Sexual dimorphism and topological variability in fingerprint ridge density in a north-west Indian population.

The science of fingerprints is very crucial in criminal investigation as it helps identify perpetrators or victims of a crime. Fingerprint ridge density (FPRD), which refers to the number of ridges within a specific area on the epidermal skin layer of the distal phalanges in humans, has been found to differ between males and females. This study attempts to estimate the sex from FPRD and evaluates the diversity in FPRD across several topological areas. The study involves 208 participants (120 males, 88 females) between the ages 18 to 25 years from a North-west Indian population. Fingerprints were collected, and FPRD was accessed in radial, ulnar, and proximal areas as recommended by Gutierrez-Redomero et al. (Forensic Sci Int 180(1):17-22, 2008). FPRD has been quantified using the techniques described by Acree (Forensic Sci Int 102(1):35-44, 1999). When evaluating FPRD in the lateral pocket loops and twin loops, the proximal-side core was considered. The study reveals that males have a mean fingerprint ridge density of 12.82 ridges/25 mm2 while females have 13.01 ridges/25 mm2. Females have higher fingerprint ridge density solely in the proximal area; males have higher fingerprint ridge density in both radial and ulnar areas. In conclusion, this research underscores the potential of fingerprint ridge density as a parameter for investigating population variations and individual identification. Future studies on fingerprint ridge density in India's diverse population will help establish reference ranges, allowing for sex and likely population group estimation, making it a valuable tool for preliminary examinations and exclusion criteria for sex estimation in crime scene investigations.

Global adoption of facial recognition technology with special reference to India-Present status and future recommendations.

The face is the most essential part of the human body, and because of its distinctive traits, it is crucial for recognizing people. Facial recognition technology (FRT) is one of the most successful and fascinating technologies of the modern times. The world is moving towards contactless FRT after the COVID-19 pandemic. Due to its contactless biometric characteristics, FRT is becoming quite popular worldwide. Businesses are replacing conventional fingerprint scanners with artificial intelligence-based FRT, opening up enormous commercial prospects. Security and surveillance, authentication/access control systems, digital healthcare, photo retrieval, etc., are some sectors where its use has become essential. In the present communication, we presented the global adoption of FRT, its rising trend in the market, utilization of the technology in various sectors, its challenges and rising concerns with special reference to India and worldwide.

ChatGPT: Forensic, legal, and ethical issues.

Artificial intelligence (AI) refers to a group of technologies that enable people to perform a variety of activities, including observing, comprehending, analysing and translating data, among other things. Nowadays, practically every school of thought is interested in AI. One such innovation, a chatbot by the name of ChatGPT (Chat Generative Pre-Trained Transformer), launched by OpenAI recently, has taken the internet by storm. It had one million users within 1 week of its launch. The present communication explores the practicability and versatility of the ChatGPT in forensic examinations and scenarios, and also addresses the ethical and legal issues surrounding its usage. The observations suggest that the said technology, in its current form, has limited relevance in the realm of forensic science and the law. Only human critical thinking, expertise, and practical experience can provide the information and competencies needed in the realms of forensics, research, clinical and legal practices. Thus, the ChatGPT should be used with utmost caution in the disciplines of medicine, forensic science and the law, irrespective of its many positive attributes.

Applicability of the Suchey-Brooks method for age estimation in an Indian population: A computed tomography-based exploration using Bayesian analysis and machine learning.

Age estimation occupies a prominent niche in the identification process. In cases where skeletal remains present for examination, age is often estimated from markers distributed throughout the skeletal framework. Within the pelvis, the pubic symphysis constitutes one of the more commonly utilized skeletal markers for age estimation, with the Suchey-Brooks method comprising one of the more commonly employed methods for pubic symphyseal age estimation. The present study was targeted towards assessing the applicability of the Suchey-Brooks method for pubic symphyseal age estimation, an aspect largely unreported for an Indian population. In order to do so, clinically undertaken pelvic computed tomography scans of individuals were evaluated using the Suchey-Brooks method, and the error associated with the method was established using Bayesian analysis and different machine learning regression models. Amongst different supervised machine learning models, support vector regression and random forest furnished lowest error computations in both sexes. Using both Bayesian analysis and machine learning, lower error computations were observed in females, suggesting that the method demonstrates greater applicability for this sex. Inaccuracy and root mean square error obtained with Bayesian analysis and machine learning illustrates that both statistical modalities furnish comparable error computations for pubic symphyseal age estimation using the Suchey-Brooks method. However, given the numerous advantages associated with machine learning, it is recommended to use the same within medicolegal settings. Error computations obtained with the Suchey-Brooks method, regardless of the statistical modality utilized, indicate that the method should be used in amalgamation with additional markers to garner accurate estimates of age.

Development, detection and decipherment of obfuscated fingerprints in humans: Implications for forensic casework.

Fingerprints have been widely used and accepted as an effective method of human identification. This biometric tool aids in criminal investigations for personal identity for over a century. Whilst the Automatic Fingerprint Identification System (AFIS) has bolstered security efforts, it has also opened doors to potential scams, affecting both civilian and law enforcement operations. Despite extensive research on fingerprint authentication issues, very little attention has been given to addressing the problem of fingerprint alteration or obfuscation. Fraudsters, with the guidance of experts, have developed new techniques to obscure their fingerprints intentionally. Fingerprint obfuscation is the deliberate alteration of fingerprint patterns with the aim of concealing their true identity, raising concerns amongst security and investigative organizations. The objective of the current communication is to highlight the numerous techniques used for obfuscation, forgery and alteration of fingerprints in humans. It further accentuates the need for identification and interpretation of these altered fingerprints and recommends notifying law enforcement agencies of potential threats.

ChatGPT: ethical concerns and challenges in academics and research.

INTRODUCTION: The emergence of artificial intelligence (AI) has presented several opportunities to ease human work. AI applications are available for almost every domain of life. A new technology, Chat Generative Pre-Trained Transformer (ChatGPT), was introduced by OpenAI in November 2022, and has become a topic of discussion across the world. ChatGPT-3 has brought many opportunities, as well as ethical and privacy considerations. ChatGPT is a large language model (LLM) which has been trained on the events that happened until 2021. The use of AI and its assisted technologies in scientific writing is against research and publication ethics. Therefore, policies and guidelines need to be developed over the use of such tools in scientific writing. The main objective of the present study was to highlight the use of AI and AI assisted technologies such as the ChatGPT and other chatbots in the scientific writing and in the research domain resulting in bias, spread of inaccurate information and plagiarism. METHODOLOGY: Experiments were designed to test the accuracy of ChatGPT when used in research and academic writing. RESULTS: The information provided by ChatGPT was inaccurate and may have far-reaching implications in the field of medical science and engineering. Critical thinking should be encouraged among researchers to raise awareness about the associated privacy and ethical risks. CONCLUSIONS: Regulations for ethical and privacy concerns related to the use of ChatGPT in academics and research need to be developed.

Applicability of the six-phase method for auricular age estimation in an Indian population: A CT-based study.

Age estimation plays a crucial role in human identification. Amongst numerous age markers located throughout the skeletal framework, the auricular surface of the ilium presents as a resilient structure, with different methods for auricular age estimation currently in practice. Amongst these methods, the Osborne method is believed to permit accurate age estimation through its use of robust age categories and discrete phase descriptors. The present study aimed to assess the applicability of the Osborne method in an Indian population through a computed tomographic (CT) examination of the auricular surface, an aspect presently unreported. In order to do so, CT scans of 380 individuals were collected and evaluated using the Osborne method. A CT-based examination indicated that surface texture described by Osborne is difficult to appreciate through 3D CT images. Indistinct definitions associated with certain features, and the mosaic display of features within each phase further prevents applying the method effectively. Overall accuracy percentages of 99.47% and 98.90% were obtained using the method in males and females, respectively, with corresponding inaccuracy values of 10.10 years and 9.04 years. Significantly reduced accuracy percentages were obtained with alternate, more robust age brackets presented within the original study, demonstrating the limited reliability associated with the method. Inaccuracy and bias values computed for each decade indicate the relative utility of the method in aging 40-59-year-old individuals. Low accuracy percentages, high error rates and different methodological hindrances encountered within the present study illustrate the limited applicability of the Osborne method in aging an Indian population.

