Sense of Smell: Structural, Functional, Mechanistic Advancements and Challenges in Human Olfactory Research

PredCoffee: A binary classification approach specifically for coffee odor

Compared to traditional methods, using machine learning to assess or predict the odor of molecules can save costs in various aspects. Our research aims to collect molecules with coffee odor and summarize the regularity of these molecules, ultimately creating a binary classifier that can determine whether a molecule has a coffee odor. In this study, a total of 371 coffee-odor molecules and 9,700 non-coffee-odor molecules were collected. The Knowledge-guided Pre-training of Graph Transformer (KPGT), support vector machine (SVM), random forest (RF), multi-layer perceptron (MLP), and message-passing neural networks (MPNN) were used to train the data. The model with the best performance was selected as the basis of the predictor. The prediction accuracy value of the KPGT model exceeded 0.84 and the predictor has been deployed as a webserver PredCoffee.

TASA: Temporal Attention With Spatial Autoencoder Network for Odor-Induced Emotion Classification Using EEG

The olfactory system enables humans to smell different odors, which are closely related to emotions. The high temporal resolution and non-invasiveness of Electroencephalogram (EEG) make it suitable to objectively study human preferences for odors. Effectively learning the temporal dynamics and spatial information from EEG is crucial for detecting odor-induced emotional valence. In this paper, we propose a deep learning architecture called Temporal Attention with Spatial Autoencoder Network (TASA) for predicting odor-induced emotions using EEG. TASA consists of a filter-bank layer, a spatial encoder, a time segmentation layer, a Long Short-Term Memory (LSTM) module, a multi-head self-attention (MSA) layer, and a fully connected layer. We improve upon the previous work by utilizing a two-phase learning framework, using the autoencoder module to learn the spatial information among electrodes by reconstructing the given input with a latent representation in the spatial dimension, which aims to minimize information loss compared to spatial filtering with CNN. The second improvement is inspired by the continuous nature of the olfactory process; we propose to use LSTM-MSA in TASA to capture its temporal dynamics by learning the intercorrelation among the time segments of the EEG. TASA is evaluated on an existing olfactory EEG dataset and compared with several existing deep learning architectures to demonstrate its effectiveness in predicting olfactory-triggered emotional responses. Interpretability analyses with DeepLIFT also suggest that TASA learns spatial-spectral features that are relevant to olfactory-induced emotion recognition.

A Consolidated Understanding of the Contribution of Redox Dysregulation in the Development of Hearing Impairment

The etiology of hearing impairment is multifactorial, with contributions from both genetic and environmental factors. Although genetic studies have yielded valuable insights into the development and function of the auditory system, the contribution of gene products and their interaction with alternate environmental factors for the maintenance and development of auditory function requires further elaboration. In this review, we provide an overview of the current knowledge on the role of redox dysregulation as the converging factor between genetic and environmental factor-dependent development of hearing loss, with a focus on understanding the interaction of oxidative stress with the physical components of the peripheral auditory system in auditory disfunction. The potential involvement of molecular factors linked to auditory function in driving redox imbalance is an important promoter of the development of hearing loss over time.

Pred-O3, a web server to predict molecules, olfactory receptors and odor relationships

The sense of smell is a biological process involving volatile molecules that interact with proteins called olfactory receptors to transmit a nervous message that allows the recognition of a perceived odor. However, the relationships between odorant molecules, olfactory receptors and odors (O3) are far from being well understood due to the combinatorial olfactory codes and large family of olfactory receptors. This is the reason why, based on 5802 odorant molecules and their annotations to 863 olfactory receptors (human) and 7029 odors and flavors annotations, a web server called Pred-O3 has been designed to provide insights into olfaction. Predictive models based on Artificial Intelligence have been developed allowing to suggest olfactory receptors and odors associated with a new molecule. In addition, based on the encoding of the odorant molecule's structure, physicochemical features related to odors and/or olfactory receptors are proposed. Finally, based on the structural models of the 98 olfactory receptors a systematic docking protocol can be applied and suggest if a molecule can bind or not to an olfactory receptor. Therefore, Pred-O3 is well suited to aid in the design of new odorant molecules and assist in fragrance research and sensory neuroscience. Pred-O3 is accessible at ' https://odor.rpbs.univ-paris-diderot.fr/'.

Transfer learning for a foundational chemistry model

Data-driven chemistry has garnered much interest concurrent with improvements in hardware and the development of new machine learning models. However, obtaining sufficiently large, accurate datasets of a desired chemical outcome for data-driven chemistry remains a challenge. The community has made significant efforts to democratize and curate available information for more facile machine learning applications, but the limiting factor is usually the laborious nature of generating large-scale data. Transfer learning has been noted in certain applications to alleviate some of the data burden, but this protocol is typically carried out on a case-by-case basis, with the transfer learning task expertly chosen to fit the finetuning. Herein, I develop a machine learning framework capable of accurate chemistry-relevant prediction amid general sources of low data. First, a chemical "foundational model" is trained using a dataset of ∼1 million experimental organic crystal structures. A task specific module is then stacked atop this foundational model and subjected to finetuning. This approach achieves state-of-the-art performance on a diverse set of tasks: toxicity prediction, yield prediction, and odor prediction.

