Impact of alcohol exposure on neural development and network formation in human cortical organoids.

Prenatal alcohol exposure is the foremost preventable etiology of intellectual disability and leads to a collection of diagnoses known as Fetal Alcohol Spectrum Disorders (FASD). Alcohol (EtOH) impacts diverse neural cell types and activity, but the precise functional pathophysiological effects on the human fetal cerebral cortex are unclear. Here, we used human cortical organoids to study the effects of EtOH on neurogenesis and validated our findings in primary human fetal neurons. EtOH exposure produced temporally dependent cellular effects on proliferation, cell cycle, and apoptosis. In addition, we identified EtOH-induced alterations in post-translational histone modifications and chromatin accessibility, leading to impairment of cAMP and calcium signaling, glutamatergic synaptic development, and astrocytic function. Proteomic spatial profiling of cortical organoids showed region-specific, EtOH-induced alterations linked to changes in cytoskeleton, gliogenesis, and impaired synaptogenesis. Finally, multi-electrode array electrophysiology recordings confirmed the deleterious impact of EtOH on neural network formation and activity in cortical organoids, which was validated in primary human fetal tissues. Our findings demonstrate progress in defining the human molecular and cellular phenotypic signatures of prenatal alcohol exposure on functional neurodevelopment, increasing our knowledge for potential therapeutic interventions targeting FASD symptoms.

RNA processing in neurological tissue: development, aging and disease.

Gene expression comprises a diverse array of enzymes, proteins, non-coding transcripts, and cellular structures to guide the transfer of genetic information to its various final products. In the brain, the coordination among genes, or lack thereof, characterizes individual brain regions, mediates a variety of brain-related disorders, and brings light to fundamental differences between species. RNA processing, occurring between transcription and translation, controls an essential portion of gene expression through splicing, editing, localization, stability, and interference. The machinery to regulate transcripts must operate with precision serving as a blueprint for proteins and non-coding RNAs to derive their identity. Therefore, RNA processing has a broad scope of influence in the brain, as it modulates cell morphogenesis during development and underlies mechanisms behind certain neurological diseases. Here, we present these ideas through recent findings on RNA processing in development and post-developmental maturity to advance therapeutic discoveries and the collective knowledge of the RNA life cycle.

Altered network and rescue of human neurons derived from individuals with early-onset genetic epilepsy.

Early-onset epileptic encephalopathies are severe disorders often associated with specific genetic mutations. In this context, the CDKL5 deficiency disorder (CDD) is a neurodevelopmental condition characterized by early-onset seizures, intellectual delay, and motor dysfunction. Although crucial for proper brain development, the precise targets of CDKL5 and its relation to patients' symptoms are still unknown. Here, induced pluripotent stem cells derived from individuals deficient in CDKL5 protein were used to generate neural cells. Proteomic and phosphoproteomic approaches revealed disruption of several pathways, including microtubule-based processes and cytoskeleton organization. While CDD-derived neural progenitor cells have proliferation defects, neurons showed morphological alterations and compromised glutamatergic synaptogenesis. Moreover, the electrical activity of CDD cortical neurons revealed hyperexcitability during development, leading to an overly synchronized network. Many parameters of this hyperactive network were rescued by lead compounds selected from a human high-throughput drug screening platform. Our results enlighten cellular, molecular, and neural network mechanisms of genetic epilepsy that could ultimately promote novel therapeutic opportunities for patients.

Outcomes and Barriers Associated with Telehealth-Based Hepatitis C Treatment During Early Phases of the COVID-19 Pandemic.

Introduction: The COVID-19 pandemic has presented challenges for hepatitis C virus (HCV) treatment given the need for thorough evaluation by specialists, treatment coordination, follow-up visits, laboratory monitoring, and potential health behavior impacts on patients. The objective of this study was to evaluate HCV treatment during the beginning of the COVID-19 pandemic, when care was conducted virtually, by examining patient demographics associated with treatment initiation and discontinuation rates. Methods: This retrospective study included 73 patients with quantifiable HCV RNA evaluated by gastroenterologists and infectious disease clinicians and referred to an HCV clinical pharmacy team for treatment coordination from March 1, 2020, to September 30, 2020. Data collection included baseline demographics, clinical characteristics, and treatment characteristics. Patients were followed until June 15, 2021. Results: Forty-three patients (59%) initiated HCV treatment while 30 patients (41%) did not. Patient demographics were not associated with HCV treatment initiation rates except for presence of alcohol use disorder within the past 6 months (P = .003). Of the 43 patients that initiated HCV treatment, 9 patients (21%) discontinued their treatment. Twenty-two of 25 patients (88%) with laboratory analysis achieved sustained virologic response. There were no demographic or geographic disparities between patients that initiated HCV treatment and those that did not during the study period. Conclusions: Results of this study suggest that active alcohol use disorder diagnosis may be associated with HCV treatment noninitiation. This study emphasizes the need for further research to define the standards of care in assessing active alcohol use disorder during HCV treatment evaluation.

Speech timing and monosyllabic diadochokinesis measures in the assessment of amyotrophic lateral sclerosis in Canadian French.

