329 papers
Biophysics sits at the fascinating intersection where the laws of physics meet the complexity of living systems. This field uses tools like light, electricity, and mechanical forces to decode how cells move, how proteins fold, and how our senses translate the world around us. Rather than just observing biology, biophysicists measure and model life to understand the fundamental machinery that powers every organism.
On Gist.Science, we make these discoveries accessible by curating the latest preprints directly from bioRxiv. Our team processes every new submission in this category, providing both clear, plain-language overviews and detailed technical summaries so readers of all backgrounds can grasp the cutting-edge science. Below are the most recent biophysics papers from bioRxiv, ready for you to explore.
This paper presents a minimal cell-based model demonstrating that active intermittent attachments drive the transition of cell populations into three-dimensional aggregates with emergent fluid-like properties, successfully explaining experimental observations of cancer cell dewetting, shape fluctuations, and collective chemotaxis.
Using macrophages as a model system, this study demonstrates that both Gβγ and Gαq independently recruit PLCβ enzymes to the plasma membrane to activate them, establishing that Gβγ alone is sufficient for PLCβ activation in specific endogenous signaling contexts.
This study utilized OpenSim inverse dynamics and static optimization on data from 16 cyclists to characterize substantial inter-subject variability in knee joint moments and reaction forces, highlighting the critical roles of specific muscle groups and supporting the need for personalized training and rehabilitation strategies in cycling.
Using cryo-electron microscopy, this study reveals that the mammalian egg's cytoplasmic lattice is a highly structured reservoir that sequesters maternal-effect proteins, ubiquitination machinery, and GTP-bound tubulin in inactive states to prime the egg for protein degradation and cytoskeletal remodeling during early development.
This study presents an in-silico pipeline combining deep learning and biophysical modeling to discover short, water-soluble, and highly specific plastic-binding peptides for effective microplastic remediation.
This study develops and evaluates nine Detectron2 and six YOLO v10 deep-learning models for real-time, single-class detection of amoebae in phase-contrast microscopic images, utilizing a diverse dataset of 88 images and 4,131 annotations to balance speed and accuracy for automated bio-imaging analysis.
This study utilizes two-dimensional replica-exchange molecular dynamics to map the detailed binding pathway of the Abl kinase substrate Abltide, revealing specific encounter regions, intermediate states, and key electrostatic/hydrophobic interactions that guide the peptide from initial encounter to its bound pose, thereby offering mechanistic insights for the rational design of peptide-based kinase inhibitors.
This study reveals that natural non-coding RNA Boltzmann ensembles largely occupy the same morphospace as random RNA, suggesting that the biophysics of the genotype-phenotype map primarily determines their structural properties rather than evolutionary selection.
This paper challenges the validity of recent claims regarding extracranial ultraweak photon emission as a non-invasive brain biomarker by demonstrating that reported signals are likely dominated by background light and scalp emission rather than genuine brain activity due to experimental flaws and tissue attenuation.
This study reveals that sodium ions regulate dopamine D2 receptor activation by remodeling allosteric coupling networks and disrupting a critical internal water column, thereby stabilizing the inactive state through newly identified binding sites and altered hydration patterns.