Olfactory Dysfunction in Adults from Rio Grande do Norte: A Cross-Sectional Study

Introduction  Smell is one of the senses of the human body, and it can be affected by several factors, such as viral infections, traumatic brain injury, iatrogenesis, smoking, and neurodegenerative and systemic diseases. Objectives  The main goal of the present study is to describe the epidemiology of olfactory disorders in Rio Grande do Norte (RN). More specifically, to determine the prevalence of olfactory dysfunction and to identify the main risk factors related to these dysfunctions in the state's population. Methods  A total of 180 volunteers living in the RN underwent the Connecticut Clinical Research Center (CCCRC) smell test and a clinical and demographic questionnaire. Results  A total of 58.89% of the patients presented normosmia and 87.78% were classified as having between normal and mild hyposmia. A statistically significant relationship was found between worse performance in the test and nasal surgery ( p  = 0.041) and the subjective feeling of not having an accurate sense of smell ( p  = 0.006 on the right nostril). There was no statistical relationship between the olfactory status and the report of coronavirus disease 2019 (COVID-19) infection ( p  = 0.254). Conclusion  The occurrence of altered sense of smell in our study was different from that reported in other studies that used the same test. The relationship with COVID-19 was not clear.

Olfactory dysfunction and its related molecular mechanisms in Parkinson's disease

Changes in olfactory function are considered to be early biomarkers of Parkinson's disease. Olfactory dysfunction is one of the earliest non-motor features of Parkinson's disease, appearing in about 90% of patients with early-stage Parkinson's disease, and can often predate the diagnosis by years. Therefore, olfactory dysfunction should be considered a reliable marker of the disease. However, the mechanisms responsible for olfactory dysfunction are currently unknown. In this article, we clearly explain the pathology and medical definition of olfactory function as a biomarker for early-stage Parkinson's disease. On the basis of the findings of clinical olfactory function tests and animal model experiments as well as neurotransmitter expression levels, we further characterize the relationship between olfactory dysfunction and neurodegenerative diseases as well as the molecular mechanisms underlying olfactory dysfunction in the pathology of early-stage Parkinson's disease. The findings highlighted in this review suggest that olfactory dysfunction is an important biomarker for preclinical-stage Parkinson's disease. Therefore, therapeutic drugs targeting non-motor symptoms such as olfactory dysfunction in the early stage of Parkinson's disease may prevent or delay dopaminergic neurodegeneration and reduce motor symptoms, highlighting the potential of identifying effective targets for treating Parkinson's disease by inhibiting the deterioration of olfactory dysfunction.

The coming future: The role of the oral-microbiota-brain axis in aroma release and perception

The field of aroma release and perception during the oral process has been well studied. However, the traditional approaches have not fully explored the integration of oral biology, microbiology, and neurology to further understand aroma release and perception mechanisms. Herein, to address the existing challenges in this field, we introduce the oral-microbiota-brain axis (OMBA), an innovative framework that encapsulates the interactive relationships among saliva and the oral mucosa, the oral microbiota, and the brain in aroma release and perception. This review introduces the OMBA and highlights its role as a key interface facilitating the sensory experience of aroma. Based on a comprehensive literature survey, the specific roles of the oral mucosa, oral microbiota, saliva, and brain in the OMBA are discussed. This integrated approach reveals the importance of each component and the interconnected relationships within this axis in the overall process of aroma release and perception. Saliva and the oral mucosa play fundamental roles in aroma release and perception; the oral microbiota regulates aroma release and impacts olfactory perception; and the brain's intricate neural circuitry is central to the decoding and interpretation of aroma signals. The components of this axis are interdependent, and imbalances can disrupt aroma perception. The OMBA framework not only enhances our comprehension of aroma release and perception but also paves the way for innovative applications that could heighten sensory experiences.

Sensory Nutrition and Bitterness and Astringency of Polyphenols

Recent studies have demonstrated that the interaction of dietary constituents with taste and olfactory receptors and nociceptors expressed in the oral cavity, nasal cavity and gastrointestinal tract regulate homeostasis through activation of the neuroendocrine system. Polyphenols, of which 8000 have been identified to date, represent the greatest diversity of secondary metabolites in plants, most of which are bitter and some of them astringent. Epidemiological studies have shown that polyphenol intake contributes to maintaining and improving cardiovascular, cognitive and sensory health. However, because polyphenols have very low bioavailability, the mechanisms of their beneficial effects are unknown. In this review, we focused on the taste of polyphenols from the perspective of sensory nutrition, summarized the results of previous studies on their relationship with bioregulation and discussed their future potential.

