Evidence map›Paper›PMID 39226301›Full record

ArticleACS nano2024

Probing Nanotopography-Mediated Macrophage Polarization via Integrated Machine Learning and Combinatorial Biophysical Cue Mapping.

Yannan Hou, Brandon Conklin, Hye Kyu Choi, Letao Yang, Ki-Bum Lee

Abstract read
In one paragraph

Article in ACS nano, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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  10. The Rise of Mechanobiology for Advanced Cell Engineering and Manufacturing.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yannan HouDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.
Brandon ConklinDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-6834-3275
Hye Kyu ChoiDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.
Letao YangDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-0572-9787
Ki-Bum LeeDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-8164-0047

Funding

Targeting Cell-Type Specific Disease Phenotypes to Promote CNS RepairRM1NS133003 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI NAGI G AYAD, Jae K Lee · 2023 to 2026
$4.8M
Rutgers Optimizes Innovation (ROI) ProgramU01HL150852 · NHLBI · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI LIBUTTI, STEVEN K., PANETTIERI, REYNOLD ALEXANDER · 2019 to 2022
$4.4M
Machine learning-enabled Comparative Transcriptomic Profiling to Validate NanoScript-induced Inner Ear Hair CellsR01DC016612 · NIDCD · RUTGERS, THE STATE UNIV OF N.J. · PI KWAN, KELVIN Y., LEE, KIBUM · 2018 to 2022
$2.8M
Training in Translating Neuroscience to TherapiesT32NS115700 · NINDS · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI MOURADIAN, M. MARAL · 2021 to 2025
$1.4M
Injectable Hybrid SMART Spheroids to Enhance Stem Cell Therapy for CNS InjuriesR01NS130836 · NINDS · RUTGERS, THE STATE UNIV OF N.J. · PI Kibum Lee · 2023 to 2026
$1.3M
Investigating mitochondrial dysfunction in neurodegeneration using A Nanoparticle-based Synthetic Mitochondrial DNA (mtDNA) Transcription RegulatorR21NS132556 · NINDS · RUTGERS, THE STATE UNIV OF N.J. · PI LEE, KIBUM · 2023 to 2024
$390k
NHLBI NIH HHS U01 HL150852NIDCD NIH HHS R01 DC016612NINDS NIH HHS R01 NS130836NINDS NIH HHS R21 NS132556NINDS NIH HHS RM1 NS133003NINDS NIH HHS T32 NS115700
6 · The paper itself

Abstract

Inflammatory responses, leading to fibrosis and potential host rejection, significantly hinder the long-term success and widespread adoption of biomedical implants. The ability to control and investigated macrophage inflammatory responses at the implant-macrophage interface would be critical for reducing chronic inflammation and improving tissue integration. Nonetheless, the systematic investigation of how surface topography affects macrophage polarization is typically complicated by the restricted complexity of accessible nanostructures, difficulties in achieving exact control, and biased preselection of experimental parameters. In response to these problems, we developed a large-scale, high-content combinatorial biophysical cue (CBC) array for enabling high-throughput screening (HTS) of the effects of nanotopography on macrophage polarization and subsequent inflammatory processes. Our CBC array, created utilizing the dynamic laser interference lithography (DLIL) technology, contains over 1 million nanotopographies, ranging from nanolines and nanogrids to intricate hierarchical structures with dimensions ranging from 100 nm to several microns. Using machine learning (ML) based on the Gaussian process regression algorithm, we successfully identified certain topographical signals that either repress (pro-M2) or stimulate (pro-M1) macrophage polarization. The upscaling of these nanotopographies for further examination has shown mechanisms such as cytoskeletal remodeling and ROCK-dependent epigenetic activation to be critical to the mechanotransduction pathways regulating macrophage fate. Thus, we have also developed a platform combining advanced DLIL nanofabrication techniques, HTS, ML-driven prediction of nanobio interactions, and mechanotransduction pathway evaluation. In short, our developed platform technology not only improves our ability to investigate and understand nanotopography-regulated macrophage inflammatory responses but also holds great potential for guiding the design of nanostructured coatings for therapeutic biomaterials and biomedical implants.

Indexed as

Machine LearningMacrophagesAnimalsMiceNanostructuresRAW 264.7 CellsSurface Propertiescombinatorial biophysical cuesepigenetic modulationhigh-throughput screeningimmunomodulationmachine-learning-driven analysisnanotopography-mediated macrophage polarization

Identifiers

PMID39226301
PMCPMC13003755

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.