Assessment of biological individuality in periodontitis patients using a specific algorithm and the Salus method

Assessment of biological individuality in periodontitis patients using a specific algorithm and the Salus method | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Assessment of biological individuality in periodontitis patients using a specific algorithm and the Salus method Lázaro Fonseca Véras Gutto, Virgílio Roriz, Rudy José Nodari Junior, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7095588/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Periodontitis is a multifactorial inflammatory disease associated with the accumulation of dysbiotic biofilm, primarily affecting adults and potentially leading to the progressive destruction of periodontal tissues. The Salus method utilizes validated computerized dermatoglyphics for biometric fingerprint evaluation, processed through a specific algorithm integrated into the Science software. This study aimed to investigate whether individuals with a clinical diagnosis of periodontitis, exhibit specific dermatoglyphic patterns identifiable through this algorithm. A total of 157 participants were evaluated, with a mean age of 53.7 years, including 62 individuals diagnosed with periodontitis (stages III and IV) and 95 periodontally healthy (control group). Periodontal status was assessed through clinical probing, and fingerprint data were collected via digital scanning using the Salus method. The images were processed by the algorithm, which performed noise reduction, pattern recognition (type, core, and delta), Galton line tracing, and ridge count calculations for each finger. Statistical analysis included the Kolmogorov-Smirnov test, Student’s t-test, Mann-Whitney test, and Fisher’s exact test, with a significance level set at p < 0.05. Results revealed no statistically significant differences between the groups in either qualitative or quantitative dermatoglyphic variables. The distribution of fingerprint types (whorls, S-shaped whorl, ulnar loops, radial loops, arches), as well as ridge and delta counts, was comparable across both groups. In clonclusion, no association was found between dermatoglyphic patterns and the presence of periodontitis. Therefore, computerized dermatoglyphics did not demonstrate utility as a standalone biometric marker for identifying or screening for the disease. Health sciences/Biomarkers Biological sciences/Computational biology and bioinformatics Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Computerized dermatoglyphics fingerprints Salus method periodontitis Science software Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Periodontitis is a chronic, multifactorial inflammatory disease that affects the supporting structures of the teeth, including the gingiva, periodontal ligament, and alveolar bone. Its primary etiological factor is the subgingival dental biofilm in dysbiosis, which elicits a host inflammatory response. In genetically susceptible individuals, this response may lead to irreversible destruction of periodontal tissues 1 . Clinically, periodontitis is characterized by gingival inflammation, bleeding on probing, periodontal pockets ≥ 4 mm, clinical attachment loss, tooth mobility, and radiographic evidence of alveolar bone loss 2 . In the United States, approximately 47% of individuals aged 30 or older present some degree of periodontitis. Severe forms—Stages III and IV, Grades B and C—affect around 11% of the global population, corresponding to more than 743 million people 1 , 2 . Diagnosis is primarily clinical, based on probing depth, bleeding on probing, and attachment loss. Although these parameters help classify disease severity, they do not necessarily reflect current disease activity, which is more accurately assessed by bleeding on probing and the presence of pockets ≥ 4 mm in at least two non-adjacent interproximal sites. Radiographic evaluation is essential for detecting and classifying alveolar bone loss 2 . The current classification system defines four stages of periodontitis: Stage I - interproximal attachment loss of 1 to 2 mm; Stage II − 3 to 4 mm; Stage III - ≥ 5 mm with up to four teeth lost due to periodontitis; Stage IV - ≥ 5 mm with five or more teeth lost. Disease progression is categorized into three grades: Grade A - slow (no attachment loss in the past five years); Grade B - moderate (< 2 mm in five years); Grade C – rapid progression (≥ 2 mm in five years) 3 . In addition to local factors such as subgingival biofilm dysbiosis, systemic and genetic influences play a critical role. Polymorphisms in genes associated with the inflammatory response, including IL-6 and TNF-α, have been linked to increased susceptibility 4 . Furthermore, growing evidence suggests associations between periodontitis and non-communicable chronic diseases - such as diabetes, cardiovascular, respiratory, and neurodegenerative diseases - through mechanisms involving low-grade systemic inflammation 5 , 6 . Dermatoglyphics, the study of epidermal ridge patterns, is a well-established method in forensic science due to the uniqueness and permanence of fingerprints, which are formed during intrauterine development. With technological advances such as neural networks and specialized software, dermatoglyphics has expanded into phenotype reconstruction and population studies, proving valuable in determining sex, ancestry, and other traits 7 – 10 . Fingerprint patterns develop between the 12th and 20th weeks of gestation under genetic control, but are also influenced by biochemical factors such as oxygenation, hormones levels, substance exposure, and gestational stress 11 , 12 . Owing to their ectodermal origin - shared with dental enamel and nervous tissue - dermatoglyphic variations have been explored as potential markers for systemic and dental conditions 13 , 14 . Mathematical models such as Turing’s reaction-diffusion theory describe fingerprint formation through molecular signaling involving EDAR, WNT, and BMP, which influence ridge and furrow patterning 15 . Until the 1990s, dermatoglyphic analysis was performed manually using ink, paper, and magnifying lenses - a process susceptible to human error. The advent of computerized systems, such as the Salus method, has revolutionized fingerprint analysis through encrypted digital scanning and proprietary software, enabling precise, automated identification of ridge counts and pattern types. Validated in 2008, the Salus method has compiled an international database of over 14,000 fingerprints from athletes and generates biometric reports predicting physical and neuromotor traits - such as strength, speed, endurance, agility, and coordination - expressed in percentiles 16 . Originally initially developed for forensic and athletic profiling, dermatoglyphics has recently gained attention in clinical research, particularly for identifying non-invasive biomarkers of multifactorial diseases with a genetic component. Associations have been reported between fingerprint patterns and dental conditions, including dental caries and periodontitis 12 , 13 , 17 . Veeresh et al. 17 observed a predominance of ulnar loops (UL) in individuals with caries and whorls (W) in caries-free subjects. Similarly, Vaidya et al. 12 found a higher frequency of whorl patterns among individuals with periodontitis. Whorl-type patterns have been found in up to 74.5% of affected individuals, while radial loops (RL) and arches (A) were more common in healthy subjects 13 , 17 . Given that both periodontitis and dermatoglyphic traits are influenced by genetic and early developmental factors, fingerprint analysis may reveal phenotypic expressions of inherited susceptibility. Periodontitis risk may thus reflect genetically modulated immune responses to dysbiotic bacterial challenge 12 . Despite growing scientific interest, dermatoglyphics remains underexplored in dentistry. Investigating the relationship between fingerprint patterns and periodontitis may offer a promising non-invasive approach to identifying genetic biomarkers of individual susceptibility. This could contribute to a better understanding of the genetic and epigenetic mechanisms underlying periodontal disease and inform preventive and diagnostic strategies. In this context, dermatoglyphic analysis may become a valuable tool for personalized dentistry, particularly in settings where direct genetic testing is not feasible. This study aimed to evaluate whether validated computerized dermatoglyphic analysis can identify fingerprint patterns associated with periodontitis, and to assess its potential as a non-invasive tool for disease screening, risk stratification, and identification of phenotypic markers linked to genetic susceptibility. The study tested the null hypothesis that there is no statistically significant association between dermatoglyphic fingerprint pattern and the presence of periodontitis. Material and Method This study was approved by the Institutional Ethics committee of the Federal University of Goiás (#45344721.5.0000.5083). All participants, or their legal guardians, provided written informed consent. All procedures were conducted in accordance with the Declaration of Helsinki. Sample size calculation Sample size was determined based on literature data and pilot studies, considering a 5% significance level. For the variable "number of ridges" on the right thumb (fist right digit; R1D), a minimal detectable difference of 1 unit between case and control groups yielded an estimated statistical power of 22.3%. Assuming a 3-unit difference, statistical power increased substantially to 94.7%, demonstrating high sensitivity for detecting large effects. The final sample included 62 individuals with periodontitis and 95 periodontally healthy controls. This sample size provided an estimated power of 63% for a 1-unit difference and 96.7% for a 3-unit difference between the groups. All calculations were performed using the PSS Health software (Power and Sample Size for Health Researchs; https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/ ), ensuring methodological rigor and appropriate planning for statistical analyses. Sample selection The study sample consisted of 157 adult participants of both sexes (85 men and 72 women), comprising 62 individuals clinically diagnosed with periodontitis and 95 periodontally healthy controls. Inclusion criteria included age over 30 years, the presence of at least 20 teeth, and no indication for tooth extraction. Exclusion criteria included pregnancy, the absence of one or more fingerprints, and any condition (e.g., scarring) that interfered with fingerprint registration. Participants were allocated to the periodontitis group based on the presence of clinical attachment loss (CAL) at two or more non-adjacent interproximal sites, or CAL ≥ 4 mm on buccal or lingual (palatal) surfaces, along with probing pockets depths ≥ 4 mm in at least two teeth. Data collection procedures and periodontal examinations were performed at the university dental clinics by a periodontics specialist. Fingerprint collection was conducted by a physiotherapist trained in the Salus method. Both professionals were previously calibrated using 10% of the study sample to ensure procedural reliability. Periodontal Status Assessment Periodontal evaluation was performed using a UNC-15 periodontal probe (PC-PUNC, Hu-Friedy, Chicago, IL, USA), with 1 mm gradations, following a rapid probing protocol. Periodontal status was classified according to the criteria proposed by Caton et al. 18 , as follows: Periodontal health: probing depth ≤ 3 mm and bleeding on probing (BoP) in < 10% of sites; Gingivitis: probing depth ≤ 3 mm with BoP ≥ 10% of sites; Periodontitis: detectable interproximal CAL at two or more non-adjacent interproximal sites; or buccal/ lingual(palatal) CAL ≥ 4 mm with PPD ≥ 4 mm in two or more teeth, excluding non-periodontitis-related causes such as: traumatic gingival recession, cervical caries, distal loss associated with third molar malposition or extraction, endodontic-periodontal lesions, or vertical root fractures 18 . Participants were then classified as periodontitis cases or as control (periodontally healthy or with gingivitis) prior to fingerprint data collection. Fingerprint Collection Fingerprint patterns were analyzed using the Salus method, which incorporates both qualitative and quantitative dermatoglyphic characteristics. Qualitative features included the fingerprint pattern type: Arch, Loop, or Whorl. Quantitative parameters included ridge count (RC) per finger, combined ridge count for both hand (RCBH), and number of deltas (ND). Fingerprint images was obtained at the dental clinic using a Watson Mini scanner (model IBNW121), following participant classification. This scanner includes