Emotional eating phenotype is associated with central dopamine D2 receptor binding independent of body mass index

PET studies have provided mixed evidence regarding central D2/D3 dopamine receptor binding and its relationship with obesity as measured by body mass index (BMI). Other aspects of obesity may be more tightly coupled to the dopaminergic system. We characterized obesity-associated behaviors and determined if these related to central D2 receptor (D2R) specific binding independent of BMI. Twenty-two obese and 17 normal-weight participants completed eating- and reward-related questionnaires and underwent PET scans using the D2R-selective and nondisplaceable radioligand (N-[(11)C]methyl)benperidol. Questionnaires were grouped by domain (eating related to emotion, eating related to reward, non-eating behavior motivated by reward or sensitivity to punishment). Normalized, summed scores for each domain were compared between obese and normal-weight groups and correlated with striatal and midbrain D2R binding. Compared to normal-weight individuals, the obese group self-reported higher rates of eating related to both emotion and reward (p < 0.001), greater sensitivity to punishment (p = 0.06), and lower non-food reward behavior (p < 0.01). Across normal-weight and obese participants, self-reported emotional eating and non-food reward behavior positively correlated with striatal (p < 0.05) and midbrain (p < 0.05) D2R binding, respectively. In conclusion, an emotional eating phenotype may reflect altered central D2R function better than other commonly used obesity-related measures such as BMI

More than smell - COVID-19 is associated with severe impairment of smell, taste, and chemesthesis

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, generally lacked quantitative measurements, were mostly restricted to data from single countries. Here, we report the development, implementation and initial results of a multi-lingual, international questionnaire to assess self-reported quantity and quality of perception in three 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, 8 other, ages 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+/- SD), 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 lack of perceived nasal obstruction suggest that SARS-CoV-2 infection may disrupt sensory-neural mechanisms.Additional co-authors: Veronica Pereda-Loth, Shannon B Olsson, Richard C Gerkin, Paloma Rohlfs Domínguez, Javier Albayay, Michael C. Farruggia, Surabhi Bhutani, Alexander W Fjaeldstad, Ritesh Kumar, Anna Menini, Moustafa Bensafi, Mari Sandell, Iordanis Konstantinidis, Antonella Di Pizio, Federica Genovese, Lina Öztürk, Thierry Thomas-Danguin, Johannes Frasnelli, Sanne Boesveldt, Özlem Saatci, Luis R. Saraiva, Cailu Lin, Jérôme Golebiowski, Liang-Dar Hwang, Mehmet Hakan Ozdener, Maria Dolors Guàrdia, Christophe Laudamiel, Marina Ritchie, Jan Havlícek, Denis Pierron, Eugeni Roura, Marta Navarro, Alissa A. Nolden, Juyun Lim, KL Whitcroft, Lauren R. Colquitt, Camille Ferdenzi, Evelyn V. Brindha, Aytug Altundag, Alberto Macchi, Alexia Nunez-Parra, Zara M. Patel, Sébastien Fiorucci, Carl M. Philpott, Barry C. Smith, Johan N Lundström, Carla Mucignat, Jane K. Parker, Mirjam van den Brink, Michael Schmuker, Florian Ph.S Fischmeister, Thomas Heinbockel, Vonnie D.C. Shields, Farhoud Faraji, Enrique Enrique Santamaría, William E.A. Fredborg, Gabriella Morini, Jonas K. Olofsson, Maryam Jalessi, Noam Karni, Anna D'Errico, Rafieh Alizadeh, Robert Pellegrino, Pablo Meyer, Caroline Huart, Ben Chen, Graciela M. Soler, Mohammed K. Alwashahi, Olagunju Abdulrahman, Antje Welge-Lüssen, Pamela Dalton, Jessica Freiherr, Carol H. Yan, Jasper H. B. de Groot, Vera V. Voznessenskaya, Hadar Klein, Jingguo Chen, Masako Okamoto, Elizabeth A. Sell, Preet Bano Singh, Julie Walsh-Messinger, Nicholas S. Archer, Sachiko Koyama, Vincent Deary, Hüseyin Yanik, Samet Albayrak, Lenka Martinec Novákov, Ilja Croijmans, Patricia Portillo Mazal, Shima T. Moein, Eitan Margulis, Coralie Mignot, Sajidxa Mariño, Dejan Georgiev, Pavan K. Kaushik, Bettina Malnic, Hong Wang, Shima Seyed-Allaei, Nur Yoluk, Sara Razzaghi, Jeb M. Justice, Diego Restrepo, Julien W Hsieh, Danielle R. Reed, Thomas Hummel, Steven D Munger, John E Haye

