Design and evaluation of an osteogenesis-on-a-chip microfluidic device incorporating 3D cell culture

Microfluidic-based tissue-on-a-chip devices have generated significant research interest for biomedical applications, such as pharmaceutical development, as they can be used for small volume, high throughput studies on the effects of therapeutics on tissue-mimics. Tissue-on-a-chip devices are evolving from basic 2D cell cultures incorporated into microfluidic devices to complex 3D approaches, with modern designs aimed at recapitulating the dynamic and mechanical environment of the native tissue. Thus far, most tissue-on-a-chip research has concentrated on organs involved with drug uptake, metabolism and removal (e.g., lung, skin, liver, and kidney); however, models of the drug metabolite target organs will be essential to provide information on therapeutic efficacy. Here, we develop an osteogenesis-on-a-chip device that comprises a 3D environment and fluid shear stresses, both important features of bone. This inexpensive, easy-to-fabricate system based on a polymerized High Internal Phase Emulsion (polyHIPE) supports proliferation, differentiation and extracellular matrix production of human embryonic stem cell-derived mesenchymal progenitor cells (hES-MPs) over extended time periods (up to 21 days). Cells respond positively to both chemical and mechanical stimulation of osteogenesis, with an intermittent flow profile containing rest periods strongly promoting differentiation and matrix formation in comparison to static and continuous flow. Flow and shear stresses were modeled using computational fluid dynamics. Primary cilia were detectable on cells within the device channels demonstrating that this mechanosensory organelle is present in the complex 3D culture environment. In summary, this device aids the development of ‘next-generation’ tools for investigating novel therapeutics for bone in comparison with standard laboratory and animal testing

Chitosan-decorated polystyrene-<i>b</i>-poly(acrylic acid) polymersomes as novel carriers for topical delivery of finasteride

International audienc

Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors

Delay in diagnosis of influenza A (H1N1)pdm09 virus infection in critically ill patients and impact on clinical outcome

Background: Patients infected with influenza A (H1N1)pdm09 virus requiring admission to the ICU remain an important source of mortality during the influenza season. The objective of the study was to assess the impact of a delay in diagnosis of community-acquired influenza A (H1N1)pdm09 virus infection on clinical outcome in critically ill patients admitted to the ICU. Methods: A prospective multicenter observational cohort study was based on data from the GETGAG/SEMICYUC registry (2009–2015) collected by 148 Spanish ICUs. All patients admitted to the ICU in which diagnosis of influenza A (H1N1)pdm09 virus infection had been established within the first week of hospitalization were included. Patients were classified into two groups according to the time at which the diagnosis was made: early (within the first 2 days of hospital admission) and late (between the 3rd and 7th day of hospital admission). Factors associated with a delay in diagnosis were assessed by logistic regression analysis. Results: In 2059 ICU patients diagnosed with influenza A (H1N1)pdm09 virus infection within the first 7 days of hospitalization, the diagnosis was established early in 1314 (63.8 %) patients and late in the remaining 745 (36.2 %). Independent variables related to a late diagnosis were: age (odds ratio (OR) = 1.02, 95 % confidence interval (CI) 1.01–1.03, P < 0.001); first seasonal period (2009–2012) (OR = 2.08, 95 % CI 1.64–2.63, P < 0.001); days of hospital stay before ICU admission (OR = 1.26, 95 % CI 1.17–1.35, P < 0.001); mechanical ventilation (OR = 1.58, 95 % CI 1.17–2.13, P = 0.002); and continuous venovenous hemofiltration (OR = 1.54, 95 % CI 1.08–2.18, P = 0.016). The intra-ICU mortality was significantly higher among patients with late diagnosis as compared with early diagnosis (26.9 % vs 17.1 %, P < 0.001). Diagnostic delay was one independent risk factor for mortality (OR = 1.36, 95 % CI 1.03–1.81, P < 0.001). Conclusions: Late diagnosis of community-acquired influenza A (H1N1)pdm09 virus infection is associated with a delay in ICU admission, greater possibilities of respiratory and renal failure, and higher mortality rate. Delay in diagnosis of flu is an independent variable related to death