The reduction in fatigue crack growth resistance of dentin with depth.

The fatigue crack growth resistance of dentin was characterized as a function of depth from the dentino-enamel junction. Compact tension (CT) specimens were prepared from the crowns of third molars in the deep, middle, and peripheral dentin. The microstructure was quantified in terms of the average tubule dimensions and density. Fatigue cracks were grown in-plane with the tubules and characterized in terms of the initiation and growth responses. Deep dentin exhibited the lowest resistance to the initiation of fatigue crack growth, as indicated by the stress intensity threshold (ΔK(th) ≈ 0.8 MPa•m(0.5)) and the highest incremental fatigue crack growth rate (over 1000 times that in peripheral dentin). Cracks in deep dentin underwent incremental extension under cyclic stresses that were 40% lower than those required in peripheral dentin. The average fatigue crack growth rates increased significantly with tubule density, indicating the importance of microstructure on the potential for tooth fracture. Molars with deep restorations are more likely to suffer from the cracked-tooth syndrome, because of the lower fatigue crack growth resistance of deep dentin.

Enhancing the prediction accuracy of bovine lameness models through transformations of limb movement variables.

The issue of modeling bovine lameness was explored by testing the hypothesis that B-spline transformation of limb movement variables (LMV) employed in predictive models improved model accuracy. The objectives were to determine the effect of number of B-spline knots and the degree of the underlying polynomial approximation (degree of freedom) on model accuracy. Knot number used in B-spline transformation improved model accuracy by improving model specificity and to a lesser extent model sensitivity. Degree of polynomial approximation had no effect on model predictive accuracy from the data set of 261 cows. Model stability, defined as changes in predictive accuracy associated with the superimposition of perturbations (0.5 and 1.0%) in LMV on the measured data, was explored. Model specificity and to a lesser degree, sensitivity, increased with increased knot number across data set perturbations. Specificity and sensitivity increased by 43 and 11%, respectively, when knot number increased from 0 to 7 for a perturbation level of 0.5%. When the perturbation level was 1%, the corresponding increases in specificity and sensitivity were 32 and 4%, respectively. Nevertheless, different levels of LMV perturbation varied the optimal knot number associated with highest model accuracy. The optimal knot number for 0.5% perturbation was 8, whereas for 1% perturbation the optimal knot number was 7. The B-spline transformation improved specificity and sensitivity of predictive models for lameness, provided the appropriate number of knots was selected.

Spatial distribution of metals in soils in Baltimore, Maryland: role of native parent material, proximity to major roads, housing age and screening guidelines.

We investigated the spatial distribution of heavy metal above-background (anthropic) contents of Cd, Co, Cu, Cr, Fe, Mn, Ni, Pb, Ti, V, and Zn in Baltimore City surface soils and related these levels to potential contaminating sources. Composite soil samples (0-10 cm depth) were digested using a nitric and hydrochloric extraction technique. Slightly more than 10% of plots exceeded United States Environmental Protection Agency screening guidelines for Pb. In a principal component analysis, the first component corresponded to Co, Cr, and Fe, which are constituents of local mafic rocks. The second component corresponded to Cu, Pb, and Zn which were significantly higher within than beyond a 100 m buffer of the major roads within the city; furthermore, Pb and Zn were higher in older residential lots.

Objective determination of claw pain and its relationship to limb locomotion score in dairy cattle.

