Likelihood Ratios for Deep Neural Networks in Face Comparison

In this study, we aim to compare the performance of systems and forensic facial comparison experts in terms of likelihood ratio computation to assess the potential of the machine to support the human expert in the courtroom. In forensics, transparency in the methods is essential. Consequently, state-of-the-art free software was preferred over commercial software. Three different open-source automated systems chosen for their availability and clarity were as follows: OpenFace, SeetaFace, and FaceNet; all three based on convolutional neural networks that return a distance (OpenFace, FaceNet) or similarity (SeetaFace). The returned distance or similarity is converted to a likelihood ratio using three different distribution fits: parametric fit Weibull distribution, nonparametric fit kernel density estimation, and isotonic regression with pool adjacent violators algorithm. The results show that with low-quality frontal images, automated systems have better performance to detect nonmatches than investigators: 100% of precision and specificity in confusion matrix against 89% and 86% obtained by investigators, but with good quality images forensic experts have better results. The rank correlation between investigators and software is around 80%. We conclude that the software can assist in reporting officers as it can do faster and more reliable comparisons with full-frontal images, which can help the forensic expert in casework

A preclinical and phase Ib study of palbociclib plus nab-paclitaxel in patients with metastatic adenocarcinoma of the pancreas

Purpose: To assess the preclinical efficacy, clinical safety and efficacy, and MTD of palbociclib plus nab-paclitaxel in patients with advanced pancreatic ductal adenocarcinoma (PDAC). Experimental Design: Preclinical activity was tested in patient-derived xenograft (PDX) models of PDAC. In the open-label, phase I clinical study, the dose-escalation cohort received oral palbociclib initially at 75 mg/day (range, 50‒125 mg/day; modified 3+3 design; 3/1 schedule); intravenous nab-paclitaxel was administered weekly for 3 weeks/28-day cycle at 100‒125 mg/m2. The modified dose–regimen cohorts received palbociclib 75 mg/day (3/1 schedule or continuously) plus nab-paclitaxel (biweekly 125 or 100 mg/m2, respectively). The prespecified efficacy threshold was 12-month survival probability of ≥65% at the MTD. Results: Palbociclib plus nab-paclitaxel was more effective than gemcitabine plus nab-paclitaxel in three of four PDX models tested; the combination was not inferior to paclitaxel plus gemcitabine. In the clinical trial, 76 patients (80% received prior treatment for advanced disease) were enrolled. Four dose-limiting toxicities were observed [mucositis (n = 1), neutropenia (n = 2), febrile neutropenia (n = 1)]. The MTD was palbociclib 100 mg for 21 of every 28 days and nab-paclitaxel 125 mg/m2 weekly for 3 weeks in a 28-day cycle. Among all patients, the most common all-causality any-grade adverse events were neutropenia (76.3%), asthenia/fatigue (52.6%), nausea (42.1%), and anemia (40.8%). At the MTD (n = 27), the 12-month survival probability was 50% (95% confidence interval, 29.9–67.2). Conclusions: This study showed the tolerability and antitumor activity of palbociclib plus nab-paclitaxel treatment in patients with PDAC; however, the prespecified efficacy threshold was not me

What Is New for an Old Molecule? Systematic Review and Recommendations on the Use of Resveratrol

Stilbenes are naturally occurring phytoalexins that generally exist as their more stable E isomers. The most well known natural stilbene is resveratrol (Res), firstly isolated in 1939 from roots of Veratrum grandiflorum (white hellebore) (1) and since then found in various edible plants, notably in Vitis vinifera L. (Vitaceae) (2). The therapeutic potential of Res covers a wide range of diseases, and multiple beneficial effects on human health such as antioxidant, anti-inflammatory and anti-cancer activities have been suggested based on several in vitro and animal studies (3). In particular, Res has been reported to be an inhibitor of carcinogenesis at multiple stages via its ability to inhibit cyclooxygenase, and is an anticancer agent with a role in antiangiogenesis (4). Moreover, both in vitro and in vivo studies showed that Res induces cell cycle arrest and apoptosis in tumor cells (4). However, clinical studies in humans evidenced that Res is rapidly absorbed after oral intake, and that the low level observed in the blood stream is caused by a fast conversion into metabolites that are readily excreted from the body (5). Thus, considerable efforts have gone in the design and synthesis of Res analogues with enhanced metabolic stability. Considering that reduced Res (dihydro- resveratrol, D-Res) conjugates may account for as much as 50% of an oral Res dose (5), and that D-Res has a strong proliferative effect on hormone-sensitive cancer cell lines such as breast cancer cell line MCF7 (6), we recently devoted our synthetic efforts to the preparation of trans-restricted analogues of Res in which the E carbon-carbon double bond is embedded into an imidazole nucleus. To keep the trans geometry, the two aryl rings were linked to the heteroaromatic core in a 1,3 fashion. Based on this design, we successfully prepared a variety of 1,4-, 2,4- and 2,5-diaryl substituted imidazoles including Res analogues 1, 2 and 3, respectively, by procedures that involve transition metal-catalyzed Suzuki-Miyaura cross-coupling reactions and highly selective N-H or C-H direct arylation reactions as key synthetic steps. The anticancer activity of compounds 1–3 was evaluated against the 60 human cancer cell lines panel of the National Cancer Institute (NCI, USA). The obtained results, that will be showed and discussed along with the protocols developed for the preparation of imidazoles 1–3, confirmed that a structural optimization of Res may provide analogues with improved potency in inhibiting the growth of human cancer cell lines in vitro when compared to their natural lead. (1) Takaoka,M.J.Chem.Soc.Jpn.1939,60,1090-1100. (2) Langcake, P.; Pryce, R. J. Physiological. Plant Patology 1976, 9, 77-86. (3) Vang, O.; et al. PLoS ONE 2011, 6, e19881. doi:10.1371/journal.pone.0019881 (4) Kraft, T. E.; et al. Critical Reviews in Food Science and Nutrition 2009, 49, 782-799. (5) Walle, T. Ann. N.Y. Acad. Sci. 2011, 1215, 9-15. doi: 10.1111/j.1749-6632.2010.05842.x (6) Gakh,A.A.;etal.Bioorg.Med.Chem.Lett.2010,20,6149-6151

Calibration of score based likelihood ratio estimation in automated forensic facial image comparison

Forensic facial image comparison lacks a methodological standardization and empirical validation. We aim to address this problem by assessing the potential of machine learning to support the human expert in the courtroom. To yield valid evidence in court, decision making systems for facial image comparison should not only be accurate, they should also provide a calibrated confidence measure. This confidence is best conveyed using a score-based likelihood ratio. In this study we compare the performance of different calibrations for such scores. The score, either a distance or a similarity, is converted to a likelihood ratio using three types of calibration following similar techniques as applied in forensic fields such as speaker comparison and DNA matching, but which have not yet been tested in facial image comparison. The calibration types tested are: naive, quality score based on typicality, and feature-based. As transparency is essential in forensics, we focus on state-of-the-art open software and study their power compared to a state-of-the-art commercial system. With the European Network of Forensic Science Institutes (ENFSI) Proficiency tests as benchmark, calibration results on three public databases namely Labeled Faces in the Wild, SC Face and ForenFace show that both quality score and feature based calibration outperform naive calibration. Overall, the commercial system outperforms open software when evaluating these Likelihood Ratios. In general, we conclude that calibration implemented before likelihood ratio estimation is recommended. Furthermore, in terms of performance the commercial system is preferred over open software. As open software is more transparent, more research on open software is urged for

Google timeline accuracy assessment and error prediction

Google Location Timeline, once activated, allows to track devices and save their locations. This feature might be useful in the future as available data for evidence in investigations. For that, the court would be interested in the reliability of these data. The position is presented in the form of a pair of coordinates and a radius, hence the estimated area for tracked device is enclosed by a circle. This research focuses on the assessment of the accuracy of the locations given by Google Location History Timeline, which variables affect this accuracy and the initial steps to develop a linear multivariate model that can potentially predict the actual error with respect to the true location considering environmental variables. The determination of the potential influential variables (configuration of mobile device connectivity, speed of movement and environment) was set through a series of experiments in which the true position of the device was recorded with a reference Global Positioning System (GPS) device with a superior order of accuracy. The accuracy was assessed measuring the distance between the Google provided position and the de facto one, later referred to as Google error. If this Google error distance is less than the radius provided, we define it as a hit. The configuration that has the largest hit rate is when the mobile device has GPS available, with a 52% success. Then the use of 3G and 2G connection go with 38% and 33% respectively. The Wi-Fi connection only has a hit rate of 7%. Regarding the means of transport, when the connection is 2G or 3G, the worst results are in Still with a hit rate of 9% and the best in Car with 57%. Regarding the prediction model, the distances and angles from the position of the device to the three nearest cell towers, and the categorical (non-numerical) variables of Environment and means of transport were taking as input variables in this initial study. To evaluate the usability of a model, a Model hit is defined when the actual observation is within the 95% confidence interval provided by the model. Out of the models developed, the one that shows the best results was the one that predicted the accuracy when the used network is 2G, with 76% of Model hits. The second model with best performance had only a 23% success (with the mobile network set to 3G).Mathematical Geodesy and Positionin