proprietary software for image processing (noise reduction, enhancement), pattern recognition, storage, and statistical reporting, as proposed by Nodari-Junior 16 . Image interpretation was conducted using Salus Science software, version 5.1 (serial number 23520000 − 17005000). The system automatically removed noise, preprocessed images, and integrated with Salus Coleta software for advanced analysis. Following image capture, the user manually defined core and delta points; the software then traced the Galton Line and computed ridge count via specific algorithms. The Salus Science software was developed in Object Pascal (Delphi 7) with a Firebird database management system (DBMS), ensuring data security and operational stability. The scanning process followed a standardized order, starting with the left little finger and progressing sequentially to the right little finger (Fig. 1 A to E). Statistical Data Analysis Data were initially organized in Microsoft Excel (version 2505; Microsoft Corporation, Richmond, WA, USA) and to SPSS version 20.0 (Statistical Package for the Social Sciences; IBM, Armonk, NY, USA) for statistical analysis. The Kolmogorov-Smirnov test was used to assess the normality of quantitative variables. Normally distributed variables were reported as mean and standard deviation, and non-normally distributed variables as median and interquartile range. Groups comparisons of quantitative variables (e.g., ridge count) were conducted using Student’s t-test (for normally distributed data) or Mann-Whitney U test (for skewed data). Analyses included total ridge count for each finger — ridge count of the first digit of the left hand (RC1DLH), index (RC2DLH), middle (RC3DLH), ring (RC4DLH), and little finger (RC5DLH), as well as the total ridge count for the left hand (TRCLH); for the right hand: ridge count of the first digit right hand (RC1DRH), index (RC2DRH), middle (RC3DRH), ring (RC4DRH), and little finger (RC5DRH), the total ridge count for the right hand (TRCRH), the combined ridge count for both hands (RCBH), and the total number of deltas (ND). Qualitative variables, including Arch (A), radial loop (RL), ulnar loop (UL), Whorl (W), and S-shaped Whorl (WS), as well as the fingerprint pattern of each finger (left hand: L1D to L5D; right hand: R1D to R5D) were expressed as frequencies and percentages. Associations between fingerprint pattern and periodontal status were evaluated using Fisher’s exact test. A significant level of p < 0.05 was adopted for all analyses. Results The results revealed a high degree of similarity between individuals with and without periodontitis regarding dermatoglyphic characteristics (Tables 1 to 9 , Figs. 2 to 4 ). No statistically significant differences were observed in anthropometric variables such as weight, height, sex. However, the mean age was significantly higher in the periodontitis group compared to the control group (53.7 ± 11.4 years vs. 48.2 ± 11.3 years; p = 0.004) (Table 1 ). Table 1 Anthropometric and demographic characteristics of individuals with and without periodontitis. Characteristics Periodontitis (n = 62) Control (n = 95) P value Weight (Kg; mean ± SD) 75.9 ± 12.3 72.9 ± 15.0 0.212* Height (meter; mean ± SD) 1.65 ± 0.09 1.65 ± 0.10 0.780* Sex n (%) 0.315** Female 30 (48.4) 55 (57.9) Male 32 (51.6) 40 (42.1) Age (years; mean ± SD) 53.7 ± 11.4 48.2 ± 11.3 0.004* SD – standard deviation. *Student’s t-test for independent samples; Fisher’s exact test). Table 2 Distribution of fingerprint pattern types by finger position in the periodontitis group. A n (%) RL n (%) UL n (%) W n (%) WS n (%) L5D - - 55 (88.7) 5 (8.1) 2 (3.2) L4D - - 40 (64.5) 17 (27.4) 5 (8.1) L3D 5 (8.1) 1 (1.6) 38 (61.3) 12 (19.3) 6 (9.7) L2D 1 (1.6) 7 (11.3) 26 (41.9) 23 (37.1) 5 (8.1) L1D 2 (3.2) - 32 (51.6) 12 (19.4) 16 (25.8) R1D - - 30 (48.4) 16 (25.8) 16 (25.8) R2D 1 (1.6) 13 (21.0) 22 (35.5) 19 (30.6) 7 (11.3) R3D 2 (3.2) 1 (1.6) 43 (69.4) 11 (17.7) 5 (8.1) R4D 1 (1.6) - 33 (53.2) 27 (43.5) 1 (1.6) R5D 1 (1.6) 52 (83.9) 7 (11.3) 2 (3.2) L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D – Right 1th digit; R2D – Right 2th digit; R3D – Right 3th digit; R4D – Right 4th digit; R5D – Right 5th digit; A – arch; RL – radial loop; UL – ulnar loop; W – whorl; WS – whorl. Table 3 Description of ridge counts, delta counts, and finger positions in the periodontitis group. Ridge count Delta numbers n (%) Mean ± SD 0 1 2 L5D 10.7 ± 4.7 - 55 (88.7) 7 (11.3) L4D 12.2 ± 5.5 - 40 (64.5) 22 (35.5) L3D 9.9 ± 5.7 5 (8.1) 39 (62.9) 18 (29.0) L2D 9.5 ± 5.3 1 (1.6) 33 (53.2) 28 (45.2) L1D 13.4 ± 5.6 2 (3.2) 32 (51.6) 28 (45.2) Total ridges count of the left hand 55.5 ± 21.0 R1D 15.2 ± 5.1 - 30 (48.4) 32 (51.6) R2D 10.0 ± 6.1 1 (1.6) 35 (56.5) 26 (41.9) R3D 10.2 ± 4.6 2 (3.2) 44 (71.0) 16 (25.8) R4D 12.5 ± 5.7 1 (1.6) 33 (53.2) 28 (45.2) R5D 10.4 ± 4.8 1 (1.6) 52 (83.9) 9 (14.5) Total ridges count of the right hand 58.2 ± 20.8 Total ridges 113.7 ± 40.6 Total deltas 13.2 ± 3.2 SD - standard deviation; L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D – Right 1th digit; R2D – Right 2th digit; R3D – Right 3th digit; R4D – Right 4th digit; R5D – Right 5th digit. Table 4 Distribution of predominant fingerprint pattern types by finger position in the control group (n = 95). A n (%) RL n (%) UL n (%) W n (%) WS n (%) L5D 3 (3.2) 1 (1.1) 78 (82.1) 8 (8.4) 5 (5.2) L4D 2 (2.1) 56 (58.9) 34 (35.8) 3 (3.2) L3D 7 (7.4) 1 (1.1) 72 (75.8) 11 (11.6) 4 (4.1) L2D 3 (3.2) 19 (20.0) 46 (48.4) 16 (16.8) 11 (11.6) L1D 2 (2.1) 2 (2.1) 50 (52.6) 15 (15.8) 26 (27.4) R1D 2 (2.1) 1 (1.1) 46 (48.4) 28 (29.5) 18 (18.9) R2D 4 (4.2) 12 (12.6) 42 (44.2) 30 (31.6) 7 (7.4) R3D 5 (5.3) 2 (2.1) 71 (74.7) 13 (13.7) 4 (4.2) R4D 2 (2.1) 48 (50.5) 41 (43.2) 4 (4.2) R5D 4 (4.2) 3 (3.2) 77 (81.1) 10 (10.4) 1 (1.1) L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D – Right 1th digit; R2D – Right 2th digit; R3D – Right 3th digit; R4D – Right 4th digit; R5D – Right 5th digit; A – arch; RL – radial loop; UL – ulnar loop; W – whorl; WS – whorl. Table 5 Description of ridge counts, delta counts, and finger positions in the control group (n = 95). Ridge count Delta numbers n(%) Mean ± SD 0 1 2 L5D 11.1 ± 5.1 3 (3.2) 79 (83.1) 13 (13.7) L4D 12.4 ± 5.5 2 (2.1) 56 (58.9) 37 (39.0) L3D 10.6 ± 6.0 7 (7.4) 73 (76.8) 15 (15.8) L2D 9.3 ± 5.8 3 (3.2) 65 (68.4) 27 (28.4) L1D 13.2 ± 6.3 2 (2.1) 52 (54.7) 41 (43.2) Total ridge count of the left hand 56.4 ± 23.3 R1D 14.2 ± 5.5 2 (2.1) 47 (49.5) 46 (48.4) R2D 9.4 ± 5.8 4 (4.2) 54 (56.8) 37 (39.0) R3D 9.8 ± 5.2 5 (5.3) 73 (76.8) 17 (17.9) R4D 11.9 ± 5.4 2 (2.1) 48 (50.5) 45 (47.4) R5D 10.9 ± 5.6 4 (4.2) 80 (84.2) 11 (11.6) Total ridges count of the right hand 56.2 ± 21.6 Total ridges 112.6 ± 43.7 Total deltas 12.7 ± 3.2 SD - standard deviation; L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D – Right 1th digit; R2D – Right 2th digit; R3D – Right 3th digit; R4D – Right 4th digit; R5D – Right 5th digit. Table 6 Comparison of qualitative fingerprint pattern types by finger position between the periodontitis and control groups. Periodontitis (n = 62) Control (n = 95) P Value* A RL UL W WS A RL UL W WS L5D n (%) - - 55(88.7) 5(8.1) 2(3.2) 3(3.2) 1(1.1) 78(82.1) 8(8.4) 5(5.2) 0.707 L4D n (%) - - 40(64.5) 17(27.4) 5(8.1) 2(2.1) 56(58.9) 34(35.8) 3(3.2) 0.273 L3D n (%) 5(8.1) 1(1.6) 38(61.3) 12(19.3) 6(9.7) 7(7.4) 1(1.1) 72(75.8) 11(11.6) 4(4.1) 0.283 L2D n (%) 1(1.6) 7(11.3) 26(41.9) 23(37.1) 5(8.1) 3(3.2) 19(20.0) 46(48.4) 16(16.8) 11(11.6) 0.060 L1D n (%) 2(3.2) - 32(51.6) 12(19.4) 16(25.8) 2(2.1) 2(2.1) 50(52.6) 15(15.8) 26(27.4) 0.847 R1D n (%) - - 30(48.4) 16(25.8) 16(25.8) 2(2.1) 1(1.1) 46(48.4) 28(29.5) 18(18.9) 0.704 R2D n (%) 1(1.6) 13(21.0) 22(35.5) 19(30.6) 7(11.3) 4(4.2) 12(12.6) 42(44.2) 30(31.6) 7(7.4) 0.461 R3D n (%) 2(3.2) 1(1.6) 43(69.4) 11(17.7) 5(8.1) 5(5.3) 2(2.1) 71(74.7) 13(13.7) 4(4.2) 0.768 R4D n (%) 1(1.6) - 33(53.2) 27(43.5) 1(1.6) 2(2.1) 48(50.5) 41(43.2) 4(4.2) 0.908 R5D n (%) 1(1.6) 52(83.9) 7(11.3) 2(3.2) 4(4.2) 3(3.2) 77(81.1) 10(10.4) 1(1.1) 0.518 *Fisher’s exact test; L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D – Right 1th digit; R2D – Right 2th digit; R3D – Right 3th digit; R4D – Right 4th digit; R5D – Right 5th digit; A – arch; RL – radial loop; UL – ulnar loop; W – whorl; WS – whorl. Table 7 Comparison of quantitative fingerprint variables (ridge and delta counts) by finger position between the periodontitis and control groups. Periodontitis (n = 62) Control (n = 95) P value* L5D 10.7 ± 4.7 11.1 ± 5.1 0.592 L4D 12.2 ± 5.5 12.4 ± 5.5 0.827 L3D 9.9 ± 5.7 10.6 ± 6.0 0.481 L2D 9.5 ± 5.3 9.3 ± 5.8 0.801 L1D 13.4 ± 5.6 13.2 ± 6.3 0.841 Total ridge count of the left hand 55.5 ± 21.0 56.4 ± 23.3 0.811 R1D 15.2 ± 5.1 14.2 ± 5.5 0.241 R2D 10.0 ± 6.1 9.4 ± 5.8 0.560 R3D 10.2 ± 4.6 9.8 ± 5.2 0.708 R4D 12.5 ± 5.7 11.9 ± 5.4 0.523 R5D 10.4 ± 4.8 10.9 ± 5.6 0.576 Total count of the right hand 58.2 ± 20.8 56.2 ± 21.6 0.568 Total ridges 113.7 ± 40.6 112.6 ± 43.7 0.873 Total deltas 13.2 ± 3.2 12.7 ± 3.2 0.290 Mean ± standart deviation; *Student t test for independent samples; L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D – Right 1th digit; R2D – Right 2th digit; R3D – Right 3th digit; R4D – Right 4th digit; R5D – Right 5th digit. Table 8 Comparison of delta counts by finger position between the periodontitis and control groups. Delta numbers Periodontitis (n = 62) Control (n = 95) P value* 0 1 2 0 1 2 L5D - 55 (88.7) 7 (11.3) 3 (3.2) 79 (83.1) 13 (13.7) 0.426 L4D - 40 (64.5) 22 (35.5) 2 (2.1) 56 (58.9) 37 (39.0) 0.571 L3D 5 (8.1) 39 (62.9) 18 (29.0) 7 (7.4) 73 (76.8) 15 (15.8) 0.119 L2D 1 (1.6) 33 (53.2) 28 (45.2) 3 (3.2) 65 (68.4) 27 (28.4) 0.084 L1D 2 (3.2) 32 (51.6) 28 (45.2) 2 (2.1) 52 (54.7) 41 (43.2) 0.863 R1D - 30 (48.4) 32 (51.6) 2 (2.1) 47 (49.5) 46 (48.4) 0.671 R2D 1 (1.6) 35 (56.5) 26 (41.9) 4 (4.2) 54 (56.8) 37 (39.0) 0.754 R3D 2 (3.2) 44 (71.0) 16 (25.8) 5 (5.3) 73 (76.8) 17 (17.9) 0.479 R4D 1 (1.6) 33 (53.2) 28 (45.2) 2 (2.1) 48 (50.5) 45 (47.4) 0.943 R5D 1 (1.6) 52 (83.9) 9 (14.5) 4 (4.2) 80 (84.2) 11 (11.6) 0.669 Data presented as n(%); *Fisher’s Exact Test; L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D – Right 1th digit; R2D – Right 2th digit; R3D – Right 3th digit; R4D – Right 4th digit; R5D – Right 5th digit. Table 9 Comparative analysis of fingerprint pattern frequency between the periodontitis and control groups. Periodontitis (n = 62) Control (n = 95) P value* W + WS 3 (1-6.3) 2 (1–5) 0.431 W 1 (0–4) 2 (0–4) 0.800 WS 1 (0-1.3) 0 (0–1) 0.466 UL + RL 7 (3.8-9) 7 (5–9) 0.609 RL 0 (0–1) 0 (0–1) 0.663 UL 7 (3.8-9) 6 (5–8) 0.748 A 0 (0–0) 0 (0–0) 0.914 Data presented as median (interquartile range); *Mann-Whitney U test.; A – arch; RL – radial loop; UL – ulnar loop; W – whorl; WS – S-whorl In terms of fingerprint pattern distribution, the ulnar loop (UL) was the most prevalent pattern across all fingers, followed by the whorl (W), particularly in digits L2D, R2D, L4D, and R4D, where its frequency exceeded 30% (Tables 2 and 4 ). Both groups presented similar mean ridge counts per finger, ranging from 9.3 to 15.2. The average total ridged count was 113.7 in the periodontitis group and 112.6 in the control group. In both groups, fingerprints typically displayed one delta per finger, consistent with the predominance of loop-type patterns (Tables 3 and 5 ). Comparative analysis between the groups showed no statistically significant differences in the distribution of fingerprint pattern types (W, WS, UL, RL, A), nor in the total number of ridges or deltas (Tables 6 to 9 ). Median values and interquartile ranges further reinforced the absence of group-specific dermatoglyphic distinctions. Figures 2 A and 2 B illustrate the dominant frequency of the UL across groups, while Fig. 3 displays overlapping mean values and standard deviations for total ridge and delta counts between periodontitis and control participants. Figure 4 presents boxplots showing the distributions of fingerprint patterns, again confirming no statistically significant differences in any dermatoglyphic category between the two groups. Discussion The comparative analysis between individuals with and without periodontitis revealed no statistically significant differences in demographic and anthropometric variables—such as weight, height, and sex—except for age, which was higher in the periodontitis group. This demographic similarity suggests that the groups were adequately matched, strengthening the validity of the comparisons. Regarding dermatoglyphic characteristics, both groups showed a predominance of ulnar loop (UL) patterns, followed by whorls (W), especially on digits L2D, R2D, L4D, and R4D. S-shaped whorls, radial loops, and arches were less frequent. However, there were no statistically significant differences in the distribution of pattern types between