the G2-M transition. We show here that HMG20b depletion by RNA interference disturbs the completion of cell division, suggesting a novel function for HMG20b. In vitro, HMG20b binds directly to the BRC repeats of BRCA2, and exhibits the highest affinity for BRC5, a motif that binds poorly to RAD51. Conversely, the BRC4 repeat binds strongly to RAD51, but not to HMG20b. In vivo, BRC5 overexpression inhibits the BRCA2-HMG20b interaction, recapitulating defects in the completion of cell division provoked by HMG20b depletion. In contrast, BRC4 inhibits the BRCA2-RAD51 interaction and the assembly of RAD51 at sites of DNA damage, but not the completion of cell division. Our findings suggest that a novel function for HMG20b in cytokinesis is regulated by its interaction with the BRC repeats of BRCA2, and separate this unexpected function for the BRC repeats from their known activity in DNA recombination. We propose that divergent tumor-suppressive pathways regulating chromosome segregation as well as chromosome structure may be governed by the conserved BRC motifs in BRCA2.

A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data with Application to the Breast Cancer Prevention Trial.

We consider inference in randomized longitudinal studies with missing data that is generated by skipped clinic visits and loss to follow-up. In this setting, it is well known that full data estimands are not identified unless unverified assumptions are imposed. We assume a non-future dependence model for the drop-out mechanism and partial ignorability for the intermittent missingness. We posit an exponential tilt model that links non-identifiable distributions and distributions identified under partial ignorability. This exponential tilt model is indexed by non-identified parameters, which are assumed to have an informative prior distribution, elicited from subject-matter experts. Under this model, full data estimands are shown to be expressed as functionals of the distribution of the observed data. To avoid the curse of dimensionality, we model the distribution of the observed data using a Bayesian shrinkage model. In a simulation study, we compare our approach to a fully parametric and a fully saturated model for the distribution of the observed data. Our methodology is motivated by, and applied to, data from the Breast Cancer Prevention Trial.

Modeling Covariance Matrices via Partial Autocorrelations.

We study the role of partial autocorrelations in the reparameterization and parsimonious modeling of a covariance matrix. The work is motivated by and tries to mimic the phenomenal success of the partial autocorrelations function (PACF) in model formulation, removing the positive-definiteness constraint on the autocorrelation function of a stationary time series and in reparameterizing the stationarity-invertibility domain of ARMA models. It turns out that once an order is fixed among the variables of a general random vector, then the above properties continue to hold and follows from establishing a one-to-one correspondence between a correlation matrix and its associated matrix of partial autocorrelations. Connections between the latter and the parameters of the modified Cholesky decomposition of a covariance matrix are discussed. Graphical tools similar to partial correlograms for model formulation and various priors based on the partial autocorrelations are proposed. We develop frequentist/Bayesian procedures for modelling correlation matrices, illustrate them using a real dataset, and explore their properties via simulations.

Prolonged hyperphagia with high-fat feeding contributes to exacerbated weight gain in rats with adult-onset obesity.

Leptin-resistant rats, when given a high-fat (HF) diet, have a delayed normalization of caloric intake and greater weight gain than those on a chow diet. Because aged, obese rats are leptin resistant, these data predict that they will also have a delayed normalization of caloric intake and exacerbated weight gain when provided a HF diet. To investigate this hypothesis, along with the consequences of a HF diet on voluntary wheel running, we compared various ages of rats on a HF or chow diet. HF-fed young rats spontaneously divided into diet-induced obese and diet-resistant rats. However, all aged rats were susceptible to the weight-gaining effects of HF feeding. Rate of initial weight gain was proportional to age, and peak caloric intake on the HF diet and the days required to normalize caloric intake to basal levels increased with age. Responsiveness to peripheral leptin before HF feeding revealed a dose-response decrease in food intake and body weight in the young but no responses in the aged to even the highest dose, 0.5 mg/day. In addition, both age and HF feeding decreased the tendency for wheel running, suggesting the propensity for inactivity with age and HF feeding may contribute to age-related obesity and accelerate the rate of diet-induced obesity. These results demonstrate that aged rats are more susceptible to the detrimental effects of a HF diet.

Prenatal stress effects on pig development and response to weaning.

