An mHealth App (Speech Banana) for Auditory Training: App Design and Development Study.

BACKGROUND: With the growing adult population using electronic hearing devices such as cochlear implants or hearing aids, there is an increasing worldwide need for auditory training (AT) to promote optimal device use. However, financial resources and scheduling conflicts make clinical AT infeasible. OBJECTIVE: To address this gap between need and accessibility, we primarily aimed to develop a mobile health (mHealth) app called Speech Banana for AT. The app would be substantially more affordable and portable than clinical AT; would deliver a validated training model that is reflective of modern techniques; and would track users' progress in speech comprehension, providing greater continuity between periodic in-person visits. To improve international availability, our secondary aim was to implement the English language training model into Korean as a proof of concept for worldwide usability. METHODS: A problem- and objective-centered Design Science Research Methodology approach was adopted to develop the Speech Banana app. A review of previous literature and computer-based learning programs outlined current AT gaps, whereas interviews with speech pathologists and users clarified the features that were addressed in the app. Past and present users were invited to evaluate the app via community forums and the System Usability Scale. RESULTS: Speech Banana has been implemented in English and Korean languages for iPad and web use. The app comprises 38 lessons, which include analytic exercises pairing visual and auditory stimuli, and synthetic quizzes presenting auditory stimuli only. During quizzes, users type the sentence heard, and the app provides visual feedback on performance. Users may select a male or female speaker and the volume of background noise, allowing for training with a range of frequencies and signal-to-noise ratios. There were more than 3200 downloads of the English iPad app and almost 100 downloads of the Korean app; more than 100 users registered for the web apps. The English app received a System Usability Scale rating of "good" from 6 users, and the Korean app received a rating of "OK" from 16 users. CONCLUSIONS: Speech Banana offers AT accessibility with a validated curriculum, allowing users to develop speech comprehension skills with the aid of a mobile device. This mHealth app holds potential as a supplement to clinical AT, particularly in this era of global telemedicine.

3DeFDR: statistical methods for identifying cell type-specific looping interactions in 5C and Hi-C data.

An important unanswered question in chromatin biology is the extent to which long-range looping interactions change across developmental models, genetic perturbations, drug treatments, and disease states. Computational tools for rigorous assessment of cell type-specific loops across multiple biological conditions are needed. We present 3DeFDR, a simple and effective statistical tool for classifying dynamic loops across biological conditions from Chromosome-Conformation-Capture-Carbon-Copy (5C) and Hi-C data. Our work provides a statistical framework and open-source coding libraries for sensitive detection of cell type-specific loops in high-resolution 5C and Hi-C data from multiple cellular conditions.

Publisher Correction: Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression.

Neuronal activation induces rapid transcription of immediate early genes (IEGs) and longer-term chromatin remodeling around secondary response genes (SRGs). Here, we use high-resolution chromosome-conformation-capture carbon-copy sequencing (5C-seq) to elucidate the extent to which long-range chromatin loops are altered during short- and long-term changes in neural activity. We find that more than 10% of loops surrounding select IEGs, SRGs, and synaptic genes are induced de novo during cortical neuron activation. IEGs Fos and Arc connect to activity-dependent enhancers via singular short-range loops that form within 20 min after stimulation, prior to peak messenger RNA levels. By contrast, the SRG Bdnf engages in both pre-existing and activity-inducible loops that form within 1-6 h. We also show that common single-nucleotide variants that are associated with autism and schizophrenia are colocalized with distinct classes of activity-dependent, looped enhancers. Our data link architectural complexity to transcriptional kinetics and reveal the rapid timescale by which higher-order chromatin architecture reconfigures during neuronal stimulation.