the groups. Quantitative analysis also revealed similar results: mean ridge and delta counts per finger, per hand, and per individual were nearly identical in both groups. The similarity of medians and interquartile ranges further supports the absence of meaningful differences. These findings indicate that dermatoglyphic patterns—whether qualitative or quantitative—do not appear to be directly associated with the presence of periodontitis. Accordingly, the null hypothesis of this study, which stated that there would be no significant association between fingerprint patterns and the presence of periodontitis, was accepted. This study utilized a validated and advanced methodology based on the Salus method, which offers substantial improvements over traditional ink-based techniques. The use of encrypted digital scanner combined with specialized software enabled precise, automated and standardized identification of fingerprint types and ridge counts. This not only improves diagnostic precision but also enhances data reliability and reproducibility 16 , critical factors in studies involving phenotypic markers of multifactorial diseases. In addition, digital methods offer advantages such as speed, secure data storage, integration with clinical databases, and applicability in large-scale or forensic research 7–10,19−21 . The absence of significant differences in ridge counts, especially in key digits such as the thumb (RC1DLH) and little finger (RC5DLH), as well as in the total ridge count per hand (RCBH and TRCLH), corroborates the idea that dermal ridges remain stable throughout life, even in the presence of chronic inflammatory conditions like periodontitis 22 . Similarly, the uniformity in delta counts across groups reinforces the morphological stability of these features. Fingerprints are formed between the 12th and 20th weeks of intrauterine development and are shaped by a combination of genetic and epigenetic influences 15 . Turing’s reaction-diffusion models explain this process through the spatial organization of biochemical signals, leading to distinct yet stable biological patterns. Because fingerprints are genetically encoded and not subject to modification by environmental factors after their formation, they may be limited in reflecting acquired conditions such as periodontitis. Although several studies have reported associations between dermatoglyphic patterns and clinical conditions 11 – 13 , 21 , 23 – 28 , the literature remains inconclusive. For example, Somani et al. 13 observed a higher prevalence of whorl patterns in children with cerebral palsy and dental caries, while Singh et al. 11 noted specific dermatoglyphic trends in girls with caries. In orthodontics, Belludi et al. 25 identified distinct fingerprint distributions in children with Class III malocclusion. However, not all studies found significant differences in quantitative variables. Vaidya et al. 12 and Kumar et al. 26 suggested that whorls and spirals may be more frequent in localized or aggressive periodontitis, while arches were associated with advanced stages. Nonetheless, such associations were not observed in the present study. In contrast to these findings, the present study identified no significant differences in fingerprint pattern types (UL, W, WS, RL, A), ridge counts, or delta counts between groups. These results indicate that dermatoglyphics, when analyzed in isolation, has low sensitivity for detecting phenotypic changes associated with acquired chronic diseases such as periodontitis 29 . This reinforces the understanding that fingerprints, as genetically programmed and developmentally fixed traits, are not modified by the inflammatory or degenerative processes involved in periodontal disease. Other studies have similarly reported limited diagnostic value of dermatoglyphics for certain morphofunctional and systemic conditions. Eslami et al. 23 found minimal differences in fingerprint traits across skeletal malocclusion types. Harini et al. 28 observed no correlation between fingerprint types and primary canine relationships. Jeddy et al. 24 reported no significant association between fingerprint patterns and diabetes, although lip prints were found to be more predictive. These findings underscore the limitations of dermatoglyphics as a standalone diagnostic tool and highlight the need for integrative approaches. The application of an innovative and validated digital method in this study, based on the work of Nodari-Júnior et al. 16 , improved the quality and reproducibility of dermatoglyphic data 14 , 20 . However, the absence of statistically significant associations may reflect the multifactorial and complex nature of periodontitis itself. This disease results from an intricate interplay of microbial, immunoinflammatory, behavioral, and genetic factors—many of which cannot be captured by static morphological markers such as fingerprints 2 , 18 . While dermatoglyphics offers advantages such as non-invasiveness, low cost, and embryological relevance, its diagnostic value for acquired chronic diseases appears limited. Still, its potential may be enhanced when integrated with clinical, genetic, and environmental data. Multimodal approaches—combining dermatoglyphics with salivary biomarkers, genomic profiles, or imaging data—could provide a more comprehensive risk assessment model for periodontal disease 1 , 30 . Dermatoglyphics continues to be a valuable tool in forensic science, particularly in adverse contexts involving decomposition or natural disasters. Its stability and uniqueness are due to its embryonic origin shared with dental enamel and nervous system structures 31 – 35 . However, its role in clinical diagnosis must be contextualized within a broader framework of risk markers 36 . Future studies should employ larger, more diverse samples and standardized methodologies, while exploring associations between dermatoglyphics and other markers of systemic or oral diseases. The integration of the Salus method with additional clinical parameters may enhance its relevance in identifying predispositions or contributing to individualized health profiles. Conclusions Based on the methodology applied in this study, no statistically significant association was identified between dermatoglyphic patterns—either qualitative or quantitative—and the clinical presence of periodontitis. Although fingerprints and dental structures share a common genetic and embryonic origin, the findings do not support the existence of a distinct dermatoglyphic profile among individuals with periodontitis. The predominance of ulnar loop (UL) patterns and the similarity in ridge and delta counts between groups suggest the absence of phenotypic distinctions related to the disease. Declarations Data availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Funding No funds were received in support of this work. No benefits in any form have been or will be received from any commercial party related directly or indirectly to the subject of this manuscript. CRediT authorship contribution statement Lázaro Gutto Fonseca Véras: Conceptualization, Methodology, Formal analysis, Investigation, Writing – review & editing. Virgílio Roriz: Software, Methodology, Conceptualization, Formal analysis, Investigation, Writing – review & editing. Rudy Nodari Junior: Software, Formal analysis, Investigation, Visualization. Karolina Kellen Matias: Formal analysis, Investigation, Visualization. Lucas Rodrigues de Araújo Estrela: Formal analysis, Investigation, Visualization. Carlos Estrela: Software, Methodology, Conceptualization, Formal analysis, Investigation, Writing – review & editing. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Lázaro Gutto Fonseca Véras PT, MSc, PhD, https://orcid.org/0000-0002-9428-4424 Virgílio Roriz DDS, MSc, PhD, https://orcid.org/0000-0003-2028-164X Rudy José Nodari Junior PT, MSc, PhD, https://orcid.org/0000-0002-8375-657X Karolina Kellen DDS, MSc, PhD, http://orcid.org/0000-0002-4527-1467 Lucas Rodrigues de Araújo Estrela DDS, MSc, http://orcid.org/0000-0003-1244-4015 Carlos Estrela, DDS, MSc, PhD, http://orcid.org/0000-0002-1488-0366 References Kwon, T., Lamster, I. B. & Levin, L. Current Concepts in the Management of Periodontitis. Int. Dent. J. 71 (6), 462–476 (2021). Heitz-Mayfield, L. J. A. Conventional diagnostic criteria for periodontal diseases (plaque-induced gingivitis and periodontitis). Periodontol 2000 . 95(1):10 – 9 (2024). Ravidà, A. et al. Agreement among international periodontal experts using the 2017 World Workshop classification of periodontitis. J. Periodontol . 92 (12), 1675–1686 (2021). Zhang, M., Liu, Y., Afzali, H. & Graves, D. T. An update on periodontal inflammation and bone loss. Front. Immunol. 15 , 1385436 (2024). Herrera, D. et al. Periodontal diseases and cardiovascular diseases, diabetes, and respiratory diseases: summary of the consensus report by the European Federation of Periodontology and WONCA Europe. Eur. J. Gen. Pract. 30 (1), 2320120 (2024). Ozmeric, N. et al. Interaction between hypertension and periodontitis. Oral Dis. 30 (3), 1622–1631 (2024). Van, Dam, A., van Beek, F. T., Aalders, M. C., van Leeuwen, T. G. & Lambrechts, S. A. Techniques that acquire donor profiling information from fingermarks - A review. Sci. Justice . 56 (2), 143–154 (2016). Wei, Q., Zhang, M., Ogorevc, B. & Zhang, X. Recent advances in the chemical imaging of human fingermarks (a review). Analyst 141 (22), 6172–6189 (2016). Vodanović, M., Subašić, M., Milošević, D. P., Galić, I. & Brkić, H. Artificial intelligence in forensic medicine and forensic dentistry. J. Forensic Odontostomatol . 41 (2), 30–41 (2023). Patra, M. et al. Surana, P. Gender determination from ridges using dermatoglyphics techniques. Bioinformation 20 (9), 1008–1011 (2024). Singh, K. K. et al. Correlation between dermatoglyphics and dental caries in children: a case-control study. J. Family Med. Prim. Care . 9 (6), 2670–2675 (2020). Vaidya, P. et al. Dermatoglyphics in periodontics: an assessment of the relationship between fingerprints and periodontal status – a cross-sectional observation study. Indian J. Dent. Res. 28 (6), 637–641 (2017). Somani, R. et al. Dermatoglyphics as a noninvasive tool for predicting dental caries in cerebral palsy and healthy children: an in vivo study. Int. J. Clin. Pediatr. Dent. 12 (3), 237–242 (2019). Ramagoni, N. K., Kumar, V., Adusumilli, H., Reddy, K. P. & Kumar, N. P. The relation between dermatoglyphics and mesiodistal width of the deciduous second molar and permanent first molar. J. Clin. Diagn. Res. 11 (8), ZC60–ZC63 (2017). Garzón-Alvarado, D. A. & Ramírez-Martinez, A. M. A biochemical hypothesis on the formation of fingerprints using a Turing patterns approach. Theor. Biol. Med. Model. 8 , 24 (2011). Nodari-Jr, R. J., Heberle, A., Ferreira-Emygdio, R. & Irany-Knackfuss, M. Using fingerprints for health diagnosis: Computerised scanning validation. Rev. Saúde Pública . 42 (5), 767–776 (2008). Veeresh, T., Mujahid, A., Deepu, P. & Sivaprakash, R. Correlation between dermatoglyphics, dental caries and salivary pH: an in vivo study. Ethiop. J. Health Sci. 29 (1), 929–934 (2019). Caton, J. G. et al. A new classification scheme for periodontal and peri-implant diseases and conditions – Introduction and key changes from the 1999 classification. J. Clin. Periodontol . 45 (Suppl 20), S1–8 (2018). Kondeková, M., Beňuš, R., Masnicová, S. & Švábová, P. Distribution of the Minutiae in Hypothenar Palm Prints in Slovak Adults: Indications for Personal Identification. J. Forensic Sci. 65 (4), 1303–1309 (2020). Chen, H., Shi, M., Ma, R. & Zhang, M.. Advances in fingermark age determination techniques. Analyst 146 (1), 33–47 (2021). Patnaik, B. B., Penmetsa, G. S., Vinnakota, K., Ramaraju, A. V. & Alla, R. K. Identification of dermal crease patterns as a link between genetics and periodontitis: reliability and credibility. J. Forensic Sci. Med. 10 (2), 106–110 (2024). Sudha, P. I., Singh, J. & Sodhi, G. S. The dermal ridges as the infallible signature of skin: an overview. Indian J. Dermatol. 66 (6), 649–653 (2021). Eslami, N., Jahanbin, A., Ezzati, A., Banihashemi, E. & Kianifar, H. Can Dermatoglyphics Be Used as a Marker for Predicting Future Malocclusions? Electron. Physician . 8 (2), 1927–1932 (2016). Jeddy, N. et al. Cheiloscopy and dermatoglyphics as screening tools for type 2 diabetes mellitus. J. Forensic Dent. Sci. 11 (3), 163–166 (2019). Belludi, A. C. et al. A Noninvasive Diagnostic Tool in Predicting Class III Skeletal Malocclusion in Children. Int. J. Clin. Pediatr. Dent. 14 (1), 63–69 (2021). Kumar, T. S. et al. Role of dermal ridge patterns in prediction of periodontal disease: A cross-sectional study. J. Clin. Diagn. Res. 17 (3), ZC43–ZC46 (2023). Ortug, G. & İşeri, H. Assessment of the Relation Between Craniofacial Tissue Profile-Morphology and Dermatoglyphics. J. Craniofac. Surg. 34 (1), 398–403 (2023). Harini, M., Ravindran, V. & Arthanari, A. A. Comparative Evaluation Between Dermatoglyphics and Canine Relationship in Deciduous Dentition: An Analysis for Prediction. Cureus 16 (9), e69802 (2024). Genco, R. J. & Loos, B. G. The use of genomic DNA fingerprinting in studies of the epidemiology of bacteria in periodontitis. J. Clin. Periodontol . 