Evaluation of palatal rugae pattern for gender determination and personal identification by comparing simulated antemortem and post mortem records in edentulous patients using a digital method

Abstract

Background:

Palatal rugoscopy offers a potential solution for identifying victims with severely damaged remains. Unlike teeth, rugae remain stable, even in extreme conditions. This study focuses on edentulous individuals, a previously unexplored area, to assess the potential of digital rugae analysis for personal identification and gender determination.

Materials and methods:

This study involved 138 edentulous patients seeking dentures. Maxillary casts were created from both intraoral impressions (Set A) which simulated ante mortem record and denture tissue surfaces (Set B) which simulated post mortem record. Set A was digitally scanned using Medit extraoral scanner, while Set B was photographed. Rugae patterns were classified based on shape and unification by digital analysis for gender determination. For personal identification, the simulated ante mortem and post mortem record patterns were digitally matched using adobe photoshop by overlapping the images to assess personal identification accuracy. Examiners determined the gender of individuals based solely on their rugae patterns and derived a formula.

Results:

Palatal rugae analysis showed potential for gender determination and identification. Females had more curved rugae, while males had more wavy ones. Digital matching achieved high accuracy for gender prediction (96.03% sensitivity, 97.58% PPV). Rugae matching also showed promise for personal identification (95.97% sensitivity, 95.97% PPV).

Conclusions:

This study demonstrates that palatal rugae patterns, even in edentulous individuals, offer reliable indicators for both gender determination and personal identification. Digital analysis and matching techniques yielded high accuracy, highlighting their forensic applicability in scenarios with compromised remains.

INTRODUCTION

Personal identification in forensic science is vital for cases involving crimes or mutilated bodies.[1] Uncovering distinctive characteristics in skeletonized or burned remains requires a multidisciplinary approach to establish identity.[2]

Forensic identification relies on visual methods, limited in complex cases. Experts recommend biometrics, fingerprinting, dental records, and DNA analysis for reliable identification.[3] Teeth analysis, crucial for identification, includes size, shape, anomalies, and dental work. Innovations like intraoral micro identification discs enhance dental identification in forensics.[4,5,6,7]

On the other hand, palatal rugae can aid in identification in cases of edentulism.[8] In medico-legal investigations, palatal rugae are considered as effective as bite marks and fingerprints for individual identification.[9]

Palatal rugae, formed by the third month of fetal development, are permanent folds on the anterior palate, retaining their unique shape throughout life, despite damage.[10,11,12,13]

Palatal rugae patterns, unique to each person, consist of stratified squamous epithelium on a connective tissue base.[14] Studied through palatal rugoscopy, introduced by Allen in 1889, termed “rugoscopy” by Trobo Hermosa in 1932. Located at the incisive papilla and median palatal raphe, divided into approximately four on each side, with men having slightly more, especially on the left side.[15,16]

Palatal rugae, protected by the tongue and buccal fat pad, are ideal for forensic ID due to their consistent patterns. Thomas and Van Wyk demonstrated their stability in identifying burnt edentulous bodies. Dentures are crucial for identification due to their accurate replication of tooth structures and durability. Forensic odontologists highly value printed rugoscopy in dentures for streamlining analyses.[17,18,19,20,21]

This study uses digital methods to examine palatal rugae patterns in edentulous individuals for identification and gender determination. Previous research primarily used manual techniques with dentulous casts, overlooking edentulous cases. The study aims to fill this gap by focusing on edentulous casts, enhancing understanding of palatal rugoscopy’s forensic potential.

MATERIALS AND METHODS

This study conducted at the Department of Oral and Maxillofacial Pathology, Manubhai Patel Dental College Hospital and ORI, Vadodara, with institutional approval and involved 138 edentulous subjects seeking complete denture prosthesis. Two sets of maxillary casts were obtained from each individual: Set A, from intraoral impressions, and Set B, from denture tissue surfaces. Set A was digitally scanned, while Set B was photographed to simulate postmortem records.

