Room temperature housing results in premature cancellous bone loss in growing female mice: implications for the mouse as a preclinical model for age-related bone loss.

UNLABELLED: Room temperature housing (22 °C) results in premature cancellous bone loss in female mice. The bone loss was prevented by housing mice at thermoneutral temperature (32 °C). Thermogenesis differs markedly between mice and humans and mild cold stress induced by standard room temperature housing may introduce an unrecognized confounding variable into preclinical studies. INTRODUCTION: Female mice are often used as preclinical models for osteoporosis but, in contrast to humans, mice exhibit cancellous bone loss during growth. Mice are routinely housed at room temperature (18-23 °C), a strategy that exaggerates physiological differences in thermoregulation between mice (obligatory daily heterotherms) and humans (homeotherms). The purpose of this investigation was to assess whether housing female mice at thermoneutral (temperature range where the basal rate of energy production is at equilibrium with heat loss) alters bone growth, turnover and microarchitecture. METHODS: Growing (4-week-old) female C57BL/6J and C3H/HeJ mice were housed at either 22 or 32 °C for up to 18 weeks. RESULTS: C57BL/6J mice housed at 22 °C experienced a 62 % cancellous bone loss from the distal femur metaphysis during the interval from 8 to 18 weeks of age and lesser bone loss from the distal femur epiphysis, whereas cancellous and cortical bone mass in 32 °C-housed mice were unchanged or increased. The impact of thermoneutral housing on cancellous bone was not limited to C57BL/6J mice as C3H/HeJ mice exhibited a similar skeletal response. The beneficial effects of thermoneutral housing on cancellous bone were associated with decreased Ucp1 gene expression in brown adipose tissue, increased bone marrow adiposity, higher rates of bone formation, higher expression levels of osteogenic genes and locally decreased bone resorption. CONCLUSIONS: Housing female mice at 22 °C resulted in premature cancellous bone loss. Failure to account for species differences in thermoregulation may seriously confound interpretation of studies utilizing mice as preclinical models for osteoporosis.

Initial occurrence of Taylorella asinigenitalis and its detection in nurse mares, a stallion and donkeys in Kentucky.

In 1998, a newly identified bacterium Taylorella asinigenitalis was isolated from the external genitalia and reproductive tracts of nurse mares, a stallion and donkey jacks in Kentucky. An extensive regulatory effort was implemented to contain the outbreak including the tracing and testing of 232 horses and donkeys on 58 premises. T. asinigenitalis was isolated from the reproductive tract of 10 adult equids, including two donkey jacks, one Paint Quarter-horse stallion and seven draft-type breeding mares. None of the infected horses had clinical signs of reproductive tract disease. The odds of being culture positive were 20 times greater for a mare bred to a donkey than for a mare bred to a stallion. Approximately 18% of mares bred to either a carrier stallion or donkey jack were confirmed culture positive. Seventy-one percent of infected mares required more than one course of treatment to clear the organism from their reproductive tracts and one mare harbored the organism for more than 300 days.

Femoral bone mineral density reflects histologically determined cortical bone volume in hemodialysis patients.

UNLABELLED: We evaluated the associations between dual energy X-ray absorptiometry (DXA) and histologically determined cancellous and cortical bone volume by controlling for vascular calcifications and demographic variables in hemodialysis (HD) patients. Femoral bone mineral density (f-BMD) was associated with cortical porosity. INTRODUCTION: Assessment of bone mass in chronic kidney disease patients is of clinical importance because of the association between low bone volume, fractures, and vascular calcifications. DXA is used for noninvasive assessment of bone mass whereby vertebral results reflect mainly cancellous bone and femoral results reflect mainly cortical bone. Bone histology allows direct measurements of cancellous and cortical bone volume. The present study evaluates the association between DXA and histologically determined cancellous and cortical bone volumes in HD patients. METHODS: In 38 HD patients, DXA was performed for assessment of bone mass, anterior iliac crest bone biopsies for bone volume, and multislice computed tomography for vascular calcifications. RESULTS: While lumbar bone mineral density (l-BMD) by DXA was not associated with histologically measured cancellous bone volume, coronary Agatson score showed a borderline statistically significant association (P = 0.055). When controlled for age and dialysis duration, f-BMD by DXA was associated with cortical porosity determined by histology (P = 0.005). CONCLUSIONS: The usefulness of l-BMD for predicting bone volume is limited most probably because of interference by soft tissue calcifications. In contrast, f-BMD shows significant association with cortical porosity.

