Exosome mimetics: a novel class of drug delivery systems

The identification of extracellular phospholipid vesicles as conveyors of cellular information has created excitement in the field of drug delivery. Biological therapeutics, including short interfering RNA and recombinant proteins, are prone to degradation, have limited ability to cross biological membranes, and may elicit immune responses. Therefore, delivery systems for such drugs are under intensive investigation. Exploiting extracellular vesicles as carriers for biological therapeutics is a promising strategy to overcome these issues and to achieve efficient delivery to the cytosol of target cells. Exosomes are a well studied class of extracellular vesicles known to carry proteins and nucleic acids, making them especially suitable for such strategies. However, the considerable complexity and the related high chance of off-target effects of these carriers are major barriers for translation to the clinic. Given that it is well possible that not all components of exosomes are required for their proper functioning, an alternative strategy would be to mimic these vesicles synthetically. By assembly of liposomes harboring only crucial components of natural exosomes, functional exosome mimetics may be created. The low complexity and use of well characterized components strongly increase the pharmaceutical acceptability of such systems. However, exosomal components that would be required for the assembly of functional exosome mimetics remain to be identified. This review provides insights into the composition and functional properties of exosomes, and focuses on components which could be used to enhance the drug delivery properties of exosome mimetics

Testing bias in clinical databases: methodological considerations

<p>Abstract</p> <p>Background</p> <p>Laboratory testing in clinical practice is never a random process. In this study we evaluated testing bias for neutrophil counts in clinical practice by using results from requested and non-requested hematological blood tests.</p> <p>Methods</p> <p>This study was conducted using data from the Utrecht Patient Oriented Database. This clinical database is unique, as it contains physician requested data, but also data that are not requested by the physician, but measured as result of requesting other hematological parameters. We identified adult patients, hospitalized in 2005 with at least two blood tests during admission, where requests for general blood profiles and specifically for neutrophil counts were contrasted in scenario analyses. Possible effect modifiers were diagnosis and glucocorticoid use.</p> <p>Results</p> <p>A total of 567 patients with requested neutrophil counts and 1,439 patients with non-requested neutrophil counts were analyzed. The absolute neutrophil count at admission differed with a mean of 7.4 × 10⁹/l for requested counts and 8.3 × 10⁹/l for non-requested counts (p-value < 0.001). This difference could be explained for 83.2% by the occurrence of cardiovascular disease as underlying disease and for 4.5% by glucocorticoid use.</p> <p>Conclusion</p> <p>Requests for neutrophil counts in clinical databases are associated with underlying disease and with cardiovascular disease in particular. The results from our study show the importance of evaluating testing bias in epidemiological studies obtaining data from clinical databases.</p

Финансовое обеспечение деятельности туристического предприятия

Целью статьи является разработка рекомендаций по повышению эффективности финансового обеспечения деятельности туристического предприятия, определение приоритетных путей совершенствования финансовых показателей его деятельности

A cluster of blood-based protein biomarkers associated with decreased cerebral blood flow relates to future cardiovascular events in patients with cardiovascular disease

Biological processes underlying decreased cerebral blood flow (CBF) in patients with cardiovascular disease (CVD) are largely unknown. We hypothesized that identification of protein clusters associated with lower CBF in patients with CVD may explain underlying processes. In 428 participants (74% cardiovascular diseases; 26% reference participants) from the Heart-Brain Connection Study, we assessed the relationship between 92 plasma proteins from the Olink® cardiovascular III panel and normal-appearing grey matter CBF, using affinity propagation and hierarchical clustering algorithms, and generated a Biomarker Compound Score (BCS). The BCS was related to cardiovascular risk and observed cardiovascular events within 2-year follow-up using Spearman correlation and logistic regression. Thirteen proteins were associated with CBF (ρSpearman range: −0.10 to −0.19, pFDR-corrected &lt;0.05), and formed one cluster. The cluster primarily reflected extracellular matrix organization processes. The BCS was higher in patients with CVD compared to reference participants (pFDR-corrected &lt;0.05) and was associated with cardiovascular risk (ρSpearman 0.42, p &lt; 0.001) and cardiovascular events (OR 2.05, p &lt; 0.01). In conclusion, we identified a cluster of plasma proteins related to CBF, reflecting extracellular matrix organization processes, that is also related to future cardiovascular events in patients with CVD, representing potential targets to preserve CBF and mitigate cardiovascular risk in patients with CVD.</p

