Mechanism and kinetics of mineral weathering under acid conditions

This study deals with the relationships between crystal structure, grain diameter, surface morphology and dissolution kinetics for feldspar and quartz under acid conditions.Intensively ground samples from large, naturally weathered mineral fragments are frequently used in dissolution studies. The surface area of such samples, estimated from their gas adsorption isotherm (BET method), is normally implied to be all freshly created by grinding. This study revealed that: (1) during natural weathering, micropores (diameters ≈2 nm) develop in feldspar but not in quartz grains; (2) the micropores account for virtually all BET surface area of naturally weathered feldspar grains; and (3) due to the micropores, grinding of large, naturally weathered feldspar fragments is highly ineffective in creating samples with only freshly ground BET surface area.By assuming all BET surface area of ground feldspar samples to be freshly created, experimental dissolution data have been explained from dissolution rates essentially independent of the grain diameter. For ground feldspar samples this study revealed that: (1) the dissolution rate of the freshly created BET surfaces is essentially proportional to the grain diameter; and (2) the dissolution rate of the naturally weathered BET surfaces, still present after grinding, is most likely independent of the grain diameter. Moreover, the dissolution rate, normalized to BET surface area, of unfractured, naturally weathered feldspar grains was essentially independent of the grain diameter. These findings can be explained if: (1) the average density of dissolution sites on freshly created feldspar surfaces is approximately proportional to the grain diameter; (2) micropores develop at dissolution sites during natural weathering; and (3) the BET surface area of the micropore "walls" (i.e. the area perpendicular to the grain surface) is essentially non-reactive.Thermodynamical considerations and Monte Carlo simulations showed that: (1) the formation of micropores in feldspar but not in quartz grains during natural weathering can be explained from enhanced dissolution at crystal defects; and (2) the BET surface area of micropore "walls" from enhanced dissolution at crystal defects is essentially non-reactive. A kinetic model is developed, showing for feldspar that the non-reactivity of the micropore "walls" helps to explain the discrepancy, reported in the literature, between laboratory and field dissolution rates

Macrofilaricidal Activity in Wuchereria bancrofti after 2 Weeks Treatment with a Combination of Rifampicin plus Doxycycline

Infection with the filarial nematode Wuchereria bancrofti can lead to lymphedema, hydrocele, and elephantiasis. Since adult worms cause pathology in lymphatic filariasis (LF), it is imperative to discover macrofilaricidal drugs for the treatment of the infection. Endosymbiotic Wolbachia in filariae have emerged as a new target for antibiotics which can lead to macrofilaricidal effects. In Ghana, a pilot study was carried out with 39 LF-infected men; 12 were treated with 200 mg doxycycline/day for 4 weeks, 16 were treated with a combination of 200 mg doxycycline/day + 10 mg/kg/day rifampicin for 2 weeks, and 11 patients received placebo. Patients were monitored for Wolbachia and microfilaria loads, antigenaemia, and filarial dance sign (FDS). Both 4-week doxycycline and the 2-week combination treatment reduced Wolbachia load significantly. At 18 months posttreatment, four-week doxycycline resulted in 100% adult worm loss, and the 2-week combination treatment resulted in a 50% adult worm loss. In conclusion, this pilot study with a combination of 2-week doxycycline and rifampicin demonstrates moderate macrofilaricidal activity against W. bancrofti

A semi-supervised large margin algorithm for white matter hyperintensity segmentation

Precise detection and quantification of white matter hyperintensities (WMH) is of great interest in studies of neurodegenerative diseases (NDs). In this work, we propose a novel semi-supervised large margin algorithm for the segmentation of WMH. The proposed algorithm optimizes a kernel based max-margin objective function which aims to maximize the margin averaged over inliers and outliers while exploiting a limited amount of available labelled data. We show that the learning problem can be formulated as a joint framework learning a classifier and a label assignment simultaneously, which can be solved efficiently by an iterative algorithm. We evaluate our method on a database of 280 brain Magnetic Resonance (MR) images from subjects that either suffered from subjective memory complaints or were diagnosed with NDs. The segmented WMH volumes correlate well with the standard clinical measurement (Fazekas score), and both the qualitative visualization results and quantitative correlation scores of the proposed algorithm outperform other well known methods for WMH segmentation

A large margin algorithm for automated segmentation of white matter hyperintensity

Precise detection and quantification of white matter hyperintensity (WMH) is of great interest in studies of neurological and vascular disorders. In this work, we propose a novel method for automatic WMH segmentation with both supervised and semi-supervised large margin algorithms provided by the framework. The proposed algorithms optimize a kernel based max-margin objective function which aims to maximize the margin between inliers and outliers. We show that the semi-supervised learning problem can be formulated to learn a classifier and label assignment simultaneously, which can be solved efficiently by an iterative algorithm. The model is learned first via the supervised approach and then fine-tuned on a target image by using the semi-supervised algorithm. We evaluate our method on 88 brain fluid-attenuated inversion recovery (FLAIR) magnetic resonance (MR) images from subjects with vascular disease. Quantitative evaluation of the proposed approach shows that it outperforms other well known methods for WMH segmentation

Comprehensive Brain MRI Segmentation in High Risk Preterm Newborns

Most extremely preterm newborns exhibit cerebral atrophy/growth disturbances and white matter signal abnormalities on MRI at term-equivalent age. MRI brain volumes could serve as biomarkers for evaluating the effects of neonatal intensive care and predicting neurodevelopmental outcomes. This requires detailed, accurate, and reliable brain MRI segmentation methods. We describe our efforts to develop such methods in high risk newborns using a combination of manual and automated segmentation tools. After intensive efforts to accurately define structural boundaries, two trained raters independently performed manual segmentation of nine subcortical structures using axial T2-weighted MRI scans from 20 randomly selected extremely preterm infants. All scans were re-segmented by both raters to assess reliability. High intra-rater reliability was achieved, as assessed by repeatability and intra-class correlation coefficients (ICC range: 0.97 to 0.99) for all manually segmented regions. Inter-rater reliability was slightly lower (ICC range: 0.93 to 0.99). A semi-automated segmentation approach was developed that combined the parametric strengths of the Hidden Markov Random Field Expectation Maximization algorithm with non-parametric Parzen window classifier resulting in accurate white matter, gray matter, and CSF segmentation. Final manual correction of misclassification errors improved accuracy (similarity index range: 0.87 to 0.89) and facilitated objective quantification of white matter signal abnormalities. The semi-automated and manual methods were seamlessly integrated to generate full brain segmentation within two hours. This comprehensive approach can facilitate the evaluation of large cohorts to rigorously evaluate the utility of regional brain volumes as biomarkers of neonatal care and surrogate endpoints for neurodevelopmental outcomes

The Rotterdam Scan Study: design and update up to 2012

Neuroimaging plays an important role in etiologic research on neurological diseases in the elderly. The Rotterdam Scan Study was initiated as part of the ongoing Rotterdam Study with the aim to unravel causes of neurological disease by performing neuroimaging in a population-based longitudinal setting. In 1995 and 1999 random subsets of the Rotterdam Study underwent neuroimaging, whereas from 2005 onwards MRI has been implemented into the core protocol of the Rotterdam Study. In this paper, we discuss the background and rationale of the Rotterdam Scan Study. We also describe the imaging protocol and post-processing techniques, and highlight the main findings to date. Finally, we make recommendations for future research, which will also be the main focus of investigation in the Rotterdam Scan Study