Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data.

Despite the remarkable advances in cancer diagnosis, treatment, and management over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by personalizing the delivery of therapies according to the predicted response for each individual patient. The design of personalized therapies requires the integration of patient-specific information with an appropriate mathematical model of tumor response. A fundamental barrier to realizing this paradigm is the current lack of a rigorous yet practical mathematical theory of tumor initiation, development, invasion, and response to therapy. We begin this review with an overview of different approaches to modeling tumor growth and treatment, including mechanistic as well as data-driven models based on big data and artificial intelligence. We then present illustrative examples of mathematical models manifesting their utility and discuss the limitations of stand-alone mechanistic and data-driven models. We then discuss the potential of mechanistic models for not only predicting but also optimizing response to therapy on a patient-specific basis. We describe current efforts and future possibilities to integrate mechanistic and data-driven models. We conclude by proposing five fundamental challenges that must be addressed to fully realize personalized care for cancer patients driven by computational models.

Rose Bengal Labeled Bovine Serum Albumin for Protein Transport Imaging in Subcutaneous Tissues Using Computed Tomography and Fluorescence Microscopy.

Subcutaneous (SC) injection of protein-based therapeutics is a convenient and clinically established drug delivery method. However, progress is needed to increase the bioavailability. Transport of low molecular weight (Mw) biotherapeutics such as insulin and small molecule contrast agents such as lipiodol has been studied using X-ray computed tomography (CT). This analysis, however, does not translate to the investigation of higher Mw therapeutics, such as monoclonal antibodies (mAbs), due to differences in molecular and formulation properties. In this study, an iodinated fluorescein analog rose bengal (RB) was used as a radiopaque and fluorescent label to track the distribution of bovine serum albumin (BSA) compared against unconjugated RB and sodium iodide (NaI) via CT and confocal microscopy following injection into ex vivo porcine SC tissue. Importantly, the high concentration BSA-RB exhibited viscosities more like that of viscous biologics than the small molecule contrast agents, suggesting that the labeled protein may serve as a more suitable formulation for the investigation of injection plumes. Three-dimensional (3D) renderings of the injection plumes showed that the BSA-RB distribution was markedly different from unconjugated RB and NaI, indicating the need for direct visualization of large protein therapeutics using conjugated tags rather than using small molecule tracers. Whereas this proof-of-concept study shows the novel use of RB as a label for tracking BSA distribution, our experimental approach may be applied to high Mw biologics, including mAbs. These studies could provide crucial information about diffusion in SC tissue and the influence of injection parameters on distribution, transport, and downstream bioavailability.

Geometry of adipocyte packing in subcutaneous tissue contributes to nonlinear tissue properties captured through a Gaussian process surrogate model.

Subcutaneous tissue mechanical response is governed by the geometry and mechanical properties at the microscale and drives physiological and clinical processes such as drug delivery. Even though adipocyte packing is known to change with age, disease, and from one individual to another, the link between the geometry of the packing and the overall mechanical response of adipose tissue remains poorly understood. Here we create 1200 periodic representative volume elements (RVEs) that sample the possible space of Laguerre packings describing adipose tissue. RVE mechanics are modeled under tri-axial loading. Equilibrium configuration of RVEs is solved by minimizing an energetic potential that includes volume change contributions from adipocyte expansion, and area change contributions from collagen foam stretching. The resulting mechanical response across all RVE samples is interpolated with the aid of a Gaussian process (GP), revealing how the microscale geometry dictates the overall RVE mechanics. For example, increase in adipocyte size and increase in sphericity lead to adipose tissue softening. We showcase the use of the homogenized model in finite element simulations of drug injection by implementing a Blatz-Ko model, informed by the GP, as a custom material in the popular open-source package FEBio. These simulations show how microscale geometry can lead to vastly different injection dynamics even if the constituent parameters are held constant, highlighting the importance of characterizing individual's adipose tissue structure in the development of personalized therapies.

