The Effects of Auditory Perception and Musical Preference on Anxiety in Naive Human Subjects

Background: The use of music as a method of relieving anxiety has been studied extensively by researchers from varying disciplines. The abundance of these reports focused on which genre of music best aided in the relief of stress. Little work has been performed in the area of auditory preference in an attempt to ascertain whether an individual’s preferred music type aids in their anxiety reduction at levels greater than music that they have little or no propensity for. Material/Methods: In the present report we seek to determine whether naive human subjects exposed to music of their preference show a decrease in anxiety, as measured by systolic and diastolic blood pressure values. We furthermore contrast these values to those obtained during non-preferred music listening. Results: We found statistically significant reduction of anxiety levels only when subjects were exposed to their preferred musical selections. Conclusions: Students participating in the study already had knowledge of what genre of music would best relax them. It is our belief, that within the general population, many people do not have this self understanding. We conclude that music therapy may provide a mechanism for this self-understanding and subsequently help alleviate anxiety and stress

Standardized volumetric 3D-analysis of SPECT/CT imaging in orthopaedics: overcoming the limitations of qualitative 2D analysis

<p>Abstract</p> <p>Background</p> <p>SPECT/CT combines high resolution anatomical 3D computerized tomography (CT) and single photon emission computerized tomography (SPECT) as functional imaging, which provides 3D information about biological processes into a single imaging modality. The clinical utility of SPECT/CT imaging has been recognized in a variety of medical fields and most recently in orthopaedics; however, clinical adoption has been limited due to shortcomings of analytical tools available. Specifically, SPECT analyses are mainly qualitative due to variation in overall metabolic uptake among patients. Furthermore, most analyses are done in 2D, although rich 3D data are available. Consequently, it is difficult to quantitatively compare the position, size, and intensity of SPECT uptake regions among patients, and therefore difficult to draw meaningful clinical conclusions.</p> <p>Methods</p> <p>We propose a method for normalizing orthopaedic SPECT/CT data that enables standardised 3D volumetric quantitative measurements and comparison among patients. Our method is based on 3D localisation using clinically relevant anatomical landmarks and frames of reference, along with intensity value normalisation using clinically relevant reference regions. Using the normalised data, we describe a thresholding technique to distinguish clinically relevant hot spots from background activity.</p> <p>Results</p> <p>Using an exemplar comparison of two patients, we demonstrate how the normalised, 3D-rendered data can provide a richer source of clinical information and allow quantitative comparison of SPECT/CT measurements across patients. Specifically, we demonstrate how non-normalized SPECT/CT analysis can lead to different clinical conclusions than the normalized SPECT/CT analysis, and that normalized quantitative analysis can be a more accurate indicator of pathology.</p> <p>Conclusions</p> <p>Conventional orthopaedic frames of reference, 3D volumetric data analysis and thresholding are used to distinguish clinically relevant hot spots from background activity. Our goal is to facilitate a standardised approach to quantitative data collection and comparison of clinical studies using SPECT/CT, enabling more widespread clinical use of this powerful imaging tool.</p

Directed Evolution of Protein-Based Neurotransmitter Sensors for MRI

The production of contrast agents sensitive to neuronal signaling events is a rate-limiting step in the development of molecular-level functional magnetic resonance imaging (molecular fMRI) approaches for studying the brain. High-throughput generation and evaluation of potential probes are possible using techniques for macromolecular engineering of protein-based contrast agents. In an initial exploration of this strategy, we used the method of directed evolution to identify mutants of a bacterial heme protein that allowed detection of the neurotransmitter dopamine in vitro and in living animals. The directed evolution method involves successive cycles of mutagenesis and screening that could be generalized to produce contrast agents sensitive to a variety of molecular targets in the nervous system

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

The Effectiveness of Alcohol Screening and Brief Intervention in Emergency Departments: A Multicentre Pragmatic Cluster Randomized Controlled Trial

