Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia

Event-based models (EBM) are a class of disease progression models that can be used to estimate temporal ordering of neuropathological changes from cross-sectional data. Current EBMs only handle scalar biomarkers, such as regional volumes, as inputs. However, regional aggregates are a crude summary of the underlying high-resolution images, potentially limiting the accuracy of EBM. Therefore, we propose a novel method that exploits high-dimensional voxel-wise imaging biomarkers: n-dimensional discriminative EBM (nDEBM). nDEBM is based on an insight that mixture modeling, which is a key element of conventional EBMs, can be replaced by a more scalable semi-supervised support vector machine (SVM) approach. This SVM is used to estimate the degree of abnormality of each region which is then used to obtain subject-specific disease progression patterns. These patterns are in turn used for estimating the mean ordering by fitting a generalized Mallows model. In order to validate the biomarker ordering obtained using nDEBM, we also present a framework for Simulation of Imaging Biomarkers' Temporal Evolution (SImBioTE) that mimics neurodegeneration in brain regions. SImBioTE trains variational auto-encoders (VAE) in different brain regions independently to simulate images at varying stages of disease progression. We also validate nDEBM clinically using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). In both experiments, nDEBM using high-dimensional features gave better performance than state-of-the-art EBM methods using regional volume biomarkers. This suggests that nDEBM is a promising approach for disease progression modeling.Comment: IPMI 201

Foreign national prisoners in the UK: explanations and implications

This article examines the rapid expansion of the foreign national prison population in the UK against a backdrop of public and political anxiety about immigration and crime. It explores official data considering some of the possible explanations for the growth in the number of foreign national prisoners and the implications this has for penal management. Whilst increases in both the number of foreign nationals entering the UK and the number of foreign nationals in UK prisons has strengthened the association between immigration and crime in the public imagination, there is little empirical evidence to suggest that foreign nationals are more dangerous than British nationals. Instead, the growth of the foreign national prison population appears to stem from a number of sources that may operate alone or in tandem

Electron transport and band structure in phosphorus-doped polycrystalline silicon films

We study transport mechanisms, effective mass, and band structure by measuring the resistivity, Hall, and Seebeck and Nernst coefficients in heavily phosphorus-doped polycrystalline silicon films made by thermal crystallization of amorphous silicon. We observe a change in transport mechanism which results in an increase in electron mobility from 10% to 80% of the single-crystal silicon mobility as the carrier concentration increases from 1019 to 1020 cm-3. Our measurements of effective mass at the Fermi level indicate that as the carrier concentration increases, there is a shift from impurity-band transport to conduction-band transport, and that the electron effective mass is lower in the impurity band than in the conduction band of Si. The shift to conduction-band transport improves electron mobility with carrier density by improving intragrain carrier mean free path lengths and relaxation times. © 2009 American Institute of Physics.published_or_final_versio

Analysis of benzo[c] phenanthridine alkaloids in Eschscholtzia californica cell culture using HPLC-DAD and HPLC-ESI-MS/MS

Effective HPLC-DAD and HPLC-ESI-MS/MS methods have been developed for the analysis of eight benzo[c] phenanthridine alkaloids (sanguinarine, chelirubine, macarpine, chelerythrine, dihydrosanguinarine, dihydrochelirubine, dihydromacarpine and dihydrochelerythrine), which are important metabolites in Eschscholtzia californica cell culture. By adopting a ternary gradient pump system, the dihydro-form alkaloids hardly separable from each other could be successfully separated, and all the target alkaloids could be simultaneously quantified with the LOD values of 0.01-0.79 mu g/mL and the LOQ values of 0.03-3.59 mu g/mL. This HPLC-DAD method was further confirmed by HPLC-ESI-MS/MS system in multiple reaction monitoring mode. Each separated HPLC peak was identified as the target alkaloid, showing its relevant ionized molecule and selected fragment ion. By applying the established method, alkaloid production during the E. californica cell culture could be successfully monitored and some valuable information on its metabolism could be deduced.11Ysciescopu

Gut microbial activity as influenced by fiber digestion: dynamic metabolomics in an in vitro colon simulator

Understanding the interaction between the gut microbial activity and the host is essential, and in vitro models are being used to test and develop hypotheses regarding the impact of food components/drugs on the human gut ecosystem. However, while in vitro models provide excellent possibilities for dynamic investigations, studies have commonly been restricted to analyses of few, targeted metabolites. In the present study, we employed NMR-based metabolomics combined with multilevel data analysis as a tool to characterize the impact of polydextrose (PDX) fiber on the in vitro derived fecal metabolome. This approach enabled us to identify and quantify the fiber-induced response on several fecal metabolites; we observed higher levels of butyrate, acetate, propionate, succinate, N-acetyl compound and a lower level of amino acids (leucine, valine, isoleucine, phenylalanine, and lysine), valerate, formate, isovalerate and trimethylamine among the PDX-treated sample compared to the control samples. In addition, by the application of multilevel data analysis we were able to examine the specific inter-individual variations, and caprylic acid was identified to be the main marker of distinct microbial compositions among the subjects. Our work is expected to provide a useful approach to understand the metabolic impact of potential prebiotic compounds and get deeper insight into the molecular regulation of gut-microbe activities in the complex gut system

