Identification of a 4-microRNA Signature for Clear Cell Renal Cell Carcinoma Metastasis and Prognosis

Renal cell carcinoma (RCC) metastasis portends a poor prognosis and cannot be reliably predicted. Early determination of the metastatic potential of RCC may help guide proper treatment. We analyzed microRNA (miRNA) expression in clear cell RCC (ccRCC) for the purpose of developing a miRNA expression signature to determine the risk of metastasis and prognosis. We used the microarray technology to profile miRNA expression of 78 benign kidney and ccRCC samples. Using 28 localized and metastatic ccRCC specimens as the training cohort and the univariate logistic regression and risk score methods, we developed a miRNA signature model in which the expression levels of miR-10b, miR-139-5p, miR-130b and miR-199b-5p were used to determine the status of ccRCC metastasis. We validated the signature in an independent 40-sample testing cohort of different stages of primary ccRCCs using the microarray data. Within the testing cohort patients who had at least 5 years follow-up if no metastasis developed, the signature showed a high sensitivity and specificity. The risk status was proven to be associated with the cancer-specific survival. Using the most stably expressed miRNA among benign and tumorous kidney tissue as the internal reference for normalization, we successfully converted his signature to be a quantitative PCR (qPCR)-based assay, which showed the same high sensitivity and specificity. The 4-miRNA is associated with ccRCC metastasis and prognosis. The signature is ready for and will benefit from further large clinical cohort validation and has the potential for clinical application

Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine

An Empirical Study of Speech Processing in the Brain by Analyzing the Temporal Syllable Structure in Speech-input Induced EEG

© 2019 IEEE. Clinical applicability of electroencephalography (EEG) is well established, however the use of EEG as a choice for constructing brain computer interfaces to develop communication platforms is relatively recent. To provide more natural means of communication, there is an increasing focus on bringing together speech and EEG signal processing. Quantifying the way our brain processes speech is one way of approaching the problem of speech recognition using brain waves. This paper analyses the feasibility of recognizing syllable level units by studying the temporal structure of speech reflected in the EEG signals. The slowly varying component of the delta band EEG(0.3-3Hz) is present in all other EEG frequency bands. Analysis shows that removing the delta trend in EEG signals results in signals that reveals syllable like structure. Using a 25 syllable framework, classification of EEG data obtained from 13 subjects yields promising results, underscoring the potential of revealing speech related temporal structure in EEG

Neural Speech Decoding During Audition, Imagination and Production

© 2013 IEEE. Interpretation of neural signals to a form that is as intelligible as speech facilitates the development of communication mediums for the otherwise speech/motor-impaired individuals. Speech perception, production, and imagination often constitute phases of human communication. The primary goal of this article is to analyze the similarity between these three phases by studying electroencephalogram(EEG) patterns across these modalities, in order to establish their usefulness for brain computer interfaces. Neural decoding of speech using such non-invasive techniques necessitates the optimal choice of signal analysis and translation protocols. By employing selection-by-exclusion based temporal modeling algorithms, we discover fundamental syllable-like units that reveal similar set of signal signatures across all the three phases. Significantly higher than chance accuracies are recorded for single trial multi-unit EEG classification using machine learning approaches over three datasets across 30 subjects. Repeatability and subject independence tests performed at every step of the analysis further strengthens the findings and holds promise for translating brain signals to speech non-invasively

Valency conversion in the type 1 fimbrial adhesin of Escherichia coli

FimH protein is a lectin-like adhesive subunit of type 1, or mannose-sensitive, fimbriae that are found on the surface of most Escherichia coli strains. All naturally occurring FimH variants demonstrate a conserved mannotriose-specific (i.e. multivalent) binding. Here, we demonstrate that replacement of residues 185-279 within the FimH pilin domain with a corresponding segment of the type 1C fimbrial adhesin FocH leads to a loss of the multivalent mannotriose-specific binding property accompanied by the acquisition of a distinct monomannose-specific (i.e. monovalent) binding capability. Bacteria expressing the monovalent hybrid adhesins were capable of binding strongly to uroepithelial tissue culture cells and guinea pig erythrocytes. They could not, however, agglutinate yeast or bind human buccal cells functions readily accomplished by the E. coli-expressing mannotriose-specific FimH variants. Based on the relative potency of inhibiting compounds of different structures, the receptor binding site within monovalent FimH-FocH adhesin has an extended structure with an overall configuration similar to that within the multivalent FimH of natural origin. The monomannose-only specific phenotype could also be invoked by a single point mutation, E89K, located within the lectin domain of FimH, but distant from the receptor binding site. The structural alterations influence the receptor-binding valency of the FimH adhesin via distal effects on the combining pocket, obviously by affecting the FimH quaternary structure