Osteoimmunology: Interactions With the Immune System in Spinal Fusion.

Spinal fusion is important for the clinical success of patients undergoing surgery, and the immune system plays an increasingly recognized role. Osteoimmunology is the study of the interactions between the immune system and bone. Inflammation impacts the osteogenic, osteoconductive, and osteoinductive properties of bone grafts and substitutes and ultimately influences the success of spinal fusion. Macrophages have emerged as important cells for coordinating the immune response following spinal fusion surgery, and macrophage-derived cytokines impact each phase of bone graft healing. This review explores the cellular and molecular immune processes that regulate bone homeostasis and healing during spinal fusion.

Computational screen for sex-specific drug effects in a cardiac fibroblast signaling network model.

Heart disease is the leading cause of death in both men and women. Cardiac fibrosis is the uncontrolled accumulation of extracellular matrix proteins, which can exacerbate the progression of heart failure, and there are currently no drugs approved specifically to target matrix accumulation in the heart. Computational signaling network models (SNMs) can be used to facilitate discovery of novel drug targets. However, the vast majority of SNMs are not sex-specific and/or are developed and validated using data skewed towards male in vitro and in vivo samples. Biological sex is an important consideration in cardiovascular health and drug development. In this study, we integrate a cardiac fibroblast SNM with estrogen signaling pathways to create sex-specific SNMs. The sex-specific SNMs demonstrated high validation accuracy compared to in vitro experimental studies in the literature while also elucidating how estrogen signaling can modulate the effect of fibrotic cytokines via multi-pathway interactions. Further, perturbation analysis and drug screening uncovered several drug compounds predicted to generate divergent fibrotic responses in male vs. female conditions, which warrant further study in the pursuit of sex-specific treatment recommendations for cardiac fibrosis. Future model development and validation will require more generation of sex-specific data to further enhance modeling capabilities for clinically relevant sex-specific predictions of cardiac fibrosis and treatment.

Determination of metarrestin (ML-246) in human plasma for a first-in-human clinical pharmacokinetic application by a simple and efficient uHPLC-MS/MS assay.

Metarrestin is a first-in-class small molecule inhibitor targeting the perinucleolar compartment, a subnuclear body associated with metastatic capacity. Promising preclinical results led to the clinical translation of the compound into a first-in-human phase I trial (NCT04222413). To characterize metarrestin's pharmacokinetic profile in humans, a uHPLC-MS/MS assay was developed and validated to determine the disposition of the drug in human plasma. Efficient sample preparation was accomplished through one-step protein precipitation paired with elution through a phospholipid filtration plate. Chromatographic separation was achieved with gradient elution through an Acuity UPLC® BEH C18 column (50 × 2.1 mm, 1.7 µm). Tandem mass spectrometry facilitated the detection of metarrestin and tolbutamide, the internal standard. The effective calibration range spanned 1-5000 ng/mL and was both accurate (range -5.9 % to 4.9 % deviation) and precise (≤9.0 %CV). Metarrestin proved stable (≤4.9 % degradation) under various assay-imposed conditions. Matrix effects, extraction efficiency, and process efficiency were assessed. Further, the assay was successfully able to determine the disposition of orally administered metarrestin in patients from the lowest dose cohort (1 mg) for 48 h post-administration. Thus, the validated analytical method detailed in this work is simple, sensitive, and clinically applicable.

Computational Screen for Sex-Specific Drug Effects in a Cardiac Fibroblast Network Model.

Heart disease is the leading cause of death in both men and women. Cardiac fibrosis is the uncontrolled accumulation of extracellular matrix proteins which can exacerbate the progression of heart failure, and there are currently no drugs approved specifically to target matrix accumulation in the heart. Computational signaling network models (SNMs) can be used to facilitate discovery of novel drug targets. However, the vast majority of SNMs are not sex-specific and/or are developed and validated using data skewed towards male in vitro and in vivo samples. Biological sex is an important consideration in cardiovascular health and drug development. In this study, we integrate a previously constructed cardiac fibroblast SNM with estrogen signaling pathways to create sex-specific SNMs. The sex-specific SNMs maintained previously high validation when compared to in vitro experimental studies in the literature. A sex-specific perturbation analysis and drug screen uncovered several potential pathways that warrant further study in the pursuit of sex-specific treatment recommendations for cardiac fibrosis.

