ABSTRACT
There are few recent and methodologically robust life expectancy (LE) tables for dogs or cats. This study aimed to generate LE tables for these species with clinical records from >1,000 Banfield Pet hospitals in the USA. Using Sullivan's method, LE tables were generated across survey years 2013-2019, by survey year, and for subpopulations defined by sex, adult body size group (purebred dogs only: toy, small, medium, large and giant), and median body condition score (BCS) over life. The deceased population for each survey year comprised animals with a recorded date of death in that year; survivors had no death date in that year and were confirmed living by a veterinary visit in a subsequent year. The dataset totaled 13,292,929 unique dogs and 2,390,078 unique cats. LE at birth (LEbirth) was 12.69 years (95% CI: 12.68-12.70) for all dogs, 12.71 years (12.67-12.76) for mixed-breed dogs, 11.18 years (11.16-11.20) for cats, and 11.12 (11.09-11.14) for mixed-breed cats. LEbirth increased with decreasing dog size group and increasing survey year 2013 to 2018 for all dog size groups and cats. Female dogs and cats had significantly higher LEbirth than males: 12.76 years (12.75-12.77) vs. 12.63 years (12.62-12.64), and 11.68 years (11.65-11.71) vs. 10.72 years (10.68-10.75), respectively. Obese dogs (BCS 5/5) had a significantly lower LEbirth [11.71 years (11.66-11.77)] than overweight dogs (BCS 4/5) [13.14 years (13.12-13.16)] and dogs with ideal BCS 3/5 [13.18 years (13.16-13.19)]. The LEbirth of cats with BCS 4/5 [13.67 years (13.62-13.71)] was significantly higher than cats with BCS 5/5 [12.56 years (12.45-12.66)] or BCS 3/5 [12.18 years (12.14-12.21)]. These LE tables provide valuable information for veterinarians and pet owners and a foundation for research hypotheses, as well as being a stepping-stone to disease-associated LE tables.
ABSTRACT
Microorganisms play a role in the construction or modulation of various types of landforms. They are especially notable for forming microbially induced sedimentary structures (MISS). Such microbial structures have been considered to be among the most likely biosignatures that might be encountered on the martian surface. Twenty-nine algorithms have been tested with images taken during a laboratory experiment for testing their performance in discriminating mat cracks (MISS) from abiotic mud cracks. Among the algorithms, neural network types produced excellent predictions with similar precision of 0.99. Following that step, a convolutional neural network (CNN) approach has been tested to see whether it can conclusively detect MISS in images of rocks and sediment surfaces taken at different natural sites where present and ancient (fossil) microbial mat cracks and abiotic desiccation cracks were observed. The CNN approach showed excellent prediction of biotic and abiotic structures from the images (global precision, sensitivity, and specificity, respectively, 0.99, 0.99, and 0.97). The key areas of interest of the machine matched well with human expertise for distinguishing biotic and abiotic forms (in their geomorphological meaning). The images indicated clear differences between the abiotic and biotic situations expressed at three embedded scales: texture (size, shape, and arrangement of the grains constituting the surface of one form), form (outer shape of one form), and pattern of form arrangement (arrangement of the forms over a few square meters). The most discriminative components for biogenicity were the border of the mat cracks with their tortuous enlarged and blistered morphology more or less curved upward, sometimes with thin laminations. To apply this innovative biogeomorphological approach to the images obtained by rovers on Mars, the main physical and biological sources of variation in abiotic and biotic outcomes must now be further considered.