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Abstract Background Traumatic knee injuries in humans trigger an immediate increase in synovial fluid levels of inflammatory cytokines that accompany impact damage to joint tissues. We developed a human in vitro cartilage-bone-synovium (CBS) coculture model to study the role of mechanical injury and inflammation in the initiation of post-traumatic osteoarthritis (PTOA)-like disease. Methods Osteochondral plugs (cartilage-bone, CB) along with joint capsule synovium explants (S) were harvested from 25 cadaveric distal femurs from 16 human donors (Collin’s grade 0–2, 23–83years). Two-week monocultures (cartilage (C), bone (B), synovium (S)) and cocultures (CB, CBS) were established. A PTOA-like disease group was initiated via coculture of synovium explants with mechanically impacted osteochondral plugs (CBS+INJ, peak stress 5MPa) with non-impacted CB as controls. Disease-like progression was assessed through analyses of changes in cell viability, inflammatory cytokines released to media (10-plex ELISA), tissue matrix degradation, and metabolomics profile. Results Immediate increases in concentrations of a panel of inflammatory cytokines occurred in CBS+INJ and CBS cocultures and cultures with S alone (IL-1, IL-6, IL-8, and TNF-α among others). CBS+INJ and CBS also showed increased chondrocyte death compared to uninjured CB. The release of sulfated glycosaminoglycans (sGAG) and associated ARGS-aggrecan neoepitope fragments to the medium was significantly increased in CBS and CBS+INJ groups. Distinct metabolomics profiles were observed for C, B, and S monocultures, and metabolites related to inflammatory response in CBS versus CB (e.g., kynurenine, 1-methylnicotinamide, and hypoxanthine) were identified. Conclusion CBS and CBS+INJ models showed distinct cellular, inflammatory, and matrix-related alterations relevant to PTOA-like initiation/progression. The use of human knee tissues from donors that had no prior history of OA disease suggests the relevance of this model in highlighting the role of injury and inflammation in earliest stages of PTOA progression.

Abstract The development and application of quantitative systems pharmacology models in neuroscience have been modest relative to other fields, such as oncology and immunology, which may reflect the complexity of the brain. Technological and methodological advancements have enhanced the quantitative understanding of brain physiology and pathophysiology and the effects of pharmacological interventions. To maximize the knowledge gained from these novel data types, pharmacometrics modelers may need to expand their toolbox to include additional mathematical and statistical frameworks. A session was held at the 10th annual American Conference on Pharmacometrics (ACoP10) to highlight several recent advancements in quantitative and systems neuroscience. In this mini‐review, we provide a brief overview of technological and methodological advancements in the neuroscience therapeutic area that were discussed during the session and how these can be leveraged with quantitative systems pharmacology modeling to enhance our understanding of neurological diseases. Microphysiological systems using human induced pluripotent stem cells (IPSCs), digital biomarkers, and large‐scale imaging offer more clinically relevant experimental datasets, enhanced granularity, and a plethora of data to potentially improve the preclinical‐to‐clinical translation of therapeutics. Network neuroscience methodologies combined with quantitative systems models of neurodegenerative disease could help bridge the gap between cellular and molecular alterations and clinical end points through the integration of information on neural connectomics. Additional topics, such as the neuroimmune system, microbiome, single‐cell transcriptomic technologies, and digital device biomarkers, are discussed in brief.

Drug‐induced kidney injury, a major cause of acute kidney injury, results in progressive kidney disease and is linked to increased mortality in hospitalized patients. Primary injury sites of drug‐induced kidney injury are proximal tubules. Clinically, kidney injury molecule‐1, an established tubule‐specific biomarker, is monitored to assess the presence and progression of injury. The ability to accurately predict drug‐related nephrotoxicity preclinically would reduce patient burden and drug attrition rates, yet state‐of‐the‐art in vitro and animal models fail to do so. In this study, we demonstrate the use of kidney injury molecule‐1 measurement in the kidney microphysiological system as a preclinical model for drug toxicity assessment. To show clinical relevance, we use quantitative systems pharmacology computational models for in vitro–in vivo translation of the experimental results and to identify favorable dosing regimens for one of the tested drugs.

Abstract Microphysiological systems (MPS), consisting of tissue constructs, biomaterials, and culture media, aim to recapitulate relevant organ functions in vitro. MPS components are housed in fluidic hardware with operational protocols, such as periodic complete media replacement. Such batch-like operations provide relevant nutrients and remove waste products but also reset cell-secreted mediators (e.g. cytokines, hormones) and potentially limit exposure to drugs (and metabolites). While each component plays an essential role for tissue functionality, MPS-specific nutrient needs are not yet well-characterized nor utilized to operate MPSs at more physiologically-relevant conditions. MPS-specific nutrient needs for gut (immortalized cancer cells), liver (human primary hepatocytes) and cardiac (iPSC-derived cardiomyocytes) MPSs were experimentally quantified. In a long-term study of the gut MPS (10 days), this knowledge was used to design operational protocols to maintain glucose and lactate at desired levels. This quasi-steady state operation was experimentally validated by monitoring glucose and lactate as well as MPS functionality. In a theoretical study, nutrient needs of an integrated multi-MPS platform (gut, liver, cardiac MPSs) were computationally simulated to identify long-term quasi-steady state operations. This integrative experimental and computational approach demonstrates the utilization of quantitative multi-scale characterization of MPSs and incorporating MPS-specific information to establish more physiologically-relevant experimental operations.

