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Dendritic cells (DCs) are the most effective professional antigen-presenting cell. They ferry antigen from the extremities to T cells and are essential for the initiation of an adaptive immune response. Despite interest in how DCs respond to chemical stimuli, there have been few attempts to model DC migration. In this paper, we simulate the motility of DCs by modeling the generation of forces by filopodia and a force balance on the cell. The direction of fliopodial extension is coupled to differential occupancy of cognate chemokine receptors across the cell. Our model simulates chemokinesis and chemotaxis in a variety of chemical and mechanical environments. Simulated DCs undergoing chemokinesis were measured to have a speed of 5.1 ± 0.07 μm·min-1 and a persistence time of 3.2 ± 0.46 min, consistent with experiment. Cells undergoing chemotaxis exhibited a stronger chemotactic response when exposed to lower average chemokine concentrations, also consistent with experiment. We predicted that when placed in two opposing gradients, cells will cluster in a line, which we call the “line of equistimulation;” this clustering has also been observed. We calculated the effect of varying gradient steepness on the line of equistimulation, with steeper gradients resulting in tighter clustering. Moreover, gradients are found to be most potent when cells are in a gradient of chemokine whose mean concentration is close to the binding of the Kd to the receptor, and least potent when the mean concentration is 0.1Kd. Comparing our simulations to experiment, we can give a quantitative measure of the strength of certain chemokines relative to others. Assigning the signal of CCL19 binding CCR7 a baseline strength of 1, we found CCL21 binding CCR7 had a strength of 0.28, and CXCL12 binding CXCR4 had a strength of 0.30. These differences emerge despite both chemokines having virtually the same Kd, suggesting a mechanism of signal amplification in DCs requiring further study. [ABSTRACT FROM AUTHOR]

Introduction: The leukocyte adhesion cascade is important for the maintenance of homeostasis and the ability of immune cells to access sites of infection and inflammation. Despite much work identifying the molecular components of the cascade, and numerous simulations to predict the relationship between molecule density, identity, and adhesion, these relationships have not been measured experimentally.Methods: Using surfaces functionalized with recombinant ICAM-1 and/or E-selectin along with immobilized SDF-1α, we used a flow chamber to measure rates of tethering, rolling and arrest of primary naïve human CD4+ T lymphocytes on different surface densities of ligand.Results: Cells required a minimum level of ligand density to progress beyond tethering. E-selectin and ICAM-1 were found to have a synergistic relationship in promoting cell arrest. Surfaces with both ligands had the highest levels of arrest, while surfaces containing only E-selectin hindered the cell’s ability to progress beyond rolling. In contrast, surfaces of ICAM-1 allowed only tethering or arrest. Cells maintained constant rolling velocity and time to stop over large variations in surface density and composition. In addition, surface densities of only O(101) sites/µm2 allowed for rolling while surface densities of O(102) sites/µm2 promoted arrest, approximately equal to previously determined simulated values.Conclusions: We have systematically and experimentally mapped out the state diagram of T cell adhesion under flow, directly demonstrating the quantitative requirements for each dynamic state of adhesion, and showing how multiple adhesion molecules can act in synergy to secure arrest. [ABSTRACT FROM AUTHOR]

The agglomeration of ferromagnetic nanoparticles in a fluid is studied using nanoparticle-level Langevin dynamics simulations. The simulations have interdigitation and bridging between ligand coatings included using a computationally-cheap, phenomenological sticking parameter c. The interactions between ligand coatings are shown in this preliminary study to be important in determining the shapes of agglomerates that form. A critical size for the sticking parameter is estimated analytically and via the simulations and indicates where particle agglomerates transition from well-ordered (c is small) to disordered (c is large) shapes. Results are also presented for the hysteresis loops (magnetization versus applied field) for these particle systems in an oscillating magnetic field appropriate for hyperthermia applications. The results show that the clumping of particles has a significant effect on their macroscopic properties, with important consequences on applications. In particular, the work done by an oscillating field on the system has a nonmonotonic dependence on c. [ABSTRACT FROM AUTHOR]

