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This article offers a critical review of the literature on how race played into the historical development of pedagogical progressivism in the late-19th and early-20th-century United States. While many historians have focused on the overt/covert racism inherent in much of progressive pedagogy as espoused by White educators, others have highlighted the ways in pedagogical progressivism supported movements toward liberation and social justice, especially when taken up by Black educators. Thus, the historical treatment of pedagogical progressivism is becoming more nuanced by incorporating the work of Black scholars, school leaders, curriculum designers, and teachers. [ABSTRACT FROM AUTHOR]

Between 1933 and 1942, the Civilian Conservation Corps (CCC) enrolled 2.5 million young men, putting them to work on public lands in relief projects meant to combat the economic and social devastation of the Great Depression. African Americans accounted for roughly 10 percent of these enrollees; however, their experiences were often defined by discrimination in selection and segregation throughout their service. Nevertheless, Black enrollees continuously looked for ways to gain more than the food, lodging, and dollar a day in salary that the corps offered to recruits. A crucial means to this end was the educational program in the camps. One of few facets of the corps in which African Americans had the chance to lead, the educational programs in segregated CCC camps were shaped by Black educational advisers who worked with their enrollees to build programs that reflected a commitment to racial pride and uplift. This article draws on federal records, camp newspapers, photographs, and personal correspondence to elucidate the educational impact of the CCC on Black Americans. [ABSTRACT FROM AUTHOR]

The first compartmental computer models of brain neurons using the Rall method predicted novel and unexpected dendrodendritic interactions between mitral and granule cells in the olfactory bulb. We review the models from a 50-year perspective on the work that has challenged, supported, and extended the original proposal that these interactions mediate both lateral inhibition and oscillatory activity, essential steps in the neural basis of olfactory processing and perception. We highlight strategies behind the neurophysiological experiments and the Rall methods that enhance the ability of detailed compartmental modeling to give counterintuitive predictions that lead to deeper insights into neural organization at the synaptic and circuit level. The application of these methods to mechanisms of neurogenesis and plasticity are exciting challenges for the future. [ABSTRACT FROM AUTHOR]

Cardiac morbidity and mortality increases with the population age. To investigate the underlying pathological mechanisms, and suggest new ways to reduce clinical risks, computational approaches complementing experimental and clinical investigations are becoming more and more important. Here we explore the possible processes leading to the occasional onset and termination of the (usually) non-fatal arrhythmias widely observed in the heart. Using a computational model of a two-dimensional network of cardiac cells, we tested the hypothesis that an ischemia alters the properties of the gap junctions inside the ischemic area. In particular, in agreement with experimental findings, we assumed that an ischemic episode can alter the gap junctions of the affected cells by reducing their average conductance. We extended these changes to include random fluctuations with time, and modifications in the gap junction rectifying conductive properties of cells along the edges of the ischemic area. The results demonstrate how these alterations can qualitatively give an account of all the main types of non-fatal arrhythmia observed experimentally, and suggest how premature beats can be eliminated in three different ways: a) with a relatively small surgical procedure, b) with a pharmacological reduction of the rectifying conductive properties of the gap-junctions, and c) by pharmacologically decreasing the gap junction conductance. In conclusion, our model strongly supports the hypothesis that non-fatal arrhythmias can develop from post-ischemic alteration of the electrical connectivity in a relatively small area of the cardiac cell network, and suggests experimentally testable predictions on their possible treatments. [ABSTRACT FROM AUTHOR]

Abstract: We present an algorithm to form watertight 3D surfaces consistent with the point-and-diameter based neuronal morphology descriptions widely used with spatial electrophysiology simulators. Such morphology descriptions are readily available online and may come from light-microscopy tracings or from an artificial cell grown algorithmically. These files contain only limited information about a neuron's full three-dimensional shape, as they consist mostly of a list of points and diameters with connectivity data. This representation is well-suited for electrophysiology simulations, where the space constants are larger than geometric ambiguities. However, the simple interpretations used for pure electrophysiological simulation produce geometries unsuitable for multi-scale models that also involve three-dimensional reaction–diffusion, as such models have smaller space constants. Although one cannot exactly reproduce an original neuron's full shape from point-and-diameter data, our new constructive tessellated neuronal geometry (CTNG) algorithm uses constructive solid geometry to define a plausible reconstruction without gaps or cul-de-sacs. CTNG then uses “constructive cubes” to produce a watertight triangular mesh of the neuron surface, suitable for use in reaction–diffusion simulations. CTNG provides the correspondence between internal voxels and surface triangles, needed to make connections between cytoplasmic and membrane mechanisms. Optimization of the underlying marching cubes algorithm and distance calculations enhanced the performance of constructive cubes for a neuronal geometry, where a large number of small objects sparsely occupy a large volume. [Copyright &y& Elsevier]

Background: Reports of kidney transplantation from donation after cardiac death (DCD) donors describe high rates of delayed graft function (DGF). Study Design: From April 1, 2003 to October 17, 2010, we performed 134 kidney transplants from DCD donors including 120 (90%) from standard-criteria donors (SCDs) and 14 (10%) from expanded-criteria donors (ECDs). Nineteen kidneys were recovered from donors managed with extracorporeal interval support for organ retrieval (EISOR) after cardiac arrest to minimize ischemic injury. Results: Comparison of donor and recipient characteristics found no differences for cases managed with or without EISOR. Overall actuarial patient survival rates were 93%, 91%, and 89% at 1, 3, and 5 years, respectively, with a mean follow-up of 31 months. Overall actuarial kidney graft survival rates were 89%, 76%, and 76% at 1, 3, and 5 years, respectively. Actuarial graft survival rates of DCD ECD kidneys were 58% and 48% at 1 and 3 years, compared with 90% and 79% at 1 and 3 years for non-ECD grafts (p = 0.013). DGF occurred in 73 patients (54%) overall and was reduced from 55% to 21% (p = 0.016) with the use of EISOR in locally recovered kidneys. The mean resistance value on machine perfusion and the mean estimated glomerular filtration rate 1 month after transplantation were both improved (p < 0.05) in kidneys from donors managed with EISOR. Mean initial hospital stay was reduced from 8.0 to 5.0 days in patients receiving kidneys recovered with EISOR (p = 0.04). Conclusions: EISOR is associated with a lower rate of DGF, lower graft resistance on machine perfusion, and shorter initial hospitalization. Kidneys from DCD SCDs have excellent medium-term outcomes and represent an important means of expanding the donor pool. Kidneys from DCD ECDs have inferior outcomes. [ABSTRACT FROM AUTHOR]

Realistic neural networks involve the coexistence of stiff, coupled, continuous differential equations arising from the integrations of individual neurons, with the discrete events with delays used for modeling synaptic connections. We present here an integration method, the local variable time-step method (lvardt), that uses separate variable-step integrators for individual neurons in the network. Cells that are undergoing excitation tend to have small time steps, and cells that are at rest with little synaptic input tend to have large time steps. A synaptic input to a cell causes reinitialization of only that cell's integrator without affecting the integration of other cells. We illustrated the use of lvardt on three models: a worst-case synchronizing mutual-inhibition model, a best-case synfire chain model, and a more realistic thalamocortical network model. [ABSTRACT FROM AUTHOR]

Objective: Our aim was to simulate the spread of membrane potential changes in microvascular trees and then make the simulation programs accessible to other researchers. We have applied our simulations to demonstrate the implications of electrical coupling between arteriolar smooth muscle and endothelium. Methods: A two-layered, cable-like model of an arteriole was used, and the assumptions involved in the approach explicitly stated. Several common experimental situations that involve the passive spread of membrane potential changes in microvascular trees were simulated. The calculations were performed using NEURON, a well-established computer simulation program that we have modified for use with vascular trees. Results: Simulated results show that membrane potential changes would probably not spread as far in the endothelium as they would in the smooth muscle of arterioles. Where feed arteries are connected to larger distributing arteries, passive spread alone may not explain the physiologically observed spread of diameter changes. Conclusions: Simulated results suggest that the morphology of an arteriole, in which the muscle layer is much thicker than the endothelium, favors electrical conduction along smooth muscle rather than the endothelium. However, it seems that passive electrical spread is insufficient to explain the apparent spread of membrane potential changes in experimental situations. Active responses involving voltage-dependent conductances may be involved, and these can also be included in our simulation. [ABSTRACT FROM AUTHOR]