18 (6), 396–405 (1991). Korgaonkar, J., Tarman, A. Y., Ceylan-Koydemir, H. & Chukkapalli, S. S. Periodontal disease and emerging point-of-care technologies for its diagnosis. Lab. Chip . 24 (14), 3326–3334 (2024). Verbov, J. Clinical significance and genetics of epidermal ridges–a review of dermatoglyphics. J. Invest. Dermatol. 54 (4), 261–271 (1970). Kücken, M. & Newell, A. C. Fingerprint formation. J. Theor. Biol. 235 (1), 71–83 (2005). Ho, Y. Y. W. et al. Common Genetic Variants Influence Whorls in Fingerprint Patterns. J. Invest. Dermatol. 136 (4), 859–862 (2016). Teicher, A. Kristine Bonnevie's theories on the genetics of fingerprints, and their application in Germany. Stud. Hist. Philos. Sci. 92 , 162–176 (2022). González, M., Gorziza, R. P., De Cássia Mariotti, K. & Pereira, L. R. Methodologies Applied to Fingerprint Analysis. J. Forensic Sci. 65 (4), 1040–1048 (2020). Blau, S., Graham, J., Smythe, L. & Rowbotham, S. Human identification: a review of methods employed within an Australian coronial death investigation system. Int. J. Legal Med. 135 (1), 375–385 (2021). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7095588","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":492323241,"identity":"7e8c2f64-4353-47df-98c5-322d1a59f0c3","order_by":0,"name":"Lázaro Fonseca Véras Gutto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYBACPghlw2DAjhBkw6sFKpvGYMBMopbDpGhhP/7wc0XFeXlzZubHHz7uYZDnFzvA9rgCnxaehGTJM2duG+5sZjOTnPGMwXDm7AR2wzN4HZZwQLKx7XaCwWEGM2aeAwwJBrcT2CQb8Gnhf9j8s7HtHFAL++fPf4jSIpHMBrTlAFALj4E0A3FanrFZNpxJBvqFp0yy54AE0C+J7Yb4tPDzpz++2VBhJ2/O3r75w48DNvL80snHHuLTgg4kgJiRFA2jYBSMglEwCrABAP1URcZnEFTtAAAAAElFTkSuQmCC","orcid":"","institution":"Federal University of Goiás","correspondingAuthor":true,"prefix":"","firstName":"Lázaro","middleName":"Fonseca Véras","lastName":"Gutto","suffix":""},{"id":492323243,"identity":"166d90a2-a8b4-49f0-9dc9-c48a57052136","order_by":1,"name":"Virgílio Roriz","email":"","orcid":"","institution":"Federal University of Goiás","correspondingAuthor":false,"prefix":"","firstName":"Virgílio","middleName":"","lastName":"Roriz","suffix":""},{"id":492323245,"identity":"b04bf31e-bbaf-47b0-b455-bb103b3b0f6b","order_by":2,"name":"Rudy José Nodari Junior","email":"","orcid":"","institution":"University of Western Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Rudy","middleName":"José Nodari","lastName":"Junior","suffix":""},{"id":492323247,"identity":"143d6764-4089-4e79-b0b2-d6d61e752b03","order_by":3,"name":"Karolina Kellen Matias","email":"","orcid":"","institution":"Pontifical Catholic University of Goiás","correspondingAuthor":false,"prefix":"","firstName":"Karolina","middleName":"Kellen","lastName":"Matias","suffix":""},{"id":492323249,"identity":"f2610f45-4bb5-4fa0-a983-cc0f1a2c8fd1","order_by":4,"name":"Lucas Rodrigues de Araújo Estrela","email":"","orcid":"","institution":"São Paulo State University","correspondingAuthor":false,"prefix":"","firstName":"Lucas","middleName":"Rodrigues de Araújo","lastName":"Estrela","suffix":""},{"id":492323250,"identity":"096f10b8-53f2-4163-8372-f1693538186a","order_by":5,"name":"Carlos Estrela","email":"","orcid":"","institution":"Federal University of Goiás","correspondingAuthor":false,"prefix":"","firstName":"Carlos","middleName":"","lastName":"Estrela","suffix":""}],"badges":[],"createdAt":"2025-07-10 18:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7095588/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7095588/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88005751,"identity":"63e7efa0-c0af-4560-8092-55dedc4a4f35","added_by":"auto","created_at":"2025-07-31 10:48:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2331622,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Watson mini scanner used for fingerprint capture; (B) highlighted image showing the delta of an actual fingerprint; (C) highlighted image illustrating how the delta appears after processing with Salus Science software; (D) qualitative patterns (from left to right): A (Arch), W (Whorl), and L (Loop); (E) quantitative pattern and Galton's line, showing the number of lines evaluated by the software and Galton's line indicated in red.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7095588/v1/23c493f14f4735ef05bded2e.png"},{"id":88005343,"identity":"19381daa-2433-401d-8c43-6d533f9cf411","added_by":"auto","created_at":"2025-07-31 10:40:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":257521,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distribution of fingerprint patterns by finger in individuals with (A) and without (B) periodontitis. L5D – Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7095588/v1/86201097f5ba107bcf390afb.png"},{"id":88005341,"identity":"46e8f954-320c-4f8e-b4c3-d5db46bd7a07","added_by":"auto","created_at":"2025-07-31 10:40:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35102,"visible":true,"origin":"","legend":"\u003cp\u003eMean and standard deviation of total ridge and delta counts in the periodontitis and control groups.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7095588/v1/97e67788e4b9dd3907cc52db.png"},{"id":88003411,"identity":"8b0addf1-ae6a-464d-9395-e55c5f4dc1af","added_by":"auto","created_at":"2025-07-31 10:32:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":32172,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot showing the distribution of fingerprint pattern types in the periodontitis and control groups. A - arch; RL – radial loop; UL – ulnar loop; W – whorl; WS – S-whorl.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7095588/v1/b064a206bf74913775320230.png"},{"id":88505205,"identity":"c8cee307-a775-45f0-9a5e-406685adc631","added_by":"auto","created_at":"2025-08-07 07:20:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4837774,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7095588/v1/6221cd65-6130-4509-934e-08c5ca3ce1e9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of biological individuality in periodontitis patients using a specific algorithm and the Salus method","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePeriodontitis is a chronic, multifactorial inflammatory disease that affects the supporting structures of the teeth, including the gingiva, periodontal ligament, and alveolar bone. Its primary etiological factor is the subgingival dental biofilm in dysbiosis, which elicits a host inflammatory response. In genetically susceptible individuals, this response may lead to irreversible destruction of periodontal tissues\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Clinically, periodontitis is characterized by gingival inflammation, bleeding on probing, periodontal pockets ≥ 4 mm, clinical attachment loss, tooth mobility, and radiographic evidence of alveolar bone loss\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn the United States, approximately 47% of individuals aged 30 or older present some degree of periodontitis. Severe forms—Stages III and IV, Grades B and C—affect around 11% of the global population, corresponding to more than 743\u0026nbsp;million people\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Diagnosis is primarily clinical, based on probing depth, bleeding on probing, and attachment loss. Although these parameters help classify disease severity, they do not necessarily reflect current disease activity, which is more accurately assessed by bleeding on probing and the presence of pockets ≥ 4 mm in at least two non-adjacent interproximal sites. Radiographic evaluation is essential for detecting and classifying alveolar bone loss\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe current classification system defines four stages of periodontitis: Stage I - interproximal attachment loss of 1 to 2 mm; Stage II − 3 to 4 mm; Stage III - ≥ 5 mm with up to four teeth lost due to periodontitis; Stage IV - ≥ 5 mm with five or more teeth lost. Disease progression is categorized into three grades: Grade A - slow (no attachment loss in the past five years); Grade B - moderate (\u0026lt; 2 mm in five years); Grade C – rapid progression (≥ 2 mm in five years)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In addition to local factors such as subgingival biofilm dysbiosis, systemic and genetic influences play a critical role. Polymorphisms in genes associated with the inflammatory response, including IL-6 and TNF-α, have been linked to increased susceptibility\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Furthermore, growing evidence suggests associations between periodontitis and non-communicable chronic diseases - such as diabetes, cardiovascular, respiratory, and neurodegenerative diseases - through mechanisms involving low-grade systemic inflammation\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDermatoglyphics, the study of epidermal ridge patterns, is a well-established method in forensic science due to the uniqueness and permanence of fingerprints, which are formed during intrauterine development. With technological advances such as neural networks and specialized software, dermatoglyphics has expanded into phenotype reconstruction and population studies, proving valuable in determining sex, ancestry, and other traits\u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Fingerprint patterns develop between the 12th and 20th weeks of gestation under genetic control, but are also influenced by biochemical factors such as oxygenation, hormones levels, substance exposure, and gestational stress\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Owing to their ectodermal origin - shared with dental enamel and nervous tissue - dermatoglyphic variations have been explored as potential markers for systemic and dental conditions\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Mathematical models such as Turing’s reaction-diffusion theory describe fingerprint formation through molecular signaling involving EDAR, WNT, and BMP, which influence ridge and furrow patterning\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eUntil the 1990s, dermatoglyphic analysis was performed manually using ink, paper, and magnifying lenses - a process susceptible to human error. The advent of computerized systems, such as the Salus method, has revolutionized fingerprint analysis through encrypted digital scanning and proprietary software, enabling precise, automated identification of ridge counts and pattern types. Validated in 2008, the Salus method has compiled an international database of over 14,000 fingerprints from athletes and generates biometric reports predicting physical and neuromotor traits - such as strength, speed, endurance, agility, and coordination - expressed in percentiles\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOriginally initially developed for forensic and athletic profiling, dermatoglyphics has recently gained attention in clinical research, particularly for identifying non-invasive biomarkers of multifactorial diseases with a genetic component. Associations have been reported between fingerprint patterns and dental conditions, including dental caries and periodontitis\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Veeresh et al.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e observed a predominance of ulnar loops (UL) in individuals with caries and whorls (W) in caries-free subjects. Similarly, Vaidya et al.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e found a higher frequency of whorl patterns among individuals with periodontitis. Whorl-type patterns have been found in up to 74.5% of affected individuals, while radial loops (RL) and arches (A) were more common in healthy subjects\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eGiven that both periodontitis and dermatoglyphic traits are influenced by genetic and early developmental factors, fingerprint analysis may reveal phenotypic expressions of inherited susceptibility. Periodontitis risk may thus reflect genetically modulated immune responses to dysbiotic bacterial challenge\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Despite growing scientific interest, dermatoglyphics remains underexplored in dentistry. Investigating the relationship between fingerprint patterns and periodontitis may offer a promising non-invasive approach to identifying genetic biomarkers of individual susceptibility. This could contribute to a better understanding of the genetic and epigenetic mechanisms underlying periodontal disease and inform preventive and diagnostic strategies. In this context, dermatoglyphic analysis may become a valuable tool for personalized dentistry, particularly in settings where direct genetic testing is not feasible.