Poly(lactic-co-glycolic) acid drug delivery systems through transdermal pathway : an overview

In past few decades, scientists have made tremendous advancement in the field of drug delivery systems (DDS), through transdermal pathway, as the skin represents a ready and large surface area for delivering drugs. Efforts are in progress to design efficient transdermal DDS that support sustained drug release at the targeted area for longer duration in the recommended therapeutic window without producing side-effects. Poly(lactic-co-glycolic acid) (PLGA) is one of the most promising Food and Drug Administration approved synthetic polymers in designing versatile drug delivery carriers for different drug administration routes, including transdermal drug delivery. The present review provides a brief introduction over the transdermal drug delivery and PLGA as a material in context to its role in designing drug delivery vehicles. Attempts are made to compile literatures over PLGA-based drug delivery vehicles, including microneedles, nanoparticles, and nanofibers and their role in transdermal drug delivery of different therapeutic agents. Different nanostructure evaluation techniques with their working principles are briefly explained.RL thanks the funding support from Singapore National Research Foundation under its Translational and Clinical Research Flagship Programme (NMRC/TCR/008-SERI/2013) and administered by the Singapore Ministry of Health’s National Medical Research Council and Co-operative Basic Research Grant from the Singapore National Medical Research Council (Project No. NMRC/CBRG/0048/2013).info:eu-repo/semantics/publishedVersio

MexEF-OprN Efflux Pump Exports the Pseudomonas Quinolone Signal (PQS) Precursor HHQ (4-hydroxy-2-heptylquinoline)

Bacterial cells have evolved the capacity to communicate between each other via small diffusible chemical signals termed autoinducers. Pseudomonas aeruginosa is an opportunistic pathogen involved, among others, in cystic fibrosis complications. Virulence of P. aeruginosa relies on its ability to produce a number of autoinducers, including 4-hydroxy-2-alkylquinolines (HAQ). In a cell density-dependent manner, accumulated signals induce the expression of multiple targets, especially virulence factors. This phenomenon, called quorum sensing, promotes bacterial capacity to cause disease. Furthermore, P. aeruginosa possesses many multidrug efflux pumps conferring adaptive resistance to antibiotics. Activity of some of these efflux pumps also influences quorum sensing. The present study demonstrates that the MexEF-OprN efflux pump modulates quorum sensing through secretion of a signalling molecule belonging to the HAQ family. Moreover, activation of MexEF-OprN reduces virulence factor expression and swarming motility. Since MexEF-OprN can be activated in infected hosts even in the absence of antibiotic selective pressure, it could promote establishment of chronic infections in the lungs of people suffering from cystic fibrosis, thus diminishing the immune response to virulence factors. Therapeutic drugs that affect multidrug efflux pumps and HAQ-mediated quorum sensing would be valuable tools to shut down bacterial virulence

Genome structure of cotton revealed by a genome-wide SSR genetic map constructed from a BC1 population between gossypium hirsutum and G. barbadense

<p>Abstract</p> <p>Background</p> <p>Cotton, with a large genome, is an important crop throughout the world. A high-density genetic linkage map is the prerequisite for cotton genetics and breeding. A genetic map based on simple polymerase chain reaction markers will be efficient for marker-assisted breeding in cotton, and markers from transcribed sequences have more chance to target genes related to traits. To construct a genome-wide, functional marker-based genetic linkage map in cotton, we isolated and mapped expressed sequence tag-simple sequence repeats (EST-SSRs) from cotton ESTs derived from the A₁, D₅, (AD)₁, and (AD)₂genome.</p> <p>Results</p> <p>A total of 3177 new EST-SSRs developed in our laboratory and other newly released SSRs were used to enrich our interspecific BC₁genetic linkage map. A total of 547 loci and 911 loci were obtained from our EST-SSRs and the newly released SSRs, respectively. The 1458 loci together with our previously published data were used to construct an updated genetic linkage map. The final map included 2316 loci on the 26 cotton chromosomes, 4418.9 cM in total length and 1.91 cM in average distance between adjacent markers. To our knowledge, this map is one of the three most dense linkage maps in cotton. Twenty-one segregation distortion regions (SDRs) were found in this map; three segregation distorted chromosomes, Chr02, Chr16, and Chr18, were identified with 99.9% of distorted markers segregating toward the heterozygous allele. Functional analysis of SSR sequences showed that 1633 loci of this map (70.6%) were transcribed loci and 1332 loci (57.5%) were translated loci.</p> <p>Conclusions</p> <p>This map lays groundwork for further genetic analyses of important quantitative traits, marker-assisted selection, and genome organization architecture in cotton as well as for comparative genomics between cotton and other species. The segregation distorted chromosomes can be a guide to identify segregation distortion loci in cotton. The annotation of SSR sequences identified frequent and rare gene ontology items on each chromosome, which is helpful to discover functions of cotton chromosomes.</p