In vitro bioreactor for mechanical control and characterization of tissue constructs.

Cardiac fibrosis is a key contributor to the onset and progression of heart failure and occurs from extracellular matrix accumulation via activated cardiac fibroblasts. Cardiac fibroblasts activate in response to mechanical stress and have been studied in the past by applying forces and deformations to three-dimensional, cell-seeded gels and tissue constructs in vitro. Unfortunately, previous stretching platforms have traditionally not enabled mechanical property assessment to be performed with an efficient throughput, thereby limiting the full potential of in vitro mechanobiology studies. We have developed a novel in vitro platform to study cell-populated tissue constructs under dynamic mechanical stimulation while also performing repeatable, non-destructive stress-strain tests in living constructs. Additionally, this platform can perform these tests across all constructs in a multi-well plate simultaneously, providing exciting potential for direct, functional readouts in future screening applications. In our pilot application, we showed that cyclically stretching cell-populated tissue constructs composed of murine cardiac fibroblasts within a 3D fibrin matrix leads to collagen accumulation and increased tissue stiffness over a three-day time course. Results of this study validate our platform's ability to apply mechanical loads to tissues while performing live mechanical analyses to observe cell-mediated tissue remodeling.

In Silico Re-Optimization of Atezolizumab Dosing Using Population Pharmacokinetic Simulation and Exposure-Response Simulation.

Atezolizumab, a humanized monoclonal antibody against programmed cell death ligand 1 (PD-L1), was initially approved in 2016, around the same time that the sponsor published the minimum serum concentration to maintain the saturation of receptor occupancy (6 µg/mL). The initially approved dose regimen of 1200 mg every 3 weeks (q3w) was subsequently modified to 840 mg q2w or 1680 mg q4w through pharmacokinetic simulations. Yet, each standard regimen yields steady-state trough concentrations (CMIN,SS ) far exceeding (≈ 40-fold) the stated target concentration. Additionally, the steady-state area under the plasma drug concentration-time curve (AUCSS ) at 1200 mg q3w was significantly (P = .027) correlated with the probability of adverse events of special interest (AESIs) in patients with non-small cell lung cancer (NSCLC) and, coupled with excess exposure, this provides incentive to explore alternative dose regimens to lower the exposure burden while maintaining an effective CMIN,SS . In this study, we first identified 840 mg q6w as an extended-interval regimen that could robustly maintain a serum concentration of 6 µg/mL (≥99% of virtual patients simulated, n = 1000), then applied this regimen to an approach that administers 2 "loading doses" of standard-interval regimens for a future clinical trial aiming to personalize dose regimens. Each standard dose was simulated for 2 loading doses, then 840 mg q6w thereafter; all yielded cycle-7 CMIN,SS values of >6 µg/mL in >99% of virtual patients. Further, the AUCSS from 840 mg q6w resulted in a flattening (P = .63) of the exposure-response relationship with adverse events of special interest (AESIs). We next aim to verify this in a clinical trial seeking to validate extended-interval dosing in a personalized approach using therapeutic drug monitoring.

Mechanical strain modulates extracellular matrix degradation and byproducts in an isoform-specific manner.

Many studies have shown that mechanical forces can alter collagen degradation by proteases, and this mechanochemical effect may potentially serve an important role in determining extracellular matrix content and organization in load-bearing tissues. However, it is not yet known whether mechano-sensitive degradation depends on particular protease isoforms, nor is it yet known whether particular degradation byproducts can be altered by mechanical loading. In this study, we tested the hypothesis that different types of proteases exhibit different sensitivities to mechanical loading both in degradation rates and byproducts. Decellularized porcine pericardium samples were treated with human recombinant matrix metalloproteinases-1, -8, -9, cathepsin K, or a protease-free control while subjected to different levels of strain in a planar, biaxial mechanical tester. Tissue degradation was monitored by tracking the decay in mechanical stresses during displacement control tests, and byproducts were assessed by mass spectrometry analysis of the sample supernatant after degradation. Our key finding shows that cathepsin K-mediated degradation of collagenous tissue was enhanced with increasing strain, while MMP1-, MMP8-, and MMP9-mediated degradation were first decreased and then increased by strain. Degradation induced changes in tissue mechanical properties, and proteomic analysis revealed strain-sensitive degradome signatures with different ECM byproducts released at low vs. high strains. This evidence suggests a potentially new type of mechanobiology wherein mechanical forces alter the degradation products that can provide important signaling feedback functions during tissue remodeling.