Uncovering Evolutionary Adaptations in Common Warthogs through Genomic Analyses

In the Suidae family, warthogs show significant survival adaptability and trait specificity. This study offers a comparative genomic analysis between the warthog and other Suidae species, including the Luchuan pig, Duroc pig, and Red River hog. By integrating the four genomes with sequences from the other four species, we identified 8868 single-copy orthologous genes. Based on 8868 orthologous protein sequences, phylogenetic assessments highlighted divergence timelines and unique evolutionary branches within suid species. Warthogs exist on different evolutionary branches compared to DRCs and LCs, with a divergence time preceding that of DRC and LC. Contraction and expansion analyses of warthog gene families have been conducted to elucidate the mechanisms of their evolutionary adaptations. Using GO, KEGG, and MGI databases, warthogs showed a preference for expansion in sensory genes and contraction in metabolic genes, underscoring phenotypic diversity and adaptive evolution direction. Associating genes with the QTLdb-pigSS11 database revealed links between gene families and immunity traits. The overlap of olfactory genes in immune-related QTL regions highlighted their importance in evolutionary adaptations. This work highlights the unique evolutionary strategies and adaptive mechanisms of warthogs, guiding future research into the distinct adaptability and disease resistance in pigs, particularly focusing on traits such as resistance to African Swine Fever Virus.

Tumor Microbial Communities and Thyroid Cancer Development-The Protective Role of Antioxidant Nutrients: Application Strategies and Future Directions

Thyroid cancer (TC), the most frequent malignancy of the endocrine system, has recorded an increasing incidence in the last decades. The etiology of TC remains at least partly unknown and, among modifiable risk factors, the gut microbiota and dietary nutrients (vitamins, essential microelements, polyphenols, probiotics) have been recognized to not only influence thyroid function, but exert critical effects on TC development and progression. Recent discoveries on the existence of tumor microbiota also in the TC microenvironment provide further evidence for the essential role of tumor microorganisms in TC etiology and severity, as well as acting as prognostic markers and as a potential target of adjuvant care in the treatment of TC patients. Therefore, in this review, we summarize current knowledge on the relationship of the tumor microbiome with the clinical tumor characteristics and TC progression, also illustrating the molecular mechanisms underlying this association, and how antioxidant nutrients may be used as a novel strategy to both control gut health and reduce the risk for TC. Furthermore, we discuss how new technologies might be exploited for the development of new foods with high nutritional values, antioxidant capability, and even attractiveness to the individual in terms of sensory and emotional features.

Developing human olfactory network and exploring olfactory receptor-odorant interaction

The Olfactory receptor (OR)-odorant interactions are perplexed. ORs can bind to structurally diverse odorants associated with one or more odor percepts. Various attempts have been made to understand the intricacies of OR-odorant interaction. In this study, experimentally documented OR-odorant interactions are investigated comprehensively to; (a) suggest potential odor percepts for ORs based on the OR-OR network; (b) determine how odorants interacting with specific ORs differ in terms of inherent pharmacophoric features and molecular properties, (c) identify molecular interactions that explained OR-odorant interactions of selective ORs; and (d) predict the probable role of ORs other than olfaction. Human olfactory receptor network (hORnet) is developed to study possible odor percepts for ORs. We identified six molecular properties which showed variation and significant patterns to differentiate odorants binding with five ORs. The pharmacophore analysis revealed that odorants subset of five ORs follow similar pharmacophore hypothesis, (one hydrogen acceptor and two hydrophobic regions) but differ in terms of distance and orientation of pharmacophoric features. To ascertain the binding site residues and key interactions between the selected ORs and their interacting odorants, 3D-structure modelling, docking and molecular dynamics studies were carried out. Lastly, the potential role of ORs beyond olfaction is explored. A human OR-OR network was developed to suggest possible odor percepts for ORs using empirically proven OR-odorant interactions. We sought to find out significant characteristics, molecular properties, and molecular interactions that could explain OR-odorant interactions and add to the understanding of the complex issue of odor perception.Communicated by Ramaswamy H. Sarma.

XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm

Determining the structure-odor relationship has always been a very challenging task. The main challenge in investigating the correlation between the molecular structure and its associated odor is the ambiguous and obscure nature of verbally defined odor descriptors, particularly when the odorant molecules are from different sources. With the recent developments in machine learning (ML) technology, ML and data analytic techniques are significantly being used for quantitative structure-activity relationship (QSAR) in the chemistry domain toward knowledge discovery where the traditional Edisonian methods have not been useful. The smell perception of odorant molecules is one of the aforementioned tasks, as olfaction is one of the least understood senses as compared to other senses. In this study, the XGBoost odor prediction model was generated to classify smells of odorant molecules from their SMILES strings. We first collected the dataset of 1278 odorant molecules with seven basic odor descriptors, and then 1875 physicochemical properties of odorant molecules were calculated. To obtain relevant physicochemical features, a feature reduction algorithm called PCA was also employed. The ML model developed in this study was able to predict all seven basic smells with high precision (>99%) and high sensitivity (>99%) when tested on an independent test dataset. The results of the proposed study were also compared with three recently conducted studies. The results indicate that the XGBoost-PCA model performed better than the other models for predicting common odor descriptors. The methodology and ML model developed in this study may be helpful in understanding the structure-odor relationship.Communicated by Ramaswamy H. Sarma.