Microphysical sensitivity of coupled springtime Arctic stratocumulus to modelled primary ice over the ice pack, marginal ice, and ocean

This study uses large eddy simulations to test the sensitivity of single-layer mixed-phase stratocumulus to primary ice number concentrations in the European Arctic. Observations from the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign are considered for comparison with cloud microphysics modelled using the Large Eddy Model (LEM, UK Met. Office). We find that cloud structure is very sensitive to ice number concentrations, Nice, and small increases can cause persisting mixed-phase clouds to glaciate and break up. Three key dependencies on Nice are identified from sensitivity simulations and comparisons with observations made over the sea ice pack, marginal ice zone (MIZ), and ocean. Over sea ice, we find deposition–condensation ice formation rates are overestimated, leading to cloud glaciation. When ice formation is limited to water-saturated conditions, we find microphysics comparable to aircraft observations over all surfaces considered. We show that warm supercooled (−13°C) mixed-phase clouds over the MIZ are simulated to reasonable accuracy when using both the DeMott et al.(2010) and Cooper(1986) primary ice nucleation parameterisations. Over the ocean, we find a strong sensitivity of Arctic stratus to Nice. The Cooper(1986) parameterisation performs poorly at the lower ambient temperatures, leading to a comparatively higher Nice (2.43L−1 at the cloud-top temperature, approximately −20°C) and cloud glaciation. A small decrease in the predicted Nice (2.07L−1 at −20°C), using the DeMott et al.(2010) parameterisation, causes mixed-phase conditions to persist for 24h over the ocean. However, this representation leads to the formation of convective structures which reduce the cloud liquid water through snow precipitation, promoting cloud break-up through a depleted liquid phase. Decreasing the Nice further (0.54L−1, using a relationship derived from ACCACIA observations) allows mixed-phase conditions to be maintained for at least 24h with more stability in the liquid and ice water paths. Sensitivity to Nice is also evident at low number concentrations, where 0.1 ×  Nice predicted by the DeMott et al.(2010) parameterisation results in the formation of rainbands within the model; rainbands which also act to deplete the liquid water in the cloud and promote break-up

Born radicals? Prevent, positivism, and ‘race-thinking’

In the contemporary Western climate, counter-terrorism discourse dealing with so-called Islamic extremism appears to be obsessed with trying to understand the motives behind what prompts somebody to turn to terrorism. This paper will argue that attempts to locate extremist motives in such a way can be seen to reinforce earlier iterations of positivist criminology and race-thinking. Through a critical examination of the works of criminologist Cesare Lombroso, this paper will tease out the interconnections between his ‘criminal types’ thesis, and the British government’s current Prevent policy that seeks to identify ‘extremist types.’ By developing a rich critique of these positivist approaches, the paper will go on to question how we might think beyond the essentialism, reductivism, and racism/Islamophobia inherent within such frameworks. In this way, the paper raises a series of conceptual implications for criminology and terrorism studies, while at the same time, develops a contribution to critical race and ethnicity studies

Impact of N-myc amplification on median survival in children with neuroblastoma

Background: Neuroblastoma is the most common extracranial malignant solid tumor in children under 5 years, and it is characterized by wide clinical and biological heterogeneity. N-myc oncogene amplification is considered to be one of the most important prognostic factors used to evaluate survival in these patients. Objectives: The aim of our study was to determine amplification of the N-myc oncogene using real-time quantitative polymerase chain reaction (PCR) and to show the influence of N-myc amplified tumors on the overall survival rate. Patients and Methods: This study is an analytical historical cohort study of forty children with neuroblastoma admitted to the Shafa Hospital, Iran from 1999 to 2010. Paraffined blocks of tumoral tissue were analyzed for N-myc amplification by a PCR. The degree of N-myc amplification was derived from the ratio of the N-myc oncogene and the single copy reference gene, NAGK. In the statistical analysis, a Kaplan-Meier survival analysis was used. Results: We found a variable degree of N-myc amplification, from 3 to 2 200, in 32 of the 40 neuroblastomas (80%). NMYC amplification was seen more frequently in patients older than 2.5 years (71.9%), stage 4 (65.6%) and female (53.1%). Median survival time in the males was significantly longer than in the females (P = 0.03). The overall median survival for N-myc amplified tumor patients was 20 months, and 30 months for the non amplified tumors. Conclusions: The N-myc amplified tumors may increase the probability of more aggressive behavior and rapid tumor progression, especially in advanced stages of neuroblastoma. This study confirmed the importance of obtaining correct measurements of oncogene amplification in the early evaluation of neuroblastomas in order to target more aggressive therapies in patients with a higher risk of cancer progression