Evaluation of Viscoelastic Properties, Blood Coagulation, and Cellular Responses of a Temperature-Sensitive Gel for Hemostatic Application.

Hemorrhagic blood loss from traumatic injury is the leading cause of death in severe accidents and combat injuries. Treating and stopping blood loss in a timely and effective manner is essential for the survival of the patient. Currently, QuikClot and dry fibrin sealant dressing are well-known approaches for hemostatic treatment. However, these dressings have limitations in slowing blood loss such as being brittle, low blood absorption, and a poor sealant of the injury site. Temperature-sensitive gels may have potential as a platform for delivery of coagulation factors to improve hemostasis and wound sealing in the treatment of traumatic injuries. Here, we developed a temperature-sensitive triblock copolymer (poly ethylene oxide (PEO)-poly propylene oxide (PPO)-poly ethylene oxide (PEO)) containing fibrinogen to promote blood coagulation through gel formation at body temperature. This temperature sensitive solution-to-gel (sol-gel) transition does not require cross-linking agents or UV photoinitiation. We determined that 22 wt % (weight percent) copolymers with and without fibrinogen was the maximum concentration for sol-gel transition at body temperature. Rheology results further confirmed this sol-gel transition of 22 wt % copolymers at body temperature. We showed that fibrinogen itself promoted blood coagulation. Additionally, 22 wt % copolymer with fibrinogen successfully demonstrated stable blood coagulation within the gel compared to 22 wt % copolymer without fibrinogen. Twenty-two weight percent copolymers with and without fibrinogen also exhibited excellent biocompatibility based on cell viability, proliferation, and morphology analysis. In addition, treatment of 22 wt % copolymers did not stimulate pro-inflammatory TNF-α production from differentiated human monocytes. Our results suggest that 22 wt % of a temperature-sensitive copolymer gel containing fibrinogen has great potential as a hemostatic agent stimulating coagulation and providing immediate wound coverage for protection through a sol-gel transition at body temperature.

Heterogenous population coding of a short-term memory and decision task.

We examined neural spike recordings from prefrontal cortex (PFC) while monkeys performed a delayed somatosensory discrimination task. In general, PFC neurons displayed great heterogeneity in response to the task. That is, although individual cells spiked reliably in response to task variables from trial-to-trial, each cell had idiosyncratic combinations of response properties. Despite the great variety in response types, some general patterns held. We used linear regression analysis on the spike data to both display the full heterogeneity of the data and classify cells into categories. We compared different categories of cells and found little difference in their ability to carry information about task variables or their correlation to behavior. This suggests a distributed neural code for the task rather than a highly modularized one. Along this line, we compared the predictions of two theoretical models to the data. We found that cell types predicted by both models were not represented significantly in the population. Our study points to a different class of models that should embrace the inherent heterogeneity of the data, but should also account for the nonrandom features of the population.

Development of neural circuitry for precise temporal sequences through spontaneous activity, axon remodeling, and synaptic plasticity.

Temporally precise sequences of neuronal spikes that span hundreds of milliseconds are observed in many brain areas, including songbird premotor nucleus, cat visual cortex, and primary motor cortex. Synfire chains-networks in which groups of neurons are connected via excitatory synapses into a unidirectional chain-are thought to underlie the generation of such sequences. It is unknown, however, how synfire chains can form in local neural circuits, especially for long chains. Here, we show through computer simulation that long synfire chains can develop through spike-time dependent synaptic plasticity and axon remodeling-the pruning of prolific weak connections that follows the emergence of a finite number of strong connections. The formation process begins with a random network. A subset of neurons, called training neurons, intermittently receive superthreshold external input. Gradually, a synfire chain emerges through a recruiting process, in which neurons within the network connect to the tail of the chain started by the training neurons. The model is robust to varying parameters, as well as natural events like neuronal turnover and massive lesions. Our model suggests that long synfire chain can form during the development through self-organization, and axon remodeling, ubiquitous in developing neural circuits, is essential in the process.

Formation and structure of ramified charge transportation networks in an electromechanical system.

We present findings in an experiment where we obtain stationary ramified transportation networks in a macroscopic nonbiological system. Our purpose here is to introduce the phenomenology of the experiment. We describe the dynamical formation of the network which consists of three growth stages: (I) strand formation, (II) boundary formation, and (III) geometric expansion. We find that the system forms statistically robust network features, like the number of termini and the number of branch points. We also find that the networks are usually trees, meaning that they lack closed loops; indeed, we find that loops are unstable in the network. Finally, we find that the final topology of the network is sensitive to the initial conditions of the particles, in particular to its geometry.