Exposing a pregnant sow to stress has been shown to affect the resulting offspring. Our objective was to determine if rough handling of pregnant sows altered the physiology of her offspring and if these alterations were different from an experimentally induced model of prenatal stress. Sow treatments consisted of i.v. injections of ACTH (1 IU/kg of BW), exposure to rough handling for 10 min (Rough), or no treatment (Control) once a week during d 42 to 77 of gestation. To determine the plasma cortisol response to treatments, blood (5 mL) was collected from 30 sows after treatment administration. To conduct the prenatal stress study, a separate group of 56 sows was used in 1 of 4 replicates. At birth, production data were collected for each litter, including birth weight, number born, anogenital distance, and pig viability. At weaning, pigs were blocked by BW and sex, and placed in a nursery pen of 6 pigs, with 2 pigs from each treatment group. To assess the effect of treatments on cortisol, corticosteroid-binding globulin (CBG), and hematological cell profiles, blood was collected every other day for 10 d after weaning. Application of treatments caused plasma cortisol concentrations to be greatest in ACTH sows compared with Control sows (P < 0.001), with Rough sows having intermediate values (P = 0.07). Treatments did not affect the number of pigs born, number of stillborn, or pig viability (P > 0.40). The ratio of cortisol to CBG did not differ between treatments (P = 0.09). Hematological variables did not differ between treatments (P > 0.19). Pigs born to ACTH sows had a smaller anogenital distance compared with controls (P < 0.03), with pigs from Rough sows being intermediate. Our data indicate that swine exposed to prenatal stress (ACTH injection) can have alterations in sexual morphology without effects on growth or the immune cell populations measured in this study.

Ultrasound simulation of real-time temperature estimation during radiofrequency ablation using finite element models.

Radiofrequency ablation is the most common minimally invasive therapy used in the United States to treat hepatocellular carcinoma and liver metastases. The ability to perform real-time temperature imaging while a patient is undergoing ablation therapy may help reduce the high recurrence rates following ablation therapy. Ultrasound echo signals undergo time shifts with increasing temperature due to sound speed and thermal expansion, which are tracked using both 1D cross correlation and 2D block matching based speckle tracking methods. In this paper, we present a quantitative evaluation of the accuracy and precision of temperature estimation using the above algorithms on both simulated and experimental data. A finite element analysis simulation of radiofrequency ablation of hepatic tissue was developed. Finite element analysis provides a method to obtain the exact temperature distribution along with a mapping of the tissue displacement due to thermal expansion. These local displacement maps were combined with the displacement due to speed of sound changes and utilized to generate ultrasound radiofrequency frames at specified time increments over the entire ablation procedure. These echo signals provide an ideal test-bed to evaluate the performance of both speckle tracking methods, since the estimated temperature results can be compared directly to the exact finite element solution. Our results indicate that the 1D cross-correlation (CC) method underestimates the cumulative displacement by 0.20mm, while the underestimation with 2D block matching (BM) is about 0.14 mm after 360 s of ablation. The 1D method also overestimates the size of the ablated region by 5.4% when compared to 2.4% with the 2D method after 720 s of ablation. Hence 2D block matching provides better tracking of temperature variations when compared to the 1D cross-correlation method over the entire duration of the ablation procedure. In addition, results obtained using 1D cross-correlation diverge from the ideal finite element results after 7 min of ablation and for temperatures greater than 65 degrees C. In a similar manner, experimental results presented using a tissue-mimicking phantom also demonstrate that the maximum percent difference with 2D block matching was 5%, when compared to 31% with the 1D method over the 700 s heating duration on the phantom.

Non-invasive ultrasound-based temperature imaging for monitoring radiofrequency heating-phantom results.

Minimally invasive therapies (such as radiofrequency ablation) are becoming more commonly used in the United States for the treatment of hepatocellular carcinomas and liver metastases. Unfortunately, these procedures suffer from high recurrence rates of hepatocellular carcinoma ( approximately 34-55%) or metastases following ablation therapy. The ability to perform real-time temperature imaging while a patient is undergoing radiofrequency ablation could provide a significant reduction in these recurrence rates. In this paper, we demonstrate the feasibility of ultrasound-based temperature imaging on a tissue-mimicking phantom undergoing radiofrequency heating. Ultrasound echo signals undergo time shifts with increasing temperature, which are tracked using 2D correlation-based speckle tracking methods. Time shifts or displacements in the echo signal are accumulated, and the gradient of these time shifts are related to changes in the temperature of the tissue-mimicking phantom material using a calibration curve generated from experimental data. A tissue-mimicking phantom was developed that can undergo repeated radiofrequency heating procedures. Both sound speed and thermal expansion changes of the tissue-mimicking material were measured experimentally and utilized to generate the calibration curve relating temperature to the displacement gradient. Temperature maps were obtained, and specific regions-of-interest on the temperature maps were compared to invasive temperatures obtained using fiber-optic temperature probes at the same location. Temperature elevation during a radiofrequency ablation procedure on the phantom was successfully tracked to within +/-0.5 degrees C.