We hypothesized that claw and foot pain could be objectively determined and have a strong effect on limb locomotion. Claw pain was measured using hoof testers equipped with a pressure gauge. Soft tissue pain was evaluated with an algometer. Pain was determined as the maximum pressure recorded at the time the limb was withdrawn following claw or soft tissue compression with the hoof tester or algometer. Locomotion scores and claw and soft tissue pain were determined on 263 Holstein cows from 2 commercial dairy farms. The frequency and the magnitude of pain had an effect on locomotion score in the ipsilateral limb for lateral, but not medial, claws. The magnitude of the lateral claw pain index for limbs with locomotion scores 1 to 5 was 0.95 +/- 0.01, 0.90 +/- 0.02, 0.67 +/- 0.04, 0.65 +/- 0.05, and 0.45 +/- 0.11, respectively. The magnitude of the medial claw pain index for limbs with locomotion scores 1 to 5 was 1.0 +/- 0.00, 0.99 +/- 0.01, 0.98 +/- 0.01, 1.0 +/- 0.00, and 1.0 +/- 0.00, respectively. The frequency of painful claws (n = 208) in limbs with locomotion scores 1, 2, and > or =3 was 0.529, 0.173, and 0.298, respectively. The frequency of painless claws (n = 318) in limbs with locomotion scores 1, 2, or > or =3 was 0.792, 0.088, and 0.120, respectively. The frequency of pain (27.1%) and total lesions (85.6%) was greater in lateral claws (n = 524) than that of pain (2.1%) and total lesions (14.4%) in medial claws (n = 524). Yet the magnitude of the pain index in sore claws was similar for medial (0.73 +/- 0.09) and lateral claws (0.64 +/- 0.02). The magnitude and frequency of claw pain in one hind limb was inconsistently and weakly affected by locomotion score or claw pain in the contralateral limb. The prevalence of unilateral (32.8%) and bilateral (23.3%) pain was similar and lower than the occurrence of bilaterally nonpainful claws (43.9%) in the study group. Painful claws (n = 78) occurred on sound limbs (n = 332) with a pain index (0.72 +/- 0.02) indicative of less pain than the pain index (0.61 +/- 0.02) of painful claws (n = 130) on lame limbs (n = 192). The results showed that lateral claw pain was related to ipsilateral limb locomotion score and subclinical pain was a relatively common occurrence. Objective measures of pain may provide a more reliable, continuous measure of clinical events used in modeling lameness.

Comparison of models to identify lame cows based on gait and lesion scores, and limb movement variables.

Bovine lameness results in pain and suffering in cattle and economic loss for producers. A system for automatically detecting lame cows was developed recently that measures vertical force components attributable to individual limbs. These measurements can be used to calculate a number of limb movement variables. The objective of this investigation was to explore whether gait scores, lesion scores, or combined gait and lesion scores were more effectively captured by a set of 5 limb movement variables. A set of 700 hind limb examinations was used to create gait-based, lesion-based, and combined (gait- and lesion-based) models. Logistic regression models were constructed using 1, 2, or 3 d of measurements. Resulting models were tested on cows not used in modeling. The accuracy of lesion-score models was superior to that of gait-score models; lesion-based models generated greater values of areas under the receiving operating characteristic curves (range 0.75 to 0.84) and lower mean-squared errors (0.13 to 0.16) compared with corresponding values for the gait-based models (0.63 to 0.73 and 0.26 to 0.31 for receiving operating characteristic and mean-squared errors, respectively). These results indicate that further model development and investigation could generate automated and objective methods of lameness detection in dairy cattle.

Clustered binary logistic regression in teratology data using a finite mixture distribution.

The beta-binomial distribution introduced by Skellam has been applied in many teratology problems for modelling the litter effect. Recently, Morel and Nagaraj proposed a new distribution for modelling cluster multinomial data when the clustering is believed to be caused by clumped sampling. It turns out that the distribution is a mixture of two binomial distributions and accommodates the estimation of an additional parameter to account for intra-litter effect. The new distribution arises from a cluster mechanism in which some individuals within a cluster exhibit the same behaviour while the remaining individuals from the cluster react independently of each other. Such a mechanism is a natural model in teratology problems, where typically a genetic trait is passed with a certain probability to the foetuses of the same litter. In this article, we use the new distribution to model binary responses with logistic regression. We analyse data from a teratology experiment to demonstrate that the new model provides a useful addition to current methodology. The experiment investigates the synergistic effect of the anticonvulsant phenytoin and trichloropopene oxide on the prenatal development of inbred mice. In a simulation study we investigate the type I error rate and the power of the maximum likelihood ratio test when the data follow a finite mixture distribution.