Interpretable machine learning predicts cardiac resynchronization therapy responses from personalized biochemical and biomechanical features.

BACKGROUND: Cardiac Resynchronization Therapy (CRT) is a widely used, device-based therapy for patients with left ventricle (LV) failure. Unfortunately, many patients do not benefit from CRT, so there is potential value in identifying this group of non-responders before CRT implementation. Past studies suggest that predicting CRT response will require diverse variables, including demographic, biomarker, and LV function data. Accordingly, the objective of this study was to integrate diverse variable types into a machine learning algorithm for predicting individual patient responses to CRT. METHODS: We built an ensemble classification algorithm using previously acquired data from the SMART-AV CRT clinical trial (n = 794 patients). We used five-fold stratified cross-validation on 80% of the patients (n = 635) to train the model with variables collected at 0 months (before initiating CRT), and the remaining 20% of the patients (n = 159) were used as a hold-out test set for model validation. To improve model interpretability, we quantified feature importance values using SHapley Additive exPlanations (SHAP) analysis and used Local Interpretable Model-agnostic Explanations (LIME) to explain patient-specific predictions. RESULTS: Our classification algorithm incorporated 26 patient demographic and medical history variables, 12 biomarker variables, and 18 LV functional variables, which yielded correct prediction of CRT response in 71% of patients. Additional patient stratification to identify the subgroups with the highest or lowest likelihood of response showed 96% accuracy with 22 correct predictions out of 23 patients in the highest and lowest responder groups. CONCLUSION: Computationally integrating general patient characteristics, comorbidities, therapy history, circulating biomarkers, and LV function data available before CRT intervention can improve the prediction of individual patient responses.

Ensemble machine learning model identifies patients with HFpEF from matrix-related plasma biomarkers.

Arterial hypertension can lead to structural changes within the heart including left ventricular hypertrophy (LVH) and eventually heart failure with preserved ejection fraction (HFpEF). The initial diagnosis of HFpEF is costly and generally based on later stage remodeling; thus, improved predictive diagnostic tools offer potential clinical benefit. Recent work has shown predictive value of multibiomarker plasma panels for the classification of patients with LVH and HFpEF. We hypothesized that machine learning algorithms could substantially improve the predictive value of circulating plasma biomarkers by leveraging more sophisticated statistical approaches. In this work, we developed an ensemble classification algorithm for the diagnosis of HFpEF within a population of 480 individuals including patients with HFpEF, patients with LVH, and referent control patients. Algorithms showed strong diagnostic performance with receiver-operating-characteristic curve (ROC) areas of 0.92 for identifying patients with LVH and 0.90 for identifying patients with HFpEF using demographic information, plasma biomarkers related to extracellular matrix remodeling, and echocardiogram data. More impressively, the ensemble algorithm produced an ROC area of 0.88 for HFpEF diagnosis using only demographic and plasma panel data. Our findings demonstrate that machine learning-based classification algorithms show promise as a noninvasive diagnostic tool for HFpEF, while also suggesting priority biomarkers for future mechanistic studies to elucidate more specific regulatory roles.NEW & NOTEWORTHY Machine learning algorithms correctly classified patients with heart failure with preserved ejection fraction with over 90% area under receiver-operating-characteristic curves. Classifications using multidomain features (demographics and circulating biomarkers and echo-based ventricle metrics) proved more accurate than previous studies using single-domain features alone. Excitingly, HFpEF diagnoses were generally accurate even without echo-based measurements, demonstrating that such algorithms could provide an early screening tool using blood-based measurements before sophisticated imaging.

Quantitation of the next-generation imipridone ONC206 in human plasma by a simple and sensitive UPLC-MS/MS assay for clinical pharmacokinetic application.

