UNIQUE: ultrasound non-destructive in-situ quantitative evaluation of stem cell spheroid deformability during differentiation into specific lineages

Abstract

Reliable assessment of 3D stem cell spheroid function and fate is crucial in regenerative medicine and cell therapy, where gene and protein analyses and mechanical probing are employed. However, current methods are often invasive and struggle with heterogeneity, frequently damaging spheroid integrity, which drives a need for non-destructive, label-free techniques to assess individual spheroids directly in their culture environment. Here, we present a label-free platform, UNIQUE (Ultrasound Non-destructive In-situ Quantitative Evaluation), for single-spheroid, in-situ quantification of stem cell spheroid deformability as a mechanical phenotype during differentiation into specific lineages. We established UNIQUE using focused ultrasound to non-invasively assess stem cell spheroid deformability under optimized conditions (3 MPa, 30% duty cycle, surface alignment). We measured changes in spheroid deformability in real time as they differentiated into specific lineages. We also achieved label-free classification of adipogenic spheroids using acoustic property-based spheroid trapping. Our UNIQUE solution provides a transformative framework for dynamic metabolic profiling and better-quality control in the manufacturing of stem cell spheroids.

Introduction

Regenerative medicine aims to restore damaged tissue structure and function through cell-based therapies. Among various stem cell sources, adipose-derived stem cells (ASCs) have attracted attention owing to their multipotency, self-renewal capacity, and relative ease of acquisition^1,2,3. Three-dimensional multicellular ASC spheroids have been shown to exhibit enhanced in vivo survival and functional efficacy compared with dissociated cells, positioning them as one of the most clinically relevant platforms for therapeutic applications^4,5,6,7.

Despite these advantages, ASC spheroids face several intrinsic limitations during cell isolation and spheroid fabrication. ASCs are derived from the stromal vascular fraction, which is inherently heterogeneous, and variability introduced during cell isolation and purification increases the risk of unintended differentiation^8,9,10. In addition, as spheroids increase in size, hypoxic and necrotic regions can form within their core, leading to substantial variability in cell viability, metabolic activity, and lineage commitment^4,11,12. Together, cellular heterogeneity and structural constraints contribute to pronounced spheroid-to-spheroid variability^13,14,15,16.

Such variability poses a major challenge for reproducible cell therapy manufacturing. For clinical translation, it is therefore essential to reliably maintain and quantitatively assess the metabolic state and functional properties of therapeutic spheroids during production^{7,15,16,17,18}. Conventional gene- and protein-based assays provide detailed molecular information but are inherently destructive and limited to endpoint analysis, requiring cell lysis and precluding repeated measurements on the same spheroid^19,20. As a result, continuous monitoring during culture and reuse of evaluated spheroids is not feasible.

To address these limitations, mechanical characterization techniques such as atomic force microscopy (AFM), micropipette aspiration, and optical or magnetic tweezers have been explored as non-destructive alternatives^4,19,21,22. Previous studies have shown that microstructural changes, including cytoskeletal remodeling at the intracellular level and cell–matrix interactions at the extracellular level, are reflected in the mechanical properties of cells^23,24,25,26. From this perspective, quantitative measurement of mechanical properties offers a label-free means to biophysically assess the state of living cells. However, existing mechanical approaches are largely restricted to single-cell analysis, are often limited to surface stiffness measurements, and typically require rigid immobilization. Moreover, most measurements are performed ex situ, making it difficult to continuously and directly assess intact spheroids under native culture conditions^{22,27,28,29,30,31,32}.

To fill these existing knowledge and methodological gaps, we propose an approach termed UNIQUE (Ultrasound Non-destructive In-situ Quantitative Evaluation of stem cell spheroid deformability). The proposed platform provides spatially confined acoustic pressure to spheroids using focused ultrasound (FUS) (Fig. 1a). This acoustic pressure generates radiation forces that induce deformation of the spheroids (Fig. 1b). The resulting deformation provides a quantitative measure of spheroid mechanical properties and can be obtained in a non-destructive manner without compromising structural integrity, enabling the individual assessment of heterogeneously fabricated spheroids to capture their intrinsic heterogeneity. In addition, acoustic potential energy enables selective trapping of spheroids based on differentiation-dependent changes in acoustic properties (Fig. 1c). The observed selective trapping of adipogenic spheroids likely reflects differentiation-related changes in acoustic properties associated with spheroid composition (Fig. 1d).

