2,380 research outputs found
Parametric bootstrap approximation to the distribution of EBLUP and related prediction intervals in linear mixed models
Empirical best linear unbiased prediction (EBLUP) method uses a linear mixed
model in combining information from different sources of information. This
method is particularly useful in small area problems. The variability of an
EBLUP is traditionally measured by the mean squared prediction error (MSPE),
and interval estimates are generally constructed using estimates of the MSPE.
Such methods have shortcomings like under-coverage or over-coverage, excessive
length and lack of interpretability. We propose a parametric bootstrap approach
to estimate the entire distribution of a suitably centered and scaled EBLUP.
The bootstrap histogram is highly accurate, and differs from the true EBLUP
distribution by only , where is the number of parameters
and the number of observations. This result is used to obtain highly
accurate prediction intervals. Simulation results demonstrate the superiority
of this method over existing techniques of constructing prediction intervals in
linear mixed models.Comment: Published in at http://dx.doi.org/10.1214/07-AOS512 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Studies of protein post-translational modifications using high resolution tandem mass spectrometry
Electron capture dissociation (ECD) is a powerful and superior
tandem mass spectrometry (MS) fragmentation technique in the study of
protein post-translational modifications (PTMs) due to its unique features
of preserving labile modifications and providing more detailed sequence
information, which has been used to study protein platination and
disulfide linked proteins. Cisplatin was found cross-linking multiple
methionine (Met) pairs on calmodulin (CaM). The crossâlinking of
cisplatin to apoâCaM or CaâCaM can inhibit the ability of CaM to
recognize its target proteins as proved by a melittin binding assay. To
further establish MS strategies to quickly assign the platinum-modification
sites, a series of peptides with potential cisplatin binding sites were
reacted with cisplatin and then analyzed by ECD. Radical-mediated side
chain losses from the charge-reduced M+Pt species (such as CH3Sâą or
CH3SH from Met, SHâą from Cys, CO2 from Glu or Asp, and NH2âą from
amine groups) were found to be characteristic indicators for rapid and
unambiguous localization of the Pt-modification sites on certain amino
acid residues. Furthermore, the potential of cisplatin as a protein crosslinking
reagent was further explored and demonstrated on other peptides
and proteins. Many of the inherent features of cisplatin make it an
interesting cross-linking reagent, such as targeting new protein functional
groups (thioether and imidazole groups), its unique isotopic pattern, its
inherent positive charges, its potential of binding to different functional
groups, etc. However, it was found that the distance constraints obtained from NMR structures of CaM are inconsistent with the measured distance
constraints by crossâlinking. Therefore, a newly developed flexibility
simulation method was applied to explore whether the flexibility motions
of CaM might contribute to the observed Pt-crosslinking on CaM. The
flexibility analysis showed that the structural flexibility of CaM is key to
cisplatin crosslinking CaM. ECD mechanism of disulfide bonds is still
under debate. To further explore the ECD mechanism of sulfurâ
containing species, a series of disulfide (SâS), sulfurâselenium (SâSe),
and diselenide (SeâSe) bondâcontaining peptides was studied by ECD.
The results demonstrate that the radical has higher tendency to stay at
selenium rather than sulfur after cleavage of SeâS bonds by ECD and
suggest that direct electron capture at SeâSe and CâSe bonds is the
main process during ECD of interâchain diselenide peptides. Last but not
least, a new active ion ECD (AI-ECD) method, named Shots-ECD, was
developed and applied to improve Top-down ECD backbone
fragmentation efficiency of disulfide-rich proteins. The results show that
the ShotsâECD approach can not only cleave multiple disulfide bonds but
also significantly improve the backbone cleavage efficiency. This strategy
is fast, efficient, and with no need of chemical reduction of samples and
instrument modification, and therefore can be a powerful approach to
improve top-down ECD efficiency of not only disulfide bonded proteins
but all proteins by Fourier transform ion cyclotron mass spectrometry
(FTICR MS)
Probing Triple-W Production and Anomalous WWWW Coupling at the CERN LHC and future 100TeV proton-proton collider
Triple gauge boson production at the LHC can be used to test the robustness
of the Standard Model and provide useful information for VBF di-boson
scattering measurement. Especially, any derivations from SM prediction will
indicate possible new physics. In this paper we present a detailed Monte Carlo
study on measuring WWW production in pure leptonic and semileptonic decays, and
probing anomalous quartic gauge WWWW couplings at the CERN LHC and future
hadron collider, with parton shower and detector simulation effects taken into
account. Apart from cut-based method, multivariate boosted decision tree method
has been exploited for possible improvement. For the leptonic decay channel,
our results show that at the sqrt{s}=8(14)[100] TeV pp collider with integrated
luminosity of 20(100)[3000] fb-1, one can reach a significance of
0.4(1.2)[10]sigma to observe the SM WWW production. For the semileptonic decay
channel, one can have 0.5(2)[14]sigma to observe the SM WWW production. We also
give constraints on relevant Dim-8 anomalous WWWW coupling parameters.Comment: Accepted version by JHE
Challenges of scale down model for disposable bioreactors: Case studies on growth & product quality impacts
Despite wide-spread use of disposable bioreactors, there is a lack of well-established scale-down model for larger scale SUBs. Here we report a case of NS0 cell culture process transfer from 2000L stainless steel bioreactor (SST) to 2000L disposable bioreactor (SUB). Initial attempts in trying to grow the NS0 cells in the small scale 2D bags yielded non-satisfactory results, as growth was impacted by bag material type as well as by suppliers of the same bag material type. However, 3D bags of 50L and above proved to be supportive of the NS0 cell line growth.
