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The soil bacteriumMyxococcus xanthusis a model organism with a set of diverse behaviors. These behaviors include the starvation-induced multicellular development program, in which cells move collectively to assemble multicellular aggregates. After initial aggregates have formed, some will disperse, with smaller aggregates having a higher chance of dispersal. Initial aggregation is driven by two changes in cell behavior: cells slow down inside of aggregates and bias their motion by reversing direction less frequently when moving toward aggregates. However, the cell behaviors that drive dispersal are unknown. Here, we use fluorescent microscopy to quantify changes in cell behavior after initial aggregates have formed. We observe that after initial aggregate formation, cells adjust the bias in reversal timings by initiating reversals more rapidly when approaching unstable aggregates. Using agent-based modeling, we then show dispersal is predominantly generated by this change in bias, which is strong enough to overcome slowdown inside aggregates. Notably, the change in reversal bias is correlated with the nearest aggregate size, connecting cellular activity to previously observed correlations between aggregate size and fate. To determine if this connection is consistent across strains, we analyze a secondM. xanthusstrain with reduced levels of dispersal. We find that far fewer cells near smaller aggregates modified their bias. This implies that aggregate dispersal is under genetic control, providing a foundation for further investigations into the role it plays in the life cycle ofM. xanthus.

Understanding the processes behind bacterial biofilm formation, maintenance, and dispersal is essential for addressing their effects on health and ecology. Within these multicellular communities, various cues can trigger differentiation into distinct cell types, allowing cells to adapt to their specific local environment. The soil bacteriumMyxococcus xanthusforms biofilms in response to starvation, marked by cells aggregating into mounds. Some aggregates persist as spore-filled fruiting bodies, while others disperse after initial formation for unknown reasons. Here, we use a combination of cell tracking analysis and computational simulations to identify behaviors at the cellular level that contribute to aggregate dispersal. Our results suggest that cells in aggregates actively determine whether to disperse or persist and undergo a transition to sporulation based on a self-produced cue related to the aggregate size. Identifying these cues is an important step in understanding and potentially manipulating bacterial cell-fate decisions.

 

Myxococcus xanthus bacteria are a model system for understanding pattern formation and collective cell behaviors. When starving, cells aggregate into fruiting bodies to form metabolically inert spores. During predation, cells self-organize into traveling cell-density waves termed ripples. Both phase-contrast and fluorescence microscopy are used to observe these patterns but each has its limitations. Phase-contrast images have higher contrast, but the resulting image intensities lose their correlation with cell density. The intensities of fluorescence microscopy images, on the other hand, are well-correlated with cell density, enabling better segmentation of aggregates and better visualization of streaming patterns in between aggregates; however, fluorescence microscopy requires the engineering of cells to express fluorescent proteins and can be phototoxic to cells. To combine the advantages of both imaging methodologies, we develop a generative adversarial network that converts phase-contrast into synthesized fluorescent images. By including an additional histogram-equalized output to the state-of-the-art pix2pixHD algorithm, our model generates accurate images of aggregates and streams, enabling the estimation of aggregate positions and sizes, but with small shifts of their boundaries. Further training on ripple patterns enables accurate estimation of the rippling wavelength. Our methods are thus applicable for many other phenotypic behaviors and pattern formation studies. 

Chronic impairment in the paretic ankle following stroke often requires that individuals use compensatory patterns such as asymmetric propulsion to achieve effective walking speeds needed for community engagement. Ankle exosuit assistance can provide ankle biomechanical benefit in the lab, but such environments inherently limit the amount of practice available. Community walking studies without exosuits can provide massed practice and benefit walking speed but are limited in their ability to assist proper mechanics. In this study, we combined the positive aspects of community training with those of exosuit assistance. We developed and evaluated a community Robotic Exosuit Augmented Locomotion (cREAL) program. Four participants in the chronic stage of stroke independently used our community ankle exosuit for walking in the community 3–5 days/week for 4 weeks. We performed lab evaluations before and after the 4‐week program. Two participants significantly improved their unassisted paretic propulsion by an average of 27% after the program and walked on average 4001 steps/day more in the week following the program. Despite the small number of participants, this study provides preliminary evidence for the potential of exosuits to augment gait training and rehabilitation in the community.

 

Telementoring platforms can help transfer surgical expertise remotely. However, most telementoring platforms are not designed to assist in austere, pre-hospital settings. This paper evaluates the system for telementoring with augmented reality (STAR), a portable and self-contained telementoring platform based on an augmented reality head-mounted display (ARHMD). The system is designed to assist in austere scenarios: a stabilized first-person view of the operating field is sent to a remote expert, who creates surgical instructions that a local first responder wearing the ARHMD can visualize as three-dimensional models projected onto the patient’s body. Our hypothesis evaluated whether remote guidance with STAR could lead to performing a surgical procedure better, as opposed to remote audio-only guidance. Remote expert surgeons guided first responders through training cricothyroidotomies in a simulated austere scenario, and on-site surgeons evaluated the participants using standardized evaluation tools. The evaluation comprehended completion time and technique performance of specific cricothyroidotomy steps. The analyses were also performed considering the participants’ years of experience as first responders, and their experience performing cricothyroidotomies. A linear mixed model analysis showed that using STAR was associated with higher procedural and non-procedural scores, and overall better performance. Additionally, a binary logistic regression analysis showed that using STAR was associated to safer and more successful executions of cricothyroidotomies. This work demonstrates that remote mentors can use STAR to provide first responders with guidance and surgical knowledge, and represents a first step towards the adoption of ARHMDs to convey clinical expertise remotely in austere scenarios.