Extended bed rest or limb immobilization can significantly reduce skeletal muscle mass and function. Recovery may be incomplete, particularly in older adults. Our laboratory recently reported that vascular mural cell (pericyte) quantity is compromised after immobilization and appropriate replacement immediately prior to remobilization can effectively recover myofiber size in mice. Identification of a single cell surface marker for isolation of the most therapeutic pericyte would streamline efforts to optimize muscle recovery. The purpose of this study was to compare the capacity for neural/glial antigen 2 (Cspg4/NG2+) and melanoma cell adhesion molecule (Mcam/CD146+) positive pericytes to uniquely recover skeletal muscle post-disuse. A single hindlimb from adult C57BL/6J mice was immobilized in full dorsiflexion via a surgical staple inserted through the center of the foot and body of the gastrocnemius. Fourteen days after immobilization, the staple was removed and pericytes, either NG2+CD45-CD31-[Lin-], CD146+NG2-Lin-, or CD146+Lin- pericytes, were injected into the atrophied tibialis anterior muscle. TA muscles were excised 14 days after transplantation and remobilization. Pericyte transplantation did not significantly improve muscle mass or myofiber CSA after 14 days of remobilization. However, injection of CD146+ pericytes significantly increased Type IIa quantity, capillarization and collagen remodeling compared to NG2+ pericytes (p<0.05). Our results suggest that selection of pericytes based on CD146 rather than NG2 results in the isolation of therapeutic mural cells with high capacity to positively remodel skeletal muscle after a period of immobilization.

Bioacoustics is a powerful and increasingly commonly used tool for terrestrial and marine biological assessments. As the scale of bioacoustic data collection has increased, techniques for processing these data have diversified. However, with analysis methods rapidly evolving and dozens of analysis software packages already available, it is challenging to identify which software, if any, meets a particular researcher’s needs. We reviewed bioacoustics software to identify packages aimed at or used by bioacoustics researchers in ecology. We compiled descriptions of the function of 65 stable or actively developed software packages used for bioacoustics analyses. Of these, 59 were free or open-source packages. In addition, we developed free, open-source Python software, OpenSoundscape, that addresses gaps in available software. OpenSoundscape simplifies the process of creating flexible, scalable deep learning algorithms for bioacoustic analysis. It can be used to train binary or multiclass convolutional neural networks with any PyTorch-implemented model structure (e.g., ResNet50, Inception v3). Researchers can easily customize its spectrogram preprocessing and data augmentation routines to improve model performance. OpenSoundscape also includes modules to work with annotated acoustic data, apply additional signal processing algorithms, perform acoustic localization, and “open the black box” of deep learning using Grad-CAM.

The performance of a design team is influenced by each team member's unique cognitive style - i.e., their preferred manner of managing structure as they solve problems, make decisions, and seek to bring about change. Cognitive style plays an important role in how teams of engineers design and collaborate, but the interactions of cognitive style with team organization and processes have not been well studied. The limitations of small-scale behavioral experiments have led researchers to develop computational models for simulating teamwork; however, none have modeled the effects of individuals' cognitive styles. This paper presents KABOOM (KAI Agent-Based Organizational Optimization Model), the first agent-based model of teamwork to incorporate cognitive style. In KABOOM, heterogeneous agents imitate the diverse problem-solving styles described by Kirton's Adaption-Innovation construct, which places each individual somewhere along the spectrum of cognitive style preference. Using the model, we investigate the interacting effects of a team's communication patterns, specialization, and cognitive style composition on design performance. By simulating cognitive style in the context of team problem solving, KABOOM lays the groundwork for the development of team simulations that reflect humans' diverse problem-solving styles.

Anabolic resistance to a mechanical stimulus may contribute to the loss of skeletal muscle mass observed with age. In this study, young and aged mice were injected with saline or human LM-111 (1 mg/kg). One week later, the myotendinous junction of the gastrocnemius muscle was removed via myotenectomy (MTE), thus placing a chronic mechanical stimulus on the remaining plantaris muscle for 2 weeks. LM-111 increased α7B integrin protein expression and clustering of the α7B integrin near DAPI+ nuclei in aged muscle in response to MTE. LM-111 reduced CD11b+ immune cells, enhanced repair, and improved the growth response to loading in aged plantaris muscle. These results suggest that LM-111 may represent a novel therapeutic approach to prevent and/or treat sarcopenia.

Collaborative problem solving can be successful or counterproductive. The performance of collaborative teams depends not only on team members' abilities, but also on their cognitive styles. Cognitive style measures differences in problem-solving behavior: how people generate solutions, manage structure, and interact. While teamwork and problem solving have been studied separately, their interactions are less understood. This paper introduces the KAI Agent-Based Organizational Optimization Model (KABOOM), the first model to simulate cognitive style in collaborative problem solving. KABOOM simulates the performance of teams of agents with heterogeneous cognitive styles on two contextualized design problems. Results demonstrate that, depending on the problem, certain cognitive styles may be more effective than others. Also, intentionally aligning agents' cognitive styles with their roles can improve team performance. These experiments demonstrate that KABOOM is a useful tool for studying the effects of cognitive style on collaborative problem solving.