Compressible Distributions for High-dimensional Statistics

We develop a principled way of identifying probability distributions whose independent and identically distributed (iid) realizations are compressible, i.e., can be well-approximated as sparse. We focus on Gaussian random underdetermined linear regression (GULR) problems, where compressibility is known to ensure the success of estimators exploiting sparse regularization. We prove that many distributions revolving around maximum a posteriori (MAP) interpretation of sparse regularized estimators are in fact incompressible, in the limit of large problem sizes. A highlight is the Laplace distribution and $\ell^{1}$ regularized estimators such as the Lasso and Basis Pursuit denoising. To establish this result, we identify non-trivial undersampling regions in GULR where the simple least squares solution almost surely outperforms an oracle sparse solution, when the data is generated from the Laplace distribution. We provide simple rules of thumb to characterize classes of compressible (respectively incompressible) distributions based on their second and fourth moments. Generalized Gaussians and generalized Pareto distributions serve as running examples for concreteness.Comment: Was previously entitled "Compressible priors for high-dimensional statistics"; IEEE Transactions on Information Theory (2012

Structured risk assessment for reduction of multiple risk outcomes in a secure mental health setting:use of the START

Background: Structured risk assessment to aid prediction and prevention of risk behaviours in secure settings is common; the expected benefits have rarely been investigated.Aims: To determine whether adverse outcomes (physical and verbal aggression, self-harm, victimisation, self-neglect, unauthorised leave, substance abuse) reduced after patients were assessed with the Short-Term Assessment of Risk and Treatability (START).Methods: In a naturalistic study, anonymised demographic and clinical information were collected from 50 male patients. Data included START assessment and frequency of target behaviour data for three months before and after first assessment. Chi square and linear mixed models analyses were used to determine whether there was any change in the behaviours of interest.Results: There were no significant changes in physical or verbal aggression over time, although a tendency towards fewer incidents was apparent. Other adverse behaviours were very infrequent at baseline, precluding adequate analysis.Conclusions: In this small sample, START risk assessment did not achieve its primary purpose of significant reduction in adverse behaviours. Although we based our sample size on a power calculation, we may have over-estimated the size of anticipated change. Further, the three-month comparison periods before and after the assessment follow-up period, were rather short. Accordingly, we recommend more research on the value of this tool in practice rather than discontinuing its use

Compressive sensing meets game theory

We introduce the Multiplicative Update Selector and Estimator (MUSE) algorithm for sparse approximation in under-determined linear regression problems. Given ƒ = Φα* + μ, the MUSE provably and efficiently finds a k-sparse vector α̂ such that ∥Φα̂ − ƒ∥∞ ≤ ∥μ∥∞ + O ( 1 over √k), for any k-sparse vector α*, any measurement matrix Φ, and any noise vector μ. We cast the sparse approximation problem as a zero-sum game over a properly chosen new space; this reformulation provides salient computational advantages in recovery. When the measurement matrix Φ provides stable embedding to sparse vectors (the so-called restricted isometry property in compressive sensing), the MUSE also features guarantees on ∥α* − α̂∥2. Simulation results demonstrate the scalability and performance of the MUSE in solving sparse approximation problems based on the Dantzig Selector

Computational Methods For Structured Sparse Component Analysis of Convolutive Speech Mixtures

We cast the under-determined convolutive speech separation as sparse approximation of the spatial spectra of the mixing sources. In this framework we compare and contrast the major practical algorithms for structured sparse recovery of speech signal. Specific attention is paid to characterization of the measurement matrix. We first propose how it can be identified using the Image model of multi-path effect where the acoustic parameters are estimated by localizing a speaker and its images in a free space model. We further study the circumstances in which the coherence of the projections induced by microphone array design tend to affect the recovery performance

Human MLH1 deficiency predisposes to hematological malignancy and neurofibromatosis type 1

