514 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
Modeling genome-wide replication kinetics reveals a mechanism for regulation of replication timing
We developed analytical models of DNA replication that include probabilistic initiation of origins, fork progression, passive replication, and asynchrony.We fit the model to budding yeast genome-wide microarray data probing the replication fraction and found that initiation times correlate with the precision of timing.We extracted intrinsic origin properties, such as potential origin efficiency and firing-time distribution, which cannot be done using phenomenological approaches.We propose that origin timing is controlled by stochastically activated initiators bound to origin sites rather than explicit time-measuring mechanisms
Misaligned spin and orbital axes cause the anomalous precession of DI Herculis
The orbits of binary stars precess as a result of general relativistic
effects, forces arising from the asphericity of the stars, and forces from
additional stars or planets in the system. For most binaries, the theoretical
and observed precession rates are in agreement. One system, however -- DI
Herculis -- has resisted explanation for 30 years. The observed precession rate
is a factor of four slower than the theoretical rate, a disagreement that once
was interpreted as evidence for a failure of general relativity. Among the
contemporary explanations are the existence of a circumbinary planet and a
large tilt of the stellar spin axes with respect to the orbit. Here we report
that both stars of DI Herculis rotate with their spin axes nearly perpendicular
to the orbital axis (contrary to the usual assumption for close binary stars).
The rotationally induced stellar oblateness causes precession in the direction
opposite to that of relativistic precession, thereby reconciling the
theoretical and observed rates.Comment: Nature, in press [11 pg
Ultrasonic Characterization of Porosity in Composites
The determination of levels of porosity is important in the engineering uses of graphite fiber/polymer matrix composites, since the interlaminar shear strength can be greatly reduced by excessive porosity [1]. Research in making nondestructive evaluations using ultrasonics as the probing energy has taken many directions. Hsu [2] has successfully modeled the frequency dependent attenuation to predict porosity levels in composites. Kline [3] has extended the work of Hashsin and Rosen [4] to determine the porosity and fiber volume fraction of composites by solving for the elastic coefficients of the composite structure. The propagation of leaky Lamb waves [5] has also been used to model porosity levels
Cavitation of Electrons Bubbles in Liquid Helium Below saturation Pressure
We have used a Hartree-type electron-helium potential together with a density
functional description of liquid He and He to study the explosion of
electron bubbles submitted to a negative pressure. The critical pressure at
which bubbles explode has been determined as a function of temperature. It has
been found that this critical pressure is very close to the pressure at which
liquid helium becomes globally unstable in the presence of electrons. It is
shown that at high temperatures the capillary model overestimates the critical
pressures. We have checked that a commonly used and rather simple
electron-helium interaction yields results very similar to those obtained using
the more accurate Hartree-type interaction. We have estimated that the
crossover temperature for thermal to quantum nucleation of electron bubbles is
very low, of the order of 6 mK for He.Comment: 22 pages, 9 figure
Distributions of charged massive scalars and fermions from evaporating higher-dimensional black holes
A detailed numerical analysis is performed to obtain the Hawking spectrum for
charged, massive brane scalars and fermions on the approximate background of a
brane charged rotating higher-dimensional black hole constructed in
arXiv:0907.5107. We formulate the problem in terms of a "spinor-like" first
order system of differential wave equations not only for fermions, but for
scalars as well and integrate it numerically. Flux spectra are presented for
non-zero mass, charge and rotation, confirming and extending previous results
based on analytic approximations. In particular we describe an inverted charge
splitting at low energies, which is not present in four or five dimensions and
increases with the number of extra dimensions. This provides another signature
of the evaporation of higher-dimensional black holes in TeV scale gravity
scenarios.Comment: 19 pages, 6 figures, minor typos corrected, 1 page added with a
discussion on higher spins, added reference
Very low prevalence of epidermal growth factor receptor (EGFR) protein expression and gene amplification in Saudi breast cancer patients
<p>Abstract</p> <p>Background</p> <p>Breast cancers which demonstrate EGFR protein expression, gene amplification and/or gene mutations may benefit therapeutically from tyrosine kinase inhibitors. In Western studies, EGFR protein expression has been demonstrated in 7-36% of breast cancer patients, while gene amplification has been found in around 6% of cases and mutations were either absent or extremely rare. Studies addressing EGFR protein expression and gene amplification in Saudi breast cancer patients are extremely scanty and the results reported have been mostly non-conclusive. Herein we report the prevalence of EGFR protein expression and gene amplification in a cohort of Saudi breast cancer patients.</p> <p>Findings</p> <p>We noticed a remarkably low incidence of EGFR protein expression (1.3%) while analyzing the spectrum of molecular subtypes of breast cancer in a Saudi population by immunohistochemistry. Also, <it>EGFR </it>gene amplification could not be demonstrated in any of 231 cases studied using silver enhanced <it>in situ </it>hybridization.