Dryad_CharacterizationData

The file contains imager characterization data, such as quantum efficiency, fixed pattern noise, concentration detection, filter optical density, filter transmission data

Bio-inspired imager improves sensitivity in near-infrared fluorescence image-guided surgery

Image-guided surgery can enhance cancer treatment by decreasing, and ideally eliminating, positive tumor margins and iatrogenic damage to healthy tissue. Current state-of-the-art near-infrared fluorescence imaging systems are bulky and costly, lack sensitivity under surgical illumination, and lack co-registration accuracy between multimodal images. As a result, an overwhelming majority of physicians still rely on their unaided eyes and palpation as the primary sensing modalities for distinguishing cancerous from healthy tissue. Here we introduce an innovative design, comprising an artificial multispectral sensor inspired by the Morpho butterfly's compound eye, which can significantly improve image-guided surgery. By monolithically integrating spectral tapetal filters with photodetectors, we have realized a single-chip multispectral imager with 1000 x higher sensitivity and 7 x better spatial co-registration accuracy compared to clinical imaging systems in current use. Preclinical and clinical data demonstrate that this technology seamlessly integrates into the surgical workflow while providing surgeons with real-time information on the location of cancerous tissue and sentinel lymph nodes. Due to its low manufacturing cost, our bio-inspired sensor will provide resource-limited hospitals with much-needed technology to enable more accurate value-based health care. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing AgreementAir Force Office of Scientific Research (AFOSR) [FA9550-12-1-0321]; National Institutes of Health (NIH) [NCI R01 CA171651]; National Science Foundation (NSF) [1724615, 1740737]Open access journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Recent Smell Loss Is the Best Predictor of COVID-19 Among Individuals With Recent Respiratory Symptoms

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.info:eu-repo/semantics/acceptedVersio

Corrigendum to: More Than Smell-COVID-19 Is Associated With Severe Impairment of Smell, Taste, and Chemesthesis.

This is a correction notice for article bjaa041 (DOI: https://doi.org/10.1093/chemse/bjaa041), published 20 June 2020. An incorrect version of the caption to Figure 5 was mistakenly included in the published paper. An updated version is given below. Neither the data nor the paper’s conclusions were affected by this correction. The authors sincerely apologize for the error

Corrigendum to::More Than Smell-COVID-19 Is Associated with Severe Impairment of Smell, Taste, and Chemesthesis (Chemical Senses (2020) DOI: 10.1093/chemse/bjaa041)

This is a correction notice for article bjaa041 (DOI: https:// doi.org/10.1093/chemse/bjaa041), published 20 June 2020. An incorrect version of the caption to Figure 5 was mistakenly included in the published paper. An updated version is given below. Neither the data nor the paper's conclusions were affected by this correction. The authors sincerely apologize for the error. (A) Correlations between the 3 principal components with respect to changes in 3 chemosensory modalities (i.e., taste, smell, and chemesthesis). Shades of gray indicate positive correlation, whereas shades of red indicate negative correlations. White denotes no correlation. (B) Clusters of participants identified by k-means clustering. The scatterplot shows each participant's loading on dimension 1 (degree of smell and taste loss, PC1 on x-Axis) and dimension 2 (degree of chemesthesis loss, PC2 on y-Axis). 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. Participants in cluster 2 (orange, N = 1724; bottom center) are generally characterized by ratings that reflect smell/taste loss with preserved chemesthesis. Loadings for participants in cluster 3 (green, N = 548; right side) are generally characterized by reduced smell and taste loss, and preserved chemesthesis