ReviewACS nano medicine2026
Micro/Nanorobots (MNRs) at the Intersection of Mechanobiology and Artificial Intelligence: An Emerging Frontier for Precision Nanomedicine.
Review in ACS nano medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Micro/nanorobots (MNRs) are emerging as active precision-nanomedicine platforms that convert physical energy into propulsion and localized cellular or tissue mechanotransduction. Yet, the ways in which MNR-mediated forces and flows reprogram cell behavior, activate mechanotransduction pathways, or drive tissue remodeling remain poorly understood. Unlike passive nanocarriers that rely on diffusion and vascular permeability, MNRs enable directional transport, barrier penetration, and spatiotemporal control. Beyond locomotion, propulsion-induced stresses act as mechanical cues that engage cellular mechanosensing pathways, including membrane-tension regulation, ion-channel activation, cytoskeletal remodeling, and downstream intracellular transcriptional signaling. Here, we review MNRs as mechanobiology-driven systems in which propulsion physics is intentionally coupled to force-sensitive biological responses. Rather than categorizing MNRs solely by actuation modality, we propose force-to-function coupling as a unifying design principle linking propulsion dynamics to defined mechanotransduction outcomes at the nano-bio interface. We further discuss how artificial intelligence (AI) introduces predictive modeling, imaging-guided feedback, and closed-loop optimization to achieve programmable biological outputs under physiological uncertainty. This review establishes a framework for biology-aware and intelligent MNRs by integrating propulsion engineering, mechanobiology, and computational control, and highlights key translational challenges that must be addressed to realize precision nanomedicine.
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What Socratic holds
Registered trials
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.