Assessing the joint impact of DNAPL source-zone behavior and degradation products on the probabilistic characterization of human health risk

The release of industrial contaminants into the subsurface has led to a rapid degradation of groundwater resources. Contamination caused by Dense Non-Aqueous Phase Liquids (DNAPLs) is particularly severe owing to their limited solubility, slow dissolution and in many cases high toxicity. A greater insight into how the DNAPL source zone behavior and the contaminant release towards the aquifer impact human health risk is crucial for an appropriate risk management. Risk analysis is further complicated by the uncertainty in aquifer properties and contaminant conditions. This study focuses on the impact of the DNAPL release mode on the human health risk propagation along the aquifer under uncertain conditions. Contaminant concentrations released from the source zone are described using a screening approach with a set of parameters representing several scenarios of DNAPL architecture. The uncertainty in the hydraulic properties is systematically accounted for by high-resolution Monte Carlo simulations. We simulate the release and the transport of the chlorinated solvent perchloroethylene and its carcinogenic degradation products in randomly heterogeneous porous media. The human health risk posed by the chemical mixture of these contaminants is characterized by the low-order statistics and the probability density function of common risk metrics. We show that the zone of high risk (hot spot) is independent of the DNAPL mass release mode, and that the risk amplitude is mostly controlled by heterogeneities and by the source zone architecture. The risk is lower and less uncertain when the source zone is formed mostly by ganglia than by pools. We also illustrate how the source zone efficiency (intensity of the water flux crossing the source zone) affects the risk posed by an exposure to the chemical mixture. Results display that high source zone efficiencies are counter-intuitively beneficial, decreasing the risk because of a reduction in the time available for the production of the highly toxic subspecies.Peer ReviewedPostprint (author's final draft

Crowdsourcing Image Extraction and Annotation: Software Development and Case Study

We describe the development of web-based software that facilitates large-scale, crowdsourced image extraction and annotation within image-heavy corpora that are of interest to the digital humanities. An application of this software is then detailed and evaluated through a case study where it was deployed within Amazon Mechanical Turk to extract and annotate faces from the archives of Time magazine. Annotation labels included categories such as age, gender, and race that were subsequently used to train machine learning models. The systemization of our crowdsourced data collection and worker quality verification procedures are detailed within this case study. We outline a data verification methodology that used validation images and required only two annotations per image to produce high-fidelity data that has comparable results to methods using five annotations per image. Finally, we provide instructions for customizing our software to meet the needs for other studies, with the goal of offering this resource to researchers undertaking the analysis of objects within other image-heavy archives

Moving beyond the weekend effect: how can we best target interventions to improve patient care?

Analysis and support of clinical decision makin

Magnetic fields in the early universe in the string approach to MHD

There is a reformulation of magnetohydrodynamics in which the fundamental dynamical quantities are the positions and velocities of the lines of magnetic flux in the plasma, which turn out to obey equations of motion very much like ideal strings. We use this approach to study the evolution of a primordial magnetic field generated during the radiation-dominated era in the early Universe. Causality dictates that the field lines form a tangled random network, and the string-like equations of motion, plus the assumption of perfect reconnection, inevitably lead to a self-similar solution for the magnetic field power spectrum. We present the predicted form of the power spectrum, and discuss insights gained from the string approximation, in particular the implications for the existence or not of an inverse cascade.Comment: 12 pages, 2 figure

Does early resection of presumed low-grade glioma improve survival? A clinical perspective

Early resection is standard of care for presumed low-grade gliomas. This is based on studies including only tumors that were post-surgically confirmed as low-grade glioma. Unfortunately this does not represent the clinicians’ situation wherein he/she has to deal with a lesion on MRI that is suspect for low-grade glioma (i.e. without prior knowledge on the histological diagnosis). We therefore aimed to determine the optimal initial strategy for patients with a lesion suspect for low-grade glioma, but not histologically proven yet. We retrospectively identified 150 patients with a resectable presumed low-grade-glioma and who were otherwise in good clinical condition. In this cohort we compared overall survival between three types of initital treatment strategy: a wait-and-scan approach (n = 38), early resection (n = 83), or biopsy for histopathological verification (n = 29). In multivariate analysis, no difference was observed in overall survival for early resection compared to wait-and-scan: hazard ratio of 0.92 (95% CI 0.43–2.01; p = 0.85). However, biopsy strategy showed a shorter overall survival compared to wait-and-scan: hazard ratio

Precursor lesions of vulvar squamous cell carcinoma – histology and biomarkers: A systematic review

The precursor lesion of vulvar squamous cell carcinoma (VSCC), namely vulvar intraepithelial neoplasia (VIN), is classified as: human papillomavirus (HPV)-related high grade squamous intraepithelial lesion (HSIL), and HPV-independent differentiated VIN (dVIN). Traditionally, histology and immunohistochemistry (IHC) have been the basis of diagnosis and classification of VIN. HSIL shows conspicuous histological atypia, and positivity on p16-IHC, whereas dVIN shows less obvious histological atypia, and overexpression or null-pattern on p53-IHC. For both types of VIN, other diagnostic immunohistochemical markers have also been evaluated. Molecular characterization of VIN has been attempted in few recent studies, and novel genotypic subtypes of HPV-independent VSCC and VIN have been identified. This systematic review appraises the VSCC precursors identified so far, focusing on histology and biomarkers (immunohistochemical and molecular). To gain further insights into the carcinogenesis and to identify additional potential biomarkers, gene expression omnibus (GEO) datasets on VSCC were analyzed; the results are presented