Heterozygous germ-line mutations in the DNA mismatch repair genes lead to hereditary nonpolyposis colorectal cancer. The disease susceptibility of individuals who constitutionally lack both wild-type alleles is unknown. We have identified three offspring in a hereditary nonpolyposis colorectal cancer family who developed hematological malignancy at a very early age, and at least two of them displayed signs of neurofibromatosis type 1 (NF1). DNA sequence analysis and allele-specific amplification in two siblings revealed a homozygous MLH1 mutation (C676T → Arg226Stop). Thus, a homozygous germ- line MLH1 mutation and consequent mismatch repair deficiency results in a mutator phenotype characterized by leukemia and/or lymphoma associated with neurofibromatosis type 1

The 3′ processing factor CstF functions in the DNA repair response

Following DNA damage, mRNA levels decrease, reflecting a coordinated interaction of the DNA repair, transcription and RNA processing machineries. In this study, we provide evidence that transcription and polyadenylation of mRNA precursors are both affected in vivo by UV treatment. We next show that the polyadenylation factor CstF, plays a direct role in the DNA damage response. Cells with reduced levels of CstF display decreased viability following UV treatment, reduced ability to ubiquitinate RNA polymerase II (RNAP II), and defects in repair of DNA damage. Furthermore, we show that CstF, RNAP II and BARD1 are all found at sites of repaired DNA. Our results indicate that CstF plays an active role in the response to DNA damage, providing a link between transcription-coupled RNA processing and DNA repair

Enhancement of immune response of HBsAg loaded poly(L-lactic acid) microspheres against Hepatitis B through incorporation of alum and chitosan

Purpose: Poly (L-lactic acid) (PLA) microparticles encapsulating Hepatitis B surface antigen (HBsAg) with alum and chitosan were investigated for their potential as a vaccine delivery system. Methods: The microparticles, prepared using a water-in-oil-in-water (w/o/w) double emulsion solvent evaporation method with polyvinyl alcohol (PVA) or chitosan as the external phase stabilising agent showed a significant increase in the encapsulation efficiency of the antigen. Results: PLA-Alum and PLA-chitosan microparticles induced HBsAg serum specific IgG antibody responses significantly higher than PLA only microparticles and free antigen following subcutaneous administration. Chitosan not only imparted a positive charge to the surface of the microparticles but was also able to increase the serum specific IgG antibody responses significantly. Conclusions: The cytokine assays showed that the serum IgG antibody response induced is different according to the formulation, indicated by the differential levels of interleukin 4 (IL-4), interleukin 6 (IL-6) and interferon gamma (IFN-γ). The microparticles eliciting the highest IgG antibody response did not necessarily elicit the highest levels of the cytokines IL-4, IL-6 and IFN-γ

Examining the Heterogeneous Genome Content of Multipartite Viruses BMV and CCMV by Native Mass Spectrometry

Since the concept was first introduced by Brian Chait and co-workers in 1991, mass spectrometry of proteins and protein complexes under non-denaturing conditions (native MS) has strongly developed, through parallel advances in instrumentation, sample preparation, and data analysis tools. However, the success rate of native MS analysis, particularly in heterogeneous mega-Dalton (MDa) protein complexes, still strongly depends on careful instrument modification. Here, we further explore these boundaries in native mass spectrometry, analyzing two related endogenous multipartite viruses: the Brome Mosaic Virus (BMV) and the Cowpea Chlorotic Mottle Virus (CCMV). Both CCMV and BMV are approximately 4.6 megadalton (MDa) in mass, of which approximately 1 MDA originates from the genomic content of the virion. Both viruses are produced as mixtures of three particles carrying different segments of the genome, varying by approximately 0.1 MDA in mass (~2%). This mixture of particles poses a challenging analytical problem for high-resolution native MS analysis, given the large mass scales involved. We attempt to unravel the particle heterogeneity using both Q-TOF and Orbitrap mass spectrometers extensively modified for analysis of very large assemblies. We show that manipulation of the charging behavior can provide assistance in assigning the correct charge states. Despite their challenging size and heterogeneity, we obtained native mass spectra with resolved series of charge states for both BMV and CCMV, demonstrating that native MS of endogenous multipartite virions is feasible. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13361-016-1348-6) contains supplementary material, which is available to authorized users