Litvak, L. | Search bioRxiv

bioRxiv2023

CompHEAR: A Customizable and Scalable Web-Enabled Auditory Performance Evaluation Platform for Cochlear Implant Sound Processing Research

ObjectiveCochlear implants (CIs) are auditory prostheses for individuals with severe to profound hearing loss, offering substantial but incomplete restoration of hearing function by stimulating the auditory nerve using electrodes. However, progress in CI performance and innovation has been constrained by the inability to rapidly test multiple sound processing strategies. Current research interfaces provided by major CI manufacturers have limitations in supporting a wide range of auditory experiments due to portability, programming difficulties, and the lack of direct comparison between sound processing algorithms. To address these limitations, we present the CompHEAR research platform, designed specifically for the Cochlear Implant Hackathon, enabling researchers to conduct diverse auditory experiments on a large scale. Study DesignQuasi-experimental SettingVirtual MethodsCompHEAR is an open-source, user-friendly platform which offers flexibility and ease of customization, allowing researchers to set up a broad set of auditory experiments. CompHEAR employs a vocoder to simulate novel sound coding strategies for CIs. It facilitates even distribution of listening tasks among participants and delivers real-time metrics for evaluation. The software architecture underlies the platforms flexibility in experimental design and its wide range of applications in sound processing research. ResultsPerformance testing of the CompHEAR platform ensured that it could support at least 10,000 concurrent users. The CompHEAR platform was successfully implemented during the COVID-19 pandemic and enabled global collaboration for the CI Hackathon (www.cihackathon.com). ConclusionThe CompHEAR platform is a useful research tool that permits comparing diverse signal processing strategies across a variety of auditory tasks with crowdsourced judging. Its versatility, scalability, and ease of use can enable further research with the goal of promoting advancements in cochlear implant performance and improved patient outcomes.

neuroscience↗

bioRxiv2023

Editing cis-regulatory elements towards generating rice stomatal morphological variation for adaptation to broad and dynamic environments

Cis-regulatory element editing can generate quantitative trait variation while mitigating against extreme phenotypes and harmful pleiotropy associated with coding sequence mutations. Here, we applied a multiplexed guide RNA design approach, informed by bioinformatic datasets, to generate genotypic variation in the promoter of OsSTOMAGEN, a positive regulator of stomatal density in rice. Engineered genotypic variation corresponded to broad and continuous variation in stomatal density, ranging from 70% to 120% of wild-type stomatal density. This near-isogenic panel of stomatal variants was leveraged in physiological assays to establish discrete relationships between stomatal morphological variation and stomatal conductance, carbon assimilation, and intrinsic water use efficiency in steady-state and fluctuating light conditions. Additionally, promoter alleles were subjected to vegetative drought regimes to assay the effects of the edited alleles on developmental response to drought. Notably, the capacity for drought-responsive stomatal density reprogramming in stomagen and two cis-regulatory edited alleles was reduced. Collectively our data demonstrate that cis-regulatory element editing can generate near-isogenic trait variation that can be leveraged for establishing relationships between anatomy, physiology, and crop improvement along diverse environmental clines.

plant biology↗