Self-consistent theory of reversible ligand binding to a spherical cell

In this article, we study the kinetics of reversible ligand binding to receptors on a spherical cell surface using a self-consistent stochastic theory. Binding, dissociation, diffusion and rebinding of ligands are incorporated into the theory in a systematic manner. We derive explicitly the time evolution of the ligand-bound receptor fraction p(t) in various regimes . Contrary to the commonly accepted view, we find that the well-known Berg-Purcell scaling for the association rate is modified as a function of time. Specifically, the effective on-rate changes non-monotonically as a function of time and equals the intrinsic rate at very early as well as late times, while being approximately equal to the Berg-Purcell value at intermediate times. The effective dissociation rate, as it appears in the binding curve or measured in a dissociation experiment, is strongly modified by rebinding events and assumes the Berg-Purcell value except at very late times, where the decay is algebraic and not exponential. In equilibrium, the ligand concentration everywhere in the solution is the same and equals its spatial mean, thus ensuring that there is no depletion in the vicinity of the cell. Implications of our results for binding experiments and numerical simulations of ligand-receptor systems are also discussed.Comment: 23 pages with 4 figure

Exponential Distribution of Locomotion Activity in Cell Cultures

In vitro velocities of several cell types have been measured using computer controlled video microscopy, which allowed to record the cells' trajectories over several days. On the basis of our large data sets we show that the locomotion activity displays a universal exponential distribution. Thus, motion resulting from complex cellular processes can be well described by an unexpected, but very simple distribution function. A simple phenomenological model based on the interaction of various cellular processes and finite ATP production rate is proposed to explain these experimental results.Comment: 4 pages, 3 figure

Marrow-Derived Stem Cell Motility in 3D Synthetic Scaffold Is Governed by Geometry Along With Adhesivity and Stiffness

Author Manuscript 2012 May 21.Design of 3D scaffolds that can facilitate proper survival, proliferation, and differentiation of progenitor cells is a challenge for clinical applications involving large connective tissue defects. Cell migration within such scaffolds is a critical process governing tissue integration. Here, we examine effects of scaffold pore diameter, in concert with matrix stiffness and adhesivity, as independently tunable parameters that govern marrow-derived stem cell motility. We adopted an “inverse opal” processing technique to create synthetic scaffolds by crosslinking poly(ethylene glycol) at different densities (controlling matrix elastic moduli or stiffness) and small doses of a heterobifunctional monomer (controlling matrix adhesivity) around templating beads of different radii. As pore diameter was varied from 7 to 17 µm (i.e., from significantly smaller than the spherical cell diameter to approximately cell diameter), it displayed a profound effect on migration of these stem cells—including the degree to which motility was sensitive to changes in matrix stiffness and adhesivity. Surprisingly, the highest probability for substantive cell movement through pores was observed for an intermediate pore diameter, rather than the largest pore diameter, which exceeded cell diameter. The relationships between migration speed, displacement, and total path length were found to depend strongly on pore diameter. We attribute this dependence to convolution of pore diameter and void chamber diameter, yielding different geometric environments experienced by the cells within. Bioeng. 2011; 108:1181–1193(National Institute of General Medical Sciences (U.S.) (NRSA Fellowship GM083472)National Institutes of Health (U.S.) (National Institute of General Medical Sciences (U.S.) Cell Migration Consortium Grant GM064346)National Science Foundation (U.S.) (CAREER CBET-0644846

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller–Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated

The Effect of Community Pharmacy–Based Interventions on Patient Health Outcomes: A Systematic Review

Many studies have demonstrated the beneficial effects that pharmacist-provided patient care services can have on patient health outcomes. However, the effectiveness of patient care services delivered by pharmacists in community pharmacy settings, where organizational barriers may affect service implementation or limit effectiveness, remains unclear. The authors systematically reviewed the literature on the effectiveness of pharmacist-delivered patient care services in community pharmacy settings in the United States. Of the 749 articles retrieved, 21 were eligible for inclusion in the review. Information concerning 134 outcomes was extracted from the included articles. Of these, 50 (37.3%) demonstrated statistically significant, beneficial intervention effects. The percentage of studies reporting favorable findings ranged from 50% for blood pressure to 0% for lipids, safety outcomes, and quality of life. Our findings suggest that evidence supporting the effectiveness of pharmacist-provided direct patient care services delivered in the community pharmacy setting is more limited than in other settings

Effectiveness and Safety of Dabigatran and Warfarin in Real-World US Patients With Non-Valvular Atrial Fibrillation: A Retrospective Cohort Study

BackgroundThe recent availability of dabigatran, a novel oral anticoagulant, provided a new treatment option for stroke prevention in atrial fibrillation beyond warfarin, the main therapy for years. Little is known about their real‐world comparative effectiveness and safety, even less among patient demographic and clinical subgroups.Methods and ResultsUsing a cohort of non‐valvular AF patients initiating anticoagulation from October 2010 to December 2012 drawn from a large US database of commercial and Medicare supplement claims, we applied propensity score weights to Cox proportional hazards regression to assess the comparative effectiveness and safety of dabigatran versus warfarin. Analyses were repeated among clinical and demographic subgroups using stratum‐specific propensity scores as an exploratory analysis. Of the 64 935 patients initiating anticoagulation, 32.5% used dabigatran. Compared with warfarin, dabigatran was associated with a lower risk of ischemic stroke or systemic embolism (composite adjusted Hazard Ratio [aHR], 95% CI: 0.86, 95% CI: 0.79 to 0.93), hemorrhagic stroke (aHR: 0.51, 0.40 to 0.65), and acute myocardial infarction (aHR: 0.88, 95% CI: 0.77 to 0.99), and no relation was seen between dabigatran and the composite harm outcome (aHR: 0.94, 95% CI: 0.87 to 1.01). However, dabigatran was associated with a higher risk of gastrointestinal bleeding (aHR: 1.11, 95% CI: 1.02 to 1.22). Estimates of effectiveness and safety appeared to be mostly similar across subgroups.ConclusionsDabigatran could be a safe and potentially more effective alternative to warfarin in patients with atrial fibrillation managed in routine practice settings

Quantitative Systems Pharmacology Approaches Applied to Microphysiological Systems (MPS): Data Interpretation and Multi-MPS Integration

Our goal in developing Microphysiological Systems (MPS) technology is to provide an improved approach for more predictive preclinical drug discovery via a highly integrated experimental/computational paradigm. Success will require quantitative characterization of MPSs and mechanistic analysis of experimental findings sufficient to translate resulting insights from in vitro to in vivo. We describe herein a systems pharmacology approach to MPS development and utilization that incorporates more mechanistic detail than traditional pharmacokinetic/pharmacodynamic (PK/PD) models. A series of studies illustrates diverse facets of our approach. First, we demonstrate two case studies: a PK data analysis and an inflammation response––focused on a single MPS, the liver/immune MPS. Building on the single MPS modeling, a theoretical investigation of a four-MPS interactome then provides a quantitative way to consider several pharmacological concepts such as absorption, distribution, metabolism, and excretion in the design of multi-MPS interactome operation and experiments.United States. Defense Advanced Research Projects Agency. Microphysiological Systems Program (W911NF-12-2-0039)National Institutes of Health (U.S.) Microphysiological Systems Program (4-UH3-TR000496-03)Massachusetts Institute of Technology. Center for Environmental Health Sciences (NIEHS Grant P30-ES002109

Tumor Cell-Driven Extracellular Matrix Remodeling Drives Haptotaxis during Metastatic Progression

Fibronectin (FN) is a major component of the tumor microenvironment, but its role in promoting metastasis is incompletely understood. Here we show that FN gradients elicit directional movement of breast cancer cells, in vitro and in vivo. Haptotaxis on FN gradients requires direct interaction between α5β1 integrin and Mena, an actin regulator, and involves increases in focal complex signaling and tumor-cell-mediated extracellular matrix (ECM) remodeling. Compared to Mena, higher levels of the pro-metastatic MenaINV isoform associate with α5, which enables 3D haptotaxis of tumor cells towards the high FN concentrations typically present in perivascular space and in the periphery of breast tumor tissue. MenaINV and FN levels were correlated in two breast cancer cohorts, and high levels of MenaINV were significantly associated with increased tumor recurrence as well as decreased patient survival. Our results identify a novel tumor-cell-intrinsic mechanism that promotes metastasis through ECM remodeling and ECM guided directional migration

3D time series analysis of cell shape using Laplacian approaches

Background: Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes. Results: We present a framework for 3D+time cell shape analysis. The main contribution is three-fold: First, we develop a fast, automatic random walker method for cell segmentation. Second, a novel topology fixing method is proposed to fix segmented binary volumes without spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil cells. Conclusions: The method we propose for cell segmentation is faster than the traditional random walker method or the level set method, and performs better on 3D time-series of neutrophil cells, which are comparatively noisy as stacks have to be acquired fast enough to account for cell motion. Our method for topology fixing outperforms the tools provided by SPHARM-MAT and SPHARM-PDM in terms of their successful fixing rates. The different tasks in the presented pipeline for 3D+time shape analysis of cells can be solved using Laplacian approaches, opening the possibility of eventually combining individual steps in order to speed up computations

Rationale and design of the Novel Uses of adaptive Designs to Guide provider Engagement in Electronic Health Records (NUDGE-EHR) pragmatic adaptive randomized trial: a trial protocol

Background: The prescribing of high-risk medications to older adults remains extremely common and results in potentially avoidable health consequences. Efforts to reduce prescribing have had limited success, in part because they have been sub-optimally timed, poorly designed, or not provided actionable information. Electronic health record (EHR)-based tools are commonly used but have had limited application in facilitating deprescribing in older adults. The objective is to determine whether designing EHR tools using behavioral science principles reduces inappropriate prescribing and clinical outcomes in older adults. Methods: The Novel Uses of Designs to Guide provider Engagement in Electronic Health Records (NUDGE-EHR) project uses a two-stage, 16-arm adaptive randomized pragmatic trial with a “pick-the-winner” design to identify the most effective of many potential EHR tools among primary care providers and their patients ≥ 65 years chronically using benzodiazepines, sedative hypnotic (“Z-drugs”), or anticholinergics in a large integrated delivery system. In stage 1, we randomized providers and their patients to usual care (n = 81 providers) or one of 15 EHR tools (n = 8 providers per arm) designed using behavioral principles including salience, choice architecture, or defaulting. After 6 months of follow-up, we will rank order the arms based upon their impact on the trial’s primary outcome (for both stages): reduction in inappropriate prescribing (via discontinuation or tapering). In stage 2, we will randomize (a) stage 1 usual care providers in a 1:1 ratio to one of the up to 5 most promising stage 1 interventions or continue usual care and (b) stage 1 providers in the unselected arms in a 1:1 ratio to one of the 5 most promising interventions or usual care. Secondary and tertiary outcomes include quantities of medication prescribed and utilized and clinically significant adverse outcomes. Discussion: Stage 1 launched in October 2020. We plan to complete stage 2 follow-up in December 2021. These results will advance understanding about how behavioral science can optimize EHR decision support to improve prescribing and health outcomes. Adaptive trials have rarely been used in implementation science, so these findings also provide insight into how trials in this field could be more efficiently conducted. Trial registration: Clinicaltrials.gov (NCT04284553, registered: February 26, 2020