A large amount of overlap exists in the B-mode ultrasound appearance of normal and abnormal liver, spleen, and kidney tissues in cats. Therefore, invasive tissue sampling procedures remain the standard method for diagnosing diseases in these organs. The purpose of our study was to assess the feasibility of ultrasound elastography as a technique for improving noninvasive characterization of the feline liver, spleen, and kidneys. Elastography was performed on 10 unsedated, clinically healthy cats. Numeric (strain) values (0 = softest to 255 = firmest) assigned to color pixels within regions of interest resulted in median scores (interquartile ranges) of body wall, 207.50 (189.75-224.00); liver, 119.00 (105.00-138.25); spleen, 127.50 (121-00-142.00); right renal cortex, 83.50 (64.00-130.00); right renal near field, 125.50 (110.75-139.75); left renal cortex, 77.50 (52.00-116.25); and left renal near field, 126.00 (114.00-145.25). Strain values were not different between organs. Body wall median was the only significantly different value (P < 0.05). Strain ratio values of body wall:organ were as follows: liver, 1.76 (1.38-2.00); spleen, 1.68 (1.47-1.83); right renal cortex, 2.31 (1.61-3.15); right renal near field, 1.62 (1.41-2.01); left renal cortex, 2.66 (1.45-4.13); and left renal near field, 1.51 (1.29-1.89). Subjectively, hepatic and splenic parenchymal tissues were homogeneous in compressibility and similar in elasticity to one another. Renal cortical tissue was softer compared to medullary tissue. Findings indicated that ultrasound elastography is a feasible technique for objectively and subjectively characterizing the feline liver, spleen, and kidneys. Further research is needed in cats with confirmed diseases of these organs, to compare the diagnostic sensitivity of ultrasound elastography vs. B-mode ultrasonography.
Difficulty has been encountered when trying to identify ante mortem prognostic indicators for dogs with meningoencephalitis of unknown etiology (MUE). Identifying MRI imaging parameters associated with prognosis may impact treatment decision-making for clinician and owner. Our hypotheses for this retrospective cohort study are that dogs diagnosed with MUE that had midline shift on brain MRI would have a poorer survival compared to dogs without midline shift; and that younger age, lower weight, and low cerebrospinal fluid (CSF) cell count would be correlated with improved survival. Medical records were reviewed from two institutions. Inclusion criteria included: clinical signs referable to intracranial disease, brain MRI at presentation, abnormal CSF analysis, and negative infectious disease testing. Magnetic resonance imaging scans were evaluated for midline shift using the T2-weighted transverse image at the interthalamic adhesion and at the site of maximal deviation. Fifty-two dogs met the inclusion criteria. Median midline deviation was 0.12 cm. Median survival for dogs with no shift was 906 days and with shift was 84 days. Survival was not significantly different between groups (P = 0.11). This remained true when correcting for age (P = 0.22) and CSF TNCC (total nucleated cell count) (P = 0.12). Age at the time of diagnosis (P = 0.02) and CSF TNCC (P = 0.03) were significantly associated with survival. Cerebrospinal fluid protein value (P = 0.84) and weight (P = 0.82) were not significantly associated with survival. In this study of 52 dogs with MUE, MRI evidence of midline brain shift between 0.04 and 0.3 cm at the level of the interthalamic adhesion was not associated with shorter survival.
We seek to guide design, development, and adoption of Renewable Assignments by testing ways learners can contribute to Open Educational Resources (OER). We design, test, and iterate four assignment structures to this end. Testing was completed in an upper-division undergraduate endocrinology course, taught emergency remote due to COVID-19.Using mixed methods: surveys, focus groups, and iterations, we assessed assignment structures and created design guidance for renewable assignments and open pedagogy. We find that in a remote course, these assignments were effective in advancing learning goals. Both students and teachers favored their inclusion in the course. Analysis revealed six design principles to maximize effectiveness of renewable assignments and courses, and empowering teachers and learners to contribute to open knowledge. These principles also provide insight to praxis related to theories of open pedagogy, scaffolding, peer interaction, and active learning.
Context
Eco-evolutionary dynamics result when interacting biological forces simultaneously produce demographic and genetic population responses. Eco-evolutionary simulators traditionally manage complexity by minimizing the influence of spatial pattern on process. However, this simplification can limit their utility in real-world applications.
Objectives
We present a novel simulation modeling approach for investigating eco-evolutionary dynamics, centered on the driving role of landscape pattern. Our spatially-explicit, individual-based mechanistic simulation approach overcomes existing methodological challenges, generates new insights, and paves the way for future investigations in four focal disciplines: Landscape Genetics, Population Genetics, Conservation Biology, and Evolutionary Ecology.
Methods
We developed a simple individual-based model to illustrate how spatial structure drives eco-evo dynamics. By making minor changes to our landscape’s structure, we simulated continuous, isolated, and semi-connected landscapes, and simultaneously tested several classical assumptions of the focal disciplines.
Results
Our results exhibit expected patterns of isolation, drift, and extinction. By imposing landscape change on otherwise functionally-static eco-evolutionary models, we altered key emergent properties such as gene-flow and adaptive selection. We observed demo-genetic responses to these landscape manipulations, including changes in population size, probability of extinction, and allele frequencies. Our model also demonstrated how demo-genetic traits, including generation time and migration rate, can arise from a mechanistic model, rather than being specified a priori.
Conclusions
We identify simplifying assumptions common to four focal disciplines, and illustrate how new insights might be developed in eco-evolutionary theory and applications by better linking biological processes to landscape patterns that we know influence them, but that have understandably been left out of many past modeling studies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.