Computed tomographic age estimation from the iliac crest and ischial tuberosity in an Indian population using supervised machine learning approaches.

Within the pelvis the iliac crest and ischial tuberosity display delayed ossification and fusion, thus, presenting as reliable maturity indicators. Amongst the different iliac crest and ischial tuberosity age estimation methods, the modified Kreitner-Kellinghaus stages constitute one of the more promising methods. The present study was directed towards establishing the applicability of the modified Kreitner-Kellinghaus method using five supervised machine learning approaches. Clinical CT scans of consenting individuals were collected and scored using the modified Kreitner-Kellinghaus method for the iliac crest and ischial tuberosity, independently. Age was subsequently estimated using different machine learning models. Cumulative scores computed from both markers were additionally employed for age estimation using machine learning. For iliac crest age estimation, Random Forest and Gradient Boosting Regression furnished lowest mean absolute error (2.42 years) and root mean square error (3.06 years). For ischial tuberosity age estimation, Gradient Boosting Regression garnered the lowest computations of mean absolute error (2.60 years) and root mean square error (3.09 years). For cumulative score based age estimation, Support Vector Regression and Gradient Boosting Regression yielded lowest mean absolute error (2.48 years) and root mean square error (3.07 years). Obtained error computations indicate that the iliac crest is a more accurate age marker in comparison to the ischial tuberosity. Additionally, cumulative score-based approaches garnered similar/ marginally more precise results in comparison to the iliac crest with all five models. This marginal improvement is not sufficient to justify employing the relatively more complicated cumulative score-based approach for age estimation. Hence, whenever available, the iliac crest should be preferred over the ischial tuberosity/ cumulative score-based approaches for age estimation.

Machine learning and regression analysis for age estimation from the iliac crest based on computed tomographic explorations in an Indian population.

Age estimation constitutes an integral parameter of identification. In children, sub-adults, and young adults, accurate age estimation is vital on various aspects of civil, criminal, and immigration law. The iliac crest presents as a suitable age marker within these age cohorts, and the modified Risser method constitutes a relatively novel and unexplored method for iliac crest age estimation. The present study attempted to ascertain the applicability of this modified method for age estimation in the Indian population, an aspect previously unexplored, through computed tomographic examination of the iliac crest. Computed tomography scans of consenting individuals undergoing routine examinations of the pelvis/ abdomen for various clinically indicated reasons were collected and scored using the modified Risser stages. Computed tomographic examinations of the iliac crest indicate that the recalibrated method accurately depicts the temporal progression of ossification and fusion changes. Different regression and machine learning models were subsequently derived and/or trained to evaluate the accuracy and precision associated with the method. Amongst the ten regression models derived herein, compound regression exhibited the lowest inaccuracy (4.78 years) and root mean squared error values (5.46 years). Machine learning yielded further reduced error rates, with decision tree regression achieving inaccuracy and root mean squared error values of 1.88 years and 2.28 years, respectively. A comparative evaluation of error computations obtained from regression analysis and machine learning illustrates the statistical superiority of machine learning for forensic age estimation. Error computations obtained with machine learning suggest that the modified Risser method is capable of permitting reliable age estimation within criminal and civil proceedings.

Bullet Embolization After a Penetrating Gunshot Wound: A Case Report.

Bullet embolization is an uncommon event after a penetrating gunshot wound. This phenomenon can occur in the venous or arterial vasculature, and patients can present with various symptoms. Physicians need to be familiar with the indications to suspect bullet embolization in patients with gunshot wounds to avoid crucial complications. We present two cases of venous bullet embolization following traumatic gunshot injuries. We will review the different types of bullet emboli, complications, and management.

Is it possible to estimate sex from signatures and handwriting? A review of literature, observations, and future perspectives.