\u003c/p\u003e\u003cp\u003eThis study aimed to evaluate whether validated computerized dermatoglyphic analysis can identify fingerprint patterns associated with periodontitis, and to assess its potential as a non-invasive tool for disease screening, risk stratification, and identification of phenotypic markers linked to genetic susceptibility. The study tested the null hypothesis that there is no statistically significant association between dermatoglyphic fingerprint pattern and the presence of periodontitis.\u003c/p\u003e"},{"header":"Material and Method","content":"\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis study was approved by the Institutional Ethics committee of the Federal University of Goiás (#45344721.5.0000.5083). All participants, or their legal guardians, provided written informed consent. All procedures were conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSample size calculation\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSample size was determined based on literature data and pilot studies, considering a 5% significance level. For the variable \"number of ridges\" on the right thumb (fist right digit; R1D), a minimal detectable difference of 1 unit between case and control groups yielded an estimated statistical power of 22.3%. Assuming a 3-unit difference, statistical power increased substantially to 94.7%, demonstrating high sensitivity for detecting large effects. The final sample included 62 individuals with periodontitis and 95 periodontally healthy controls. This sample size provided an estimated power of 63% for a 1-unit difference and 96.7% for a 3-unit difference between the groups. All calculations were performed using the PSS Health software (Power and Sample Size for Health Researchs; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/\u003c/span\u003e\u003cspan address=\"https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), ensuring methodological rigor and appropriate planning for statistical analyses.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSample selection\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe study sample consisted of 157 adult participants of both sexes (85 men and 72 women), comprising 62 individuals clinically diagnosed with periodontitis and 95 periodontally healthy controls. Inclusion criteria included age over 30 years, the presence of at least 20 teeth, and no indication for tooth extraction. Exclusion criteria included pregnancy, the absence of one or more fingerprints, and any condition (e.g., scarring) that interfered with fingerprint registration.\u003c/p\u003e\u003cp\u003eParticipants were allocated to the periodontitis group based on the presence of clinical attachment loss (CAL) at two or more non-adjacent interproximal sites, or CAL ≥ 4 mm on buccal or lingual (palatal) surfaces, along with probing pockets depths ≥ 4 mm in at least two teeth.\u003c/p\u003e\u003cp\u003eData collection procedures and periodontal examinations were performed at the university dental clinics by a periodontics specialist. Fingerprint collection was conducted by a physiotherapist trained in the Salus method. Both professionals were previously calibrated using 10% of the study sample to ensure procedural reliability.\u003c/p\u003e\u003cp\u003e\u003cem\u003ePeriodontal Status Assessment\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePeriodontal evaluation was performed using a UNC-15 periodontal probe (PC-PUNC, Hu-Friedy, Chicago, IL, USA), with 1 mm gradations, following a rapid probing protocol. Periodontal status was classified according to the criteria proposed by Caton et al.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, as follows: Periodontal health: probing depth ≤ 3 mm and bleeding on probing (BoP) in \u0026lt; 10% of sites; Gingivitis: probing depth ≤ 3 mm with BoP ≥ 10% of sites; Periodontitis: detectable interproximal CAL at two or more non-adjacent interproximal sites; or buccal/ lingual(palatal) CAL ≥ 4 mm with PPD ≥ 4 mm in two or more teeth, excluding non-periodontitis-related causes such as: traumatic gingival recession, cervical caries, distal loss associated with third molar malposition or extraction, endodontic-periodontal lesions, or vertical root fractures\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eParticipants were then classified as periodontitis cases or as control (periodontally healthy or with gingivitis) prior to fingerprint data collection.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFingerprint Collection\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFingerprint patterns were analyzed using the Salus method, which incorporates both qualitative and quantitative dermatoglyphic characteristics. Qualitative features included the fingerprint pattern type: Arch, Loop, or Whorl. Quantitative parameters included ridge count (RC) per finger, combined ridge count for both hand (RCBH), and number of deltas (ND).\u003c/p\u003e\u003cp\u003eFingerprint images was obtained at the dental clinic using a Watson Mini scanner (model IBNW121), following participant classification. This scanner includes proprietary software for image processing (noise reduction, enhancement), pattern recognition, storage, and statistical reporting, as proposed by Nodari-Junior\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eImage interpretation was conducted using Salus Science software, version 5.1 (serial number 23520000 − 17005000). The system automatically removed noise, preprocessed images, and integrated with Salus Coleta software for advanced analysis. Following image capture, the user manually defined core and delta points; the software then traced the Galton Line and computed ridge count via specific algorithms.\u003c/p\u003e\u003cp\u003eThe Salus Science software was developed in Object Pascal (Delphi 7) with a Firebird database management system (DBMS), ensuring data security and operational stability. The scanning process followed a standardized order, starting with the left little finger and progressing sequentially to the right little finger (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA to E).\u003c/p\u003e\u003cp\u003e\u003cem\u003eStatistical Data Analysis\u003c/em\u003e\u003c/p\u003e\u003cp\u003eData were initially organized in Microsoft Excel (version 2505; Microsoft Corporation, Richmond, WA, USA) and to SPSS version 20.0 (Statistical Package for the Social Sciences; IBM, Armonk, NY, USA) for statistical analysis. The Kolmogorov-Smirnov test was used to assess the normality of quantitative variables. Normally distributed variables were reported as mean and standard deviation, and non-normally distributed variables as median and interquartile range.\u003c/p\u003e\u003cp\u003eGroups comparisons of quantitative variables (e.g., ridge count) were conducted using Student’s t-test (for normally distributed data) or Mann-Whitney U test (for skewed data). Analyses included total ridge count for each finger — ridge count of the first digit of the left hand (RC1DLH), index (RC2DLH), middle (RC3DLH), ring (RC4DLH), and little finger (RC5DLH), as well as the total ridge count for the left hand (TRCLH); for the right hand: ridge count of the first digit right hand (RC1DRH), index (RC2DRH), middle (RC3DRH), ring (RC4DRH), and little finger (RC5DRH), the total ridge count for the right hand (TRCRH), the combined ridge count for both hands (RCBH), and the total number of deltas (ND).\u003c/p\u003e\u003cp\u003eQualitative variables, including Arch (A), radial loop (RL), ulnar loop (UL), Whorl (W), and S-shaped Whorl (WS), as well as the fingerprint pattern of each finger (left hand: L1D to L5D; right hand: R1D to R5D) were expressed as frequencies and percentages. Associations between fingerprint pattern and periodontal status were evaluated using Fisher’s exact test. A significant level of p \u0026lt; 0.05 was adopted for all analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe results revealed a high degree of similarity between individuals with and without periodontitis regarding dermatoglyphic characteristics (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e to \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e to \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). No statistically significant differences were observed in anthropometric variables such as weight, height, sex. However, the mean age was significantly higher in the periodontitis group compared to the control group (53.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4 years vs. 48.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3 years; p\u0026thinsp;=\u0026thinsp;0.004) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnthropometric and demographic characteristics of individuals with and without periodontitis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeriodontitis (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight (Kg; mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75.9\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.212*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight (meter; mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.780*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.315**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55 (57.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (51.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (42.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years; mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eSD \u0026ndash; standard deviation. *Student\u0026rsquo;s t-test for independent samples; Fisher\u0026rsquo;s exact test).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of fingerprint pattern types by finger position in the periodontitis group.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRL n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUL n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eW n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWS n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55 (88.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (64.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17 (27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (8.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (61.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12 (19.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 (9.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (41.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23 (37.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (8.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (51.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12 (19.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16 (25.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 (25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16 (25.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (35.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19 (30.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (11.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (69.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11 (17.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (8.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27 (43.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52 (83.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7 (11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eL5D \u0026ndash; Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D \u0026ndash; Right 1th digit; R2D \u0026ndash; Right 2th digit; R3D \u0026ndash; Right 3th digit; R4D \u0026ndash; Right 4th digit; R5D \u0026ndash; Right 5th digit; A \u0026ndash; arch; RL \u0026ndash; radial loop; UL \u0026ndash; ulnar loop; W \u0026ndash; whorl; WS \u0026ndash; whorl.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescription of ridge counts, delta counts, and finger positions in the periodontitis group.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRidge count\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eDelta numbers n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55 (88.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7 (11.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (64.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22 (35.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (62.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 (29.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (45.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (51.