Developing an interpretation model for body fluid identification.

Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to provide context. In most cases this can be achieved by conventional methods, however, in certain scenarios, alternative molecular methods are required. An example of this is the detection of menstrual fluid and vaginal material, which are not able to be identified using conventional techniques. Endpoint reverse-transcription PCR (RT-PCR) is currently used for this purpose to amplify body fluid specific messenger RNA (mRNA) transcripts in forensic casework. Real-time quantitative reverse-transcription PCR (RT-qPCR) is a similar method but utilises fluorescent markers to generate quantitative results in the form of threshold cycle (Cq) values. Despite the uncertainty surrounding body fluid identification, most interpretation guidelines utilise categorical statements. Probabilistic modelling is more realistic as it reflects biological variation as well as the known performance of the method. This research describes the application of various machine learning models to single-source mRNA profiles obtained by RT-qPCR and assesses their performance. Multinomial logistic regression (MLR), Naïve Bayes (NB), and linear discriminant analysis (LDA) were used to discriminate between the following body fluid categories: saliva, circulatory blood, menstrual fluid, vaginal material, and semen. We identified that the performance of MLR was somewhat improved when the quantitative dataset of the original Cq values was used (overall accuracy of approximately 0.95) rather than presence/absence coded data (overall accuracy of approximately 0.94). This indicates that the quantitative information obtained by RT-qPCR amplification is useful in assigning body fluid class. Of the three classification methods, MLR performed the best. When we utilised receiver operating characteristic curves to observe performance by body fluid class, it was clear that all methods found difficulty in classifying menstrual blood samples. Future work will involve the modelling of body fluid mixtures, which are common in samples analysed as part of sexual assault investigations.

Reductive Metabolism Influences the Toxicity and Pharmacokinetics of the Hypoxia-Targeted Benzotriazine Di-Oxide Anticancer Agent SN30000 in Mice.

3-(3-Morpholinopropyl)-7,8-dihydro-6H-indeno[5,6-e][1,2,4]triazine 1,4-dioxide (SN30- 000), an analog of the well-studied bioreductive prodrug tirapazamine (TPZ), has improved activity against hypoxic cells in tumor xenografts. However, little is known about its biotransformation in normal tissues. Here, we evaluate implications of biotransformation of SN30000 for its toxicokinetics in NIH-III mice. The metabolite profile demonstrated reduction to the 1-N-oxide (M14), oxidation of the morpholine side-chain (predominantly to the alkanoic acid M18) and chromophore, and subsequent glucuronidation. Plasma pharmacokinetics of SN30000 and its reduced metabolites was unaffected by the presence of HT29 tumor xenografts, indicating extensive reduction in normal tissues. This bioreductive metabolism, as modeled by hepatic S9 preparations, was strongly inhibited by oxygen indicating that it proceeds via the one-electron (radical) intermediate previously implicated in induction of DNA double strand breaks and cytotoxicity by SN30000. Plasma pharmacokinetics of SN30000 and M14 (but not M18) corresponded closely to the timing of reversible acute clinical signs (reduced mobility) and marked hypothermia (rectal temperature drop of ∼8°C at nadir following the maximum tolerated dose). Similar acute toxicity was elicited by dosing with TPZ or M14, although M14 did not induce the kidney and lung histopathology caused by SN30000. M14 also lacked antiproliferative potency in hypoxic cell cultures. In addition M14 showed much slower redox cycling than SN30000 in oxic cultures. Thus a non-bioreductive mechanism, mediated through M14, appears to be responsible for the acute toxicity of SN30000 while late toxicities are consistent with DNA damage resulting from its one-electron reduction. A two-compartment pharmacokinetic model, in which clearance of SN30000 is determined by temperature-dependent bioreductive metabolism to M14, was shown to describe the non-linear PK of SN30000 in mice. This study demonstrates the importance of non-tumor bioreductive metabolism in the toxicology and pharmacokinetics of benzotriazine di-oxides designed to target tumor hypoxia.