The five most commonly used intact parathyroid hormone assays are useful for screening but not for diagnosing bone turnover abnormalities in CKD-5 patients.

BACKGROUND/AIMS: Assessment of bone turnover for management of renal osteodystrophy is part of routine care in chronic kidney disease Stage 5 (CKD-5) patients. Measurement of intact parathyroid hormone (iPTH) is the most commonly used surrogate marker for bone turnover in these patients. The current study was conducted to evaluate the predictive value of the five most commonly used iPTH assays for bone turnover. METHODS: In a cross-sectional study, 84 CKD-5 patients underwent bone biopsy and blood drawings for determination of iPTH and total serum alkaline phosphatase (AP). RESULTS: Histologically, patients presented with a broad range of bone turnover abnormalities as determined by activation frequency and bone formation rate/bone surface. Results of the five iPTH assays in each patient correlated but were significantly different. There were also significant differences between iPTH measurements at the same bone turnover level. Using Kidney Disease Outcome Quality Initiative recommended iPTH ranges, all assays showed comparably poor diagnostic performance. At 80% specificity, cut-off values of the 5 iPTH assays for low bone turnover varied from 165 to 550 pg/ml and for high bone turnover from 404 to 1,003 pg/ml. Sensitivities at these cutoffs remained below acceptable standards. Addition of AP measurements to iPTH did not improve diagnostic accuracy. CONCLUSIONS: Precise assessment of bone turnover will require utilization of established and novel bone markers reflecting effects of bone turnover rather than measuring only iPTH or other effectors.

Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey.

A flexible hierarchical Bayesian spatiotemporal regression model for foot-and-mouth disease (FMD) was applied to data on the annual number of reported FMD cases in Turkey from 1996 to 2003. The longitudinal component of the model was specified as a latent province-specific stochastic process. This stochastic process can accommodate various types of FMD temporal profiles. The model accounted for differences in FMD occurrence across provinces and for spatial correlation. Province-level covariate information was incorporated into the analysis. Results pointed to a decreasing trend in the number of FMD cases in western Turkey and an increasing trend in eastern Turkey from 1996 to 2003. The model also identified provinces with high and with low propensities for FMD occurrence. The model's use of flexible structures for temporal trend and of generally applicable methods for spatial correlation has broad application to predicting future spatiotemporal distributions of disease in other regions of the world.

Relationships between milk culture results and treatment for clinical mastitis or culling in Norwegian dairy cattle.

In quarter milk samples from 2,492 randomly sampled cows that were selected without regard to their current or previous udder health status, the relationships between the following outcome variables were studied: treatment of clinical mastitis; the joint event of either treatment or culling for mastitis; culling for all reasons; culling specifically for mastitis; and the covariates of positive milk culture for Staphylococcus aureus, Streptococcus spp., and coagulase-negative Staphylococcus spp., or other pathogens, or of negative culture for mastitis pathogens. Microbiological diagnoses were assigned at the cow level, and altogether 3,075 diagnoses were related to the outcome variables. The relation between the absence of pathogens and rich (>1,500 cfu/mL of milk) or sparse (

Effect of diagnostic testing error on intracluster correlation coefficient estimation.

