No abstract

Extracellular vesicle (EV) trafficking provides for a constitutive mode of cell-cell communication within tissues and between organ systems. Different EV subtypes have been identified that transfer regulatory molecules between cells, influencing gene expression, and altering cellular phenotypes. Evidence from a range of studies suggests that EV trafficking enhances cell survival and resistance to chemotherapy in solid tumors. In acute myeloid leukemia (AML), EVs contribute to the dynamic crosstalk between AML cells, hematopoietic elements and stromal cells and promote adaptation of compartmental bone marrow (BM) function through transport of protein, RNA, and DNA. Careful analysis of leukemia cell EV content and phenotypic outcomes provide evidence that vesicles are implicated in transferring several known key mediators of chemoresistance, including miR-155, IL-8, and BMP-2. Here, we review the current understanding of how EVs exert their influence in the AML niche, and identify research opportunities to improve outcomes for relapsed or refractory AML patients.

The feasibility of a two-layer contact-independent 3D neuronal co-culture model to test the bioactivity of brain-derived neurotrophic factor (BDNF), produced by non-virally transfected A7 astrocytes (trA7), on neurite growth in a second cell population of SH-SY5Y (CRL-2266) neuroblastoma cells with (oxSH-SY5Y) or without oxidative damage (SH-SY5Y) was evaluated. Transfection of A7 astrocytes was carried out with BDNF-encoding plasmid using K2® nanoparticle gene delivery system (K2-NPs). The physicochemical characteristics of K2-NPs, transfection efficiency, and BDNF production were evaluated using dynamic light scattering, flow cytometry, and enzyme-linked immunosorbent assay (ELISA), respectively. Neurite counts and length measurements were performed after anti-neuron-specific β-III tubulin antibody immunostaining using confocal laser scanning microscopy. Transfection efficiency of A7 astrocytes by K2-NPs (diameter 83.9 ± 0.4 nm, zeta potential +57.3 ± 2.8 mV) was 39.5 ± 4.6 % with cell viability of 73 ± 2 %. BDNF levels produced were 3750.8 ± 251.1, 9052.6 ± 1391.2, and 10,367.1 ± 390.8 pg/mL at 24, 48, and 72 h, respectively. The increased number of neurites with higher neurite lengths confirmed the bioactivity of BDNF secreted from the transfected A7 astrocytes over 72 h. Neurite count comparisons showed that both trA7/oxSH-SY5Y and trA7/SH-SY5Y consistently produced higher neurite counts compared to A7/oxSH-SY5Y and oxSH-SY5Y only experimental conditions. The results of this study demonstrate that neurite outgrowth quantitation in astrocyte-SH-SY5Y cell co-culture is a suitable bioassay model for evaluating non-viral gene delivery systems. Furthermore, it also demonstrates a proof-of-concept for nanoparticle-based neurotrophic factor gene delivery to astrocytes and stimulation of neurite outgrowth.

Regeneration of damaged retinal ganglion cells (RGC) and their axons is an important aspect of reversing vision loss in glaucoma patients. While current therapies can effectively lower intraocular pressure, they do not provide extrinsic support to RGCs to actively aid in their protection and regeneration. The unmet need could be addressed by neurotrophic factor gene therapy, where plasmid DNA, encoding neurotrophic factors, is delivered to retinal cells to maintain sufficient levels of neurotrophins in the retina. In this review, we aim to describe the intricacies in the design of the therapy including: the choice of neurotrophic factor, the site and route of administration and target cell populations for gene delivery. Furthermore, we also discuss the challenges currently being faced in RGC-related therapy development with special considerations to the existence of multiple RGC subtypes and the lack of efficient and representative in vitro models for rapid and reliable screening in the drug development process.

With the increasing number of multilingual texts in the internet, multilingual text retrieval techniques have become an important research issue. However, the discovery of relationships between different languages remains an open problem. In this paper we propose a method, which applies the growing hierarchical self-organizing map (GHSOM) model, to discover knowledge from multilingual text documents. Multilingual parallel corpora were trained by the GHSOM to generate hierarchical feature maps. A discovery process is then applied on these maps to discover the relationships between documents of different languages. The relationships between keywords of different languages are also revealed. We conducted experiments on a set of Chinese—English bilingual parallel corpora to discover the relationships between documents of these languages. We also use such relationships to perform multilingual information retrieval tasks. The experimental results show that our multilingual text mining approach may capture conceptual relationships among documents as well as keywords written in different languages.