Bayesian inference and neural estimation of acoustic wave propagation

In this work, we introduce a novel framework which combines physics and machine learning methods to analyse acoustic signals. Three methods are developed for this task: a Bayesian inference approach for inferring the spectral acoustics characteristics, a neural-physical model which equips a neural network with forward and backward physical losses, and the non-linear least squares approach which serves as benchmark. The inferred propagation coefficient leads to the room impulse response (RIR) quantity which can be used for relocalisation with uncertainty. The simplicity and efficiency of this framework is empirically validated on simulated data

Evolutionary History of Mammalian Transposons Determined by Genome-Wide Defragmentation

The constant bombardment of mammalian genomes by transposable elements (TEs) has resulted in TEs comprising at least 45% of the human genome. Because of their great age and abundance, TEs are important in comparative phylogenomics. However, estimates of TE age were previously based on divergence from derived consensus sequences or phylogenetic analysis, which can be unreliable, especially for older more diverged elements. Therefore, a novel genome-wide analysis of TE organization and fragmentation was performed to estimate TE age independently of sequence composition and divergence or the assumption of a constant molecular clock. Analysis of TEs in the human genome revealed ∼600,000 examples where TEs have transposed into and fragmented other TEs, covering >40% of all TEs or ∼542 Mbp of genomic sequence. The relative age of these TEs over evolutionary time is implicit in their organization, because newer TEs have necessarily transposed into older TEs that were already present. A matrix of the number of times that each TE has transposed into every other TE was constructed, and a novel objective function was developed that derived the chronological order and relative ages of human TEs spanning >100 million years. This method has been used to infer the relative ages across all four major TE classes, including the oldest, most diverged elements. Analysis of DNA transposons over the history of the human genome has revealed the early activity of some MER2 transposons, and the relatively recent activity of MER1 transposons during primate lineages. The TEs from six additional mammalian genomes were defragmented and analyzed. Pairwise comparison of the independent chronological orders of TEs in these mammalian genomes revealed species phylogeny, the fact that transposons shared between genomes are older than species-specific transposons, and a subset of TEs that were potentially active during periods of speciation

Bioconductor: open software development for computational biology and bioinformatics.

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples

Localized Mucosal Response to Intranasal Live Attenuated Influenza Vaccine in Adults

Background. Influenza virus infection is a major public health burden worldwide. Available vaccines include the inactivated intramuscular trivalent vaccine and, more recently, an intranasal live attenuated influenza vaccine (LAIV). The measure of successful vaccination with the inactivated vaccine is a systemic rise in immunoglobulin G (IgG) level, but for the LAIV no such correlate has been established

MethylomeDB: a database of DNA methylation profiles of the brain

MethylomeDB (http://epigenomics.columbia.edu/methylomedb/index.html) is a new database containing genome-wide brain DNA methylation profiles. DNA methylation is an important epigenetic mark in the mammalian brain. In human studies, aberrant DNA methylation alterations have been associated with various neurodevelopmental and neuropsychiatric disorders such as schizophrenia, and depression. In this database, we present methylation profiles of carefully selected non-psychiatric control, schizophrenia, and depression samples. We also include data on one mouse forebrain sample specimen to allow for cross-species comparisons. In addition to our DNA methylation data generated in-house, we have and will continue to include published DNA methylation data from other research groups with the focus on brain development and function. Users can view the methylation data at single-CpG resolution with the option of wiggle and microarray formats. They can also download methylation data for individual samples. MethylomeDB offers an important resource for research into brain function and behavior. It provides the first source of comprehensive brain methylome data, encompassing whole-genome DNA methylation profiles of human and mouse brain specimens that facilitate cross-species comparative epigenomic investigations, as well as investigations of schizophrenia and depression methylomes

Association of interleukin-6 with suicidal ideation in veterans: a longitudinal perspective

IntroductionStudies showing associations between inflammation in suicide are typically cross-sectional. Present study investigated how cytokine levels track with suicidal ideation and severity longitudinally.MethodsVeterans with a diagnosis of major depressive disorder (MDD) with or without suicide attempt history (MDD/SA n = 38, MDD/NS n = 41) and non-psychiatric non-attempter controls (HC n = 33) were recruited, MDD/SA and HC groups were followed longitudinally at 3 months and 6 months. Blood plasma was collected and processed using Luminex Immunology Multiplex technology.ResultsSignificant differences in depression severity (BDI) and suicidal ideation severity (SSI) were observed across all groups at study entry, wherein MDD/SA group had the highest scores followed by MDD/NS and HC, respectively. Cytokines IL-1β, IL-4, TNF-α, IFN-γ, and IL-6 were examined at study entry and longitudinally, with IL6 levels differing significantly across the groups (p = 0.0123) at study entry. Significant differences in changes in cytokine levels between depressed attempters and the control group were detected for IL-6 (interaction F1,91.77 = 5.58, p = 0.0203) and TNF-α (F1,101.73 = 4.69, p = 0.0327). However, only depressed attempters showed a significant change, in IL-6 and TNF-α levels, decreasing over time [IL-6: b = −0.04, 95% CI = (−0.08, −0.01), p = 0.0245 and TNF-α: b = −0.02, 95% CI = (−0.04, −0.01), p = 0.0196]. Although IL-6 levels were not predictive of suicidal ideation presence [OR = 1.34, 95% CI = (0.77, 2.33), p = 0.3067], IL-6 levels were significantly associated with suicidal ideation severity (b = 0.19, p = 0.0422).DiscussionIL-6 was not associated with presence of suicidal ideation. IL-6 however, was associated with severity of ideation, suggesting that IL-6 may be useful in clinical practice, as an objective marker of heightened suicide risk

One-Pot Green Synthesis and Bioapplication ofl-Arginine-Capped Superparamagnetic Fe3O4 Nanoparticles

Water-solublel-arginine-capped Fe3O4 nanoparticles were synthesized using a one-pot and green method. Nontoxic, renewable and inexpensive reagents including FeCl3,l-arginine, glycerol and water were chosen as raw materials. Fe3O4 nanoparticles show different dispersive states in acidic and alkaline solutions for the two distinct forms of surface bindingl-arginine. Powder X-ray diffraction and X-ray photoelectron spectroscopy were used to identify the structure of Fe3O4 nanocrystals. The products behave like superparamagnetism at room temperature with saturation magnetization of 49.9 emu g−1 and negligible remanence or coercivity. In the presence of 1-ethyl-3-(dimethylaminopropyl) carbodiimide hydrochloride, the anti-chloramphenicol monoclonal antibodies were connected to thel-arginine-capped magnetite nanoparticles. The as-prepared conjugates could be used in immunomagnetic assay

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Control of the False Discovery Proportion for Independently Tested Null Hypotheses

Consider the multiple testing problem of testing m null hypotheses H1,…,Hm, among which m0 hypotheses are truly null. Given the P-values for each hypothesis, the question of interest is how to combine the P-values to find out which hypotheses are false nulls and possibly to make a statistical inference on m0. Benjamini and Hochberg proposed a classical procedure that can control the false discovery rate (FDR). The FDR control is a little bit unsatisfactory in that it only concerns the expectation of the false discovery proportion (FDP). The control of the actual random variable FDP has recently drawn much attention. For any level 1−α, this paper proposes a procedure to construct an upper prediction bound (UPB) for the FDP for a fixed rejection region. When 1−α=50%, our procedure is very close to the classical Benjamini and Hochberg procedure. Simultaneous UPBs for all rejection regions' FDPs and the upper confidence bound for the unknown m0 are presented consequently. This new proposed procedure works for finite samples and hence avoids the slow convergence problem of the asymptotic theory