Frequency-dependent transition in power-law rheological behavior of living cells

Scaling-law mechanical marker for liver fibrosis diagnosis and drug screening through machine learning

Studies of cell and tissue mechanics have shown that significant changes in cell and tissue mechanics during lesions and cancers are observed, which provides new mechanical markers for disease diagnosis based on machine learning. However, due to the lack of effective mechanic markers, only elastic modulus and iconographic features are currently used as markers, which greatly limits the application of cell and tissue mechanics in disease diagnosis. Here, we develop a liver pathological state classifier through a support vector machine method, based on high dimensional viscoelastic mechanical data. Accurate diagnosis and grading of hepatic fibrosis facilitates early detection and treatment and may provide an assessment tool for drug development. To this end, we used the viscoelastic parameters obtained from the analysis of creep responses of liver tissues by a self-similar hierarchical model and built a liver state classifier based on machine learning. Using this classifier, we implemented a fast classification of healthy, diseased, and mesenchymal stem cells (MSCs)-treated fibrotic live tissues, and our results showed that the classification accuracy of healthy and diseased livers can reach 0.99, and the classification accuracy of the three liver tissues mixed also reached 0.82. Finally, we provide screening methods for markers in the context of massive data as well as high-dimensional viscoelastic variables based on feature ablation for drug development and accurate grading of liver fibrosis. We propose a novel classifier that uses the dynamical mechanical variables as input markers, which can identify healthy, diseased, and post-treatment liver tissues.

Beyond stiffness: Multiscale viscoelastic features as biomechanical markers for assessing cell types and states

Cell mechanics are pivotal in regulating cellular activities, diseases progression, and cancer development. However, the understanding of how cellular viscoelastic properties vary in physiological and pathological stimuli remains scarce. Here, we develop a hybrid self-similar hierarchical theory-microrheology approach to accurately and efficiently characterize cellular viscoelasticity. Focusing on two key cell types associated with livers fibrosis-the capillarized liver sinusoidal endothelial cells and activated hepatic stellate cells-we uncover a universal two-stage power-law rheology characterized by two distinct exponents, αshort and αlong. The mechanical profiles derived from both exponents exhibit significant potential for discriminating among diverse cells. This finding suggests a potential common dynamic creep characteristic across biological systems, extending our earlier observations in soft tissues. Using a tailored hierarchical model for cellular mechanical structures, we discern significant variations in the viscoelastic properties and their distribution profiles across different cell types and states from the cytoplasm (elastic stiffness E1 and viscosity η), to a single cytoskeleton fiber (elastic stiffness E2), and then to the cell level (transverse expansion stiffness E3). Importantly, we construct a logistic-regression-based machine-learning model using the dynamic parameters that outperforms conventional cell-stiffness-based classifiers in assessing cell states, achieving an area under the curve of 97% vs. 78%. Our findings not only advance a robust framework for monitoring intricate cell dynamics but also highlight the crucial role of cellular viscoelasticity in discerning cell states across a spectrum of liver diseases and prognosis, offering new avenues for developing diagnostic and therapeutic strategies based on cellular viscoelasticity.

Mechanical insights into jawbone characteristics under chronic kidney disease: A comprehensive nanoindentation approach

The mechanical properties of the jawbone play a critical role in determining the successful integration of dental prostheses. Chronic kidney disease (CKD) has been identified to abnormally accelerate bone turnover rates. However, the impact of CKD on the mechanical characteristics of the jawbone has not been extensively studied. This study sought to evaluate the time-dependent viscoelastic behaviors of rat jawbones, particularly in the scenarios both with and without CKD. We hypothesized that CKD might compromise the bone's innate toughening mechanisms, potentially owing to the time-dependent viscoelasticity of the bone matrix proteins. The maxillary and mandibular bones of Wistar rats were subjected to nanoindentation and Raman micro-spectroscopy. Load-hold-displacement curves from the cortical regions were obtained via nanoindentation and were mathematically characterized using a suitable viscoelastic constitutive model. Raman micro-spectroscopy was employed to identify nuanced vibrational changes in local molecular structures induced by CKD. The time course of indenter penetration onto cortical bones during the holding stage (creep behavior) can be mathematically represented by a series arrangement of the Kelvin-Voigt bodies. This configuration dictates the overall viscoelastic response observed during nanoindentation tests. The CKD model exhibited a reduced extent of viscoelastic contributions, especially during the initial ramp loading phase in both the maxillary and mandibular cortical bones. The generalized Kelvin-Voigt model comprises 2 K-Voigt elements that signify an immediate short retardation time (τ1) and a subsequent prolonged retardation time (τ2), respectively. Notably, the mandibular CKD model led to an increase in the delayed τ2 alongside an increase in non-enzymatic collagen cross-linking. These suggest that, over time, CKD diminishes the bone's capability for supplementary energy absorption and dimensional recovery, thus heightening their susceptibility to fractures.

Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics.

Anisotropic power-law viscoelasticity of living cells is dominated by cytoskeletal network structure

During physiological and pathological processes, cells experience significant morphological alterations with the re-arrangement of cytoskeletal filaments, resulting in anisotropic viscoelasticity. Here, a structure-based cell model is proposed to study the anisotropic viscoelastic mechanical behaviors of living cells. We investigate how cell shape affects its creep responses in longitudinal and perpendicular directions. It is shown that cells exhibit power-law rheological behavior in both longitudinal and perpendicular directions under step stress, with a more solid-like behavior along the longitudinal direction. We reveal that the cell volume and cytoskeletal filament orientation, which have been neglected in most existing models, play a critical role in regulating cellular anisotropic viscoelasticity. The stiffness of the cell in both directions increases linearly with increasing its aspect ratio, due to the decrease of cell volume. Moreover, the increase in the cell's aspect ratio produces the aggregation of cytoskeletal filaments along the longitudinal direction, resulting in higher stiffness in this direction. It is also shown that the increase in cell's aspect ratio corresponds to a process of cellular ordering, which can be quantitatively characterized by the orientational entropy of cytoskeletal filaments. In addition, we present a simple yet robust method to establish the relationship between cell's aspect ratio and cell volume, thus providing a theoretical framework to capture the anisotropic viscoelastic behavior of cells. This study suggests that the structure-based cell models may be further developed to investigate cellular rheological responses to external mechanical stimuli and may be extended to the tissue scale. STATEMENT OF SIGNIFICANCE: The viscoelastic behaviors of cells hold significant importance in comprehending the roles of mechanical forces in embryo development, invasion, and metastasis of cancer cells. Here, a structure-based cell model is proposed to study the anisotropic viscoelastic mechanical behaviors of living cells. Our study highlights the crucial role of previously neglected factors, such as cell volume and cytoskeletal filament orientation, in regulating cellular anisotropic viscoelasticity. We further propose an orientational entropy of cytoskeletal filaments to quantitatively characterize the ordering process of cells with increasing aspect ratios. Moreover, we derived the analytical interrelationships between cell aspect ratio, cell stiffness, cell volume, and cytoskeletal fiber orientation. This study provides a theoretical framework to describe the anisotropic viscoelastic mechanical behavior of cells.

Acoustic Wave-Induced Stroboscopic Optical Mechanotyping of Adherent Cells

In this study, a novel, high content technique using a cylindrical acoustic transducer, stroboscopic fast imaging, and homodyne detection to recover the mechanical properties (dynamic shear modulus) of living adherent cells at low ultrasonic frequencies is presented. By analyzing the micro-oscillations of cells, whole populations are simultaneously mechanotyped with sub-cellular resolution. The technique can be combined with standard fluorescence imaging allowing to further cross-correlate biological and mechanical information. The potential of the technique is demonstrated by mechanotyping co-cultures of different cell types with significantly different mechanical properties.

