Hydroxyurea Use and Hospitalization Trends in a Comprehensive Pediatric Sickle Cell Program

Background

A decline in hospitalizations and pain episodes among those with sickle cell disease (SCD) who take hydroxyurea (HU) has been shown when compared to pre-HU patterns but paradoxically, when compared to those who have never been treated, HU recipients often have more frequent hospitalizations. This analysis evaluates the impact of increasing usage of HU on trends in hospitalizations and blood transfusions within a large SCD treatment program.

Methods

Eligibility was restricted to patients with Hb SS or Hb Sβ⁰-thalassemia who were 2–18 years old between 2006–2010 and received care at St. Jude Children''s Research Hospital (N = 508). Hospitalizations and blood transfusions were calculated for each of the years under study for those exposed and never exposed to HU. Differences in number of hospitalizations before and after HU initiation were compared.

Results

The proportion of patients receiving HU increased by 4% per year on average. In the HU exposed group, a modest decline in mean per-patient hospitalizations and per-patient hospital days occurred, while those never exposed to HU trended toward a slight increase over time. Rates of blood transfusions declined among those on HU but not in patients never exposed to HU. Patients on HU had a median of one fewer hospital admission in the year after initiation of HU, compared to the year prior. Two deaths occurred in the patient population, both of whom were not exposed to HU.

Conclusions

Increasing usage of HU was concurrent with decreased hospitalization rates and blood transfusions. Our results support the utility of HU on decreasing hospitalizations and transfusions for patients with SCD outside of the clinical trial setting.     