Interpenetrating Networks of Collagen and Hyaluronic Acid That Serve as In Vitro Tissue Models for Assessing Macromolecular Transport.

High-fidelity preclinical in vitro tissue models can reduce the failure rate of drugs entering clinical trials. Collagen and hyaluronic acid (HA) are major components of the extracellular matrix of many native tissues and affect therapeutic macromolecule diffusion and recovery through tissues. Although collagen and HA are commonly used in tissue engineering, the physical and mechanical properties of these materials are variable and depend highly on processing conditions. In this study, HA was chemically modified and crosslinked via hydrazone bonds to form interpenetrating networks of crosslinked HA (HAX) with collagen (Col). These networks enabled a wide range of mechanical properties, including stiffness and swellability, and microstructures, such as pore morphology and size, that can better recapitulate diverse tissues. We utilized these interpenetrating ColHAX hydrogels as in vitro tissue models to examine macromolecular transport and recovery for early-stage drug screening. Hydrogel formulations with varying collagen and HAX concentrations imparted different gel properties based on the ratio of collagen to HAX. These gels were stable and swelled up to 170% of their original mass, and the storage moduli of the ColHAX gels increased over an order of magnitude by increasing collagen and HA concentration. Interestingly, when HAX concentration was constant and collagen concentration increased, both the pore size and spatial colocalization of collagen and HA increased. HA in the system dominated the ζ-potentials of the gels. The hydrogel and macromolecule properties impacted the mass transport and recovery of lysozyme, ß-lactoglobulin, and bovine serum albumin (BSA) from the ColHAX gels─large molecules were largely impacted by mesh size, whereas small molecules were influenced primarily by electrostatic forces. Overall, the tunable properties demonstrated by the ColHAX hydrogels can be used to mimic different tissues for early-stage assays to understand drug transport and its relationship to matrix properties.

Transcriptomic alterations in hypertrophy of the ligamentum flavum: interactions of Rho GTPases, RTK, PIK3, and FGF.

PURPOSE: To analyze the differential transcriptome expression in hypertrophic ligaments flavum (HLF) compared to normal ligaments. METHODS: A case-control study was conducted that included 15 patients with hypertrophy of LF and 15 controls. Samples of LF were obtained through a lumbar laminectomy and analyzed by DNA microarrays and histology. The dysregulated biological processes, signaling pathways, and pathological markers in the HLF were identified using bioinformatics tools. RESULTS: The HLF had notable histological alterations, including hyalinosis, leukocyte infiltration, and disarrangement of collagen fibers. Transcriptomic analysis showed that up-regulated genes were associated with the signaling pathways of Rho GTPases, receptor tyrosine kinases (RTK), fibroblast growth factors (FGF), WNT, vascular endothelial growth factor, phosphoinositide 3-kinase (PIK3), mitogen-activated protein kinases, and immune system. The genes PIK3R1, RHOA, RPS27A, CDC42, VAV1, and FGF5, 9, 18, and 19 were highlighted as crucial markers in HLF. The down-expressed genes in the HLF had associations with the metabolism of RNA and proteins. CONCLUSION: Our results suggest that abnormal processes in hypertrophied LF are mediated by the interaction of the Rho GTPase, RTK, and PI3K pathways, which have not been previously described in the HLF, but for which there are currently therapeutic proposals. More studies are required to confirm the therapeutic potential of the pathways and mediators described in our results.

High-Throughput Magnetic Actuation Platform for Evaluating the Effect of Mechanical Force on 3D Tumor Microenvironment.