</p> <p>Conclusions</p> <p>The extremely low incidence of EGFR protein expression and gene amplification in Saudi breast cancer patients as compared to Western populations is most probably ethnically related as supported by our previous finding in the same cohort of a spectrum of molecular breast cancer types that is unique to the Saudi population and in stark contrast with Western and other regionally based studies. Further support to this view is provided by earlier studies from Saudi Arabia that have similarly shown variability in molecular breast cancer subtype distribution between Saudi and Caucasian populations as well as a predominance of the high-grade pathway in breast cancer development in Middle East women. More studies on EGFR in breast cancer are needed from different regions of Saudi Arabia before our assumption can be confirmed, however.</p
Antisense DNA parameters derived from next-nearest-neighbor analysis of experimental data
<p>Abstract</p> <p>Background</p> <p>The enumeration of tetrameric and other sequence motifs that are positively or negatively correlated with <it>in vivo </it>antisense DNA effects has been a useful addition to the arsenal of information needed to predict effective targets for antisense DNA control of gene expression. Such retrospective information derived from <it>in vivo </it>cellular experiments characterizes aspects of the sequence dependence of antisense inhibition that are not predicted by nearest-neighbor (NN) thermodynamic parameters derived from <it>in vitro </it>experiments. However, quantitation of the antisense contributions of motifs is problematic, since individual motifs are not isolated from the effects of neighboring nucleotides, and motifs may be overlapping. These problems are circumvented by a next-nearest-neighbor (NNN) analysis of antisense DNA effects in which the overlapping nature of nearest-neighbors is taken into account.</p> <p>Results</p> <p>Next-nearest-neighbor triplet combinations of nucleotides are the simplest that include overlapping sequence effects and therefore can encompass interactions beyond those of nearest neighbors. We used singular value decomposition (SVD) to fit experimental data from our laboratory in which phosphorothioate-modified antisense DNAs (S-DNAs) 20 nucleotides long were used to inhibit cellular protein expression in 112 experiments involving four gene targets and two cell lines. Data were fitted using a NNN model, neglecting end effects, to derive NNN inhibition parameters that could be combined to give parameters for a set of 49 sequences that represents the inhibitory effects of all possible overlapping triplet interactions in the cellular targets of these antisense S-DNAs. We also show that parameters to describe subsets of the data, such as the mRNAs being targeted and the cell lines used, can be included in such a derivation. While NNN triplet parameters provided an adequate model to fit our data, NN doublet parameters did not.</p> <p>Conclusions</p> <p>The methodology presented illustrates how NNN antisense inhibitory information can be derived from <it>in vivo </it>cellular experiments. Subsequent calculations of the antisense inhibitory parameters for any mRNA target sequence automatically take into account the effects of all possible overlapping combinations of nearest-neighbors in the sequence. This procedure is more robust than the tallying of tetrameric motifs that have positive or negative antisense effects. The specific parameters derived in this work are limited in their applicability by the relatively small database of experiments that was used in their derivation.</p
Contrasting effects of hemiparasites on ecosystem processes: can positive litter effects offset the negative effects of parasitism?
Hemiparasites are known to influence community structure and ecosystem functioning, but the underlying mechanisms are not well studied. Variation in the impacts of hemiparasites on diversity and production could be due to the difference in the relative strength of two interacting pathways: direct negative effects of parasitism and positive effects on N availability via litter. Strong effects of parasitism should result in substantial changes in diversity and declines in productivity. Conversely, strong litter effects should result in minor changes in diversity and increased productivity. We conducted field-based surveys to determine the association of Castillejaoccidentalis with diversity and productivity in the alpine tundra. To examine litter effects, we compared the decomposition of Castilleja litter with litter of four other abundant plant species, and examined the decomposition of those four species when mixed with Castilleja. Castilleja was associated with minor changes in diversity but almost a twofold increase in productivity and greater foliar N in co-occurring species. Our decomposition trials suggest litter effects are due to both the rapid N loss of Castilleja litter and the effects of mixing Castilleja litter with co-occurring species. Castilleja produces litter that accelerates decomposition in the alpine tundra, which could accelerate the slow N cycle and boost productivity. We speculate that these positive effects of litter outweigh the effects of parasitism in nutrient-poor systems with long-lived hemiparasites. Determining the relative importance of parasitism and litter effects of this functional group is crucial to understand the strong but variable roles hemiparasites play in affecting community structure and ecosystem processes
A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls.
BACKGROUND: Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. RESULTS: A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups. CONCLUSION: The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles
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