Estimation of sex holds great significance in the field of Forensic Science since it helps establish the identity of an individual during a crime scene investigation. Sex differences in human behaviour are the result of natural selection. Sexually dimorphic stimuli of cognitive and behavioural activities may influence the phenotypic expression of our motor skills. Human traits such as signatures and handwriting are phenotypic manifestation of these skills. These phenotypic biological and behavioural traits have inherent sexual dimorphism and may help to identify sex in different circumstances. For instance, to establish the sex of an individual or deceased, forensic samples of the human body such as voice samples, features of fingerprints and footprints, the skeleton, or its remains are helpful. Similarly, the sex of an individual may also be identified from their corresponding handwriting and signature. Handwriting experts can extract peculiar features from handwriting and signatures which could help establish whether the signatures belong to a male or a female. A female writer may have attractive, rounded, upright, tidy, skilled, well-formed strokes, artistic design, better penmanship, and greater length of the signature compared to the signature of a male. Here, we review the studies related to the identification of sex from signatures and handwriting and present inferences about vital features and methods of sex identification through handwriting. These mainly suggest that the accuracy of sex prediction from signature and handwriting ranges from 45 to 80%. We also present writing examples to show sex-based differences in the signature and handwriting of males and females. The female's handwriting is more decorative, arranged, aligned, neat, and clean as compared to that of the male. Based on the writing samples and the review of literature, we suggest that forensic handwriting experts may eliminate suspects based on the sex of the writer, which can simplify the identification process of disputed or questionable signatures and handwriting.

Odontoma and other congenital dental anomalies: Implications for forensic identification.

Forensic odontology plays a crucial role in establishing the identity in mass disasters and criminal cases with high accuracy. Dental anomalies and features help in such situations. Congenital and developmental dental anomalies can be easily documented to establish distinctive and individualistic characteristics of an individual. The location, number of teeth involved, and the type of anomaly vary between individuals. Similarly, dental malformations also assist greatly in the identification process. Many types of dental anomalies have been studied in the past for their individualistic characteristics in forensic examinations. One such dental anomaly is odontoma, which is a benign odontogenic malformation. This malformation may also help in the identification of the deceased, when recorded and examined accurately. An odontome is a malformed teeth-like structures consisting of enamel, dentin, and pulpal tissue, formed due to the growth of completely differentiated epithelial and mesenchymal cells. If antemortem (AM) dental records incorporate information regarding odontomes and other dental anomalies, including in radiographs, orthopantomograms or microradiographs, positive identification may be established by comparison of these records with postmortem (PM) records. In the present communication, a rare case of compound composite odontoma in the anterior mandible with multiple denticles has been discussed with a brief overview of congenital and developmental dental anomalies. The authors emphasize the importance of such rare dental anomalies and malformations which may be used for identifying the deceased in mass disasters and forensic identification.

Fractional Laser Resurfacing for Acne Scars: Our Experience at Tertiary Care Hospital of North India.

Background: Acne is very common among adolescents, which may sometimes persist into adulthood, and acne scars continue to have a profoundly negative impact on quality of life. Of all the various modalities available, fractional lasers have shown effective results. Aims and Objectives: The aim of this study was to assess the efficacy and safety of fractional carbon dioxide (CO2) laser resurfacing in atrophic facial acne scars. Materials and Methods: The study included 104 subjects aged ≥18 years with atrophic acne scars on face of more than 6 months of duration recruited over a period of 1 year. All the patients were treated with fractional CO2 laser (600 W power and wavelength 10,600 nm). Four sessions of fractional CO2 laser resurfacing were done at 6-week intervals in each patient. We compared the improvement rate of scars after every session at 6-week interval, 2 weeks after the last session, and finally 6 months after the last laser session. Results: The difference between the mean baseline score (3.43) and mean final score (1.83) using Goodman and Baron's qualitative scar scale was found to be statistically significant (P = 0.001). Mean improvement increased from first treatment session to the end of the treatment course from 0.56 to 1.62 indicating the role of the number of sessions in the overall improvement of acne scars. With regard to overall satisfaction, maximum number of patients were either very satisfied (55.8%) or satisfied (25%) as compared to those who were only slightly satisfied (11.5%) or completely unsatisfied (7.7%). Conclusion: Fractional ablative laser gives excellent results in the management of acne scars and has emerged as an appealing non-invasive option for this indication. Being a safe and effective option for atrophic acne scar treatment, it can be recommended wherever available.

An evaluation of the Gilbert-McKern pubic symphyseal age estimation method using Bayesian statistics and principal component analysis: A computed tomographic exploration in an Indian population.

