Does training with amplitude modulated tones affect tone-vocoded speech perception?

Temporal-envelope cues are essential for successful speech perception. We asked here whether training on stimuli containing temporal-envelope cues without speech content can improve the perception of spectrally-degraded (vocoded) speech in which the temporal-envelope (but not the temporal fine structure) is mainly preserved. Two groups of listeners were trained on different amplitude-modulation (AM) based tasks, either AM detection or AM-rate discrimination (21 blocks of 60 trials during two days, 1260 trials; frequency range: 4Hz, 8Hz, and 16Hz), while an additional control group did not undertake any training. Consonant identification in vocoded vowel-consonant-vowel stimuli was tested before and after training on the AM tasks (or at an equivalent time interval for the control group). Following training, only the trained groups showed a significant improvement in the perception of vocoded speech, but the improvement did not significantly differ from that observed for controls. Thus, we do not find convincing evidence that this amount of training with temporal-envelope cues without speech content provide significant benefit for vocoded speech intelligibility. Alternative training regimens using vocoded speech along the linguistic hierarchy should be explored

A new mathematical model for environmental monitoring and assessment

Versão dos Autores para este artigo.In this paper we are concerned with a quantitative method of Landscape Ecology. More in details we consider an environmental system distributed in landscape units (ecological sectors) and we propose a new mathematical model in order to implement a method for the evaluation of the ecological state of the system under investigation. After having performed a stability analysis of the model, we apply the proposed procedure first by considering separately each landscape unit and then extending our investigation to the system as a whole, by taking into account the connections between all the landscape units themselves. Our investigation includes some numerical computations that were performed for a Northern district of the Turin Province, using an approximation procedure that should avoid stiffness problems.National Group GNFM of INdAM, Italyinfo:eu-repo/semantics/publishedVersio

Insight into glucocorticoid receptor signalling through interactome model analysis

Glucocorticoid hormones (GCs) are used to treat a variety of diseases because of their potent anti-inflammatory effect and their ability to induce apoptosis in lymphoid malignancies through the glucocorticoid receptor (GR). Despite ongoing research, high glucocorticoid efficacy and widespread usage in medicine, resistance, disease relapse and toxicity remain factors that need addressing. Understanding the mechanisms of glucocorticoid signalling and how resistance may arise is highly important towards improving therapy. To gain insight into this we undertook a systems biology approach, aiming to generate a Boolean model of the glucocorticoid receptor protein interaction network that encapsulates functional relationships between the GR, its target genes or genes that target GR, and the interactions between the genes that interact with the GR. This model named GEB052 consists of 52 nodes representing genes or proteins, the model input (GC) and model outputs (cell death and inflammation), connected by 241 logical interactions of activation or inhibition. 323 changes in the relationships between model constituents following in silico knockouts were uncovered, and steady-state analysis followed by cell-based microarray genome-wide model validation led to an average of 57% correct predictions, which was taken further by assessment of model predictions against patient microarray data. Lastly, semi-quantitative model analysis via microarray data superimposed onto the model with a score flow algorithm has also been performed, which demonstrated significantly higher correct prediction ratios (average of 80%), and the model has been assessed as a predictive clinical tool using published patient microarray data. In summary we present an in silico simulation of the glucocorticoid receptor interaction network, linked to downstream biological processes that can be analysed to uncover relationships between GR and its interactants. Ultimately the model provides a platform for future development both by directing laboratory research and allowing for incorporation of further components, encapsulating more interactions/genes involved in glucocorticoid receptor signalling

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON

Generalized DNA Barcode Design Based on Hamming Codes

The diversity and scope of multiplex parallel sequencing applications is steadily increasing. Critically, multiplex parallel sequencing applications methods rely on the use of barcoded primers for sample identification, and the quality of the barcodes directly impacts the quality of the resulting sequence data. Inspection of the recent publications reveals a surprisingly variable quality of the barcodes employed. Some barcodes are made in a semi empirical fashion, without quantitative consideration of error correction or minimal distance properties. After systematic comparison of published barcode sets, including commercially distributed barcoded primers from Illumina and Epicentre, methods for improved, Hamming code-based sequences are suggested and illustrated. Hamming barcodes can be employed for DNA tag designs in many different ways while preserving minimal distance and error-correcting properties. In addition, Hamming barcodes remain flexible with regard to essential biological parameters such as sequence redundancy and GC content. Wider adoption of improved Hamming barcodes is encouraged in multiplex parallel sequencing applications

Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment

Adverse Events in a Cohort of HIV Infected Pregnant and Non-Pregnant Women Treated with Nevirapine versus Non-Nevirapine Antiretroviral Medication

BACKGROUND: Predictors of adverse events (AE) associated with nevirapine use are needed to better understand reports of severe rash or liver enzyme elevation (LEE) in HIV+ women. METHODOLOGY: AE rates following ART initiation were retrospectively assessed in a multi-site cohort of 612 women. Predictors of onset of rash or LEE were determined using univariate and multivariate analyses. PRINCIPAL FINDINGS: Of 612 subjects, 152 (24.8%) initiated NVP-based regimens with 86 (56.6%) pregnant; 460 (75.2%) initiated non-NVP regimens with 67 (14.6%) pregnant. LEE: No significant difference was found between regimens in the development of new grade ≥2 LEE (p  =  0.885). Multivariate logistic regression demonstrated an increased likelihood of LEE with HCV co-infection (OR 2.502, 95% CI: 1.04 to 6, p =  0.040); pregnancy, NVP-based regimen, and baseline CD4 >250 cells/mm(3) were not associated with this toxicity. RASH: NVP initiation was associated with rash after controlling for CD4 and pregnancy (OR 2.78; 95%CI: 1.14-6.76), as was baseline CD4 >250 cells/mm(3) when controlling for pregnancy and type of regimen (OR 2.68; 95% CI: 1.19-6.02 p  =  0.017). CONCLUSIONS: CD4 at initiation of therapy was a predictor of rash but not LEE with NVP use in HIV+ women. Pregnancy was not an independent risk factor for the development of AEs assessed. The findings from this study have significant implications for women of child-bearing age initiating NVP-based ART particularly in resource limited settings. This study sheds more confidence on the lack of LEE risk and the need to monitor rash with the use of this medication