9,160 research outputs found
Fast non-negative deconvolution for spike train inference from population calcium imaging
Calcium imaging for observing spiking activity from large populations of
neurons are quickly gaining popularity. While the raw data are fluorescence
movies, the underlying spike trains are of interest. This work presents a fast
non-negative deconvolution filter to infer the approximately most likely spike
train for each neuron, given the fluorescence observations. This algorithm
outperforms optimal linear deconvolution (Wiener filtering) on both simulated
and biological data. The performance gains come from restricting the inferred
spike trains to be positive (using an interior-point method), unlike the Wiener
filter. The algorithm is fast enough that even when imaging over 100 neurons,
inference can be performed on the set of all observed traces faster than
real-time. Performing optimal spatial filtering on the images further refines
the estimates. Importantly, all the parameters required to perform the
inference can be estimated using only the fluorescence data, obviating the need
to perform joint electrophysiological and imaging calibration experiments.Comment: 22 pages, 10 figure
Down regulation of the high-affinity IgE receptor associated with successful treatment of chronic idiopathic urticaria with omalizumab
Chronic idiopathic urticaria is a condition that is often controllable with antihistamine therapy. However, some patients have disease burden that is difficult to manage, non-responsive to antihistamines and often requires immunosuppressive medications such as corticosteroids or cyclosporine. We present here a study that demonstrates the effectiveness of omalizumab in treating this condition and the temporal relationship between improvement and down regulation of the high affinity IgE receptor (FcεRI). For this, blood samples were obtained from a symptomatic patient before each treatment and processed for flow cytometric analysis of FcεRI levels on the surface of blood basophils. Down regulation of FcεRI was observed in association with significant clinical improvement and discontinuation of immunosuppressive medications
Influences of Excluded Volume of Molecules on Signaling Processes on Biomembrane
We investigate the influences of the excluded volume of molecules on
biochemical reaction processes on 2-dimensional surfaces using a model of
signal transduction processes on biomembranes. We perform simulations of the
2-dimensional cell-based model, which describes the reactions and diffusion of
the receptors, signaling proteins, target proteins, and crowders on the cell
membrane. The signaling proteins are activated by receptors, and these
activated signaling proteins activate target proteins that bind autonomously
from the cytoplasm to the membrane, and unbind from the membrane if activated.
If the target proteins bind frequently, the volume fraction of molecules on the
membrane becomes so large that the excluded volume of the molecules for the
reaction and diffusion dynamics cannot be negligible. We find that such
excluded volume effects of the molecules induce non-trivial variations of the
signal flow, defined as the activation frequency of target proteins, as
follows. With an increase in the binding rate of target proteins, the signal
flow varies by i) monotonically increasing; ii) increasing then decreasing in a
bell-shaped curve; or iii) increasing, decreasing, then increasing in an
S-shaped curve. We further demonstrate that the excluded volume of molecules
influences the hierarchical molecular distributions throughout the reaction
processes. In particular, when the system exhibits a large signal flow, the
signaling proteins tend to surround the receptors to form receptor-signaling
protein clusters, and the target proteins tend to become distributed around
such clusters. To explain these phenomena, we analyze the stochastic model of
the local motions of molecules around the receptor.Comment: 31 pages, 10 figure
Projective simulation for artificial intelligence
We propose a model of a learning agent whose interaction with the environment
is governed by a simulation-based projection, which allows the agent to project
itself into future situations before it takes real action. Projective
simulation is based on a random walk through a network of clips, which are
elementary patches of episodic memory. The network of clips changes
dynamically, both due to new perceptual input and due to certain compositional
principles of the simulation process. During simulation, the clips are screened
for specific features which trigger factual action of the agent. The scheme is
different from other, computational, notions of simulation, and it provides a
new element in an embodied cognitive science approach to intelligent action and
learning. Our model provides a natural route for generalization to