Age of an individual constitutes a primary facet of human identification. In cases where skeletal remains present for examination, bony markers distributed throughout the skeletal framework are employed for age estimation. Amongst these markers, the pubic symphysis constitutes one of the more commonly utilized structures. Gilbert-McKern's pubic symphyseal age estimation method was derived to complement the original three component method, and permit accurate age estimation in females. However, subsequent investigations with the Gilbert-McKern method are limited, and completely lacking for an Indian population. In the present study, CT scans of 380 consenting individuals (190 males and 190 females) undergoing CT examinations for therapeutic purposes, aged 10 years and above, were scored according to Gilbert-McKern's three component method. A significant sexual dimorphism was observed with the scoring of the ventral rampart and symphyseal rim. An overall accuracy of 29.50% was obtained in females, indicating that the method lacks forensic utility in its primal form. Highest posterior density and highest posterior density region values were computed for each component using Bayesian analysis in both sexes, to enable age estimation from individual components, whilst overcoming issues of age mimicry. Amongst the three components, symphyseal rim furnished the most accurate and precise estimates of age, whereas the ventral rampart garnered highest error computations, in both sexes. Principal component analysis was utilized for multivariate age estimation by taking into consideration this differential contribution of individual components. Weighted summary age models, derived using principal component analysis, furnished inaccuracy values of 12.19 years and 12.30 years in females and males, respectively. Bayesian error computations obtained with the symphyseal rim in both sexes were even lower than those obtained with weighted summary age models, demonstrating its suitability as an independent age marker. Despite the use of statistical modalities of Bayesian inference and principal component analysis for age estimation, the method did not yield significantly reduced error rates in females, demonstrating its limited forensic applicability. While, statistically significant sex differences were observed with the scoring of Gilbert-McKern's components, concordant correlations, comparable accuracy and absolute error values were obtained for both sexes, indicating that the Gilbert-McKern method can be utilized to age either sex. However, inaccuracy and bias values obtained with different statistical modalities, as well as broad age intervals furnished with Bayesian analysis demonstrate the overall limited applicability of the Gilbert-McKern method in aging males and females of an Indian population.

Age estimation from iliac auricular surface using Bayesian inference and principal component analysis: a CT-based study in an Indian population.

Age estimation constitutes one of the pillars of human identification. The auricular surface of the ilium presents as a durable and robust structure within the human skeletal framework, capable of enabling accurate age estimation in older adults. Amongst different documented auricular age estimation methods, the Buckberry-Chamberlain method offers greater objectivity through its component-based approach. The present study aimed to test the applicability of the Buckberry-Chamberlain method in an Indian population through a CT-based examination of the auricular surface. CT scans of 435 participants undergoing CT examinations following the advice of their treating physicians were scrutinized for different age-related auricular changes. Three of the five morphological features described by Buckberry-Chamberlain could be appreciated on CT scans, and thus further statistical analysis was restricted to these features. Transition analysis coupled with Bayesian inference was undertaken individually for each feature to enable age estimation from individual features, while circumventing age mimicry. A Bayesian analysis of individual features yielded highest accuracy percentages (98.64%) and error rates (12.99 years) with macroporosity. Transverse organization and apical changes yielded accuracy percentages of 91.67% and 94.84%, respectively, with inaccuracy computations of 10.18 years and 11.74 years, respectively. Summary age models, i.e. multivariate age estimation models, derived by taking this differential accuracy and inaccuracy into consideration yielded a reduced inaccuracy value of 8.52 years. While Bayesian analysis undertaken within the present study enables age estimation from individual morphological features, summary age models appropriately weigh all appreciable features to yield more accurate and reliable estimates of age.

An evaluation of the three-component pubic symphyseal human age estimation method: a CT-based exploration in an Indian population.

