A miniaturized sandwich immunoassay platform for the detection of protein-protein interactions

<p>Abstract</p> <p>Background</p> <p>Analysis of protein-protein interactions (PPIs) is a valuable approach for the characterization of huge networks of protein complexes or proteins of unknown function. Co-immunoprecipitation (coIP) using affinity resins coupled to protein A/G is the most widely used method for PPI detection. However, this traditional large scale resin-based coIP is too laborious and time consuming. To overcome this problem, we developed a miniaturized sandwich immunoassay platform (MSIP) by combining antibody array technology and coIP methods.</p> <p>Results</p> <p>Based on anti-FLAG antibody spotted aldehyde slides, MSIP enables simple, rapid and large scale detection of PPIs by fluorescent labeling anti-myc antibody. By analyzing well-known interacting and non-interacting protein pairs, MSIP was demonstrated to be highly accurate and reproducible. Compared to traditional resin-based coIP, MSIP results in higher sensitivity and enhanced throughput, with the additional benefit of digital read-outs. In addition, MSIP was shown to be a highly useful validation platform to confirm PPI candidates that have been identified from yeast two hybrid systems.</p> <p>Conclusions</p> <p>In conclusion, MSIP is proved to be a simple, cost-saving and highly efficient technique for the comprehensive study of PPIs.</p

Combined exome and whole-genome sequencing identifies mutations in ARMC4 as a cause of primary ciliary dyskinesia with defects in the outer dynein arm

Primary ciliary dyskinesia (PCD) is a rare, genetically heterogeneous ciliopathy disorder affecting cilia and sperm motility. A range of ultrastructural defects of the axoneme underlie the disease, which is characterised by chronic respiratory symptoms and obstructive lung disease, infertility and body axis laterality defects. We applied a next-generation sequencing approach to identify the gene responsible for this phenotype in two consanguineous families

Design and optimization of an advanced time-of-flight neutron spectrometer for deuterium plasmas of the large helical device

A time-of-flight neutron spectrometer based on the Time-Of-Flight Enhanced Diagnostic (TOFED) concept has been designed and is under development for the Large Helical Device (LHD). It will be the first advanced neutron spectrometer to measure the 2.45 MeV D–D neutrons (DDNs) from helical/stellarator plasmas. The main mission of the new TOFED is to study the supra-thermal deuterons generated from the auxiliary heating systems in helical plasmas by measuring the time-of-flight spectra of DDN. It will also measure the triton burnup neutrons (TBNs) from the d+t reactions, unlike the original TOFED in the EAST tokamak. Its capability of diagnosing the TBN ratios is evaluated in this work. This new TOFED is expected to be installed in the basement under the LHD hall and shares the collimator with one channel of the vertical neutron camera to define its line of sight. The distance from its primary scintillators to the equatorial plane of LHD plasmas is about 15.5 m. Based on Monte Carlo simulation by a GEANT4 model, the resolution of the DDN energy spectra is 6.6%. When projected onto the neutron rates that are typically obtained in LHD deuterium plasmas (an order of 1015 n/s with neutral beam injection), we expect to obtain the DDN and TBN counting rates of about 2.5 · 105 counts/s and 250 counts/s, respectively. This will allow us to analyze the DDN time-of-flight spectra on time scales of 0.1 s and diagnose the TBN emission rates in several seconds with one instrument, for the first time in helical/stellarator plasmas

Induction of antigen-specific tolerance through hematopoietic stem cell-mediated gene therapy: the future for therapy of autoimmune disease?

Based on the principle that immune ablation followed by HSC-mediated recovery purges disease-causing leukocytes to interrupt autoimmune disease progression, hematopoietic stem cell transplantation (HSCT) has been increasingly used as a treatment for severe autoimmune diseases. Despite clinically-relevant outcomes, HSCT is associated with serious iatrogenic risks and is suitable only for the most serious and intractable diseases. A further limitation of autologous HSCT is that relapse rates can be high, suggesting disease-causing leukocytes are incompletely purged or the environmental and genetic determinants that drive disease remain active. Incorporation of antigen-specific tolerance approaches that synergise with autologous HSCT could reduce or prevent relapse. Further, by reducing the requirement for highly toxic immune-ablation and instead relying on antigen-specific tolerance, the clinical utility of HSCT could be significantly diversified. Substantial progress has been made exploring HSCT-mediated induction of antigen-specific tolerance in animal models but studies have focussed on primarily on prevention of autoimmune diseases. However, as diagnosis of autoimmune disease is often not made until autoimmune disease is well developed and populations of autoantigen-specific pathogenic effector and memory T cells have become well established, immunotherapies must be developed to address effector and memory T-cell responses which have traditionally been considered the key impediment to immunotherapy. Here, focusing on T-cell mediated autoimmune diseases we review progress made in antigen-specific immunotherapy using HSCT-mediated approaches, induction of tolerance in effector and memory T cells and the challenges for progression and clinical application of antigen-specific ‘tolerogenic’ HSCT therapy

