Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESCs), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI) histograms. Moreover, the algorithm calculates ISI thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average (CMA) and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA) data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays

Morphological Analysis of technologies using multidimensional scaling

This study focuses on the application of Morphological Analysis to making technology analyses. In this study, Morphological Analysis is used as a framework for applying expert opinion, bibliometrics, text mining and multidimensional scaling to problem- structuring. We describe the method used as well as its application and apply it to a case of portable fuel cell technology. The results demonstrate the practicality of using Morphological Analysis in structuring complex problems and offer an example of its application in assessing the status of a technology.<br

General state-space population dynamics model for Bayesian stock assessment

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FLT3-ITD allelic ratio and HLF expression predict FLT3 inhibitor efficacy in adult AML

FLT3 internal tandem duplication (FLT3-ITD) is a frequent mutation in acute myeloid leukemia (AML) and remains a strong prognostic factor due to high rate of disease recurrence. Several FLT3-targeted agents have been developed, but determinants of variable responses to these agents remain understudied. Here, we investigated the role FLT3-ITD allelic ratio (ITD-AR), ITD length, and associated gene expression signatures on FLT3 inhibitor response in adult AML. We performed fragment analysis, ex vivo drug testing, and next generation sequencing (RNA, exome) to 119 samples from 87 AML patients and 13 healthy bone marrow controls. We found that ex vivo response to FLT3 inhibitors is significantly associated with ITD-AR, but not with ITD length. Interestingly, we found that the HLF gene is overexpressed in FLT3-ITD+ AML and associated with ITD-AR. The retrospective analysis of AML patients treated with FLT3 inhibitor sorafenib showed that patients with high HLF expression and ITD-AR had better clinical response to therapy compared to those with low ITD-AR and HLF expression. Thus, our findings suggest that FLT3 ITD-AR together with increased HLF expression play a role in variable FLT3 inhibitor responses observed in FLT3-ITD+ AML patients.Peer reviewe

Amine-modified hyaluronic acid-functionalized porous silicon nanoparticles for targeting breast cancer tumors

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The genetic variant rs4073 A→T of the Interleukin-8 promoter region is associated with the earlier onset of exudative age-related macular degeneration

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Hierarchical Porous Silicon and Porous Silicon Nanowires Produced with Regenerative Electroless Etching (ReEtching) and Metal Assisted Catalytic Etching (MACE)

ReEtching produces nanostructured silicon when a catalytic agent, e.g. dissolved V2O5, is used to facilitate etching between Si and H2O2. H2O2 regenerates dissolved V in a 5+ oxidation state, which initiates etching by injecting holes into the Si valence band. Independent control over the extent of reaction (controlled by the amount of H2O2 added) and the rate of reaction (controlled by the rate at which H2O2 is pumped into the etchant solution) allows us to porosify Si substrates of arbitrary size, shape and doping, including wafers, single-crystal powders, polycrystalline powders, metallurgical grade powder, Si nanowires, Si pillars and Si powders that have been textured with metal-assisted catalytic etching (MACE). Similarly, improved control over the nucleation and etching in MACE is achieved by pumped delivery of reagents. Nanowires are not produced directly by MACE of powders, rather they form when a porosified layers is cleaved by capillary forces or sonication

Preparation and biological evaluation of ethionamide-mesoporous silicon nanoparticles against Mycobacterium tuberculosis

Ethionamide (ETH) is an important second-line antituberculosis drug used for the treatment of patients infected with multidrug-resistant Mycobacterium tuberculosis. Recently, we reported that the loading of ETH into thermally carbonized-porous silicon (TCPSi) nanoparticles enhanced the solubility and permeability of ETH at different pH-values and also increased its metabolization process. Based on these results, we synthesized carboxylic acid functionalized thermally hydrocarbonized porous silicon nanoparticles (UnTHCPSi NPs) conjugated with ETH and its antimicrobial effect was evaluated against Mycobacterium tuberculosis strain H37Rv. The activity of the conjugate was increased when compared to free-ETH, which suggests that the nature of the synergy between the NPs and ETH is likely due to the weakening of the bacterial cell wall that improves conjugate-penetration. These ETH-conjugated NPs have great potential in reducing dosing frequency of ETH in the treatment of multidrug-resistant tuberculosis (MDR-TB). (C) 2016 Elsevier Ltd. All rights reserved.Fundação para a Ciência e Tecnologia (FCT, Portugal) and FEDER (European Union) for funding through UID/MULTI/04378/2013, project grant IF/00092/2014 and IF2014 position. Thanks are also due to “Comissão de Coordenação e Desenvolvimento Regional do Norte (CCDR-N)/NORTE2020/Portugal 2020” for funding through project DESignBIOtechHealth (ref. Norte-01-0145-FEDER-000024). H.A.S. acknowledges financial support from the Academy of Finland (decision nos. 252215 and 281300), the University of Helsinki Research Funds, the Biocentrum Helsinki, and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013, Grant No. 310892). The content is solely the responsibility of the authors and does not necessarily represent the official views of the FCT or CCDR-Ninfo:eu-repo/semantics/publishedVersio

Quantitative Analysis of Porous Silicon Nanoparticles Functionaliza-tion by 1H NMR

Porous silicon (PSi) nanoparticles have been applied in various fields, such as catalysis, imaging, and biomedical applications, because of their large specific surface area, easily modifiable surface chemistry, biocompatibility, and biodegradability. For biomedical applications, it is important to precisely control the surface modification of PSi-based materials and quantify the functionalization density, which determines the nanoparticle’s behavior in the biological system. Therefore, we propose here an optimized solution to quantify the functionalization groups on PSi, based on the nuclear magnetic resonance (NMR) method by combining the hydrolysis with standard 1H NMR experiments. We optimized the hydrolysis conditions to degrade the PSi, providing mobility to the molecules for NMR detection. The NMR parameters were also optimized by relaxation delay and the number of scans to provide reliable NMR spectra. With an internal standard, we quantitatively analyzed the surficial amine groups and their sequential modification of polyethylene glycol. Our investigation provides a reliable, fast, and straightforward method in quantitative analysis of the surficial modification characterization of PSi requiring a small amount of sample.Peer reviewe