Microbubbles have several applications in gas-liquid contacting operations. Conventional production of microbubbles is energetically unfavourable since surface energy required to generate the bubbles is inversely proportional to the size of the bubble generated. Fluidic oscillators have demonstrated a size decrease for a system with high throughput and low energetics but the achievable bubble size is limited due to coalescence. The hypothesis of this paper is that this limitation can be overcome by modifying bubble formation dynamics mediated by oscillatory flow. Frequency and amplitude are two easily controlled factors in oscillatory flow. The bubble can be formed at the displacement phase of the frequency cycle if the amplitude is sufficient to detach the bubble. If the frequency is too low, the conventional steady flow detachment mechanism occurs instead; if the frequency is too high, the bubbles coalesce. Our hypothesis proposes the existence of a resonant mode or 'sweet-spot' condition, via frequency modulation and increase in amplitude, to reduce coalescence and produce smallest bubble size with no additional energy input. This condition is identified for an exemplar system showing relative size changes, and a bubble size reduction from 650 µm for steady flow, to 120 µm for oscillatory-flow, and 60 µm for resonant condition (volume average) and 250 µm for steady-flow, 15 µm for oscillatory-flow, 7 µm for the resonant condition. A 10-fold reduction in bubble size with minimal increase in associated energetics results in a substantial reduction in energy requirements for all processes involving gas-liquid operations. The reduction in the energetic footprint of this method has widespread ramifications in all gas-liquid contacting operations including but not limited to wastewater aeration, desalination, flotation separation operations, and other operations. [ABSTRACT FROM AUTHOR]

Bullet embolus is a rare complication of penetrating missile injury in children with only a handful of case reports. We describe a seven year old with a venous bullet embolus to the right ventricle. [ABSTRACT FROM AUTHOR]

For spiking neural network simulations on parallel machines, interprocessor spike communication can be a significant portion of the total simulation time. The simplest spike exchange method is to alternately integrate the cell equations for the minimum spike delay interval between spike initiation and spike delivery, and, at the end of the interval, send all spikes generated in the interval to all processors using the standard Message Passsing Interface MPI_Allgather operation. Given that a source cell is typically connected to thousands of target cells in large network models, the MPI_Allgather method is very effective on supercomputer clusters with thousands of processors. However, as the number of available processors becomes much larger than the cell-to-cell fanout, more complication point-to-point exchange methods should become faster than MPI_Allgather. The Blue Gene/P supercomputer provides direct memory access (DMA) interprocessor communication across the 3- D torus network connecting adjacent quad-core nodes. The DMA controller accepts a list of destination processors and transfer takes place in the background without affecting normal CPU computation speed. The Deep Computing Messaging Framework (DCMF) provides an API to use this feature which is initiated by the function DCMF_Multicast. With DCMF_Multicast, a spike message consists of a double precision spike initiation time and a long integer global source cell identifier. DCMF_Multicast is called when a cell fires and computation continues. In order to allow a substantial time interval between the time a multicase is initiated and the time that the spikes must be received before computation can continue on the target machines, the minimum delay interval is divided into alternating even and odd intervals. This a multicast initiated in an even interval does not have to complete until the end of the following odd interval. At the end of an interval, a spike conservation loop using MPI_Allreduce is used to guarantee that the number of spikes received at the end of the current interval is equal to the number of spikes sent in the previous interval. In this way, as long as half-delay interval computation time is longer than the multicast transfer time, transfer time should not contribute to the overall runtime and the only communication portions that increase the runtime consist of the initiation of the multicast, the handling of received spikes, and the MPI_Allreduce latency. We compared the performance of MPI_Allgather and DCMF_Multicast spike exchange methods using 256 K artificial cell text models with each cell randomly spiking every 10-20 ms. One model had each cell randomly connected to 1 K target cells and the other model used 10 K connections per cell. To minimize MPI_Allgather commu nication time, the MPI_Allgather buffer size was set large enough so that overflow spikes requiring a subsequent MPI_Allgather collecting was rarely or never necessary. Furthermore, because there are fewer than 256 integration steps per minimum delay interval and fewer than 256 neurons per processor, the MPI_Allgather method can usefully compress each (spiketime, gid) pair from 12-2 bytes, reducing the constant payload to a minimum. Of course, spike compression provides no benefit with the DCMF_Multicast method since a single (spiketime, gid) pair fits into the 16 byte msginfo field of a minimum size 32 byte header packet and requires no receive callback to assemble the message data. With the 1 K connectivity text model, the turnover point where the DCMF_Multicast method has less runtime that MPI_Allgather is 16 K cores. This unexpectedly large size is primarily due to the computation time noise introduced by the small random number of DCMF_Multicast calls on a core during the half -- interval.… [ABSTRACT FROM AUTHOR]

