TongueSim: Development of an Automated Method for Rapid Assessment of Fungiform Papillae Density for Taste Research

Investigation of the fungiform papillae number in children with tooth number anomalies

OBJECTIVE

This cross-sectional study investigated the association between fungiform papillae (FP) numbers and tooth number anomalies in children, considering variables related to hypodontia and hyperdontia. The aim was to explore this association while adjusting for age and sex differences.

MATERIALS AND METHODS

A total of 144 children (aged 8-10) were categorized into hypodontia (n = 48), hyperdontia (n = 48), and control groups (n = 48). Clinical and radiographic diagnoses were used to classify tooth number anomalies. Hypodontia was categorized by number and location, while hyperdontia was categorized by number, shape, and location. FP were assessed using the Denver Papillae Protocol. Data analyses were performed using NCSS software, with p < 0.05 considered statistically significant.

RESULTS

The hypodontia group (22.5 ± 8.4) exhibited significantly lower FP than the control group (30.4 ± 9.2) and the hyperdontia group (27.9 ± 7.8) (p < 0.0005, p = 0.003, respectively). No significant difference existed between the hyperdontia and control groups. FP numbers in hypodontia subgroups showed no significant differences based on teeth agenesis numbers or locations. Similarly, hyperdontia subgroup analyses revealed no significant differences in FP numbers based on supernumerary teeth shapes (supplemental, conical, tuberculoid, paramolar) or the numbers of supernumerary teeth.

CONCLUSIONS

The lower FP numbers in children with hypodontia suggested an association between teeth and FP number. However, the non-significant difference in FP numbers with hyperdontia underscored the complexity of tooth development, warranting further investigations.

CLINICAL RELEVANCE

Children with hypodontia may exhibit distinct FP numbers compared to those without tooth number anomalies.

Machine learning and topological data analysis identify unique features of human papillae in 3D scans

The tongue surface houses a range of papillae that are integral to the mechanics and chemistry of taste and textural sensation. Although gustatory function of papillae is well investigated, the uniqueness of papillae within and across individuals remains elusive. Here, we present the first machine learning framework on 3D microscopic scans of human papillae ([Formula: see text]), uncovering the uniqueness of geometric and topological features of papillae. The finer differences in shapes of papillae are investigated computationally based on a number of features derived from discrete differential geometry and computational topology. Interpretable machine learning techniques show that persistent homology features of the papillae shape are the most effective in predicting the biological variables. Models trained on these features with small volumes of data samples predict the type of papillae with an accuracy of 85%. The papillae type classification models can map the spatial arrangement of filiform and fungiform papillae on a surface. Remarkably, the papillae are found to be distinctive across individuals and an individual can be identified with an accuracy of 48% among the 15 participants from a single papillae. Collectively, this is the first evidence demonstrating that tongue papillae can serve as a unique identifier, and inspires a new research direction for food preferences and oral diagnostics.

Umami taste evaluation based on a novel mouse taste receptor cell-based biosensor

Umami, a taste sensation known for its savory and delicious properties, has garnered considerable attention from both consumers and the food industry. However, current understanding and evaluation of umami characteristics remain limited, presenting a long-standing issue. To address this challenge, we have developed a self-assembled biosensor based on matured taste receptor cells (TRCs), obtained through isolation and culture of taste stem cells. TRCs, as the recognition element, were mounted onto the surface of a glassy carbon electrode (GCE) treated with gold nanoparticles (AuNPs) and poly-L-lysine (PLL). Key parameters including the cell incubation time and concentration were optimized to ensure the optimal performance of the TRCs-based biosensor. AuNPs were deposited onto the GCE surface via 90 s electrochemical reduction. TRCs concentration of 106 cells/mL and incubation time of 12 h were chosen by electrochemical characterization. Using this novel, rapid, and sensitive TRCs-based biosensor, we successfully detected L-monosodium glutamate (MSG) and other umami substances, demonstrating a good linear relationship within the range of 10-9 - 10-5 M between response signals and concentration of MSG stimuli. Our results provide insights into taste signal transduction mechanisms and suggest the potential for biomimetic sensors in intelligent perception applications.

Application of a salt substitute in bitter taste suppression and toward better acceptance of cruciferous vegetables in diet

The addition of table salt has been reported to enable better acceptance when consuming the least preferred vegetables belonging to the Cruciferae family. Considering the adverse effect of excessive table salt intake on incidence of hypertension and cardiovascular diseases, it is essential to explore an alternative healthier option for better acceptance and to encourage consumption of these vegetables. In this study, 261 adult participants were evaluated for their preferences toward basic tastes and food as well as sensory evaluation of a meal prepared from cruciferous vegetables with the addition of two different salts, sodium chloride and salt substitute containing a blend of potassium and sodium salts. A general questionnaire was used to assess taste and food preferences, while the Cruciferous Vegetable Food Frequency Questionnaire (CVFFQ) was used for vegetable intake assessment. The Labeled Magnitude Scale (LMS), Just About Right (JAR) scale, and several hedonic scales were used to determine taster status and sensory evaluation. The results show that a low concentration of the salt substitute did not impact bitterness suppression but did result in higher preference of the cruciferous vegetable meal. Although, subjects self-reported to have salty taste preferences were more sensitive to bitter taste, they did not perceive samples as less salty and less acceptable than subjects with lower sensitivity. The results show the necessity for further examination of the effectiveness of different concentrations of the assessed salt substitute in suppressing perceived bitterness of cruciferous vegetables and regarding their overall acceptance for inclusion in diets.

Comparison of manual and machine learning image processing approaches to determine fungiform papillae on the tongue

Human taste perception is associated with the papillae on the tongue as they contain a large proportion of chemoreceptors for basic tastes and other chemosensation. Especially the density of fungiform papillae (FP) is considered as an index for responsiveness to oral chemosensory stimuli. The standard procedure for FP counting involves visual identification and manual counting of specific parts of the tongue by trained operators. This is a tedious task and automated image analysis methods are desirable. In this paper a machine learning image processing method based on a convolutional neural network is presented. This automated method was compared with three standard manual FP counting procedures using tongue pictures from 132 subjects. Automated FP counts, within the selected areas and the whole tongue, significantly correlated with the manual counting methods (all ρs ≥ 0.76). When comparing the images for gender and PROP status, the density of FP predicted from automated analysis was in good agreement with data from the manual counting methods, especially in the case of gender. Moreover, the present results reinforce the idea that caution should be applied in considering the relationship between FP density and PROP responsiveness since this relationship can be an oversimplification of the complexity of phenomena arising at the central and peripherical levels. Indeed, no significant correlations were found between FP and PROP bitterness ratings using the automated method for selected areas or the whole tongue. Besides providing estimates of the number of FP, the machine learning approach used a tongue coordinate system that normalizes the size and shape of an individual tongue and generated a heat map of the FP position and normalized area they cover. The present study demonstrated that the machine learning approach could provide similar estimates of FP on the tongue as compared to manual counting methods and provide estimates of more difficult-to-measure parameters, such as the papillae's areas and shape.

Correlation of PTC Taste Status with Fungiform Papillae Count and Body Mass Index in Smokers and Non-Smokers of Eastern Province, Saudi Arabia

Phenylthiocarbamide (PTC) is a bitter compound that is similar in taste to the polyphenols present in most vegetables and fruits. The human taste response towards this compound influences dietary preference, which has a bearing on an individual's body mass index (BMI). Another factor that influences taste perception is fungiform papillae count. This, in turn, is governed by genetic factors or deleterious habits such as smoking. Establishing a link between all the above factors could lead to a wider understanding of obesity, which is a global health issue. PTC taste response, BMI, and fungiform papillae were recorded and statistically analyzed between two groups-smokers and nonsmokers. There was no statistically significant difference between smokers and nonsmokers with regard to PTC tasting ability. However, there was a significant inverse relationship between BMI and PTC tasting ability and fungiform papillae count both in smokers and nonsmokers. Thus, it can be inferred that as BMI increases, there is a lower likelihood of experiencing the bitter taste of PTC. Additionally, the ability to taste PTC decreases with diminishing numbers of fungiform papillae. Smoking does not affect bitter PTC tasting ability despite negatively affecting fungiform papillae count.

Taste Exam: A Brief and Validated Test

The emerging importance of taste in medicine and biomedical research, and new knowledge about its genetic underpinnings, has motivated us to supplement classic taste-testing methods in two ways. First, we explain how to do a brief assessment of the mouth, including the tongue, to ensure that taste papillae are present and to note evidence of relevant disease. Second, we draw on genetics to validate taste test data by comparing reports of perceived bitterness intensity and inborn receptor genotypes. Discordance between objective measures of genotype and subjective reports of taste experience can identify data collection errors, distracted subjects or those who have not understood or followed instructions. Our expectation is that fast and valid taste tests may persuade researchers and clinicians to assess taste regularly, making taste testing as common as testing for hearing and vision. Finally, because many tissues of the body express taste receptors, taste responses may provide a proxy for tissue sensitivity elsewhere in the body and, thereby, serve as a rapid, point-of-care test to guide diagnosis and a research tool to evaluate taste receptor protein function.

An automated method to detect and quantify fungiform papillae in the human tongue: Validation and relationship to phenotypical differences in taste perception

Determination of the number of fungiform papillae (FP) on the human tongue is an important measure that has frequently been associated with individual differences in oral perception, including taste sensitivity. At present, there is no standardised method consistently used to identify the number of FP, and primarily scientists manually count papillae over a small region(s) of the anterior tip of a stained tongue. In this study, a rapid automated method was developed to quantify the number of FP across the anterior 2 cm of an unstained tongue from high resolution digital images. In 60 participants, the automated method was validated against traditional manual counting, and then used to assess the relationship between the number of FP and taste phenotype (both 6-n-propylthiouracil (PROP) and Thermal Taster Status). FP count on the anterior 2 cm of the tongue was found to correlate significantly with PROP taster status. PROP supertasters (PSTs) had a significantly higher FP count compared with PROP non-tasters (PNTs). Conversely, the common approach used to determine the number of FP in a small 6 mm diameter circle on the anterior tongue tip, did not show a significant correlation irrespective of whether it was determined via automated or manual counting. The regional distribution of FP was assessed across PROP taster status groups. PSTs had a significantly higher FP count within the first centimetre of the anterior tongue compared with the PNT and PROP medium-tasters (PMT), with no significant difference in the second centimetre. No significant relationship was found with Thermal Taster Status and FP count, or interaction with PROP taster status groups, supporting previous evidence suggesting these phenomena are independent. The automated method is a valuable tool, enabling reliable quantification of FP over the anterior 2 cm surface of the tongue, and overcomes subjective discrepancies in manual counting.

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Automatic, rapid quantification of FP across the anterior 2 cm of the tongue

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FP count in small tongue tip areas does not reliably correlate reliably with PROP status.

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Number of FP across the anterior 2 cm of the tongue correlates with PROP status.

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No relationship identified between the number of FP and thermal taster status.

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PROP and thermal taste are independent phenomena.