Effects of photoperiod on food intake, activity and metabolic rate in adult neutered male cats

How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households

Surprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the season influences the daily behaviour of cats. Using accelerometer data and a validated machine learning model, behaviours including being active, eating, grooming, littering, lying, scratching, sitting, and standing were quantified for 28 pet cats. Generalized estimating equation models were used to determine the effects of different environmental conditions. Increasing cat age was negatively correlated with time spent active (p < 0.05). Cats with outdoor access (n = 18) were less active in winter than in summer (p < 0.05), but no differences were observed between seasons for indoor-only (n = 10) cats. Cats living in rural areas (n = 7) spent more time eating than cats in urban areas (n = 21; p < 0.05). Cats living in single-cat households (n = 12) spent more time lying but less time sitting than cats living in multi-cat households (n = 16; p < 0.05). Cats in households with at least one child (n = 20) spent more time standing in winter (p < 0.05), and more time lying but less time sitting in summer compared to cats in households with no children (n = 8; p < 0.05). This study clearly shows that the home environment has a major impact on cat behaviour.

Comparison of Locomotor and Feeding Rhythms between Indoor and Outdoor Cats Living in Captivity

The plastic nature of cat behaviour allows this “friendly symbiont” of humans to adapt to various housing conditions. Beyond daylight, one could wonder if other environmental factors affect its patterns. Yet, how its activity and feeding rhythms are impacted by its environment is rarely studied in standardised conditions between populations. We compared the behaviour of cats living in a 29 m2 indoor room and cats living in a 1145 m2 outdoor enclosure, tracking them simultaneously in summer for 21 days, with advanced technologies. Both populations received daylight but weather fluctuations only occurred outdoors. Bimodality was detected in the activity and feeding rhythms of both groups, while twilight triggered crepuscular peaks. Daily, the outdoor population covered more distance (4.29 ± 0.27 km; p < 0.001) and consumed more food (67.44 ± 2.65 g; p < 0.05) than the indoor population (2.33 ± 0.17 km, 57.75 ± 2.85 g, respectively), but displayed less rhythmic behaviours, assumedly because of rhythm disruptors met only in outdoor conditions. Finally, outdoor housing seemed to promote the exploratory behaviour of the cats at night, while indoor housing increased both meal frequency (p = 0.063) and the impact of human interactions on the feeding rhythms of the cats.

Physical activity patterns of free living dogs diagnosed with osteoarthritis

Osteoarthritis (OA) affects about 90% of dogs > 5 yr of age in the United States, resulting in reduced range of motion, difficulty climbing and jumping, reduced physical activity, and lower quality of life. Our objective was to use activity monitors to measure physical activity and identify how activity counts correlate with age, body weight (BW), body condition score (BCS), serum inflammatory markers, veterinarian pain assessment, and owner perception of pain in free-living dogs with OA. The University of Illinois Institutional Animal Care and Use Committee approved the study and owner consent was received prior to experimentation. Fifty-six client-owned dogs (mean age = 7.8 yr; mean BCS = 6.1) with clinical signs and veterinary diagnosis of OA wore HeyRex activity collars continuously over a 49-d period. Blood samples were collected on day 0 and 49, and dog owners completed canine brief pain inventory (CBPI) and Liverpool osteoarthritis in dogs (LOAD) surveys on day 0, 21, 35, and 49. All data were analyzed using SAS 9.3 using repeated measures and R Studio 1.0.136 was used to generate Pearson correlation coefficients between data outcomes. Average activity throughout the study demonstrated greater activity levels on weekends. It also showed that 24-h activity spiked twice daily, once in the morning and another in the afternoon. Serum C-reactive protein concentration was lower (P < 0.01) at day 49 compared to day 0. Survey data indicated lower (P < 0.05) overall pain intensity and severity score on day 21, 35 and 49 compared to day 0. BW was correlated with average activity counts (P = 0.02; r = -0.12) and run activity (P = 0.10; r = -0.24). Weekend average activity counts were correlated with owner pain intensity scores (P = 0.0813; r = -0.2311), but weekday average activity count was not. Age was not correlated with total activity count, sleep activity, or run activity, but it was correlated with scratch (P = 0.03; r = -0.10), alert (P = 0.03; r = -0.13), and walk (P = 0.09; r = -0.23) activities. Total activity counts and activity type (sleep, scratch, alert, walk, and run) were not correlated with pain scored by veterinarians, pain intensity or severity scored by owners, or baseline BCS. Even though the lack of controls and/or information on the individual living conditions of dogs resulted in a high level of variability in this study, our data suggest that the use of activity monitors have the potential to aid in the management of OA and other conditions affecting activity (e.g., allergy; anxiety).

Seasonal fluctuations in body weight during growth of Thoroughbred racehorses during their athletic career

Background

Domesticated horses adapt to environmental conditions through seasonal fluctuations in their metabolic rate. The seasonal change of metabolic rates of domesticated horses in pastures is documented. However, there are few investigations on seasonal body weight change of domesticated horses housed in stables, which are provided constant energy intake throughout the year. Both seasonal changes and gain in body weight of racehorses during their athletic career is known to a lesser extent because their body weight are not measured in most countries. Here, we used a seasonal-trend decomposition method to conduct a time series analysis of body weight of Thoroughbred racehorses participating in flat races held by the Japan Racing Association from 1 January 2002 to 31 December 2014.

Results

We acquired 640,431 body weight measurements for race starts and included 632,540 of these in the time series analysis. Based on seasonal component analysis, the body weight of male and gelding horses peaked in autumn and winter and reached its nadir in summer. In contrast, the body weight of female horses peaked in autumn and reached the nadir in spring. Based on trend component analysis, most of the increase in body weight was observed when all sexes approached 5 years of age. The slope of the body weight gain was smaller after that, and an approximately 30 kg gain was observed during their careers.

Conclusion

These results indicate that the body weight of a Thoroughbred racehorse fluctuates seasonally, and that there may be sex differences in energy balance mechanisms. Moreover, the present results suggest that the physiological development of Thoroughbred racehorses is completed just before they reach 5 years of age.

The Use of Functional Data Analysis to Evaluate Activity in a Spontaneous Model of Degenerative Joint Disease Associated Pain in Cats

Introduction and objectives

Accelerometry is used as an objective measure of physical activity in humans and veterinary species. In cats, one important use of accelerometry is in the study of therapeutics designed to treat degenerative joint disease (DJD) associated pain, where it serves as the most widely applied objective outcome measure. These analyses have commonly used summary measures, calculating the mean activity per-minute over days and comparing between treatment periods. While this technique has been effective, information about the pattern of activity in cats is lost. In this study, functional data analysis was applied to activity data from client-owned cats with (n = 83) and without (n = 15) DJD. Functional data analysis retains information about the pattern of activity over the 24-hour day, providing insight into activity over time. We hypothesized that 1) cats without DJD would have higher activity counts and intensity of activity than cats with DJD; 2) that activity counts and intensity of activity in cats with DJD would be inversely correlated with total radiographic DJD burden and total orthopedic pain score; and 3) that activity counts and intensity would have a different pattern on weekends versus weekdays.

Results and conclusions

Results showed marked inter-cat variability in activity. Cats exhibited a bimodal pattern of activity with a sharp peak in the morning and broader peak in the evening. Results further showed that this pattern was different on weekends than weekdays, with the morning peak being shifted to the right (later). Cats with DJD showed different patterns of activity from cats without DJD, though activity and intensity were not always lower; instead both the peaks and troughs of activity were less extreme than those of the cats without DJD. Functional data analysis provides insight into the pattern of activity in cats, and an alternative method for analyzing accelerometry data that incorporates fluctuations in activity across the day.

Effect of photoperiod on the feline adipose transcriptome as assessed by RNA sequencing

Background

Photoperiod is known to cause physiological changes in seasonal mammals, including changes in body weight, physical activity, reproductive status, and adipose tissue gene expression in several species. The objective of this study was to determine the effects of day length on the adipose transcriptome of cats as assessed by RNA sequencing. Ten healthy adult neutered male domestic shorthair cats were used in a randomized crossover design study. During two 12-wk periods, cats were exposed to either short days (8 hr light:16 hr dark) or long days (16 hr light:8 hr dark). Cats were fed a commercial diet to maintain baseline body weight to avoid weight-related bias. Subcutaneous adipose biopsies were collected at wk 12 of each period for RNA isolation and sequencing.

Results

A total of 578 million sequences (28.9 million/sample) were generated by Illumina sequencing. A total of 170 mRNA transcripts were differentially expressed between short day- and long day-housed cats. 89 annotated transcripts were up-regulated by short days, while 24 annotated transcripts were down-regulated by short days. Another 57 un-annotated transcripts were also different between groups. Adipose tissue of short day-housed cats had greater expression of genes involved with cell growth and differentiation (e.g., myostatin; frizzled-related protein), cell development and structure (e.g., cytokeratins), and protein processing and ubiquitination (e.g., kelch-like proteins). In contrast, short day-housed cats had decreased expression of genes involved with immune function (e.g., plasminogen activator inhibitor 1; chemokine (C-C motif) ligand 2; C-C motif chemokine 5; T-cell activators), and altered expression of genes associated with carbohydrate and lipid metabolism.

Conclusions

Collectively, these gene expression changes suggest that short day housing may promote adipogenesis, minimize inflammation and oxidative stress, and alter nutrient metabolism in feline adipose tissue, even when fed to maintain body weight. Although this study has highlighted molecular mechanisms contributing to the seasonal metabolic changes observed in cats, future research that specifically targets and studies these biological pathways, and the physiological outcomes that are affected by them, is justified.

Seasonal variation in the voluntary food intake of domesticated cats (Felis catus)

There are numerous reports about seasonal cycles on food intake in animals but information is limited in dogs and cats. A 4-year prospective, observational, cohort study was conducted to assess differences in food intake in 38 ad-libitum-fed adult colony cats, of various breeds, ages and genders. Individual food intake was recorded on a daily basis, and the mean daily intake for each calendar month was calculated. These data were compared with climatic data (temperature and daylight length) for the region in the South of France where the study was performed. Data were analysed using both conventional statistical methods and by modelling using artificial neural networks (ANN). Irrespective of year, an effect of month was evident on food intake (P<0.001), with three periods of broadly differing intake. Food intake was least in the summer months (e.g. June, to August), and greatest during the months of late autumn and winter (e.g. October to February), with intermediate intake in the spring (e.g. March to May) and early autumn (e.g. September). A seasonal effect on bodyweight was not recorded. Periods of peak and trough food intake coincided with peaks and troughs in both temperature and daylight length. In conclusion, average food intake in summer is approximately 15% less than food intake during the winter months, and is likely to be due to the effects of outside temperatures and differences in daylight length. This seasonal effect in food intake should be properly considered when estimating daily maintenance energy requirements in cats.