Alright, future engineers!
**Newton's 2nd Law:** F=ma. An object's acceleration is directly proportional to the net force & inversely to its mass. Ex: Pushing a 1kg object with 10N creates 10m/s^2 accel. Pro-Tip: F and 'a' are vectors – direction matters!
Cytokine-mediated communication is a central mechanism by which immune cells coordinate activation, differentiation and proliferation. While mechanistic reaction-diffusion models provide detailed descriptions of cytokine secretion and uptake at the cellular scale, their computational cost limits their applicability to large and densely packed cell populations. Previously employed approximations of cytokine diffusion fields rely on assumptions that neglect the influence of cellular geometry and volume exclusion. In this work, we study a macroscopic description of cytokine diffusion and reaction dynamics based on homogenization techniques, rigorously linking microscopic reaction-diffusion formulations to effective continuum models. The resulting homogenized equations replace discrete responder cells with a continuous density, while retaining essential features of cellular uptake and excluded-volume effects. Further, we show that in regimes with approximate radial symmetry, classical Yukawa-type solutions emerge as limiting cases of the homogenized model, provided appropriate correction factors are included. Overall, our approach allows efficient multiscale modeling of cytokine signaling in complex immune-cell environments. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, https://ror.org/018mejw64 Germany's Excellence Strategy
The metastatic process initiates with collective cell invasion into surrounding tissues and axillary nodes, and subsequent colonization at a distant site. Previously, we found collective invasion is augmented during the G2 cell cycle phase, facilitated through Aurora kinase A (AURKA)-mediated centrosome polarization in the leader cell. Here, we identify cell cycle-associated gene signatures as overrepresented in axilla and liver metastatic sites, with AURKA expression strongly correlated with breast cancer metastasis signatures, and pan-cancer patient survival. Then, we show GFP-AURKA expression endows breast epithelia cells with the ability to form metastatic outgrowths within immune-incompetent chicken embryos. Multi-parametric imaging of wound closure assays reveals phenotypes enabled by, and dependent upon AURKA expression. We discover leader cells express AURKA and acquire front-polarized centrosomes, which differentiates them from other cells in the migrating group. Ectopic expression of GFP-AURKA induces a leader cell phenotype. Conversely, inhibition of AURKA activity alters actin dynamics, promotes turnover of cell contacts, and reduces coordination within migrating groups. Specifically, AURKA interacts with the actin regulator EPLIN, and AURKA inhibition localizes EPLIN to lamellipodia and away from E-cadherin-positive contacts. Inhibiting these necessary roles for AURKA may provide a critical barrier against the metastatic spread of human breast carcinoma cells. ### Competing Interest Statement The authors have declared no competing interest. Canadian Institutes of Health Research, CIHR F-19 03865, TFRI PPG F22-00533, CIHR F22-03789, CIHR F24-00975
Deterministic many-body systems governed by simple interactions can self-organize into macroscopic patterns, and the determinants of long-time behavior are assumed to be encoded in the initial configuration. Here we show that predictability can instead be constructed dynamically rather than being accessible in the initial configuration. We study a generalized cellular automaton of secrete-and-sense cells that self-organizes from disorder into static configurations, rectilinear waves, or spiral waves. Although dynamics are deterministic, the final outcome cannot be reliably inferred from the initial state alone. Treating cell states as a discrete phase field, we uncover emergent topological modes - charged vortices connected by strings that form non-contractible loops. Tracking their dynamics reveals that predictive signatures of macroscopic fate appear only late in the trajectory: vortex annihilation becomes readable through loop loss, whereas vortex persistence remains unreadable until spiral waves form abruptly. These results show how predictability can be dynamically constructed in deterministic nonequilibrium systems.
An unbiased, quantitative view of biomolecules in a living cell is a prerequisite for accurate modeling approaches and informs our understanding of cellular metabolism at scale. In this work, we used the total protein approach (TPA), in which the total protein mass of a given proteomics sample is used as a calibrator for absolute protein quantification, to determine protein abundances during the Chlamydomonas reinhardtii diurnal cycle. We use external, independently measured quantitative markers (metals, pigments) to assess the absolute protein abundances in unlabeled whole cell extracts. We calculate protein abundances in fg / cell of 7322 Chlamydomonas proteins, 2266 of which were captured in every time point, including the major proteins involved in the light reactions, photoprotection, proteostasis and fatty acid metabolism during a cell cycle. As expected, Rubisco large and small subunits are present in a 1:1 stoichiometry, with the large subunit being the most abundant protein in our data set, averaging 5.05 x 106 molecules per cell, reflecting 2.7% of the total protein mass. We noticed that PSII is the most abundant complex involved in the light reactions with 2.08 x 106 complexes per cell. PSI averages 1.75 x 106 complexes per cell and cytochrome b6f averages 0.77 x 106 complexes per cell. The TPA is a robust tool to study proteome dynamics quantitatively, while avoiding artefacts due to biochemical fractionation. Our proteome data set with an unprecedented temporal resolution is a valuable resource to assess protein abundances during the cell cycle in the reference alga Chlamydomonas. ### Competing Interest Statement The authors have declared no competing interest. National Institutes of Health, https://ror.org/01cwqze88, GM42143 National Science Foundation, MCB-1712608 Department of Energy (DOE), Biological and Environmental Research (BER), DE-AC05-76RL01830
Epidermal Growth factor (EGF) signaling is associated with (oncogenic) proliferation. Conversely, EGF-family ligands are able to trigger a differentiation program in cultured cells, an effect attributed to ligand affinity and EGFR phosphorylation. How EGF/EGFR driven proliferation-differentiation dynamics underlie tissue self-renewal has not been addressed. We show that culturing mouse small intestinal organoids (mSIOs) without EGF enhanced EGFR expression and base phosphorylation while maintaining a balanced development of proliferative crypts and differentiated villi. Addition of EGF or EREG triggers receptor endocytosis, reducing cell-surface and expression levels. While EGF promoted crypt proliferation, EREG promoted both proliferation and villus differentiation compared to untreated controls. Removal or re-introduction of EGF or EREG proved sufficient to induce development comparable to constant presence of ligands over 96h. Sub-saturating concentrations of EGF led to increased villus differentiation, resembling EREG treatments, suggesting that control over EGFR endocytic cycle ultimately regulates the balance of proliferation and differentiation in mSIOs ### Competing Interest Statement The authors have declared no competing interest.
Notch-mediated lateral inhibition is a conserved patterning process that controls alternative cell fate decisions and produces regular cell fate patterns. Prevailing models posit that lateral inhibition singles-out cells from fields of initially equipotent cells by amplifying stochastic fluctuations of Notch or pre-existing fate biases. Here, we revisited the role of Notch in early Drosophila neurogenesis, studying the dynamics of Neuroblast specification by live imaging the transcription of two proneural genes, scute and lethal of scute. We found that proneural gene expression is biased spatially along the dorsal-ventral axis prior to germ band extension and that early proneural expression predicts Neuroblast fate acquisition. This indicated that Neuroblast specification is pre-patterned by positional cues. Additionally, positional cues appeared to instruct individual cells to delaminate in a correct stereotyped pattern in proneural mutant embryos. Finally, contrary to current models, Notch signaling, measured by E(spl)m8 expression, was not detectable within proneural clusters until after Neuroblasts had initiated delamination. This indicated that Notch functions to stabilize rather than initiate fate decisions. We therefore propose that positional cues, not Notch, single-out Neuroblasts during early Drosophila neurogenesis, challenging long-held assumptions about the role of Notch in Neuroblast selection. ### Competing Interest Statement The authors have declared no competing interest. Agence Nationale de la Recherche, ANR-10-LABX-0073 Fondation pour la Recherche Médicale, FRM-DEQ20180339219
Quantifying chromatin-state dynamics in living cells remains challenging, in part because most methods require fixation or cell lysis. Here, we benchmark and introduce three simple live-cell image-derived metrics computed from routine DNA staining - the coefficient of variation (CV), 1-Gini, and the Diffuse Signal Index (DSI), introduced here - as fixation-free readouts of chromatin state. Using HL60-derived neutrophils (dHL-60) undergoing NETosis as a model system with a pronounced compact-to-decompact chromatin transition, we show that all three metrics track progressive chromatin reorganization in live-cell trajectories, but differ markedly in sensitivity: DSI provides the strongest trajectory-level discrimination between NETing and non-NETing cells, followed by 1-Gini and CV. Comparison with Tn5-based chromatin accessibility measurements in fixed cells further shows that all three metrics correlate with chromatin accessibility, supporting their biological relevance. Together, our results provide a practical framework for extracting chromatin-state readouts from routine live-cell DNA staining and identify DSI as the most discriminative metric for tracking chromatin reorganization in this benchmark. ### Competing Interest Statement The authors have declared no competing interest. Chan Zuckerberg Biohub San Francisco, https://ror.org/00knt4f32 David and Lucile Packard Foundation, https://ror.org/032atxq54
kipriyanovich
Rxiv mechanobio