Estimation of the intracluster correlation coefficient (ICC) for infectious animal diseases may be of interest for survey planning and for calculating variance inflation factors for estimators of prevalence. Typically, diagnostic tests with imperfect sensitivity and specificity are used in surveys. In such studies, where animals from multiple herds are tested, the ICC often is estimated using apparent (test-based) rather than true prevalence data. Through Monte Carlo simulation, we examined the effect of substituting diagnostic test outcomes for true infection status on an ANOVA estimator of ICC, which was designed for use with true infection status data. We considered effects of diagnostic test sensitivity and specificity on the estimated ICC when the true ICC value and infection status of the sampled individuals were known. The ANOVA estimator underestimated the true ICC when the diagnostic test was imperfect. We also demonstrated, under the beta-binomial model, that the ICC based on apparent infection status for individuals is < or = ICC based on true infection status. In addition, we propose a Bayesian model for estimating the ICC that incorporates imperfect sensitivity and specificity and illustrate the Bayesian model using a simulation study and one example; a seroprevalence survey of ovine progressive pneumonia in U.S. sheep flocks.

Estimation of diagnostic-test sensitivity and specificity through Bayesian modeling.

We review recent Bayesian approaches to estimation (based on cross-sectional sampling designs) of the sensitivity and specificity of one or more diagnostic tests. Our primary goal is to provide veterinary researchers with a concise presentation of the computational aspects involved in using the Bayesian framework for test evaluation. We consider estimation of diagnostic-test sensitivity and specificity in the following settings: (i) one test in one population, (ii) two conditionally independent tests in two or more populations, (iii) two correlated tests in two or more populations, and (iv) three tests in two or more populations, where two tests are correlated but jointly independent of the third test. For each scenario, we describe a Bayesian model that incorporates parameters of interest. The WinBUGS code used to fit each model, which is available at http://www.epi.ucdavis.edu/diagnos-tictests/, can be altered readily to conform to different data.

Predicting the probability of abortion in dairy cows: a hierarchical Bayesian logistic-survival model using sequential pregnancy data.

Although abortion contributes substantially to poor reproductive health of dairy herds, little is known about the predictability of abortion based on age, previous abortion or gravidity (number of previous pregnancies). A poor understanding of effects of maternal factors on abortion risk exists, in part, because of methodological difficulties related to non-independence of multiple pregnancies of the same cow in analysis of fetal survival data. We prospectively examined sequential pregnancies to investigate relationships between fetal survival and putative dam risk factors for 2991 abortions from 24,706 pregnancies of 13,145 cows in nine California dairy herds. Relative risks and predicted probabilities of abortion (PPA) were estimated using a previously described hierarchical Bayesian logistic-survival model generalized to incorporate longitudinal data of multiple pregnancies from a single cow. The PPA increased with increasing dam age at conception, with increasing number of previous abortions, and if the previous pregnancy was aborted >60 days in gestation. The PPA decreased with increasing gravidity and with increasing number of days open. For cows that aborted, the median time to fetal death decreased slightly as gravidity increased. The study considers several methodological issues faced in epidemiologic investigations of fetal health, including multi-modal hazard functions, extensive censoring and non-independence of multiple pregnancies. The model improves our ability to predict bovine abortion and to characterize fetal survival, which have important applications to herd health management.

Bayesian modeling of animal- and herd-level prevalences.

We reviewed Bayesian approaches for animal-level and herd-level prevalence estimation based on cross-sectional sampling designs and demonstrated fitting of these models using the WinBUGS software. We considered estimation of infection prevalence based on use of a single diagnostic test applied to a single herd with binomial and hypergeometric sampling. We then considered multiple herds under binomial sampling with the primary goal of estimating the prevalence distribution and the proportion of infected herds. A new model is presented that can be used to estimate the herd-level prevalence in a region, including the posterior probability that all herds are non-infected. Using this model, inferences for the distribution of prevalences, mean prevalence in the region, and predicted prevalence of herds in the region (including the predicted probability of zero prevalence) are also available. In the models presented, both animal- and herd-level prevalences are modeled as mixture distributions to allow for zero infection prevalences. (If mixture models for the prevalences were not used, prevalence estimates might be artificially inflated, especially in herds and regions with low or zero prevalence.) Finally, we considered estimation of animal-level prevalence based on pooled samples.