Fig. 1: UNIQUE platform-based cell evaluation process.

a FUS generates a spatially confined acoustic pressure field around the spheroids. b The acoustic radiation force acts on spheroids through scattering and absorption of ultrasound waves, which results in an expansion that can be measured to determine their deformability. c A potential energy well enables selective trapping and manipulation of particles at the focal point. d Acoustic properties-dependent trapping distinguishes adipogenic spheroids from skeletogenic spheroids. Adipogenic spheroids are pulled toward the focal point, whereas skeletogenic spheroids are repelled. e Sequential workflow of this study with UNIQUE. Spheroids are assessed in-situ within culture media, followed by dynamic monitoring of mechanical responses, label-free identification of differentiation states, and estimation of functional phenotypes

Using this platform, we establish a measurement sequence that integrates in-situ deformability assessment, continuous monitoring, and lineage-specific identification (Fig. 1e). The in-situ measurement enables real-time observation of spheroid mechanical responses within their native culture environment, while continuous monitoring allows dynamic tracking of mechanical and functional changes throughout differentiation. By correlating pre-differentiation mechanical properties with subsequent functional phenotypes, our results suggest that spheroid mechanics can serve as a quantitative indicator of cell fate potential. This work provides, to our knowledge, an initial demonstration of an acoustically driven biophysical framework for functional evaluation of individual ASC spheroids and may offer a foundation for real-time quality control and early fate prediction in regenerative cell manufacturing.

Results

Design and working principle of the UNIQUE platform

UNIQUE employs FUS to induce physical changes that can be directly observed under a microscope (Fig. S1a). To enable synchronized mechanical simulations and imaging, the platform integrates motorized stages to precisely align the acoustic focal plane and spheroids. UNIQUE is compatible with standard culture dishes and thus allows for non-destructive in-situ measurements within native culture environments.

The proposed platform was used for cell deformation and trapping. The deformation of the spheroids was primarily assessed using an inverted microscope in which changes in the projected cell area provided a quantitative measure of deformability (Fig. S1b). A digital microscope was used to visualize the compression along the z-axis. This microscope was installed to observe the area changes according to the location of the spheroids, and quantitative analysis was performed using an inverted microscope (Movie S1). The deformability was evaluated by calculating the change in the cross-sectional area of the spheroid, as described in Eq. (1)^33,34.

$$Deformability=\frac{{A}_{{initial}}-{A}_{{deformed}}}{{A}_{{initial}}}$$

(1)

Here, ${A}_{{initial}}$ and ${A}_{{deformed}}$ are cross-sectional areas of spheroid before and after ultrasound exposure. For each deformability measurement, the spheroid size was measured individually at the time of testing, and ${A}_{{initial}}$ was defined separately for each spheroid and each time point, rather than assumed to be constant over the differentiation period. UNIQUE also enables physical characterization of spheroids through cell manipulation (Fig. S1c). The spheroids can be trapped at the focal point using the appropriate acoustic parameters. This phenomenon is theoretically explained by Gor’kov potential (Eq. 2)³⁵, which models the action on small particles within an acoustic field as a function of potential energy.

$${\bf{U}}\left({\bf{r}}\right)=\frac{{\bf{4}}{{\bf{\pi a}}}^{{\bf{3}}}}{{\bf{3}}}\left[\frac{{\bf{1}}}{{\bf{2}}}{{\boldsymbol{f}}}_{{\boldsymbol{1}}}\left\langle {{\bf{p}}}^{{\bf{2}}}\left({\bf{r}}\right)\right\rangle -\frac{{\bf{4}}}{{\bf{3}}}{{\boldsymbol{f}}}_{{\boldsymbol{2}}}{{\boldsymbol{\rho }}}_{{\bf{0}}}\left\langle {{\boldsymbol{v}}}^{{\bf{2}}}\left({\bf{r}}\right)\right\rangle \right]$$

(2)

Here, ${\boldsymbol{a}}$ denotes the radius of the particle, ${\boldsymbol{p}}\left({\bf{r}}\right)$ is the acoustic pressure at position ${\bf{r}}$, ${\boldsymbol{v}}\left({\bf{r}}\right)$ is the velocity of the oscillating fluid particle in the surrounding medium induced by the acoustic field, ${{\boldsymbol{\rho }}}_{{\boldsymbol{0}}}$ is the density of the surrounding medium. The coefficients ${{\boldsymbol{f}}}_{{\boldsymbol{1}}}$ and ${{\boldsymbol{f}}}_{{\boldsymbol{2}}}$ are dimensionless contrast factors that represent the compressibility and density contrasts between the particle and the surrounding medium. These coefficients are defined as

$${f}_{1}=1-\frac{{\rho }_{0}{c}_{0}^{2}}{\rho {c}^{2}},\,{f}_{2}=\frac{2\left(\rho -{\rho }_{0}\right)}{2\rho +{\rho }_{0}}$$

(3)

where $\rho$ and $c$ are the density and speed of sound of the particle, and ${c}_{0}$ is the speed of sound of the surrounding medium³⁵. Physically, the Gor’kov potential describes particle migration along acoustic pressure gradients toward regions of minimum potential energy, which are governed by the impedance mismatch. Because acoustic impedances are defined as the product of the density and speed of sound, acoustic trapping in UNIQUE reflects changes in the effective acoustic impedance of spheroids associated with differentiation.

