419 papers
Cell biology is the study of life at its most fundamental unit: the cell. This field explores how these microscopic building blocks function, communicate, and replicate to sustain living organisms, from the simplest bacteria to complex human tissues. By understanding the machinery inside a cell, scientists unlock secrets about growth, disease, and the very nature of existence itself.
At Gist.Science, we track every new preprint uploaded to bioRxiv within this dynamic category. Our team processes each submission to provide both accessible plain-language explanations and detailed technical summaries, ensuring you can grasp complex discoveries without getting lost in dense jargon. Below are the latest papers in cell biology, offering a fresh look at the inner workings of life as they are shared with the world.
By reconstituting centrosome duplication on synthetic beads in Drosophila embryos, this study demonstrates that a "Seed–Scaffold–Self-Assemble" mechanism allows simple molecular inputs to generate complex, self-duplicating organelles without requiring a pre-existing template.
This study identifies a distinct proteomic signature in mouse oocytes and cumulus cells that differentiates in vivo maturation from two in vitro maturation (IVM) models, revealing dysregulation in key pathways such as eukaryotic translation, autophagy, and endocytosis in oocytes and oxidative stress metabolism in cumulus cells, which underpins the reduced developmental competence observed in IVM-derived oocytes and offers targets for optimizing future IVM protocols.
This study presents a multi-omics-guided differentiation strategy that successfully enriches Parkinson's disease-vulnerable SOX6+ midbrain dopaminergic neurons, which, upon transplantation into hemiparkinsonian mice, restored motor function and established a foundation for precision disease modeling and targeted cell replacement therapies.
The paper introduces cloneXplorer, a high-throughput platform utilizing conical microwell arrays to monitor single-cell proliferation and cytokine secretion, enabling the efficient discovery, isolation, and expansion of rare antigen-specific T cells directly from peripheral blood.
This paper presents a novel likelihood-based framework that combines analytical modeling with neural network approximation of first-passage-time distributions to statistically identify and distinguish between bacterial cell division mechanisms (sizer vs. adder), demonstrating for the first time that these underlying control strategies are identifiable from lineage data.
This study reveals that inefficient autophagosome formation acts as a rate-limiting step in neuronal mitophagy, causing significantly slower clearance of damaged mitochondria compared to non-neuronal models and potentially contributing to neuronal vulnerability in neurodegenerative diseases.
This study demonstrates that coordinated chromosome motion during metaphase is an emergent mechanical property arising from the viscoelastic spindle environment, where microtubules and chromatin facilitate force transmission and tuning through stochastic mechanical coupling rather than direct regulatory signaling.
This paper introduces quantitative expansion microscopy (qExM), a cryo-fixed method that leverages molecular decrowding to accurately estimate endogenous protein abundance in situ, achieving a mean error of 9.4% in benchmarking nuclear pore complexes and enabling the quantification of mitochondrial respiratory chain complexes in diverse cellular contexts.
This paper introduces MorphoLearn, a morphology-driven AI framework that enables scalable and accurate 3D segmentation of diverse diatom ultrastructures from FIB-SEM data by optimizing lightweight neural networks, leveraging transfer learning, and employing boundary-aware strategies to overcome challenges posed by high morphological variability and limited annotations.