Age estimation constitutes an important facet of human identification within forensic, bioarchaeological, repatriation, and humanitarian contexts. Within the human skeletal framework, the pubic symphysis comprises one of the more commonly utilized structures for age estimation. The present investigation was aimed at establishing the applicability of the McKern-Stewart pubic symphyseal age estimation method in males and females of an Indian population, an aspect previously unreported. Three hundred and eighty clinical CT scans of the pubic symphysis were collected and scored in accordance with the McKern-Stewart method. An overall accuracy of 68.90% was obtained on applying the method to males, demonstrating a limited applicability of the method in its primal form. Subsequently, Bayesian analysis was undertaken to enable accurate age estimation from individual components in both sexes. Bayesian parameters obtained with females suggest that McKern-Stewart's components fail to accommodate for age-related changes within the female pubic bone. Improved accuracy percentages and reduced inaccuracy values were obtained with Bayesian analysis in males. With females, the error computations were high. Weighted summary age models were utilized for multivariate age estimation, and furnished inaccuracy values of 11.51 years (males) and 17.92 years (females). Error computations obtained with descriptive analysis, Bayesian analysis, and principal component analysis demonstrate the limited applicability of McKern-Stewart's components in generating accurate age profiles for Indian males and females. The onset and progression of age-related changes within the male and female pubic bone may be of interest to biological anthropologists and anatomists involved in exploring the underlying basis for aging.

Ghosting phenomenon in static and dynamic footprints in India and the United States.

Ghosting is the phenomenon that exists when a footprint has a lighter area around the tip of one or more toes or a shadow-like area at the back of the heel. To date, ghosting has been considered primarily a finding of dynamic (walking) footprints, rather than static (standing) footprints. The prevalence of ghosting in static footprints is unknown, and research on its presence in static and dynamic footprints from the same participant is sparse, as are studies on its occurrence in different geographic populations. This study is among the first to evaluate the occurrence of ghosting in the static and dynamic footprints from a particular individual with participants in two geographic populations. A combination of both inkless and ink footprint collection systems were used to obtain a total of 206 bare footprints from 103 adult participants from the United States and India. The data comprised 103 static and 103 dynamic footprints. Ghosting occurred significantly in static footprints, though less frequently than in dynamic footprints. Ghosting in static footprints was seen most often at the first toe, followed by the third and second respectively. This aspect appeared least at the heel. In dynamic footprints, it occurred most at the first toe, followed by the second and fourth toes, and then the third toe and the heel. The prevalence of ghosting in footprints from the United States and India differed in their locations, notably at the first and second toes in the static footprints and at the heel in the dynamic footprints.

Hair Shaft Disorders in Children - An Update.

Disorders of hair shaft are a diverse group of congenital and acquired abnormalities of the hair that can pose a diagnostic and therapeutic challenge to the dermatologists. Hair shaft abnormalities can occur as an isolated phenomenon or can be associated with an underlying genetic syndrome. Any change in the texture, appearance, and growth of the hair should prompt evaluation of the patient for the presence of any hair shaft anomaly. The diagnosis can be suggested by a complete history and physical examination of the hair-bearing areas as well as other ectodermal structures (nails and teeth). A key feature in the evaluation of hair shaft defects is to determine the fragility of the hair shaft that can be elucidated by performing the "tug test." Trichoscopy and light microscopy serve as valuable tools in establishing the specific type of hair shaft disorder. An update of the approach for the diagnosis and management is included in this review.

Methods of forensic facial reconstruction and human identification: historical background, significance, and limitations.

Facial reconstruction is the most frequently used method for human identification in forensic examinations. It is a complex and time-consuming technique and an actively growing field with a wide array of applications. The methods of forensic facial reconstruction are helpful in those cases where other methods of identification are not applicable. Identification of the dead is always a challenging task for forensic teams in cases involving terrorists' attacks and mass disasters where the corpses are fragmented, decomposed, and skeletonized. In such cases, only the skeletal remains and few other clues are available to establish the identity of a person. The progress of facial reconstruction was initiated in the nineteenth century, reconstructing the facial profiles of some famous and rich people. Various novel techniques for facial reconstruction have been devised in the recent past. We conducted literature search, using databases PubMed, Scopus, Web of Science, and ScienceDirect for analyzing different methods developed and practiced till date for human facial reconstruction. We outline the brief history along with a discussion regarding the different methods of forensic facial reconstruction and their limitations. We also discuss future recommendations and preferences for further research in the field of forensic facial reconstruction and human identification.