Future therapeutic strategies for olfactory disorders: electrical stimulation, stem cell therapy, and transplantation of olfactory epithelium-an overview

Olfactory disorders may be temporary or permanent and can have various causes. Currently, many COVID-19 patients report a reduced or complete loss of olfactory function. A wide range of treatment options have been investigated in the past, such as olfactory training, acupuncture, medical therapy, transcranial magnetic stimulation, or surgical excision of olfactory epithelium, e.g., in severe qualitative smell disorders. The development of a bioelectric nose, e.g., in connection with direct electrical stimulation or transplantation of olfactory epithelium or stem cells, represent treatment options of the future. The basis of these developments and the state of knowledge is discussed in the following work.

Olfactory Dysfunction following COVID-19 and the Potential Benefits of Olfactory Training

COVID-19 is associated with a common symptom of olfactory dysfunction, which may persist even after the infection is resolved. Olfactory training (OT) has emerged as the most effective intervention for post-viral olfactory dysfunction. OT involves daily exposure of the olfactory system to various odors. The current study aims to explore olfactory dysfunction following COVID-19 and the potential benefits of olfactory training.

METHODS

This is a cross-sectional study conducted among adults aged 18-60 living in Alahssa, Saudi Arabia. An online questionnaire containing an informed consent form and a survey to collect demographic data, vaccination status, level of loss of smell and taste, and the level of awareness about olfactory training (OT) was distributed among all participants who agreed to participate in this study.

RESULTS

The study included 524 participants and presented their baseline characteristics, including age, gender, COVID-19 infection status, and complaints. Most patients were female (66.0%), and 46.2% had previously been infected with COVID-19. About 54.8% of participants reported chemosensory dysfunction, while 286 had olfactory dysfunction. Of those, 29.8% had anosmia, 16.8% had hyposmia, and 8.0% had parosmia. Results suggest that being fully or partially vaccinated may offer some protection against olfactory dysfunction compared to being unvaccinated. Adherence to olfactory training was associated with improvement in the sense of smell.

CONCLUSIONS

The study highlights the importance of awareness and adherence to olfactory training, which may improve the sense of smell in individuals with chemosensory dysfunction. The findings of this study can inform public health policies and interventions aimed at reducing the burden of olfactory dysfunction associated with COVID-19 vaccination.

Reduction of Odor-causing Compounds in Wastewater using Biochar: A Review

Wastewater contains chemical compounds that cause malodors, such as ammonium cation, dimethyl sulfide, and volatile organic compounds. Biochar-based reduction in the odorants has been proposed as an effective approach along with maintaining environmental neutrality as biochar is a sustainable material made from biomass and biowaste. Biochar can have high specific surface area and microporous structure with proper activation, appropriate for sorption purposes. Recently, various research directions have been proposed to determine the removal efficiency of biochar for different odorants contained in wastewater. This article is aimed at providing the most updated review of biochar-based removal of odor-causing compounds in wastewater while highlighting the current advances. It was distinguished that the odorant removal performance of biochar is highly associated with the raw material and modification method of biochar, and the kind of odorants. Further research should be required for more practical use of biochar for the reduction of odorants in wastewater.

Smelling the Disease: Diagnostic Potential of Breath Analysis

Breath analysis is a relatively recent field of research with much promise in scientific and clinical studies. Breath contains endogenously produced volatile organic components (VOCs) resulting from metabolites of ingested precursors, gut and air-passage bacteria, environmental contacts, etc. Numerous recent studies have suggested changes in breath composition during the course of many diseases, and breath analysis may lead to the diagnosis of such diseases. Therefore, it is important to identify the disease-specific variations in the concentration of breath to diagnose the diseases. In this review, we explore methods that are used to detect VOCs in laboratory settings, VOC constituents in exhaled air and other body fluids (e.g., sweat, saliva, skin, urine, blood, fecal matter, vaginal secretions, etc.), VOC identification in various diseases, and recently developed electronic (E)-nose-based sensors to detect VOCs. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible, and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. However, the success of VOC-based identification of diseases is limited to laboratory settings. Large-scale clinical data are warranted for establishing the robustness of disease diagnosis. Also, to identify specific VOCs associated with illness states, extensive clinical trials must be performed using both analytical instruments and electronic noses equipped with stable and precise sensors.

