Thrombin-induced events in non-platelet cells are mediated by the unique proteolytic mechanism established for the cloned platelet thrombin receptor.

We recently isolated a cDNA clone encoding a functional platelet thrombin receptor that defined a unique mechanism of receptor activation. Thrombin cleaves its receptor's extracellular amino terminal extension, unmasking a new amino terminus that functions as a tethered peptide ligand and activates the receptor. A novel peptide mimicking this new amino terminus was a full agonist for platelet secretion and aggregation, suggesting that this unusual mechanism accounts for platelet activation by thrombin. Does this mechanism also mediate thrombin's assorted actions on non-platelet cells? We now report that the novel thrombin receptor agonist peptide reproduces thrombin-induced events (specifically, phosphoinositide hydrolysis and mitogenesis) in CCL-39 hamster lung fibroblasts, a naturally thrombin-responsive cell line. Moreover, these thrombin-induced events could be recapitulated in CV-1 cells, normally poorly responsive to thrombin, after transfection with human platelet thrombin receptor cDNA. Our data show that important thrombin-induced cellular events are mediated by the same unusual mechanism of receptor activation in both platelets and fibroblasts, very likely via the same or very similar receptors

A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences

Stimulus-specific adaptation (SSA) occurs when the spike rate of a neuron decreases with repetitions of the same stimulus, but recovers when a different stimulus is presented. It has been suggested that SSA in single auditory neurons may provide information to change detection mechanisms evident at other scales (e.g., mismatch negativity in the event related potential), and participate in the control of attention and the formation of auditory streams. This article presents a spiking-neuron model that accounts for SSA in terms of the convergence of depressing synapses that convey feature-specific inputs. The model is anatomically plausible, comprising just a few homogeneously connected populations, and does not require organised feature maps. The model is calibrated to match the SSA measured in the cortex of the awake rat, as reported in one study. The effect of frequency separation, deviant probability, repetition rate and duration upon SSA are investigated. With the same parameter set, the model generates responses consistent with a wide range of published data obtained in other auditory regions using other stimulus configurations, such as block, sequential and random stimuli. A new stimulus paradigm is introduced, which generalises the oddball concept to Markov chains, allowing the experimenter to vary the tone probabilities and the rate of switching independently. The model predicts greater SSA for higher rates of switching. Finally, the issue of whether rarity or novelty elicits SSA is addressed by comparing the responses of the model to deviants in the context of a sequence of a single standard or many standards. The results support the view that synaptic adaptation alone can explain almost all aspects of SSA reported to date, including its purported novelty component, and that non-trivial networks of depressing synapses can intensify this novelty response

Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp. Author Summary Sensory processing of time-varying stimuli, such as speech, is associated with high-frequency oscillatory cortical activity, the functional significance of which is still unknown. One possibility is that the oscillations are part of a stimulus-encoding mechanism. Here, we investigate a computational model of such a mechanism, a spiking neuronal network whose intrinsic oscillations interact with external input (waveforms simulating short speech segments in a single acoustic frequency band) to encode stimuli that extend over a time interval longer than the oscillation's period. The network implements a temporally sparse encoding, whose robustness to time warping and neuronal noise we quantify. To our knowledge, this study is the first to demonstrate that a biophysically plausible model of oscillations occurring in the processing of auditory input may generate a representation of signals that span multiple oscillation cycles.National Science Foundation (DMS-0211505); Burroughs Wellcome Fund; U.S. Air Force Office of Scientific Researc

Neural Decision Boundaries for Maximal Information Transmission

We consider here how to separate multidimensional signals into two categories, such that the binary decision transmits the maximum possible information transmitted about those signals. Our motivation comes from the nervous system, where neurons process multidimensional signals into a binary sequence of responses (spikes). In a small noise limit, we derive a general equation for the decision boundary that locally relates its curvature to the probability distribution of inputs. We show that for Gaussian inputs the optimal boundaries are planar, but for non-Gaussian inputs the curvature is nonzero. As an example, we consider exponentially distributed inputs, which are known to approximate a variety of signals from natural environment.Comment: 5 pages, 3 figure

Acquired A amyloidosis from injection drug use presenting with atraumatic splenic rupture in a hospitalized patient: a case report

