A simplified protocol for the detection of blood, saliva, and semen from a single biological trace using immunochromatographic tests.

The detection of body fluids (e.g., blood, saliva or semen) provides information that is important both for the investigation and for the choice of the analytical protocols. Because of their sensitivity, specificity, as well as their simplicity of use, immunochromatographic tests are widely applied. These tests target different body fluids and generally require specific buffer solutions. If one needs to investigate whether the material is of a specific nature (e.g., blood), this is fine. However, if the material can also contain other material (e.g., saliva or semen) then the use of different tests can be problematic. Indeed, if the different tests require different buffers, it will not be possible to perform all tests on the exact same specimen.In this study, we assess the use of the RSID™-universal buffer to perform three immunochromatographic tests (HEXAGON OBTI, RSID-saliva, and PSA Semiquant) as well as spermatozoa detection. We use the same eluate for the detection of all three body fluids. The proposed protocol provides similar results to those obtained when each test is conducted independently. Furthermore, it does not affect the quality of the DNA profiles. The main advantage of this protocol is that the results of the presumptive test(s) and of the DNA analyses are representative of the exact same specimen.

Use of Bayesian Networks for the investigation of the nature of biological material in casework.

Chemical and staining methods, immunochromatography, spectroscopy, RNA expression or methylation patterns, do not allow to determine the nature of the biological material with certainty. However, to our knowledge, there are few forensic scientists that assess the value of such test results using a probabilistic approach. This is surprising as it would allow account for false positives and false negatives and avoid misleading conclusions. In this paper, we developed three Bayesian Networks (BNs) to assess the presence of blood, saliva and sperm in the recovered material and combine potentially contradictory observations. The approach was successfully tested using 188 traces from proficiency tests. We have implemented an online user-friendly application (https://forensic-genetic.shinyapps.io/BodyFluidsApp/) that allows forensic scientists to assess the value of their results without having to build Bayesian Networks themselves. They can also input their own data, use the application to identify a potential lack of knowledge and report their conclusions regarding the presence of sperm, blood or/and saliva considering uncertainty.

A Swiss collaborative exercise for Disaster Victim Identification (DVI): Covering situations with different levels of complexity.

The identification of victims of a disaster (DVI) requires the collaboration of different specialists. Within a DVI context, DNA analyses often play an important role. Consequently, forensic genetic laboratories should be prepared to cope with DVI situations, as this can involve large-scale DNA profile comparisons. Six forensic genetic laboratories from Switzerland participated in an exercise where supposedly a plane had crashed. The goal of the exercise was to monitor participants use of dedicated software with ground truth cases and to make them aware of the existence of particular situations that may occur in real cases. For assigning the value of the comparison of the DNA profiles, all participating laboratories used the DVI module of Familias v3.2.1 In addition, one of the 6 laboratories used the Pedigree Searcher from CODIS v7.0. The data (AmpFlSTR® NGM SElect™ profiles) were generated to challenge the participating laboratories: cases with first, second degree biological parents, mutation events, as well as non-paternity cases were included. This study shows that the majority of the participants used the software in an appropriate way. However, a few misleading conclusions were detected for the most challenging situations. These errors belonged to one of the following categories: false pedigree, false association using the higher LR, misleading contextual information (false paternity) and not clustering family members. Specific recommendations are provided in order to reduce misuse of the software and the risk of misinterpretations by using all the relevant information.