ProDeGe: a computational protocol for fully automated decontamination of genomes

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). The procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.Recent technological advancements have enabled the large-scale sampling of genomes from uncultured microbial taxa, through the high-throughput sequencing of single amplified genomes (SAGs; Rinke et al., 2013; Swan et al., 2013) and assembly and binning of genomes from metagenomes (GMGs; Cuvelier et al., 2010; Sharon and Banfield, 2013). The importance of these products in assessing community structure and function has been established beyond doubt (Kalisky and Quake, 2011). Multiple Displacement Amplification (MDA) and sequencing of single cells has been immensely successful in capturing rare and novel phyla, generating valuable references for phylogenetic anchoring. However, efforts to conduct MDA and sequencing in a high-throughput manner have been heavily impaired by contamination from DNA introduced by the environmental sample, as well as introduced during the MDA or sequencing process (Woyke et al., 2011; Engel et al., 2014; Field et al., 2014). Similarly, metagenome binning and assembly often carries various errors and artifacts depending on the methods used (Nielsen et al., 2014). Even cultured isolate genomes have been shown to lack immunity to contamination with other species (Parks et al., 2014; Mukherjee et al., 2015). As sequencing of these genome product types rapidly increases, contaminant sequences are finding their way into public databases as reference sequences. It is therefore extremely important to define standardized and automated protocols for quality control and decontamination, which would go a long way towards establishing quality standards for all microbial genome product types.Current procedures for decontamination and quality control of genome sequences in single cells and metagenome bins are heavily manual and can consume hours/megabase when performed by expert biologists. Supervised decontamination typically involves homology-based inspection of ribosomal RNA sequences and protein coding genes, as well as visual analysis of k-mer frequency plots and guanine–cytosine content (Clingenpeel, 2015). Manual decontamination is also possible through the software SmashCell (Harrington et al., 2010), which contains a tool for visual identification of contaminants from a self-organizing map and corresponding U-matrix. Another existing software tool, DeconSeq (Schmieder and Edwards, 2011), automatically removes contaminant sequences, however, the contaminant databases are required input. The former lacks automation, whereas the latter requires prior knowledge of contaminants, rendering both applications impractical for high-throughput decontamination.Here, we introduce ProDeGe, the first fully automated computational protocol for decontamination of genomes. ProDeGe uses a combination of homology-based and sequence composition-based approaches to separate contaminant sequences from the target genome draft. It has been pre-calibrated to discard at least 84% of the contaminant sequence, which results in retention of a median 84% of the target sequence. The standalone software is freely available at http://prodege.jgi-psf.org//downloads/src and can be run on any system that has Perl, R (R Core Team, 2014), Prodigal (Hyatt et al., 2010) and NCBI Blast (Camacho et al., 2009) installed. A graphical viewer allowing further exploration of data sets and exporting of contigs accompanies the web application for ProDeGe at http://prodege.jgi-psf.org, which is open to the wider scientific community as a decontamination service (Supplementary Figure S1).The assembly and corresponding NCBI taxonomy of the data set to be decontaminated are required inputs to ProDeGe (Figure 1a). Contigs are annotated with genes following which, eukaryotic contamination is removed based on homology of genes at the nucleotide level using the eukaryotic subset of NCBI''s Nucleotide database as the reference. For detecting prokaryotic contamination, a curated database of reference contigs from the set of high-quality genomes within the Integrated Microbial Genomes (IMG; Markowitz et al., 2014) system is used as the reference. This ensures that errors in public reference databases due to poor quality of sequencing, assembly and annotation do not negatively impact the decontamination process. Contigs determined as belonging to the target organism based on nucleotide level homology to sequences in the above database are defined as ‘Clean'', whereas those aligned to other organisms are defined as ‘Contaminant''. Contigs whose origin cannot be determined based on alignment are classified as ‘Undecided''. Classified clean and contaminated contigs are used to calibrate the separation in the subsequent 5-mer based binning module, which classifies undecided contigs as ‘Clean'' or ‘Contaminant'' using principal components analysis (PCA) of 5-mer frequencies. This parameter can also be specified by the user. When data sets do not have taxonomy deeper than phylum level, or a single confident taxonomic bin cannot be detected using sequence alignment, solely 9-mer based binning is used due to more accurate overall classification. In the absence of a user-defined cutoff, a pre-calibrated cutoff for 80% or more specificity separates the clean contigs from contaminated sequences in the resulting PCA of the 9-mer frequency matrix. Details on ProDeGe''s custom database, evaluation of the performance of the system and exploration of the parameter space to calibrate ProDeGe for a high accurate classification rate are provided in the Supplementary Material.Open in a separate windowFigure 1(a) Schematic overview of the ProDeGe engine. (b) Features of data sets used to validate ProDeGe: SAGs from the Arabidopsis endophyte sequencing project, MDM project, public data sets found in IMG but not sequenced at the JGI, as well as genomes from metagenomes. All the data and results can be found in Supplementary Table S3.The performance of ProDeGe was evaluated