Purpose The college of pharmacy has operated pharmacies on campus for over 26 years. Employees and patients are users of the pharmacies; however, utilization across the campus has been limited. This paper describes a process, as well as results, that was used to gather input from employees on a large university health sciences center campus on pharmacy needs and related behaviors on campus pharmacy utilization. Methods Two focus groups of staff and 4 focus groups of prescribers were conducted over 1 month. Participants were selected through purposive sampling via email within an academic health sciences center campus over a 1-month period. The sessions were moderated by one investigator using a preconstructed discussion guide and lasted 1 hour. Two additional investigators observed sessions for nonverbal communication; all sessions were audio recorded for subsequent transcription. An open-coding process was performed on verbatim transcripts using NVivo12. The investigator team then developed, refined, and grouped themes during subsequent group discussions. Results A total of 44 participants took part in 6 focus groups. Participants included prescribers (physicians, nurses, physician assistants) and staff (nonprescribers). Two major themes identified were (1) factors related to on-campus pharmacies and (2) qualities valued in a pharmacy. There was an equal split (8% for each group) on awareness of the on-campus pharmacies. Almost 11% of participants commented on the accessibility of a pharmacy being a quality valued in a pharmacy. Conclusion Focus groups provided insights for the administration team regarding additional value-added services that would be helpful for the campus community, as well as various approaches to increase utilization of the on-campus pharmacies. Focus group methodology is an effective approach to engage employees of a large university campus to garner new ideas to enhance existing policies or services, as well as to gather thoughts on preliminary strategic plans before implementation. [ABSTRACT FROM AUTHOR]

The article presents a study on the use of Bayesian filtering in estimating the log-likelihood function of neuron simulation environment parameter. It states that Bayesian filtering includes particle filter and kalman filter. Furthermore, the Bayes rule method selects the optimal tradeoff between process noise and measurement noise. The method allows the user to understand how the standard deviations are modified by the Bayes rule.

The precise mechanism by which synaptic excitation and inhibition interact with each other in odor coding through the unique dendrodendritic synaptic microcircuits present in olfactory bulb is unknown. Here a scaled-up model of the mitral- granule cell network in the rodent olfactory bulb is used to analyze dendrodendritic processing of experimentally determined odor patterns. We found that the interaction between excitation and inhibition is responsible for two fundamental computational mechanisms: (1) a balanced excitation/ inhibition in strongly activated mitral cells, leading to a sparse representation of odorant input, and (2) an unbalanced excitation/ inhibition (inhibition dominated) in surrounding weakly activated mitral cells, leading to lateral inhibition. These results suggest how both mechanisms can carry information about the input patterns, with optimal level of synaptic excitation and inhibition producing the highest level of sparseness and decorrelation in the network response. The results suggest how the learningprocess, through the emergent development of these mechanisms, can enhance odor representation of olfactory bulb. [ABSTRACT FROM AUTHOR]

In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and generation of testable hypotheses of the functional mechanisms underlying odor representation in the olfactory bulb circuit. Specifically, we demonstrate that lateral inhibition emerges within the olfactory bulb network through recurrent dendrodendritic synapses when constrained by a range of balanced excitatory and inhibitory conductances. We find that the spatio-temporal dynamics of lateral inhibition plays a critical role in building the glomerular-related cell clusters observed in experiments, through the modulation of synaptic weights during odor training. Lateral inhibition also mediates the development of sparse and synchronized spiking patterns of mitral cells related to odor inputs within the network, with the frequency of these synchronized spiking patterns also modulated by the sniff cycle. [ABSTRACT FROM AUTHOR]

Abstract: In an effort to design a simulation environment that is more similar to that of neurophysiology, we introduce a virtual slice setup in the NEURON simulator. The virtual slice setup runs continuously and permits parameter changes, including changes to synaptic weights and time course and to intrinsic cell properties. The virtual slice setup permits shocks to be applied at chosen locations and activity to be sampled intra- or extracellularly from chosen locations. By default, a summed population display is shown during a run to indicate the level of activity and no states are saved. Simulations can run for hours of model time, therefore it is not practical to save all of the state variables. These, in any case, are primarily of interest at discrete times when experiments are being run: the simulation can be stopped momentarily at such times to save activity patterns. The virtual slice setup maintains an automated notebook showing shocks and parameter changes as well as user comments. We demonstrate how interaction with a continuously running simulation encourages experimental prototyping and can suggest additional dynamical features such as ligand wash-in and wash-out—alternatives to typical instantaneous parameter change. The virtual slice setup currently uses event-driven cells and runs at approximately 2min/h on a laptop. [Copyright &y& Elsevier]

Background: Most reports of donation after cardiac death (DCD) donors are exclusive to kidney transplantation and report high rates of delayed graft function (DGF). Study Design: From April 1, 2003, to October 3, 2007, we performed 53 kidney transplantations and 4 simultaneous kidney-pancreas transplantations from DCD donors. All DCD donor kidneys were managed with pulsatile perfusion preservation, and all simultaneous kidney-pancreas transplantation donors were managed with extracorporeal support. Results: Of 53 DCD kidney transplantations, 44 (83%) were from standard criteria donors (SCD) and 9 (17%) from expanded criteria donors (ECD). With a mean followup of 12 months, actual patient and kidney graft survival rates were 94% and 87%, respectively. Patient and graft survival rates were 100% in the 4 simultaneous kidney-pancreas transplantations. Incidence of DGF was 57% (60% without versus 20% with extracorporeal support, p = 0.036). Comparison of the 53 DCD donor kidney transplantations with 316 concurrent donation after brain death (DBD) donor adult kidney transplantations (178 SCD, 138 ECD) revealed no differences in demographics or outcomes, except that the DCD donor group had fewer ECDs (17% DCD versus 44% DBD; p = 0.0002), fewer 0-antigen mismatch kidney transplantations (7.5% DCD versus 19% DBD; p = 0.05), and more kidneys preserved with pulsatile perfusion (100% DCD versus 52% DBD; p < 0.0001). Incidences of DGF (57% DCD versus 19% DBD; p < 0.0001) and acute rejection (19% DCD versus 10% DBD; p = 0.10) were higher in the DCD donor group, which resulted in a longer initial length of stay (mean 11 days DCD versus 8.0 days DBD; p = 0.006). Conclusions: Despite a high incidence of DGF in the absence of extracorporeal support and greater initial resource use, comparable short-term results can be achieved with DCD and DBD donor kidney transplantations. [Copyright &y& Elsevier]

Dendritic spikes in thin dendritic branches (basal and oblique dendrites) are traditionally inferred from spikelets measured in the cell body. Here, we used laser-spot voltage-sensitive dye imaging in cortical pyramidal neurons (rat brain slices) to investigate the voltage waveforms of dendritic potentials occurring in response to spatially restricted glutamatergic inputs. Local dendritic potentials lasted 200-500 ms and propagated to the cell body, where they caused sustained 10- to 20-mV depolarizations. Plateau potentials propagating from dendrite to soma and action potentials propagating from soma to dendrite created complex voltage waveforms in the middle of the thin basal dendrite, comprised of local sodium spikelets, local plateau potentials, and backpropagating action potentials, superimposed on each other. Our model replicated these voltage waveforms across a gradient of glutamatergic stimulation intensities. The model then predicted that somatic input resistance (Rin) and membrane time constant (tau) may be reduced during dendritic plateau potential. We then tested these model predictions in real neurons and found that the model correctly predicted the direction of Rin and tau change but not the magnitude. In summary, dendritic plateau potentials occurring in basal and oblique branches put pyramidal neurons into an activated neuronal state ("prepared state"), characterized by depolarized membrane potential and smaller but faster membrane responses. The prepared state provides a time window of 200-500 ms, during which cortical neurons are particularly excitable and capable of following afferent inputs. At the network level, this predicts that sets of cells with simultaneous plateaus would provide cellular substrate for the formation of functional neuronal ensembles. [ABSTRACT FROM AUTHOR]

Background: Industrial biotechnology will play an increasing role in creating a more sustainable global economy. For conventional aerobic bioprocesses supplying O2 can account for 15% of total production costs. Microbubbles (MBs) are micron-sized bubbles that are widely used in industry and medical imaging. Using a fluidic oscillator to generate energy-efficient MBs has the potential to decrease the costs associated with aeration. However, little is understood about the effect of MBs on microbial physiology. To address this gap, a laboratory-scale MB-based Saccharomyces cerevisiae Ethanol Red propagation–fermentation bioethanol process was developed and analysed. Results: Aeration with MBs increased O2 transfer to the propagation cultures. Titres and yields of bioethanol in subsequent anaerobic fermentations were comparable for MB-propagated and conventional, regular bubble (RB)-propagated yeast. However, transcript profiling showed significant changes in gene expression in the MB-propagated yeast compared to those propagated using RB. These changes included up-regulation of genes required for ergosterol biosynthesis. Ergosterol contributes to ethanol tolerance, and so the performance of MB-propagated yeast in fed-batch fermentations sparged with 1% O2 as either RBs or MBs were tested. The MB-sparged yeast retained higher levels of ergosteryl esters during the fermentation phase, but this did not result in enhanced viability or ethanol production compared to ungassed or RB-sparged fermentations. Conclusions: The performance of yeast propagated using energy-efficient MB technology in bioethanol fermentations is comparable to that of those propagated conventionally. This should underpin the future development of MB-based commercial yeast propagation. [ABSTRACT FROM AUTHOR]

Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN’s core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal’s origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN’s ability to associate signals across scales makes it a unique tool for translational neuroscience research. [ABSTRACT FROM AUTHOR]

Large multiscale neuronal network simulations are of increasing value as more big data are gathered about brain wiring and organization under the auspices of a current major research initiative, such as Brain Research through Advancing Innovative Neurotechnologies. The development of these models requires new simulation technologies. We describe here the current use of the NEURON simulator with message passing interface (MPI) for simulation in the domain of moderately large networks on commonly available high-performance computers (HPCs). We discuss the basic layout of such simulations, including the methods of simulation setup, the run-time spike-passing paradigm, and postsimulation data storage and data management approaches. Using the Neuroscience Gateway, a portal for computational neuroscience that provides access to large HPCs, we benchmark simulations of neuronal networks of different sizes (500-100,000 cells), and using different numbers of nodes (1-256).We compare three types of networks, composed of either Izhikevich integrate-and-fire neurons (I&F), single-compartment Hodgkin- Huxley (HH) cells, or a hybrid network with half of each. Results show simulation run time increased approximately linearly with network size and decreased almost linearly with the number of nodes. Networks with I&F neurons were faster than HH networks, although differences were small since all tested cells were point neurons with a single compartment. [ABSTRACT FROM AUTHOR]

Calcium (Ca2+) waves provide a complement to neuronal electrical signaling, forming a key part of a neuron's second messenger system. We developed a reaction-diffusion model of an apical dendrite with diffusible inositol triphosphate (IP3), diffusible Ca2+, IP3 receptors (IP3Rs), endoplasmic reticulum (ER) Ca2+ leak, and ER pump (SERCA) on ER. Ca2+ is released from ER stores via IP3Rs upon binding of IP3 and Ca2+. This results in Ca2+-induced-Ca2+ -release (CICR) and increases Ca2+ spread. At least two modes of Ca2+ wave spread have been suggested: a continuous mode based on presumed relative homogeneity of ER within the cell and a pseudo-saltatory model where Ca2+ regeneration occurs at discrete points with diffusion between them. We compared the effects of three patterns of hypothesized IP3R distribution: (1) continuous homogeneous ER, (2) hotspots with increased IP3R density (IP3R hotspots), and (3) areas of increased ER density (ER stacks). All three modes produced Ca2+ waves with velocities similar to those measured in vitro (approximately 50-90 *#956;m /sec). Continuous ER showed high sensitivity to IP3R density increases, with time to onset reduced and speed increased. Increases in SERCA density resulted in opposite effects. The measures were sensitive to changes in density and spacing of IP3R hotspots and stacks. Increasing the apparent diffusion coefficient of Ca2+ substantially increased wave speed. An extended electrochemical model, including voltage-gated calcium channels and AMPA synapses, demonstrated that membrane priming via AMPA stimulation enhances subsequent Ca2+ wave amplitude and duration. Our modeling suggests that pharmacological targeting of IP3Rs and SERCA could allow modulation of Ca2+ wave propagation in diseases where Ca2+ dysregulation has been implicated. [ABSTRACT FROM AUTHOR]

