A range of cell types, including embryonic stem cells, neurons and astrocytes have been shown to release extracellular vesicles (EVs) containing molecular cargo. Across cell types, EVs facilitate transfer of mRNA, microRNA and proteins between cells. Here we describe the release kinetics and content of EVs from mouse retinal progenitor cells (mRPCs). Interestingly, mRPC derived EVs contain mRNA, miRNA and proteins associated with multipotency and retinal development. Transcripts enclosed in mRPC EVs, include the transcription factors Pax6, Hes1, and Sox2, a mitotic chromosome stabilizer Ki67, and the neural intermediate filaments Nestin and GFAP. Proteomic analysis of EV content revealed retinogenic growth factors and morphogen proteins. mRPC EVs were shown to transfer GFP mRNA between cell populations. Finally, analysis of EV mediated functional cargo delivery, using the Cre-loxP recombination system, revealed transfer and uptake of Cre+ EVs, which were then internalized by target mRPCs activating responder loxP GFP expression. In summary, the data supports a paradigm of EV genetic material encapsulation and transfer within RPC populations. RPC EV transfer may influence recipient RPC transcriptional and post-transcriptional regulation, representing a novel mechanism of differentiation and fate determination during retinal development.

The variations in recovery time, complications, and survival among cardiac patients who have undergone coronary artery bypass graft (CABG) procedures are vast. Many formulas and theories are used to predict clinical outcome and recovery time, and current prognostic predictions are based on medical and family history, lifestyle, co-morbidities, and performance status. The identification of biomarkers that provide concrete evidence supporting clinical outcome has greatly affected the field of medicine, helping clinicians in many medicine sub-specialties to forecast clinical course. Recent studies have discovered biomarkers that may be used as predictors of cardiac patients’ status post-cardiothoracic surgery, and the applications are numerous. In this review, we assess currently available cardiac biomarkers as predictors of clinical outcome for post-operative CABG patients. Data were collected from various studies in which cardiac biomarkers were measured in pre-operative and post-operative CABG patients.

Background/Aim: We investigated the cytotoxic effects of plumbagin on metastatic retinoblastoma, using the highly metastatic cell line Y79. Materials and Methods: Effect of plumbagin on cell growth was assessed with water-soluble tetrazolium 1 (WST-1) cell proliferation assay and automated hemocytometry with trypan blue-exclusion assay. Cell death was studied with acridine orange/ethidium bromide live-dead assay and annexin-V-fluorescein isothiocyanate/propidium iodide microscopy. Loss of mitochondrial membrane potential was studied with JC-10 dye and caspase activation was investigated using CellEvent Caspase-3/7 Green detection reagent. Results: Plumbagin highly significantly reduced the growth of Y79 cells treated for 24 h with 2.5 μM or more. Plumbagin also induced significantly high levels of cell death which was associated with loss of mitochondrial membrane potential and caspase activation. Conclusion: At very low concentration (2.5 μM), plumbagin potently induced cytotoxicity in metastatic retinoblastoma cells via loss of mitochondrial membrane potential and caspase activation.

Background: High risk, unfavorable classical Hodgkin lymphoma (cHL) includes those patients with primary refractory or early relapse, and progressive disease. To improve the availability of biomarkers for this group of patients, we investigated both tumor biopsies and peripheral blood leukocytes (PBL) of untreated (chemo-naïve, CN) Nodular Sclerosis Classic Hodgkin Lymphoma (NS-cHL) patients for consistent biomarkers that can predict the outcome prior to frontline treatment. Methods and materials: Bioinformatics data mining was used to generate 151 candidate biomarkers, which were screened against a library of 10 HL cell lines. Expression of FGF2 and SDC1 by CD30+ cells from HL patient samples representing good and poor outcomes were analyzed by qRT-PCR, immunohistochemical (IHC), and immunofluorescence analyses. Results: To identify predictive HL-specific biomarkers, potential marker genes selected using bioinformatics approaches were screened against HL cell lines and HL patient samples. Fibroblast Growth Factor-2 (FGF2) and Syndecan-1 (SDC1) were overexpressed in all HL cell lines, and the overexpression was HL-specific when compared to 116 non-Hodgkin lymphoma tissues. In the analysis of stratified NS-cHL patient samples, expression of FGF2 and SDC1 were 245 fold and 91 fold higher, respectively, in the poor outcome (PO) group than in the good outcome (GO) group. The PO group exhibited higher expression of the HL marker CD30, the macrophage marker CD68, and metastatic markers TGFβ1 and MMP9 compared to the GO group. This expression signature was confirmed by qualitative immunohistochemical and immunofluorescent data. A Kaplan-Meier analysis indicated that samples in which the CD30+ cells carried an FGF2+/SDC1+ immunophenotype showed shortened survival. Analysis of chemo-naive HL blood samples suggested that in the PO group a subset of CD30+ HL cells had entered the circulation. These cells significantly overexpressed FGF2 and SDC1 compared to the GO group. The PO group showed significant down-regulation of markers for monocytes, T-cells, and B-cells. These expression signatures were eliminated in heavily pretreated patients. Conclusion: The results suggest that small subsets of circulating CD30+/CD15+ cells expressing FGF2 and SDC1 represent biomarkers that identify NS-cHL patients who will experience a poor outcome (primary refractory and early relapsing).