Accurately replicating and analyzing cellular responses to mechanical cues is vital for exploring metastatic disease progression. However, many of the existing in vitro platforms for applying mechanical stimulation seed cells on synthetic substrates. To better recapitulate physiological conditions, a novel actuating platform is developed with the ability to apply tensile strain on cells at various amplitudes and frequencies in a high-throughput multi-well culture plate using a physiologically-relevant substrate. Suspending fibrillar fibronectin across the body of the magnetic actuator provides a matrix representative of early metastasis for 3D cell culture that is not reliant on a synthetic substrate. This platform enables the culturing and analysis of various cell types in an environment that mimics the dynamic stretching of lung tissue during normal respiration. Metabolic activity, YAP activation, and morphology of breast cancer cells are analyzed within one week of cyclic stretching or static culture. Further, matrix degradation is significantly reduced in breast cancer cell lines with metastatic potential after actuation. These new findings demonstrate a clear suppressive cellular response due to cyclic stretching that has implications for a mechanical role in the dormancy and reactivation of disseminated breast cancer cells to macrometastases.

Collagen- and hyaluronic acid-based hydrogels and their biomedical applications.

Hydrogels have been widely investigated in biomedical fields due to their similar physical and biochemical properties to the extracellular matrix (ECM). Collagen and hyaluronic acid (HA) are the main components of the ECM in many tissues. As a result, hydrogels prepared from collagen and HA hold inherent advantages in mimicking the structure and function of the native ECM. Numerous studies have focused on the development of collagen and HA hydrogels and their biomedical applications. In this extensive review, we provide a summary and analysis of the sources, features, and modifications of collagen and HA. Specifically, we highlight the fabrication, properties, and potential biomedical applications as well as promising commercialization of hydrogels based on these two natural polymers.

Backbone-Degradable Polymers Prepared by Chemical Vapor Deposition.

Polymers prepared by chemical vapor deposition (CVD) polymerization have found broad acceptance in research and industrial applications. However, their intrinsic lack of degradability has limited wider applicability in many areas, such as biomedical devices or regenerative medicine. Herein, we demonstrate, for the first time, a backbone-degradable polymer directly synthesized via CVD. The CVD co-polymerization of [2.2]para-cyclophanes with cyclic ketene acetals, specifically 5,6-benzo-2-methylene-1,3-dioxepane (BMDO), results in well-defined, hydrolytically degradable polymers, as confirmed by FTIR spectroscopy and ellipsometry. The degradation kinetics are dependent on the ratio of ketene acetals to [2.2]para-cyclophanes as well as the hydrophobicity of the films. These coatings address an unmet need in the biomedical polymer field, as they provide access to a wide range of reactive polymer coatings that combine interfacial multifunctionality with degradability.

Nanobubble ultrasound contrast agents for enhanced delivery of thermal sensitizer to tumors undergoing radiofrequency ablation.

PURPOSE: Pluronic has been shown to sensitize various tumor cell lines to chemotherapy and hyperthermia by altering the membrane fluidity, depleting ATP, and modulating the heat shock protein 70 expression. In our prior work, Pluronic was also used to formulate nanosized ultrasound contrast agents. In the current study we evaluate the use of these contrast agents as vehicles for image-guided delivery of Pluronic to improve outcomes of tumor radiofrequency (RF) ablation. METHODS: Lipid-shelled Pluronic nanobubbles were prepared and examined for size distribution, zeta potential, stability, biodistribution, accumulation of nanobubbles in the tumor, and treatment efficacy. LS174-T xenograft tumor-bearing mice were used to evaluate tumor growth suppression and measure treatment efficacy after RF ablation. RESULTS: The average diameter of Pluronic bubbles was 230 nm, and initial bubble echogenicity was 16 dB. In vitro, cells exposed to Pluronic nanobubbles exhibited low cytotoxicity in the absence of ultrasound, even if heat (43 ºC) was applied. When the cells were exposed to Pluronic nanobubbles, heat, and ultrasound; viability was significantly reduced. In vivo, tumors treated with ultrasound-modulated nanobubbles prior to RF ablation showed a significant reduction in growth compared to the RF alone (P<0.05). CONCLUSION: Lipid and Pluronic-shelled, echogenic nanobubbles combined with ultrasound modulation can serve as an effective theranostic method for sensitization of tumors to RF ablation.

Multidimensional opioid abuse deterrence using a nanoparticle-polymer hybrid formulation.

Misuse of prescription opioid drugs is the leading cause of the opioid crisis and overdose-related death. Abuse deterrent formulations (ADFs) have been developed to discourage attempts to tamper with the formulation and alter the ingestion methods. However, abusers develop complex extraction strategies to circumvent the ADF technologies. For comprehensive deterrence of drug abuse, we develop tannic acid nanoparticles (NPs) that protect encapsulated opioids from solvent extraction and thermal challenge (crisping), complementing the existing formulation strategy to deter injection abuse. Here, we develop a hybrid ADF tablet (NP-Tab), consisting of iron-crosslinked tannic acid NPs encapsulating thebaine (model opioid compound), xanthan gum, and chitosan (gel-forming polymers), and evaluate its performance in common abuse conditions. NP-Tab tampered by crushing and suspended in aqueous solvents forms an instantaneous gel, which is difficult to pull or push through a 21-gauge needle. NPs insulate the drug from organic solvents, deterring solvent extraction. NPs also promote thermal destruction of the drug to make crisping less rewarding. However, NP-Tab releases thebaine in the simulated gastric fluid without delay, suggesting that its analgesic effect may be unaffected if consumed orally as prescribed. These results demonstrate that NP-Tab can provide comprehensive drug abuse deterrence, resisting aqueous/organic solvent extraction, injection, and crisping, while retaining its therapeutic effect upon regular usage.

α-Gal Nanoparticles in CNS Trauma: I. In Vitro Activation of Microglia Towards a Pro-Healing State.

BACKGROUND: Macrophages and microglia play critical roles after spinal cord injury (SCI), with the pro-healing, anti-inflammatory (M2) subtype being implicated in tissue repair. We hypothesize that promoting this phenotype within the post-injured cord microenvironment may provide beneficial effects for mitigating tissue damage. As a proof of concept, we propose the use of nanoparticles incorporating the carbohydrate antigen, galactose-α-1,3-galactose (α-gal epitope) as an immunomodulator to transition human microglia (HMC3) cells toward a pro-healing state. METHODS: Quiescent HMC3 cells were acutely exposed to α-gal nanoparticles in the presence of human serum and subsequently characterized for changes in cell shape, expression of anti or pro-inflammatory markers, and secretion of phenotype-specific cytokines. RESULTS: HMC3 cells treated with serum activated α-gal nanoparticles exhibited rapid enlargement and shape change in addition to expressing CD68. Moreover, these activated cells showed increased expression of anti-inflammatory markers like Arginase-1 and CD206 without increasing production of pro-inflammatory cytokines TNF-α or IL-6. CONCLUSION: This study is the first to show that resting human microglia exposed to a complex of α-gal nanoparticles and anti-Gal (from human serum) can be activated and polarized toward a putative M2 state. The data suggests that α-gal nanoparticles may have therapeutic relevance to the CNS microenvironment, in both recruiting and polarizing macrophages/microglia at the application site. The immunomodulatory activity of these α-gal nanoparticles post-SCI is further described in the companion work (Part II).

Inverse resolution of spatially varying diffusion coefficient using Physics-Informed neural networks.

