Green Tea-Derived Catechins have Beneficial Effects on Cognition in the Pond Snail

Green tea has been used as a medicine in East Asia for thousands of years. Plant-derived compounds called flavanols, which are included in green tea, may have potentials to help maintain healthy brain function. In this chapter, we review the effects of flavanols, e.g. epicatechin (EpiC), on cognitive ability in the pond snail, Lymnaea stagnalis. In this decade, the Lukowiak’s group has tested the effects of EpiC on cognition ability in Lymnaea. In a Lymnaea model system, they showed that EpiC and EpiC-containing foods have a rapid and activity-dependent effect enhancing the formation of long-term memory (LTM) following operant conditioning of aerial respiratory behavior. In the last part of this chapter, we also introduce our study for the effects of EpiC on LTM formation in another model system in Lymnaea. This study showed that EpiC increases the persistence of LTM formed by classical conditioning of feeding behavior, and suggested that EpiC alters some electrophysiological properties of a neuron in the feeding system.

Feasibility of Using the Hexoskin Smart Garment for Natural Environment Observation of Respiration Topography

Background: Limited research has been done to measure ambulatory respiratory behavior, in particular those associated with tobacco use, in the natural environment due to a lack of monitoring techniques. Respiratory topography parameters provide useful information for modeling particle deposition in the lung and assessing exposure risk and health effects associated with tobacco use. Commercially available Wearable Respiratory Monitors (WRM), such as the Hexoskin Smart Garment, have embedded sensors that measure chest motion and may be adapted for measuring ambulatory lung volume. Methods: Self-reported “everyday” and “some days” Hookah and Cigarette smokers were recruited for a 3-day natural environment observation study. Participants wore the Hexoskin shirt while using their preferred tobacco product. The shirt was calibrated on them prior to, during, and after the observation period. A novel method for calculating the calibration parameters is presented. Results: NH = 5 Hookah and NC = 3 Cigarette participants were enrolled. Calibration parameters were obtained and applied to the observed chest motion waveform from each participant to obtain their lung volume waveform. Respiratory topography parameters were derived from the lung volume waveform. Conclusion: The feasibility of using the Hexoskin for measuring ambulatory respiratory topography parameters in the natural environment is demonstrated.

Feasibility of Using the Hexoskin Smart Garment for Natural Environment Observation of Respiration Topography

Background: Limited research has been done to measure ambulatory respiratory behavior, in particular those associated with tobacco use, in the natural environment due to a lack of monitoring techniques. Respiratory topography parameters provide useful information for modelling particle deposition in the lung and assessing exposure risk and health effects associated with tobacco use. Commercially available Wearable Respiratory Monitors (WRM), such as the Hexoskin Smart Garment, have embedded sensors which measure chest motion and may be adapted for measuring ambulatory lung volume. Methods: Self-reported ‘everyday’ and ‘some days’ Hookah and Cigarette smokers were recruited for a 3-day natural environment observation study. Participants wore the Hexoskin shirt while using their preferred tobacco product. The shirt was calibrated on them prior to, during, and after the observation period. A novel method for calculating the calibration parameters is presented. Results: N=5 Hookah and N=3 Cigarette participants were enrolled. Calibration parameters were obtained and applied to the observed chest motion waveform from each participant to obtain their lung volume waveform. Respiratory topography parameters were derived from the lung volume waveform. Conclusion: The feasibility of using the Hexoskin for measuring ambulatory respiratory topography parameters in the natural environment is demonstrated..

Distracted and Drowsy Driving Modeling Using Deep Physiological Representations and Multitask Learning

In this paper, we investigated various physiological indicators on their ability to identify distracted and drowsy driving. In particular, four physiological signals are being tested: blood volume pulse (BVP), respiration, skin conductance and skin temperature. Data were collected from 45 participants, under a simulated driving scenario, through different times of the day and during their engagement on a variety of physical and cognitive distractors. We explore several statistical features extracted from those signals and their efficiency to discriminate between the presence or not of each of the two conditions. To that end, we evaluate three traditional classifiers (Random Forests, KNN and SVM), which have been extensively applied by the related literature and we compare their performance against a deep CNN-LSTM network that learns spatio-temporal physiological representations. In addition, we explore the potential of learning multiple conditions in parallel using a single machine learning model, and we discuss how such a problem could be formulated and what are the benefits and disadvantages of the different approaches. Overall, our findings indicate that information related to the BVP data, especially features that describe patterns with respect to the inter-beat-intervals (IBI), are highly associates with both targeted conditions. In addition, features related to the respiratory behavior of the driver can be indicative of drowsiness, while being less associated with distractions. Moreover, spatio-temporal deep methods seem to have a clear advantage against traditional classifiers on detecting both driver conditions. Our experiments show, that even though learning both conditions jointly can not compete directly to individual, task-specific CNN-LSTM models, deep multitask learning approaches have a great potential towards that end as they offer the second best performance on both tasks against all other evaluated alternatives in terms of sensitivity, specificity and the area under the receiver operating characteristic curve (AUC).