ONC206 is an imipridone derivative that is being developed clinically as a single agent given orally in a first-in-human trial (NCT04541082). This ongoing clinical trial requires pharmacokinetic analysis of ONC206 to fully characterize its pharmacologic profile. There is currently no published bioanalytical method for ONC206 quantitation. To understand the clinical pharmacokinetics of ONC206, a sensitive yet simple uHPLC-MS/MS method for quantitation of ONC206 in human plasma was developed. Protein-precipitation allowed rapid and sensitive bioanalytical measurement of ONC206 in human plasma. A Phenomenex Kinetex C18 (50 ×2.1 mm, 1.3 µm, 100 Å) analytical column achieved symmetrical and sharp chromatography peaks of ONC206 and the internal standard, [2H]7-ONC206, which were detected using multiple reaction monitoring. The assay calibration range was 1-500 ng/mL and was best fit by a linear regression model (r2 > 0.99732 ± 0.0010). The method proved accurate (< ± 9% deviation), precise (<11%CV), selective and specific with no interference and low inter-lot matrix variability. ONC206 demonstrated excellent short-term, long-term, and multiple freeze-thaw cycle stability in solution and human plasma. This fully validated method was used to quantitate ONC206 plasma concentrations from patients enrolled in the aforementioned clinical trial at the NCI to demonstrate its clinical applicability.

Fibroblast mechanotransduction network predicts targets for mechano-adaptive infarct therapies.

Regional control of fibrosis after myocardial infarction is critical for maintaining structural integrity in the infarct while preventing collagen accumulation in non-infarcted areas. Cardiac fibroblasts modulate matrix turnover in response to biochemical and biomechanical cues, but the complex interactions between signaling pathways confound efforts to develop therapies for regional scar formation. We employed a logic-based ordinary differential equation model of fibroblast mechano-chemo signal transduction to predict matrix protein expression in response to canonical biochemical stimuli and mechanical tension. Functional analysis of mechano-chemo interactions showed extensive pathway crosstalk with tension amplifying, dampening, or reversing responses to biochemical stimuli. Comprehensive drug target screens identified 13 mechano-adaptive therapies that promote matrix accumulation in regions where it is needed and reduce matrix levels in regions where it is not needed. Our predictions suggest that mechano-chemo interactions likely mediate cell behavior across many tissues and demonstrate the utility of multi-pathway signaling networks in discovering therapies for context-specific disease states.

Network modeling predicts personalized gene expression and drug responses in valve myofibroblasts cultured with patient sera.

Aortic valve stenosis (AVS) patients experience pathogenic valve leaflet stiffening due to excessive extracellular matrix (ECM) remodeling. Numerous microenvironmental cues influence pathogenic expression of ECM remodeling genes in tissue-resident valvular myofibroblasts, and the regulation of complex myofibroblast signaling networks depends on patient-specific extracellular factors. Here, we combined a manually curated myofibroblast signaling network with a data-driven transcription factor network to predict patient-specific myofibroblast gene expression signatures and drug responses. Using transcriptomic data from myofibroblasts cultured with AVS patient sera, we produced a large-scale, logic-gated differential equation model in which 11 biochemical and biomechanical signals were transduced via a network of 334 signaling and transcription reactions to accurately predict the expression of 27 fibrosis-related genes. Correlations were found between personalized model-predicted gene expression and AVS patient echocardiography data, suggesting links between fibrosis-related signaling and patient-specific AVS severity. Further, global network perturbation analyses revealed signaling molecules with the most influence over network-wide activity, including endothelin 1 (ET1), interleukin 6 (IL6), and transforming growth factor ß (TGFß), along with downstream mediators c-Jun N-terminal kinase (JNK), signal transducer and activator of transcription (STAT), and reactive oxygen species (ROS). Lastly, we performed virtual drug screening to identify patient-specific drug responses, which were experimentally validated via fibrotic gene expression measurements in valvular interstitial cells cultured with AVS patient sera and treated with or without bosentan-a clinically approved ET1 receptor inhibitor. In sum, our work advances the ability of computational approaches to provide a mechanistic basis for clinical decisions including patient stratification and personalized drug screening.

Pharmacokinetics and tolerability of the dual TORC1/2 inhibitor sapanisertib in combination with the MEK inhibitor trametinib in dogs.