Resolving the diffusion coefficient is a key element in many biological and engineering systems, including pharmacological drug transport and fluid mechanics analyses. Additionally, these systems often have spatial variation in the diffusion coefficient which must be determined, such as for injectable drug-eluting implants into heterogeneous tissues. Unfortunately, obtaining the diffusion coefficient from images in such cases is an inverse problem with only discrete data points. The development of a robust method that can work with such noisy and ill-posed datasets to accurately determine spatially-varying diffusion coefficients is of great value across a large range of disciplines. Here, we developed an inverse solver that uses physics informed neural networks (PINNs) to calculate spatially-varying diffusion coefficients from numerical and experimental image data in varying biological and engineering applications. The residual of the transient diffusion equation for a concentration field is minimized to find the diffusion coefficient. The robustness of the method as an inverse solver was tested using both numerical and experimental datasets. The predictions show good agreement with both the numerical and experimental benchmarks; an error of less than 6.31% was obtained against all numerical benchmarks, while the diffusion coefficient calculated in experimental datasets matches the appropriate ranges of other reported literature values. Our work demonstrates the potential of using PINNs to resolve spatially-varying diffusion coefficients, which may aid a wide-range of applications, such as enabling better-designed drug-eluting implants for regenerative medicine or oncology fields.

Poroelastic Characterization and Modeling of Subcutaneous Tissue Under Confined Compression.

Subcutaneous tissue mechanics are important for drug delivery. Yet, even though this material is poroelastic, its mechanical characterization has focused on its hyperelastic response. Moreover, advancement in subcutaneous drug delivery requires effective tissue mimics such as hydrogels for which similar gaps of poroelastic data exist. Porcine subcutaneous samples and gelatin hydrogels were tested under confined compression at physiological conditions and strain rates of 0.01%/s in 5% strain steps with 2600 s of stress relaxation between loading steps. Force-time data were used in an inverse finite element approach to obtain material parameters. Tissues and gels were modeled as porous neo-Hookean materials with properties specified via shear modulus, effective solid volume fraction, initial hydraulic permeability, permeability exponent, and normalized viscous relaxation moduli. The constitutive model was implemented into an isogeometric analysis (IGA) framework to study subcutaneous injection. Subcutaneous tissue exhibited an initial spike in stress due to compression of the solid and fluid pressure buildup, with rapid relaxation explained by fluid drainage, and longer time-scale relaxation explained by viscous dissipation. The inferred parameters aligned with the ranges reported in the literature. Hydraulic permeability, the most important parameter for drug delivery, was in the range k 0 ∈ [ 0.142 , 0.203 ] mm 4 /(N s). With these parameters, IGA simulations showed peak stresses due to a 1-mL injection to reach 48.8 kPa at the site of injection, decaying after drug volume disperses into the tissue. The poro-hyper-viscoelastic neo-Hookean model captures the confined compression response of subcutaneous tissue and gelatin hydrogels. IGA implementation enables predictive simulations of drug delivery.

Rapid Self-Healing Hydrogel with Ultralow Electrical Hysteresis for Wearable Sensing.

Self-healing hydrogels are in high demand for wearable sensing applications due to their remarkable deformability, high ionic and electrical conductivity, self-adhesiveness to human skin, as well as resilience to both mechanical and electrical damage. However, these hydrogels face challenges such as delayed healing times and unavoidable electrical hysteresis, which limit their practical effectiveness. Here, we introduce a self-healing hydrogel that exhibits exceptionally rapid healing with a recovery time of less than 0.12 s and an ultralow electrical hysteresis of less than 0.64% under cyclic strains of up to 500%. This hydrogel strikes an ideal balance, without notable trade-offs, between properties such as softness, deformability, ionic and electrical conductivity, self-adhesiveness, response and recovery times, durability, overshoot behavior, and resistance to nonaxial deformations such as twisting, bending, and pressing. Owing to this unique combination of features, the hydrogel is highly suitable for long-term, durable use in wearable sensing applications, including monitoring body movements and electrophysiological activities on the skin.

α-Gal Nanoparticles in CNS Trauma: II. Immunomodulation Following Spinal Cord Injury (SCI) Improves Functional Outcomes.

BACKGROUND: Previous investigations have shown that local application of nanoparticles presenting the carbohydrate moiety galactose-α-1,3-galactose (α-gal epitopes) enhance wound healing by activating the complement system and recruiting pro-healing macrophages to the injury site. Our companion in vitro paper suggest α-gal epitopes can similarly recruit and polarize human microglia toward a pro-healing phenotype. In this continuation study, we investigate the in vivo implications of α-gal nanoparticle administration directly to the injured spinal cord. METHODS: α-Gal knock-out (KO) mice subjected to spinal cord crush were injected either with saline (control) or with α-gal nanoparticles immediately following injury. Animals were assessed longitudinally with neurobehavioral and histological endpoints. RESULTS: Mice injected with α-gal nanoparticles showed increased recruitment of anti-inflammatory macrophages to the injection site in conjunction with increased production of anti-inflammatory markers and a reduction in apoptosis. Further, the treated group showed increased axonal infiltration into the lesion, a reduction in reactive astrocyte populations and increased angiogenesis. These results translated into improved sensorimotor metrics versus the control group. CONCLUSIONS: Application of α-gal nanoparticles after spinal cord injury (SCI) induces a pro-healing inflammatory response resulting in neuroprotection, improved axonal ingrowth into the lesion and enhanced sensorimotor recovery. The data shows α-gal nanoparticles may be a promising avenue for further study in CNS trauma.

KRAS-mediated upregulation of CIP2A promotes suppression of PP2A-B56α to initiate pancreatic cancer development.

Oncogenic mutations in KRAS are present in approximately 95% of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) and are considered the initiating event of pancreatic intraepithelial neoplasia (PanIN) precursor lesions. While it is well established that KRAS mutations drive the activation of oncogenic kinase cascades during pancreatic oncogenesis, the effects of oncogenic KRAS signaling on regulation of phosphatases during this process is not fully appreciated. Protein Phosphatase 2A (PP2A) has been implicated in suppressing KRAS-driven cellular transformation. However, low PP2A activity is observed in PDAC cells compared to non-transformed cells, suggesting that suppression of PP2A activity is an important step in the overall development of PDAC. In the current study, we demonstrate that KRASG12D induces the expression of both an endogenous inhibitor of PP2A activity, Cancerous Inhibitor of PP2A (CIP2A), and the PP2A substrate, c-MYC. Consistent with these findings, KRASG12D sequestered the specific PP2A subunit responsible for c-MYC degradation, B56α, away from the active PP2A holoenzyme in a CIP2A-dependent manner. During PDAC initiation in vivo, knockout of B56α promoted KRASG12D tumorigenesis by accelerating acinar-to-ductal metaplasia (ADM) and the formation of PanIN lesions. The process of ADM was attenuated ex vivo in response to pharmacological re-activation of PP2A utilizing direct small molecule activators of PP2A (SMAPs). Together, our results suggest that suppression of PP2A-B56α through KRAS signaling can promote the MYC-driven initiation of pancreatic tumorigenesis.

Basic Salt Additives Modulate the Acidic Microenvironment Around In Situ Forming Implants.

There is a growing number of protein drugs, yet their limited oral bioavailability requires that patients receive frequent, high dose injections. In situ forming implants (ISFIs) for controlled release of biotherapeutics have the potential to greatly reduce the injection frequency and improve patient compliance. However, protein release from ISFIs is a challenge due to their proclivity for instability. Specifically, factors such as the acidic microclimate within ISFIs can lead to protein aggregation and denaturation. Basic salts have been shown in PLGA microparticle and microcylinder formulations to significantly reduce protein instability by neutralizing this acidic environment. The overall objective of the study was to demonstrate that basic salts can be used with an ISFI system to neutralize the implant acidification. To this end, the basic salts MgCO3 and Mg(OH)2 were added to a protein-releasing ISFI and the effect on drug release, pH, implant swelling, implant diffusivity, and implant erosion were evaluated. Either salt added at 3 wt% neutralized the acidic environment surrounding the implants, keeping the pH at 6.64 ± 0.03 (MgCO3) and 6.46 ± 0.11 (Mg(OH)2) after 28 day compared to 3.72 ± 0.05 with no salts added. The salts initially increased solution uptake into the implants but delayed implant degradation and erosion. The 3 wt% Mg(OH)2 formulation also showed slightly improved drug release with a lower burst and increased slope. We showed that salt additives can be an effective way to modulate the pH in the ISFI environment, which can improve protein stability and ultimately improve the capacity of ISFIs for delivering pH-sensitive biomolecules. Such a platform represents a low-cost method of improving overall patient compliance and reducing the overall healthcare burden.

