TARGETED DELIVERY OF ANTI-INFLAMMATORY AND ANTI-OXIDANT DRUGS FOR TREATMENT OF CHRONIC OBSTRUCTIVE PULMONARY DISEASES

Chronic obstructive pulmonary disease (COPD) was found to be the fourth leading cause of death in 2004, but current treatments can only relieve the symptoms and improve the quality of life for the patients. Glucocorticoids have been broadly applied in other inflammatory conditions with promising therapeutic effects, but performed poorly in COPD. The phenomenon called glucocorticoid resistance is responsible for glucocorticoid insensitivity in COPD. Researchers have proven that elevated oxidative stress in the lung of a COPD patient is one of the main causes of blocking the function of glucocorticoids. We hypothesize that reducing the oxidative stress in the lung can restore the therapeutic effect of glucocorticoids in COPD. Thus, simultaneous administration of antioxidant and glucocorticoid drugs could be a promising approach to treat this condition. In order to achieve this goal, liposomes loaded with both glucocorticoids and antioxidants were developed and characterized. First, several types of nano-carrier candidates were prepared and tested, and based on the comparative study liposomes were selected as the nano-carrier system of choice for further experiments. In order to quantitatively determine the relationship between the targeting efficacy and the amount of the targeting antibody immobilized on the surface of the liposomes, surface plasmon resonance (SPR) was performed. It was shown that initial increase of the affinity upon the increase of the targeting antibody surface density was followed by the saturation of binding affinity at certain antibody surface density. This saturation surface density was independent regardless of the size of the liposomes or even the type of the targeting antibody and its ligand. This saturation point was important in optimization of the targeting efficacy of the liposomes coated with the targeting antibody. In order to address the glucocorticoid resistance induced by the oxidative stress, and test the hypothesis of the synergistic action of the antioxidant and glucocorticoid drugs, a cell culture model was developed. Exogenous ROS were proven to be necessary in this model. The synergistic effect of the co-delivery of the two drugs was demonstrated by measuring pro-inflammatory response. Analysis of the gene expression of several important biomarkers showed that the mechanism of action involved restoration of the expression of histone deacetylases 2 (HDAC2) in the presence of the antioxidant. Later, this cell culture model also proved the increased drug availability in the case of targeted liposome-based delivery. Overall, this targeted delivery system loaded both antioxidant and glucocorticoid drugs provided another approach to address the problem of treatment of COPD

A probabilistic data association based MIMO detector using joint detection of consecutive symbol vectors

A new probabilistic data association (PDA) approach is proposed for symbol detection in spatial multiplexing multiple-input multiple-output (MIMO) systems. By designing a joint detection (JD) structure for consecutive symbol vectors in the same transmit burst, more a priori information is exploited when updating the estimated posterior marginal probabilities for each symbol per iteration. Therefore the proposed PDA detector (denoted as PDA-JD detector) outperforms the conventional PDA detectors in the context of correlated input bit streams. Moreover, the conventional PDA detectors are shown to be a special case of the PDA-JD detector. Simulations and analyses are given to demonstrate the effectiveness of the new method

Multi-group frequency hopping OFDMA based on statistical multiplexing

In this paper, the multi-group frequency hopping OFDMA (MG-FH OFDMA) based on the statistical multiplexing is proposed for the downlink cellular system. Compared with the existed random frequency hopping OFDMA (RFH-OFDMA) system utilizing the statistical multiplexing, the proposed MG-FH OFDMA invokes the deterministic hopping pattern to reduce the number of subcarrier collisions. By dividing all users into different groups, the subcarriers are utilized sufficiently. Latin Square hopping pattern and user index updating scheme are applied to randomize the subcarrier collisions among users. The user capacity, defined as the maximum number of users served with a basic data-rate in a cell, is calculated with the consideration of intra-cell capacity and the other cell interference (OCI). Results show that the proposed MG-FH OFDMA achieves higher user capacity than that of the RFH-OFDMA

Approximate minimum BER power allocation for MIMO-THP system

This paper proposes a transmit power allocation (TPA) scheme based on multiple-input multiple-output (MIMO) Tomlinson-Harashima precoding (THP) structure, where a TPA matrix is introduced to the conventional MIMO-THP. We analyze the influence of the introduced TPA matrix on the performance of MIMO-THP. The proposed TPA scheme invokes the minimum average uncoded bit-error rate (BER) criterion subjected to a sum-power constraint. During the derivation, we consider the effects of precoding loss factor on the TPA scheme and obtain a closed-form expression of the TPA. Compared to existing TPA methods for MIMO-THP systems, the proposed scheme reduces processing complexity and improves the BER performance

Simulated annealing based multiuser detection for synchronous SDMA system

In this treatise, a novel Simulated Annealing (SA) based Multi-User Detection (MUD) is proposed in synchronous Space Division Multiple Access (SDMA) system. SA MUD modifies experiential Cooling Schedule (CS) of traditional SA algorithm according to its use in MUD. Moreover, in order to ensure sufficient diversity acquired in the whole Markov chain and to prevent from being trapped at local optima, Uniform Mutation (UM) based trial vector generation scheme is brought forward. In addition, the optimal solution recording scheme is also invoked in case of being lost during cooling process. Simulation results illustrate that in comparison with Genetic Algorithm (GA) MUD in the same simulation conditions, without turbo processing and soft-information, SA MUD proposed in this paper performs better, approaching the performance of Maximum Likelihood (ML) MUD and imposes lower complexity