This study evaluates the performance of analysing surface DNA samples using massively parallel sequencing (MPS) compared to traditional capillary electrophoresis (CE). A total of 30 samples were collected from various surfaces in an office environment and were analysed with CE and MPS. These were compared against 60 reference samples (office inhabitants). To identify contributors, likelihood ratios (LRs) were calculated for MPS and CE data using the probabilistic genotyping software MPSproto and EuroForMix respectively. Although a higher number of sequences/peaks were observed per DNA profile in MPS compared to CE, LR values were found to be lower for MPS data formats. This might be the result of the increased complexity of MPS data, along with a possible elevation of unknown alleles and/or artefacts. The study highlights avenues for improving MPS data quality and analysis to facilitate more robust interpretation of challenging casework-like samples.

Performance evaluation of source camera attribution methods typically stop at the level of analysis of hard to interpret similarity scores. Standard analytic tools include Detection Error Trade-off or Receiver Operating Characteristic curves, or other scalar performance metrics, such as Equal Error Rate or error rates at a specific decision threshold. However, the main drawback of similarity scores is their lack of probabilistic interpretation and thereby their lack of usability in forensic investigation, when assisting the trier of fact to make more sound and more informed decisions. The main objective of this work is to demonstrate a transition from the similarity scores to likelihood ratios in the scope of digital evidence evaluation, which not only have probabilistic meaning, but can be immediately incorporated into the forensic casework and combined with the rest of the case-related forensic. Likelihood ratios are calculated from the Photo Response Non-Uniformity source attribution similarity scores. The experiments conducted aim to compare different strategies applied to both digital images and videos, by considering their respective peculiarities. The results are presented in a format compatible with the guideline for validation of forensic likelihood ratio methods.

Pepper sprays of the OC type constitute the majority of self-defense sprays available on the market. The active ingredient in these preparations is pepper extract: Oleoresin Capsicum, which contains capsaicinoids - natural compounds with irritant properties. Preparations from OC pepper sprays can be distinguished based on differences in the quantitative ratios of four main capsaicinoids: capsaicin, dihydrocapsaicin, nordihydrocapsaicin, and nonivamide. This raises the question whether information on the quantitative ratios of capsaicinoids can also provide answers to questions regarding comparisons of traces of OC preparations, such as whether traces revealed on the clothing of the victim could originate from an OC spray secured from the suspect, or whether traces on the clothing of the suspect and the victim could come from the same pepper spray. Such comparisons would be viable only if the capsaicinoid profile remained unchanged during evidence storage and as a result of solvent extraction from the tested material. The aim of the presented research was to determine if this is indeed the case. Model aging experiments were conducted to examine whether the capsaicinoid profile in traces of OC preparations changed over time and whether solvent extraction affected this profile. Samples of five different OC preparations were applied to cotton swabs, which, after the evaporation of volatile solvents, were placed in three types of packaging with varying levels of tightness and transparency (tight amber vials, polyethylene bags, paper envelopes). These prepared samples underwent solvent extraction with methanol and analysis using gas chromatography - mass spectrometry, after 28, 84, 147, 196, 252, and 301 days from preparation. The likelihood ratio (LR) was applied as a statistical tool to investigate the data obtained. The LR model was computed using the three variables based on the relative content of nordihydrocapsaicin, nonivamide, and dihydrocapsaicin. The cotton swabs used in the experiments served as a model for both the swabs used by the police for securing liquid evidence and the cotton clothing of individuals sprayed with OC pepper sprays. The findings of the conducted studies suggest that the quantitative relationships of capsaicinoids indeed change over time, both in preparations stored in original containers and in traces of these preparations present on clothing. For traces of OC preparations secured on swabs or present on clothing, these changes are more significant the longer the sample is stored and the less airtight the packaging used.

OBJECTIVE: We aimed to develop an easily deployable artificial intelligence (AI)-driven model for rapid prediction of urine culture test results.
METHODS: We utilized a training dataset (n = 34,584 urine samples) and two separate, unseen test sets (n = 10,083 and 9,289 samples). Various machine learning models were compared for diagnostic performance. Predictive parameters included urinalysis results (dipstick and flow cytometry), patient demographics (age and gender), and sample collection method.
RESULTS: Although more complex models achieved the highest AUCs for predicting positive cultures (highest: multilayer perceptron (MLP) with AUC of 0.884, 95% CI 0.878-0.89), multiple logistic regression (MLR) using only flow cytometry parameters achieved a very good AUC (0.858, 95% CI 0.852-0.865). To aid interpretation, prediction results of the MLP and MLR models were categorized based on likelihood ratio (LR) for positivity: highly unlikely (LR 0.1), unlikely (LR 0.3), grey zone (LR 0.9), likely (LR 5.0), and highly likely (LR 40). This resulted in 17%, 28%, 34%, 9%, and 13% of samples falling into each respective category for the MLR model and 20%, 26%, 31%, 7%, and 16% for the MLP model.
CONCLUSIONS: In conclusion, this robust model has the potential to assist clinicians in their decision-making process by providing insights prior to the availability of urine culture results in a significant portion of samples (∼2/3rd).

