Highlights d Searchable astroglial translatome database of male and female mice during development d Astroglia show early (P1-P7) and late (P14-adult) developmental phenotypes d Astroglia show sex differences in gene expression patterns during development
Highlights d MethylSight is used to identify candidate methylation sites in the human proteome d 45 histone methylation sites are uncovered by MethylSight and validated d The H2B-K43 methylation site is demethylated by KDM5B
Multiple private and public insurers compensate workers whose hearing loss can be directly attributed to excessive exposure to noise in the workplace. The claim assessment process is typically lengthy and requires significant effort from human adjudicators who must interpret hand-recorded audiograms, often sent via fax or equivalent. In this work, we present a solution developed in partnership with the Workplace Safety Insurance Board of Ontario to streamline the adjudication process. We present a flexible and opensource audiogram digitization algorithm capable of automatically extracting the hearing thresholds from a scanned or faxed audiology report as a proof-of-concept. The algorithm extracts most thresholds within 5 dB accuracy, allowing to substantially lessen the time required to convert an audiogram into digital format in a semi-supervised fashion, and is a first step towards the automation of the adjudication process. The source code for the digitization algorithm and a desktop-based implementation of our NIHL annotation portal is publicly available on GitHub https://github.com/GreenCUBIC/AudiogramDigitization.
Recent mobile and automated audiometry technologies have allowed for the democratization of hearing healthcare and enables non-experts to deliver hearing tests. The problem remains that a large number of such users are not trained to interpret audiograms. In this work, we outline the development of a data-driven audiogram classification system designed specifically for the purpose of concisely describing audiograms. More specifically, we present how a training dataset was assembled and the development of the classification system leveraging supervised learning techniques. We show that three practicing audiologists had high intra-and inter-rater agreement over audiogram classification tasks pertaining to audiogram configuration, symmetry and severity. The system proposed here achieves a performance comparable to the state of the art, but is significantly more flexible. Altogether, this work lays a solid foundation for future work aiming to apply machine learning techniques to audiology for audiogram interpretation.
Ferric uptake regulators (Fur) are a family of transcription factors coupling gene regulatory events to metal concentration. Recent evidence has expanded the mechanistic repertoires employed by Fur to activate or repress gene expression in the presence or absence of regulatory metals. However, the mechanistic basis underlying this extended repertoire has remained largely unexplored. In this study, we used an extensive set of mutations to demonstrate that Campylobacter jejuni Fur (CjFur) employs the same surface to positively and negatively control gene expression regardless of the presence or absence of metals. Moreover, the crystal structure determination of a CjFur devoid of any regulatory metals shows that subtle reorientation of the transcription factor DNA binding domain negatively impacts DNA binding, gene expression and gut colonization in chickens. Overall, these results highlight the versatility of the CjFur DNA binding domain in mediating all gene regulatory events controlled by the metalloregulator and that the full metalation of CjFur is critical to the Campylobacter jejuni life cycle in vivo.
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