The archaeological artifact known as the Shroud of Turin bears the faint ventral and dorsal images of a man and reddish stains interpreted as bloodstains. Numerous observers have noted that the Shroud bloodstains are much redder than would be expected for blood that is 700–2000 years old. A prevalent explanation that is widely promoted in many Shroud “scientific fact lists” and media discussions, including those involving physicians, is that blood with high bilirubin is known to remain red. What began as an idea to explain the Shroud’s blood color became fortified by the incorrect notion that this observation was previously established in forensic and medical science. Here, the evidence for the declaration that blood with high bilirubin is known to remain red is reviewed, highlighting the strengths and weaknesses of the procedures used in these investigations. This example demonstrates how important it is in the forensic sciences to clearly distinguish between hypotheses, experimental evidence, secondary citations, and repetitions in the media of popular science claims.
Short tandem repeat (STR) analysis is routinely used in forensic human identification and kinship testing; however, the interpretation of mutations at highly polymorphic loci, such as SE33, remains challenging when based solely on fragment size analysis. We evaluated a practical heteroduplex-assisted analytical approach for resolving complex SE33 discrepancies encountered during routine forensic casework. Two forensic kinship cases involving isolated inconsistencies at the SE33 locus were investigated. In Case 1, an apparent SE33 mismatch was observed between the alleged father and a male child, despite concordant Y-STR haplotypes. In Case 2, a single-locus discrepancy was identified between the mother and female child in a biological parent–child trio. Conventional capillary electrophoresis and size-based polyacrylamide gel electrophoresis were insufficient to determine the parental origin of the discrepant alleles. Heteroduplex analysis enabled the separation of individual alleles, which were subsequently characterized by Sanger sequencing to determine their internal repeat structures. Structural analysis indicated that the child’s SE33*24.2 allele in Case 1 most likely originated from the paternal SE33*29.2 allele through repeat contraction, whereas the child’s SE33*29.2 allele in Case 2 was confirmed to be paternally inherited, consistent with a single-repeat expansion of the maternal SE33*30.2 allele to SE33*31.2. In addition, substantial isoallelic diversity and pseudohomozygous genotypes were identified among alleles with identical CE-based fragment sizes. These findings demonstrate that heteroduplex-assisted structural analysis provides sequence-level information beyond conventional fragment size analysis and may facilitate the interpretation of otherwise ambiguous SE33 discrepancies. Because this approach requires only standard PCR, polyacrylamide gel electrophoresis, and Sanger sequencing, it provides a simple and readily implementable complementary method for investigating complex STR mutations and single-locus discrepancies in routine forensic casework.
Crimes against cultural property pose a complex investigative challenge because such cases often involve incomplete recovery, uncertain provenance, mixed-origin assemblages, and fragmentary evidentiary conditions. Under these circumstances, probabilistic reasoning may offer a useful way to structure uncertainty rather than force premature categorical conclusions. This study presents a proof-of-concept Naïve Bayes framework that links broad contextual variables, principally archaeological period and site type, to probabilistic expectations regarding artefact categories. In the present study, the synthetic reference structure and illustrative case applications focus primarily on artefact categories associated with illicit metal-detecting activity and the recovery of metal finds. This reflects the empirical context examined here and should not be understood as restricting the conceptual framework itself to metallic artefacts. The framework is constructed from a literature-informed synthetic dataset and is illustrated through case applications from Fejér County. The article is methodological in scope. It does not claim external validation on an independent real-case corpus, does not compare model performance against specialist archaeological assessment, and is not intended to replace archaeological expertise or function as a standalone evidentiary technique. Instead, it shows how archaeologically informed expectations may be formalised in a transparent, reproducible, and updatable probabilistic form. Within these limits, the framework may support forensic-intelligence and OSINT-based investigative work by helping analysts prioritise contextually plausible artefact categories, structure preliminary hypotheses, and identify which lines of inquiry or online-marketplace signals may warrant closer attention. Internal sensitivity analysis suggests that the model outputs remain relatively stable under moderate perturbations of priors and conditional parameters, while also indicating that the magnitude and interpretability of these outputs depend substantially on the quality and representativeness of the underlying reference data. The proposed approach should therefore be understood as a methodological tool for analytical prioritisation and decision support in the investigation of crimes against cultural property, rather than as a validated predictive or provenance-attribution system.
Anatomical and artistic knowledge, along with technological advancements and newer statistical applications has facilitated the reconstruction and recognition of facial appearance from unknown skulls retrieved from forensic contexts through the application of the techniques of forensic craniofacial reconstruction (CFR). Facial reconstruction techniques have multiple applications in the field of forensic anthropology where identification of the victims of mass disasters becomes crucial. The present review aims to scrutinize the status, evolution, and applications of CFR approaches integrating facial soft tissue thickness (FSTT), in the context of technological advancements, statistical and computational methods, and recent artificial intelligence (AI)-based approaches. For this purpose, the relevant peer-reviewed studies published during the last more than one and half decade (2010–2026) were searched and identified for analyses. An in-depth search of articles describing different aspects of forensic facial reconstruction was done using the scientific search-engines of PubMed, Science-direct, and Scopus. A total of 703 records were identified through the database searches, and only 32 of them met the predefined eligibility criteria, thus were formally included in this systematic review. The selected studies were analysed based on study design, instrumentation, methodological protocols, statistical and computational approaches, applications, limitations, and research gaps relevant to FSTT-integrated CFR. Thus, the present article gives a conclusive outlook towards latest research trends in craniofacial reconstruction technology, where we lack and where we can improve like incorporation of AI based algorithms and molecular photo fittings in forensic facial approximation. The potential benefits and advantages of AI in forensic facial reconstruction, its disadvantages, limitations and future directions have been discussed briefly in present article. This review highlights the integration of AI and statistical methodologies in FSTT-integrated CFR and examines the methodological developments, accuracy, reliability, and limitations of these approaches in reconstructing facial features from unknown human skulls.