The development of probabilistic genotyping (PG) systems to quantitatively analyze DNA mixture samples has been transformative in forensic science. TrueAllele® Casework (TA) and STRmix™ (STRmix) are the two most widely used PG systems in the United States. The two systems were challenged with 48 two-, three-, and four-person mock casework samples, for a total of 152 likelihood ratio (LR) comparisons. TA and STRmix converged on the same result (supportive, non-supportive, or inconclusive) for ~91% of contributor-specific comparisons. Where moderate or substantial differences in log(LR) values were observed, 9% affected the conclusion of the reference association to the mixture. The PG systems exhibited high correlations for estimated contributor-specific template quantities (~92%) and log(LR)s produced (>88%). When the log(LR)s for only low-template contributors (<100 pg) were compared, the R2 value dropped to ~68% and the difference became statistically significant. Of the 14 contributor comparisons where the conclusion differed, two were contradictory (supportive vs. non-supportive) and 12 were either inconclusive versus non-supportive or inconclusive versus supportive. The differing results were likely due to dissimilarities in the mixture input file as STRmix uses a lab-defined analytical threshold (AT) and TA models to 10 RFUs for each electropherogram. When 7 of the 14 mixtures were reanalyzed by STRmix using a 10 RFU AT, the log(LR)s for the low-template contributors became more similar to TAs. This study shows that while both systems may produce accurate and calibrated LRs, their results can deviate, especially for low-template, degraded contributors, and the deviation is generally predictable.

The evaluation of the results from a fibre comparison given activity level propositions is well established when considering only a single group of potential primary transfers. However, secondary transfers are less prevalent in the literature despite their potential value, especially in cases where the primary transfers are not sufficiently informative. In particular, one can consider the fibres from frequented environments of the person of interest (POI) identified in a struggle. If the POI did struggle with the complainant, these fibres can potentially be recovered in small quantities on the surface of the complainant as a result of secondary or higher order transfers. Therefore, these fibres may provide useful information that can resolve competing propositions involving struggles, as well as forensic intelligence in the form of linkages or investigative leads. If a non-differentiation is indeed found between recovered fibres and fibres from the frequented environments of the POI, these results need to be properly interpreted. In this paper, a model, based on an object oriented Bayesian network (OOBN), for evaluating such findings along with its implementation is proposed. Using available data from the literature and other sources, the model was then used to assess a few hypothetical scenarios involving secondary transfers. The results provided useful insights into secondary transfer that help to validate the model and demonstrate the potential utility that can be gained by considering transfers beyond the primary order. Moreover, these results can be used to help guide future research by identifying gaps in the literature. Finally, the direct application to a case study was conducted to demonstrate the practical aspects of such a model.