Abstract The extracellular signal‐regulated kinase (ERK) signaling pathway controls cell proliferation and differentiation in metazoans. Two hallmarks of its dynamics are adaptation of ERK phosphorylation, which has been linked to negative feedback, and nucleocytoplasmic shuttling, which allows active ERK to phosphorylate protein substrates in the nucleus and cytosol. To integrate these complex features, we acquired quantitative biochemical and live‐cell microscopy data to reconcile phosphorylation, localization, and activity states of ERK. While maximal growth factor stimulation elicits transient ERK phosphorylation and nuclear translocation responses, ERK activities available to phosphorylate substrates in the cytosol and nuclei show relatively little or no adaptation. Free ERK activity in the nucleus temporally lags the peak in nuclear translocation, indicating a slow process. Additional experiments, guided by kinetic modeling, show that this process is consistent with ERK's modification of and release from nuclear substrate anchors. Thus, adaptation of whole‐cell ERK phosphorylation is a by‐product of transient protection from phosphatases. Consistent with this interpretation, predictions concerning the dose‐dependence of the pathway response and its interruption by inhibition of MEK were experimentally confirmed.

Inhibition of the ubiquitin-proteasome protein degradation pathway has been identified as a viable strategy for anti-tumor therapy based on its broad effects on cell proliferation. By the same token, the variety of elicited effects confounds the interpretation of cell-based experiments using proteasome inhibitors such as MG132. It has been proposed that MG132 treatment reduces growth factor-stimulated phosphorylation of extracellular signal-regulated kinases (ERKs), at least in part through upregulation of dual specificity phosphatases (DUSPs). Here, we show that the effects of MG132 treatment on ERK signaling are more widespread, leading to a reduction in activation of the upstream kinase MEK. This suggests that MG132 systemically perturbs the intracellular phosphoproteome, impacting ERK signaling by reducing phosphorylation status at multiple levels of the kinase cascade.

Productive cell migration requires the spatiotemporal coordination of cell adhesion, membrane protrusion, and actomyosin-mediated contraction. Integrins, engaged by the extracellular matrix (ECM), nucleate the formation of adhesive contacts at the cell's leading edge(s), and maturation of nascent adhesions to form stable focal adhesions constitutes a functional switch between protrusive and contractile activities. To shed additional light on the coupling between integrin-mediated adhesion and membrane protrusion, we have formulated a quantitative model of leading edge dynamics combining mechanistic and phenomenological elements and studied its features through classical bifurcation analysis and stochastic simulation. The model describes in mathematical terms the feedback loops driving, on the one hand, Rac-mediated membrane protrusion and rapid turnover of nascent adhesions, and on the other, myosin-dependent maturation of adhesions that inhibit protrusion at high ECM density. Our results show that the qualitative behavior of the model is most sensitive to parameters characterizing the influence of stable adhesions and myosin. The major predictions of the model, which we subsequently confirmed, are that persistent leading edge protrusion is optimal at an intermediate ECM density, whereas depletion of myosin IIA relieves the repression of protrusion at higher ECM density.

Signal transduction networks in mammalian cells, comprising a limited set of interacting biochemical pathways, are accessed by various growth factor and cytokine receptors to elicit distinct cell responses. This raises the question as to how specificity of the stimulus–response relationship is encoded at the molecular level. It has been proposed that specificity arises not only from the activation of unique signalling pathways, but also from quantitative differences in the activation and regulation of shared receptor-proximal signalling proteins. To address such hypotheses, data sets with greater precision and coverage of experimental conditions will need to be acquired, and rigorous frameworks that codify and parameterize the inherently non-linear relationships among signalling activities will need to be developed. In the present study we apply a systematic approach combining quantitative measurements and mathematical modelling to compare the signalling networks accessed by FGF (fibroblast growth factor) and PDGF (platelet-derived growth factor) receptors in mouse fibroblasts, in which the ERK (extracellular-signal-regulated kinase) cascade is activated by Ras- and PI3K (phosphoinositide 3-kinase)-dependent pathways. We show that, whereas the FGF stimulation of PI3K signalling is relatively weak, this deficiency is compensated for by a more potent Ras-dependent activation of ERK. Thus, as the modelling would predict, the ERK pathway is activated to a greater extent in cells co-stimulated with FGF and PDGF, relative to the saturated levels achieved with either ligand alone. It is envisaged that similar approaches will prove valuable in the elucidation of quantitative differences among other closely related receptor signalling networks. [ABSTRACT FROM AUTHOR]