FGF13 Is Required for Histamine-Induced Itch Sensation by Interaction with Na1.7.

Itch can be induced by activation of small-diameter DRG neurons, which express abundant intracellular fibroblast growth factor 13 (FGF13). Although FGF13 is revealed to be essential for heat nociception, its role in mediating itch remains to be investigated. Here, we reported that loss of FGF13 in mouse DRG neurons impaired the histamine-induced scratching behavior.

Nerve Injury-Induced Neuronal PAP-I Maintains Neuropathic Pain by Activating Spinal Microglia.

Pancreatitis-associated proteins (PAPs) display multiple functions in visceral diseases. Previous studies showed that the expression level of PAP-I was low in the DRG of naive rats but was expressed after peripheral nerve injury. However, its role in neuropathic pain remains unknown.

[Clinical Value of Serum Fructosamine Measurement in IgA Type Multiple Myeloma].

Objective: To investigate the value of serum fructosamine (FMN) measurement in clinical typing and staging of multiple myeloma(MM) as well as evaluation of curative efficacy and prognosis of IgA type MM.

Methods: The levels of FMN were detected by nitro-blue-tetrazolium colorimetric method in 62 IgA type MM patients, 65 IgG type MM patients, 24 IgM type MM patients. The difference between the serum FMN levels and different MM types and its relationship with IgA type MM, patients' stages, efficacy and as well as, the effect of FMN level on overall survival (OS) time of IgA type MM patients were analyzed.

Parallel mutual information estimation for inferring gene regulatory networks on GPUs.

Background: Mutual information is a measure of similarity between two variables. It has been widely used in various application domains including computational biology, machine learning, statistics, image processing, and financial computing. Previously used simple histogram based mutual information estimators lack the precision in quality compared to kernel based methods.

A parallel algorithm for error correction in high-throughput short-read data on CUDA-enabled graphics hardware.

Emerging DNA sequencing technologies open up exciting new opportunities for genome sequencing by generating read data with a massive throughput. However, produced reads are significantly shorter and more error-prone compared to the traditional Sanger shotgun sequencing method. This poses challenges for de novo DNA fragment assembly algorithms in terms of both accuracy (to deal with short, error-prone reads) and scalability (to deal with very large input data sets).

A gradual noisy chaotic neural network for solving the broadcast scheduling problem in packet radio networks.

In this paper, we propose a gradual noisy chaotic neural network (G-NCNN) to solve the NP-complete broadcast scheduling problem (BSP) in packet radio networks. The objective of the BSP is to design an optimal time-division multiple-access (TDMA) frame structure with minimal TDMA frame length and maximal channel utilization. A two-phase optimization is adopted to achieve the two objectives with two different energy functions, so that the G-NCNN not only finds the minimum TDMA frame length but also maximizes the total node transmissions.

Broadcast scheduling in wireless multihop networks using a neural-network-based hybrid algorithm.

In wireless multihop networks, the objective of the broadcast scheduling problem is to find a conflict free transmission schedule for each node at different time slots in a fixed length time cycle, called TDMA cycle. The optimization criterion is to find an optimal TDMA schedule with minimal TDMA cycle length and maximal node transmissions. In this paper we propose a two-stage hybrid method to solve this broadcast scheduling problem in wireless multihop networks.