Nonnative implicit phonetic training in multiple reverberant environments.

Speech intelligibility is adversely affected by reverberation, particularly when listening to a foreign language. However, little is known about how phonetic learning is affected by room acoustics. This study investigated how room reverberation impacts the acquisition of novel phonetic categories during implicit training in virtual environments. Listeners were trained to distinguish a difficult nonnative dental-retroflex contrast in phonemes presented either in a fixed room (anechoic or reverberant) or in multiple anechoic and reverberant spaces typical of everyday listening. Training employed a videogame in which phonetic stimuli were paired with rewards delivered upon successful task performance, in accordance with the task-irrelevant perceptual learning paradigm. Before and after training, participants were tested using familiar and unfamiliar speech tokens, speakers, and rooms. Implicit training performed in multiple rooms induced learning, while training in a single environment did not. The multiple-room training improvement generalized to untrained rooms and tokens, but not to untrained voices. These results show that, following implicit training, nonnative listeners can overcome the detrimental effects of reverberation and that exposure to sounds in multiple reverberant environments during training enhances implicit phonetic learning rather than disrupting it

Proteomics in cardiovascular disease: recent progress and clinical implication and implementation

Introduction: Although multiple efforts have been initiated to shed light into the molecular mechanisms underlying cardiovascular disease, it still remains one of the major causes of death worldwide. Proteomic approaches are unequivocally powerful tools that may provide deeper understanding into the molecular mechanisms associated with cardiovascular disease and improve its management. Areas covered: Cardiovascular proteomics is an emerging field and significant progress has been made during the past few years with the aim of defining novel candidate biomarkers and obtaining insight into molecular pathophysiology. To summarize the recent progress in the field, a literature search was conducted in PubMed and Web of Science. As a result, 704 studies from PubMed and 320 studies from Web of Science were retrieved. Findings from original research articles using proteomics technologies for the discovery of biomarkers for cardiovascular disease in human are summarized in this review. Expert commentary: Proteins associated with cardiovascular disease represent pathways in inflammation, wound healing and coagulation, proteolysis and extracellular matrix organization, handling of cholesterol and LDL. Future research in the field should target to increase proteome coverage as well as integrate proteomics with other omics data to facilitate both drug development as well as clinical implementation of findings

Predictors of Treatment Adherence in Adolescents with Inflammatory Bowel Disease: The Role of Age, Body Satisfaction and Prospective Memory in Medication and Diet Behavior.

Inflammatory bowel disease (IBD; Crohn’s disease & ulcerative colitis) is a chronic illness in which medication and dietary adherence may determine disease natural history and severity of symptoms. We hypothesized that age, prospective memory (PM) and body satisfaction would predict medication and dietary adherence in adolescents with IBD and that gender and age would modify the relation between body satisfaction and adherence, with older girls being less adherent than younger children. Fifty-seven participants aged 10-21 (M = 16.5, SD = 2.3) with IBD and their caregivers were recruited. Informed consent, demographics and body satisfaction questionnaires were completed. PM was assessed using a naturalistic task. Adherence was measured by the 1-week completion of a medication and dietary log. A questionnaire was administered to evaluate coping strategies used for overcoming obstacles to dietary adherence. Two hierarchical regressions were conducted for medication and diet adherence respectively. As hypothesized, age had a significant effect (â = -.42, p \u3c .01) on dietary adherence, accounting for approximately 17% of the variance (R2change = .17; Fchange (1,41) = 8.57, p = .006), with younger children being more adherent. Body satisfaction had a greater and more significant effect on dietary adherence than age (â = -.33, p \u3c .01); i.e. participants more satisfied with their body reported better dietary adherence (R2change = .28; Fchange (2,35) = 6.97, p \u3c .05). Findings remained consistent across multiple measures of body satisfaction and dietary adherence. None of the predictors had a significant effect on medication adherence. Health care providers who treat adolescents with IBD and parents should be made aware of factors affecting adherence in order to improve disease outcomes and patients’ quality of life

Clinical proteomics for precision medicine: the bladder cancer case

Precision medicine can improve patient management by guiding therapeutic decision based on molecular characteristics. The concept has been extensively addressed through the application of –omics based approaches. Proteomics attract high interest, as proteins reflect a “real-time” dynamic molecular phenotype. Focusing on proteomics applications for personalized medicine, a literature search was conducted to cover: a) disease prevention, b) monitoring/ prediction of treatment response, c) stratification to guide intervention and d) identification of drug targets. The review indicates the potential of proteomics for personalized medicine by also highlighting multiple challenges to be addressed prior to actual implementation. In oncology, particularly bladder cancer, application of precision medicine appears especially promising. The high heterogeneity and recurrence rates together with the limited treatment options, suggests that earlier and more efficient intervention, continuous monitoring and the development of alternative therapies could be accomplished by applying proteomics-guided personalized approaches. This notion is backed by studies presenting biomarkers that are of value in patient stratification and prognosis, and by recent studies demonstrating the identification of promising therapeutic targets. Herein, we aim to present an approach whereby combining the knowledge on biomarkers and therapeutic targets in bladder cancer could serve as basis towards proteomics- guided personalized patient management

BcCluster: a bladder cancer database at the molecular level

Background: Bladder Cancer (BC) has two clearly distinct phenotypes. Non-muscle invasive BC has good prognosis and is treated with tumor resection and intravesical therapy whereas muscle invasive BC has poor prognosis and requires usually systemic cisplatin based chemotherapy either prior to or after radical cystectomy. Neoadjuvant chemotherapy is not often used for patients undergoing cystectomy. High-throughput analytical omics techniques are now available that allow the identification of individual molecular signatures to characterize the invasive phenotype. However, a large amount of data produced by omics experiments is not easily accessible since it is often scattered over many publications or stored in supplementary files. Objective: To develop a novel open-source database, BcCluster (http://www.bccluster.org/), dedicated to the comprehensive molecular characterization of muscle invasive bladder carcinoma. Materials: A database was created containing all reported molecular features significant in invasive BC. The query interface was developed in Ruby programming language (version 1.9.3) using the web-framework Rails (version 4.1.5) (http://rubyonrails.org/). Results: BcCluster contains the data from 112 published references, providing 1,559 statistically significant features relative to BC invasion. The database also holds 435 protein-protein interaction data and 92 molecular pathways significant in BC invasion. The database can be used to retrieve binding partners and pathways for any protein of interest. We illustrate this possibility using survivin, a known BC biomarker. Conclusions: BcCluster is an online database for retrieving molecular signatures relative to BC invasion. This application offers a comprehensive view of BC invasiveness at the molecular level and allows formulation of research hypotheses relevant to this phenotype

Freeze fracturing of elastic porous media: a mathematical model.

We present a mathematical model of the fracturing of water-saturated rocks and other porous materials in cold climates. Ice growing inside porous rocks causes large pressures to develop that can significantly damage the rock. We study the growth of ice inside a penny-shaped cavity in a water-saturated porous rock and the consequent fracturing of the medium. Premelting of the ice against the rock, which results in thin films of unfrozen water forming between the ice and the rock, is one of the dominant processes of rock fracturing. We find that the fracture toughness of the rock, the size of pre-existing faults and the undercooling of the environment are the main parameters determining the susceptibility of a medium to fracturing. We also explore the dependence of the growth rates on the permeability and elasticity of the medium. Thin and fast-fracturing cracks are found for many types of rocks. We consider how the growth rate can be limited by the existence of pore ice, which decreases the permeability of a medium, and propose an expression for the effective 'frozen' permeability.This research was supported by a PhD studentship from the EPSRC.This is the final version. It first appeared at http://dx.doi.org/10.1098/rspa.2014.074

A combinatorial approach of Proteomics and Systems Biology in unravelling the mechanisms of acute kidney injury (AKI): involvement of NMDA receptor GRIN1 in murine AKI

BACKGROUND: Acute kidney injury (AKI) is a frequent condition in hospitalised patients undergoing major surgery or the critically ill and is associated with increased mortality. Based on the volume of the published literature addressing this condition, reporting both supporting as well as conflicting molecular evidence, it is apparent that a comprehensive analysis strategy is required to understand and fully delineate molecular events and pathways which can be used to describe disease induction and progression as well as lead to a more targeted approach in intervention therapies.<p></p> RESULTS: We used a Systems Biology approach coupled with a de-novo high-resolution proteomic analysis of kidney cortex samples from a mouse model of folic acid-induced AKI (12 animals in total) and show comprehensive mapping of signalling cascades, gene activation events and metabolite interference by mapping high-resolution proteomic datasets onto a de-novo hypothesis-free dataspace. The findings support the involvement of the glutamatergic signalling system in AKI, induced by over-activation of the N-methyl-D-aspartate (NMDA)-receptor leading to apoptosis and necrosis by Ca2+-influx, calpain and caspase activation, and co-occurring reactive oxygen species (ROS) production to DNA fragmentation and NAD-rundown. The specific over-activation of the NMDA receptor may be triggered by the p53-induced protein kinase Dapk1, which is a known non-reversible cell death inducer in a neurological context. The pathway mapping is consistent with the involvement of the Renin-Angiotensin Aldosterone System (RAAS), corticoid and TNFalpha signalling, leading to ROS production and gene activation through NFkappaB, PPARgamma, SMAD and HIF1alpha trans-activation, as well as p53 signalling cascade activation. Key elements of the RAAS-glutamatergic axis were assembled as a novel hypothetical pathway and validated by immunohistochemistry.<p></p> CONCLUSIONS: This study shows to our knowledge for the first time in a molecular signal transduction pathway map how AKI is induced, progresses through specific signalling cascades that may lead to end-effects such as apoptosis and necrosis by uncoupling of the NMDA receptor. Our results can potentially pave the way for a targeted pharmacological intervention in disease progression or induction.<p></p&gt

PeptiCKDdb-peptide- and protein-centric database for the investigation of genesis and progression of chronic kidney disease

The peptiCKDdb is a publicly available database platform dedicated to support research in the field of chronic kidney disease (CKD) through identification of novel biomarkers and molecular features of this complex pathology. PeptiCKDdb collects peptidomics and proteomics datasets manually extracted from published studies related to CKD. Datasets from peptidomics or proteomics, human case/control studies on CKD and kidney or urine profiling were included. Data from 114 publications (studies of body fluids and kidney tissue: 26 peptidomics and 76 proteomics manuscripts on human CKD, and 12 focusing on healthy proteome profiling) are currently deposited and the content is quarterly updated. Extracted datasets include information about the experimental setup, clinical study design, discovery-validation sample sizes and list of differentially expressed proteins (P-value < 0.05). A dedicated interactive web interface, equipped with multiparametric search engine, data export and visualization tools, enables easy browsing of the data and comprehensive analysis. In conclusion, this repository might serve as a source of data for integrative analysis or a knowledgebase for scientists seeking confirmation of their findings and as such, is expected to facilitate the modeling of molecular mechanisms underlying CKD and identification of biologically relevant biomarkers.Database URL: www.peptickddb.com