Inclusion criteria

1. Completely edentulous patients were included in the study.

2. Patients with at least one set of dentures were included.

Exclusion criteria

1. Patients with exostosis, palatal lesions, previous surgery at anterior palate region were excluded from the study.

2. Patients with known hypersensitivity to alginate impression material were excluded.

3. Patients not willing to participate.

Obtaining Set A casts

a) Obtaining Maxillary casts from intraoral impressions of patients

In the present study, maxillary impressions for edentulous patients were created using Zermack dust-free alginate loaded into perforated edentulous metal trays. These impressions were promptly poured with Type III Dental stone to form durable and detailed casts. After forming the casts, they were trimmed to eliminate excess material and ensure anatomical accuracy. A base former was used to provide stability and uniformity to each cast. The resulting casts, designated as Set A, were systematically assigned blind reference numbers to maintain confidentiality and prevent bias in subsequent analyses.

b) Extraoral Scanning of maxillary casts:

The edentulous casts from Set A, obtained from intraoral maxillary impressions of 138 patients (69 males and 69 females), underwent digitization using the Medit T500 extraoral scanner. The resulting digital data was stored in STL format using EXOCAD 3.2 software, creating simulated antemortem records. This modern approach facilitated easy storage, retrieval, and further digital analyses and comparisons. The use of advanced technology, such as the Medit scanner and EXOCAD software, demonstrated the study’s commitment to incorporating contemporary methodologies in dental research.

Obtaining Set B casts

a) Obtaining maxillary casts from tissue surface of maxillary dentures

Maxillary dentures were obtained from patients whose intraoral alginate impressions had been made. Modelling wax was used to block any undercuts on the tissue surface of the dentures, ensuring smooth and precise impressions. Two coats of cold mould seal were then applied to the denture surface as a separating agent to prevent dental stone from adhering to the denture, facilitating easy separation. After the seal dried, dental stone was poured into the denture’s tissue surface to form casts, which constituted Set B as simulated postmortem records. These casts were trimmed to remove excess material and ensure anatomical accuracy, with base formers used for uniformity. Each cast in Set B was assigned a blind reference number to maintain confidentiality and prevent bias in subsequent analyses.

b) Photographs of maxillary casts obtained from maxillary denture base

The dental casts obtained from Set B, derived from the tissue surface of maxillary dentures, were acquired from 138 patients, evenly distributed with 69 males and 69 females. A high-quality single-lens reflex (SLR) camera was employed for documentation. Images were saved in.jpg format to ensure accessibility and ease of retrieval for subsequent examination and detailed analysis. This meticulous approach to photographic documentation, utilizing advanced equipment, emphasized a dedicated commitment to maintaining comprehensive records of the dental impressions.

Determining the characteristics of rugae patterns

The principal investigator organized the records comprising Set A for both genders using Adobe Photoshop. Rugae patterns were identified and delineated using a red colour marking tool, following the classification system outlined by Thomas and Kortz. These rugae patterns were categorized into four shapes: Curved, wavy, straight, and circular, as well as two unification patterns: Convergent and divergent. Subsequently, the rugae patterns on the casts were further categorized based on their shape and unification characteristics to analyze the predominant patterns observed in both genders.

Digitally matching the rugae patterns for individual identification

All images from both Set A and Set B were uploaded onto Adobe Photoshop by the principal investigator. Two additional examiners, blinded to the underlying data, digitally compared rugae patterns. To ensure consistency in the analysis, the background of all images was removed. Set A images, which had delineated rugae patterns, were set at a transparency level of 80%, while Set B images were set at 20%. The adjusted Set A images were then presented to the examiners in a random order. Blinded to the original data, the examiners were tasked with accurately matching the rugae patterns by overlaying the Set A images onto the Set B images. This method was employed to assess the proficiency of the examiners in objectively aligning and matching the rugae patterns.

Digital evaluation of rugae patterns for gender determination

The records from Set A, initially marked with a red marker and adjusted to an 80% transparency level, were modified by increasing their opacity to 100%. The principal investigator organized them into mixed groups of males and females based on gender information provided in the dataset. Blinded examiners then scrutinized and examined the rugae patterns using the classification system proposed by Thomas and Kortz. They were asked to categorize the patterns into male or female groups. Twenty images of casts were displayed on the screen (10 males and 10 females), and the observers were tasked with categorizing them into their respective genders. Reference articles by Gadicherla et al. (2017)[22] and Pereira et al. (2018)[23] were provided and explained regarding the shapes of palatal rugae and unification patterns, which included curved, wavy, straight, circular, converging, and diverging patterns.