Acoustic parameters and geometric effects on spheroid deformability

We conducted finite element analysis (FEA) simulations to determine whether the radiation force of the FUS can induce deformation. Upon examining the effect of acoustic pressure and spheroid diameter on the deformability, we noted that the width of the ultrasound beam determines the response of spheroids of varying sizes. As expected, the deformability increased with increasing acoustic pressure, which reflects the quadratic dependence of the radiation force on pressure. This trend can be explained by the acoustic radiation force (${{\boldsymbol{F}}}_{{\boldsymbol{R}}}$), which increases proportionally with the square of the acoustic pressure (${p}^{2}$)³⁶. In this context, the deformation is governed by an absorption-induced axial radiation force associated with momentum transfer along the propagation direction, which can be obtained from momentum conservation as

$${{\bf{F}}}_{{\boldsymbol{R}}}=\frac{{\bf{1}}}{{\boldsymbol{c}}}{\int }_{{\bf{0}}}^{{{\boldsymbol{L}}}_{{\boldsymbol{eff}}}}{\bf{2}}\cdot {\boldsymbol{\alpha }}\cdot {\boldsymbol{I}}\left({\boldsymbol{z}}\right)\cdot {\boldsymbol{D}}{\boldsymbol{F}}\cdot {\boldsymbol{A}}\,{\boldsymbol{d}}{\boldsymbol{z}}\approx \frac{{\boldsymbol{\alpha }}\cdot {\boldsymbol{DF}}\cdot {{\boldsymbol{p}}}^{{\bf{2}}}\cdot {\boldsymbol{A}}\cdot {{\boldsymbol{L}}}_{{\boldsymbol{eff}}}}{{\boldsymbol{Z}}\cdot {\boldsymbol{c}}}$$

(4)

Here, $\alpha ,\,I,\,\mathrm{DF},\,A,\,Z,\,c$ and ${L}_{{eff}}$ denote the ultrasound absorption coefficient, acoustic intensity, directivity factor, beam cross-sectional area, acoustic impedance, sound speed in the medium, and the effective interaction length, respectively. In addition, simulations with spheroid diameters ranging from 200 to 350 µm showed that smaller spheroids experienced higher stress concentrations and consequently greater relative deformation (Fig. 2a, b). Although the larger spheroids experienced a greater total radiation force owing to their larger surface area, this force was distributed across a disproportionately larger volume. At 1.5 MPa, the 200 µm spheroid exhibited 0.60% deformability, whereas the 350-µm spheroid showed 0.23% deformability. Consequently, smaller spheroids exhibited greater relative deformation under the same acoustic pressure. Taking together, these results demonstrate the strong dependence of spheroid deformability on both the acoustic pressure and spheroid size, which underscores the combined importance of pressure scaling and geometric effects in determining mechanical responses.

Fig. 2: Analysis of spheroid deformability in relation to acoustic parameters and spheroid diameter.

a FEM simulations of acoustic radiation–induced deformation in spheroids with diameters of 350 μm and 200 μm. b Deformability of simulated and experimentally measured ASC spheroids, which indicates a nonlinear relationship between acoustic pressure and spheroid diameter. The measured spheroid deformability as a function of c acoustic pressure (0.9–3.0 MPa), d duty factor (10–70%), and e travel distance (−100 to +500 μm), grouped by spheroid diameter (201–250 μm, 251–300 μm, and 301–350 μm). Representative images of spheroid deformation under f 3.0 MPa acoustic pressure, 30% duty factor, and 0 μm travel distance, g 70% duty factor, 1.5 MPa acoustic pressure and 0 μm travel distance, and h 200 μm travel distance, 1.5 MPa acoustic pressure, and 30% duty factor. Blue and red outlines indicate spheroid boundaries before and during ultrasound exposure, respectively. In c–e, measurements were performed on spheroids derived from three independent donors, with n = 4 spheroids analyzed per donor (total n = 12). All bar graphs represent mean ± S.D. All scale bars indicate 100 μm

Subsequently, we investigated the effects of acoustic pressure, duty factor, and travel distance on spheroid deformability (Fig. 2c–e). Spheroids were grouped into three diameter ranges (201–250, 251–300, and 301–350 µm) to account for size dependence. At a fixed duty factor (30%) and travel distance (0 µm), increasing acoustic pressure (0.9–3.0 MPa) was associated with quadratically increasing deformability, which is consistent with simulation results (Fig. 2c, f). In contrast, increasing the duty factor at a constant acoustic pressure and travel distance (1.5 MPa and 0 µm) produced a linear increase in deformability, which reflects the direct proportionality between the duty factor and the time-averaged acoustic power (Fig. 2d, g). Subsequently, we evaluated the effect of the travel distance for a fixed acoustic pressure and duty factor at 1.5 MPa and 30%, respectively. The maximum deformation occurred when the ultrasound focal point was aligned with the top surface of the spheroids. The optimal distance scaled with the spheroid diameter, measuring 200, 300, and 400 µm for the smallest to largest groups, respectively (Fig. 2e, h). This result is explained by the strong acoustic radiation force generated at the interface between the spheroid and the surrounding medium, where the mismatch in acoustic impedance is most significant.

All subsequent experiments were therefore performed after aligning the focal point on the spheroid surface at a fixed acoustic pressure of 3.0 MPa and a duty factor of 30%. These parameters were chosen to ensure reliable detection while minimizing side effects, and the surface alignment was optimized to maximize the interface radiation forces.

