Probabilistic modeling of one dimensional water movement and leaching from highway embankments containing secondary materials

Predictive methods for contaminant release from virgin and secondary road construction materials are important for evaluating potential long-term soil and groundwater contamination from highways. The objective of this research was to describe the field hydrology in a highway embankment and to investigate leaching under unsaturated conditions by use of a contaminant fate and transport model. The HYDRUS2D code was used to solve the Richards equation and the advection–dispersion equation with retardation. Water flow in a Minnesota highway embankment was successfully modeled in one dimension for several rain events after Bayesian calibration of the hydraulic parameters against water content data at a point 0.32 m from the surface of the embankment. The hypothetical leaching of Cadmium from coal fly ash was probabilistically simulated in a scenario where the top 0.50 m of the embankment was replaced by coal fly ash. Simulation results were compared to the percolation equation method where the solubility is multiplied by the liquid-to-solid ratio to estimate total release. If a low solubility value is used for Cadmium, the release estimates obtained using the percolation/equilibrium model are close to those predicted from HYDRUS2D simulations (10–4–10–2 mg Cd/kg ash). If high solubility is used, the percolation equation over predicts the actual release (0.1–1.0 mg Cd/kg ash). At the 90th percentile of uncertainty, the 10-year liquid-to-solid ratio for the coal fly ash embankment was 9.48 L/kg, and the fraction of precipitation that infiltrated the coal fly ash embankment was 92%. Probabilistic modeling with HYDRUS2D appears to be a promising realistic approach to predicting field hydrology and subsequent leaching in embankments

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions

Safety and Pharmacokinetics of Chimeric Anti-Shiga Toxin 1 and Anti-Shiga Toxin 2 Monoclonal Antibodies in Healthy Volunteers▿

Shiga toxin (Stx)-producing Escherichia coli (STEC) causes hemorrhagic colitis and hemolytic-uremic syndrome (HUS). The rates of STEC infection and complications, including death, are highest among young children and elderly individuals. There are no causal therapies. Because Stx is the primary pathological agent leading to organ injury in patients with STEC disease, therapeutic antibodies are being developed to neutralize systemically absorbed toxin during the early phase of the infection. Two phase I, single-dose, open-label, nonrandomized studies were conducted to evaluate the safety and pharmacokinetics of the chimeric monoclonal antibodies (antitoxins) against Stx 1 and 2 (cαStx1 and cαStx2, respectively). In the first study, 16 volunteers received 1 or 3 mg/kg of body weight of cαStx1 or cαStx2 as a single, short (1-h) intravenous infusion (n = 4 per group). In a second study, 10 volunteers received a 1-h infusion of cαStx1 and cαStx2 combined at 1 or 3 mg/kg (n = 5 per group). Treatment-emergent adverse events were mild, resolved spontaneously, and were generally unrelated to the antibody infusion. No serious adverse events were observed. Human antichimeric antibodies were detected in a single blood sample collected on day 57. Antibody clearance was slightly greater for cαStx1 (0.38 ± 0.16 ml/h/kg [mean ± standard deviation]) than for cαStx2 (0.20 ± 0.07 ml/h/kg) (P = 0.0013, t test). The low clearance is consistent with the long elimination half-lives of cαStx1 (190.4 ± 140.2 h) and cαStx2 (260.6 ± 112.4 h; P = 0.151). The small volume of distribution (0.08 ± 0.05 liter/kg, combined data) indicates that the antibodies are retained within the circulation. The conclusion is that cαStx1 and cαStx2, given as individual or combined short intravenous infusions, are well tolerated. These results form the basis for future safety and efficacy trials with patients with STEC infections to ameliorate or prevent HUS and other complications

Vitamin D status is inversely associated with anemia and serum erythropoietin during pregnancy

ABSTRACTBackground: Vitamin D and iron deficiencies frequently co-exist.It is now appreciated that mechanistic interactions between iron andvitamin D metabolism may underlie these associations.Objective: We examined interrelations between iron and vitamin Dstatus and their regulatory hormones in pregnant adolescents, whoare a group at risk of both suboptimal vitamin D and suboptimaliron status.Design: The trial was a prospective longitudinal study of 158 pregnantadolescents (aged #18 y). Maternal circulating biomarkers ofvitamin D and iron were determined at midgestation (w25 wk) anddelivery (w40 wk). Linear regression was used to assess associationsbetween vitamin D and iron status indicators. Bivariate andmultivariate logistic regressions were used to generate the OR ofanemia as a function of vitamin D status. A mediation analysis wasperformed to examine direct and indirect relations between vitaminD status, hemoglobin, and erythropoietin in maternal serum.Results: Maternal 25-hydroxyvitamin D [25(OH)D] was positivelyassociated with maternal hemoglobin at both midgestation and atdelivery (P , 0.01 for both). After adjustment for age at enrollmentand race, the odds of anemia at delivery was 8 times greater inadolescents with delivery 25(OH)D concentrations ,50 nmol/L thanin those with 25(OH)D concentrations $50 nmol/L (P ,0.001).Maternal 25(OH)D was inversely associated with erythropoietin atboth midgestation (P ,0.05) and delivery (P ,0.001). The significantrelation observed between 25(OH)D and hemoglobin could beexplained by a direct relation between 25(OH)D and hemoglobin andan indirect relation that was mediated by erythropoietin.Conclusions: In this group of pregnant adolescents, suboptimal vitaminD status was associated with increased risk of iron insufficiency andvice versa. These findings emphasize the need for screening for multiplenutrient deficiencies during pregnancy and greater attention tooverlapping metabolic pathways when selecting prenatal supplementationregimens