Statistical analysis used in the study

Descriptive analysis student’s t-test Kappa statistics liner regression discriminant functional analysis ANOVA test.

RESULTS

The study used digital methods to examine palatal rugae patterns in edentulous individuals, assessing their utility for personal identification and gender determination. It involved 138 completely edentulous subjects (69 males, 69 females), aged 48 to 75, seeking complete denture prostheses.

Characteristics of rugae patterns

In the study encompassing 138 individuals, a total of 909 rugae were identified, with 457 (50.27%) in females and 452 (49.73%) in males. The most prevalent rugae pattern was the curvy type, comprising 360 instances (39.60%), followed by the wavy type with 312 instances (34.32%). Straight rugae were observed in 105 instances (11.55%), while circular patterns were rare, found only three times (0.33%). Diverging unification occurred in 121 patients (13.31%), whereas a converging unification was noted in eight patients (0.88%).

Table 1 shows that a total of 909 rugae were found in the 138 individuals. Among total rugae, the most common pattern observed was curvy type, followed by wavy type, straight type, and circular type. Diverging type of unification was found in 13.31% patients and a converging type of unification in 0.88% of patients.

Table 1.

Patterns of palatal rugae

Type of the rugae	Frequency	Percentage
Curvy	360	39.60%
Wavy	312	34.32%
Straight	105	11.55%
Circular	3	0.33%
Diverging	121	13.31%
Converging	8	0.88%
Total	909	100%

Figure 1 shows that a total of 909 rugae were found in the 138 individuals.

Figure 1.

Types of rugae pattern

Table 2 shows that the mean of the curved-shaped palatal rugae in females was significantly higher than the males (P < 0.0001), but the mean of the wavy-shaped palatal rugae in males was significantly higher than the females (P < 0.0001). The mean of the straight-shaped palatal rugae was higher in females, but the difference was not statistically significant. Furthermore, the mean of the diverging unification was significantly higher in males than the females (P = 0.0002), but there was no significant difference between males and females in converging unification (P = 0.48).

Table 2.

The difference between the two genders for the type and unification of palatal rugae (students’ t-test)

	Male	Female	P	Significance
Shape	Mean±SD	Mean±SD
Curved	2.2±0.7	3.1±0.87	P<0.0001	Significant
Wavy	2.7±0.85	1.84±0.72	P<0.0001	Significant
Straight	0.68±0.71	0.83±0.72	P=0.23	Not significant
Unification
Converging	0.04±0.21	0.07±0.26	P=0.4829	Not significant
Diverging	1.07±0.65	0.67±0.58	P=0.0002	Significant

The table reveals significant gender differences in palatal rugae characteristics. Specifically, the mean of curved-shaped rugae in females significantly exceeded that of males (P < 0.0001), while the mean of wavy-shaped rugae in males was notably higher than in females (P < 0.0001). Although the mean of straight-shaped rugae was slightly higher in females, the difference lacked statistical significance. Moreover, the mean of diverging unification was significantly greater in males compared to females (P = 0.0002), while no significant difference was found between genders in converging unification (P = 0.48).

In the study, females exhibited a significantly higher average number of curved-shaped palatal rugae (23.65%) compared to males (16.06%), with a P value of < 0.0001, indicating a greater prevalence among females. Conversely, males displayed a significantly higher average number of wavy-shaped palatal rugae (20.13%) compared to females (14.19%), with a P value of < 0.0001, indicating a higher prevalence among males. While females had a slightly higher average number of straight-shaped palatal rugae (6.38%) compared to males (5.17%), this difference was not statistically significant (P = 0.23). There was no statistically significant difference in terms of converging unification between males (0.33%) and females (0.55%) with a P value of 0.48, indicating similar levels. However, males exhibited a significantly higher average number of diverging unifications (8.14%) compared to females (5.17%), with a P value of 0.0002, suggesting a greater prevalence among males.

Figure 2 shows that the Box-Whisker’s plot shows the mean of the curved-shaped palatal rugae in females which is significantly higher than the males (P 0.0001), but the mean of the wavy-shaped palatal rugae in males is significantly higher than the females (P < 0.0001). The mean of the straight-shaped palatal rugae is higher in females, but the difference is not statistically significant. Also, the mean of the diverging unification is significantly higher in males than the females (P = 0.0002), but there is no significant difference between males and females in converging unification (P = 0.48).

Figure 2.

Box-Whisker plot of gender-wise rugae patterns

Gender determination based on the characteristics of rugae patterns studied

Gender determination was performed using digital overlapping of the Set A and Set B cast images. The sensitivity, specificity, positive predictive value, and negative predictive value were calculated along with Kappa statistics for intra observer agreement.

Table 3 shows that the sensitivity of the gender identification through palatal rugae of two observers was 96.03% and the specificity was 75%. The positive predictive value for gender identification was 97.58%, and the negative predictive value was 64.29%.

Table 3.

Accuracy of the gender identification formula for the gender identification from the palatal rugae

Test	Value	95% CI
Sensitivity	96.03%	90.98% to 98.70%
Specificity	75.00%	42.81% to 94.51%
Positive predictive value	97.58%	93.09% to 99.50%
Negative predictive value	64.29%	35.14% to 87.24%

The sensitivity of gender identification through palatal rugae for both observers was 96.03%, indicating they correctly identified 96.03% of positive cases. Specificity was 75%, meaning they correctly identified 75% of negative cases where rugae patterns were unclear. The positive predictive value (PPV) for gender identification was 97.58%, signifying a 97.58% chance of true positive identification from the images. The negative predictive value (NPV) was 64.29%, indicating a 64.29% chance of true negative identification when gender was not determined from the images.

Using regression statistics and discriminant functional analysis, a formula for gender determination was derived based on the distribution of rugae patterns.

Table 4 shows canonical discriminant functional coefficients which is used to derive a formula for gender determination in Gujarati population.

Table 4.

Canonical discriminant functional coefficients

	Coefficients
Constant	0.081
Curvy	0.246
Wavy	−0.073
Straight	0.105
Diverging	−0.150
Converging	−0.072

Gender = 0.081 + 0.246 (Curvy) – 0.073 (Wavy) +0.105 (Straight) – 0.105 (Diverging unification) – 0.072 (Converging unification)

The cutoff value for gender determination was obtained 0.5. Values > 0.5 were deemed as females and < 0.5 as male.

Personal identification by overlapping using digital method

Personal identification was performed using digital overlapping of the Set A and Set B cast images. The sensitivity, specificity, PPV and NPV were calculated along with Kappa statistics for intraobserver agreement.

Table 5 shows that the sensitivity of the matching of the palatal rugae with images of two observers is 95.97% and the specificity is 64.29%. The PPV for matching of the palatal rugae with imaging is 95.97%, and the NPV is 64.29%.

Table 5.

Sensitivity and specificity test for personal identification

Test	Value	95% CI
Sensitivity	95.97%	90.84% to 98.68%
Specificity	64.29%	35.14% to 87.24%
Positive predictive value	95.97%	90.84% to 98.68%
Negative predictive value	64.29%	35.14% to 87.24%

Table illustrates that the sensitivity of palatal rugae matching with images for two observers is 95.97%, indicating they correctly identified 95.97% of positive cases. Specificity stands at 64.29%, denoting correct identification of 64.29% of negative cases where rugae patterns were unclear. The PPV for matching palatal rugae with imaging is 95.97%, signifying a 95.97% chance of true positive identification from the images. The NPV is 64.29%, indicating a 64.29% chance of true negative identification when palatal rugae were not identified in the images.

DISCUSSION

Forensic identification combines fingerprint, lip print, DNA, and rugae analysis. Fingerprints provide reliable individual identification, while dental and DNA comparisons offer further insights. Palatal rugae and lip prints supplement these efforts. By integrating diverse techniques, investigators assemble crucial evidence for accurate identification in criminal investigations and missing persons cases, highlighting the importance of leveraging varied tools for precise results in forensic identification.[24,25]

Palatoscopy, pioneered by Troban Hermaso (1932) and extensively studied by Carrea (1937), Da Silva (1938), Lysell (1955), and Thomas and Wyk (1988), involves examining palatal rugae patterns for identity confirmation. These patterns remain stable throughout life, surviving decomposition for up to seven days after death. The resistance of palatal rugae to high temperatures and decomposition makes them particularly useful in forensic cases involving fire victims or mass disasters, where conventional methods like DNA analysis may be compromised.