Even for cell lines that do not have growth issues in SUBs, surprising product quality difference between SUBs and traditional bench top glass bioreactors are still being observed, thus making the bench top glass bioreactors non-ideal as scale down models. We report two cases where glycan profiles of the expressed antibody products show such dramatic differences. In one case, extensive testing of glass bioreactors from various suppliers led to a particular type being able to mimic the glycan profiles from the SUB, whereas in the other case, alternative scale down model had to be identified and the process had to be modified to maintain the glycan profiles when scaling up to the 200L SUB
Towards Top-Down Stereoscopic Image Quality Assessment via Stereo Attention
Stereoscopic image quality assessment (SIQA) plays a crucial role in
evaluating and improving the visual experience of 3D content. Existing
binocular properties and attention-based methods for SIQA have achieved
promising performance. However, these bottom-up approaches are inadequate in
exploiting the inherent characteristics of the human visual system (HVS). This
paper presents a novel network for SIQA via stereo attention, employing a
top-down perspective to guide the quality assessment process. Our proposed
method realizes the guidance from high-level binocular signals down to
low-level monocular signals, while the binocular and monocular information can
be calibrated progressively throughout the processing pipeline. We design a
generalized Stereo AttenTion (SAT) block to implement the top-down philosophy
in stereo perception. This block utilizes the fusion-generated attention map as
a high-level binocular modulator, influencing the representation of two
low-level monocular features. Additionally, we introduce an Energy Coefficient
(EC) to account for recent findings indicating that binocular responses in the
primate primary visual cortex are less than the sum of monocular responses. The
adaptive EC can tune the magnitude of binocular response flexibly, thus
enhancing the formation of robust binocular features within our framework. To
extract the most discriminative quality information from the summation and
subtraction of the two branches of monocular features, we utilize a
dual-pooling strategy that applies min-pooling and max-pooling operations to
the respective branches. Experimental results highlight the superiority of our
top-down method in simulating the property of visual perception and advancing
the state-of-the-art in the SIQA field. The code of this work is available at
https://github.com/Fanning-Zhang/SATNet.Comment: 13 pages, 4 figure
Recommended from our members
An integrated native mass spectrometry and top-down proteomics method that connects sequence to structure and function of macromolecular complexes.
Mass spectrometry (MS) has become a crucial technique for the analysis of protein complexes. Native MS has traditionally examined protein subunit arrangements, while proteomics MS has focused on sequence identification. These two techniques are usually performed separately without taking advantage of the synergies between them. Here we describe the development of an integrated native MS and top-down proteomics method using Fourier-transform ion cyclotron resonance (FTICR) to analyse macromolecular protein complexes in a single experiment. We address previous concerns of employing FTICR MS to measure large macromolecular complexes by demonstrating the detection of complexes up to 1.8â
MDa, and we demonstrate the efficacy of this technique for direct acquirement of sequence to higher-order structural information with several large complexes. We then summarize the unique functionalities of different activation/dissociation techniques. The platform expands the ability of MS to integrate proteomics and structural biology to provide insights into protein structure, function and regulation
Small area estimation: an empirical best linear unbiased prediction approach
In a large scale survey, we are usually concerned with estimation of
some characteristics of interest for a large area (e.g., a country).
But we are frequently interested in estimating similar
characteristics for a subpopulation using the same survey data. The
direct survey estimator which utilizes data only from the small area
of interest has been found to be highly unreliable due to small
sample size. Model-based methods have been used in small area
estimation in order to combine information available from the survey
data and various administrative and census data.
We study the empirical best linear unbiased prediction (EBLUP) and
its inferences under the general Fay-Herriot small area model.
Considering that the currently used variance estimation methods
could produce zero estimates, we propose the adjusted density
method (ADM) following Morris' comments. This new method always
produces positive estimates. Morris only suggested such adjustment
to the restricted maximum likelihood. Asymptotic theory of ADM is
unknown. We prove the consistency for the ADM estimator. We also
propose an alternate consistent ADM estimator by adjusting the
maximum likelihood. By comparing these two ADM estimators both in
theory and simulation, we find that the ADM estimator using maximum
likelihood is better than the one using the restricted likelihood in
terms of bias. We provide a concrete proof for the positiveness and
consistency of both ADM estimators.
We also propose EBLUP estimator of where we use two ADM
estimators of . The associated second-order unbiased Taylor
linearization MSE estimators are also proposed.
In addition, a new parametric bootstrap prediction interval method
using ADM estimator is proposed. The positiveness of ADM estimators
is emphasized in the construction of the prediction interval. We
also show that the coverage probability of this new method is
accurate up to .
Extensive Monte Carlo simulations are conducted. A data analysis for
the SAIPE data set is also presented. The positiveness of ADM
estimators plays a vital role here since for this data set the
method-of-moments, REML, ML and FH methods could be all zero. We
observe that ADM methods produce EBLUP's which generally put more
weights to the direct survey estimates than the corresponding
EBLUP's that use the other methods of variance component estimation
- âŠ