Activation of one or both the Ras/MAPK and PI3K/Akt/mTOR signal transduction pathways are known to mediate oncogenicity of several canine and human cancers, including mucosal melanomas. Reciprocal cross activation between the two pathways can be a source of drug resistance. Consequently, oral dosing for plasma pharmacokinetic (PK) analysis and tolerability to a combination of sapanisertib, a dual TORC1/2 inhibitor, and trametinib, a MEK inhibitor, was evaluated in nontumor-bearing laboratory dogs for its potential application in parallel pathway targeting. Twelve dogs, divided into three equal cohorts, received either the combination or single agents. Animals were monitored for PK following single dose and 17-day repeat dosing, and by clinical observations, hematology, serum biochemistry, coagulation studies and urinalyses. A single trametinib dose (0.025 mg/kg), sulfated as dimethyl sulfoxide which enhanced its absorption, reached mean maximum concentration (Cmax) 0.64 ng/mL [18% coefficient of variation (CV)] at a median time to maximum concentration (Tmax) of 1.5 h (hr), and mean area under the concentration-time curve (AUC) 16.8 hr*ng/mL (14%CV), which were similar when given alone or in combination with sapanisertib. A prolonged half-life afforded 3-4-fold plasma accumulation of trametinib with daily dosing, analogous to humans. Trametinib PK mirrored previous regulatory data in dogs, while exposure approximated some published human values but generally not all patients. Sapanisertib-alone in canine plasma following single 0.1 mg/kg dose [mean Cmax 26.3 ng/mL (21%CV), median Tmax 2.0 hr, and mean AUC 248 hr*ng/mL (41%CV)] resembled levels in human therapeutic trials; whereas canine sapanisertib exposure was reduced when combined with trametinib, a known cytochrome P450 CYP3A4 inducer. Sex differences were not observed for either drug. Side effects upon repeat dosing with either or both drugs may include body weight loss, maldigestion, and cutaneous discoloration. The combination was tolerated without dose limiting toxicity, although clinical laboratory analyses revealed drug-induced acute-phase inflammation, proteinuria, and decreased blood reticulocytes, mild changes not necessitating intervention. Short-term results in dogs with this combination would appear to hold translational promise for clinical trial evaluation to target canine and possibly human melanoma, as well as other cancers having one or both signal transduction pathway activations.

Mitral Valve Prolapse Induces Regionalized Myocardial Fibrosis.

Background Mitral valve prolapse (MVP) is one of the most common forms of cardiac valve disease and affects 2% to 3% of the population. Previous imaging reports have indicated that myocardial fibrosis is common in MVP and described its association with sudden cardiac death. These data combined with evidence for postrepair ventricular dysfunction in surgical patients with MVP support a link between fibrosis and MVP. Methods and Results We performed histopathologic analysis of left ventricular (LV) biopsies from peripapillary regions, inferobasal LV wall and apex on surgical patients with MVP, as well as in a mouse model of human MVP (Dzip1S14R/+). Tension-dependent molecular pathways were subsequently assessed using both computational modeling and cyclical stretch of primary human cardiac fibroblasts in vitro. Histopathology of LV biopsies revealed regionalized fibrosis in the peripapillary myocardium that correlated with increased macrophages and myofibroblasts. The MVP mouse model exhibited similar regional increases in collagen deposition that progress over time. As observed in the patient biopsies, increased macrophages and myofibroblasts were observed in fibrotic areas within the murine heart. Computational modeling revealed tension-dependent profibrotic cellular and molecular responses consistent with fibrosis locations related to valve-induced stress. These simulations also identified mechanosensing primary cilia as involved in profibrotic pathways, which was validated in vitro and in human biopsies. Finally, in vitro stretching of primary human cardiac fibroblasts showed that stretch directly activates profibrotic pathways and increases extracellular matrix protein production. Conclusions The presence of prominent regional LV fibrosis in patients and mice with MVP supports a relationship between MVP and progressive damaging effects on LV structure before overt alterations in cardiac function. The regionalized molecular and cellular changes suggest a reactive response of the papillary and inferobasal myocardium to increased chordal tension from a prolapsing valve. These studies raise the question whether surgical intervention on patients with MVP should occur earlier than indicated by current guidelines to prevent advanced LV fibrosis and potentially reduce residual risk of LV dysfunction and sudden cardiac death.

Effects of Sex and 17 ß-Estradiol on Cardiac Fibroblast Morphology and Signaling Activities In Vitro.