Monitoring lineage-specific differentiation by deformability

ASC spheroids were induced to differentiate into adipogenic, chondrogenic, and osteogenic lineages, and undifferentiated ASCs were used as controls. The expression of two phenotypic markers was used to determine the lineage of the differentiation-induced spheroids (Fig. 3a). We evaluated the deformability of differentiating spheroids every two days using UNIQUE. Measurements were conducted for a duration of less than 1 s, not to compromise cell viability (Fig. S2). Over time, adipogenic spheroids showed higher deformability, whereas skeletogenic spheroids showed lower deformability (Fig. S3 and Movie S2).

Fig. 3: Monitoring of the differentiation profile based on spheroid deformability across adipogenic, chondrogenic, and osteogenic lineages.

a Differentiation status of spheroids into adipogenic, chondrogenic, and osteogenic lineages evaluated by immunofluorescence at differentiation culture periods (Control, days 7, 14, and 21). Correlation between deformability and gene expression fold change in b adipogenic, c chondrogenic, d and osteogenic lineages over 21 days. e Representative images of adipogenic spheroid deformability. Blue outlines and red areas indicate spheroid boundaries before and during ultrasound exposure, respectively. f Comparison of deformability across differentiation periods within each lineage. g Statistical comparison of deformability among lineages on days 5, 7, and 13. h Deformability of each lineage under different acoustic pressures on day 21. Origin-specific correlation between deformability and gene expression for fate estimation: i adipogenic, j chondrogenic, and k osteogenic spheroids differentiated for 21 days. In c–h, deformability measurements were performed using n = 10 spheroids per donor, with three independent donors (total n = 30). For gene expression analyses, the number of biological replicates was n = 3 per donor, and each measurement was performed with n = 3 technical replicates. In i–k, deformability measurements were performed using n = 10 spheroids per donor. All bar graphs represent mean ± S.D. All scale bars indicate 100 μm

Based on the lineage-specific deformability profiles, we classified the differentiation status of each spheroid while simultaneously monitoring temporal changes and assessing gene expression (Figs. 3b–e and S4a–c). The adipogenic spheroids exhibited an increase in deformability from 2% to 4% during the differentiation period (Fig. 3b, e). Deformability fluctuated without significant change during the first 7 days but showed a clear upward trend thereafter. The expression levels of LPL and PPAR-γ, key markers of adipogenesis, increased proportionally over time. In contrast, the skeletogenic spheroids showed different patterns. Chondrogenic spheroids displayed a decrease in deformability from 2% to 0.4% with a concurrent increase in ACAN and SOX9 expression (Fig. 3c). Osteogenic spheroids showed an initial reduction in deformability with little change thereafter, whereas the expression levels of RUNX2 and OSP increased (Fig. 3d). These results suggest that adipogenic differentiation is associated with increased deformability owing to lipid accumulation³⁷, whereas chondrogenic differentiation results in decreased deformability, which reflects ECM (extracellular matrix) deposition³⁸. Osteogenic spheroids showed little change in deformability despite increased expression of osteogenic markers. This weak correlation may be due to the differentiation stage, as RUNX2 and OSP are early markers of osteoprogenitor commitment rather than full maturation³⁹. The mechanical properties of osteogenic cells are primarily determined by matrix mineralization, which requires not only chemical induction but also a stiff microenvironment⁴⁰. Therefore, although osteogenic differentiation was initiated, the absence of mineralization was likely limited by detectable changes in deformability.

Next, the deformability trend was comparatively analyzed for each lineage (Fig. 3f). By day 7, adipogenic spheroids were distinguishable, and by day 13, chondrogenic spheroids were distinguishable (Fig. 3g). To further validate the ability of UNIQUE to distinguish the differentiation status, we analyzed deformability at varying acoustic pressures to evaluate the pressure-dependent mechanical responses of each lineage (Fig. 3h). The results showed that deformability increased with acoustic pressure; significant differences between lineages were observed at pressures of 1.8 MPa or higher after 14 days of differentiation. These findings indicate that the deformation rate serves as a mechanical phenotype for assessing the differentiation status and defines the optimal measurement conditions and pressure thresholds required for reliable lineage differentiation.

Donor-dependent initial deformability as a predictor of lineage maturation

We investigated the relationship between initial deformability and differentiation potential based on the deformability and gene expression in lineage-specific spheroids. The deformability of the ASC spheroids varied depending on their origin (Fig. S4d). The initial deformability measurements from three different donors were 1.0%, 1.8%, and 2.2%. Origin 1 exhibited the lowest deformability, followed by origins 2 and 3. After 21 days of cultivation, the deformability values decreased to 1.1%, 1.3%, and 1.6%, respectively, maintaining the order of origin. This trend suggests that spheroid deformability exhibits donor-dependent variability and maintains a proportional relationship throughout the culture period. Analysis of the relationship between deformability and gene expression revealed that the deformability of the control was correlated with the differentiation potential (Fig. 3i–k and Table S1).

In adipogenic differentiation-induction, expression of LPL and PPAR-γ showed strong positive correlations with deformability (R² = 0.999 and 0.952, respectively; Fig. 3i). Therefore, softer spheroids exhibited stronger adipogenic commitment. This result highlights deformability as a reliable predictor for early selection of adipogenic potential. During chondrogenic differentiation-induction, ACAN expression was positively correlated with deformability (R² = 0.511), whereas SOX9 expression was negatively correlated (R² = –0.873) (Fig. 3j). This pattern indicates that softer spheroids favor early chondrogenic commitment through SOX9 activation, whereas stiffer spheroids promote ECM accumulation and maturation, as reflected by the higher ACAN expression. This result indicated that spheroid mechanics influence the distinct stages of chondrogenic progression. During osteogenic differentiation-induction, OSP expression was positively correlated with deformability (R² = 0.523), whereas RUNX2 expression was negatively correlated (R² = –0.576) (Fig. 3k). These results suggest that stiffer spheroids favor early osteogenic commitment via RUNX2, whereas softer spheroids facilitate later maturation stages marked by OSP expression.

Collectively, these findings demonstrate that initial deformability is a stable, donor-dependent property that predicts lineage outcomes. Levels of adipogenic markers increased proportionally with deformability, which is indicative of enhanced adipogenesis in softer spheroids. In chondrogenic spheroids, the late marker ACAN was elevated in softer spheroids, whereas in osteogenic spheroids, OSP followed the same trend. Thus, greater deformability was associated with stronger terminal differentiation across all three lineages. These results establish that spheroid deformability is a consistent predictor of differentiation efficiency.

Selective trapping and mechanical characterization of differentiated spheroids

We next examined another feature of UNIQUE that assesses spheroid differentiation not only by deformability but also by acoustic trapping behavior. During adipogenic differentiation, lipid accumulation results in a negative Gor’kov potential and stable trapping at the focal region (Eq. (2)). To clarify the physical origin of this trapping behavior, we examined whether changes in sound speed contribute to the effective acoustic impedance (Fig. S5). Independent measurements revealed only minor variations in the speed of sound during adipogenic differentiation, indicating that its contribution is limited, likely due to concurrent changes in bulk modulus and density. Consistent with this observation, subsequent analyses consider density variations as a plausible contributor to the observed impedance contrast, under the assumption of minimal sound-speed variation.

Motivated by this interpretation, we first simulated selective trapping of adipogenic spheroids based on differentiation-induced changes (Fig. 4a). Trapping forces were varied by spheroid diameter, but the direction of the trapping force was not (Fig. 4b). This behavior arises from differentiation-induced changes in the acoustic property contrast between the spheroid and the surrounding medium. Consequently, adipogenic spheroids with acoustic properties consistent with a lower effective density than water were selectively trapped at the focal point, whereas skeletogenic spheroids with higher densities were repelled (Fig. 4c, d). The parameters used in the simulations are listed in Table S2. To validate these simulations, UNIQUE was used as an acoustic tweezer to trap spheroids from the control, adipogenic, chondrogenic, and osteogenic spheroids (Fig. S6). Consistent with the simulation results, only adipogenic spheroids were effectively trapped at the center of the FUS beam, whereas the others were repelled from the center. The effective trapping range of the UNIQUE platform was quantified by measuring the maximum initial radial offset from the beam center at which stable spheroid trapping could be maintained (Fig. S7)^41,42. Moreover, the adipogenic spheroids were stably manipulated in a two-dimensional x-y plane at the acoustic focal point (Fig. 4e, f). The deformability of the spheroids increased with increasing acoustic pressure while maintaining their trapped state (Fig. 5g, h, and Movie S3). This result demonstrates that UNIQUE can probe pressure-dependent mechanical responses without the loss of trapping stability.

Fig. 4: Spheroid trapping and simulation based on the mechanical properties of different lineages.

a Simulated selective trapping of adipogenic spheroids based on assumed density variations. b Trapping forces as a function of spheroid diameter. c Two-dimensional acoustic potential wells as a function of assumed spheroid density. d Three-dimensional acoustic potential wells as a function of assumed spheroid density. Two-dimensional manipulation of trapped adipogenic spheroids in the upward e and rightward f directions. g Deformation of adipogenic spheroids under increasing acoustic pressure and continuous trapping. h Progressive increase in deformability of adipogenic spheroids over time and under increased acoustic pressures. All scale bars indicate 200 μm

In conclusion, we successfully characterized the physical properties of spheroid differentiation-induction using the UNIQUE platform and demonstrated that deformability can be stable and selectively measured through acoustic trapping.

