Nanoengineering Neural Stem Cells on Biomimetic Substrates Using Magnetofection Technology

Tissue engineering studies are witnessing a major paradigm shift to cell culture on biomimetic materials that replicate native tissue features from which the cells are derived. Few studies have been performed in this regard for neural cells, particularly in nanomedicine. For example, platforms such as magnetic nanoparticles (MNPs) have proven efficient as multifunctional tools for cell tracking and genetic engineering of neural transplant populations. However, as far as we are aware, all current studies have been conducted using neural cells propagated on non-neuromimetic substrates that fail to represent the mechano-elastic properties of brain and spinal cord microenvironments. Accordingly, it can be predicted that such data is of less translational and physiological relevance than that derived from cells grown in neuromimetic environments. Therefore, we have performed the first test of magnetofection technology (enhancing MNP delivery using applied magnetic fields with significant potential for therapeutic application) and its utility in genetically engineering neural stem cells (NSCs; a population of high clinical relevance) propagated in biomimetic hydrogels. We demonstrate magnetic field application safely enhances MNP mediated transfection of NSCs grown as 3D spheroid structures in collagen which more closely replicates the intrinsic mechanical and structural properties of neural tissue than routinely used hard substrates. Further, as it is well known that MNP uptake is mediated by endocytosis we also investigated NSC membrane activity grown on both soft and hard substrates. Using high resolution scanning electron microscopy we were able to prove that NSCs display lower levels of membrane activity on soft substrates compared to hard, a finding which could have particular impact on MNP mediated engineering strategies of cells propagated in physiologically relevant systems

Editorial: crime patterns in time and space: the dynamics of crime opportunities in urban areas

The routine activity approach and associated crime pattern theory emphasise how crime emerges from spatio-temporal routines. In order to understand this crime should be studied in both space and time. However, the bulk of research into crime patterns and related activities has investigated the spatial distributions of crime, neglecting the temporal dimension. Specifically, disaggregation of crime by place and by time, for example hour of day, day of week, month of year, season, or school day versus none school day, is extremely relevant to theory. Modern data make such spatio-temporal disaggregation increasingly feasible, as exemplified in this special issue. First, much larger data files allow disaggregation of crime data into temporal and spatial slices. Second, new forms of data are generated by modern technologies, allowing innovative and new forms of analyses. Crime pattern analyses and routine activity inquiries are now able to explore avenues not previously available. The unique collection of nine papers in this thematic issue specifically examine spatio-temporal patterns of crime to; demonstrate the value of this approach for advancing knowledge in the field; consider how this informs our theoretical understanding of the manifestations of crime in time and space; to consider the prevention implications of this; and to raise awareness of the need for further spatio-temporal research into crime event

Functional analysis of altered Tenascin isoform expression in breast cancer

Background: Cellular interactions with the extracellular matrix (ECM) control many aspects of cell function. The complex ECM protein Tenascin-C (TN), which exists as multiple isoforms, is upregulated in breast cancer. We previously have identified a change in the TN isoform profile in breast cancer, with detection of two additional isoforms — TN16 and TN14/16 — not seen in normal breast [1]. The purpose of this study was to investigate directly the effects of these tumour-associated TNC isoforms on breast cancer cell behaviour

Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy

We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters’ concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals’ neurophysiological observations. At the second level, individuals’ 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions

Characterization of Inhibitory Anti-Duffy Binding Protein II Immunity: Approach to Plasmodium vivax Vaccine Development in Thailand

Plasmodium vivax Duffy binding protein region II (DBPII) is an important vaccine candidate for antibody-mediated immunity against vivax malaria. A significant challenge for vaccine development of DBPII is its highly polymorphic nature that alters sensitivity to neutralizing antibody responses. Here, we aim to characterize naturally-acquired neutralizing antibodies against DBPII in individual Thai residents to give insight into P. vivax vaccine development in Thailand. Anti-DBPII IgG significantly increased in acute vivax infections compared to uninfected residents and naive controls. Antibody titers and functional anti-DBPII inhibition varied widely and there was no association between titer and inhibition activity. Most high titer plasmas had only a moderate to no functional inhibitory effect on DBP binding to erythrocytes, indicating the protective immunity against DBPII binding is strain specific. Only 5 of 54 samples were highly inhibitory against DBP erythrocyte-binding function. Previously identified target epitopes of inhibitory anti-DBPPII IgG (H1, H2 and H3) were localized to the dimer interface that forms the DARC binding pocket. Amino acid polymorphisms (monomorphic or dimorphic) in H1 and H3 protective epitopes change sensitivity of immune inhibition by alteration of neutralizing antibody recognition. The present study indicates Thai variant H1.T1 (R308S), H3.T1 (D384G) and H3.T3 (K386N) are the most important variants for a DBPII candidate vaccine needed to protect P. vivax in Thai residents

Optimal search strategies for identifying sound clinical prediction studies in EMBASE

BACKGROUND: Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges") for retrieval of empirically tested clinical prediction guides from EMBASE. METHODS: An analytic survey was conducted, testing the retrieval performance of search strategies run in EMBASE against the gold standard of hand searching, using a sample of all 27,769 articles identified in 55 journals for the 2000 publishing year. All articles were categorized as original studies, review articles, general papers, or case reports. The original and review articles were then tagged as 'pass' or 'fail' for methodologic rigor in the areas of clinical prediction guides and other clinical topics. Search terms that depicted clinical prediction guides were selected from a pool of index terms and text words gathered in house and through request to clinicians, librarians and professional searchers. A total of 36,232 search strategies composed of single and multiple term phrases were trialed for retrieval of clinical prediction studies. The sensitivity, specificity, precision, and accuracy of search strategies were calculated to identify which were the best. RESULTS: 163 clinical prediction studies were identified, of which 69 (42.3%) passed criteria for scientific merit. A 3-term strategy optimized sensitivity at 91.3% and specificity at 90.2%. Higher sensitivity (97.1%) was reached with a different 3-term strategy, but with a 16% drop in specificity. The best measure of specificity (98.8%) was found in a 2-term strategy, but with a considerable fall in sensitivity to 60.9%. All single term strategies performed less well than 2- and 3-term strategies. CONCLUSION: The retrieval of sound clinical prediction studies from EMBASE is supported by several search strategies

Finding and Resolving Security Misusability with Misusability Cases

Although widely used for both security and usability concerns, scenarios used in security design may not necessarily inform the design of usability, and vice- versa. One way of using scenarios to bridge security and usability involves explicitly describing how design deci- sions can lead to users inadvertently exploiting vulnera- bilities to carry out their production tasks. This paper describes how misusability cases, scenarios that describe how design decisions may lead to usability problems sub- sequently leading to system misuse, address this problem. We describe the related work upon which misusability cases are based before presenting the approach, and illus- trating its application using a case study example. Finally, we describe some findings from this approach that further inform the design of usable and secure systems