Topological mechanism in the nonlinear power-law relaxation of cell cortex

Different types of cells exhibit a universal power-law rheology, but the mechanism underneath is still unclear. Based on the exponential distribution of actin filament length, we treat the cell cortex as a collection of chains of crosslinkers with exponentially distributed binding energy, and show that the power-law exponent of its stress relaxation should scale with the chain length. Through this model, we are able to explain how the exponent can be regulated by the crosslinker number and imposed strain during cortex relaxation. Network statistics show that the average length of filament-crosslinker chains decreases with the crosslinker number, which endows a denser network with lower exponent. Due to gradual molecular alignment with the stretch direction, the number of effectively stretched crosslinkers in the network is found to increase with the imposed strain. This effective growth in network density diminishes the exponent under large strain. By incorporating the inclined angle of crosslinkers into the model without in-series structure, we show that the exponent cannot be altered by crosslinker rotation directly, refining our previous conjectures. This work may help to understand cellular mechanics from the molecular perspective.

E-cadherin adhesion dynamics as revealed by an accelerated force ramp are dependent upon the presence of α-catenin

Tissue remodeling and shape changes often rely on force-induced cell rearrangements occurring via cell-cell contact dynamics. Epithelial cell-cell contact shape changes are particularly dependent upon E-cadherin adhesion dynamics which are directly influenced by cell-generated and external forces. While both the mobility of E-cadherin adhesions and their adhesion strength have been reported before, it is not clear how these two aspects of E-cadherin adhesion dynamics are related. Here, using magnetic pulling cytometry, we applied an accelerated force ramp on the E-cadherin adhesion between an E-cadherin-coated magnetic microbead and an epithelial cell to ascertain this relationship. Our approach enables the determination of the adhesion strength and force-dependent mobility of individual adhesions, which revealed a direct correlation between these key characteristics. Since α-catenin has previously been reported to play a role in both E-cadherin mobility and adhesion strength when studied independently, we also probed epithelial cells in which α-catenin has been knocked out. We found that, in the absence of α-catenin, E-cadherin adhesions not only had lower adhesion strength, as expected, but were also more mobile. We observed that α-catenin was required for the recovery of strained cell-cell contacts and propose that the adhesion strength and force-dependent mobility of E-cadherin adhesions act in tandem to regulate cell-cell contact homeostasis. Our approach introduces a method which relates the force-dependent adhesion mobility to adhesion strength and highlights the morphological role played by α-catenin in E-cadherin adhesion dynamics.

Polymerization force-regulated actin filament-Arp2/3 complex interaction dominates self-adaptive cell migrations

Cells migrate by adapting their leading-edge behaviors to heterogeneous extracellular microenvironments (ECMs) during cancer invasions and immune responses. Yet it remains poorly understood how such complicated dynamic behaviors emerge from millisecond-scale assembling activities of protein molecules, which are hard to probe experimentally. To address this gap, we establish a spatiotemporal "resistance-adaptive propulsion" theory based on the interactions between Arp2/3 complexes and polymerizing actin filaments and a multiscale dynamic modeling system spanning from molecular proteins to the cell. We quantitatively find that cells can accurately self-adapt propulsive forces to overcome heterogeneous ECMs via a resistance-triggered positive feedback mechanism, dominated by polymerization-induced actin filament bending and the bending-regulated actin-Arp2/3 binding. However, for high resistance regions, resistance triggers a negative feedback, hindering branched filament assembly, which adapts cellular morphologies to circumnavigate the obstacles. Strikingly, the synergy of the two opposite feedbacks not only empowers the cell with both powerful and flexible migratory capabilities to deal with complex ECMs but also enables efficient utilization of intracellular proteins by the cell. In addition, we identify that the nature of cell migration velocity depending on ECM history stems from the inherent temporal hysteresis of cytoskeleton remodeling. We also show that directional cell migration is dictated by the competition between the local stiffness of ECMs and the local polymerizing rate of actin network caused by chemotactic cues. Our results reveal that it is the polymerization force-regulated actin filament-Arp2/3 complex binding interaction that dominates self-adaptive cell migrations in complex ECMs, and we provide a predictive theory and a spatiotemporal multiscale modeling system at the protein level.