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Concentration-Invariant Odor Representation in the Olfactory System by Presynaptic Inhibition

The present study investigates a network model for implementing concentration-invariant representation for odors in the olfactory system. The network consists of olfactory receptor neurons, projection neurons, and inhibitory local neurons. Receptor neurons send excitatory inputs to projection neurons, which are modulated by the inhibitory inputs from local neurons. The modulation occurs at the presynaptic site from a receptor neuron to a projection one, leading to the operation of divisive normalization. The responses of local interneurons are determined by the total activities of olfactory receptor neurons. We find that with a proper parameter condition, the responses of projection neurons become effectively independent of the odor concentration. Simulation results confirm our theoretical analysis

Circuit motifs for contrast-adaptive differentiation in early sensory systems: the role of presynaptic inhibition and short-term plasticity.

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems

Personalized Standard Deviations Improve the Baseline Estimation of Collaborative Filtering Recommendation

Baseline estimation is a critical component for latent factor-based collaborative filtering (CF) recommendations to obtain baseline predictions by evaluating global deviations for both users and items from personalized ratings. Classical baseline estimation presupposes that the user&rsquo;s factual rating range is the same as the system&rsquo;s given rating range. However, from observations on real datasets of movie recommender systems, we found that different users have different actual rating ranges, and users can be classified into four kinds according to their personalized rating criterion, including normal, strict, lenient, and middle. We analyzed ratings&rsquo; distributions and found that the proportion of user ratings&rsquo; local standard deviation to the system&rsquo;s global standard deviation is equal to that of the user&rsquo;s actual rating range to the system&rsquo;s rating range. We propose an improved and unified baseline estimation model based on the standard deviation&rsquo;s proportion to alleviate the influence of classical baseline estimation&rsquo;s limitation. We also apply the proposed baseline estimation model in existing latent factor-based CF recommendations and propose two instances. We performed experiments on full ratings of datasets by cross evaluations, including Flixster, Movielens (10 M), Movielens (latest small), FilmTrust, and MiniFilm. The results prove that the proposed baseline estimation model has better predictive accuracy than the classical model and is efficient in improving prediction performance for existing latent factor-based CF recommendations

Contrast adaptive perfect differentiation.

<p>A: <b>PostE</b> neurons’ transient firing rate response for different input contrasts (low, medium, and high). B: Normalizing the <b>PostE</b> neurons’ response (of panel A) to the peak amplitude reveals the contrast dependent dynamics of the decay. C: Estimated filters for the three stimulus contrasts. Note that the width of the integration window (positive part) is stimulus contrast dependent. D: When varying the baseline activity of <b>PreE</b> neurons (<i>r</i>₁) while fixing the contrast to 2 (by setting <i>r</i>₂ accordingly), the estimated filter remains identical. Thus, the estimated filter of the PI circuit is intensity invariant. Parameters: <i>r</i>₁ = 20 Hz, <i>r</i>₂ = 60 Hz, 140 Hz and 220 Hz.</p

The complete chloroplast genome of a distinctive fern, Coniogramme intermedia Hieron. (Pteridaceae)

Coniogramme intermedia Hieron. is a morphologically distinctive species in the genus. It is identified by lanceolate pinnules with serrated margins, free veins, hydathodes extending into teeth, and laminae abaxially hairy. It is mainly distributed in the tropical and subtropical regions of Asia. Herein, we report the first complete chloroplast genome sequence of C. intermedia. Also, it is the opening one of the genus Coniogramme Fée. The chloroplast genome sequence is 153,561 bp in length. The genome has a typical quadripartite structure, including a large single-copy (LSC) region of 82,817 bp, a small single-copy (SSC) region of 21,236 bp, and two inverted repeat (IR) regions of 24,754bp each. The total GC content is 45.0%. The complete plastome sequence contains 114 genes, including, 81 protein-coding, 29 tRNA, and four rRNA genes. The phylogenetic analysis of Pteridaceae based on the complete chloroplast genomes was also presented in this study