Down-Regulation of EBV-LMP1 Radio-Sensitizes Nasal Pharyngeal Carcinoma Cells via NF-κB Regulated ATM Expression

BACKGROUND:The latent membrane protein 1 (LMP1) encoded by EBV is expressed in the majority of EBV-associated human malignancies and has been suggested to be one of the major oncogenic factors in EBV-mediated carcinogenesis. In previous studies we experimentally demonstrated that down-regulation of LMP1 expression by DNAzymes could increase radiosensitivity both in cells and in a xenograft NPC model in mice. RESULTS:In this study we explored the molecular mechanisms underlying the radiosensitization caused by the down-regulation of LMP1 in nasopharyngeal carcinoma. It was confirmed that LMP1 could up-regulate ATM expression in NPCs. Bioinformatic analysis of the ATM ptomoter region revealed three tentative binding sites for NF-κB. By using a specific inhibitor of NF-κB signaling and the dominant negative mutant of IkappaB, it was shown that the ATM expression in CNE1-LMP1 cells could be efficiently suppressed. Inhibition of LMP1 expression by the DNAzyme led to attenuation of the NF-κB DNA binding activity. We further showed that the silence of ATM expression by ATM-targeted siRNA could enhance the radiosensitivity in LMP1 positive NPC cells. CONCLUSIONS:Together, our results indicate that ATM expression can be regulated by LMP1 via the NF-κB pathways through direct promoter binding, which resulted in the change of radiosensitivity in NPCs

Facile Fabrication of Ultrafine Hollow Silica and Magnetic Hollow Silica Nanoparticles by a Dual-Templating Approach

The development of synthetic process for hollow silica materials is an issue of considerable topical interest. While a number of chemical routes are available and are extensively used, the diameter of hollow silica often large than 50 nm. Here, we report on a facial route to synthesis ultrafine hollow silica nanoparticles (the diameter of ca. 24 nm) with high surface area by using cetyltrimethylammmonium bromide (CTAB) and sodium bis(2-ethylhexyl) sulfosuccinate (AOT) as co-templates and subsequent annealing treatment. When the hollow magnetite nanoparticles were introduced into the reaction, the ultrafine magnetic hollow silica nanoparticles with the diameter of ca. 32 nm were obtained correspondingly. Transmission electron microscopy studies confirm that the nanoparticles are composed of amorphous silica and that the majority of them are hollow

Accurate Prediction of Protein Structural Class

Because of the increasing gap between the data from sequencing and structural genomics, the accurate prediction of the structural class of a protein domain solely from the primary sequence has remained a challenging problem in structural biology. Traditional sequence-based predictors generally select several sequence features and then feed them directly into a classification program to identify the structural class. The current best sequence-based predictor achieved an overall accuracy of 74.1% when tested on a widely used, non-homologous benchmark dataset 25PDB. In the present work, we built a multiple linear regression (MLR) model to convert the 440-dimensional (440D) sequence feature vector extracted from the Position Specific Scoring Matrix (PSSM) of a protein domain to a 4-dimensinal (4D) structural feature vector, which could then be used to predict the four major structural classes. We performed 10-fold cross-validation and jackknife tests of the method on a large non-homologous dataset containing 8,244 domains distributed among the four major classes. The performance of our approach outperformed all of the existing sequence-based methods and had an overall accuracy of 83.1%, which is even higher than the results of those predicted secondary structure-based methods