using 182 manually screened SAGs (Figure 1b,Supplementary Table S1) from two studies whose data sets are publicly available within the IMG system: genomes of 107 SAGs from an Arabidopsis endophyte sequencing project and 75 SAGs from the Microbial Dark Matter (MDM) project* (only 75/201 SAGs from the MDM project had 1:1 mapping between contigs in the unscreened and the manually screened versions, hence these were used; Rinke et al., 2013). Manual curation of these SAGs demonstrated that the use of ProDeGe prevented 5311 potentially contaminated contigs in these data sets from entering public databases. Figure 2a demonstrates the sensitivity vs specificity plot of ProDeGe results for the above data sets. Most of the data points in Figure 2a cluster in the top right of the box reflecting a median retention of 89% of the clean sequence (sensitivity) and a median rejection of 100% of the sequence of contaminant origin (specificity). In addition, on average, 84% of the bases of a data set are accurately classified. ProDeGe performs best when the target organism has sequenced homologs at the class level or deeper in its high-quality prokaryotic nucleotide reference database. If the target organism''s taxonomy is unknown or not deeper than domain level, or there are few contigs with taxonomic assignments, a target bin cannot be assessed and thus ProDeGe removes contaminant contigs using sequence composition only. The few samples in Figure 2a that demonstrate a higher rate of false positives (lower specificity) and/or reduced sensitivity typically occur when the data set contains few contaminant contigs or ProDeGe incorrectly assumes that the largest bin is the target bin. Some data sets contain a higher proportion of contamination than target sequence and ProDeGe''s performance can suffer under this condition. However, under all other conditions, ProDeGe demonstrates high speed, specificity and sensitivity (Figure 2). In addition, ProDeGe demonstrates better performance in overall classification when nucleotides are considered than when contigs are considered, illustrating that longer contigs are more accurately classified (Supplementary Table S1).Open in a separate windowFigure 2ProDeGe accuracy and performance scatterplots of 182 manually curated single amplified genomes (SAGs), where each symbol represents one SAG data set. (a) Accuracy shown by sensitivity (proportion of bases confirmed ‘Clean'') vs specificity (proportion of bases confirmed ‘Contaminant'') from the Endophyte and Microbial Dark Matter (MDM) data sets. Symbol size reflects input data set size in megabases. Most points cluster in the top right of the plot, showing ProDeGe''s high accuracy. Median and average overall results are shown in Supplementary Table S1. (b) ProDeGe completion time in central processing unit (CPU) core hours for the 182 SAGs. ProDeGe operates successfully at an average rate of 0.30 CPU core hours per megabase of sequence. Principal components analysis (PCA) of a 9-mer frequency matrix costs more computationally than PCA of a 5-mer frequency matrix used with blast-binning. The lack of known taxonomy for the MDM data sets prevents blast-binning, thus showing longer finishing times than the endophyte data sets, which have known taxonomy for use in blast-binning.All SAGs used in the evaluation of ProDeGe were assembled using SPAdes (Bankevich et al., 2012). In-house testing has shown that reads assembled with SPAdes from different strains or even slightly divergent species of the same genera may be combined into the same contig (Personal communications, KT and Robert Bowers). Ideally, the DNA in a well that gets sequenced belongs to a single cell. In the best case, contaminant sequences need to be at least from a different species to be recognized as such by the homology-based screening stage. In the absence of closely related sequenced organisms, contaminant sequences need to be at least from a different genus to be recognized as such by the composition-based screening stage (Supplementary Material). Thus, there is little risk of ProDeGe separating sequences from clonal populations or strains. We have found species- and genus-level contamination in MDA samples to be rare.To evaluate the quality of publicly available uncultured genomes, ProDeGe was used to screen 185 SAGs and 14 GMGs (Figure 1b). Compared with CheckM (Parks et al., 2014), a tool which calculates an estimate of genome sequence contamination using marker genes, ProDeGe generally marks a higher proportion of sequence as ‘Contaminant'' (Supplementary Table S2). This is because ProDeGe has been calibrated to perform at high specificity levels. The command line version of ProDeGe allows users to conduct their own calibration and specify a user-defined distance cutoff. Further, CheckM only outputs the proportion of contamination, but ProDeGe actually labels each contig as ‘Clean'' or ‘Contaminant'' during the process of automated removal.The web application for ProDeGe allows users to export clean and contaminant contigs, examine contig gene calls with their corresponding taxonomies, and discover contig clusters in the first three components of their k-dimensional space. Non-linear approaches for dimensionality reduction of k-mer vectors are gaining popularity (van der Maaten and Hinton, 2008), but we observed no systematic advantage of using t-Distributed Stochastic Neighbor Embedding over PCA (Supplementary Figure S2).ProDeGe is the first step towards establishing a standard for quality control of genomes from both cultured and uncultured microorganisms. It is valuable for preventing the dissemination of contaminated sequence data into public databases, avoiding resulting misleading analyses. The fully automated nature of the pipeline relieves scientists of hours of manual screening, producing reliably clean data sets and enabling the high-throughput screening of data sets for the first time. ProDeGe, therefore, represents a critical component in our toolkit during an era of next-generation DNA sequencing and cultivation-independent microbial genomics.     

