Search

People often confuse smell loss with taste loss, so it is unclear how much gustatory function is reduced in patients self-reporting taste loss. Our pre-registered cross-sectional study design included an online survey in 12 languages with instructions for self-administering chemosensory tests with 10 household items. Between June 2020 and March 2021, 10,953 individuals participated. Of these, 5,225 self-reported a respiratory illness and were grouped based on their reported COVID test results: COVID-positive (COVID+, N = 3,356), COVID-negative (COVID−, N = 602), and COVID unknown for those waiting for a test result (COVID?, N = 1,267). The participants who reported no respiratory illness were grouped by symptoms: sudden smell/taste changes (STC, N = 4,445), other symptoms excluding smell or taste changes (OthS, N = 832), and no symptoms (NoS, N = 416). Taste, smell, and oral irritation intensities and self-assessed abilities were rated on visual analog scales. Compared to the NoS group, COVID+ was associated with a 21% reduction in taste (95% confidence interval (CI): 15–28%), 47% in smell (95% CI: 37–56%), and 17% in oral irritation (95% CI: 10–25%) intensity. There were medium to strong correlations between perceived intensities and self-reported abilities (r = 0.84 for smell, r = 0.68 for taste, and r = 0.37 for oral irritation). Our study demonstrates that COVID-19-positive individuals report taste dysfunction when self-tested with stimuli that have little to none olfactory components. Assessing the smell and taste intensity of household items is a promising, cost-effective screening tool that complements self-reports and may help to disentangle taste loss from smell loss. However, it does not replace standardized validated psychophysical tests. [ABSTRACT FROM AUTHOR]

AbstractGraph Neural Networks (GNNs) have achieved promising performance in a variety of graph-focused tasks. Despite their success, however, existing GNNs suffer from two significant limitations: a lack of interpretability in their results due to their black-box nature, and an inability to learn representations of varying orders. To tackle these issues, we propose a novel Model-agnostic Graph Neural Network (MaGNet) framework, which is able to effectively integrate information of various orders, extract knowledge from high-order neighbors, and provide meaningful and interpretable results by identifying influential compact graph structures. In particular, MaGNet consists of two components: an estimation model for the latent representation of complex relationships under graph topology, and an interpretation model that identifies influential nodes, edges, and node features. Theoretically, we establish the generalization error bound for MaGNet via empirical Rademacher complexity, and demonstrate its power to represent layer-wise neighborhood mixing. We conduct comprehensive numerical studies using simulated data to demonstrate the superior performance of MaGNet in comparison to several state-of-the-art alternatives. Furthermore, we apply MaGNet to a real-world case study aimed at extracting task-critical information from brain activity data, thereby highlighting its effectiveness in advancing scientific research. [ABSTRACT FROM AUTHOR]

In a preregistered, cross-sectional study, we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0–100 visual analog scales (VAS) for participants reporting a positive (C19+; n = 4148) or negative (C19−; n = 546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19− groups exhibited smell loss, but it was significantly larger in C19+ participants (mean ± SD, C19+: −82.5 ± 27.2 points; C19−: −59.8 ± 37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC = 0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g. fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0–10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4 < OR < 10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable. [ABSTRACT FROM AUTHOR]

A wealth of rapidly evolving reports suggests that olfaction and taste disturbances may be manifestations of the novel COVID-19 pandemic. While otolaryngological societies worldwide have started to consider chemosensory evaluation as a screening tool for COVID-19 infection, the true nature of the relationship between the changes in chemosensory ability and COVID-19 is unclear. Our goal with this review is to provide a brief overview of published and archived literature, as well as the anecdotal reports and social trends related to this topic up to April 29, 2020. We also aim to draw parallels between the clinical/chemosensory symptomology reported in association to past coronavirus pandemics (such as SARS and MERS) and the novel COVID-19. This review also highlights current evidence on persistent chemosensory disturbances after the infection has resolved. Overall, our analysis pinpoints the need for further studies: (1) to better quantify olfaction and taste disturbances associated with SARS-CoV-2 infection, compared to those of other viral and respiratory infections, (2) to understand the relation between smell, taste, and chemesthesis disturbances in COVID-19, and (3) to understand how persistent are these disturbances after the infection has resolved. [ABSTRACT FROM AUTHOR]

Participants in cluster 2 (orange,N= 1724; bottom center) are generally characterized by ratings that reflect smell/taste loss with preserved chemesthesis. Based on the centroid of each cluster, participants in cluster 1 (blue,N= 1767; top left) are generally characterized by significant smell, taste and chemesthesis loss. Loadings for participants in cluster 3 (green,N= 548; right side) are generally characterized by reduced smell and taste loss, and preserved chemesthesis. [Extracted from the article]

Introduction: There have been large geographical differences in the infection and death rates of COVID-19. Foods and beverages containing high amounts of phytochemicals with bioactive properties were suggested to prevent contracting and to facilitate recovery from COVID-19. The goal of our study was to determine the correlation of the type of foods/beverages people consumed and the risk reduction of contracting COVID-19 and the recovery from COVID-19., Methods: We developed an online survey that asked the participants whether they contracted COVID-19, their symptoms, time to recover, and their frequency of eating various types of foods/beverages. The survey was developed in 10 different languages., Results: The participants who did not contract COVID-19 consumed vegetables, herbs/spices, and fermented foods/beverages significantly more than the participants who contracted COVID-19. Among the six countries (India/Iran/Italy/Japan/Russia/Spain) with over 100 participants and high correspondence between the location of the participants and the language of the survey, in India and Japan the people who contracted COVID-19 showed significantly shorter recovery time, and greater daily intake of vegetables, herbs/spices, and fermented foods/beverages was associated with faster recovery., Conclusions: Our results suggest that phytochemical compounds included in the vegetables may have contributed in not only preventing contraction of COVID-19, but also accelerating their recovery., (Copyright © 2024 Koyama, Joseph, Shields, Heinbockel, Adhikari, Kaur, Kumar, Alizadeh, Bhutani, Calcinoni, Mucignat-Caretta, Chen, Cooper, Das, Rohlfs Domínguez, Guàrdia, Klyuchnikova, Laktionova, Mori, Namjoo, Nguyen, Özdener, Parsa, Özdener Poyraz, Strub, Taghizadeh-Hesary, Ueha and Voznessenskaya.)