Automated Layer Identification Method for Skin Tissue Histology Images.

We present a novel automated tissue layer identification method for histology images. The method requires a single user input: the number of layers to be identified. The method incorporates a coarse boundary identification step followed by a refinement step. The coarse identification segments the image into 125 × 125 pixel sub-tiles, computes the histogram of each sub-tile, implements K-means clustering to label each sub-tile, and uses Dijkstra's algorithm to form the layer boundary. The refinement step identifies hair follicles, improves the detail and accuracy of the boundary, and segments the epidermis. The method only uses one color channel (blue). We test our proposed method using eight excised porcine tissue samples taken at different anatomical locations. The layer segmentations demonstrated that the dermis thickness increased, and the subcutaneous thickness decreased moving from breast to belly. Minimal variation in the thickness of the epidermis layer across anatomical locations was observed. Overall, these results highlight the importance of quantifying and assessing the tissue environment. Moreover, we demonstrate that our proposed method was robust across different histology stains and did not depend on color-specific information.

Multi-feature-Based Robust Cell Tracking.

Cell tracking algorithms have been used to extract cell counts and motility information from time-lapse images of migrating cells. However, these algorithms often fail when the collected images have cells with spatially and temporally varying features, such as morphology, position, and signal-to-noise ratio. Consequently, state-of-the-art algorithms are not robust or reliable because they require manual inputs to overcome the cell feature changes. To address these issues, we present a fully automated, adaptive, and robust feature-based cell tracking algorithm for the accurate detection and tracking of cells in time-lapse images. Our algorithm tackles measurement limitations twofold. First, we use Hessian filtering and adaptive thresholding to detect the cells in images, overcoming spatial feature variations among the existing cells without manually changing the input thresholds. Second, cell feature parameters are measured, including position, diameter, mean intensity, area, and orientation, and these parameters are simultaneously used to accurately track the cells between subsequent frames, even under poor temporal resolution. Our technique achieved a minimum of 92% detection and tracking accuracy, compared to 16% from Mosaic and Trackmate. Our improved method allows for extended tracking and characterization of heterogeneous cell behavior that are of particular interest for intravital imaging users.

Damage and Fracture Mechanics of Porcine Subcutaneous Tissue Under Tensile Loading.

Subcutaneous injection, which is a preferred delivery method for many drugs, causes deformation, damage, and fracture of the subcutaneous tissue. Yet, experimental data and constitutive modeling of these dissipation mechanisms in subcutaneous tissue remain limited. Here we show that subcutaneous tissue from the belly and breast anatomical regions in the swine show nonlinear stress-strain response with the characteristic J-shaped behavior of collagenous tissue. Additionally, subcutaneous tissue experiences damage, defined as a decrease in the strain energy capacity, as a function of the previously experienced maximum deformation. The elastic and damage response of the tissue are accurately described by a microstructure-driven constitutive model that relies on the convolution of a neo-Hookean material of individual fibers with a fiber orientation distribution and a fiber recruitment distribution. The model fit revealed that subcutaneous tissue can be treated as initially isotropic, and that changes in the fiber recruitment distribution with loading are enough to explain the dissipation of energy due to damage. When tested until failure, subcutaneous tissue that has undergone damage fails at the same peak stress as virgin samples, but at a much larger stretch, overall increasing the tissue toughness. Together with a finite element implementation, these data and constitutive model may enable improved drug delivery strategies and other applications for which subcutaneous tissue biomechanics are relevant.