In this short review, we highlight recent findings in the emerging field of epitranscriptomic mechanisms and discuss their potential role in neural plasticity, learning and memory. These include the influence of RNA modifications on activity-induced RNA structure states, RNA editing and RNA localization, and how qualitative state changes in RNA increase the functional diversity and information-carrying capacity of RNA molecules. We predict that RNA modifications may be just as important for synaptic plasticity and memory as quantitative changes in transcript and protein abundance, but with the added advantage of not being required to signal back to the nucleus, and therefore better suited to be coordinated with the temporal dynamics of learning.

No abstract

For the past 50 years, positive pressure ventilation has been a cornerstone of treatment for respiratory failure. Consensus surrounding the epidemiology of respiratory failure has permitted a relatively good fit between the supply of ventilators and the demand. However, the current COVID-19 pandemic has increased demand for mechanical ventilators well beyond supply. Respiratory failure complicates most critically ill patients with COVID-19 and is characterized by highly heterogeneous pulmonary parenchymal involvement, profound hypoxemia and pulmonary vascular injury. The profound increase in the incidence of respiratory failure has exposed critical shortages in the supply of mechanical ventilators, and those with the necessary skills to treat. While most traditional ventilators rely on an internal compressor and mixer to moderate and control the gas mixture delivered to a patient, the current emergency climate has catalyzed alternative designs that might enable greater flexibility in terms of supply chain, manufacturing, storage and maintenance. Design considerations of these 'emergency response' ventilators have generally fallen into two categories: those that rely on mechanical compression of a known volume of gas and those powered by an internal compressor to deliver time cycled pressure- or volume-limited gas to the patient. The present work introduces a low-cost, ventilator designed and built in accordance with the Emergence Use guidance provided by the US Food and Drug Administration (FDA) wherein an external gas supply feeds into the ventilator and time limited flow interruption guarantees tidal volume. The goal of this device is to allow a patient to be treated by a single ventilator platform, capable of supporting the various treatment paradigms during a potential COVID-19 related hospitalization. This is a unique aspect of this design as it attempts to become a one-device-one-visit solution to the problem. The device is designed as a single use ventilator that is sufficiently robust to treat a patient being mechanically ventilated. The overall design philosophy and its applicability in this new crisis-laden world view is first described, followed by both bench top and animal testing results used to confirm the precision, capability, safety and reliability of this low cost and novel approach to mechanical ventilation during the COVID-19 pandemic. The ventilator is shown to perform in a range of critical requirements listed in the FDA emergency regulations and can safely and effectively ventilate a porcine subject. As of August 2020, only 13 emergency ventilators have been authorized by the FDA, and this work represents the first to publish animal data using the ventilator. This proof-of-concept provides support for this cost-effective, readily mass-produced ventilator that can be used to support patients when the demand for ventilators outstrips supply in hospital settings worldwide. More details for this project can be found at https://ventilator.stanford.edu/

COVID-19 has become a significant burden on the healthcare systems in the United States and around the world, with many patients requiring invasive mechanical ventilation (IMV) to survive. Close monitoring of patients is critical, with total volume per breath (tidal volume) being one of the most important data points. However, ventilators are complex and expensive devices, typically in the range of tens of thousands of US dollars, and are challenging to manufacture, typically requiring months. Solutions which could augment the ventilator supply rapidly and at low cost in the United States and elsewhere would be valuable. In this paper, we present a standalone tidal volume measurement system consisting of a D-Lite spirometer, pressure sensor, microcontroller, and tubing with a cost of parts less than $50 USD. We also provide a model to predict the error in tidal volume measurements based on the pressure sensor used and the flow during ventilation. We validate this system and show that the tidal volume accuracy for flows above 10L/min was within 10%. We envision this system being used to increase the ventilator supply in resource-constrained settings.

Continuous monitoring of voltages ranging from tens to hundreds of kV over environmental conditions, such as temperature, is of great interest in power grid applications. This is typically done via instrument transformers. These transformers, although accurate and robust to environmental conditions, are bulky and expensive, limiting their use in microgrids and distributed sensing applications. Here, we present a millimeter-sized optical voltage sensor based on piezoelectric aluminum nitride (AlN) thin film for continuous measurements of AC voltages <350kV rms (via capacitive division) that avoids the drawbacks of existing voltage-sensing transformers. This sensor operated with 110μW incident optical power from a low-cost LED achieved a resolution of 170mV rms in a 5kHz bandwidth, 0.04% second harmonic distortion, and a gain deviation of +/-0.2% over the temperature range of ~20-60°C. The sensor has a breakdown voltage of 100V, and its lifetime can meet or exceed that of instrument transformers when operated at voltages <70kV rms with capacitive division. We believe that our sensor has the potential to reduce the cost of grid monitoring, providing a path towards more distributed sensing and control of the grid.