Palatal rugoscopy offers a reliable alternative for identification, especially in difficult scenarios. Palatal rugae patterns are unique to each individual, even among identical twins, due to genetic factors. Despite global variations, these patterns remain stable throughout life, providing a reliable tool for forensic identification, surpassing traditional methods’ limitations.[26,27] Palatal rugae analysis can serve as a supplementary tool in forensic anthropology, providing valuable information in cases where skeletal remains are fragmented or incomplete.

In forensic investigations, establishing the sex of human remains is crucial for forming a “biological profile.” This assessment guides further examinations like dental records comparison, DNA analysis, and evaluation of skeletal features, contributing to a comprehensive understanding of the individual’s identity and circumstances of death.[28]

Rugoscopy, primarily used in forensic context, offers a unique and relatively available method for personal identification in edentulous cases, particularly in scenarios like homicide investigations or missing person cases involving elderly individuals. Most of the past investigations employed casts from younger dentulous individuals by trimming off teeth for personal identification and gender determination via palatal rugae analysis. Only few studies have focused on edentulous individuals, reflecting real-life scenarios encountered in forensic investigations where conventional identification methods may be unavailable or inconclusive. This study did not analyze differences in the number or length of rugae on both sides of the palate, as these parameters were deemed statistically insignificant by prior research.[14]

This study involved 138 completely edentulous individuals seeking denture treatment. Simulated antemortem and postmortem records were obtained for each, with Set A comprising digitally scanned dental casts and Set B representing postmortem data from maxillary dentures. The digitally outlined patterns in Set A were overlapped with Set B for personal identification by two blinded examiners. This comparative approach minimized observer bias and enhanced accuracy in analysis. Thus, in the current study, two sets of casts were obtained from edentulous subjects seeking complete denture prosthesis. Set A casts poured from intraoral maxillary impressions served as simulated antemortem records, while Set B casts poured from tissue surface of maxillary complete dentures were used as simulated post mortem records.

The methodology employed in this study ensured the preservation of rugae characteristics by using high-resolution digital scanning and overlay techniques, which helped accurately match patterns between antemortem and postmortem records. This study’s focus on edentulous patients enhances the practical relevance of its findings in such forensic context.

In a 2020 case report by Lima de Castro, the remains of an elderly Asian-European mixed ancestry male were discovered in Brazil. While the cause of death remained undetermined, anthropological examination estimated his height and identified an old fracture on the left clavicle. Dentures found with the remains matched the size and shape of the jawbone. A missing person’s family provided information about a man with similar characteristics, including a healed left clavicle fracture, and provided his old dentures. Forensic dentists compared the postmortem dentures with the antemortem ones provided by the family. Casts were made of the dentures’ insides to analyze palatal rugae and edentulous ridges, examined under magnification, and documented. Digital outlines of the rugae patterns were created for further comparison. The analysis revealed a high degree of compatibility between the two sets of dentures, with rugae patterns matching in shape, location, and size. Minor discrepancies were attributed to casting imperfections. Furthermore, the shape and bone loss pattern of the lower jaw matched between the remains and the dentures, leading forensic dentists to conclude that the dentures found with the remains belonged to the missing person.[21]

This study exclusively focused on fully edentulous patients aged 48 to 75 years to improve the accuracy of analyzing palatal rugae patterns for forensic purposes, aiming to minimize age-related confounding effects. Various methods, such as direct visual inspection, intraoral photography, and 3D scanners, have been used for palatal rugae analysis in forensic investigations. The transition to digital methods offers enhanced accuracy and record-keeping convenience compared to traditional manual techniques. Prior to digital technologies, manual methods involved outlining rugae patterns on dental casts and visually comparing them for similarity. Studies achieved high accuracy rates using these methods, albeit potentially influenced by dentulous casts. Some studies explored intraoral photography as an alternative, showcasing the ongoing evolution of digital methodologies in rugae analysis. Digital methods offer advantages in precision and durability compared to physical casts, which can deteriorate over time. Furthermore, the integration of machine learning for automated pattern recognition in palatal rugae analysis could significantly enhance forensic identification accuracy and efficiency.

