Antitumor effect of therapeutic HPV DNA vaccines with chitosan-based nanodelivery systems

Cervical cancer is the second-most-common cause of malignancies in women worldwide, and the oncogenic activity of the human papilloma virus types (HPV) E7 protein has a crucial role in anogenital tumors. In this study, we have designed a therapeutic vaccine based on chitosan nanodelivery systems to deliver HPV-16 E7 DNA vaccine, considered as a tumor specific antigen for immunotherapy of HPV-associated cervical cancer. We have developed a Nano-chitosan (NCS) as a carrier system for intramuscular administration using a recombinant DNA vaccine expressing HPV-16 E7 (NCS-DNA E7 vaccine). NCS were characterized in vitro for their gene transfection ability. Results: The transfection of CS-pEGFP NPs was efficient in CHO cells and the expression of green fluorescent proteins was well observed. In addition, NCS-DNA E7 vaccine induced the strongest E7-specific CD8+ T cell and interferon γ responses in C57BL/6 mice. Mice vaccinated with NCS-DNA E7 vaccine were able to generate potent protective and therapeutic antitumor effects against challenge with E7-expressing tumor cell line, TC-1. Conclusions: The strong therapeutic effect induced by the Chitosan-based nanodelivery suggest that nanoparticles may be an efficient carrier to improve the immunogenicity of DNA vaccination upon intramuscular administration and the platform could be further exploited as a potential cancer vaccine candidate in humans. © 2014 Tahamtan et al

Simultaneous determination of irinotecan hydrochloride and its related compounds by high performance liquid chromatography using ultraviolet detection

A new simple, precise and accurate high performance liquid chromatography (HPLC) method was developed and validated for the simultaneous determination of irinotecan (CPT-11) and two related compounds viz., 7-ethyl-10 hydroxycamptothecin (SN-38) and camptothecin (CPT) in pharmaceutical dosage forms. Chromatography was accomplished using a reversed-phase C18 column and ultraviolet (UV)detection and an isocratic mobile phase consisting of 3 % v/v triethylammonium acetate buffer (pH 3) and acetonitrile (70:30 v/v). The linear range of quantitation for all the compounds was 0.1-10 μg/mL. The limit of quantitation for all the compounds ranged between 0.01-0.05 μg/mL. The method has the requisite accuracy, selectivity, sensitivity and precision to assay of CPT-11 and related compounds in pharmaceutical dosage forms and bulk API

Chitosan nanoparticles as a potential nonviral gene delivery for HPV-16 E7 into mammalian cells

Chitosan nanoparticles (CS NPs) were prepared as a carrier for Human papillomavirus type 16 HPV-16) E7 gene and their gene transfection ability were evaluated in vitro . The plasmid expressing green fl uorescent protein (pEGFP) was used as a reporter gene. Gel electrophoresis demonstrated full binding of CS NPs with the pDNA. The transfection of CS-pEGFP NPs was effi cient in CHO cells and the expression of green fl uorescent proteins was well observed. The expression of E7 proteins was confi rmed under SDS-PAGE and western blot analysis. As a conclusion CS NPs may serve as an eff ective nonviral carrier for delivery of nucleotides into eukaryotic cells. Copyright © 2014 Informa Healthcare USA, Inc

Application of distributed lighting control architecture in dementia-friendly smart homes

Dementia is a growing problem in societies with aging populations, not only for patients, but also for family members and for the society in terms of the associated costs of providing health care. Helping patients to maintain a degree of independence in their home environment while ensuring their safeties is considered as a positive step forward for addressing individual needs of dementia patients. A common symptom for dementia patients including those with Alzheimer's Disease and Related Dementia (ADRD) is sleep disturbance, patients being awake at night and asleep during the day. One of the problems with night time sleep disturbance in dementia patients is the possible accidental falls of patients in the dark environment. An issue associated with un-hourly sleeping behavior in these patients is the lighting condition of their surroundings. Clinical studies indicate that appropriate level of lightning can help to restore the rest-activity cycles of ADRD patients. This study tackles this problem by generating machine learning solutions for controlling the lighting conditions of multiple rooms in the house in different hours based on patterns of behaviors generated for the patient. Several neural network oriented classification methods are investigated and their feasibilities are assessed with a collection of synthetic data capturing two conditions of balanced and unbalanced inter-class samples. The classifiers are utilized within two centric and distributed lighting control architectures. The results indicate the feasibility of the distributed architecture in achieving a high level of classification performance resulting in adequate control over lighting conditions of the house in various time periods

A comparative review on mobile robot path planning : classical or meta-heuristic methods?

The involvement of Meta-heuristic algorithms in robot motion planning has attracted the attention of researchers in the robotics community due to the simplicity of the approaches and their effectiveness in the coordination of the agents. This study explores the implementation of many meta-heuristic algorithms, e.g. Genetic Algorithm (GA), Differential Evolution (DE), Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) in multiple motion planning scenarios. The study provides comparison between multiple meta-heuristic approaches against a set of well-known conventional motion planning and navigation techniques such as Dijkstra’s Algorithm (DA), Probabilistic Road Map (PRM), Rapidly Random Tree (RRT) and Potential Field (PF). Two experimental environments with difficult to manipulate layouts are used to examine the feasibility of the methods listed. several performance measures such as total travel time, number of collisions, travel distances, energy consumption and displacement errors are considered for assessing feasibility of the motion planning algorithms considered in the study. The results show the competitiveness of meta-heuristic approaches against conventional methods. Dijkstra ’s Algorithm (DA) is considered a benchmark solution and Constricted Particle Swarm Optimization (CPSO) is found performing better than other meta-heuristic approaches in unknown environments

Ex Vivo Evaluation of Insulin Nanoparticles Using Chitosan and Arabic Gum

Polymeric delivery systems based on nanoparticles have emerged as a promising approach for peroral insulin delivery. The aim of the present study was to investigate the release of insulin nanoparticulate systems and ex vivo studies. The nanoparticles were prepared by the ion gelation method. Particle size distribution, zeta potential, and polydispersity index of the nanoparticles were determined. It was found that the nanoparticles carried positive charges and showed a size distribution in the range of 170–200 nm. The electrostatic interactions between the positively charged group of chitosan and negatively charged groups of Arabic gum play an important role in the association efficiency of insulin in nanoparticles. In vitro insulin release studies showed an initial burst followed by a slow release of insulin. The mucoadhesion of the nanosystem was evaluated using excised rat jejunum. Ex vivo studies have shown a significant increase in absorption of insulin in the presence of chitosan nanoparticles in comparison with free insulin

Evaluation of serum adenosine deaminase and its isoenzymes in patients with ovarian cancer

Ovarian cancer is the most lethal gynecological cancer worldwide. There are great relationships between the activities of adenosine deaminase (ADA), one of the enzymes in purine nucleotide pathway and carcinogenic process. In the present study the activities of the total ADA, ADA1 and ADA2 were measured in the sera of the patients with ovarian cancer. In this study, activities of tADA, ADA1 and ADA2 were assessed in sera of 30 patients with ovarian cancer and 30 normal control individuals, using a modified Ellis method in which only ADA2 activity was measured in the present of a specific inhibitor, erythro-9-(2-hydroxy-3-nonyl) adenine (EHNA). Our results showed that the tADA, ADA1, and ADA2 serum activities of patients were found to be significantly increased (P < 0.05) than those of healthy control group. Although, ADA and its isoenzymes were not the specific markers for diagnosis of ovarian cancer, measurement of their activities may be used as a diagnostic means in ovarian cancer as well as the other analytical procedures

A comprehensive review of swarm optimization algorithms

Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained, and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches