Jeremy Schmit

@schmitbiophysics.bsky.social

Statistical mechanics & biophysics theorist. Emergent properties in biomolecules. Systems biology curious. Father, former athlete. Kansas State University Physics. Occasional appearance of Legos.

Physicist Leo Szilard, in a short science fiction story from 1948, describing how to retard science by making the funding application longer and harder than the proposed research - now called the ‘Szilard point’

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The US is funding fewer grants compared to the past. The money is given in one lump sum instead a yearly infusion from a multi-year funded grant. This leads to more competition, less $ and time to do research. Not a win-win situation. 🧪🎁🔗 www.nytimes.com/interactive/...

The U.S. Is Funding Fewer Grants in Every Area of Science and Medicine (Gift Article)

A quiet policy change means the government is making fewer bets on long-term science.

nytimes.com

"I, at any rate, am convinced that He is not playing at dice." Einstein sent a letter to Max Born #OTD in 1926, in which he gave his oft-quoted objection to the probabilistic interpretation of the wavefunction in quantum mechanics. 🧪 ⚛️ You may be surprised by where this is headed. (1/n)

pubs.aip.org

New publication! How to read the curves in biomolecular phase diagrams! A collaboration between the Schmit Group and Jonathon Ditlev, Les Loew, and @ani-chattaraj.bsky.social. 1/7 pubs.acs.org/doi/10.1021/...

Biomolecular Phase Boundaries are Described by a Solubility Product That Accounts for Variable Stoichiometry and Soluble Oligomers

The solubility product is a rigorous description of the phase boundary for salt precipitation and has previously been shown to qualitatively describe the condensation of biomolecules. Here we present a derivation of the solubility product showing that the solubility product is also a robust description of biomolecule phase boundaries if care is taken to account for soluble oligomers and variable composition within the dense phase. Our calculation describes equilibrium between unbound monomers, the dense phase, and an ensemble of oligomer complexes with significant finite-size contributions to their free energy. The biomolecule phase boundary very nearly resembles the power law predicted by the solubility product when plotted as a function of the monomer concentrations. However, this simple form is concealed by the presence of oligomers in the dilute phase. Accounting for the oligomer ensemble introduces complexities to the power law phase boundary including re-entrant behavior and large shifts for stoichiometrically matched molecules. We show that allowing variable stoichiometry in the dense phase expands the two phase region, which appears as curvature of the phase boundary on a double-logarithmic plot. Furthermore, this curvature can be used to predict variations in the dense phase composition at different points along the phase boundary. Finally, we show how the solubility product power law can be identified in experiments by using dilute phase dissociation constants to account for the oligomer ensemble.

pubs.acs.org

Excited to share our paper: “Historical and Experimental Evidence that Inherent Properties Are Overweighted in Early Scientific Explanation” I’m grateful to Zach Horne & my dear advisor @andreicimpian.bsky.social to let me be part of this project, it was a great experience! doi.org/10.1073/pnas...

Historical and experimental evidence that inherent properties are overweighted in early scientific explanation | PNAS

Scientific explanation is one of the most sophisticated forms of human reasoning. Nevertheless, here we hypothesize that scientific explanation is ...

doi.org

In lab’s #FIRSTPREPRINT, we present methods to measure nanometer-scale organization around & between specific proteins in condensates in live cells. We uncover unexpected heterogeneity for a liquid-like phase with local meshwork spanning 10-50nm, stemming from ribosome biogenesis in the nucleolus.

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bioRxiv Biophysics@biorxiv-biophys.bsky.social · last yr.

Nanometer condensate organization in live cells derived from partitioning measurements https://www.biorxiv.org/content/10.1101/2025.02.26.640428v1