ABSTRACT
In forensic investigations, semen samples are a common form of biological evidence, especially in cases involving sexual assault. Therefore, accurately estimating the age of an individual is crucial in criminal cases. This study presents a novel age estimation model based on semen-specific CpG methylation patterns. A multiplex panel was developed, consisting of 12 CpG sites (PARP14, C5orf25, cg23488376, MXRA5, PFKFB3, DLL1, NOX4, cg12837463, TTC7B, KCNA7, NKX2-1, and SYNE4), which exhibit strong correlations with age. Additionally, this study investigates the resilience of these methylation markers under simulated environmental challenges. We collected ejaculate samples from a diverse cohort of 115 male individuals, aged 20-71 years, who underwent deoxyribonucleic acid extraction and bisulfite conversion. Methylation levels of the selected CpG sites were assessed using a SNaPshot assay, which revealed significant correlations with chronological age. We developed and validated two robust age estimation models through stepwise and enter regression analyses, achieving reliable accuracy with mean absolute errors ranging from 3.81 to 4.1 years. Additionally, the study also investigated the robustness of semen stains under diverse environmental conditions, including fabric type, washing, hematin exposure, and UV-C light. The selected methylation markers demonstrated remarkable resilience despite the challenges posed by washing procedures and environmental exposure, confirming their potential for age estimation in forensic genetics. This research presents successful age estimation models, emphasizing the strong correlations between methylation levels and chronological age. The proposed methodology's accuracy is affirmed through model validation on an independent test set, while also highlighting the resilience of semen stains on fabrics under varying storage and washing conditions.
ABSTRACT
According to several recent studies, physicians in various medical branches have some differences in attitudes towards transgender and gender-diverse (TGD) persons based on religious or political beliefs. Our study aims to uncover the attitudes of the general physician community in Turkey, which has a youthful profile, regarding TGD individuals. The attitudes towards transgender individuals scale (ATTI) and the general conservatism scale, along with a form that asks about socio-demographic factors, political beliefs, and level of religion, were administered online to physicians. The ATTI score of physicians (mean = 77.8) is favourable and did not vary among branches. Being female, being close to TGD, having left-wing views, low conservatism and low religious belief scores were associated with positive attitudes towards TGD individuals. The physician profile's moderate religious belief and left-wing views can be interpreted as a country-specific dynamic and did not prevent the approach from being positive. Despite physicians' positive attitude towards TGD individuals on a professional level, there is resistance to contacting them in their daily lives. The possibility of the partial contribution of socially desirable response behaviour to positive scores should not be ignored.
ABSTRACT
There may be cases where malignant tumor samples can be used for forensic DNA profiling studies. STRs are the first systems preferred in forensic science laboratories for identification purposes. However, genetic instability in tumoral tissues causes STR polymorphism to change, leading to erroneous results. On the other hand, insertion/deletion polymorphism (InDels) are used as genetic markers in forensic science, as they have features that make both STR and SNPs preferable. Although previous studies approved that STR instability is observed in many different tumors, there are only a few studies that have displayed the instability of InDels in tumoral tissues before. In this study, it was aimed to determine whether instability is observed in formalin-fixed paraffin-embedded breast and thyroid tumoral tissues at 36plex InDel Panel. A total of 47 cases, 26 of which were diagnosed as breast cancer and 21 as thyroid cancer, were included in the study. In 21 of 26 (80.76%) breast cancers mutational changes were observed, however only 6 of 21 (28.57%) thyroid carcinoma cases displayed instability.Moreover, in these six cases, mutations were detected at only 1 or 2 loci. The most common change in both tissues was loss of heterozygosity. These findings suggest that paraffin embedded tissues of thyroid tumor can be used in cases of forensic genetic identification, however paraffin embedded breast cancer tissues should be examined with care. In conclusion, low InDel mutation rates compared to STR instability, make InDel analysis from paraffin blocks suitable for forensic genetic identification. However, researchers should keep in mind that there may be differences between the profiles of the tumoral tissues taken as reference and the actual case. In addition, by incorporating additional markers such as SNPs and microhaplotypes with low mutation rates into the study alongside Indels, researchers can significantly enhance the discrimination power in identification processes.
ABSTRACT
Aging is a complex process influenced by genetic, epigenetic, and environmental factors that lead to tissue deterioration and frailty. Epigenetic mechanisms, such as DNA methylation, play a significant role in gene expression regulation and aging. This study presents a new age estimation model developed for the Turkish population using blood samples. Eight CpG sites in loci TOM1L1, ELOVL2, ASPA, FHL2, C1orf132, CCDC102B, cg07082267, and RASSF5 were selected based on their correlation with age. Methylation patterns of these sites were analyzed in blood samples from 100 volunteers, grouped into age categories (20-35, 36-55, and ≥56). Sensitivity analysis indicated a reliable performance with DNA inputs ≥1 ng. Statistical modeling, utilizing Multiple Linear Regression, underscores the reliability of the primary 6-CpG model, excluding cg07082267 and TOM1L1. This model demonstrates strong correlations with chronological age (r = 0.941) and explains 88% of the age variance with low error rates (MAE = 4.07, RMSE = 5.73 years). Validation procedures, including a training-test split and fivefold cross-validation, consistently confirm the model's accuracy and consistency. The study indicates minimal variation in error scores across age cohorts and no significant gender differences. The developed model showed strong predictive accuracy, with the ability to estimate age within certain prediction intervals. This study contributes to the age prediction by using DNA methylation patterns, which can have disparate applications, including forensic and clinical assessments.