Cellular Interactions in Hemopoietic Progenitor Cell Homing: A Review

Within the bone marrow microenvironment, dynamic cellular interactions are constantly occurring. These interactions involve hemopoietic stem cells, progenitor cells and maturing cells, physically interacting with other cells, some of which may function as accessory cells, and others which comprise the stromal elements; hemopoietic cells also interact with non-cellular elements, such as glycoproteins and fibrous proteins of the extracellular matrix (ECM). These interactions serve to regulate normal hemopoiesis by allowing the communication of regulatory information, migration and subsequent homing of stem cells within specific organs, and presentation of hemopoietic growth factors in a biologically relevant fashion. The goal of this review is to examine the specific cellular interactions that relate to the phenomenon of homing of intravenously transplanted stem cells to the bone marrow

Growth differentiation factor 15 as mortality predictor in heart failure patients with non-reduced ejection fraction

Altres ajuts: This study was supported by Fundació d'Investigació Sant Pau (G-60136934).The prognostic value of biomarkers in patients with heart failure (HF) and mid-range (HFmrEF) or preserved ejection fraction (HFpEF) has not been widely addressed. The aim of this study was to assess whether the prognostic value of growth differentiation factor 15 (GDF-15) is superior to that of N-terminal pro-brain natriuretic peptide (NT-proBNP) in patients with HFmrEF or HFpEF. Heart failure patients with either HFpEF or HFmrEF were included in the study. During their first visit to the HF unit, serum samples were obtained and stored for later assessment of GDF-15 and NT-proBNP concentrations. Patients were followed up by the HF unit. The main endpoint was all-cause mortality. A total of 311 patients, 90 (29%) HFmrEF and 221 (71%) HFpEF, were included. Mean age was 72 ± 13 years, and 136 (44%) were women. No differences were found in GDF-15 or NT-proBNP concentrations between both HF groups. During a median follow-up of 15 months (Q1-Q3: 9-30 months), 98 patients (32%) died, most (71%) of cardiovascular causes. Patients who died had higher median concentrations of GDF-15 (4085 vs. 2270 ng/L, P 65 years (P 4330 ng/L), and survival curves were evaluated using the Kaplan-Meier technique. Patients in the highest tertile had the poorest 5 year survival, at 16%, whereas the lowest tertile had the best survival, of 78% (P < 0.001). Growth differentiation factor 15 was superior to NT-proBNP for assessing prognosis in patients with HFpEF and HFmrEF. GDF-15 emerges as a strong, independent biomarker for identifying HFmrEF and HFpEF patients with worse prognosis

Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials

Introduction: Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent. Methods: The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have. Results: Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation. Discussion: Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal