PRX Life

@AmitabhPiyush and @RParthasarathy7 at @PhysicsUo @uoregon are the authors of this new study.

A new quantitative framework can image and track #neutrophil and #macrophage dynamics in larval zebrafish, enabling scientists to decrypt the motility, behavior, and migration patterns of distinct cell populations in the vicinity of the gut. 🔗 go.aps.org/4sppGav

A new theory of rapid behavioral inferences enables observers to leverage statistical regularities under strong time constraints — and can be applied to improve escape performance and capture features of escape behavior in fruit flies. 🔗 go.aps.org/4siVFs8

The study was conducted by @ahmed_alharraq, Gayoung Choi, and ​​@shaevitz at @Princeton and Sujit S. Datta (@TheSquishyLab) at @Caltech.

Using a transparent soil mimic and the model bacterium #Ecoli, researchers characterized how soil texture affects bacterial motility across pore scales, finding bacteria shift from run-and-tumble behavior in large pores to frequent trapping in small ones. go.aps.org/4lJCCFG

Join APS TV Host Clara Nellist as she sits down with the editors of PRX Intelligence, a new @APSPhysics journal. Watch them introduce their vision for a publication dedicated to research at the intersection of physics, AI & machine learning. #APSSummit26 youtu.be/3UpwDhHLGRE

#ICYMI: A new paper applies an ensemble learning algorithm to interrogate the kinetic pathways that shape CRISPR cleavage efficiency. The findings could boost CRISPR’s accuracy and efficiency for sgRNA design and target site selection. Check it out: go.aps.org/4sluQUh

A maximum entropy model of peptidomes across different species shows that peptide distributions — from those of humans to those of tuberculosis — resemble each other quantitatively, with potential implications for human immunogenicity. Read more: go.aps.org/40tAuIl

Using reverse-time stochastic dynamics theory, a study identifies the underlying mechanism of cytokinesis — establishing reverse-time ensemble theory as a useful approach for understanding target state directed biological processes. 🔗 go.aps.org/3N2iNMC

Two scaling relations for low-dimensional slices of the phase boundary, derived from a multi-component Flory-Huggins model with many-body interactions, opens up a new path to quantitatively characterizing multicomponent phase-separating systems. 🔗 go.aps.org/405Ipew

A method to efficiently simulate conformational changes of mechanosensitive proteins subjected to different mechanical forces provides a way to study membrane protein dynamics and understand the gating mechanism of mechanosensitive ion channels. 🔗 go.aps.org/4kXPt6x

This study is part of the journal's collection on the physics of biomolecular condensates and was conducted by Marcel Ernst, Riccardo Rossetto, and David Zwicker at the Max Planck Institute for Dynamics and Self-Organization. See the full collection here: go.aps.org/3O4wcUB

This study introduces an extended coarsening model of chromosomal crossover placement — offering a coherent explanation of experimental data across mutants by incorporating material exchange between droplets, the synaptonemal complex, and the nucleoplasm. go.aps.org/414h2ln

This study was conducted by Josep-Maria Armengol-Collado, Leonardo Puggioni, Livio Nicola Carenza, and Luca Giomi at Leiden University.

Researchers analyze the interplay between mechanical activity, lateral adhesion, and hexatic order by developing a continuum model of epithelial layers — providing insights on the general principles governing pattern formation and stability. 📄 go.aps.org/4s2IaNJ

This study was conducted by Kengo Nishi, Christoph Schmidt, and colleagues at @DukeU and researchers at @UNC, @NIH_NINDS, and @RiceUniversity.

Using a new method to characterize the mechanical properties and driving forces of microtubules in living cells, this study finds that polyglutamylation increases microtubule stiffness, while tube-like mitochondria have a much lower bending stiffness. 🔗 go.aps.org/4rTJFh2

A #NeuralNetwork model of neurons with intrinsic plasticity captures how neuronal excitability is influenced by external inputs to the network via plasticity — elucidating how these inputs alter network firing-rate heterogeneity at the population scale. go.aps.org/4kI84U2

By combining large-scale simulations with mathematical analysis, a study uncovers potential mechanisms for the emergence of different synaptic structures in the developing visual pathway — providing insights on cortical synaptic structure development. 🔗 go.aps.org/4aoxRx3

Manuel Razo-Mejia and Dimitri A. Petrov at @Stanford and Madhav Mani at @NorthwesternU conducted the study, which is part of our collection on #AdaptationAndLearning: go.aps.org/49BVr7Y

A study details a data-driven implementation of Fisher's geometric model — providing an empirically grounded approach for understanding evolutionary dynamics using #DeepLearning methods. 🔗 go.aps.org/4rhKyPt