Brain computer interfaces are devices that collect signals from a subject's cortical surface and interpret these signals to control a computer. Recently much development has been done on these devices with the help of epilepsy patients and the clinical staff who treat these patients. The types of data collected from epilepsy patients, particularly the invasive data give a unique opportunity to researchers in this area. The clinical staff has a unique opportunity to use the treatment of one patient population to help another. [ABSTRACT FROM AUTHOR]

Abstract: Two studies demonstrate that negotiation processes and outcomes can be altered by the creation of Positive Expectations. Study 1 participants were American undergraduates seeking agreement with a confederate about allocation of funds to programs differentially favoring undergraduates vs. graduates. Study 2 participants were Israeli Business School students seeking agreement with an Arab confederate about allocation of funds to projects differentially favoring Israelis vs. Palestinians. In both studies prior information suggesting the consistent success of previous dyads prompted acceptance of the confederate’s “final proposal” whereas merely urging participants to try to reach agreement resulted in consistent rejection of the same proposal. Moreover, participants reaching agreement in these Positive Expectations conditions subsequently offered more positive assessments of the negotiation process and of their counterpart than those doing so in control conditions. The theoretical and applied relevance of these findings, including the role played by post-agreement dissonance reduction, are discussed. [Copyright &y& Elsevier]

Electrical signals acquired from the cortical surface, or electrocorticography (EC0G), exhibit high spatial and temporal resolution and are valuable for mapping brain activity, detecting irregularities, and controlling a brain-computer interface. As with scalp-recorded EEG, much of the identified information content in ECoG is manifested as amplitude modulations of specific frequency bands. Autoregressive (AR) spectral estimation has proven successful for modeling the well-defined and comparatively limited EEG spectrum. However, because the ECoG spectrum is significantly more extensive with yet undefined dynamics, it cannot be assumed that the ECoG spectrum can be accurately estimated using the same AR model parameters that are valid for analogous EEG studies. This study provides an offline evaluation of AR modeling of ECoG signals for detecting tongue movements. The resulting model parameters can serve as a reference for related AR spectral analysis of ECoG signals. [ABSTRACT FROM AUTHOR]

The electroencephalogram (EEG) equipment industry has recently been developing systems that display, not only the raw EEG signal, but also a transformed version of the signal that highlights critical features and can be viewed in a more user friendly manner. A computer automated analysis of the signal is a quantitative approach that can make precise temporal measurements of the signal features, perform digital filtering to allow for identification of specific components of the signal, and statistically analyze the resulting signal. These quantitative analyses have created the potential to decrease the time required for EEG reviewers, allow for seizures to be more accurately detected with a simpler metric, and prevent confusion of symptom detection, thus providing for a more effective and efficient diagnosis. Many companies have addressed this opportunity for development and designed systems, each with their own name and features. This article attempts to explain the techniques for signal transformation that are starting to see wide use and point out some of the benefits of this type of interpretation that have been identified in the literature. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To explore how the implementation of a comprehensive new bioinformatics analysis system would affect workflow, collaboration and information management in a small genetic research lab. Design: This was a longitudinal qualitative study of seven individuals involved in genomic and proteomic research. The study data were gathered using the illuminative/responsive approach of immersion in the environment. Additional qualitative data were gathered using informal semi-structured interviews, participant observation in lab meetings, and direct observation of lab researchers engaged in specific tasks. Measurements: Interview, observation and field note data were coded and analyzed based on three analysis perspectives. A subset of the data was independently evaluated by an external researcher to enhance the trustworthiness of results. Results: Three reoccurring themes were observed in the study. (1) Satisfaction and acceptance of software tools tended to be role and goal specific. (2) The system was seen primarily as a measurement system rather than a “total laboratory analysis system”. (3) Lab meetings deemphasized the system, preferring more traditional data analysis techniques. These themes support the observations that the system was not used to its full potential in the lab. Conclusion: Themes identified in this study suggest that sophisticated genetic researchers face similar problems of technology implementation as do professionals in other fields. We recommend that leadership support and on-going training and evolution of academic curricula can improve chances of bioinformatics analysis systems becoming used more effectively. [Copyright &y& Elsevier]