BACKGROUND: Angiogenic imbalances, characterized by an excess of antiangiogenic factors (soluble fms-like tyrosine kinase 1) and reduced angiogenic factors (vascular endothelial growth factor and placental growth factor), contribute to the mechanisms of disease in preeclampsia. The ratio of soluble fms-like tyrosine kinase 1 to placental growth factor has been used as a biomarker for preeclampsia, but the cutoff values may vary with gestational age and assay platform.
OBJECTIVE: This study aimed to compare multiples of the median of the maternal plasma soluble fms-like tyrosine kinase 1 to placental growth factor ratio, soluble fms-like tyrosine kinase 1, placental growth factor, and conventional clinical and laboratory values in their ability to predict preeclampsia with severe features.
METHODS: We conducted a cohort study across 18 United States centers involving hospitalized individuals with hypertension between 23 and 35 weeks\' gestation. Receiver operating characteristic curve analyses of maternal plasma biomarkers, highest systolic or diastolic blood pressures, and laboratory values at enrollment were performed for the prediction of preeclampsia with severe features. The areas under the curve were compared, and quasi-Poisson regression models were fitted to estimate relative risks. The primary outcome was preeclampsia with severe features within 2 weeks of enrollment. Secondary outcomes were a composite of severe adverse maternal outcomes (elevated liver enzymes, low platelets count, placental abruption, eclampsia, disseminated intravascular coagulation, and pulmonary edema) and a composite of severe adverse perinatal outcomes (birth weight below the third percentile, very preterm birth [<32 weeks\' gestation], and fetal or neonatal death).
RESULTS: Of the 543 individuals included in the study, preeclampsia with severe features within 2 weeks was observed in 33.1% (n=180) of them. A receiver operating characteristic curve-derived cutoff of 11.5 multiples of the median for the soluble fms-like tyrosine kinase 1 to placental growth factor plasma ratio provided good sensitivity (90.6%), specificity (76.9%), positive predictive value (66.0%), negative predictive value (94.3%), positive likelihood ratio (3.91), negative likelihood ratio (0.12), and accuracy (81.4%) for preeclampsia with severe features within 2 weeks. This cutoff was used to compare test positive cases (≥ cutoff) and test negative cases (< cutoff). Preeclampsia with severe features (66.0% vs 5.7%; P<.001) and composites of severe adverse maternal (8.11% vs 2.7%; P=.006) or perinatal (41.3% vs 10.14%; P=.001) outcomes within 2 weeks were more frequent in test positive cases than in test negative cases. A soluble fms-like tyrosine kinase 1 to placental growth factor plasma ratio ≥11.5 multiples of the median was independently associated with preeclampsia with severe features (adjusted incidence rate ratio, 9.08; 95% confidence interval, 6.11-14.06; P<.001) and a composite of severe adverse perinatal outcomes (adjusted incidence rate ratio, 9.42; 95% confidence interval, 6.36-14.53; P<.001) but not with a composite of severe adverse maternal outcomes (adjusted incidence rate ratio, 2.20; 95% confidence interval, 0.95-5.54; P=.08). The area under the curve for the soluble fms-like tyrosine kinase 1 to placental growth factor plasma ratio in multiples of the median (0.91; 95% confidence interval, 0.89-0.94) for preeclampsia with severe features within 2 weeks was significantly higher (P<.001 for all comparisons) than either plasma biomarker alone or any other parameter with the exception of absolute soluble fms-like tyrosine kinase 1 to placental growth factor plasma ratio values.
CONCLUSIONS: A soluble fms-like tyrosine kinase 1 to placental growth factor plasma ratio ≥11.5 multiples of the mean among hospitalized patients with hypertension between 23 and 35 week\'s gestation predicts progression to preeclampsia with severe features and severe adverse perinatal outcomes within 2 weeks.

Internal quality control in clinical chemistry laboratories are based on analyzing samples of stable control materials among the patient samples. The control results are interpreted by using quality control rules that usually are designed to detect systematic errors. The best rules have a high probability of error detection (Ped), i.e. to detect the maximal allowable (critical) systematic error and a low probability of false rejection (Pfr, false alarm). In this work we show that quality control rules can be represented by points on a ROC curve which appears when Ped is plotted against Pfr and only the control limit is varied. Further, we introduce a new method for choosing the optimal control limit, analogous to choosing the optimal operating point on the ROC curve of a diagnostic test. This decision needs knowledge of the pretest probability of a critical systematic error, the benefit of detecting it when it occurs and the cost of false alarm. The ROC curve analysis showed that if rules based on N = 2 are used, mean rules outperform Westgard rules because the ROC curve of the mean rules was lying above the ROC curves of the Westgard rules. A mean rule also had a lower maximum expected increase in the number of unacceptable patient results reported during the presence of an out-of-control error condition (Max E(NUF)) than comparable Westgard rules.

In recent years, there has been discussion and controversy relating to the treatment of inconclusive decisions in forensic feature comparison disciplines when considering the reliability of examination methods and results. In this article, we offer a brief review of the various viewpoints and suggestions that have been recently put forth, followed by a solution that we believe addresses the treatment of inconclusive decisions. We consider the issues in the context of method conformance and method performance as two distinct concepts, both of which are necessary for the determination of reliability. Method conformance relates to an assessment of whether the outcome of a method is the result of the analyst\'s adherence to the procedures that define the method. Method performance reflects the capacity of a method to discriminate between different propositions of interest (e.g., mated and non-mated comparisons). We then discuss implications of these issues for the forensic science community.

Expert testimony is only admissible in common-law systems if it will potentially assist the trier of fact. In order for a forensic-voice-comparison expert\'s testimony to assist a trier of fact, the expert\'s forensic voice comparison should be more accurate than the trier of fact\'s speaker identification. \"Speaker identification in courtroom contexts - Part I\" addressed the question of whether speaker identification by an individual lay listener (such as a judge) would be more or less accurate than the output of a forensic-voice-comparison system that is based on state-of-the-art automatic-speaker-recognition technology. The present paper addresses the question of whether speaker identification by a group of collaborating lay listeners (such as a jury) would be more or less accurate than the output of such a forensic-voice-comparison system. As members of collaborating groups, participants listen to pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case, confer, and make a probabilistic consensus judgement on each pair of recordings. The present paper also compares group-consensus responses with \"wisdom of the crowd\" which uses the average of the responses from multiple independent individual listeners.