In vivo surveillance and elimination of teratoma-forming human embryonic stem cells with monoclonal antibody 2448 targeting annexin A2

This study describes the use of a previously reported chimerised monoclonal antibody (mAb), ch2448, to kill human embryonic stem cells (hESCs) in vivo and prevent or delay the formation of teratomas. ch2448 was raised against hESCs and was previously shown to effectively kill ovarian and breast cancer cells in vitro and in vivo. The antigen target was subsequently found to be Annexin A2, an oncofetal antigen expressed on both embryonic cells and cancer cells. Against cancer cells, ch2448 binds and kills via antibody-dependent cell-mediated cytotoxicity (ADCC) and/or antibody-drug conjugate (ADC) routes. Here, we investigate if the use of ch2448 can be extended to hESC. ch2448 was found to bind specifically to undifferentiated hESC but not differentiated progenitors. Similar to previous study using cancer cells, ch2448 kills hESC in vivo either indirectly by eliciting ADCC or directly as an ADC. The treatment with ch2448 post-transplantation eliminated the in vivo circulating undifferentiated cells and prevented or delayed the formation of teratomas. This surveillance role of ch2448 adds an additional layer of safeguard to enhance the safety and efficacious use of pluripotent stem cell-derived products in regenerative medicine. Thereby, translating the use of ch2448 in the treatment of cancers to a proof of concept study in hESC (or pluripotent stem cell [PSC]), we show that mAbs can also be used to eliminate teratoma forming cells in vivo during PSC-derived cell therapies. We propose to use this strategy to complement existing methods to eliminate teratoma-forming cells in vitro. Residual undifferentiated cells may escape in vitro removal methods and be introduced into patients together with the differentiated cells.     

Activity-dependent fluorescent labeling of bacterial cells expressing the TOL pathway

3-Ethynylbenzoate (3EB) functions as a novel, activity-dependent, fluorogenic, and chromogenic probe for bacterial strains expressing the TOL pathway, which degrade toluene via conversion to benzoate, followed by meta ring fission of the intermediate catechol. This direct physiological analysis allows the fluorescent labeling of cells whose toluene-degrading enzymes have been induced by an aromatic substrate.     

Concentration of trace metals in excrements of two species of penguins from different locations of the Antarctic Peninsula

The presence of metals in Antarctica is becoming an issue that needs to be more investigated as human presence is increasing in the region, especially in the Antarctic Peninsula, where most of the polar animals, scientific bases and tourists are concentrated. Penguins are endemic species of Antarctica situated at the top of food web and are useful sentinels of pollution. To improve data of trace metal contamination in the Antarctic Peninsula region, concentrations of Cd, Pb, As, Cu and Zn in fresh excrement of penguins were determined by atomic absorption. Samples were collected in several locations during the 2011/2012 austral summer: eight sites (O’Higgins Station, Yankee Harbour, Mikkelsen Harbor, Danco Island, Gonzalez Videla Base, Yelcho Station and Brown Station) from gentoo penguin (Pygoscelis papua) colonies and four locations (Hydrurga Rocks, Cape Shirreff, Narebski Point and Kopaitic Island) from chinstrap penguin (Pygoscelis antarctica) colonies. Data showed that gentoo penguin colonies had higher levels of metals (μg g^?1 dw) like Pb, Cu and Zn at locations such as O’Higgins (2.89 for Pb, 199.95 for Cu and 379.99 for Zn) and Gonzalez Videla (2.74 for Pb and 222.51 for Cu). Levels of Cd in excreta of chinstrap penguins were higher at Narebski Point (3.13 μg g^?1). The levels of Pb, As, Cd, Cu and Zn were similar or even higher to those reported in excreta of the same species by previous studies at Antarctica. Data suggest that metals ingested by these two penguin species feeding in the sea end up in terrestrial ecosystems.     

