Clinical and pathological classification of canine intraocular lymphoma

The objectives of this retrospective study of 100 dogs with intraocular lymphoma were to describe the histomorphologic and immunohistochemical features of canine intraocular lymphoma, determine the proportion of cases with presumed solitary ocular lymphoma (PSOL) compared to multicentric disease, and assess the clinical outcomes of these patients. Selected cases from Penn Vet Diagnostic Laboratory and Comparative Ocular Pathology Lab of Wisconsin (2004–2015) were evaluated and subtyped using the WHO classification system. Peripheral T‐cell lymphoma and diffuse large B‐cell lymphoma were the two most common subtypes. Questionnaires were distributed to the referring veterinarians and veterinary ophthalmologists inquiring about clinical signs at time of enucleation, staging, patient outcome, treatment, and disease progression. Cases were categorized as PSOL if only ocular involvement was noted at the time of diagnosis based on the clinical staging criteria. The majority of cases (61%) did not have systemic involvement at the time of diagnosis, and these cases did not progress postoperatively. Median survival time (MST) was significantly higher for the presumed solitary intraocular cases: 769 vs. 103 days, hazard ratio of 0.23 (95% CI: 0.077–0.68). The subtype of lymphoma did not affect survival time. The results of this study suggest two significant points of clinical interest: the majority of dogs (61%) presented without signs of systemic involvement of lymphoma at the time of enucleation, and dogs with only ocular involvement showed no disease progression postenucleation.     

Rainfall Interception by Singleleaf Piñon and Utah Juniper: Implications for Stand-Level Effective Precipitation

The expansion of piñon and juniper trees into sagebrush steppe and the infilling of historic woodlands has caused a reduction in the cover and density of the understory vegetation. Water is the limiting factor in these systems; therefore, quantifying redistribution of water resources by tree species is critical to understanding the dynamics of these formerly sagebrush-dominated rangelands. Tree canopy interception may have a significant role in reducing the amount of rainfall that reaches the ground beneath the tree, thereby reducing the amount of available soil moisture. We measured canopy interception of rainfall by singleleaf piñon (Pinus monophylla Torr. & Frém.) and Utah juniper (Juniperus osteosperma [Torr.] Little) across a gradient of storm sizes. Simulated rainfall was used to quantify interception and effective precipitation during 130 rainfall events ranging in size from 2.2 to 25.9 mm hr^? 1 on 19 trees of each species. Effective precipitation was defined as the sum of throughfall and stemflow beneath tree canopies. Canopy interception averaged 44.6% (± 27.0%) with no significant difference between the two species. Tree allometrics including height, diameter at breast height, stump diameter, canopy area, live crown height, and width were measured and used as predictor variables. The best fit predictive model of effective precipitation under canopy was described by stump diameter and gross precipitation (R² = 0.744, P < 0.0001). An alternative management model based on canopy area and gross precipitation predicted effective precipitation with similar accuracy (R² = 0.741, P < 0.0001). Canopy area can be derived from various remote sensing techniques, allowing these results to be extrapolated to larger spatial scales to quantify the effect of increasing tree canopy cover on rainfall interception loss and potential implications for the water budget.     

Transpalpebral ultrasonographic measurement of the optic nerve sheath diameter in healthy dogs

Objective

To develop a reference range for ultrasonographically measured optic nerve sheath diameter (ONSD‐US) in dogs. We hypothesized that ONSD‐US can be measured reliably and is associated with weight but not age, sex, or body condition score (BCS), and that the relationship between weight and ONSD‐US in dogs is allometric due to canine size variations.

Design

Prospective, observational study.

Setting

University teaching hospital.

Animals

Seventy‐eight healthy adult dogs.

Interventions

The ONSD was measured by a standardized transpalpebral approach.

Measurements and Main Results

Regression analysis showed the relationship between weight and ONSD was better fit with a linear model (R² = 0.8510) than an allometric model (R² = 0.7917). Multiple regression analysis showed ONSD is associated with weight (P < 0.0001), age (P = 0.0021), and BCS (P = 0.0007), but not with sex. Dominance analysis showed 94.6% of the variance explained by the model was due to weight. Intraclass correlation coefficient (ICC) analysis showed excellent interobserver (ICC = 0.9338–0.9608) and intraobserver (ICC = 0.9893) reliability.

Conclusions

These results suggest that ONSD‐US may be reliably measured in dogs using our described transpalpebral approach, and we have calculated prediction intervals based on body weight. Future studies are needed to determine if ONSD‐US measurements are associated with intracranial hypertension as shown in human medicine.     

Surface metrics: scaling relationships and downscaling behavior

Context

Considerable research has examined scale effects for patch-based metrics with the ultimate goal of predicting values at finer resolutions (i.e., downscaling), but results have been inconsistent. Surface metrics have been suggested as an alternative to patch-based metrics, although far less is known about their scaling relationships and downscaling potential. If successful, downscaling would enable integration of disparate datasets and comparison of landscapes using different resolution datasets.

Objectives

(1) Determine how surface metrics scale as resolution changes and how consistent those scaling relationships are across landscapes. (2) Test whether these scaling relationships can be accurately downscaled to predict metric values for finer resolutions.

Methods

Various scaling functions were fit to 16 surface metrics computed for multiple resolutions for a set of landscapes. Best-fitting functions were then extrapolated to test downscaling behavior (i.e., predict metric value for a finer resolution) for an independent set of validation landscapes. Relative error was assessed between the predicted and true values to determine downscaling robustness.

Results

Seven surface metrics (Sa, Sq, S10z, Sdq, Sds, Sdr, Srwi) fit consistently well (R² > 0.99) with a 3rd order polynomial or power law. Of those, the scaling functions for Sa, Sq, and S10z were able to predict metric values at a finer resolution within 5 %. Three metrics, (Ssk, Sku, Sfd) were also notable in terms of fit and downscaling.

Conclusions

Many metrics exhibit consistent scaling relations across resolution, and several are able to accurately predict values at finer resolutions. However, prediction accuracy is likely related to the amount of information lost during aggregation.