<p>Abstract</p> <p>Introduction</p> <p>Little is known about splenic rupture in patients who develop systemic acquired A amyloidosis. This is the first report of a case of atraumatic splenic rupture in a patient with acquired A amyloidosis from chronic injection drug use.</p> <p>Case presentation</p> <p>A 58-year-old Caucasian man with a long history of injection drug use, hospitalized for infective endocarditis, experienced atraumatic splenic rupture and underwent splenectomy. Histopathological and microbiological analyses of the splenic tissue were consistent with systemic acquired A amyloidosis, most likely from injection drug use, that led to splenic rupture without any recognized trauma or evidence of bacterial embolization to the spleen.</p> <p>Conclusion</p> <p>In patients with chronic inflammatory conditions, including the use of injection drugs, who experience acute onset of left upper quadrant pain, the diagnosis of atraumatic splenic rupture must be considered.</p

Auditory-Visual Object Recognition Time Suggests Specific Processing for Animal Sounds

cote interne IRCAM: Suied09bNone / NoneNational audienceAuditory-visual object recognition time suggests specific processing for animal sound

Outcome after failure of allogeneic hematopoietic stem cell transplantation in children with acute leukemia: a study by the Société Francophone de Greffe de Moelle et de Thérapie Cellulaire (SFGM-TC)

Allogeneic hematopoietic stem cell transplantation (SCT) contributes to improved outcome in childhood acute leukemia (AL). However, therapeutic options are poorly defined in case of post-transplantation relapse. We aimed to compare treatment strategies in 334 consecutive children with acute leukemia relapse or progression after SCT in a recent ten-year period. Data could be analyzed in 288 patients (157 ALL, 123 AML and 8 biphenotypic AL) with a median age of 8.16 years at transplantation. The median delay from first SCT to relapse or progression was 182 days. The treatment consisted in chemotherapy alone (n=108), chemotherapy followed by second SCT (n=70), supportive/palliative care (n=67), combination of chemotherapy and DLI (n=30), or isolated reinfusion of donor lymphocytes (DLI) (n=13). The median OS duration after relapse was 164 days and differed according to therapy: DLI after chemotherapy = 385 d, second allograft = 391d, chemotherapy = 174d, DLI alone = 140d, palliative care = 43d. A second SCT or a combination of chemotherapy and donor lymphocytes infusion yielded similar outcome (HR=0.85, p=0.53) unlike chemotherapy alone (HR 1.43 p=0.04), palliative care (HR=4.24, p<0.0001) or isolated DLI (HR=1,94, p<0.04). Despite limitations in this retrospective setting, strategies including immunointervention appear superior to other approaches, mostly in AML

Adaptation and Selective Information Transmission in the Cricket Auditory Neuron AN2

Sensory systems adapt their neural code to changes in the sensory environment, often on multiple time scales. Here, we report a new form of adaptation in a first-order auditory interneuron (AN2) of crickets. We characterize the response of the AN2 neuron to amplitude-modulated sound stimuli and find that adaptation shifts the stimulus–response curves toward higher stimulus intensities, with a time constant of 1.5 s for adaptation and recovery. The spike responses were thus reduced for low-intensity sounds. We then address the question whether adaptation leads to an improvement of the signal's representation and compare the experimental results with the predictions of two competing hypotheses: infomax, which predicts that information conveyed about the entire signal range should be maximized, and selective coding, which predicts that “foreground” signals should be enhanced while “background” signals should be selectively suppressed. We test how adaptation changes the input–response curve when presenting signals with two or three peaks in their amplitude distributions, for which selective coding and infomax predict conflicting changes. By means of Bayesian data analysis, we quantify the shifts of the measured response curves and also find a slight reduction of their slopes. These decreases in slopes are smaller, and the absolute response thresholds are higher than those predicted by infomax. Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals. The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant. Less information is transmitted about signals with lower intensity

GABAA-Mediated Inhibition Modulates Stimulus-Specific Adaptation in the Inferior Colliculus

The ability to detect novel sounds in a complex acoustic context is crucial for survival. Neurons from midbrain through cortical levels adapt to repetitive stimuli, while maintaining responsiveness to rare stimuli, a phenomenon called stimulus-specific adaptation (SSA). The site of origin and mechanism of SSA are currently unknown. We used microiontophoretic application of gabazine to examine the role of GABAA-mediated inhibition in SSA in the inferior colliculus, the midbrain center for auditory processing. We found that gabazine slowed down the process of adaptation to high probability stimuli but did not abolish it, with response magnitude and latency still depending on the probability of the stimulus. Blocking GABAA receptors increased the firing rate to high and low probability stimuli, but did not completely equalize the responses. Together, these findings suggest that GABAA-mediated inhibition acts as a gain control mechanism that enhances SSA by modifying the responsiveness of the neuron