The Respiratory Foundations of Spoken Language

Why is breathing relevant in linguistics? In this review, we approach this question from different perspectives. The most popular view is that breathing adapts to speech because respiratory behavior has astonishing flexibility. We review research that shows that breathing pauses occur mostly at meaningful places, that breathing adapts to cognitive load during speech perception, and that breathing adapts to communicative needs in dialogue. However, speech may also adapt to breathing (e.g., the larynx can compensate for air loss, breathing can partially affect f0 declination). Enhanced breathing control may have played a role in vocalization and language evolution. These views are not mutually exclusive but, rather, reveal that speech production and breathing have an interwoven relationship that depends on communicative and physical constraints. We suggest that breathing should become an important topic for different linguistic areas and that future work should investigate the interaction between breathing and speech in different situational contexts. Expected final online publication date for the Annual Review of Linguistics, Volume 7 is January 14, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Vascular control of the CO2/H+-dependent drive to breathe

Respiratory chemoreceptors regulate breathing in response to changes in tissue CO2/H+. Blood flow is a fundamental determinant of tissue CO2/H+, yet little is known regarding how regulation of vascular tone in chemoreceptor regions contributes to respiratory behavior. Previously, we showed in rat that CO2/H+-vasoconstriction in the retrotrapezoid nucleus (RTN) supports chemoreception by a purinergic-dependent mechanism (Hawkins et al., 2017). Here, we show in mice that CO2/H+ dilates arterioles in other chemoreceptor regions, thus demonstrating CO2/H+ vascular reactivity in the RTN is unique. We also identify P2Y2 receptors in RTN smooth muscle cells as the substrate responsible for this response. Specifically, pharmacological blockade or genetic deletion of P2Y2 from smooth muscle cells blunted the ventilatory response to CO2, and re-expression of P2Y2 receptors only in RTN smooth muscle cells fully rescued the CO2/H+ chemoreflex. These results identify P2Y2 receptors in RTN smooth muscle cells as requisite determinants of respiratory chemoreception.

ß2-Arrestin germline knockout does not attenuate opioid respiratory depression

Opioids are perhaps the most effective analgesics in medicine. However, from 1999 to 2018, they also killed more than 400,000 people in the United States by suppressing breathing, a common side-effect known as opioid induced respiratory depression. This doubled-edged sword has inspired the dream of developing novel therapeutics that provide opioid-like analgesia without respiratory depression. One such approach has been to develop so-called ‘biased agonists’ that activate some, but not all pathways downstream of the µ-opioid receptor (MOR), the target of morphine and other opioid analgesics. This hypothesis stems from a study suggesting that MOR-mediated activation of ß2-Arrestin is the downstream signaling pathway responsible for respiratory depression, whereas inhibition of adenylyl cyclase produces analgesia. To further verify this model, which represents the motivation for the biased agonist approach, we examined respiratory behavior in mice lacking the gene for ß2-Arrestin. Contrary to previous findings, we find no correlation between ß2-Arrestin function and opioid-induced respiratory depression, suggesting that any effect of biased agonists must be mediated through an as-yet to be identified signaling mechanism.

Vascular control of the CO2/H+ dependent drive to breathe

Respiratory chemoreceptors regulate breathing in response to changes in tissue CO2/H+. Blood flow is a fundamental determinant of tissue CO2/H+, yet little is known regarding how regulation of vascular tone in chemoreceptor regions contributes to respiratory behavior. Previously, we showed in rat that CO2/H+-vasoconstriction in the retrotrapezoid nucleus (RTN) supports chemoreception by a purinergic-dependent mechanism (Hawkins et al. 2017). Here, we show in mice that CO2/H+ dilates arterioles in other chemoreceptor regions, thus demonstrating CO2/H+ vascular reactivity in the RTN is unique. We also identify P2Y2 receptors in RTN smooth muscle cells as the substrate responsible for this response. Specifically, pharmacological blockade or genetic deletion of P2Y2 from smooth muscle cells blunted the ventilatory response to CO2, and re-expression of P2Y2 receptors only in RTN smooth muscle cells fully rescued the CO2/H+ chemoreflex. These results identify P2Y2 receptors in RTN smooth muscle cells as requisite determinants of respiratory chemoreception.Significance StatementDisruption of vascular control as occurs in cardiovascular disease leads to compromised chemoreceptor function and unstable breathing. Despite this, virtually nothing is known regarding how regulation of vascular tone in chemoreceptor regions contributes to respiratory behavior. Here, we identify P2Y2 receptors in RTN vascular smooth muscle cells as a novel vascular element of respiratory chemoreception. Identification of this mechanism may facilitate development of treatments for breathing problems including those associated with cardiovascular disease.

Fiber-Optic Based Smart Textiles for Real-Time Monitoring of Breathing Rate

Wearable light textiles are gaining widespread interest in application for measurement and monitoring of biophysical parameters. Fiber optic sensors, in particular Bragg Grating (FBG) sensors, can be a competitive method for monitoring of respiratory behavior for chest and abdomen regions since the sensors are able to convert physical movement into wavelength shift. This study aims to show the performance of elastic belts with integrated optical fibers during the breathing activities done by two volunteers. Additionally, the work aims to determine how the positions of the volunteers affect the breathing pattern detected by optical fibers. As a reference, commercial mobile application for sensing vibration is used. The obtained results show that the FBGs are able to detect chest and abdomen movements during breathing and consequently reconstruct the breathing pattern. The accuracy of the results varies for two volunteers but remains consistent.