The dental field increasingly relies on 3D scanner technology and virtual models for their accuracy and reliability. Studies by Taneva ED[29] and Suhartono et al.[30] explore the potential of 3D evaluation of palatal rugae for human identification using digital study models. These highlight the utility of 3D reconstruction in accurately assessing rugae features. As technology advances, 3D reconstruction is poised to revolutionize workflows across various domains.[30,31,32,33]

This study employed a hybrid approach using extraoral scanned casts and photographs of dental casts to analyze palatal rugae for personal identification and gender determination. It employed a structured methodology where intraoral impressions were taken from the subjects to create dental casts. These casts were then scanned using the Medit T500 scanner, ensuring high-resolution digital images. The rugae patterns were carefully delineated using Adobe Photoshop, allowing for precise visualization and mapping of individual characteristics. The digitally outlined patterns in Set A were overlapped with Set B for personal identification by two blinded examiners. This comparative approach minimized observer bias and enhanced accuracy in analysis. Gender determination was carried out by blinded observers on the basis of rugae patterns using reference articles by Gadicherla et al. (2017)[22] and Pereira et al. (2018).[23] The study derived a formula for gender determination henceforth and utilized the Thomas and Kotze classification system for rugae patterns, with all cases conforming to the established patterns. The Medit T500 scanner was utilized for the casts obtained from intraoral impressions (Set A), while Adobe Photoshop was used to delineate rugae patterns.

The study found a total of 909 rugae, with no significant gender-based difference in total number observed. Curvy patterns were most common (39.60%), followed by wavy (34.32%), straight (11.55%), and circular (0.33%) patterns. Diverging unification was predominant (13.31%), while converging unification was less common (0.88%). Gender-wise distribution revealed significant differences in rugae patterns, with males having a higher prevalence of wavy patterns and females showing a higher prevalence of curvy patterns. Diverging unification was more prominent in males, while converging unification showed no significant gender-based difference. Gender determination based on rugae patterns showed high sensitivity (96.03%) and specificity (75.00%). A formula for gender determination specific to the Gujarati population was derived. The stability and uniqueness of palatal rugae make them valuable for personal identification in forensic odontology, particularly in edentulous cases.

Existing literature investigating palatal rugae analysis for identification demonstrates accuracy rates ranging from 70% to 100%. In this study, two observers exhibited a high level of agreement, with a sensitivity of 95.97% and specificity of 64.29%. The positive predictive value was 95.97%, and negative predictive value was 64.29%. The Kappa statistic yielded a value of 0.6, indicating “moderate to substantial agreement.” Despite some variations, the reliability of palatal rugae analysis for gender identification by trained observers was strongly supported. These findings align with previous studies by Limson and Julian,[34] Bansode and Kulkarni,[14] Adisa et al.,[35] English et al.,[3] Maki Ohtani et al.,[36] Hemant M,[19] and Mohammed et al.,[11] which also demonstrated high accuracy rates. Unlike dentulous casts, edentulous casts used in this study minimize age-related changes, such as alveolar ridge resorption, potentially enhancing accuracy in palatal rugae analysis for identification.

CONCLUSION

This study investigated palatal rugae patterns in 138 edentulous individuals (69 males, 69 females) aged 48 to 75, using a digital approach for personal identification and gender determination. The most common rugae patterns observed were curvy (39.60%) and wavy (34.32%). Males had a significantly higher prevalence of wavy patterns, while females had more curvy patterns, both with P < 0.0001. Straight patterns showed no significant gender difference. Diverging unification was more prominent in males, whereas converging unification showed no significant gender difference. Observers demonstrated almost perfect agreement in gender identification, with a Kappa statistic of 0.6. The derived formula for gender determination was based on rugae patterns specific to the Gujarati population.

For personal identification, the study showed high agreement between observers, with a sensitivity of 95.97% and a specificity of 64.29%. The Kappa statistic indicated moderate to substantial agreement, supported by a 95% confidence interval. The use of extraoral scanned images and Adobe Software enhanced the accuracy and efficiency of rugae pattern analysis.

In conclusion, digital analysis of palatal rugae patterns appears promising for identifying and determining gender in edentulous individuals. However, the specificity limitations highlight the need for further research and potentially combining this method with other forensic techniques to improve accuracy.

Ethical clearance

The study was conducted in accordance with the ethical standards outlined in the Declaration of Helsinki. Ethical approval was obtained from the Institutional Ethics Committee (IEC) for Research under approval number IEC/MPDC_252/OP-42/22, dated 22/09/2022. Informed consent was obtained from all participants, and confidentiality was maintained throughout the study.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.