PIK3CA mutations, phosphatase and tensin homolog, human epidermal growth factor receptor 2, and insulin-like growth factor 1 receptor and adjuvant tamoxifen resistance in postmenopausal breast cancer patients

Introduction: Inhibitors of the phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) pathway can overcome endocrine resistance in estrogen receptor (ER) α-positive breast cancer, but companion diagnostics indicating PI3K/AKT/mTOR activation and consequently endocrine resistance are lacking. PIK3CA mutations frequently occur in ERα-positive breast cancer and result in PI3K/AKT/mTOR activation in vitro. Nevertheless, the prognostic and treatment-predictive value of these mutations in ERα-positive breast cancer is contradictive. We tested the clinical validity of PIK3CA mutations and other canonic pathway drivers to predict intrinsic resistance to adjuvant tamoxifen. In addition, we tested the association between these drivers and downstream activated proteins.Methods: Primary tumors from 563 ERα-positive postmenopausal patients, randomized between adjuvant tamoxifen (1 to 3 years) versus observation were recollected. PIK3CA hotspot mutations in exon 9 and exon 20 were assessed with Sequenom Mass Spectometry. Immunohistochemistry was performed for human epidermal growth factor receptor 2 (HER2), phosphatase and tensin homolog (PTEN), and insulin-like growth factor 1 receptor (IGF-1R). We tested the association between these molecular alterations and downstream activated proteins (like phospho-protein kinase B (p-AKT), phospho-mammalian target of rapamycin (p-mTOR), p-ERK1/2, and p-p70S6K). Recurrence-free interval improvement with tamoxifen versus control was assessed according to the presence or absence of canonic pathway drivers, by using Cox proportional hazard models, including a test for interaction.Results: PIK3CA mutations (both exon 9 and exon 20) were associated with low tumor grade. An enrichment of PIK3CA exon 20 mutations was observed in progesterone receptor- positive tumors. PIK3CA exon 20 mutations were not associated with downstream-activated proteins. No significant interaction between PIK3CA mutations or any of the other canonic pathway drivers and tamoxifen-treatment benefit was found.Conclusion: PIK3CA mutations do not have clinical validity to predict intrinsic resistance to adjuvant tamoxifen and may therefore be unsuitable as companion diagnostic for PI3K/AKT/mTOR inhibitors in ERα- positive, postmenopausal, early breast cancer patients

Kernel Spectral Clustering and applications

In this chapter we review the main literature related to kernel spectral clustering (KSC), an approach to clustering cast within a kernel-based optimization setting. KSC represents a least-squares support vector machine based formulation of spectral clustering described by a weighted kernel PCA objective. Just as in the classifier case, the binary clustering model is expressed by a hyperplane in a high dimensional space induced by a kernel. In addition, the multi-way clustering can be obtained by combining a set of binary decision functions via an Error Correcting Output Codes (ECOC) encoding scheme. Because of its model-based nature, the KSC method encompasses three main steps: training, validation, testing. In the validation stage model selection is performed to obtain tuning parameters, like the number of clusters present in the data. This is a major advantage compared to classical spectral clustering where the determination of the clustering parameters is unclear and relies on heuristics. Once a KSC model is trained on a small subset of the entire data, it is able to generalize well to unseen test points. Beyond the basic formulation, sparse KSC algorithms based on the Incomplete Cholesky Decomposition (ICD) and $L_0$, $L_1, L_0 + L_1$, Group Lasso regularization are reviewed. In that respect, we show how it is possible to handle large scale data. Also, two possible ways to perform hierarchical clustering and a soft clustering method are presented. Finally, real-world applications such as image segmentation, power load time-series clustering, document clustering and big data learning are considered.Comment: chapter contribution to the book "Unsupervised Learning Algorithms

Bypass surgery versus stenting for the treatment of multivessel disease in patients with unstable angina compared with stable angina

BACKGROUND: Earlier reports have shown that the outcome of balloon angioplasty or bypass surgery in unstable angina is less favorable than in stable angina. Recent improvements in percutaneous treatment (stent implantation) and bypass surgery (arterial grafts) warrant reevaluation of the relative merits of either technique in treatment of unstable angina. Methods and Results- Seven hundred fifty-five patients with stable angina were randomly assigned to coronary stenting (374) or bypass surgery (381), and 450 patients with unstable angina were randomly assigned to coronary stenting (226) or bypass surgery (224). All patients had multivessel disease considered to be equally treatable by either technique. Freedom from major adverse events, including death, myocardial infarction, and cerebrovascular events, at 1 year was not different in unstable patients (91.2% versus 88.9%) and stable patients (90.4% versus 92.6%) treated, respectively, with coronary stenting or bypass surgery. Freedom from repeat revascularization at 1 year was similar in unstable and stable angina treated with stenting (79.2% versus 78.9%) or bypass surgery (96.3% versus 96%) but was significantly higher in both unstable and stable patients treated with stenting (16.8% versus 16.9%) compared with bypass surgery (3.6% versus 3.5%). Neither the difference in costs between stented or bypassed stable or unstable angina ($2594 versus$3627) nor the cost-effectiveness was significantly different at 1 year. CONCLUSIONS: There was no difference in rates of death, myocardial infarction, and cerebrovascular event at 1 year in patients with unstable angina and multivessel disease treated with either stented angioplasty or bypass surgery compared with patients with stable angina. The rate of repeat revascularization of both unstable and stable angina was significantly higher in patients with stents