There is a critical need for safer and more convenient treatments for organ transplant rejection and autoimmune disorders such as rheumatoid arthritis. Janus tyrosine kinases (JAK1, JAK3) are expressed in lymphoid cells and are involved in the signaling of multiple cytokines important for various T cell functions. Blockade of the JAK1/JAK3-STAT pathway with a small molecule was anticipated to provide therapeutic immunosuppression/immunomodulation. The Pfizer compound library was screened against the catalytic domain of JAK3 resulting in the identification of a pyrrolopyrimidine-based series of inhibitors represented by CP-352,664 (2a). Synthetic analogues of 2a were screened against the JAK enzymes and evaluated in an IL-2 induced T cell blast proliferation assay. Select compounds were evaluated in rodent efficacy models of allograft rejection and destructive inflammatory arthritis. Optimization within this chemical series led to identification of CP-690,550 1, a potential first-in-class JAK inhibitor for treatment of autoimmune diseases and organ transplant rejection. [ABSTRACT FROM AUTHOR]

Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. While neuronal simulators such as NEURON, GENESIS, MOOSE, NEST, and PSICS facilitate the development of these data-driven neuronal models, the specialized languages they employ are generally not interoperable, limiting model accessibility and preventing reuse of model components and cross-simulator validation. To overcome these problems we have used an Open Source software approach to develop NeuroML, a neuronal model description language based on XML (Extensible Markup Language). This enables these detailed models and their components to be defined in a standalone form, allowing them to be used across multiple simulators and archived in a standardized format. Here we describe the structure of NeuroML and demonstrate its scope by converting into NeuroML models of a number of different voltage- and ligand-gated conductances, models of electrical coupling, synaptic transmission and short-term plasticity, together with morphologically detailed models of individual neurons. We have also used these NeuroML-based components to develop an highly detailed cortical network model. NeuroML-based model descriptions were validated by demonstrating similar model behavior across five independently developed simulators. Although our results confirm that simulations run on different simulators converge, they reveal limits to model interoperability, by showing that for some models convergence only occurs at high levels of spatial and temporal discretisation, when the computational overhead is high. Our development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience. [ABSTRACT FROM AUTHOR]

As a result of the ever widening disparity between organ supply and demand, a resurgence of interest has occurred in kidney recovery from donation after cardiac death (DCD) donors. New techniques of in situ extracorporeal support offer the potential to reduce warm ischemic injury and optimize donor management prior to organ recovery. In addition, preliminary outcomes using kidneys from selected deceased donors with rising serum creatinine levels have been promising. However, contraindications to successful organ donation and transplantation may include the presence of abdominal compartment syndrome, generalized bowel infarction, refractory shock with profound metabolic and lactic acidosis, and acute anuric renal failure, particularly in the setting of DCD. We report herein the successful recovery and transplantation of kidneys from an unstable donor with the above constellation of conditions in the setting of extracorporeal support after declaration of death by asystole. [ABSTRACT FROM AUTHOR]

The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON's standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that added items to the queue only when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run. [ABSTRACT FROM AUTHOR]

We present a patient who was found to have constrictive pericarditis 6 months after cardiac allograft transplantation. The many invasive and non-invasive diagnostic procedures that were undertaken are reviewed, as is the gross pathology seen during surgery. In addition, the entity of constriction in the transplant patient is placed in context by an examination of the previous literature. [Copyright &y& Elsevier]

Behcet’s disease is a rare autoimmune vasculitis characterized by oral aphthosis, genital ulcers, and ocular and cutaneous lesions. Vascular involvement usually affects the veins more commonly than the arteries, and coronary arterial involvement is extremely rare. We report an adolescent with Behcet’s disease who developed a large pseudoaneurysm of the left anterior descending coronary artery requiring a coronary arterial bypass graft. [ABSTRACT FROM AUTHOR]

An abstract of the article "Reaction-diffusion modeling in the NEURON simulator," by Robert A. McDougal, Yosef Skolnick, James C. Schaff, William W. Lytton, and Michael L. Hines is presented.

An abstract of the article "Extracorporeal Life Support Improves Survival in Adult Trauma Patients With Severe Respiratory Failure: A Multicenter Retrospective Cohort Study" by Derek Guirand and colleagues is presented.