[The alleged mechanisms of olfactory disorders in the new coronavirus infection]

In March 2020, the World Health Organization (WHO) announced the beginning of the COVID-19 pandemic, which continues to the present. A change in the sense of smell, up to the complete disappearance of odors, is regarded as one of the early symptoms of the disease. Sometimes anosmia was the only sign of infection of the patient. As is known, a disturbance of the sense of smell indicates a serious pathology of the brain, such as the consequences of traumatic brain injuries, strokes, Alzheimer's disease, Parkinson's disease, autoimmune diseases, a side-effect of drug therapy. The review is dedicated to the pathogenesis of anosmia in COVID-19. For a better understanding of the pathogenesis, the article presents a brief anatomy and physiology of the olfactory organ as well as the probable mechanisms of anosmia: encephalitis, inflammatory edema of the olfactory cleft, olfactory epithelium damage, apoptosis of bipolar neurons, damage of olfactory cell cilia and damage of olfactory bulbs. Because of the rapid accumulation of information on this topic, there is a need to structure, periodic systematization and presentation to a wide range of specialists.

The Luminescence Hypothesis of Olfaction

A new hypothesis for the mechanism of olfaction is presented. It begins with an odorant molecule binding to an olfactory receptor. This is followed by the quantum biology event of inelastic electron tunneling as has been suggested with both the vibration and swipe card theories. It is novel in that it is not concerned with the possible effects of the tunneled electrons as has been discussed with the previous theories. Instead, the high energy state of the odorant molecule in the receptor following inelastic electron tunneling is considered. The hypothesis is that, as the high energy state decays, there is fluorescence luminescence with radiative emission of multiple photons. These photons pass through the supporting sustentacular cells and activate a set of olfactory neurons in near-simultaneous timing, which provides the temporal basis for the brain to interpret the required complex combinatorial coding as an odor. The Luminescence Hypothesis of Olfaction is the first to present the necessity of or mechanism for a 1:3 correspondence of odorant molecule to olfactory nerve activations. The mechanism provides for a consistent and reproducible time-based activation of sets of olfactory nerves correlated to an odor. The hypothesis has a biological precedent: an energy feasibility assessment is included, explaining the anosmia seen with COVID-19, and can be confirmed with existing laboratory techniques.

Advances in the Production of Olfactory Receptors for Industrial Use

In biological olfactory systems, olfactory receptors (ORs) can recognize and discriminate between thousands of volatile organic compounds with very high sensitivity and specificity. The superior properties of ORs have led to the development of OR-based biosensors that have shown promising potential in many applications over the past two decades. In particular, newly designed technologies in gene synthesis, protein expression, solubilization, purification, and membrane mimetics for membrane proteins have greatly opened up the previously inaccessible industrial potential of ORs. In this review, gene design, expression and solubilization strategies, and purification and reconstitution methods available for modern industrial applications are examined, with a focus on ORs. The limitations of current OR production technology are also estimated, and future directions for further progress are suggested.

Lectin histochemistry of the olfactory mucosa of Korean native cattle, Bos taurus coreanae

BACKGROUND

The olfactory mucosa (OM) is crucial for odorant perception in the main olfactory system. The terminal carbohydrates of glycoconjugates influence chemoreception in the olfactory epithelium (OE).

OBJECTIVES

The histological characteristics and glycoconjugate composition of the OM of Korean native cattle (Hanwoo, Bos taurus coreae) were examined to characterize their morphology and possible functions during postnatal development.

METHODS

The OM of neonate and adult Korean native cattle was evaluated using histological, immunohistochemical, and lectin histochemical methods.

RESULTS

Histologically, the OM in both neonates and adults consists of the olfactory epithelium and the lamina propria. Additionally, using periodic acid Schiff and Alcian blue (pH 2.5), the mucus specificity of the Bowman's gland duct and acini in the lamina propria was determined. Immunohistochemistry demonstrated that mature and immature olfactory sensory neurons of OEs express the olfactory marker protein and growth associated protein-43, respectively. Lectin histochemistry indicated that numerous glycoconjugates, including as N-acetylglucosamine, mannose, galactose, N-acetylgalactosamine, complex type N-glycan, and fucose groups, were expressed at varied levels in the different cell types in the OMs of neonates and adults at varying levels. According to our observations, the cattle possessed a well-developed olfactory system, and the expression patterns of glycoconjugates in neonatal and adult OMs varied considerably.

CONCLUSIONS

This is the first study to describe the morphological assessment of the OM of Korean native cattle with a focus on lectin histochemistry. The findings suggest that glycoconjugates may play a role in olfactory chemoreception, and that their labeling properties may be closely related to OM development and maturity.

Odour hedonics and the ubiquitous appeal of vanilla

Our food choices and consumption behaviours are often influenced by odour hedonics, especially in the case of those orthonasally experienced aromas (that is, those odours that are food-related). The origins of odour hedonics remain one of the most intriguing puzzles in olfactory science and, over the years, several fundamentally different accounts have been put forwards to try and explain the varying hedonic responses that people have to a wide range of odorants. Associative learning, innate and molecular accounts of odour pleasantness have all been suggested. Here the origins of the hedonic response to vanilla, which is one of the most liked smells cross-culturally, are explored. The history of vanilla's use in food and medicine is outlined, with a focus on its neurocognitive appeal. While vanilla is one of the most widely liked aromas, it is also rated as smelling sweet to most people. Food scientists are becoming increasingly interested in the possibility that such 'sweet smells' could be used to help maintain the sweetness of commercial food products while, at the same time, reducing the use of calorific sweeteners. Such an approach is likely to be facilitated by the low cost of artificial vanilla flavouring (when compared with the high and fluctuating price of natural vanilla pods).

The effect of intra-nasal tetra sodium pyrophosphate on decreasing elevated nasal calcium and improving olfactory function post COVID-19: a randomized controlled trial

Background

Olfactory dysfunction is recognized as a symptom of COVID-19. Reports revealed the nasal calcium increase has adverse effects on olfactory function. Tetra sodium pyrophosphate, a chelating agent, can bind calcium and help improve olfaction.

Methods

Sixty-four patients with olfactory dysfunction persisting for more than 90 days after COVID-19 were recruited. Participants were divided into 2 groups that received either 0.9% sodium chloride or 1% tetra sodium pyrophosphate for topical application. Olfactory function was tested with the Sniffin' Sticks test before treatment and 1 month later. In addition, nasal calcium was determined with an ion-selective electrode.

Results

After topical application of tetra sodium pyrophosphate compared to sodium chloride, improvement from anosmia to hyposmia with decrease in calcium level was demonstrated. As for the results of tetra-sodium pyrophosphate, 81% showed improved olfactory function and 19% did not exhibit olfaction improvement.

Conclusions

Intranasal application of tetra sodium pyrophosphate may be associated with improvement in olfactory function after COVID -19 infection.

Trial registration Ethical Committee of Damietta Faculty of Medicine approved this study on January 2021 (approval number, IRB 00012367-21-03-010).

Chemosensory loss in COVID ‐19

The COVID‐19 pandemic caused by SARS‐CoV‐2 virus quickly spread globally, infecting over half a billion individuals, and killing over 6 million*. One of the more unusual symptoms was patients' complaints of sudden loss of smell and/or taste, a symptom that has become more apparent as the virus mutated into different variants. Anosmia and ageusia, the loss of smell and taste, respectively, seem to be transient for some individuals, but for others persists even after recovery from the infection. Causes for COVID‐19‐associated chemosensory loss have undergone several hypotheses. These include non‐functional or destroyed olfactory neurons and gustatory receptors or of their supporting cells, disruption of the signaling protein Neuropilin‐1, and disruption in the interaction with semaphorins, key molecules in the gustatory and olfactory axon guidance. The current paper will review these hypotheses and chart out potential therapeutic avenues.

Aromatherapy with inhalation can effectively improve the anxiety and depression of cancer patients: A meta-analysis

PURPOSE

This meta-analysis was to critically evaluate the effects of aromatherapy on the symptoms of anxiety and depression in cancer patients.

METHODS

Eight Chinese and English databases (CNKI, Wanfang, VIP, CBM, Cochrane Library, PubMed, Embase, and PsycINFO) were systematically searched from the inception of databases to October 2021 for randomized controlled trials (RCTs). According to Cochrane Collaboration criteria, two reviewers independently assessed the risk of bias and extract data from included studies. All analyses were performed with Review Manager 5.4.

RESULTS

Eleven qualified studies were included in the meta-analysis, ten of which reported the effect of aromatherapy on anxiety in cancer patients, including 1724 patients; five of the studies reported the effect on depression, including 1039 patients. The quality of the included studies was low, and most studies compared aromatherapy to usual care. This meta-analysis indicated that aromatherapy appeared to be effective for anxiety [SMD = -0.51, 95%CI (-0.83, -0.19), P = 0.002] and depression [SMD = -0.44, 95%CI (-0.76, -0.12), P = 0.008] symptoms in cancer patients. Inhalation aromatherapy may be more effective than massage. Aromatherapy seemed to improve the anxiety symptoms in cancer patients in a short time, especially in perioperative patients, but had no effect for patients treated with radiation, chemotherapy or palliative therapy. Placebo also appeared to be effective in some studies.

CONCLUSIONS

Aromatherapy, especially inhalation aromatherapy, may help relieve symptoms of anxiety and depression in cancer patients, but more and higher-quality studies are needed. The literature does not yet support clinical implementation.

DeepOlf: Deep Neural Network Based Architecture for Predicting Odorants and Their Interacting Olfactory Receptors

Olfaction transduction mechanism is triggered by the binding of odorants to the specific olfactory receptors (OR's) present in the nasal cavity. Different odorants stimulate different OR's due to the difference in shape, physical and chemical properties. In this paper, a deep neural network architecture DeepOlf, based on molecular features and fingerprints of odorants and ORs, to predict whether a chemical compound is a potential odorant or not along with its interacting OR is proposed. Odorant identification and Odorant-OR interaction were modeled as a binary classification through multiple classifiers. The evaluation of these classifier's performance showed that the deep-neural network framework not only fits data with better accuracy in comparison to other classical methods (SVM, RF, k-NN) but also able to predict odorant-OR interactions more accurately. To our knowledge, this study is the first realization of deep learning ideas for the problem of odorant and interacting OR prediction. The accuracy of DeepOlf was found to be 94.83 and 99.92 percent for the prediction of odorants and Odorant- OR interactions respectively. Comparison of DeepOlf prediction with the existing SVM based prediction server, ODORactor, showed that better performance can be achieved with the proposed deep learning approach. The DeepOlf tool can be accessed at https://bioserver.iiita.ac.in/deepolf/.

Understanding responses to chemical mixtures: looking forward from the past

Our goal in this article is to provide a perspective on how to understand the nature of responses to chemical mixtures. In studying responses to mixtures, researchers often identify "mixture interactions"-responses to mixtures that are not accurately predicted from the responses to the mixture's individual components. Critical in these studies is how to predict responses to mixtures and thus to identify a mixture interaction. We explore this issue with a focus on olfaction and on the first level of neural processing-olfactory sensory neurons-although we use examples from taste systems as well and we consider responses beyond sensory neurons, including behavior and psychophysics. We provide a broadly comparative perspective that includes examples from vertebrates and invertebrates, from genetic and nongenetic animal models, and from literature old and new. In the end, we attempt to recommend how to approach these problems, including possible future research directions.

OlfactionBase: a repository to explore odors, odorants, olfactory receptors and odorant-receptor interactions

Olfaction is a multi-stage process that initiates with the odorants entering the nose and terminates with the brain recognizing the odor associated with the odorant. In a very intricate way, the process incorporates various components functioning together and in synchronization. OlfactionBase is a free, open-access web server that aims to bring together knowledge about many aspects of the olfaction mechanism in one place. OlfactionBase contains detailed information of components like odors, odorants, and odorless compounds with physicochemical and ADMET properties, olfactory receptors (ORs), odorant- and pheromone binding proteins, OR-odorant interactions in Human and Mus musculus. The dynamic, user-friendly interface of the resource facilitates exploration of different entities: finding chemical compounds having desired odor, finding odorants associated with OR, associating chemical features with odor and OR, finding sequence information of ORs and related proteins. Finally, the data in OlfactionBase on odors, odorants, olfactory receptors, human and mouse OR-odorant pairs, and other associated proteins could aid in the inference and improved understanding of odor perception, which might provide new insights into the mechanism underlying olfaction. The OlfactionBase is available at https://bioserver.iiita.ac.in/olfactionbase/.

[Future therapeutic strategies for olfactory disorders: electrical stimulation, stem cell therapy, and transplantation of olfactory epithelium-an overview]

Passagere oder permanente Riechstörungen können verschiedene Ursachen haben. Ganz aktuell berichtet eine Vielzahl von Patienten im Rahmen von COVID-19-Infektionen über ein fehlendes oder vermindertes Riechvermögen. In der Vergangenheit wurden vielfältige Therapieoptionen untersucht, diese variieren vom Riechtraining über Akupunktur und medikamentöse Therapien bis hin zur transkraniellen Magnetstimulation oder, z. B. bei ausgeprägten qualitativen Riechstörungen, der chirurgischen Resektion der Riechschleimhaut. Die Entwicklung einer bioelektrischen Nase, z. B. in Verbindung mit direkter elektrischer Stimulation des Bulbus olfactorius, oder die Transplantation von Riechschleimhaut oder von Stammzellen stellen Behandlungsmöglichkeiten der Zukunft dar. Die Grundlagen für diese Entwicklungen sowie der Stand des Wissens werden in der vorliegenden Arbeit erläutert.

COVID-19 and Parkinson's disease: Defects in neurogenesis as the potential cause of olfactory system impairments and anosmia

Anosmia, a neuropathogenic condition of loss of smell, has been recognized as a key pathogenic hallmark of the current pandemic SARS-CoV-2 infection responsible for COVID-19. While the anosmia resulting from olfactory bulb (OB) pathology is the prominent clinical characteristic of Parkinson's disease (PD), SARS-CoV-2 infection has been predicted as a potential risk factor for developing Parkinsonism-related symptoms in a significant portion of COVID-19 patients and survivors. SARS-CoV-2 infection appears to alter the dopamine system and induce the loss of dopaminergic neurons that have been known to be the cause of PD. However, the underlying biological basis of anosmia and the potential link between COVID-19 and PD remains obscure. Ample experimental studies in rodents suggest that the occurrence of neural stem cell (NSC) mediated neurogenesis in the olfactory epithelium (OE) and OB is important for olfaction. Though the occurrence of neurogenesis in the human forebrain has been a subject of debate, considerable experimental evidence strongly supports the incidence of neurogenesis in the human OB in adulthood. To note, various viral infections and neuropathogenic conditions including PD with olfactory dysfunctions have been characterized by impaired neurogenesis in OB and OE. Therefore, this article describes and examines the recent reports on SARS-CoV-2 mediated OB dysfunctions and defects in the dopaminergic system responsible for PD. Further, the article emphasizes that COVID-19 and PD associated anosmia could result from the regenerative failure in the replenishment of the dopaminergic neurons in OB and olfactory sensory neurons in OE.

SMILES to Smell: Decoding the Structure-Odor Relationship of Chemical Compounds Using the Deep Neural Network Approach

Finding the relationship between the structure of an odorant molecule and its associated smell has always been an extremely challenging task. The major limitation in establishing the structure-odor relation is the vague and ambiguous nature of the descriptor-labeling, especially when the sources of odorant molecules are different. With the advent of deep networks, data-driven approaches have been substantiated to achieve more accurate linkages between the chemical structure and its smell. In this study, the deep neural network (DNN) with physiochemical properties and molecular fingerprints (PPMF) and the convolution neural network (CNN) with chemical-structure images (IMG) are developed to predict the smells of chemicals using their SMILES notations. A data set of 5185 chemical compounds with 104 smell percepts was used to develop the multilabel prediction models. The accuracies of smell prediction from DNN + PPMF and CNN + IMG (Xception based) were found to be 97.3 and 98.3%, respectively, when applied on an independent test set of chemicals. The deep learning architecture combining both DNN + PPMF and CNN + IMG prediction models is proposed, which classifies smells and may help understand the generic mechanism underlying the relationship between chemical structure and smell perception.

Sensory Perception of Non-Deuterated and Deuterated Organic Compounds

The chemical background of olfactory perception has been subject of intensive research, but no available model can fully explain the sense of smell. There are also inconsistent results on the role of the isotopology of molecules. In experiments with human subjects it was found that the isotope effect is weak with acetone and D6 -acetone. In contrast, clear differences were observed in the perception of octanoic acid and D15 -octanoic acid. Furthermore, a trained sniffer dog was initially able to distinguish between these isotopologues of octanoic acid. In chromatographic measurements, the respective deuterated molecule showed weaker interaction with a non-polar liquid phase. Quantum chemical calculations give evidence that deuterated octanoic acid binds more strongly to a model receptor than non-deuterated. In contrast, the binding of the non-deuterated molecule is stronger with acetone. The isotope effect is calculated in the framework of statistical mechanics. It results from a complicated interplay between various thermostatistical contributions to the non-covalent free binding energies and it turns out to be very molecule-specific. The vibrational terms including non-classical zero-point energies play about the same role as rotational/translational contributions and are larger than bond length effects for the differential isotope perception of odor for which general rules cannot be derived.

Altered Functional Connectivity Strength of Primary Visual Cortex in Subjects with Diabetic Retinopathy

OBJECTIVE

The purpose of the study was to find the differences in intrinsic functional connectivity (FC) patterns of the primary visual area (V1) among diabetic retinopathy (DR), diabetes mellitus (DM), and healthy controls (HCs) applying resting-state functional magnetic resonance imaging (rs-fMRI).

PATIENTS AND METHODS

Thirty-five subjects with DR (18 males and 17 females), 22 DM (10 males and 12 females) and 38 HCs (16 males and 22 females) matched for sex, age, and education underwent rs-fMRI scanning. Seed-based FC analysis was performed to find the alterations in the intrinsic FC patterns of V1 in DR compared with DM and HCs.

RESULTS

The study found that DR patients had a significant lower FC between the bilateral calcarine (CAL)/left lingual gyrus (LING) (BA 17/18) and the left V1, and between the bilateral CAL/left LING (BA 17/18) and the right V1 compared with the HCs. Meanwhile, patients with DR exhibited higher FC strength between the left V1 and the bilateral Caudate/Olfactory/Orbital superior frontal gyrus (OSFG), and between the bilateral Caudate/Olfactory/OSFG (BA 3/4/6) and the right V1. Compared with DM group, patients with DR showed increased FC strength between the right CAL (BA 17/18) and the right V1. DM group exhibited lower FC strength between the left fusiform and the left V1, and between the bilateral CAL and the right V1 when compared with HCs. Moreover, DM group was observed to have higher FC strength between the left superior frontal gyrus and the left V1.

CONCLUSION

Our findings indicated that DR patients exhibited FC disruptions between V1 and higher visual regions at rest, which may reflect the aberrant information communication in the V1 area of DR individuals. The findings offer important insights into the neuromechanism of vision disorder in DR patients.

Odor coding in the mammalian olfactory epithelium

Noses are extremely sophisticated chemical detectors allowing animals to use scents to interpret and navigate their environments. Odor detection starts with the activation of odorant receptors (ORs), expressed in mature olfactory sensory neurons (OSNs) populating the olfactory mucosa. Different odorants, or different concentrations of the same odorant, activate unique ensembles of ORs. This mechanism of combinatorial receptor coding provided a possible explanation as to why different odorants are perceived as having distinct odors. Aided by new technologies, several recent studies have found that antagonist interactions also play an important role in the formation of the combinatorial receptor code. These findings mark the start of a new era in the study of odorant-receptor interactions and add a new level of complexity to odor coding in mammals.