Effects of sample treatments on genome recovery via single-cell genomics

Single-cell genomics is a powerful tool for accessing genetic information from uncultivated microorganisms. Methods of handling samples before single-cell genomic amplification may affect the quality of the genomes obtained. Using three bacterial strains we show that, compared to cryopreservation, lower-quality single-cell genomes are recovered when the sample is preserved in ethanol or if the sample undergoes fluorescence in situ hybridization, while sample preservation in paraformaldehyde renders it completely unsuitable for sequencing.Relatively little is known about the functioning of complex microbial communities, largely due to the difficulty in culturing most microbes (Rappe and Giovannoni, 2003). Although metagenomics can provide information on the genetic capabilities of the entire community, it is difficult to connect predicted gene functions to specific organisms using metagenomics (Morales and Holben, 2011). One method to address these challenges is single-cell genomics, where a single microbial cell is isolated from a sample, lysed, and its genome amplified by multiple displacement amplification (MDA; Lasken, 2012; Blainey, 2013).When working with environmental or clinical samples it is generally impractical to work with fresh samples. Most samples need to be preserved in some way before they are studied by single-cell genomics. A possible difficulty is that preservation methods could induce damage to the DNA that would negatively impact genome recovery. The effect of treatments on the cells is especially important in single-cell genomics because it is already established that the process produces incomplete genomes even with fresh cells (Marcy et al., 2007). The average estimated genome completeness of 650 single-cell genomes that are publicly available in IMG (https://img.jgi.doe.gov) is 41%, as based on the presence of conserved single copy genes by the method in Rinke et al. (2013).The purpose of this study was to test the effects of common sample treatments on the recovery of genomes from single cells. Three methods of sample preservation were tested: cryopreservation with 20% glycerol as a cryoprotectant, preservation in 70% ethanol, and preservation in 4% paraformaldehyde. Because paraformaldehyde treatment causes crosslinks between nucleic acids and proteins, we tested cells exposed to 4% paraformaldehyde with and without having their crosslinks reversed by heat treatment. Additionally, there is demand for obtaining single-cell genomes from particular taxa within a microbial community. A common approach for this type of isolation makes use of fluorescence in situ hybridization (FISH) to identify the target cells (Podar et al., 2007; Haroon et al., 2013). Thus, cells that had undergone a typical FISH protocol without prior fixation (Yilmaz et al., 2010) were included as an additional treatment to separate the FISH protocol from the fixation steps.In order to determine if the GC content of a genome would affect the results, three bacterial strains were chosen with differing genomic G+C contents: Pedobacter heparinus DSM 2366, 42% GC; Escherichia coli K12-MG1655, 51% GC; and Meiothermus ruber DSM 1279, 63% GC. These have complete genome sequences available and have the same cell structure (Gram negative) to control for major differences in lysis efficiency. Forty cells of each of the three strains underwent each of the five treatments outlined above (Figure 1).Open in a separate windowFigure 1Schematic of experimental workflow. For clarity the treatments are color coded throughout the figure and are: blue, Cryo—cryopreservation; green, FISH—FISH treatment; yellow, EtOH—ethanol fixation; orange, PFA xlinks—paraformaldehyde fixation with crosslinks reversed; red, PFA—paraformaldehyde fixation with crosslinks intact; brown, Pos—positive controls (wells each with 100 cryopreserved cells); purple, Neg—no cell-negative controls. The layout used for the single cell isolations in a 384-well plate is shown. Each strain/treatment combination was sorted separately onto one plate per strain. The MDA step in this figure plots the Cp (inflection point) values for the real-time MDA amplification curves for all three bacterial species combined. The MDA reaction is run for 16 h, so any wells that show no amplification by that time are indicated as 16+ on the graph. Each column in the chart summarizes data from 120 separate MDA reactions, except for the negative control, which involves 60 reactions. 