Several studies have demonstrated estrogen's cardioprotective abilities in decreasing the fibrotic response of cardiac fibroblasts (CFs). However, the majority of these studies are not sex-specific, and those at the cellular level utilize tissue culture plastic, a substrate with a much higher stiffness than physiological conditions. Understanding the intrinsic differences between male and female CFs under more physiologically "healthy" conditions will help to elucidate the divergences in their complex signaling networks. We aimed to do this by conducting a sex-disaggregated analysis of changes in cellular morphology and relative levels of profibrotic signaling proteins in CFs cultured on 8 kPa stiffness plates with and without 17 ß-estradiol (E2). Cyclic immunofluorescent analysis indicated that there was a negligible change in cellular morphology due to sex and E2 treatment and that the differences between male and female CFs occur at a biochemical rather than structural level. Several proteins corresponding to profibrotic activity had various sex-specific responses with and without E2 treatment. Single-cell correlation analysis exhibited varied protein-protein interaction across experimental conditions. These findings demonstrate the need for further research into the dimorphisms of male and female CFs to develop better tailored sex-informed prevention and treatment interventions of cardiac fibrosis.

Fabrication and characterization methods for investigating cell-matrix interactions in environments possessing spatial orientation heterogeneity.

Fibrillar collagen is a ubiquitous structural protein that plays a significant role in determining the mechanical properties of various tissues. The constituent collagen architecture can give direct insight into the respective functional role of the tissue due to the strong structure-function relationship that is exhibited. In such tissues, matrix structure can vary across local subregions contributing to mechanical heterogeneity which can be implicated in tissue function or failure. The post-myocardial infarction scar environment is an example of note where mechanically insufficient collagen can result in impaired cardiac function and possibly tissue rupture due to post-MI cellular response and matrix interactions. In order to further develop the understanding of cell-matrix interactions within heterogeneous environments, we developed a method of heterogeneous collagen gel fabrication which produces a region of randomly oriented fibers directly adjacent to an interconnected region of anisotropic alignment. To fully capture and evaluate the degree of alignment and spatial orientation heterogeneity, several image processing and automated analysis methods were employed. Our analysis revealed the successful fabrication of an interconnected spatially heterogeneous collagen gel possessing distinct regions of random or preferential alignment. Additionally, embedded cell populations were observed to recognize and reorient with their underlying and surrounding architectures through our cell-centric analysis techniques. STATEMENT OF SIGNIFICANCE: Fibrillar collagen is a structural protein that contributes to the architecture-function relationship exhibited by various tissues where mechanically insufficient collagen architecture can lead to tissue failure. One environment where this can occur is the post-myocardial infarction scar environment where too much or too little collagen accumulation coupled with spatial fiber orientation heterogeneity can lead to environments incapable of normal mechanical functionality. While there are methodologies capable of generating aligned constructs, they do so with varying degrees of control and complexity with many producing uniform construct alignment. The presented platform is simple and produces continuous constructs possessing inherent spatial orientation heterogeneity. Coupling this with image processing and automated analysis methods enables the probing of fundamental cell-matrix interactions within heterogeneous environments.

Does the Heart Want What It Wants? A Case for Self-Adapting, Mechano-Sensitive Therapies After Infarction.

There is a critical need for interventions to control the development and remodeling of scar tissue after myocardial infarction. A significant hurdle to fibrosis-related therapy is presented by the complex spatial needs of the infarcted ventricle, namely that collagenous buildup is beneficial in the ischemic zone but detrimental in the border and remote zones. As a new, alternative approach, we present a case to develop self-adapting, mechano-sensitive drug targets in order to leverage local, microenvironmental mechanics to modulate a therapy's pharmacologic effect. Such approaches could provide self-tuning control to either promote fibrosis or reduce fibrosis only when and where it is beneficial to do so.

The connexin 43 carboxyl terminal mimetic peptide αCT1 prompts differentiation of a collagen scar matrix in humans resembling unwounded skin.