PURPOSE: The primary objective of this study was to determine if speech and pause measures obtained using a passage reading task and timing measures from a monosyllabic diadochokinesis (DDK) task differ across speakers of Canadian French diagnosed with amyotrophic lateral sclerosis (ALS) presenting with and without bulbar symptoms, and healthy controls. The secondary objective was to determine if these measures can reflect the severity of bulbar symptoms. METHOD: A total of 29 Canadian French speakers with ALS (classified as bulbar symptomatic [n = 14] or pre-symptomatic [n = 15]) and 17 age-matched healthy controls completed a passage reading task and a monosyllabic DDK task (/pa/ and /ta/), for up to three follow-up visits. Measures of speaking rate, total duration, speech duration, and pause events were extracted from the passage reading recordings using a semi-automated speech and pause analysis procedure. Manual analysis of DDK recordings provided measures of DDK rate and variability. RESULT: Group comparisons revealed significant differences (p = < .05) between the symptomatic group and the pre-symptomatic and control groups for all passage measures and DDK rates. Only the DDK rate in /ta/ differentiated the pre-symptomatic and control groups. Repeated measures correlations revealed moderate correlations (rrm = > 0.40; p = < 0.05) between passage measures of total duration, speaking rate, speech duration, and number of pauses, and ALSFRS-R total and bulbar scores, as well as between DDK rate and ALSFRS-R total score. CONCLUSION: Speech and pause measures in passage and timing measures in monosyllabic DDK tasks might be suitable for monitoring bulbar functional symptoms in French speakers with ALS, but more work is required to identify which measures are sensitive to the earliest stages of the disease.

Validation of automated pipeline for the assessment of a motor speech disorder in amyotrophic lateral sclerosis (ALS).

Background and objective: Amyotrophic lateral sclerosis (ALS) frequently causes speech impairments, which can be valuable early indicators of decline. Automated acoustic assessment of speech in ALS is attractive, and there is a pressing need to validate such tools in line with best practices, including analytical and clinical validation. We hypothesized that data analysis using a novel speech assessment pipeline would correspond strongly to analyses performed using lab-standard practices and that acoustic features from the novel pipeline would correspond to clinical outcomes of interest in ALS. Methods: We analyzed data from three standard speech assessment tasks (i.e., vowel phonation, passage reading, and diadochokinesis) in 122 ALS patients. Data were analyzed automatically using a pipeline developed by Winterlight Labs, which yielded 53 acoustic features. First, for analytical validation, data were analyzed using a lab-standard analysis pipeline for comparison. This was followed by univariate analysis (Spearman correlations between individual features in Winterlight and in-lab datasets) and multivariate analysis (sparse canonical correlation analysis (SCCA)). Subsequently, clinical validation was performed. This included univariate analysis (Spearman correlation between automated acoustic features and clinical measures) and multivariate analysis (interpretable autoencoder-based dimensionality reduction). Results: Analytical validity was demonstrated by substantial univariate correlations (Spearman's ρ > 0.70) between corresponding pairs of features from automated and lab-based datasets, as well as interpretable SCCA feature groups. Clinical validity was supported by strong univariate correlations between automated features and clinical measures (Spearman's ρ > 0.70), as well as associations between multivariate outputs and clinical measures. Conclusion: This novel, automated speech assessment feature set demonstrates substantial promise as a valid tool for analyzing impaired speech in ALS patients and for the further development of these technologies.

Analytical Validation of a Webcam-Based Assessment of Speech Kinematics: Digital Biomarker Evaluation following the V3 Framework.

Introduction: Kinematic analyses have recently revealed a strong potential to contribute to the assessment of neurological diseases. However, the validation of home-based kinematic assessments using consumer-grade video technology has yet to be performed. In line with best practices for digital biomarker development, we sought to validate webcam-based kinematic assessment against established, laboratory-based recording gold standards. We hypothesized that webcam-based kinematics would possess psychometric properties comparable to those obtained using the laboratory-based gold standards. Methods: We collected data from 21 healthy participants who repeated the phrase "buy Bobby a puppy" (BBP) at four different combinations of speaking rate and volume: Slow, Normal, Loud, and Fast. We recorded these samples twice back-to-back, simultaneously using (1) an electromagnetic articulography ("EMA"; NDI Wave) system, (2) a 3D camera (Intel RealSense), and (3) a 2D webcam for video recording via an in-house developed app. We focused on the extraction of kinematic features in this study, given their demonstrated value in detecting neurological impairments. We specifically extracted measures of speed/acceleration, range of motion (ROM), variability, and symmetry using the movements of the center of the lower lip during these tasks. Using these kinematic features, we derived measures of (1) agreement between recording methods, (2) test-retest reliability of each method, and (3) the validity of webcam recordings to capture expected changes in kinematics as a result of different speech conditions. Results: Kinematics measured using the webcam demonstrated good agreement with both the RealSense and EMA (ICC-A values often ≥0.70). Test-retest reliability, measured using the absolute agreement (2,1) formulation of the intraclass correlation coefficient (i.e., ICC-A), was often "moderate" to "strong" (i.e., ≥0.70) and similar between the webcam and EMA-based kinematic features. Finally, the webcam kinematics were typically as sensitive to differences in speech tasks as EMA and the 3D camera gold standards. Discussion and Conclusions: Our results suggested that webcam recordings display good psychometric properties, comparable to laboratory-based gold standards. This work paves the way for a large-scale clinical validation to continue the development of these promising technologies for the assessment of neurological diseases via home-based methods.