Real-time calibration of temperature estimates during radiofrequency ablation.

Radiofrequency ablation is an interstitial focal ablative therapy that can be used in a percutaneous fashion and permits in situ destruction of hepatic tumors. Recurrence rates after rf therapy are as high as 34-55%, due to difficulties in accurately identifying the zone of necrosis (thermal lesion) because of the low intrinsic acoustic contrast between normal and ablated liver tissue. Our goal is to provide real-time ultrasonic tracking of temperature changes over the large range of temperatures traditionally used (40-100 degrees C) in rfablation procedures using an external ultrasound transducer. Temperature estimates are obtained using a cross-correlation algorithm applied to rf ultrasound echo signal data acquired at discrete intervals during heating. Apparent tissue displacement estimates obtained at these discrete time-intervals are accumulated to obtain a cumulative displacement map, whose gradient provides after appropriate scaling provides a temperature map at the specified elapsed ablation duration. Temperature maps are used to display the initial temperature rise and to continuously update a thermal map of the treated region. In this paper, we develop calibration curves that relate the echo shift due to the change in the speed of sound and thermal expansion to the corresponding temperature increase on in-vitro tissue specimens. These calibration curves can then be utilized for the real time calibration and analysis of temperature estimates obtained from the rf echo signals during ablation. Temperature maps obtained using the calibration curve compare favorably to temperature estimates observed using the invasive thermosensor readings on the ablation electrode and previous results that utilized a linear calibration factor.

The potential role of wild rabbits Oryctolagus cuniculus in the epidemiology of paratuberculosis in domestic ruminants.

Mycobacterium avium subspecies paratuberculosis, the organism responsible for paratuberculosis in cattle and sheep has been found in wild rabbits (Oryctolagus cuniculus) in the east of Scotland. Few studies have investigated either the level of faecal contamination by rabbits on farms, or the potential infectivity of rabbit excreta. The rate of rabbit faecal contamination deposited and the numbers encountered were estimated for 21 fields on 4 farms with a paratuberculosis problem. 7357 +/- 2571 S.E.M. rabbit faecal pellets were deposited per hectare per day and up to 81,000 pellets/ha ('standing crop') were encountered in October/November 1998. Where access to rabbits was restricted, the standing crop of faeces encountered fell to 22,000 pellets/ha. The prevalence of infection with M. a. paratuberculosis was assessed for 83 rabbits from the four farms. M. a. paratuberculosis was isolated from rabbits on all farms with an overall prevalence of 17%. Out of 17 rabbits from which urine was available, M. a. paratuberculosis was isolated from two--the first reported isolation from urine in wild rabbits. The mean number of colony-forming units per gram of infected rabbit faeces was 7.6 x 10(5) +/- 5.2 x 10(5). A relative estimate of the input of M. a. paratuberculosis onto pasture, at the stocking levels found on the four farms, showed that sheep and cattle potentially contributed 4 and 125 times more organisms/ha per day respectively than rabbits. However, rabbits could still contribute millions of M. a. paratuberculosis organisms per ha per day. Existing rabbit control measures on farms may be inadequate in reducing the risk of transmission to livestock.

The risk of disease transmission to livestock posed by contamination of farm stored feed by wildlife excreta.

Livestock feed is susceptible to contamination from wildlife excreta during on farm storage. Pathogens associated with diseases such as paratuberculosis, salmonella and cryptosporidiosis are present in wild rodent and bird excreta. Feed stores on four farms in the east of Scotland were monitored monthly over the winter of 1998/9 to quantify the levels of wildlife faecal contamination. A mean of 79.9 rodent (95% confidence interval: 37.5-165.9) and 24.9 (14.3-41.7) bird faeces were deposited per m2 of stored feed per month. It was estimated that individual cattle and sheep could encounter 1626 and 814 wildlife faeces over the winter. A model based on the numbers of infected faeces consumed per annum was used to estimate 'infectious probabilities' (Pinf) required to account for the reported prevalence of paratuberculosis, salmonella and cryptosporidiosis in sheep and cattle in the east of Scotland in 1998. Based on empirical data for input variables [the number of faeces encountered (Fe), the number ingested (Fi) and the prevalence of infection in wildlife species (Ip)], Pinf estimates ranged from 1.6 x 10(-8) for cryptosporidiosis in sheep to 8.2 x 10(-8) for paratuberculosis in cattle. The model suggested that ingestion of feed contaminated by wildlife faeces could account for the prevalence of all three diseases. Wildlife faecal contamination of stored feed should be given serious consideration as a potential source of infection to livestock.