16S rRNA gene screening indicates the percentage of the wells for each treatment that produced a 16S rRNA gene sequence from the reference organism.All cells underwent an alkaline lysis and MDA (Woyke et al., 2011). The time at which the inflection point of the real-time amplification curves occurs (crossing point; Cp value) correlates with the completeness of the recovered single-cell genomes (Supplementary Figure S1). Cp order was ranked as follows: cryopreservation<FISH<ethanol<paraformaldehyde with crosslinks reversed<paraformaldehyde with crosslinks intact=negative controls (Figure 1). Although the real-time kinetics showed some amplification, in no cases did the MDA products from paraformaldehyde with or without crosslink reversal treatments produce a 16S rRNA gene amplicon from PCR (Figure 1) indicating that the MDA amplicons were likely due to nonspecific amplification of primers. For each strain, eight cells from each of the three treatments that produced the expected 16S rRNA gene sequence and had the earliest Cp times in the treatment (cryopreservation, ethanol, and FISH) were selected for shotgun sequencing.To eliminate any biases due to varying sequencing depth, the sequences were randomly subsampled to a coverage depth of 315 × for each single amplified genome (SAG; Supplementary Figure S2). The reads were mapped to the reference genomes, a de novo assembly was performed and the assembled data were also mapped to the reference genomes.Cryopreservation resulted in SAGs with the highest percentage of the genome recovered for all three strains of bacteria (Figure 2; Supplementary Figure S3). FISH treatment produced reduced genome coverage, and ethanol preservation resulted in the lowest amount of the genome recovered. These treatments are significantly different from each other (Figure 2; Supplementary Figure S3). Despite the trend for cells with a higher GC content to have higher MDA Cp values, there is no clear effect of GC content on the amount of genome recovered by the various treatments (Supplementary Figures S1 and S3).Open in a separate windowFigure 2(a) Coverage plots for each organism/treatment combination. Cryo—cryopreservation, EtOH—ethanol preservation, FISH—FISH treatment. The horizontal black lines in the center of each plot represent the complete reference genomes and the vertical colored lines indicate which parts of the genome were recovered in the assemblies. Redder colors indicate that more single cells contained that region in their assembly. (b) Percent of the genomes recovered for each treatment with the single cells from all three organisms averaged together and the error bars indicating one standard deviation. Light gray bars indicate the genome recovery by mapping the reads to the reference genomes. A base pair was considered to be recovered if at least 10 reads were mapped to cover it. Dark gray bars are the genome recovery by mapping contigs produced by de novo assembly to the reference genomes. The treatments are significantly different from each other (ANOVA; P<0.0001).The lack of amplicons from cells treated with paraformaldehyde is likely due to the crosslinks preventing the phi29 polymerase from accessing the DNA. The heat treatment to reverse the crosslinks was either insufficient to reverse them or resulted in DNA strand breakage and depurination that damaged the DNA sufficiently that it was unable to be amplified.The FISH process is intended to improve access of the oligo probe to its RNA or DNA target site in the cells. As this might result in greater access of the phi29 polymerase to the DNA, one would expect the MDA from this treatment to be the most efficient. However, the fact that the MDA kinetics were delayed and that the genome recovery was reduced compared to the cryopreserved samples indicates that other factors must be involved. As the washing steps should remove the components of the FISH buffers prior to MDA, they would not directly affect the MDA process. Thus, the reduced genome recovery is likely derived from damage to the DNA during the FISH treatment. Since the FISH process can denature high-AT regions of DNA at the temperatures used, the single-stranded DNA that results could be more susceptible to damage (Blake and Delcourt, 1996). This interpretation is supported by the genome recovery in the low-GC-organism P. heparinus being lower than in the other two organisms (Supplementary Figure S3). In addition, it has been shown that formamide can degrade purine nucleosides (Saladino et al., 1996). Small amounts of damage could explain the reduction in the genome recovered by the MDA.The significant reduction in genome recovery from ethanol-preserved cells is challenging to explain. It is unlikely that ethanol could carry over and inhibit the MDA reaction because the cells were washed twice before sorting and the sorting process itself results in significant dilution of the sample (Rodrigue et al., 2009). Since there is no known mechanism for ethanol to damage the DNA, the substantial reduction in the amount of the genome recovered must be due to the polymerase having restricted access to the DNA. Ethanol causes proteins to denature and precipitate (Yoshikawa et al., 2012). These could aggregate around the DNA and prevent access by the polymerase.Although single-cell genomics has great potential to provide insight into the vast number of microbes that have not been cultivated, sample handling can greatly impact the completeness of single-cell genomes. Our results suggest that samples that have been archived by preservation in paraformaldehyde will be unsuitable for the production of single-cell genomes and that ethanol-preserved samples are likely to produce single-cell genomes of reduced quality. Thus, we recommend use of cryopreserved specimens for best results and fixation-free FISH (Yilmaz et al., 2010; Haroon et al., 2013) if targeted flow sorting is to be employed.     