Discussion

To understand how UNIQUE detects differentiation, it is essential to consider how the mechanical properties reflect lineage commitment. UNIQUE monitors differentiation by detecting mechanical changes at both intracellular and multicellular levels^23,43. For instance, lipid accumulation during adipogenesis softens cells and spheroids, whereas ECM deposition during chondrogenesis increases stiffness. These physical changes are functionally linked to differentiation; softer cells often exhibit relaxed cytoskeletal tension and nuclear compliance, thus favoring adipogenic lineage commitment, whereas stiffer cells with higher cytoskeletal stress are associated with skeletogenic fates²⁴. Stem cell size, elasticity, and viscoelasticity correlate with lineage potential even before differentiation^23,43. Although UNIQUE focuses on stiffness, incorporating complementary markers from previous studies could help address the detection challenges in high-stiffness lineages such as osteogenesis. Despite these limitations in some lineages, UNIQUE remains a powerful and noninvasive tool for detecting integrated mechanical signatures across entire spheroids. However, interpretation of these mechanically defined phenotypes requires caution when they are probed using acoustic measurements. Although the speed of sound remained approximately constant during differentiation, this does not imply that the observed changes in deformability can be directly interpreted as density variations (Fig. S5). Rather, deformability reflects an integrated mechanical phenotype of multicellular spheroids, arising from collective changes in cellular mechanics, extracellular matrix remodeling, and cell–cell interactions.

When interpreting mechanically defined phenotypes using the UNIQUE platform, it is also important to consider the potential influence of ultrasound-based mechanical stimulation. Accordingly, the ultrasound exposure used in this study was deliberately limited in both duration and intensity. Nevertheless, to directly evaluate potential effects, we compared lineage-specific gene expression between spheroids exposed to ultrasound during deformability measurements and spheroids differentiated without ultrasound exposure (Fig. S8). No statistically significant differences were observed between the two groups, indicating that the ultrasound-based measurements employed here did not measurably perturb differentiation under the applied conditions. Nevertheless, sustained, repeated, or higher-intensity ultrasound exposure could, in principle, influence differentiation through mechanotransduction pathways, and thus careful parameter selection is required when extending this platform to other experimental regimes⁴⁴.

Within the defined operational boundaries, UNIQUE offers key advantages over current methods for real-time, non-destructive evaluation of 3D cellular states. Fluorescence-based live-cell imaging offers high resolution but is limited to shallow depths (<300 µm) and requires labeling, which hinders therapeutic use^45,46,47. Optical methods such as photoacoustic (PA) imaging and optical coherence tomography (OCT) are label-free but still shallow (<1 mm) and rely on predefined contrast mechanisms^48,49,50. In contrast, UNIQUE enables label-free, real-time monitoring by detecting mechanical changes throughout the entire spheroid without contrast limitations inherent to PA or OCT, thereby allowing measurement across any cell type and making UNIQUE a strong candidate for clinical translation.

Additionally, this approach is scalable across various cell types and biological states. It can distinguish epidermal lineages from dermal ones or track adipogenic commitment in metabolic disease models^51,52. It also detects functional changes, such as increased deformability in metastatic cancer cells or stiffness changes in response to drugs^{7,25,36,53,54,55,56}. Although it is limited to mechanical readouts, UNIQUE uniquely offers a beneficial assessment of cell state and function, which supports its use in regenerative medicine, disease modeling, and drug screening^19,57. In conclusion, UNIQUE has the potential to become a user-friendly, label-free platform that is suitable for real-time and non-destructive assessment of ASC spheroids. Our findings indicate that deformability is dependent on acoustic parameters and is correlated with lineage-specific differentiation. Initial deformability, influenced by donor origin, served as a predictor of differentiation outcomes, and acoustic trapping effectively distinguished adipogenic spheroids. Overall, these findings demonstrate that UNIQUE provides a versatile and dependable method for monitoring biomechanics directly at the site, thereby enhancing quality control in regenerative medicine and increasing its efficiency and accessibility.

Materials and methods

UNIQUE system

The deformability of ASC spheroids was measured using the UNIQUE system, which integrates a FUS transducer with an inverted microscope setup (Fig. S1). The ultrasound beam was generated by amplifying a sinusoidal signal from a function generator (SG382, Stanford Research Systems, USA) using a 50 dB power amplifier (525LA, Electronics & Innovation, Ltd., USA). The FUS transducer was mounted on a three-axis motorized linear stage (OSMS20-85, Sigma Koki Co., Ltd., Japan) and equipped with a goniometer to enable precise translational and angular alignment relative to the spheroids. Images were acquired using an inverted fluorescence microscope (IX-73, Olympus, USA) equipped with a CMOS camera (ORCA-Flash4.0 V3, Hamamatsu Photonics, Japan).

During each experiment, the transducer position was adjusted in the x, y, z, and θ directions such that the pulse–echo impulse response waveform and peak amplitude matched the reference impulse response corresponding to the calibrated focal position with the hydrophone (Fig. S9). This impulse-response-based alignment ensured that the spheroids were positioned within an acoustic field equivalent to the calibrated focal pressure, thereby enabling reproducible application of the defined acoustic pressure at the experimental working location. For each deformability measurement, ultrasound was applied as a single exposure with a duration of less than 1 s.

Fabrication of FUS transducer

A spherically focused single-element ultrasound transducer was fabricated using a 36° Y-cut lithium niobate (LiNbO₃) crystal (Boston Piezo Optics, USA) piezoelectric layer with deposited chrome/gold electrodes on both sides, a 2–3 μm silver-epoxy matching layer, and a backing layer (E-Solder 3022, VonRoll, USA) (Fig. S9a). The thickness of each layer was optimized via KLM model simulations (PiezoCAD, Sonic Concepts, USA), yielding optimal values of 12 μm (matching), 98 μm (piezoelectric), and 2000 μm (backing), with a 6 mm aperture. Acoustic layers were assembled in a brass housing with Epo-Tek 301 (Epoxy Technology, USA) epoxy and mechanically pressed onto a 9 mm steel ball (f-number: 0.75). The device was coated with Parylene C to ensure biocompatibility.

Characteristics of FUS

The transducer was characterized via pulse-echo testing using a pulser/receiver (DPR500, JSR Corporation, USA) and a quartz target. The measured center frequency was approximately 30.45 MHz, with a −6 dB fractional bandwidth of 41.8% (Fig. S9b). The beam profile was obtained using a 5-axis scanning system (IPB760, IMP Systems, South Korea) and a hydrophone (NH0040, Precision Acoustics, UK) (Fig. S9c–f). Pressure measurements were conducted at 30 MHz with a duty factor of 5% and a pulse repetition frequency of 1 kHz to ensure operation within the linear measurement range of the hydrophone. The hydrophone position was scanned along the X-, Y-, and Z-axes, while angular alignment of the transducer was adjusted along the θ_x-z and θ_y-z axes to achieve three-dimensional focal alignment (Fig. S9c).

Acoustic pressure was measured at the location of maximum pressure while incrementally increasing the applied input voltage. The hydrophone output voltage $v(t)$ was converted to acoustic pressure $p(t)$ using the manufacturer-provided frequency-dependent sensitivity according to:

$$p\left(t\right)=\frac{v(t)}{S({f}_{0})}$$

Where ${f}_{0}$ = 30 MHz. Within the linear operating range of the hydrophone, applied input voltages of 3.3, 3.96, 4.62, 5.28, 5.94, and 6.6 V corresponded to measured peak pressures of 0.29, 0.35, 0.41, 0.47, 0.52, and 0.59 MPa, respectively. Acoustic pressures at higher excitation levels were estimated by linear extrapolation based on the voltage–pressure relationship (Fig. S9d). Using this procedure, the lateral beam width and focal length were determined to be 60.4 µm and 278 µm, respectively, at the full width at half maximum (FWHM) (Fig. S9e, f). The calibrated acoustic pressure range used in the deformability experiments was 0.9–3.0 MPa.

ASC preparation

The International Federation for Adipose Therapeutics and Science (IFATS) and the International Society for Cellular Therapy (ISCT) have proposed a minimum of three criteria for defining ASCs: (1) adherence to plastic; (2) surface marker expression of CD73, CD90, and CD105, while lacking the expression of CD14, CD34, CD45, and HLA-DR; and (3) the ability of a tripotent lineage (adipogenic, chondrogenic, and osteogenic lineages)⁹. The ASCs used in this study met the eligibility requirements for this category (Fig. S10).

In this study, the ASCs from adipose tissue were isolated and expanded to meet these criteria. ASCs were extracted from three donor-originated adipose tissues obtained via liposuction or tissue excision, and human tissues were obtained from Seoul St. Mary’s Hospital. The adipose tissues were washed with phosphate-buffered saline (PBS) and digested with an equal volume of 0.1% collagenase for 30 min at 37 °C in an incubator to yield the SVF. The SVF was centrifuged three times at 1300 rpm for 3 min in Dulbecco’s Modified Eagle Medium (DMEM) containing 10% fetal bovine serum (FBS) and 1% antibiotic-antimycotic (AA) to obtain a high-density SVF pellet. The SVF was filtered through a 100 µm filter to remove undigested ECM, then cultured overnight in DMEM containing 10% FBS and 1% AA in a 37 °C, 5% CO₂ incubator. Unattached cells were washed three times with PBS, and adherent cells were cultured until sufficient expansion was achieved. To harvest the cells, the cells were washed once with PBS and then incubated with trypsin-EDTA for 5 min at 37 °C in a 5% CO₂ incubator to detach them from the culture dish. The cell suspension with trypsin-EDTA was immediately neutralized using a culture medium. The ASCs were then subcultured or cryopreserved for further experiments. All procedures involving human-derived adipose stem cells were approved by the Institutional Review Board (IRB) of the Catholic University of Korea (Approval No. KC23RISI0779).

Fluorescence-activated cell sorting (FACS) was performed to identify the ASCs. After sufficient expansion in growth culture media to passage 4, ASCs were trypsinized for harvesting, with 50,000 cells allocated per marker into individual immunotubes. The harvested cells were centrifuged at 1300 rpm for 3 min to form pellets and to remove the media. The antibodies diluted in Hank’s balanced salt solution (HBSS) were then added to each immunotube, and the cells were stained at 4 °C in the dark room for 30 min. After staining, the antibody solution was removed by centrifugation, and the cells were washed with HBSS before FACS analysis. Using a FACS machine (FACS Canto II; BD Biosciences, USA), an unstained control group was used to set gate 1, to ensure that gate 1 included over 90% of the total events. The expression levels of each marker were measured within this gate, and the results confirmed the identification of ASCs. The expression levels of CD73, CD90, and CD105 and the lack of expression of CD14, CD34, CD45, and HLA-DR confirmed the identity of the ASCs. The materials are listed in Table S3.

Differentiation induction

The ASCs were induced to differentiate into adipogenic, chondrogenic, and osteogenic lineages using differentiation induction media, which were the StemPro™ Chondrogenesis Differentiation Kit (A1007101, Gibco, USA), StemPro™ Adipogenesis Differentiation Kit (A1007001, Gibco, USA), and StemPro™ Osteogenesis Differentiation Kit (A1007201, Gibco, USA). ASCs with passage three were harvested and seeded onto culture dishes at the same seeding density as the proliferation cultures. After one day, the growth medium was replaced with differentiation induction medium, which was replaced daily.

Verification of tripotency

ASCs were evaluated using real-time quantitative polymerase chain reaction (RT-qPCR) assay to confirm their tripotency into three lineages. After three weeks of differentiation-induction, the ASCs were harvested for mRNA extraction. In the control group, ASCs were harvested after 2–3 days of proliferation. All extracted mRNA was stored at −20 °C before the RT-qPCR assay. The primers used were CEBP-alpha, PPAR-γ, SOX9, aggrecan (AGG), RUNX2, and Collagen type I alpha I (Table S4)^58,59,60. mRNA was extracted from each differentiation-induced ASC and control using Trizol reagent (Ambion, USA), and genomic DNA was removed using an RT-PCR amplification kit (Biofact, Seoul, Korea). cDNA was synthesized via reverse transcription, and the expression levels of the markers were detected using the RT-qPCR system (Light Cycler 480, Roche, Switzerland) and SYBR green I master reagent (Roche Diagnostics, Germany). The ΔCt values were calculated by comparing them to reference gene (GAPDH) levels, and each group’s relative gene expression levels were determined using the 2^−ΔΔCt method compared to the control group. In addition, an immunocytochemistry (ICC) was performed to visually observe the differentiation status depending on the culture period. Differentiation-induced and control ASC Spheroids were stained according to the manufacturer’s protocol. The antibodies used in this study are listed in Table S5. Images were acquired using a confocal microscope (LSM 900, Carl Zeiss, Germany). The acquired images were analyzed using software (ZEISS ZEN 3.8, Carl Zeiss, Germany) with z-stack images.

Spheroids fabrication

ASCs spheroids were fabricated in PDMS microwells (stemFIT 3D; Microfit, Korea)⁶¹. One million cells were seeded in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS) and 1% Antibiotic-Antimycotic solution. The ASCs were concentrated at the bottom by gravity and formed spheroids by adhering to each other during the first day. The process yielded a minimum of 150 μm and a maximum of 400 μm of ASC spheroids. The diameter of the spheroids was observed under a microscope, and particle analysis was performed using ImageJ software.

Measurement of speed of sound

During stem cell differentiation, mechanical properties and compressibility may change, which can affect the speed of sound through the relation ${\rm{c}}=\sqrt{1/(\rho \kappa )}=\sqrt{{\rm{K}}/\rho }$, where $\kappa$ denotes the bulk compressibility, and $K$ is the corresponding bulk modulus. To examine how speed of sound changes during adipogenic differentiation, ASC spheroids were prepared and differentiated under controlled conditions. The speed of sound within spheroids was measured using an ultrasound pulse–echo method (Fig. S5a). The arrival time of the maximum reflected acoustic signal from the upper spheroid surface was defined as ${t}_{1}$ (negative peak), and the arrival time of the subsequently reflected signal from the lower surface of the spheroid was defined as ${t}_{2}$ (positive peak). The time difference between these two signals, ${\Delta t=t}_{2}-{t}_{1}$, was taken to represent the round-trip travel time of the ultrasound pulse across the spheroid diameter d (Fig. S5b). Accordingly, the speed of sound c within the spheroid was calculated as $c=2d/\Delta t$.

Viability test

Cell viability was evaluated using a LIVE/DEAD assay (Invitrogen, Carlsbad, CA, USA) following ultrasound exposure. Spheroids were first transferred to 6-well plates containing 6 mL of serum-free DMEM per well and allowed to stabilize for 30 min at 37 °C under 5% CO₂. Control spheroids (no ultrasound exposure) and ultrasound-treated spheroids (3 MPa, 30% duty factor, travel distance 0 µm) were then incubated for an additional 30 or 60 min after ultrasound exposure prior to endpoint LIVE/DEAD staining. After incubation, spheroids were stained with LIVE/DEAD reagents at final concentrations of 2 µM Calcein-AM and EthD-1 for 15 min at 37 °C in the dark. The medium was gently removed, and spheroids were washed with PBS prior to imaging. Identical exposure times (500 ms) were applied for both the GFP channel (Calcein-AM) and the RFP channel (EthD-1).