Phase II clinical trials have reported that acute treatment of surgical skin wounds with the therapeutic peptide alpha Connexin Carboxy-Terminus 1 (αCT1) improves cutaneous scar appearance by 47% 9-month postsurgery. While Cx43 and ZO-1 have been identified as molecular targets of αCT1, the mode-of-action of the peptide in scar mitigation at cellular and tissue levels remains to be further characterized. Scar histoarchitecture in αCT1 and vehicle-control treated skin wounds within the same patient were compared using biopsies from a Phase I clinical trial at 29-day postwounding. The sole effect on scar structure of a range of epidermal and dermal variables examined was that αCT1-treated scars had less alignment of collagen fibers relative to control wounds-a characteristic that resembles unwounded skin. The with-in subject effect of αCT1 on scar collagen order observed in Phase I testing in humans was recapitulated in Sprague-Dawley rats and the IAF hairless guinea pig. Transient increase in histologic collagen density in response to αCT1 was also observed in both animal models. Mouse NIH 3T3 fibroblasts and primary human dermal fibroblasts treated with αCT1 in vitro showed more rapid closure in scratch wound assays, with individual cells showing decreased directionality in movement. An agent-based computational model parameterized with fibroblast motility data predicted collagen alignments in simulated scars consistent with that observed experimentally in human and the animal models. In conclusion, αCT1 prompts decreased directionality of fibroblast movement and the generation of a 3D collagen matrix postwounding that is similar to unwounded skin-changes that correlate with long-term improvement in scar appearance.

Mechano-chemo signaling interactions modulate matrix production by cardiac fibroblasts.

Extracellular matrix remodeling after myocardial infarction occurs in a dynamic environment in which local mechanical stresses and biochemical signaling species stimulate the accumulation of collagen-rich scar tissue. It is well-known that cardiac fibroblasts regulate post-infarction matrix turnover by secreting matrix proteins, proteases, and protease inhibitors in response to both biochemical stimuli and mechanical stretch, but how these stimuli act together to dictate cellular responses is still unclear. We developed a screen of cardiac fibroblast-secreted proteins in response to combinations of biochemical agonists and cyclic uniaxial stretch in order to elucidate the relationships between stretch, biochemical signaling, and cardiac matrix turnover. We found that stretch significantly synergized with biochemical agonists to inhibit the secretion of matrix metalloproteinases, with stretch either amplifying protease suppression by individual agonists or antagonizing agonist-driven upregulation of protease expression. Stretch also modulated fibroblast sensitivity towards biochemical agonists by either sensitizing cells towards agonists that suppress protease secretion or de-sensitizing cells towards agonists that upregulate protease secretion. These findings suggest that the mechanical environment can significantly alter fibrosis-related signaling in cardiac fibroblasts, suggesting caution when extrapolating in vitro data to predict effects of fibrosis-related cytokines in situations like myocardial infarction where mechanical stretch occurs.

A Simple Method to Test Mechanical Strain on Epithelial Cell Monolayers Using a 3D-Printed Stretcher.

With the realization that mechanical forces mediate many biological processes and contribute to disease progression, researchers are focusing on developing new methods to understand the role of mechanotransduction in biological systems. Despite recent advances in stretching devices that analyze the effects of mechanical strain in vitro, there are still possibilities to develop new equipment. For example, many of these devices tend be expensive, whereas few have been designed to assess the effects of mechanical strain driven by the extracellular matrix (ECM) to epithelial cell monolayers and to cell-cell adhesion. In this chapter, we introduce a cost-efficient, user-friendly, 3D-printed stretching device that can be used to test the effects of mechanical strain on cultured epithelial cells. Evaluation of the device using speckle-tracking shows homogeneous strain distribution along the horizontal plane of membranes at 2.5% and 5% strains, supporting the reliability of the device. Since cell-cell junctions are mechanosensitive protein complexes, we hereby used this device to examine effects on cell-cell adhesion. For this, we used colon epithelial Caco2 cell monolayers that well-differentiate in culture and form mature adherens junctions. Subjecting Caco2 cells to 2.5% and 5% strain using our device resulted in significant reduction in the localization of the core adherens junction component E-cadherin at areas of cell-cell contact and its increased translocation to the cytoplasm, which in agreement with other methodologies showing that increased ECM-driven strain negatively affects cell-cell adhesion. In summary, we here present a new, cost-effective, homemade device that can be reliably used to examine effects of mechanical strain on epithelial cell monolayers and cell-cell adhesion, in vitro.