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (45.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridges count of the left hand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55.5\u0026thinsp;\u0026plusmn;\u0026thinsp;21.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32 (51.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35 (56.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26 (41.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44 (71.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 (25.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (45.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52 (83.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9 (14.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridges count of the right hand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.2\u0026thinsp;\u0026plusmn;\u0026thinsp;20.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridges\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e113.7\u0026thinsp;\u0026plusmn;\u0026thinsp;40.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal deltas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eSD - standard deviation; L5D \u0026ndash; Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D \u0026ndash; Right 1th digit; R2D \u0026ndash; Right 2th digit; R3D \u0026ndash; Right 3th digit; R4D \u0026ndash; Right 4th digit; R5D \u0026ndash; Right 5th digit.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of predominant fingerprint pattern types by finger position in the control group (n\u0026thinsp;=\u0026thinsp;95).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRL n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUL n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eW n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWS n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78 (82.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (5.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (58.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34 (35.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72 (75.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11 (11.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (4.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 (16.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11 (11.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50 (52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15 (15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26 (27.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (29.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18 (18.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (44.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30 (31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (7.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71 (74.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13 (13.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41 (43.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e77 (81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (1.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eL5D \u0026ndash; Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D \u0026ndash; Right 1th digit; R2D \u0026ndash; Right 2th digit; R3D \u0026ndash; Right 3th digit; R4D \u0026ndash; Right 4th digit; R5D \u0026ndash; Right 5th digit; A \u0026ndash; arch; RL \u0026ndash; radial loop; UL \u0026ndash; ulnar loop; W \u0026ndash; whorl; WS \u0026ndash; whorl.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescription of ridge counts, delta counts, and finger positions in the control group (n\u0026thinsp;=\u0026thinsp;95).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRidge count\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eDelta numbers n(%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e79 (83.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13 (13.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (58.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37 (39.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (76.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15 (15.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65 (68.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27 (28.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41 (43.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridge count of the left hand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56.4\u0026thinsp;\u0026plusmn;\u0026thinsp;23.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47 (49.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46 (48.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (56.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37 (39.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (76.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17 (17.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45 (47.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80 (84.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11 (11.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridges count of the right hand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56.2\u0026thinsp;\u0026plusmn;\u0026thinsp;21.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridges\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112.6\u0026thinsp;\u0026plusmn;\u0026thinsp;43.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal deltas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eSD - standard deviation; L5D \u0026ndash; Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D \u0026ndash; Right 1th digit; R2D \u0026ndash; Right 2th digit; R3D \u0026ndash; Right 3th digit; R4D \u0026ndash; Right 4th digit; R5D \u0026ndash; Right 5th digit.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of qualitative fingerprint pattern types by finger position between the periodontitis and control groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e\u003cp\u003ePeriodontitis (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP Value*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eW\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eUL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eW\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eWS\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55(88.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1(1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e78(82.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e8(8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e5(5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.707\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40(64.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17(27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5(8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2(2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e56(58.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e34(35.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e3(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.273\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5(8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38(61.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12(19.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6(9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7(7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1(1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e72(75.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e11(11.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e4(4.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7(11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26(41.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23(37.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5(8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e19(20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e46(48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e16(16.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e11(11.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.060\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32(51.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12(19.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16(25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2(2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2(2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e50(52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e15(15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e26(27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.847\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR1D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30(48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16(25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16(25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2(2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1(1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e46(48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e28(29.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e18(18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.704\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13(21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22(35.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19(30.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7(11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4(4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e12(12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e42(44.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e30(31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e7(7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.461\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR3D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43(69.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11(17.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5(8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5(5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2(2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e71(74.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e13(13.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e4(4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.768\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33(53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27(43.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2(2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e48(50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e41(43.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e4(4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.908\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR5D n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52(83.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7(11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4(4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e77(81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e10(10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1(1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.518\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\u003cp\u003e*Fisher\u0026rsquo;s exact test; L5D \u0026ndash; Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D \u0026ndash; Right 1th digit; R2D \u0026ndash; Right 2th digit; R3D \u0026ndash; Right 3th digit; R4D \u0026ndash; Right 4th digit; R5D \u0026ndash; Right 5th digit; A \u0026ndash; arch; RL \u0026ndash; radial loop; UL \u0026ndash; ulnar loop; W \u0026ndash; whorl; WS \u0026ndash; whorl.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of quantitative fingerprint variables (ridge and delta counts) by finger position between the periodontitis and control groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeriodontitis (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP value*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.592\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.827\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.481\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.801\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.841\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridge count of the left hand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55.5\u0026thinsp;\u0026plusmn;\u0026thinsp;21.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56.4\u0026thinsp;\u0026plusmn;\u0026thinsp;23.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.811\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.241\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.708\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.523\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.576\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal count of the right hand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.2\u0026thinsp;\u0026plusmn;\u0026thinsp;20.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56.2\u0026thinsp;\u0026plusmn;\u0026thinsp;21.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.568\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal ridges\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e113.7\u0026thinsp;\u0026plusmn;\u0026thinsp;40.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e112.6\u0026thinsp;\u0026plusmn;\u0026thinsp;43.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.873\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal deltas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.290\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;standart deviation; *Student t test for independent samples; L5D \u0026ndash; Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D \u0026ndash; Right 1th digit; R2D \u0026ndash; Right 2th digit; R3D \u0026ndash; Right 3th digit; R4D \u0026ndash; Right 4th digit; R5D \u0026ndash; Right 5th digit.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of delta counts by finger position between the periodontitis and control groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDelta numbers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003ePeriodontitis (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP value*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55 (88.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e79 (83.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e13 (13.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.426\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (64.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (35.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e56 (58.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e37 (39.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39 (62.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (29.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e73 (76.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e15 (15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (45.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e65 (68.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e27 (28.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 (51.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (45.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e52 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e41 (43.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.863\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR1D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (51.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e47 (49.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e46 (48.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.671\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (56.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (41.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e54 (56.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e37 (39.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.754\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (71.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e73 (76.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e17 (17.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.479\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR4D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (45.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48 (50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e45 (47.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.943\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR5D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (83.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (14.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e80 (84.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e11 (11.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.669\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eData presented as n(%); *Fisher\u0026rsquo;s Exact Test; L5D \u0026ndash; Left 5th digit; L4D - Left 4th digit; L3D - Left 3th digit; L2D - Left 2th digit; L1D - Left 1th digit; R1D \u0026ndash; Right 1th digit; R2D \u0026ndash; Right 2th digit; R3D \u0026ndash; Right 3th digit; R4D \u0026ndash; Right 4th digit; R5D \u0026ndash; Right 5th digit.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative analysis of fingerprint pattern frequency between the periodontitis and control groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeriodontitis (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP value*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eW\u0026thinsp;+\u0026thinsp;WS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1-6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.431\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.800\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0-1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.466\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUL\u0026thinsp;+\u0026thinsp;RL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (3.8-9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (5\u0026ndash;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.609\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.663\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (3.8-9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (5\u0026ndash;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.748\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eData presented as median (interquartile range); *Mann-Whitney U test.; A \u0026ndash; arch; RL \u0026ndash; radial loop; UL \u0026ndash; ulnar loop; W \u0026ndash; whorl; WS \u0026ndash; S-whorl\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn terms of fingerprint pattern distribution, the ulnar loop (UL) was the most prevalent pattern across all fingers, followed by the whorl (W), particularly in digits L2D, R2D, L4D, and R4D, where its frequency exceeded 30% (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Both groups presented similar mean ridge counts per finger, ranging from 9.3 to 15.2. The average total ridged count was 113.7 in the periodontitis group and 112.6 in the control group. In both groups, fingerprints typically displayed one delta per finger, consistent with the predominance of loop-type patterns (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eComparative analysis between the groups showed no statistically significant differences in the distribution of fingerprint pattern types (W, WS, UL, RL, A), nor in the total number of ridges or deltas (Tables\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e to \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Median values and interquartile ranges further reinforced the absence of group-specific dermatoglyphic distinctions.\u003c/p\u003e\u003cp\u003eFigures \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB illustrate the dominant frequency of the UL across groups, while Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays overlapping mean values and standard deviations for total ridge and delta counts between periodontitis and control participants. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents boxplots showing the distributions of fingerprint patterns, again confirming no statistically significant differences in any dermatoglyphic category between the two groups.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe comparative analysis between individuals with and without periodontitis revealed no statistically significant differences in demographic and anthropometric variables\u0026mdash;such as weight, height, and sex\u0026mdash;except for age, which was higher in the periodontitis group. This demographic similarity suggests that the groups were adequately matched, strengthening the validity of the comparisons. Regarding dermatoglyphic characteristics, both groups showed a predominance of ulnar loop (UL) patterns, followed by whorls (W), especially on digits L2D, R2D, L4D, and R4D. S-shaped whorls, radial loops, and arches were less frequent. However, there were no statistically significant differences in the distribution of pattern types between the groups. Quantitative analysis also revealed similar results: mean ridge and delta counts per finger, per hand, and per individual were nearly identical in both groups. The similarity of medians and interquartile ranges further supports the absence of meaningful differences. These findings indicate that dermatoglyphic patterns\u0026mdash;whether qualitative or quantitative\u0026mdash;do not appear to be directly associated with the presence of periodontitis. Accordingly, the null hypothesis of this study, which stated that there would be no significant association between fingerprint patterns and the presence of periodontitis, was accepted.\u003c/p\u003e\u003cp\u003eThis study utilized a validated and advanced methodology based on the Salus method, which offers substantial improvements over traditional ink-based techniques. The use of encrypted digital scanner combined with specialized software enabled precise, automated and standardized identification of fingerprint types and ridge counts. This not only improves diagnostic precision but also enhances data reliability and reproducibility\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, critical factors in studies involving phenotypic markers of multifactorial diseases. In addition, digital methods offer advantages such as speed, secure data storage, integration with clinical databases, and applicability in large-scale or forensic research\u003csup\u003e7\u0026ndash;10,19\u0026minus;21\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe absence of significant differences in ridge counts, especially in key digits such as the thumb (RC1DLH) and little finger (RC5DLH), as well as in the total ridge count per hand (RCBH and TRCLH), corroborates the idea that dermal ridges remain stable throughout life, even in the presence of chronic inflammatory conditions like periodontitis\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Similarly, the uniformity in delta counts across groups reinforces the morphological stability of these features.\u003c/p\u003e\u003cp\u003eFingerprints are formed between the 12th and 20th weeks of intrauterine development and are shaped by a combination of genetic and epigenetic influences\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Turing\u0026rsquo;s reaction-diffusion models explain this process through the spatial organization of biochemical signals, leading to distinct yet stable biological patterns. Because fingerprints are genetically encoded and not subject to modification by environmental factors after their formation, they may be limited in reflecting acquired conditions such as periodontitis.\u003c/p\u003e\u003cp\u003eAlthough several studies have reported associations between dermatoglyphic patterns and clinical conditions\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, the literature remains inconclusive. For example, Somani et al.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e observed a higher prevalence of whorl patterns in children with cerebral palsy and dental caries, while Singh et al.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e noted specific dermatoglyphic trends in girls with caries. In orthodontics, Belludi et al.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e identified distinct fingerprint distributions in children with Class III malocclusion. However, not all studies found significant differences in quantitative variables. Vaidya et al.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and Kumar et al.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e suggested that whorls and spirals may be more frequent in localized or aggressive periodontitis, while arches were associated with advanced stages. Nonetheless, such associations were not observed in the present study.\u003c/p\u003e\u003cp\u003eIn contrast to these findings, the present study identified no significant differences in fingerprint pattern types (UL, W, WS, RL, A), ridge counts, or delta counts between groups. These results indicate that dermatoglyphics, when analyzed in isolation, has low sensitivity for detecting phenotypic changes associated with acquired chronic diseases such as periodontitis\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. This reinforces the understanding that fingerprints, as genetically programmed and developmentally fixed traits, are not modified by the inflammatory or degenerative processes involved in periodontal disease.\u003c/p\u003e\u003cp\u003eOther studies have similarly reported limited diagnostic value of dermatoglyphics for certain morphofunctional and systemic conditions. Eslami et al.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e found minimal differences in fingerprint traits across skeletal malocclusion types. Harini et al.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e observed no correlation between fingerprint types and primary canine relationships. Jeddy et al.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e reported no significant association between fingerprint patterns and diabetes, although lip prints were found to be more predictive. These findings underscore the limitations of dermatoglyphics as a standalone diagnostic tool and highlight the need for integrative approaches.\u003c/p\u003e\u003cp\u003eThe application of an innovative and validated digital method in this study, based on the work of Nodari-J\u0026uacute;nior et al.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, improved the quality and reproducibility of dermatoglyphic data\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. However, the absence of statistically significant associations may reflect the multifactorial and complex nature of periodontitis itself. This disease results from an intricate interplay of microbial, immunoinflammatory, behavioral, and genetic factors\u0026mdash;many of which cannot be captured by static morphological markers such as fingerprints\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile dermatoglyphics offers advantages such as non-invasiveness, low cost, and embryological relevance, its diagnostic value for acquired chronic diseases appears limited. Still, its potential may be enhanced when integrated with clinical, genetic, and environmental data. Multimodal approaches\u0026mdash;combining dermatoglyphics with salivary biomarkers, genomic profiles, or imaging data\u0026mdash;could provide a more comprehensive risk assessment model for periodontal disease\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDermatoglyphics continues to be a valuable tool in forensic science, particularly in adverse contexts involving decomposition or natural disasters. Its stability and uniqueness are due to its embryonic origin shared with dental enamel and nervous system structures\u003csup\u003e\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. However, its role in clinical diagnosis must be contextualized within a broader framework of risk markers\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFuture studies should employ larger, more diverse samples and standardized methodologies, while exploring associations between dermatoglyphics and other markers of systemic or oral diseases. The integration of the Salus method with additional clinical parameters may enhance its relevance in identifying predispositions or contributing to individualized health profiles.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eBased on the methodology applied in this study, no statistically significant association was identified between dermatoglyphic patterns\u0026mdash;either qualitative or quantitative\u0026mdash;and the clinical presence of periodontitis. Although fingerprints and dental structures share a common genetic and embryonic origin, the findings do not support the existence of a distinct dermatoglyphic profile among individuals with periodontitis. The predominance of ulnar loop (UL) patterns and the similarity in ridge and delta counts between groups suggest the absence of phenotypic distinctions related to the disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funds were received in support of this work. No benefits in any form have been or will be received from any commercial party related directly or indirectly to the subject of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL\u0026aacute;zaro Gutto Fonseca V\u0026eacute;ras: Conceptualization, Methodology, Formal analysis, Investigation, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVirg\u0026iacute;lio Roriz: Software, Methodology, Conceptualization, Formal analysis, Investigation, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRudy Nodari Junior: Software, Formal analysis, Investigation, Visualization.\u003c/p\u003e\n\u003cp\u003eKarolina Kellen Matias: Formal analysis, Investigation, Visualization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLucas Rodrigues de Ara\u0026uacute;jo Estrela: Formal analysis, Investigation, Visualization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCarlos Estrela: Software, Methodology, Conceptualization, Formal analysis, Investigation, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003eL\u0026aacute;zaro Gutto Fonseca V\u0026eacute;ras PT, MSc, PhD,\u003cimg width=\"16\" height=\"16\" src=\"data:image/png;base64,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\" alt=\"image\"\u003e\u0026nbsp;https://orcid.org/0000-0002-9428-4424\u003c/p\u003e\n\u003cp\u003eVirg\u0026iacute;lio Roriz DDS, MSc, PhD,\u003cimg width=\"16\" height=\"16\" src=\"data:image/png;base64,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\" alt=\"image\"\u003e\u0026nbsp;https://orcid.org/0000-0003-2028-164X\u003c/p\u003e\n\u003cp\u003eRudy Jos\u0026eacute; Nodari Junior PT, MSc, PhD,\u003cimg width=\"16\" height=\"16\" src=\"data:image/png;base64,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\" alt=\"image\"\u003e\u0026nbsp;https://orcid.org/0000-0002-8375-657X\u003c/p\u003e\n\u003cp\u003eKarolina Kellen DDS, MSc, PhD,\u003cimg width=\"16\" height=\"16\" src=\"data:image/png;base64,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\" alt=\"image\"\u003e\u0026nbsp;http://orcid.org/0000-0002-4527-1467\u003c/p\u003e\n\u003cp\u003eLucas Rodrigues de Ara\u0026uacute;jo Estrela DDS, MSc,\u003cimg width=\"16\" height=\"16\" src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAA2ZpVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADw/eHBhY2tldCBiZWdpbj0i77u/IiBpZD0iVzVNME1wQ2VoaUh6cmVTek5UY3prYzlkIj8+IDx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6bWV0YS8iIHg6eG1wdGs9IkFkb2JlIFhNUCBDb3JlIDUuMC1jMDYwIDYxLjEzNDc3NywgMjAxMC8wMi8xMi0xNzozMjowMCAgICAgICAgIj4gPHJkZjpSREYgeG1sbnM6cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1zeW50YXgtbnMjIj4gPHJkZjpEZXNjcmlwdGlvbiByZGY6YWJvdXQ9IiIgeG1sbnM6eG1wTU09Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC9tbS8iIHhtbG5zOnN0UmVmPSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvc1R5cGUvUmVzb3VyY2VSZWYjIiB4bWxuczp4bXA9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8iIHhtcE1NOk9yaWdpbmFsRG9jdW1lbnRJRD0ieG1wLmRpZDo1N0NEMjA4MDI1MjA2ODExOTk0QzkzNTEzRjZEQTg1NyIgeG1wTU06RG9jdW1lbnRJRD0ieG1wLmRpZDozM0NDOEJGNEZGNTcxMUUxODdBOEVCODg2RjdCQ0QwOSIgeG1wTU06SW5zdGFuY2VJRD0ieG1wLmlpZDozM0NDOEJGM0ZGNTcxMUUxODdBOEVCODg2RjdCQ0QwOSIgeG1wOkNyZWF0b3JUb29sPSJBZG9iZSBQaG90b3Nob3AgQ1M1IE1hY2ludG9zaCI+IDx4bXBNTTpEZXJpdmVkRnJvbSBzdFJlZjppbnN0YW5jZUlEPSJ4bXAuaWlkOkZDN0YxMTc0MDcyMDY4MTE5NUZFRDc5MUM2MUUwNEREIiBzdFJlZjpkb2N1bWVudElEPSJ4bXAuZGlkOjU3Q0QyMDgwMjUyMDY4MTE5OTRDOTM1MTNGNkRBODU3Ii8+IDwvcmRmOkRlc2NyaXB0aW9uPiA8L3JkZjpSREY+IDwveDp4bXBtZXRhPiA8P3hwYWNrZXQgZW5kPSJyIj8+84NovQAAAR1JREFUeNpiZEADy85ZJgCpeCB2QJM6AMQLo4yOL0AWZETSqACk1gOxAQN+cAGIA4EGPQBxmJA0nwdpjjQ8xqArmczw5tMHXAaALDgP1QMxAGqzAAPxQACqh4ER6uf5MBlkm0X4EGayMfMw/Pr7Bd2gRBZogMFBrv01hisv5jLsv9nLAPIOMnjy8RDDyYctyAbFM2EJbRQw+aAWw/LzVgx7b+cwCHKqMhjJFCBLOzAR6+lXX84xnHjYyqAo5IUizkRCwIENQQckGSDGY4TVgAPEaraQr2a4/24bSuoExcJCfAEJihXkWDj3ZAKy9EJGaEo8T0QSxkjSwORsCAuDQCD+QILmD1A9kECEZgxDaEZhICIzGcIyEyOl2RkgwAAhkmC+eAm0TAAAAABJRU5ErkJggg==\" alt=\"image\"\u003e\u0026nbsp;http://orcid.org/0000-0003-1244-4015\u003c/p\u003e\n\u003cp\u003eCarlos Estrela, DDS, MSc, PhD,\u003cimg width=\"16\" height=\"16\" src=\"data:image/png;base64,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\" alt=\"image\"\u003ehttp://orcid.org/0000-0002-1488-0366\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKwon, T., Lamster, I. 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Kristine Bonnevie's theories on the genetics of fingerprints, and their application in Germany. \u003cem\u003eStud. Hist. Philos. Sci.\u003c/em\u003e \u003cb\u003e92\u003c/b\u003e, 162\u0026ndash;176 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGonz\u0026aacute;lez, M., Gorziza, R. P., De C\u0026aacute;ssia Mariotti, K. \u0026amp; Pereira, L. R. Methodologies Applied to Fingerprint Analysis. \u003cem\u003eJ. Forensic Sci.\u003c/em\u003e \u003cb\u003e65\u003c/b\u003e (4), 1040\u0026ndash;1048 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlau, S., Graham, J., Smythe, L. \u0026amp; Rowbotham, S. Human identification: a review of methods employed within an Australian coronial death investigation system. \u003cem\u003eInt. J. Legal Med.\u003c/em\u003e \u003cb\u003e135\u003c/b\u003e (1), 375\u0026ndash;385 (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Computerized dermatoglyphics, fingerprints, Salus method, periodontitis, Science software","lastPublishedDoi":"10.21203/rs.3.rs-7095588/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7095588/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePeriodontitis is a multifactorial inflammatory disease associated with the accumulation of dysbiotic biofilm, primarily affecting adults and potentially leading to the progressive destruction of periodontal tissues. The Salus method utilizes validated computerized dermatoglyphics for biometric fingerprint evaluation, processed through a specific algorithm integrated into the Science software. This study aimed to investigate whether individuals with a clinical diagnosis of periodontitis, exhibit specific dermatoglyphic patterns identifiable through this algorithm. A total of 157 participants were evaluated, with a mean age of 53.7 years, including 62 individuals diagnosed with periodontitis (stages III and IV) and 95 periodontally healthy (control group). Periodontal status was assessed through clinical probing, and fingerprint data were collected via digital scanning using the Salus method. The images were processed by the algorithm, which performed noise reduction, pattern recognition (type, core, and delta), Galton line tracing, and ridge count calculations for each finger. Statistical analysis included the Kolmogorov-Smirnov test, Student\u0026rsquo;s t-test, Mann-Whitney test, and Fisher\u0026rsquo;s exact test, with a significance level set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Results revealed no statistically significant differences between the groups in either qualitative or quantitative dermatoglyphic variables. The distribution of fingerprint types (whorls, S-shaped whorl, ulnar loops, radial loops, arches), as well as ridge and delta counts, was comparable across both groups. In clonclusion, no association was found between dermatoglyphic patterns and the presence of periodontitis. Therefore, computerized dermatoglyphics did not demonstrate utility as a standalone biometric marker for identifying or screening for the disease.\u003c/p\u003e","manuscriptTitle":"Assessment of biological individuality in periodontitis patients using a specific algorithm and the Salus method","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 10:32:23","doi":"10.21203/rs.3.rs-7095588/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-06T10:42:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-06T08:14:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-01T17:57:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"17154847887460792626360902957196474977","date":"2025-08-01T16:43:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"164231367911281816217935193976488674593","date":"2025-07-29T04:32:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-29T02:48:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-23T18:05:40+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-17T19:12:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-15T18:12:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-15T16:54:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4a4d7e1d-32e2-4b9f-8560-03f7fe2bfb83","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":52271762,"name":"Health sciences/Biomarkers"},{"id":52271763,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":52271764,"name":"Health sciences/Diseases"},{"id":52271765,"name":"Health sciences/Health care"},{"id":52271766,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-05-12T03:09:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-31 10:32:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7095588","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7095588","identity":"rs-7095588","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}