Background: Smell disorders are commonly reported with COVID-19 infection. The smell-related issues associated with COVID-19 may be prolonged, even after the respiratory symptoms are resolved. These smell dysfunctions can range from anosmia (complete loss of smell) or hyposmia (reduced sense of smell) to parosmia (smells perceived differently) or phantosmia (smells perceived without an odor source being present). Similar to the difficulty that people experience when talking about their smell experiences, patients find it difficult to express or label the symptoms they experience, thereby complicating diagnosis. The complexity of these symptoms can be an additional burden for patients and health care providers and thus needs further investigation., Objective: This study aims to explore the smell disorder concerns of patients and to provide an overview for each specific smell disorder by using the longitudinal survey conducted in 2020 by the Global Consortium for Chemosensory Research, an international research group that has been created ad hoc for studying chemosensory dysfunctions. We aimed to extend the existing knowledge on smell disorders related to COVID-19 by analyzing a large data set of self-reported descriptive comments by using methods from natural language processing., Methods: We included self-reported data on the description of changes in smell provided by 1560 participants at 2 timepoints (second survey completed between 23 and 291 days). Text data from participants who still had smell disorders at the second timepoint (long-haulers) were compared with the text data of those who did not (non-long-haulers). Specifically, 3 aims were pursued in this study. The first aim was to classify smell disorders based on the participants' self-reports. The second aim was to classify the sentiment of each self-report by using a machine learning approach, and the third aim was to find particular food and nonfood keywords that were more salient among long-haulers than those among non-long-haulers., Results: We found that parosmia (odds ratio [OR] 1.78, 95% CI 1.35-2.37; P<.001) as well as hyposmia (OR 1.74, 95% CI 1.34-2.26; P<.001) were more frequently reported in long-haulers than in non-long-haulers. Furthermore, a significant relationship was found between long-hauler status and sentiment of self-report (P<.001). Finally, we found specific keywords that were more typical for long-haulers than those for non-long-haulers, for example, fire, gas, wine, and vinegar., Conclusions: Our work shows consistent findings with those of previous studies, which indicate that self-reports, which can easily be extracted online, may offer valuable information to health care and understanding of smell disorders. At the same time, our study on self-reports provides new insights for future studies investigating smell disorders., (©Nick S Menger, Arnaud Tognetti, Michael C Farruggia, Carla Mucignat, Surabhi Bhutani, Keiland W Cooper, Paloma Rohlfs Domínguez, Thomas Heinbockel, Vonnie D C Shields, Anna D'Errico, Veronica Pereda-Loth, Denis Pierron, Sachiko Koyama, Ilja Croijmans. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 10.05.2024.)

Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments, such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, and generally lacked quantitative measurements. Here, we report the development, implementation, and initial results of a multilingual, international questionnaire to assess self-reported quantity and quality of perception in 3 distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, and 8 others, aged 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste, and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change ±100) revealed a mean reduction of smell (-79.7 ± 28.7, mean ± standard deviation), taste (-69.0 ± 32.6), and chemesthetic (-37.3 ± 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell but also affects taste and chemesthesis. The multimodal impact of COVID-19 and the lack of perceived nasal obstruction suggest that severe acute respiratory syndrome coronavirus strain 2 (SARS-CoV-2) infection may disrupt sensory-neural mechanisms., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The main neurological manifestation of COVID-19 is loss of smell or taste. The high incidence of smell loss without significant rhinorrhea or nasal congestion suggests that SARS-CoV-2 targets the chemical senses through mechanisms distinct from those used by endemic coronaviruses or other common cold-causing agents. Here we review recently developed hypotheses about how SARS-CoV-2 might alter the cells and circuits involved in chemosensory processing and thereby change perception. Given our limited understanding of SARS-CoV-2 pathogenesis, we propose future experiments to elucidate disease mechanisms and highlight the relevance of this ongoing work to understanding how the virus might alter brain function more broadly., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Traveling waves are hypothesized to support the long-range coordination of anatomically distributed circuits. Whether separate strongly interacting circuits exhibit traveling waves remains unknown. The hippocampus exhibits traveling 'theta' waves and interacts strongly with the medial entorhinal cortex (MEC). To determine whether the MEC also activates in a traveling wave, we performed extracellular recordings of local field potentials (LFP) and multi-unit activity along the MEC. These recordings revealed progressive phase shifts in activity, indicating that the MEC also activates in a traveling wave. Variation in theta waveform along the region, generated by gradients in local physiology, contributed to the observed phase shifts. Removing waveform-related phase shifts left significant residual phase shifts. The residual phase shifts covaried with theta frequency in a manner consistent with those generated by weakly coupled oscillators. These results show that the coordination of anatomically distributed circuits could be enabled by traveling waves but reveal heterogeneity in the mechanisms generating those waves., Competing Interests: JH, KC, EN No competing interests declared, (© 2020, Hernández-Pérez et al.)