TPP-Fabricated All-Fiber Nanoforce Sensor with Deep Learning Analysis Enables Ultrasensitive Cancer Cell Mechanophenotyping
Clinical Snapshot
PICO Framework
| P — Population | A549 and HepG2 cancer cell lines at different invasion stages, plus polydimethylsiloxane validation samples |
| I — Intervention | All-fiber nanoforce sensor (AFNS) with two-photon-polymerized microcantilever and EfficientNet-based force analysis |
| C — Comparator | Atomic force microscopy (AFM) as reference standard |
| O — Outcomes | Force resolution (0.41 nN), measurement accuracy (R² = 0.9999), Young's modulus quantification, cellular mechanophenotyping parameters |
Bottom Line
This technology validation study demonstrates an innovative all-fiber nanoforce sensor achieving exceptional analytical performance (0.41 nN resolution, R² = 0.9999 accuracy) for cellular mechanics measurements. The system successfully differentiated mechanophenotypes between A549 and HepG2 cancer cells at different invasion stages, with results comparable to atomic force microscopy. Key advantages include compact design, replaceable probes, and significantly lower cost than conventional platforms. While the analytical validation is rigorous, biological validation remains limited to two cell lines. The technology shows promise for routine cellular mechanics analysis in cancer research, potentially democratising access to quantitative mechanophenotyping. However, broader biological validation and long-term stability assessment are needed before widespread clinical research adoption. The compact, cost-effective design makes this particularly relevant for resource-constrained research environments, including emerging Australian cancer research programs seeking accessible alternatives to expensive AFM systems.
Key Findings
P Value: Not reported for statistical comparisons
Effect Size: Mean absolute error <0.2% for force measurements
Primary Outcome: Force resolution of 0.41 nN with measurement accuracy R² = 0.9999
Nnt Or Sensitivity: Force sensitivity: 0.41 nN resolution, stable over 100 repeated measurements
Confidence Interval: Not explicitly reported
Clinical Application
High feasibility for research applications; requires technical expertise in fiber optics and cell culture Relevant for Australian cancer research institutes and universities; could complement existing AFM facilities with more accessible, cost-effective cellular mechanics analysis Research laboratories conducting cellular mechanics studies, particularly cancer biology research
Abstract
Cellular mechanics provide sensitive, quantitative markers of cancer progression, yet routine nanoforce measurements remain constrained by the cost, footprint, and electromagnetic limitations of conventional platforms. Here we report an all-fiber nanoforce sensor (AFNS) that integrates a two-photon-polymerized (TPP) microcantilever on the end facet of a multimode fiber, establishing a compact and robust analytical strategy for ultrasensitive force measurements. The printed structure comprises a rigid base, a ∼2 μm-thick cantilever disk, and a probe tip. Finite-element analysis is employed to estimate the effective spring constant and to optimize mechanical compliance. Force-dependent multimode specklegrams are quantitatively decoded using an EfficientNet-based regression model, enabling highly accurate force readout (R2 = 0.9999; mean absolute error <0.2%). The sensor achieves a force resolution of 0.41 nN and maintains stable analytical performance over 100 repeated loading cycles, representing a rigorous repeatability assessment for this class of fiber-tip force sensors. The analytical capability of the AFNS is validated by quantifying the Young's modulus of polydimethylsiloxane and by mechanically phenotyping A549 and HepG2 cells at different invasion stages, showing strong agreement with atomic force microscopy. With low cost, replaceable probes, and a compact all-fiber configuration, this work provides a scalable analytical methodology for high-precision micro/nano-force characterization and quantitative cellular mechanics assays.
References
- 1.Xie, J., Li, S., Li, J., Fang, F., & Song, L. (2026). TPP-Fabricated All-Fiber Nanoforce Sensor with Deep Learning Analysis Enables Ultrasensitive Cancer Cell Mechanophenotyping. Analytical Chemistry. https://doi.org/10.1021/acs.analchem.6c00152
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