Orally delivered microencapsulated probiotic formulation favorably impacts polyp formation in APC (Min/+) model of intestinal carcinogenesis.

The development of intestinal polyps in an orthotopic colorectal mouse model, receiving a probiotic yogurt formulation containing microencapsulated live Lactobacillus acidophilus cells was investigated. The expression of various immunohistochemical markers namely CD8, Mac-1, Ki-67, and cleaved caspase-3, was evaluated. Results suggest that the probiotic formulation decreases overall intestinal inflammation. Mice receiving the probiotic formulation were found to develop almost two-fold fewer tumors in the small intestines. In the large intestine, however, there was no significant difference observed among polyp numbers. The formulation appears to have potential application in the prevention of various GI pathological conditions.

QoS and energy aware cooperative routing protocol for wildfire monitoring wireless sensor networks.

Wireless sensor networks (WSN) are presented as proper solution for wildfire monitoring. However, this application requires a design of WSN taking into account the network lifetime and the shadowing effect generated by the trees in the forest environment. Cooperative communication is a promising solution for WSN which uses, at each hop, the resources of multiple nodes to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modeling, optimizing a cooperative communication protocol based on RSSI and node energy consumption in a competitive context (RSSI/energy-CC), that is, an energy and quality-of-service aware-based cooperative communication routing protocol. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.

An improved method for the estimation of firing rate dynamics using an optimal digital filter.

In most neural systems, neurons communicate by means of sequences of action potentials or 'spikes'. Information encoded by spike trains is often quantified in terms of the firing rate which emphasizes the frequency of occurrence of action potentials rather than their exact timing. Common methods for estimating firing rates include the rate histogram, the reciprocal interspike interval, and the spike density function. In this study, we demonstrate the limitations of these aforementioned techniques and propose a simple yet more robust alternative. By convolving the spike train with an optimally designed Kaiser window, we show that more robust estimates of firing rate are obtained for both low and high-frequency inputs. We illustrate our approach by considering spike trains generated by simulated as well as experimental data obtained from single-unit recordings of first-order sensory neurons in the vestibular system. Improvements were seen in the prevention of aliasing, phase and amplitude distortion, as well as in the noise reduction for sinusoidal and more complex input profiles. We review the generality of the approach, and show that it can be adapted to describe neurons with sensory or motor responses that are characterized by marked nonlinearities. We conclude that our method permits more robust estimates of neural dynamics than conventional techniques across all stimulus conditions.