An olfactory self-test effectively screens for COVID-19

International audienceAbstract Background Key to curtailing the COVID-19 pandemic are wide-scale screening strategies. An ideal screen is one that would not rely on transporting, distributing, and collecting physical specimens. Given the olfactory impairment associated with COVID-19, we developed a perceptual measure of olfaction that relies on smelling household odorants and rating them online. Methods Each participant was instructed to select 5 household items, and rate their perceived odor pleasantness and intensity using an online visual analogue scale. We used this data to assign an olfactory perceptual fingerprint, a value that reflects the perceived difference between odorants. We tested the performance of this real-time tool in a total of 13,484 participants (462 COVID-19 positive) from 134 countries who provided 178,820 perceptual ratings of 60 different household odorants. Results We observe that olfactory ratings are indicative of COVID-19 status in a country, significantly correlating with national infection rates over time. More importantly, we observe indicative power at the individual level (79% sensitivity and 87% specificity). Critically, this olfactory screen remains effective in participants with COVID-19 but without symptoms, and in participants with symptoms but without COVID-19. Conclusions The current odorant-based olfactory screen adds a component to online symptom-checkers, to potentially provide an added first line of defense that can help fight disease progression at the population level. The data derived from this tool may allow better understanding of the link between COVID-19 and olfaction

An olfactory self-test effectively screens for COVID-19

BACKGROUND: Key to curtailing the COVID-19 pandemic are wide-scale screening strategies. An ideal screen is one that would not rely on transporting, distributing, and collecting physical specimens. Given the olfactory impairment associated with COVID-19, we developed a perceptual measure of olfaction that relies on smelling household odorants and rating them online. METHODS: Each participant was instructed to select 5 household items, and rate their perceived odor pleasantness and intensity using an online visual analogue scale. We used this data to assign an olfactory perceptual fingerprint, a value that reflects the perceived difference between odorants. We tested the performance of this real-time tool in a total of 13,484 participants (462 COVID-19 positive) from 134 countries who provided 178,820 perceptual ratings of 60 different household odorants. RESULTS: We observe that olfactory ratings are indicative of COVID-19 status in a country, significantly correlating with national infection rates over time. More importantly, we observe indicative power at the individual level (79% sensitivity and 87% specificity). Critically, this olfactory screen remains effective in participants with COVID-19 but without symptoms, and in participants with symptoms but without COVID-19. CONCLUSIONS: The current odorant-based olfactory screen adds a component to online symptom-checkers, to potentially provide an added first line of defense that can help fight disease progression at the population level. The data derived from this tool may allow better understanding of the link between COVID-19 and olfaction

Predicting the future is hard and other lessons from a population time series data science competition

Population forecasting, in which past dynamics are used to make predictions of future state, has many real-world applications. While time series of animal abundance are often modeled in ways that aim to capture the underlying biological processes involved, doing so is neither necessary nor sufficient for making good predictions. Here we report on a data science competition focused on modelling time series of Antarctic penguin abundance. We describe the best performing submitted models and compare them to a Bayesian model previously developed by domain experts and build an ensemble model that outperforms the individual component models in prediction accuracy. The top performing models varied tremendously in model complexity, ranging from very simple forward extrapolations of average growth rate to ensembles of models integrating recently developed machine learning techniques. Despite the short time frame for the competition, four of the submitted models outperformed the model previously created by the team of domain experts. We discuss the structure of the best performing models and components therein that might be useful for other ecological applications, the benefit of creating ensembles of models for ecological prediction, and the costs and benefits of including detailed domain expertise in ecological modelling. Additionally, we discuss the benefits of data science competitions, among which are increased visibility for challenging science questions, the generation of new techniques not yet adopted within the ecological community, and the ability to generate ensemble model forecasts that directly address model uncertainty

Novel DNA sequences at chromosome 10q26 are amplified in human gastric carcinoma cell lines: molecular cloning by competitive DNA reassociation.

Molecular cloning of genomic sequences altered in cancer cells is believed to lead to the identification of new genes involved in the initiation and progression of the malignant phenotype. DNA amplification is a frequent molecular alteration in tumor cells, and is a mode of proto-oncogene activation. The cytologic manifestation of this phenomenon is the appearance of chromosomal homogeneously staining regions (HSRs) or double minute bodies (DMs). The gastric carcinoma cell line KATO III is characterized by a large HSR on chromosome 11. In-gel renaturation analysis confirmed the amplification of DNA sequences in this cell line, yet none of 42 proto-oncogenes that we tested is amplified in KATO III DNA. We employed the phenol-enhanced reassociation technique (PERT) to isolate 21 random DNA fragments from the amplified domain, and used 6 of them to further clone some 150 kb from that genomic region. While in situ hybridization performed with some of these sequences indicated that in KATO III they are indeed amplified within the HSR on chromosome 11, somatic cell hybrid analysis and in situ hybridization to normal lymphocyte chromosomes showed that they are derived from chromosome 10, band q26. The same sequences were found to be amplified in another gastric carcinoma cell line, SNU-16, which contains DMs, but were not amplified in other 70 cell lines representing a wide variety of human neoplasms. One of these sequences was highly expressed in both KATO III and SNU-16. Thus, the cloned sequences supply a starting point for identification of novel genes which might be involved in the pathogenesis of gastric cancers, and are located in a relatively unexplored domain of the human genome

Olfactory sniffing signals consciousness in unresponsive patients with brain injuries.

After severe brain injury, it can be difficult to determine the state of consciousness of a patient, to determine whether the patient is unresponsive or perhaps minimally conscious1, and to predict whether they will recover. These diagnoses and prognoses are crucial, as they determine therapeutic strategies such as pain management, and can underlie end-of-life decisions2,3. Nevertheless, there is an error rate of up to 40% in determining the state of consciousness in patients with brain injuries4,5. Olfaction relies on brain structures that are involved in the basic mechanisms of arousal6, and we therefore hypothesized that it may serve as a biomarker for consciousness7. Here we use a non-verbal non-task-dependent measure known as the sniff response8-11 to determine consciousness in patients with brain injuries. By measuring odorant-dependent sniffing, we gain a sensitive measure of olfactory function10-15. We measured the sniff response repeatedly over time in patients with severe brain injuries and found that sniff responses significantly discriminated between unresponsive and minimally conscious states at the group level. Notably, at the single-patient level, if an unresponsive patient had a sniff response, this assured future regaining of consciousness. In addition, olfactory sniff responses were associated with long-term survival rates. These results highlight the importance of olfaction in human brain function, and provide an accessible tool that signals consciousness and recovery in patients with brain injuries

C. elegans and mutants with chronic nicotine exposure as a novel model of cancer phenotype

This article provides evidence in support of C. elegans as initial in vivo model to study nicotine and its effects on oncogenic mutations identified in humans