Astrocytes Regulate Daily Rhythms in the Suprachiasmatic Nucleus (SCN) and Behavior

Astrocytes are active partners in neural information processing. However, the roles of astrocytes in regulating behavior remain unclear. Because astrocytes have persistent circadian clock gene expression and ATP release in vitro, I hypothesized that they regulate daily rhythms in neurons and behavior. Here, I demonstrated that daily rhythms in astrocytes within the mammalian master circadian pacemaker, the suprachiasmatic nucleus (SCN), determine the period of wheel-running activity. Ablating the essential clock gene Bmal1 specifically in SCN astrocytes lengthened the circadian period of clock gene expression in the SCN and in locomotor behavior. Similarly, excision of the short-period CK1_ tau mutation specifically from SCN astrocytes also resulted in lengthened rhythms in the SCN and behavior. These results indicate that astrocytes within the SCN communicate to neurons to determine circadian rhythms in physiology and in wheel-running activity. As a first step to understanding how the two cell types interact, I attempted to delineate the circadian phase relationship of clock gene expression between neurons and astrocytes. With limited success, I will discuss both preliminary findings and challenges I faced. Lastly, I will present SCN single-cell transcriptomics data as a first step to understand properties of SCN astrocytes and diversity of SCN cell types. Clock genes enriched in SCN astrocytes identified by single-cell transcriptomics here can serve as a launching point to investigate how SCN astrocytes communicate to SCN neurons

Semisupervised Deep Learning Techniques for Predicting Acute Respiratory Distress Syndrome From Time-Series Clinical Data: Model Development and Validation Study

BackgroundA high number of patients who are hospitalized with COVID-19 develop acute respiratory distress syndrome (ARDS). ObjectiveIn response to the need for clinical decision support tools to help manage the next pandemic during the early stages (ie, when limited labeled data are present), we developed machine learning algorithms that use semisupervised learning (SSL) techniques to predict ARDS development in general and COVID-19 populations based on limited labeled data. MethodsSSL techniques were applied to 29,127 encounters with patients who were admitted to 7 US hospitals from May 1, 2019, to May 1, 2021. A recurrent neural network that used a time series of electronic health record data was applied to data that were collected when a patient’s peripheral oxygen saturation level fell below the normal range (<97%) to predict the subsequent development of ARDS during the remaining duration of patients’ hospital stay. Model performance was assessed with the area under the receiver operating characteristic curve and area under the precision recall curve of an external hold-out test set. ResultsFor the whole data set, the median time between the first peripheral oxygen saturation measurement of <97% and subsequent respiratory failure was 21 hours. The area under the receiver operating characteristic curve for predicting subsequent ARDS development was 0.73 when the model was trained on a labeled data set of 6930 patients, 0.78 when the model was trained on the labeled data set that had been augmented with the unlabeled data set of 16,173 patients by using SSL techniques, and 0.84 when the model was trained on the entire training set of 23,103 labeled patients. ConclusionsIn the context of using time-series inpatient data and a careful model training design, unlabeled data can be used to improve the performance of machine learning models when labeled data for predicting ARDS development are scarce or expensive

Cell-Autonomous Regulation of Astrocyte Activation by the Circadian Clock Protein BMAL1

Circadian clock dysfunction is a common symptom of aging and neurodegenerative diseases, though its impact on brain health is poorly understood. Astrocyte activation occurs in response to diverse insults and plays a critical role in brain health and disease. We report that the core circadian clock protein BMAL1 regulates astrogliosis in a synergistic manner via a cell-autonomous mechanism and a lesser non-cell-autonomous signal from neurons. Astrocyte-specific Bmal1 deletion induces astrocyte activation and inflammatory gene expression in vitro and in vivo, mediated in part by suppression of glutathione-S-transferase signaling. Functionally, loss of Bmal1 in astrocytes promotes neuronal death in vitro. Our results demonstrate that the core clock protein BMAL1 regulates astrocyte activation and function in vivo, elucidating a mechanism by which the circadian clock could influence many aspects of brain function and neurological disease. [Display omitted] •Circadian disruption promotes astrocyte activation•Astrocyte-specific deletion of the circadian clock gene BMAL1 induces activation•BMAL1 regulates astrocyte activation by altering glutathione-S-transferase signaling•Loss of astrocyte BMAL1 enhances neuronal cell death in a co-culture system Lananna et al. show that the circadian clock protein BMAL1 regulates astrocyte activation via a cell-autonomous mechanism involving diminished glutathione-S-transferase signaling. This finding elucidates a function of the core circadian clock in astrocytes and reveals BMAL1 as a modulator of astrogliosis