Sparse Polynomial Surrogates for F-Actin Networks with Compliant Crosslinkers

Sparse Polynomial Surrogates for F-Actin Networks with Compliant Crosslinkers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sparse Polynomial Surrogates for F-Actin Networks with Compliant Crosslinkers Luís Pacheco, Marco Parente, João Ferreira This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8315851/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Filamentous actin (F-actin) constitutes the primary contributor to cell elasticity and structural integrity, forming dynamic, crosslinked networks in the actin cortex. Existing mechanical models for F-actin and crosslinked filament networks successfully describe filament- and network-level behaviour, but are often limited in accounting for biological dynamic processes and inherentmaterial uncertainty and variability. We develop a stochastic modelling framework that integrates Polynomial Chaos Expansion (PCE) surrogates using the Finite Element Method (FEM). These surrogates replace filament-scale equations for compliant crosslinked F-actin networks, efficiently enabling uncertainty quantification and sensitivity analysis of key material parameters. First- and second-order statistical moments from the PCE are incorporated into a micro-sphere network model and implemented via a user-defined material subroutine Validation was performed against 10,000 Monte Carlo simulations (MCS) for each of four FEM test cases: three simple deformation modes applied to a unit length cubic element and a thin gel layer under shear mimicking a parallel plate rheology setup. In every test, the surrogate predicts the expected value of relevant stress quantities at maximum deformation with under 1% relative error versus the MCS reference. Moreover, the surrogate captures the network'svariability as measured by second order moments, demonstrating its ability to deliver rapid, statistically faithful predictions of both mean response and standard deviation in simple element tests and experimentally relevant rheology geometries. The proposed methodology seems to offer a scalable route for incorporating intrinsic material variabilityinto F-actin mechanical modelling, with implications for studying cell motility, division, and pathologies related to cytoskeletal remodelling. Actin networks Continuum mechanics Finite elements Sparse polynomial chaos expansions Uncertainty quantification Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 18 Jan, 2026 Reviews received at journal 15 Jan, 2026 Reviews received at journal 13 Jan, 2026 Reviews received at journal 09 Jan, 2026 Reviews received at journal 31 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 18 Dec, 2025 Reviewers agreed at journal 17 Dec, 2025 Reviewers agreed at journal 17 Dec, 2025 Reviewers invited by journal 17 Dec, 2025 Editor assigned by journal 12 Dec, 2025 Submission checks completed at journal 10 Dec, 2025 First submitted to journal 09 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8315851","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":562403793,"identity":"69a64768-5d59-464b-ae64-0476ef9496dc","order_by":0,"name":"Luís 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Existing mechanical models for F-actin and crosslinked filament networks successfully describe filament- and network-level behaviour, but are often limited in accounting for biological dynamic processes and inherentmaterial uncertainty and variability. We develop a stochastic modelling framework that integrates Polynomial Chaos Expansion (PCE) surrogates using the Finite Element Method (FEM). These surrogates replace filament-scale equations for compliant crosslinked F-actin networks, efficiently enabling uncertainty quantification and sensitivity analysis of key material parameters. First- and second-order statistical moments from the PCE are incorporated into a micro-sphere network model and implemented via a user-defined material subroutine Validation was performed against 10,000 Monte Carlo simulations (MCS) for each of four FEM test cases: three simple deformation modes applied to a unit length cubic element and a thin gel layer under shear mimicking a parallel plate rheology setup. In every test, the surrogate predicts the expected value of relevant stress quantities at maximum deformation with under 1% relative error versus the MCS reference. Moreover, the surrogate captures the network'svariability as measured by second order moments, demonstrating its ability to deliver rapid, statistically faithful predictions of both mean response and standard deviation in simple element tests and experimentally relevant rheology geometries. The proposed methodology seems to offer a scalable route for incorporating intrinsic material variabilityinto F-actin mechanical modelling, with implications for studying cell motility, division, and pathologies related to cytoskeletal remodelling.\u003c/p\u003e","manuscriptTitle":"Sparse Polynomial Surrogates for F-Actin Networks with Compliant Crosslinkers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-19 05:43:31","doi":"10.21203/rs.3.rs-8315851/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-18T12:54:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-15T10:16:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-13T10:37:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-09T12:04:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-31T21:14:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186563129872803378035777768214754829743","date":"2025-12-19T19:43:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316202434832993128403349368377327953733","date":"2025-12-19T15:08:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"144285810351532254493349050369601554466","date":"2025-12-18T12:55:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324778191642181548589253899216648948354","date":"2025-12-17T22:13:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28824983039573581805544822347027219148","date":"2025-12-17T11:24:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-17T10:12:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-12T09:55:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-11T03:42:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biomechanics and Modeling in Mechanobiology","date":"2025-12-09T09:29:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biomechanics-and-modeling-in-mechanobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmmb","sideBox":"Learn more about [Biomechanics and Modeling in Mechanobiology](http://link.springer.com/journal/10237)","snPcode":"10237","submissionUrl":"https://submission.nature.com/new-submission/10237/3","title":"Biomechanics and Modeling in Mechanobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"37b95c33-6ab3-4a56-b918-76d0806cad79","owner":[],"postedDate":"December 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T10:27:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-19 05:43:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8315851","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8315851","identity":"rs-8315851","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}