More Like this

1. AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing

   https://doi.org/10.1038/s42003-025-08162-0  

   Saraithong, Prakaimuk; Krajcarski, Peyton; Kusaka, Yukako; Yamada, Moe; Matsumoto, Junichi; Cunningham, Hailey; Salih, Sama; Jones, Darby; Baddhan, Devika; Hausner, Christian; et al (December 2025, Communications Biology)

   Current methods for producing cardiomyocytes from human induced pluripotent stem cells (hiPSCs) using 2D monolayer differentiation are often hampered by batch-to-batch variability and inef!cient puri!cation processes. Here, we introduce CM-AI, a novel arti!cial intelligence-guided laser cell processing platform designed for rapid, label-free puri!cation of hiPSC-derived cardiomyocytes (hiPSC-CMs). This approach signi!cantly reduces processing time without the need for chronic metabolic selection or antibody-based sorting. By integrating real-time cellular morphology analysis and targeted laser ablation, CM-AI selectively removes non-cardiomyocyte populations with high precision. This streamlined process preserves cardiomyocyte viability and function, offering a scalable and ef!cient solution for cardiac regenerative medicine, disease modeling, and drug disco 

   more » « less
2. Mathematical analysis of simple behavioral epidemic models

   https://doi.org/10.1016/j.mbs.2024.109250  

   LeJeune, Leah; Ghaffarzadegan, Navid; Childs, Lauren M; Saucedo, Omar (September 2024, Mathematical Biosciences)

   COVID-19 highlighted the importance of considering human behavior change when modeling disease dynamics. This led to developing various models that incorporate human behavior. Our objective is to contribute to an in-depth, mathematical examination of such models. Here, we consider a simple deterministic compartmental model with endogenous incorporation of human behavior (i.e., behavioral feedback) through transmission in a classic Susceptible–Exposed–Infectious–Recovered (SEIR) structure. Despite its simplicity, the SEIR structure with behavior (SEIRb) was shown to perform well in forecasting, especially compared to more complicated models. We contrast this model with an SEIR model that excludes endogenous incorporation of behavior. Both models assume permanent immunity to COVID-19, so we also consider a modification of the models which include waning immunity (SEIRS and SEIRSb). We perform equilibria, sensitivity, and identifiability analyses on all models and examine the fidelity of the models to replicate COVID-19 data across the United States. Endogenous incorporation of behavior significantly improves a model’s ability to produce realistic outbreaks. While the two endogenous models are similar with respect to identifiability and sensitivity, the SEIRSb model, with the more accurate assumption of the waning immunity, strengthens the initial SEIRb model by allowing for the existence of an endemic equilibrium, a realistic feature of COVID-19 dynamics. When fitting the model to data, we further consider the addition of simple seasonality affecting disease transmission to highlight the explanatory power of the models. 

   more » « less
3. Contact Tracing: A Low Cost Reconstruction Framework for Surface Contact Interpolation

   Lakshmipathy, A.; Bauer, D.; Pollard, N. (October 2021, Proceedings of the IEEERSJ International Conference on Intelligent Robots and Systems)

   null (Ed.)

   We present a novel, low cost framework for reconstructing surface contact movements during in-hand manipulations. Unlike many existing methods focused on hand pose tracking, ours models the behavior of contact patches, and by doing so is the first to obtain detailed contact tracking estimates for multi-contact manipulations. Our framework is highly accessible, requiring only low cost, readily available paint materials, a single RGBD camera, and a simple, deterministic interpolation algorithm. Despite its simplicity, we demonstrate the framework’s effectiveness over the course of several manipulations on three common household items. Finally, we demonstrate the use of a generated contact time series in manipulation learning for a simulated robot hand. 

   more » « less
4. Evolutionarily stable strategy analysis and its links to demography and genetics through invasion fitness

   https://doi.org/10.1098/rstb.2021.0496  

   Van Cleve, Jeremy (May 2023, Philosophical Transactions of the Royal Society B: Biological Sciences)

   Evolutionarily stable strategy (ESS) analysis pioneered by Maynard Smith and Price took off in part because it often does not require explicit assumptions about the genetics and demography of a population in contrast to population genetic models. Though this simplicity is useful, it obscures the degree to which ESS analysis applies to populations with more realistic genetics and demography: for example, how does ESS analysis handle complexities such as kin selection, group selection and variable environments when phenotypes are affected by multiple genes? In this paper, I review the history of the ESS concept and show how early uncertainty about the method lead to important mathematical theory linking ESS analysis to general population genetic models. I use this theory to emphasize the link between ESS analysis and the concept of invasion fitness . I give examples of how invasion fitness can measure kin selection, group selection and the evolution of linked modifier genes in response to variable environments. The ESSs in these examples depend crucially on demographic and genetic parameters, which highlights how ESS analysis will continue to be an important tool in understanding evolutionary patterns as new models address the increasing abundance of genetic and long-term demographic data in natural populations. This article is part of the theme issue ‘Half a century of evolutionary games: a synthesis of theory, application and future directions’. 

   more » « less
5. A New Theoretical Framework for Understanding Multiscale Atmospheric Predictability

   https://doi.org/10.1175/jas-d-19-0271.1  

   Sun, Y. Qiang; Zhang, Fuqing (May 2020, Journal of the Atmospheric Sciences)

   Here we present a new theoretical framework that connects the error growth behavior in numerical weather prediction (NWP) with the atmospheric kinetic energy spectrum. Building on previous studies, our newly proposed framework applies to the canonical observed atmospheric spectrum that has a -3 slope at synoptic scales and a -5/3 slope at smaller scales. Based on this realistic hybrid energy spectrum, our new experiment using hybrid numerical models provides reasonable estimations for the finite predictable ranges at different scales. We further derive an analytical equation that helps understand the error growth behavior. Despite its simplicity, this new analytical error growth equation is capable of capturing the results of previous comprehensive theoretical and observational studies of atmospheric predictability. The success of this new theoretical framework highlights the combined effects of quasi-two-dimensional dynamics at synoptic-scales (-3 slope) and three-dimensional turbulence-like small-scale chaotic flows (-5/3 slope) in dictating the error growth. It is proposed that this new framework could serve as a guide for understanding and estimating the predictability limit in the real world. 

   more » « less