Information theoretic evaluation of a noiseband-based cochlear implant simulator

Noise-band vocoders are often used to simulate the signal processing algorithms used in cochlear implants (CIs), producing acoustic stimuli that may be presented to normal hearing (NH) subjects. Such evaluations may obviate the heterogeneity of CI user populations, achieving greater experimental control than when testing on CI subjects. However, it remains an open question whether advancements in algorithms developed on NH subjects using a simulator will necessarily improve performance in CI users. This study assessed the similarity in vowel identification of CI subjects and NH subjects using an 8-channel noise-band vocoder simulator configured to match input and output frequencies or to mimic output after a basalward shift of input frequencies. Under each stimulus condition, NH subjects performed the task both with and without feedback/training. Similarity of NH subjects to CI users was evaluated using correct identification rates and information theoretic approaches. Feedback/training produced higher rates of correct identification, as expected, but also resulted in error patterns that were closer to those of the CI users. Further evaluation remains necessary to determine how patterns of confusion at the token level are affected by the various parameters in CI simulators, providing insight into how a true CI simulation may be developed to facilitate more rapid prototyping and testing of novel CI signal processing and electrical stimulation strategies

Evidence for the utility of cfDNA plasma concentrations to predict disease severity in COVID-19: a retrospective pilot study

Background COVID-19 is a worldwide pandemic caused by the highly infective SARS-CoV-2. There is a need for biomarkers not only for overall prognosis but also for predicting the response to treatments and thus for improvements in the clinical management of patients with COVID-19. Circulating cell-free DNA (cfDNA) has emerged as a promising biomarker in the assessment of various pathological conditions. The aim of this retrospective and observational pilot study was to investigate the range of cfDNA plasma concentrations in hospitalized COVID-19 patients during the first wave of SARS-CoV-2 infection, to relate them to established inflammatory parameters as a correlative biomarker for disease severity, and to compare them with plasma levels in a healthy control group. Methods Lithium-Heparin plasma samples were obtained from COVID-19 patients (n = 21) during hospitalization in the University Medical Centre of Mainz, Germany between March and June 2020, and the cfDNA concentrations were determined by quantitative PCR yielding amplicons of long interspersed nuclear elements (LINE-1). The cfDNA levels were compared with those of an uninfected control group (n = 19). Results Plasma cfDNA levels in COVID-19 patients ranged from 247.5 to 6,346.25 ng/ml and the mean concentration was 1,831 ± 1,388 ng/ml (± standard deviation), which was significantly different from the levels of the uninfected control group (p < 0.001). Regarding clinical complications, the highest correlation was found between cfDNA levels and the myositis (p = 0.049). In addition, cfDNA levels correlated with the “WHO clinical progression scale”. D-Dimer and C-reactive protein (CRP) were the clinical laboratory parameters with the highest correlations with cfDNA levels. Conclusion The results of this observational pilot study show a wide range in cfDNA plasma concentrations in patients with COVID-19 during the first wave of infection and confirm that cfDNA plasma concentrations serve as a predictive biomarker of disease severity in COVID-19