Background: Providing for long-term and consistent public access to scientific data is a growing concern in biomedical research. One aspect of this problem can be demonstrated by evaluating the persistence of supplementary data associated with published biomedical papers. Methods: We manually evaluated 655 supplementary data links extracted from PubMed abstracts published 1998-2005 (Method 1) as well as a further focused subset of 162 full-text manuscripts published within three representative high-impact biomedical journals between September and December 2004 (Method 2). Results: For Method 1 we found that since 2001, only 71 - 92% of supplementary data were still accessible via the links provided, with 93% of these inaccessible links occurring where supplementary data was not stored with the publishing journal. Of the manuscripts evaluated in Method 2, we found that only 83% of these links were available approximately a year after publication, with 55% of these inaccessible links were at locations outside the journal of publication. Conclusion: We conclude that if supplemental data is required to support the publication, journals policies must take-on the responsibility to accept and store such data or require that it be maintained with a credible independent institution or under the terms of a strategic data storage plan specified by the authors. We further recommend that publishers provide automated systems to ensure that supplementary links remain persistent, and that granting bodies such as the NIH develop policies and funding mechanisms to maintain long-term persistent access to these data. [ABSTRACT FROM AUTHOR]

Introduction: The arrest of rolling T lymphocytes at specific locations is crucial to proper immune response function. We previously developed a model of chemokine-driven integrin activation, termed integrative signaling adhesive dynamics (ISAD). In addition, we have shown that loss of diacylglycerol kinase (DGK) leads to a gain of function regarding adhesion under shear flow. We undertook this study to understand the sensitivity of adhesion to perturbations in other signaling molecules. Methods: We adapted multi-parametric sensitivity analysis (MPSA) for use in our ISAD model to identify important parameters, including initial protein concentrations and kinetic rate constants, for T lymphocyte arrest. We also compared MPSA results to those obtained from a single parametric sensitivity analysis. Results: In addition to the previously shown importance of DGK in lymphocyte arrest, PIP2 cleavage and Rap1 activation are crucial in determining T cell arrest dynamics, which agree with previous experimental findings. The l-selectin density on the T lymphocyte surface also plays a large role in determining the distance rolled before arrest. Both the MPSA and single-parametric method returned similar results regarding the most sensitive kinetic rate constants. Conclusion: We show here that the regulation of the amount of second messengers are, in general, more critical for determining T lymphocyte arrest over the initial signaling proteins, highlighting the importance of amplification of signaling in cell adhesion responses. Overall, this work provides a mechanistic insight of the contribution of key pathways and components, thus may help to identify potential therapeutic targets for drug development against immune disorders. [ABSTRACT FROM AUTHOR]

We study nonlinear spin motion in one-dimensional magnetic chains. We find significant differences from the classic Fermi-Pasta-Ulam (FPU) problem examining nonlinear elastic motion in a chain. We find that FPU behavior, the transfer of energy among low order eigenmodes, does not occur in magnetic systems with only exchange and external fields, but does exist if a uniaxial anisotropy is also present. The FPU behavior may be altered or turned off through the magnitude and orientation of an external magnetic field. A realistic micromagnetic model shows such behavior could be measurable. [ABSTRACT FROM AUTHOR]

In the first large study of its kind, we quantified changes in electrocorticographic signals associated with motor movement across 22 subjects with subdural electrode arrays placed for identification of seizure foci. Patients underwent a 5-7 d monitoring period with array placement, before seizure focus resection, and during this time they participated in the study. An interval-based motor-repetition task produced consistent and quantifiable spectral shifts that were mapped on a Talairach-standardized template cortex. Maps were created independently for a high-frequency band (HFB) (76 -100 Hz) and a low-frequency band (LFB) (8 -32 Hz) for several different movement modalities in each subject. The power in relevant electrodes consistently decreased in the LFB with movement, whereas the power in the HFB consistently increased. In addition, the HFB changes were more focal than the LFB changes. Sites of power changes corresponded to stereotactic locations in sensorimotor cortex and to the results of individual clinical electrical cortical mapping. Sensorimotor representation was found to be somatotopic, localized in stereotactic space to rolandic cortex, and typically followed the classic homunculus with limited extrarolandic representation. [ABSTRACT FROM AUTHOR]