Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients

Although significant progress has been made in understanding outcomes following cochlear implantation, predicting performance remains a challenge. Duration of hearing loss, age at implantation, and electrode positioning within the cochlea together explain ~ 25% of the variability in speech-perception scores in quiet using the cochlear implant (CI). Electrocochleography (ECochG) responses, prior to implantation, account for 47% of the variance in the same speech-perception measures. No study to date has explored CI performance in noise, a more realistic measure of natural listening. This study aimed to (1) validate ECochG total response (ECochG-TR) as a predictor of performance in quiet and (2) evaluate whether ECochG-TR explained variability in noise performance. Thirty-five adult CI recipients were enrolled with outcomes assessed at 3-months post-implantation. The results confirm previous studies showing a strong correlation of ECochG-TR with speech-perception in quiet (r = 0.77). ECochG-TR independently explained 34% of the variability in noise performance. Multivariate modeling using ECochG-TR and Montreal Cognitive Assessment (MoCA) scores explained 60% of the variability in speech-perception in noise. Thus, ECochG-TR, a measure of the cochlear substrate prior to implantation, is necessary but not sufficient for explaining performance in noise. Rather, a cognitive measure is also needed to improve prediction of noise performance

Is characteristic frequency limiting real-time electrocochleography during cochlear implantation?

Objectives: Electrocochleography (ECochG) recordings during cochlear implantation have shown promise in estimating the impact on residual hearing. The purpose of the study was (1) to determine whether a 250-Hz stimulus is superior to 500-Hz in detecting residual hearing decrement and if so; (2) to evaluate whether crossing the 500-Hz tonotopic, characteristic frequency (CF) place partly explains the problems experienced using 500-Hz. Design: Multifrequency ECochG comprising an alternating, interleaved acoustic complex of 250- and 500-Hz stimuli was used to elicit cochlear microphonics (CMs) during insertion. The largest ECochG drops (≥30% reduction in CM) were identified. After insertion, ECochG responses were measured using the individual electrodes along the array for both 250- and 500-Hz stimuli. Univariate regression was used to predict whether 250- or 500-Hz CM drops explained low-frequency pure tone average (LFPTA; 125-, 250-, and 500-Hz) shift at 1-month post-activation. Postoperative CT scans were performed to evaluate cochlear size and angular insertion depth. Results: For perimodiolar insertions ( Conclusion: Using 250-Hz stimulus for ECochG feedback during implantation is more predictive of hearing preservation than 500-Hz. This is due to the electrode passing the 500-Hz CF during insertion which may be misidentified as intracochlear trauma; this is particularly important in subjects with smaller cochlear diameters and deeper insertions. Multifrequency ECochG can be used to differentiate between trauma and advancement of the apical electrode beyond the CF

Design, assessment, and in vivo evaluation of a computational model illustrating the role of CAV1 in CD4+ T-lymphocytes

Caveolin-1 (CAV1) is a vital scaffold protein heterogeneously expressed in both healthy and malignant tissue. We focus on the role of CAV1 when overexpressed in T-cell leukemia. Previously, we have shown that CAV1 is involved in cell-to-cell communication, cellular proliferation, and immune synapse formation; however, the molecular mechanisms have not been elucidated. We hypothesize that the role of CAV1 in immune synapse formation contributes to immune regulation during leukemic progression, thereby warranting studies of the role of CAV1 in CD4+ T-cells in relation to antigen-presenting cells. To address this need, we developed a computational model of a CD4+ immune effector T-cell to mimic cellular dynamics and molecular signaling under healthy and immunocompromised conditions (i.e., leukemic conditions). Using the Cell Collective computational modeling software, the CD4+ T-cell model was constructed and simulated under CAV1+/+, CAV1+/−, and CAV1−/− conditions to produce a hypothetical immune response. This model allowed us to predict and examine the heterogeneous effects and mechanisms of CAV1 in silico. Experimental results indicate a signature of molecules involved in cellular proliferation, cell survival, and cytoskeletal rearrangement that were highly affected by CAV1 knock out. With this comprehensive model of a CD4+ T-cell, we then validated in vivo protein expression levels. Based on this study, we modeled a CD4+ T-cell, manipulated gene expression in immunocompromised versus competent settings, validated these manipulations in an in vivo murine model, and corroborated acute T-cell leukemia gene expression profiles in human beings. Moreover, we can model an immunocompetent versus an immunocompromised microenvironment to better understand how signaling is regulated in patients with leukemia

Single-cell multi-omic analysis of the vestibular schwannoma ecosystem uncovers a nerve injury-like state

Vestibular schwannomas (VS) are benign tumors that lead to significant neurologic and otologic morbidity. How VS heterogeneity and the tumor microenvironment (TME) contribute to VS pathogenesis remains poorly understood. In this study, we perform scRNA-seq on 15 VS, with paired scATAC-seq (n = 6) and exome sequencing (n = 12). We identify diverse Schwann cell (SC), stromal, and immune populations in the VS TME and find that repair-like and MHC-II antigen-presenting SCs are associated with myeloid cell infiltrate, implicating a nerve injury-like process. Deconvolution analysis of RNA-expression data from 175 tumors reveals Injury-like tumors are associated with larger tumor size, and scATAC-seq identifies transcription factors associated with nerve repair SCs from Injury-like tumors. Ligand-receptor analysis and in vitro experiments suggest that Injury-like VS-SCs recruit myeloid cells via CSF1 signaling. Our study indicates that Injury-like SCs may cause tumor growth via myeloid cell recruitment and identifies molecular pathways that may be therapeutically targeted

Design, assessment, and \u3ci\u3ein vivo\u3c/i\u3e evaluation of a computational model illustrating the role of CAV1 in CD4\u3csup\u3e+\u3c/sup\u3e T-lymphocytes

Caveolin-1 (CAV1) is a vital scaffold protein heterogeneously expressed in both healthy and malignant tissue. We focus on the role of CAV1 when overexpressed in T-cell leukemia. Previously, we have shown that CAV1 is involved in cell-to-cell communication, cellular proliferation, and immune synapse formation; however, the molecular mechanisms have not been elucidated.We hypothesize that the role of CAV1 in immune synapse formation contributes to immune regulation during leukemic progression, thereby warranting studies of the role of CAV1 in CD4+ T-cells in relation to antigen-presenting cells. To address this need, we developed a computational model of a CD4+ immune effector T-cell to mimic cellular dynamics and molecular signaling under healthy and immunocompromised conditions (i.e., leukemic conditions). Using the Cell Collective computational modeling software, the CD4+ T-cell model was constructed and simulated under CAV1+/+, CAV1+/−, and CAV1−/− conditions to produce a hypothetical immune response. This model allowed us to predict and examine the heterogeneous effects and mechanisms of CAV1 in silico. Experimental results indicate a signature of molecules involved in cellular proliferation, cell survival, and cytoskeletal rearrangement that were highly affected by CAV1 knock out. With this comprehensive model of a CD4+ T-cell, we then validated in vivo protein expression levels. Based on this study, we modeled a CD4+ T-cell, manipulated gene expression in immunocompromised versus competent settings, validated these manipulations in an in vivo murine model, and corroborated acute T-cell leukemia gene expression profiles in human beings. Moreover, we can model an immunocompetent versus an immunocompromised microenvironment to better understand how signaling is regulated in patients with leukemia

Imputation of missing values for cochlear implant candidate audiometric data and potential applications.

ObjectiveAssess the real-world performance of popular imputation algorithms on cochlear implant (CI) candidate audiometric data.Methods7,451 audiograms from patients undergoing CI candidacy evaluation were pooled from 32 institutions with complete case analysis yielding 1,304 audiograms. Imputation model performance was assessed with nested cross-validation on randomly generated sparse datasets with various amounts of missing data, distributions of sparsity, and dataset sizes. A threshold for safe imputation was defined as root mean square error (RMSE) ResultsGreater quantities of missing data were associated with worse performance. Sparsity in audiometric data is not uniformly distributed, as inter-octave frequencies are less commonly tested. With 3-8 missing features per instance, a real-world sparsity distribution was associated with significantly better performance compared to other sparsity distributions (Δ RMSE 0.3 dB- 5.8 dB, non-overlapping 99% confidence intervals). With a real-world sparsity distribution, models were able to safely impute up to 6 missing datapoints in an 11-frequency audiogram. MICE consistently outperformed other models across all metrics and sparsity distributions (p ConclusionPrecision medicine will inevitably play an integral role in the future of hearing healthcare. These methods are data dependent, and rigorously validated imputation models are a key tool for maximizing datasets. Using the largest CI audiogram dataset to-date, we demonstrate that in a real-world scenario MICE can safely impute missing data for the vast majority (>99%) of audiograms with RMSE well below a clinically significant threshold of 10dB. Evaluation across a range of dataset sizes and sparsity distributions suggests a high degree of generalizability to future applications

CRYSTALLIZATION AND PRELIMINARY X-RAY ANALYSIS OF A LIPASE FROM A SPECIES OF PSEUDOMONAS

A lipase from a species of Pseudomonas has been cloned and expressed in E. coli. Variants of this lipase have been generated, using sitespecific mutagenesis, that have significantly altered k,,,, K, and substrate specificity. We have undertaken to determine the threedimensional structure of this enzyme using X-ray crystallography. Crystals have been obtained and these crystals diffract to 2.5 Angstrom resolution. We are now in the process of evaluating heavy atom derivatives to be used to improve the phase information used to calculate electron density maps

Normal hematopoiesis and neurofibromin-deficient myeloproliferative disease require Erk

Neurofibromatosis type 1 (NF1) predisposes individuals to the development of juvenile myelomonocytic leukemia (JMML), a fatal myeloproliferative disease (MPD). In genetically engineered murine models, nullizygosity of Nf1 , a tumor suppressor gene that encodes a Ras-GTPase–activating protein, results in hyperactivity of Raf/Mek/Erk in hematopoietic stem and progenitor cells (HSPCs). Activated Erk1/2 phosphorylate kinases and transcription factors with myriad mitogenic roles in diverse cell types. However, genetic studies examining Erk1/2’s differential and/or combined control of normal and Nf1 -deficient myelopoiesis are lacking. Moreover, prior studies relying on chemical Mek/Erk inhibitors have reached conflicting conclusions in normal and Nf1 -deficient mice. Here, we show that while single Erk1 or Erk2 disruption did not grossly compromise myelopoiesis, dual Erk1/2 disruption rapidly ablated granulocyte and monocyte production in vivo, diminished progenitor cell number, and prevented HSPC proliferation in vitro. Genetic disruption of Erk1/2 in the context of Nf1 nullizygosity ( Mx1Cre + Nf1 flox/flox Erk1 –/– Erk2 flox/flox ) fully protects against the development of MPD. Collectively, we identified a fundamental requirement for Erk1/2 signaling in normal and Nf1 -deficient hematopoiesis, elucidating a critical hematopoietic function for Erk1/2 while genetically validating highly selective Mek/Erk inhibitors in a leukemia that is otherwise resistant to traditional therapy