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An objective approach for odor detection is to analyze the brain activity using imaging techniques during the odor stimulation. In this study, Functional Near Infrared Spectroscopy (fNIRS) is used to record hemodynamic response from the frontal region of the brain by using a 4-channel fNIRS system. The fNIRs data is collected during the odor detection task in which the subjects were asked to press a button when they detect the given odor. Functional Data Analysis (FDA) was applied on fNIRs data to convert discrete measured samples of data to continuous smooth curves. The FDA method enables us to use the bases coefficients of fNIRS smoothed curves for features that represent the shape of the raw fNIRS signal. With the learning algorithm that we proposed, these features were used to train the support vector machine classifier. We evaluated the odor detection problem, in two binary classification cases: odorant vs. non-odorant and odorant vs. fingertapping. The model achieved a classification accuracy of 94.12% and 97.06% over the stimulus condition in the two cases, respectively. Moreover to find the actual predictors we used the extracted defined features (slope, standard deviation, and delta) to train our classifier. We achieved an average accuracy of 91.18 % on classifying odorant vs. non-odorant and an accuracy of 94.12% for odorant vs. fingertapping on the stimulus condition. The results determined that fNIRs signals of odorant and non-odorant are distinguishable without being affected by the motor activity during the experiment.These findings suggest that fNIRs measurement on the forehead could be potentially used for objective and comparably inexpensive assessment of odor detection in cases that the subjective report is unreliable.

Objective Liver biopsy is still needed for fibrosis staging in many patients with non-alcoholic fatty liver disease. The aims of this study were to evaluate the individual diagnostic performance of liver stiffness measurement by vibration controlled transient elastography (LSM-VCTE), Fibrosis-4 Index (FIB-4) and NAFLD (non-alcoholic fatty liver disease) Fibrosis Score (NFS) and to derive diagnostic strategies that could reduce the need for liver biopsies. Design Individual patient data meta-analysis of studies evaluating LSM-VCTE against liver histology was conducted. FIB-4 and NFS were computed where possible. Sensitivity, specificity and area under the receiver operating curve (AUROC) were calculated. Biomarkers were assessed individually and in sequential combinations. Results Data were included from 37 primary studies (n=5735; 45% women; median age: 54 years; median body mass index: 30 kg/m2; 33% had type 2 diabetes; 30% had advanced fibrosis). AUROCs of individual LSM-VCTE, FIB-4 and NFS for advanced fibrosis were 0.85, 0.76 and 0.73. Sequential combination of FIB-4 cut-offs (

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.

PICOLON (Pure Inorganic Crystal Observatory for LOw-energy Neutr(al)ino) aims to search for cosmic dark matter by high purity NaI(Tl) scintillator. We developed extremely pure NaI(Tl) crystal by hybrid purification method. The recent result of $^{210}$Pb in our NaI(Tl) is less than 5.7 $\mu$Bq/kg. We will report the test experiment in the low-background measurement at Kamioka Underground Laboratory. The sensitivity for annual modulating signals and finding dark matter particles will be discussed., Comment: To be published in the Proceedings of TAUP2021. (Journal of Physics: Conference Series (JPCS),)

BACKGROUND: Considerable evidence suggests that smell dysfunction is common in coronavirus disease-2019 (COVID-19). Unfortunately, extant data on prevalence and reversibility over time are highly variable, coming mainly from self-report surveys prone to multiple biases. Thus, validated psychophysical olfactory testing is sorely needed to establish such parameters. METHODS: One hundred severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-positive patients were administered the 40-item University of Pennsylvania Smell Identification Test (UPSIT) in the hospital near the end of the acute phase of the disease. Eighty-two were retested 1 or 4 weeks later at home. The data were analyzed using analysis of variance and mixed-effect regression models. RESULTS: Initial UPSIT scores were indicative of severe microsmia, with 96% exhibiting measurable dysfunction; 18% were anosmic. The scores improved upon retest (initial test: mean, 21.97; 95% confidence interval [CI], 20.84-23.09; retest: mean, 31.13; 95% CI, 30.16-32.10; p < 0.0001); no patient remained anosmic. After 5 weeks from COVID-19 symptom onset, the test scores of 63% of the retested patients were normal. However, the mean UPSIT score at that time continued to remain below that of age- and sex-matched healthy controls (p < 0.001). Such scores were related to time since symptom onset, sex, and age. CONCLUSION: Smell loss was extremely common in the acute phase of a cohort of 100 COVID-19 patients when objectively measured. About one third of cases continued to exhibit dysfunction 6 to 8 weeks after symptom onset. These findings have direct implications for the use of olfactory testing in identifying SARS-CoV-2 carriers and for counseling such individuals with regard to their smell dysfunction and its reversibility.

