Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.12.13.628330

Accelerometer-derived classifiers for early detection of degenerative joint disease in cats

Montout, A.·Maniaki, E.·Burghardt, T.·Hezzell, M.·Blackwell, E.·Dowsey, A. W.
View original source ↗Export metadata ↓

Abstract

Decreased mobility is a clinical sign of degenerative joint disease (DJD) in cats, which is highly prevalent, with 61% of cats aged six years or older showing radiographic evidence of DJD. Radiographs can reveal morphological changes and assess joint degeneration, but they cannot determine the extent of pain experienced by cats. Additionally, there is no universal objective assessment method for DJD-associated pain in cats. Developing an accurate evaluation model could enable earlier treatment, slow disease progression, and improve cats well-being. This study aimed to predict early signs of DJD in cats using accelerometers and machine learning techniques. Cats were restricted to indoors or limited outdoor access, including being walked on a lead or allowed into enclosed areas for short periods. Fifty-six cats were fitted with collar-mounted sensors that collected accelerometry data over 14 days, with data from 51 cats included in the analysis. Cat owners assessed their cats mobility and assigned condition scores, validated through clinical orthopaedic examinations. The study group comprised 24 healthy cats (no owner-reported mobility changes) and 27 unhealthy cats (owner-reported mobility changes, suggestive of early DJD). Data were segmented into 60-second windows centred around peaks of high activity. Using a Support Vector Machine (SVM) algorithm, the model achieved 78% (confidence interval: 0.65, 0.88) area under the curve (AUC), with 68% sensitivity (0.64, 0.77) at 75% specificity (0.68, 0.79). These results demonstrate the potential of accelerometry and machine learning to aid early DJD diagnosis and improve management, offering significant advances in non-invasive diagnostic techniques for cats.

Source connections

Explore related subjects

animal behavior and cognitionPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Montout, A., Maniaki, E., Burghardt, T., Hezzell, M., Blackwell, E., Dowsey, A. W.. 2024-12-17. Accelerometer-derived classifiers for early detection of degenerative joint disease in cats. https://doi.org/10.1101/2024.12.13.628330

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Deconstructing Boldness: Latent behavioural structure across novelty, predation, and exploration in an endangered species translocation program

Risk-related behaviours including neophobia, exploration, and predator avoidance are often assumed to covary along a general boldness axis. Although some translocation studies have linked one or more of these behaviours with fitness, it is possible that the underlying behavioural structure varies under different selective environments. Conservation breeding programs provide a unique opportunity to evaluate the structure of behavioural correlations in a non-domestic species under artificial conditions. We tested whether risk-related behaviours represent a unified boldness syndrome in a captive population of the endangered Attwaters prairie chicken (APC; Tympanuchus cupido attwateri). We quantified the repeatable behaviours of 257 juveniles and compared 11 models of behavioural covariation structure using multivariate mixed models and confirmatory factor analysis. There was no support for a single risk-taking axis; instead, we found three dimensions representing responses to novelty and environmental stimuli (Engagement), predator avoidance (Threat Response), and maze exploration (Maze Progression). Our results indicate that these risk-related behaviours are not organized along a single axis in captive APCs, challenging assumptions that risk-taking represents a universal behavioural syndrome. To anticipate post-release success accurately, conservation managers should understand the exact behavioural architecture of the captive population rather than assume that the classical bold-shy structure occurs in all contexts.

animal behavior and cognition↗
bioRxiv2026

Social costs of group life: Larger groups have less affiliative behavior and more social conflict

The costs and benefits of sociality depend in part upon the size of groups. Therefore, individual behavior should vary across groups of different sizes, reflecting group size-dependent costs and benefits. Here, we test this prediction using a long-term dataset on wild female baboons (Papio cynocephalus x P. anubis). We find that individuals who live in larger groups suffer social costs: compared to animals in smaller groups, they experience more agonistic interactions, fewer grooming interactions, and sparser social networks. These social costs arise, in part, from a pattern in which relationships within dyads become more agonistic as group size increases (i.e., a given dyad exhibits fewer grooming interactions relative to agonistic interactions when it is living in a larger group). While individuals in large groups generally maintain the same number of strong bonds as individuals in small groups, they tend to develop weak bonds with a greater number of social partners that results in, on average, weaker bonds overall. Our results demonstrate that, despite potential benefits to large groups in terms of predation risk and intergroup competition, the social lives of individuals in larger groups involve less affiliation and more conflict in this wild primate population.

animal behavior and cognition↗
bioRxiv2026

Shared brain transcriptome signatures of social evolution and plasticity in shell-dwelling cichlid fishes

Inter-individual variability in phenotypic traits is widespread in nature both across and within species, with similar patterns of variation often occurring between and within species. Given that these two types of variation are generated by evolutionary and plasticity processes respectively, it raises the question to what extent the causal mechanisms underlying such variability at these two different levels are shared or not. To address this question, we studied the variation in brain transcriptomes in Tanganyikan cichlids that exhibit both intra- and interspecific variation in social behavior. We compared two facultatively social cichlid species, each containing naturally occurring solitary and social-living individuals, with a closely related obligatory solitary resembling the ancestral state. Differential gene expression and Gene Set Enrichment Analyses were performed in the telencephalon and diencephalon transcriptomes to investigate the molecular basis of both behavioral plasticity and the evolution of sociality. Behavioral plasticity involved few differentially expressed genes but extensive changes in biological pathways, supporting a highly polygenic architecture of social behavior. Across both species, social-living individuals consistently upregulated pathways involved in translation, protein homeostasis, and energy metabolism, whereas solitary individuals showed enrichment of neuronal morphogenesis, cell adhesion, and structural plasticity. Remarkably, these same functional programs were associated with the independent evolution of sociality, revealing a strong overlap between evolutionary and plastic transcriptional responses. This convergence was largely restricted to the telencephalon, while the diencephalon showed limited and inconsistent functional signatures. Together, our results support the repeated recruitment of gene regulatory programs during the evolution of sociality and demonstrate that behavioral plasticity and evolutionary transitions share common neurogenomic responses, consistent with a conserved genetic toolkit for social behavior.

animal behavior and cognition↗