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1. A three-dimensional musculoskeletal model of the dog

   https://doi.org/10.1038/s41598-021-90058-0  

   Stark, Heiko; Fischer, Martin S.; Hunt, Alexander; Young, Fletcher; Quinn, Roger; Andrada, Emanuel (December 2021, Scientific Reports)

   null (Ed.)

   Abstract The domestic dog is interesting to investigate because of the wide range of body size, body mass, and physique in the many breeds. In the last several years, the number of clinical and biomechanical studies on dog locomotion has increased. However, the relationship between body structure and joint load during locomotion, as well as between joint load and degenerative diseases of the locomotor system (e.g. dysplasia), are not sufficiently understood. Collecting this data through in vivo measurements/records of joint forces and loads on deep/small muscles is complex, invasive, and sometimes unethical. The use of detailed musculoskeletal models may help fill the knowledge gap. We describe here the methods we used to create a detailed musculoskeletal model with 84 degrees of freedom and 134 muscles. Our model has three key-features: three-dimensionality, scalability, and modularity. We tested the validity of the model by identifying forelimb muscle synergies of a walking Beagle. We used inverse dynamics and static optimization to estimate muscle activations based on experimental data. We identified three muscle synergy groups by using hierarchical clustering. The activation patterns predicted from the model exhibit good agreement with experimental data for most of the forelimb muscles. We expect that our model will speed up the analysis of how body size, physique, agility, and disease influence neuronal control and joint loading in dog locomotion. 

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2. DoG is SGD’s Best Friend: A Parameter-Free Dynamic Step Size Schedule

   Ivgi, Maor; Hinder, Oliver; Carmon, Yair (July 2023, Proceedings of the 40th International Conference on Machine Learning)

   We propose a tuning-free dynamic SGD step size formula, which we call Distance over Gradients (DoG). The DoG step sizes depend on simple empirical quantities (distance from the initial point and norms of gradients) and have no “learning rate” parameter. Theoretically, we show that, for stochastic convex optimization, a slight variation of the DoG formula enjoys strong, high-probability parameter-free convergence guarantees and iterate movement bounds. Empirically, we consider a broad range of vision and language transfer learning tasks, and show that DoG’s performance is close to that of SGD with tuned learning rate. We also propose a per-layer variant of DoG that generally outperforms tuned SGD, approaching the performance of tuned Adam. A PyTorch implementation of our algorithms is available at https://github.com/formll/dog. 

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3. The shared selection landscape of dog and human cancers

   https://doi.org/10.1101/2025.10.15.682624  

   Genereux, Diane P; Megquier, Kate; Swofford, Ross; Turner-Maier, Jason; White, Michelle; Sohrab, Vista; Husted, Christopher; Gardner, Heather; Painter, Corrie; London, Cheryl; et al (October 2025, bioRxiv)

   Cancers in pet dogs are prevalent, progress rapidly, and closely resemble human cancers, positioning them as powerful models for precision oncology. While genetic drivers of human cancer often transcend histologic boundaries, most comparative studies have focused on matched cancer types, leaving the broader scope of genomic similarity unresolved. We performed the first exome-wide, histology-agnostic comparison of canine and human cancers, analyzing 429 dog and 14,966 human tumors across 39 types. Mutational signatures and genes under selection are widely shared between species, and cancer types are as genomically similar between species as within species, with no greater similarity within dog breeds than between breeds. Machine-learning models identify genetic features shared by dog and human tumors of different histologies, mirroring cross-histology patterns in human cancer. These findings establish dog cancer as a powerful system for genomics-informed precision oncology and support pan cancer approaches to discover translationally relevant models beyond histologic classification. 

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4. Prey depletion, interspecific competition, and the energetics of hunting in endangered African wild dogs, Lycaon pictus

   https://doi.org/10.1073/pnas.2414772122  

   Creel, Scott; Redcliffe, James; Goodheart, Ben; Reyes_de_Merkle, Johnathan; Mwape, Henry; Matsushima, Stephanie; Dart, Chase; Banda, Kachama; Mayani, Bridget; Njobvu, Johane; et al (February 2025, Proceedings of the National Academy of Sciences)

   Large herbivores are in decline in much of the world, including sub-Saharan Africa, and true apex carnivores like the lion (Panthera leo) decline in parallel with their prey. As a consequence, competitively subordinate carnivores like the African wild dog (Lycaon pictus) are simultaneously experiencing a costly reduction in resources and a beneficial reduction in dominant competitors. The net effect is not intuitively obvious, but wild dogs’ density, survival, and reproduction are all low in areas that are strongly affected by prey depletion. To assess whether these correlations are causal, we tested the hypothesized mechanism, using data from 13 wild dog packs in two ecosystems to relate the energetic costs and benefits of hunting to variation in prey density, while controlling for the effects of local lion density, pack size, the number of dependent pups, and the level of protection. All of these variables affected the energetic costs and benefits of hunting. In areas with low prey density, the magnitude of movements and vectorial dynamic body acceleration (a measure of energy expenditure) both increased, the mass of killed prey decreased, and the number of kills per day did not change detectably. Programs to reduce or reverse the decline of large herbivore populations should be an effective means of improving the status of endangered subordinate competitors like the wild dog, and should be a high priority. Our results demonstrate the utility of research that integrates data from biomonitoring with direct, long-term observation of endangered species, their competitors, and their resources. 

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5. Body size is not correlated with the evolution of male coloration in darters (Percidae: Etheostomatinae)

   https://doi.org/10.1093/biolinnean/blac050  

   Ciccotto, Patrick J; Mendelson, Tamra C (May 2022, Biological Journal of the Linnean Society)

   Abstract Coloration and body size are among the many morphological traits that vary among fish lineages. Elaborate coloration and body size covary in other animal groups, but relationships between these two morphological characteristics have not been rigorously examined in fishes. We formally test for correlations between coloration and body size in darters (Percidae: Etheostomatinae), a group of North American freshwater fishes that vary in the presence of male coloration and maximum body size. Although uncorrected analyses indicate a significant correlation between colour traits and body size in darters, phylogenetically corrected logistic regression models and ANOVAs revealed no significant correlations, suggesting body size does not act as a constraint on elaborate coloration or vice versa. These results are discussed in an ecological and behavioural context. 

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