BACKGROUND: Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), is responsible for the largest pandemic since the 1918 influenza A virus subtype H1N1 influenza outbreak. The symptoms presently recognized by the World Health Organization are cough, fever, tiredness, and difficulty breathing. Patient-reported smell and taste loss has been associated with COVID-19 infection, yet no empirical olfactory testing on a cohort of COVID-19 patients has been performed. METHODS: The University of Pennsylvania Smell Identification Test (UPSIT), a well-validated 40-odorant test, was administered to 60 confirmed COVID-19 inpatients and 60 age- and sex-matched controls to assess the magnitude and frequency of their olfactory dysfunction. A mixed effects analysis of variance determined whether meaningful differences in test scores existed between the 2 groups and if the test scores were differentially influenced by sex. RESULTS: Fifty-nine (98%) of the 60 patients exhibited some smell dysfunction (mean [95% CI] UPSIT score: 20.98 [19.47, 22.48]; controls: 34.10 [33.31, 34.88]; p < 0.0001). Thirty-five of the 60 patients (58%) were either anosmic (15/60; 25%) or severely microsmic (20/60; 33%); 16 exhibited moderate microsmia (16/60; 27%), 8 mild microsmia (8/60; 13%), and 1 normosmia (1/60; 2%). Deficits were evident for all 40 UPSIT odorants. No meaningful relationships between the test scores and sex, disease severity, or comorbidities were found. CONCLUSION: Quantitative smell testing demonstrates that decreased smell function, but not always anosmia, is a major marker for SARS-CoV-2 infection and suggests the possibility that smell testing may help, in some cases, to identify COVID-19 patients in need of early treatment or quarantine.

Objective assessment of olfactory function has diagnostic and legal value. We have designed an odor detection task in which the subject reported the conscious sensing of an odorant via a button press while the hemodynamic activity from the forehead was monitored using a 4-channel fNIRS system. The task consisted of intermingled odor and non-odor trials. We recorded from 17 subjects and each of them underwent 60 trials. The time domain analysis of the raw data showed that the hemodynamic activity was statistically different between the odor and non-odor trials especially for oxyhemoglobin in far channels. In order to single out the odor-induced hemodynamic response from that of motor activity, finger tapping was considered as a control condition for odor detection. Pairwise correlation indicated that motor activity had a short lasting influence on hemodynamic response while the hemodynamic response to different odors were highly correlated over time. In conclusion, we believe that fNIRS monitoring of hemodynamic response could be potentially used for objective assessment of odor detection in cases that subjective report is unreliable.

COVID-19 has heterogeneous manifestations, though one of the most common symptoms is a sudden loss of smell (anosmia or hyposmia). We investigated whether olfactory loss is a reliable predictor of COVID-19. This preregistered, cross-sectional study used 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 singular and cumulative 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 single and cumulative feature models (ROC AUC=0.72), with additional features providing no significant model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms, such as fever or cough. Olfactory recovery within 40 days was reported for ~50% of participants and was best predicted by time since illness onset. As smell loss is the best predictor of COVID-19, we developed the ODoR-19 tool, a 0-10 scale to screen for recent olfactory loss. Numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (10