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 $O(d^3n^{-3/2})$, where $d$ is the number of parameters and $n$ 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 cross–linking of cisplatin to apo–CaM or Ca–CaM 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 CH3S• or CH3SH from Met, SH• from Cys, CO2 from Glu or Asp, and NH2• 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 cross–linking. 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 sulfur– containing species, a series of disulfide (S–S), sulfur–selenium (S–Se), and diselenide (Se–Se) bond–containing peptides was studied by ECD. The results demonstrate that the radical has higher tendency to stay at selenium rather than sulfur after cleavage of Se–S bonds by ECD and suggest that direct electron capture at Se–Se and C–Se bonds is the main process during ECD of inter–chain 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 Shots–ECD 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

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 1.8 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 $\theta_i$ where we use two ADM estimators of $A$. 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 $O(m^{-3/2})$. 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