BACKGROUND: Alcohol misuse is common in people attending emergency departments (EDs) and there is some evidence of efficacy of alcohol screening and brief interventions (SBI). This study investigated the effectiveness of SBI approaches of different intensities delivered by ED staff in nine typical EDs in England: the SIPS ED trial. METHODS AND FINDINGS: Pragmatic multicentre cluster randomized controlled trial of SBI for hazardous and harmful drinkers presenting to ED. Nine EDs were randomized to three conditions: a patient information leaflet (PIL), 5 minutes of brief advice (BA), and referral to an alcohol health worker who provided 20 minutes of brief lifestyle counseling (BLC). The primary outcome measure was the Alcohol Use Disorders Identification Test (AUDIT) status at 6 months. Of 5899 patients aged 18 or more presenting to EDs, 3737 (63·3%) were eligible to participate and 1497 (40·1%) screened positive for hazardous or harmful drinking, of whom 1204 (80·4%) gave consent to participate in the trial. Follow up rates were 72% (n?=?863) at six, and 67% (n?=?810) at 12 months. There was no evidence of any differences between intervention conditions for AUDIT status or any other outcome measures at months 6 or 12 in an intention to treat analysis. At month 6, compared to the PIL group, the odds ratio of being AUDIT negative for brief advice was 1·103 (95% CI 0·328 to 3·715). The odds ratio comparing BLC to PIL was 1·247 (95% CI 0·315 to 4·939). A per protocol analysis confirmed these findings. CONCLUSIONS: SBI is difficult to implement in typical EDs. The results do not support widespread implementation of alcohol SBI in ED beyond screening followed by simple clinical feedback and alcohol information, which is likely to be easier and less expensive to implement than more complex interventions

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

Over and Under-utilization of Cyclooxygenase-2 Selective Inhibitors by Primary Care Physicians and Specialists: The Tortoise and the Hare Revisited

To compare prescribing trends and appropriateness of use of traditional and cyclooxygenase-2 selective (COX-2) nonsteroidal anti-inflammatory drugs (NSAIDs) by primary care physicians (PCPs) and specialists. DESIGN : Retrospective cohort study. PATIENTS : One thousand five hundred and seventy-six adult patients continuously enrolled for at least 1 year with an independent practice association of a University-associated managed care plan who were started on a traditional NSAID or a COX-2 inhibitor from 1999 to 2002 and received at least 3 separate medication fills. MEASUREMENTS : Physician specialty was identified from office visits. Appropriateness of utilization was based on gastrointestinal risk characteristics. RESULTS : Primary care patients were younger and less likely to have comorbid conditions. Despite similar GI risk, COX-2 use among patients seen by PCPs was half that of patients seen by specialists (21% vs 44%, P <.001). While PCPs overused cyclooxygenase-2-specific inhibitors (COX-2s) less often than specialists (19% vs 41%, P <.001), they also tended to underuse COX-2s in patients who were at increased GI risk (46% vs 32%, P =.063). This represents a 3-fold and 8-fold difference in overuse versus underuse for PCPs and specialists, respectively. CONCLUSIONS : Using COX-2s as a model for physician adoption of new therapeutic agents, specialists were more likely to use these new medications for patients likely to benefit but were also significantly more likely to use them for patients without a clear indication. This study demonstrates the tension between appropriate adoption of innovative therapies for those individuals who would benefit from their use and those individuals who would receive no added clinical benefit but would incur added cost and be placed at increased risk.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75173/1/j.1525-1497.2006.00463.x.pd

Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression

<p>Abstract</p> <p>Background</p> <p>In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a complex network that regulate the state of chromatin and processes that depend on it including transcription and DNA replication. Currently, a large number of these epigenetic modifications are being mapped in a variety of cell lines at different stages of development using high throughput sequencing by members of the ENCODE consortium, the NIH Roadmap Epigenomics Program and the Human Epigenome Project. An extremely promising and underexplored area of research is the application of machine learning methods, which are designed to construct predictive network models, to these large-scale epigenomic data sets.</p> <p>Results</p> <p>Using a ChIP-Seq data set of 20 histone lysine and arginine methylations and histone variant H2A.Z in human CD4⁺T-cells, we built predictive models of gene expression as a function of histone modification/variant levels using Multilinear (ML) Regression and Multivariate Adaptive Regression Splines (MARS). Along with extensive crosstalk among the 20 histone methylations, we found H4R3me2 was the most and second most globally repressive histone methylation among the 20 studied in the ML and MARS models, respectively. In support of our finding, a number of experimental studies show that PRMT5-catalyzed symmetric dimethylation of H4R3 is associated with repression of gene expression. This includes a recent study, which demonstrated that H4R3me2 is required for DNMT3A-mediated DNA methylation--a known global repressor of gene expression.</p> <p>Conclusion</p> <p>In stark contrast to univariate analysis of the relationship between H4R3me2 and gene expression levels, our study showed that the regulatory role of some modifications like H4R3me2 is masked by confounding variables, but can be elucidated by multivariate/systems-level approaches.</p

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data

Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease