Age-related decreases in olfactory sensitivity are often accompanied by a decrease in the quality of life. However, the molecular mechanisms underlying these changes are not well described. Inhaled substances including odorants are detected by sensory neurons in the olfactory cleft covered with a layer of mucus. This olfactory mucus is the first molecular machinery responsible for tissue protection and for detection of environmental odorants. Yet, little is known about the molecular identities of the actors because of the lack of information on the mucus proteome and its age-related changes. Here, we sampled human mucus from different nasal locations and from young and elderly subjects. The composition of the mucus was extensively analyzed by shotgun proteomic analysis for a vast array of proteins. We also explored correlations between the levels of each mucus proteins with the olfactory sensitivity of subjects. This analysis revealed previously unrecognized proteins with potentially important functions in olfaction. Taken together, this report describes the most comprehensive catalogue of the nasal mucus proteins to date, their positional and age-related differences, and candidate proteins associated with olfaction. This catalogue will provide fundamental information useful for future studies, such as identification of olfactory auxiliary proteins, causes of age-related declines in olfaction, and biomarkers for neurodegenerative disorders.

Background Oral dryness is a common symptom that may interfere with swallowing, chewing, and taste. The most common reason for oral dryness is hyposalivation. Some individuals experiencing oral dryness do not have hyposalivation, however, and the reverse is also true. Here, we focused on healthy individuals with a lower salivary flow rate and evaluated the relationship between the perception of oral dryness and salivary parameters to clarify the cause underlying the perception of oral dryness. Methods A total of 59 participants were divided into 2 groups with a lower or higher salivary flow rate according to the median salivary flow rate. In participants with a lower salivary flow rate, we assessed salivary bacterial counts, protease activities, protein concentrations, oral parameters, and the subjective perception of oral dryness. Results Protease activities and concentrations of protease inhibitors such as cystatin-D and cystatin-SA in the saliva of participants experiencing oral dryness were significantly higher and lower, respectively, than in those not experiencing oral dryness, even though no difference in the salivary flow rate was detected. Salivary cystatin-D and cystatin-SA concentrations correlated negatively with salivary protease activities. Conclusions The composition of salivary protease inhibitors and increased protease activities affect the subjective perception of oral dryness.

Background As people have regularly worn facial masks due to the coronavirus disease 2019 (COVID‐19) pandemic, mask‐wear‐related adverse effects on the skin have been recognized. The aim of this study was to explore skin changes, their seasonal variations in the general population caused by commonly used masks and a possible mechanism underlying negative effects of mask‐wearing. Materials and methods Eighteen Japanese females participated in the study during summer and winter in Japan. Skin characteristics were measured in the non‐mask‐wearing preauricular area and the mask‐wearing cheek and perioral areas. Results Trans‐epidermal water loss (TEWL) on the cheek area tended to be increased in winter, which was positively correlated with skin scaliness on the same area. Ceramide (CER) content and composition in the mask‐covered stratum corneum (SC) were slightly changed between summer and winter, and CER [NP]/[NS] ratio was negatively correlated with the TEWL on the perioral skin in winter. Skin hydration and sebum secretion were higher on the cheek compared to the perioral area in summer. Skin redness was particularly high on the cheek in winter. Conclusion Mask‐wear‐related skin changes were season‐ and facial site‐specific, and alterations in SC CER may play a role in barrier‐related skin problems caused by mask use.

BACKGROUND Human health status can be measured in several different ways and statistical relationships among various measurements can be represented as a joint probability distribution. Approximation of the current health status of individuals will allow for more personalized and preventive healthcare by informing the potential risks and developing personalized interventions. Understanding the modifiable risk factors related to lifestyle, diet, and physical activity will facilitate the design of optimal treatment approaches for individuals. OBJECTIVE This study aims to provide a high-dimensional, cross-sectional dataset of comprehensive healthcare information to construct a virtual human generative model (VHGM) based on a joint probability distribution. METHODS In this cross-sectional observational study, data will be collected from a population of 1000 adult men and women (aged ≥20 years) matching the age ratio of the typical adult Japanese population. Data will include biochemical and metabolic profiles from blood, urine, saliva, and oral glucose tolerance tests; bacterial profiles from feces, facial skin, scalp skin, and saliva; mRNA, proteome, and metabolite analyses from facial and scalp skin surface lipids; lifestyle survey and questionnaire; physical, motor, cognitive, and vascular function analyses; alopecia; and comprehensive analyses of body odor components. Statistical analyses will examine multiple health-related items using a joint probability distribution model. We will train a joint probability distribution, the VHGM, by combining a commercially available healthcare dataset containing large amounts of relatively low-dimensional data with a high-dimensional, cross-sectional dataset. The trained VHGM is expected to enable various healthcare applications through application program interface calls. RESULTS Written informed consent will be required to participate in the study. The study has been approved by the Institutional Review Boards of the Kao Corporation (Approval # K0023-2108) and the Preferred Network, Inc. (Approval # ET22110047). CONCLUSIONS The collected data are expected to provide information on the relationships between various health statuses. Because different degrees of health status correlations are expected to have different effects on individual health status, this study will contribute to developing empirically justified interventions based on the population. CLINICALTRIAL The trial is registered with the University Hospital Medical Information Network (Registration No. UMIN000045746).

Multiple factors, including physical changes of the nasal mucosa and epithelium and exposure to air-borne environmental agents, appear to contribute to age-related olfactory loss. However, the molecular aspects of aging-associated olfactory loss in humans are not well understood.Although inflammation can be a significant underlying cause for olfactory impairment, whether aging increases the levels of inflammatory cytokines in the human olfactory mucosa and whether any inflammatory markers are associated with age-related olfactory loss remain unclear. Using a noninvasive method for collecting human olfactory mucus, we characterized and compared inflammatory cytokines, chemokines, and some growth factors, in the mucus collected from the olfactory cleft or the anterior nasal cavity from 12 healthy, young (18-40 years old) and 12 elderly (60-85 years old) individuals. We also hoped to identify candidate molecular biomarkers associated with age-associated olfactory loss in humans. Olfactory thresholds were obtained for two odorants and individual mucus samples were analyzed using multiplex assays for the levels of 30 cytokines. Results indicated elevated levels of certain inflammatory cytokines (IL-12, MCP-1) in olfactory mucus of the elderly, and high levels of some inflammatory factors (MCP-1, IL-8, IL-13 and VEGF) were associated with reduced olfactory sensitivity, suggesting that inflammation may play a role in olfactory decline associated with aging.