Graphene quantum dot doped viscoelastic lyotropic liquid crystal nanocolloids for antibacterial applications

Graphene quantum dots (GQDs) are prepared and characterized via X-ray diffraction (XRD), UV-Visible spectroscopy, atomic force microscopy (AFM), transmission electron microscopy (TEM) and photoluminescence (PL). GQDs are doped (5 mg and 10 mg) in the lyotropic liquid crystalline (LLC) lamellar and hexagonal phases to prepare GQD/LLC nanocolloids. Polarizing optical microscopy and X-ray diffraction measurement reveals that GQDs do not affect the lamellar and hexagonal LLC structures and may organize on their interface. Pure LLC phases and nanocolloids are studied for steady and dynamic rheological behavior. LLC phases and GQD/LLC nanocolloids possess shear thinning and frequency dependent liquid viscoelastic behavior. A complex moduli study of LLCs and GQD/LLC nanocolloids is carried out which indicates the gel to viscous transition in LLCs and GQD/LLC nanocolloids as a function of frequency. LLC phases and GQD/LLC nanocolloids are tested for antibacterial activity against Listeria ivanovii. The effect of surfactant concentration, LLC phase geometry and GQD concentration has been studied and discussed. A probable mechanism for the strong antimicrobial activity of LLCs and GQD/LLC nanocolloids is presented considering intermolecular interactions. The viscoelastic behavior and strong antibacterial activity (inhibition zone 49.2 mm) of LLCs and GQD/LLC nanocolloids make them valuable candidates for lubrication, cleaning, cosmetics and pharmaceutical applications.

New Mechanical Markers for Tracking the Progression of Myocardial Infarction

The mechanical properties of soft tissues can often be strongly correlated with the progression of various diseases, such as myocardial infarction (MI). However, the dynamic mechanical properties of cardiac tissues during MI progression remain poorly understood. Herein, we investigate the rheological responses of cardiac tissues at different stages of MI (i.e., early-stage, mid-stage, and late-stage) with atomic force microscopy-based microrheology. Surprisingly, we discover that all cardiac tissues exhibit a universal two-stage power-law rheological behavior at different time scales. The experimentally found power-law exponents can capture an inconspicuous initial rheological change, making them particularly suitable as markers for early-stage MI diagnosis. We further develop a self-similar hierarchical model to characterize the progressive mechanical changes from subcellular to tissue scales. The theoretically calculated mechanical indexes are found to markedly vary among different stages of MI. These new mechanical markers are applicable for tracking the subtle changes of cardiac tissues during MI progression.

α-Catenin Dependent E-cadherin Adhesion Dynamics as Revealed by an Accelerated Force Ramp

Tissue remodeling and shape changes often rely on force-induced cell rearrangements occurring via cell-cell contact dynamics. Epithelial cell-cell contact shape changes are particularly dependent upon E-cadherin adhesion dynamics which are directly influenced by cell-generated and external forces. While both the mobility of E-cadherin adhesions and their adhesion strength have been reported before, it is not clear how these two aspects of E-cadherin adhesion dynamics are related. Here, using magnetic pulling cytometry, we applied an accelerated force ramp on the E-cadherin adhesion between an E-cadherin-coated magnetic microbead and an epithelial cell to ascertain this relationship. Our approach enables the determination of the adhesion strength and force-dependent mobility of individual adhesions, which revealed a direct correlation between these key characteristics. Since α-catenin has previously been reported to play a role in both E-cadherin mobility and adhesion strength when studied independently, we also probed epithelial cells in which α-catenin has been knocked out. We found that, in the absence of α-catenin, E-cadherin adhesions not only had lower adhesion strength, as expected, but were also more mobile. We observed that α-catenin was required for the recovery of strained cell-cell contacts and propose that the adhesion strength and force-dependent mobility of E-cadherin adhesions act in tandem to regulate cell-cell contact homeostasis. Our approach introduces a method which relates the force-dependent adhesion mobility to adhesion strength and highlights the morphological role played by α-catenin in E-cadherin adhesion dynamics.

Large Scale Zigzag Pattern Emerging from Circulating Active Shakers

We report the emergence of large zigzag bands in a population of reversibly actuated magnetic rotors that behave as active shakers, namely squirmers that shake the fluid around them without moving. The shakers collectively organize into dynamic structures displaying self-similar growth and generate topological defects in the form of cusps that connect vortices of rolling particles with alternating chirality. By combining experimental analysis with particle-based simulation, we show that the special flow field created by the shakers is the only ingredient needed to reproduce the observed spatiotemporal pattern. We unveil a self-organization scenario in a collection of driven particles in a viscoelastic medium emerging from the reduced particle degrees of freedom, as here the frozen orientational motion of the shakers.

Living cells as a biological analog of optical tweezers - a non-invasive microrheology approach

Microrheology, the study of fluids on micron length-scales, promises to reveal insights into cellular biology, including mechanical biomarkers of disease and the interplay between biomechanics and cellular function. Here a minimally-invasive passive microrheology technique is applied to individual living cells by chemically binding a bead to the surface of a cell, and observing the mean squared displacement of the bead at timescales ranging from milliseconds to 100s of seconds. Measurements are repeated over the course of hours, and presented alongside analysis to quantify changes in the cells' low-frequency elastic modulus, G0', and the cell's dynamics over the time window ∼10-2 s to 10 s. An analogy to optical trapping allows verification of the invariant viscosity of HeLa S3 cells under control conditions and after cytoskeletal disruption. Stiffening of the cell is observed during cytoskeletal rearrangement in the control case, and cell softening when the actin cytoskeleton is disrupted by Latrunculin B. These data correlate with conventional understanding that integrin binding and recruitment triggers cytoskeletal rearrangement. This is, to our knowledge, the first time that cell stiffening has been measured during focal adhesion maturation, and the longest time over which such stiffening has been quantified by any means. STATEMENT OF SIGNIFICANCE: Here, we present an approach for studying mechanical properties of live cells without applying external forces or inserting tracers. Regulation of cellular biomechanics is crucial to healthy cell function. For the first time in literature, we can non-invasively and passively quantify cell mechanics during interactions with functionalised surface. Our method can monitor the maturation of adhesion sites on the surface of individual live cells without disrupting the cell mechanics by applying forces to the cell. We observe a stiffening response in cells over tens of minutes after a bead chemically binds. This stiffening reduces the deformation rate of the cytoskeleton, although the internal force generation increases. Our method has potential for applications to study mechanics during cell-surface and cell-vesicle interactions.

Quantitative characterization of cell physiological state based on dynamical cell mechanics for drug efficacy indication

Cell mechanics is essential to cell development and function, and its dynamics evolution reflects the physiological state of cells. Here, we investigate the dynamical mechanical properties of single cells under various drug conditions, and present two mathematical approaches to quantitatively characterizing the cell physiological state. It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate, and can be mathematically characterized by a linear time-invariant dynamical model. It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions. Furthermore, it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties, and the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model. This study builds a relationship between the cellular mechanical properties and the cellular physiological state, adding information for evaluating drug efficacy.

Cytochalasin B Influences Cytoskeletal Organization and Osteogenic Potential of Human Wharton's Jelly Mesenchymal Stem Cells

Among perinatal stem cells of the umbilical cord, human Wharton's jelly mesenchymal stem cells (hWJ-MSCs) are of great interest for cell-based therapy approaches in regenerative medicine, showing some advantages over other MSCs. In fact, hWJ-MSCs, placed between embryonic and adult MSCs, are not tumorigenic and are harvested with few ethical concerns. Furthermore, these cells can be easily cultured in vitro, maintaining both stem properties and a high proliferative rate for several passages, as well as trilineage capacity of differentiation. Recently, it has been demonstrated that cytoskeletal organization influences stem cell biology. Among molecules able to modulate its dynamics, Cytochalasin B (CB), a cyto-permeable mycotoxin, influences actin microfilament polymerization, thus affecting several cell properties, such as the ability of MSCs to differentiate towards a specific commitment. Here, we investigated for the first time the effects of a 24 h-treatment with CB at different concentrations (0.1-3 μM) on hWJ-MSCs. CB influenced the cytoskeletal organization in a dose-dependent manner, inducing changes in cell number, proliferation, shape, and nanomechanical properties, thus promoting the osteogenic commitment of hWJ-MSCs, as confirmed by the expression analysis of osteogenic/autophagy markers.