quantum-mechanical operation and connects the fields of reinforcement learning
and quantum computation.Comment: 22 pages, 18 figures. Close to published version, with footnotes
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Presumptive self-diagnosis of malaria and other febrile illnesses in Sierra Leone
Introduction: The objective of this study was to evaluate the prevalence of self-diagnosis of malaria and other febrile illnesses in Bo, Sierra Leone. Methods: All households in two neighboring sections of Bo were invited to participate in a cross-sectional survey. Results: A total of 882 households (an 85% participation rate) that were home to 5410 individuals participated in the study. Of the 910 individuals reported to have had what the household considered to be malaria in the past month, only 41% were diagnosed by a healthcare professional or a laboratory test. Of the 1402 individuals reported to have had any type of febrile illness within the past six months, only 34% had sought a clinical or laboratory diagnosis. Self-diagnosis of influenza, yellow fever, typhoid, and pneumonia was also common. Conclusion: Self-diagnosis and presumptive treatment with antimalarial drugs and other antibiotic medications that are readily available without a prescription may compromise health outcomes for febrile adults and children.Key words: Malaria, fevers, self-care, health services accessibility, community pharmacy services, West Afric
Majorana Zero-modes and Topological Phases of Multi-flavored Jackiw-Rebbi model
Motivated by the recent Kitaev's K-theory analysis of topological insulators
and superconductors, we adopt the same framework to study the topological phase
structure of Jackiw-Rebbi model in 3+1 dimensions. According to the K-theory
analysis based on the properties of the charge conjugation and time reversal
symmetries, we classify the topological phases of the model. In particular, we
find that there exist Majorana zero-modes hosted by the
hedgehogs/t'Hooft-Polyakov monopoles, if the model has a time reversal
symmetry. Guided by the K-theory results, we then explicitly show that a single
Majorana zero mode solution exists for the SU(2) doublet fermions in some
co-dimensional one planes of the mass parameter space. It turns out we can see
the existence of none or a single zero mode when the fermion doublet is only
two. We then take a step further to consider four-fermion case and find there
can be zero, one or two normalizable zero mode in some particular choices of
mass matrices. Our results also indicate that a single normalizable Majorana
zero mode can be compatible with the cancellation of SU(2) Witten anomaly.Comment: 29 pages, 3 figures; v2, typos correcte
Two-dimensional amine and hydroxy functionalized fused aromatic covalent organic framework
Ordered two-dimensional covalent organic frameworks (COFs) have generally been synthesized using reversible reactions. It has been difficult to synthesize a similar degree of ordered COFs using irreversible reactions. Developing COFs with a fused aromatic ring system via an irreversible reaction is highly desirable but has remained a significant challenge. Here we demonstrate a COF that can be synthesized from organic building blocks via irreversible condensation (aromatization). The as-synthesized robust fused aromatic COF (F-COF) exhibits high crystallinity. Its lattice structure is characterized by scanning tunneling microscopy and X-ray diffraction pattern. Because of its fused aromatic ring system, the F-COF structure possesses high physiochemical stability, due to the absence of hydrolysable weak covalent bonds
A computational framework to emulate the human perspective in flow cytometric data analysis
Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation.
<p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods.
<p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics
Holographic Anyons in the ABJM Theory
We consider the holographic anyons in the ABJM theory from three different
aspects of AdS/CFT correspondence. First, we identify the holographic anyons by
using the field equations of supergravity, including the Chern-Simons terms of
the probe branes. We find that the composite of Dp-branes wrapped over CP3 with
the worldvolume magnetic fields can be the anyons. Next, we discuss the
possible candidates of the dual anyonic operators on the CFT side, and find the
agreement of their anyonic phases with the supergravity analysis. Finally, we
try to construct the brane profile for the holographic anyons by solving the
equations of motion and Killing spinor equations for the embedding profile of
the wrapped branes. As a by product, we find a BPS spiky brane for the dual
baryons in the ABJM theory.Comment: 1+33 pages, 3 figures; v2 discussion for D4-D6 case added, references
added; v3 comments adde
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