Delays in Admittance-Controlled Haptic Devices Make Simulated Masses Feel Heavier

In an admittance-controlled haptic device, input forces are used to calculate the movement of the device. Although developers try to minimize delays, there will always be delays between the applied force and the corresponding movement in such systems, which might affect what the user of the device perceives. In this experiment we tested whether these delays in a haptic human-robot interaction influence the perception of mass. In the experiment an admittance-controlled manipulator was used to simulate various masses. In a staircase design subjects had to decide which of two virtual masses was heavier after gently pushing them leftward with the right hand in mid-air (no friction, no gravity). The manipulator responded as quickly as possible or with an additional delay (25 or 50 ms) to the forces exerted by the subject on the handle of the haptic device. The perceived mass was ~10% larger for a delay of 25 ms and ~20% larger for a delay of 50 ms. Based on these results, we estimated that the delays that are present in nowadays admittance-controlled haptic devices (up to 20ms) will give an increase in perceived mass which is smaller than the Weber fraction for mass (~10% for inertial mass). Additional analyses showed that the subjects’ decision on mass when the perceptual differences were small did not correlate with intuitive variables such as force, velocity or a combination of these, nor with any other measured variable, suggesting that subjects did not have a consistent strategy during guessing or used other sources of information, for example the efference copy of their pushes.     

Biochemical and pharmacological characterization of the human bradykinin subtype 2 receptor produced in mammalian cells using the Semliki Forest virus system

Bradykinin, a vasoactive peptide, plays a crucial role in many cardiovascular processes via activation of the bradykinin subtype 2 receptor (B2R). B2R, a member of the G protein-coupled receptor (GPCR) superfamily, is a potential drug target in the treatment of cardiovascular disorders, pain and inflammation. In this study, human B2R was expressed at high levels in baby hamster kidney (BHK) cells using Semliki Forest virus-based vectors. The recombinant receptor was produced as a fusion protein with affinity tags and an expression level of 11 pmol/mg (i.e., approx. 0.2 mg of active receptor per liter of culture) was obtained. Radioligand binding analysis revealed that the recombinant receptor binds to its endogenous ligand bradykinin with high affinity (Kd = 0.12 nM) and its pharmacological profile was similar to that of B2R in native tissues. Bradykinin-stimulated accumulation of inositol phosphate was observed in BHK cells expressing the recombinant receptor, which indicated the activation of endogenous G alpha(q) protein by the recombinant B2R. Confocal laser scanning microscopy and immunogold staining revealed that the recombinant receptor was predominantly localized intracellularly. To the best of our knowledge, this is the first report of an affinity-tagged recombinant B2R been expressed at high levels in BHK cells and extensively characterized.     

Fixed Dystonia in Complex Regional Pain Syndrome: a Descriptive and Computational Modeling Approach

Background  

Complex regional pain syndrome (CRPS) may occur after trauma, usually to one limb, and is characterized by pain and disturbed blood flow, temperature regulation and motor control. Approximately 25% of cases develop fixed dystonia. Involvement of dysfunctional GABAergic interneurons has been suggested, however the mechanisms that underpin fixed dystonia are still unknown. We hypothesized that dystonia could be the result of aberrant proprioceptive reflex strengths of position, velocity or force feedback.