Direct tool for quantitative analysis of cell/object dynamic behavior - metastasis and far beyond

INTRODUCTION

The dynamics and depth of invasion as well as the ability of cancer cells to penetrate the walls of  lymphatic or blood vessels represent critical survival-influencing factors in cancer patients. Depending on the cell type and tissue environment, cancer cell invasion differ in terms of motility mechanism and migration modes. Thus, there is the need of effective models allowing not only for single cell invasion potential assessment but also for collective migration and expansive growth evaluation in 3D microenvironment e.g. basement membranes. To meet this task, the specimens should be compared and analyzed in terms of the dynamics of movement and the evolution of the shape.

OBJECTIVES

Our main objective was development of the mathematical method that enables fast and credible calculation of parameters of shape and position, namely standard deviations (σ_X, σ_Y), centroid position (μ_X, μ_Y) and correlation coefficient ρ, based only on the contour of the aggregate.

METHODS

In order to accomplish this goal we measured geometrical properties of aggregates of RGM1 cells seeded in 3D Geltrex basement membrane. Referential microscopic images were taken 24 and 48 h after seeding and cell group dynamics was registered over 8 h periods using time lapse microscopy.

RESULTS

Based on gathered data, we managed to develop and fully test universal numerical tool allowing for estimation of statistical parameters of cell groups and aggregates which then allows for the precise evaluation of their behavior within microenvironment with time.

CONCLUSION

We conclude, that our tool is suitable for any research on the metastatic potential and motility of cancer cells in a given microenvironment, regardless of the migration mechanism, which together with the advanced analysis like cell single-cell transcriptomic, proteomic, and chromatin accessibility data may allow to identify precise targets for anti-cancer therapies, to predict the degree of malignancy of neoplastic lesions as well as it can be useful during architecting therapeutic strategies. Moreover, the developed tool seems to be broadly applicable for assessment of behavioural dynamics of any population.

Network dynamics of the nonlinear power-law relaxation of cell cortex

Living cells are known to exhibit universal power-law rheological behaviors, but their underlying biomechanical principles are still not fully understood. Here, we present a network dynamics picture to decipher the nonlinear power-law relaxation of cortical cytoskeleton. Under step strains, we present a scaling relation between instantaneous differential stiffness and external stress as a result of chain reorientation. Then, during the relaxation, we show how the scaling law theoretically originates from an exponential form of cortical disorder, with the scaling exponent decreased by the imposed strain or crosslinker density in the nonlinear regime. We attribute this exponent variation to the molecular realignment along the stretch direction or the transition of network structure from in-series to in-parallel modes, both solidifying the network toward our one-dimensional theoretical limit. In addition, the rebinding of crosslinkers is found to be crucial for moderating the relaxation speed under small strains. Together with the disorder nature, we demonstrate that the structural effects of networks provide a unified interpretation for the nonlinear power-law relaxation of cell cortex, and may help to understand cell mechanics from the molecular scale.

Mechanically robust bamboo node and its hierarchically fibrous structural design

Although short bamboo nodes function in mechanical support and fluid exchange for bamboo survival, their structures are not fully understood compared to unidirectional fibrous internodes. Here, we identify the spatial heterostructure of the bamboo node via multiscale imaging strategies and investigate its mechanical properties by multimodal mechanical tests. We find three kinds of hierarchical fiber reinforcement schemes that originate from the bamboo node, including spatially tightened interlocking, triaxial interconnected scaffolding and isotropic intertwining. These reinforcement schemes, built on porous vascular bundles, microfibers and more-refined twist-aligned nanofibers, govern the structural stability of the bamboo via hierarchical toughening. In addition, the spatial liquid transport associated with these multiscale fibers within the bamboo node is experimentally verified, which gives perceptible evidence for life-indispensable multidirectional fluid exchange. The functional integration of mechanical reinforcement and liquid transport reflects the fact that the bamboo node has opted for elaborate structural optimization rather than ingredient richness. This study will advance our understanding of biological materials and provide insight into the design of fiber-reinforced structures and biomass utilization.