Ribosomal Protein Mutations Induce Autophagy through S6 Kinase Inhibition of the Insulin Pathway

Mutations affecting the ribosome lead to several diseases known as ribosomopathies, with phenotypes that include growth defects, cytopenia, and bone marrow failure. Diamond-Blackfan anemia (DBA), for example, is a pure red cell aplasia linked to the mutation of ribosomal protein (RP) genes. Here we show the knock-down of the DBA-linked RPS19 gene induces the cellular self-digestion process of autophagy, a pathway critical for proper hematopoiesis. We also observe an increase of autophagy in cells derived from DBA patients, in CD34+ erythrocyte progenitor cells with RPS19 knock down, in the red blood cells of zebrafish embryos with RP-deficiency, and in cells from patients with Shwachman-Diamond syndrome (SDS). The loss of RPs in all these models results in a marked increase in S6 kinase phosphorylation that we find is triggered by an increase in reactive oxygen species (ROS). We show that this increase in S6 kinase phosphorylation inhibits the insulin pathway and AKT phosphorylation activity through a mechanism reminiscent of insulin resistance. While stimulating RP-deficient cells with insulin reduces autophagy, antioxidant treatment reduces S6 kinase phosphorylation, autophagy, and stabilization of the p53 tumor suppressor. Our data suggest that RP loss promotes the aberrant activation of both S6 kinase and p53 by increasing intracellular ROS levels. The deregulation of these signaling pathways is likely playing a major role in the pathophysiology of ribosomopathies

Megakaryocyte lineage development is controlled by modulation of protein acetylation

Treatment with lysine deacetylase inhibitors (KDACi) for haematological malignancies, is accompanied by haematological side effects including thrombocytopenia, suggesting that modulation of protein acetylation affects normal myeloid development, and specifically megakaryocyte development. In the current study, utilising ex-vivo differentiation of human CD34+ haematopoietic progenitor cells, we investigated the effects of two functionally distinct KDACi, valproic acid (VPA), and nicotinamide (NAM), on megakaryocyte differentiation, and lineage choice decisions. Treatment with VPA increased the number of megakaryocyte/erythroid progenitors (MEP), accompanied by inhibition of megakaryocyte differentiation, whereas treatment with NAM accelerated megakaryocyte development, and stimulated polyploidisation. Treatment with bot

Automated Detection of External Ventricular and Lumbar Drain-Related Meningitis Using Laboratory and Microbiology Results and Medication Data

OBJECTIVE: Monitoring of healthcare-associated infection rates is important for infection control and hospital benchmarking. However, manual surveillance is time-consuming and susceptible to error. The aim was, therefore, to develop a prediction model to retrospectively detect drain-related meningitis (DRM), a frequently occurring nosocomial infection, using routinely collected data from a clinical data warehouse. METHODS: As part of the hospital infection control program, all patients receiving an external ventricular (EVD) or lumbar drain (ELD) (2004 to 2009; n = 742) had been evaluated for the development of DRM through chart review and standardized diagnostic criteria by infection control staff; this was the reference standard. Children, patients dying <24 hours after drain insertion or with <1 day follow-up and patients with infection at the time of insertion or multiple simultaneous drains were excluded. Logistic regression was used to develop a model predicting the occurrence of DRM. Missing data were imputed using multiple imputation. Bootstrapping was applied to increase generalizability. RESULTS: 537 patients remained after application of exclusion criteria, of which 82 developed DRM (13.5/1000 days at risk). The automated model to detect DRM included the number of drains placed, drain type, blood leukocyte count, C-reactive protein, cerebrospinal fluid leukocyte count and culture result, number of antibiotics started during admission, and empiric antibiotic therapy. Discriminatory power of this model was excellent (area under the ROC curve 0.97). The model achieved 98.8% sensitivity (95% CI 88.0% to 99.9%) and specificity of 87.9% (84.6% to 90.8%). Positive and negative predictive values were 56.9% (50.8% to 67.9%) and 99.9% (98.6% to 99.9%), respectively. Predicted yearly infection rates concurred with observed infection rates. CONCLUSION: A prediction model based on multi-source data stored in a clinical data warehouse could accurately quantify rates of DRM. Automated detection using this statistical approach is feasible and could be applied to other nosocomial infections

Clinical Expression of a Rare β-Globin Gene Mutation Co-Inherited with Haemoglobin E-Disease

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