Kinetics of coupled Fe(II)-catalysed ferrihydrite transformation and U(VI) reduction

Antimony is released into the environment in some natural and man-induced processes. [1]. Yet, its impact on the transformation processes of heavy metal-adsorbing minerals remains poorly understood. In acid-mine drainage systems and shooting ranges, the adsorption of antimony by iron oxides such as ferrihydrite can play a major role. The poorly crystalline 2-line ferrihydrite represents one of the most common Fe oxides in these settings and can transform to goethite (,-FeOOH) or hematite (,-Fe2O3) with time [2]. The rate of transformation depends on the pH, temperature, and on the ions and molecules present during the transformation process [3]. This study focuses on the transformation of synthetic ferrihydrite to crystalline iron oxides in the presence of Sb(V). Transformations were carried out for 1-16 days at 70 ºC and at pH 4, 7 and 12, with different concentrations of Sb(V) (0.00, 0.23, 0.75, 2.25 and 6.00 mM Sb). Samples taken from aqueous suspensions were washed, dried, and characterized by X-ray diffraction (XRD) and atomic absorption spectroscopy (AAS). At pH 12, goethite (Sb concentrations up to 3.7 mg Sb/g) is favored and the transformation is completed after one day. Only a concentration of 6 mM Sb retarded the transformation, where even after 8 days only 50 % of the ferrihydrite was transformed into goethite. Transformations at pH 7 led to a mixture of 75 % hematite and 25 % goethite (4.3 mg Sb/g). However, at concentrations of 6 mM Sb, feroxyhyte (!- FeOOH) (9.1 mg Sb/g) was favored instead. At pH 4, hematite (32.3 mg Sb/g) was favored except for concentrations of 6 mM Sb, were again feroxyhyte (141.1 mg Sb/g) occurred. We assume that increased Sb concentrations favor feroxyhyte and indicate the incorporation of Sb into the structure of feroxyhyte. © The Author

Ferric iron geometry and coordination during hydrolysis and ferrihydrite precipitation

Definitive structural characterisation of ferrihydrite has challenged scientists primarily due to its nanosized particles and inherent long-range structural disorder which challenges analytical methodology (and modelling) typically employed to determine the structure of minerals. Here we report on the application of a synchrotron quick-scanning X-ray absorption spectroscopy (XAS) approach, which allows the collection of Extended X-ray Absorption Fine Structure (EXAFS) spectral data to k = 15 Å-1 in < 1 minute, to obtain unparalleled iron Kedge data on the hydrolysis of FeIII(H2O)6 and ferrihydrite precipitation. Modelling of the pre-edge and EXAFS data: 1) supports theoretical studies which have suggested the existence of a monomeric penta-coordinated FeIII hydrolysis species and; 2) corroborates recently proposed structural models of ferrihydrite that contain tetrahedral FeIII. Modelling results indicate that ferrihydrite consists of 15 to 25 % tetrahedral FeIII and suggest that this geometry must be included in any comprehensive structural model of ferrihydrite and, furthermore, should be considered when evaluating the reactivity, stability and other structure-property relationships of this mineral. © The Authors

Carbon black and titanium dioxide nanoparticles elicit distinct apoptotic pathways in bronchial epithelial cells

<p>Abstract</p> <p>Background</p> <p>Increasing environmental and occupational exposures to nanoparticles (NPs) warrant deeper insight into the toxicological mechanisms induced by these materials. The present study was designed to characterize the cell death induced by carbon black (CB) and titanium dioxide (TiO₂) NPs in bronchial epithelial cells (16HBE14o- cell line and primary cells) and to investigate the implicated molecular pathways.</p> <p>Results</p> <p>Detailed time course studies revealed that both CB (13 nm) and TiO₂(15 nm) NP exposed cells exhibit typical morphological (decreased cell size, membrane blebbing, peripheral chromatin condensation, apoptotic body formation) and biochemical (caspase activation and DNA fragmentation) features of apoptotic cell death. A decrease in mitochondrial membrane potential, activation of Bax and release of cytochrome <it>c </it>from mitochondria were only observed in case of CB NPs whereas lipid peroxidation, lysosomal membrane destabilization and cathepsin B release were observed during the apoptotic process induced by TiO₂NPs. Furthermore, ROS production was observed after exposure to CB and TiO₂but hydrogen peroxide (H₂O₂) production was only involved in apoptosis induction by CB NPs.</p> <p>Conclusions</p> <p>Both CB and TiO₂NPs induce apoptotic cell death in bronchial epithelial cells. CB NPs induce apoptosis by a ROS dependent mitochondrial pathway whereas TiO₂NPs induce cell death through lysosomal membrane destabilization and lipid peroxidation. Although the final outcome is similar (apoptosis), the molecular pathways activated by NPs differ depending upon the chemical nature of the NPs.</p

Odontoid metastasis: a potential lethal complication

Nearly one third of cervical spine metastasis has a primary breast malignancy. Patients with cervical metastasis have higher mortality due to advanced stage of the malignancy. Treatment is palliative to relieve pain, prevent pathological fracture, improve mobility and function, and prolong survival. We describe a 40-year-old woman with a history of breast cancer who presented with neck and shoulder pain of 1 week duration with no neurological deficit. Following clinical examination, radiographs taken of the cervical spine was normal. Radiographs repeated 3 weeks later revealed a large lytic lesion of the odontoid occupying 70–80% of the peg. Further investigation including magnetic resonance imaging and bone scan showed no further spinal lesions. She underwent cyclical radiotherapy with complete resolution of the odontoid peg lesion and clinically was asymptomatic at 2 years. Metastatic lesions of the odontoid are atypical, and this case reinforces the necessity of early detection to evade disastrous consequences

?2-Microglobulin Amyloid Fibril-Induced Membrane Disruption Is Enhanced by Endosomal Lipids and Acidic pH

Although the molecular mechanisms underlying the pathology of amyloidoses are not well understood, the interaction between amyloid proteins and cell membranes is thought to play a role in several amyloid diseases. Amyloid fibrils of ?2-microglobulin (?2m), associated with dialysis-related amyloidosis (DRA), have been shown to cause disruption of anionic lipid bilayers in vitro. However, the effect of lipid composition and the chemical environment in which ?2m-lipid interactions occur have not been investigated previously. Here we examine membrane damage resulting from the interaction of ?2m monomers and fibrils with lipid bilayers. Using dye release, tryptophan fluorescence quenching and fluorescence confocal microscopy assays we investigate the effect of anionic lipid composition and pH on the susceptibility of liposomes to fibril-induced membrane damage. We show that ?2m fibril-induced membrane disruption is modulated by anionic lipid composition and is enhanced by acidic pH. Most strikingly, the greatest degree of membrane disruption is observed for liposomes containing bis(monoacylglycero)phosphate (BMP) at acidic pH, conditions likely to reflect those encountered in the endocytic pathway. The results suggest that the interaction between ?2m fibrils and membranes of endosomal origin may play a role in the molecular mechanism of ?2m amyloid-associated osteoarticular tissue destruction in DRA

Influences of H on the Adsorption of a Single Ag Atom on Si(111)-7 × 7 Surface

The adsorption of a single Ag atom on both clear Si(111)-7 × 7 and 19 hydrogen terminated Si(111)-7 × 7 (hereafter referred as 19H-Si(111)-7 × 7) surfaces has been investigated using first-principles calculations. The results indicated that the pre-adsorbed H on Si surface altered the surface electronic properties of Si and influenced the adsorption properties of Ag atom on the H terminated Si surface (e.g., adsorption site and bonding properties). Difference charge density data indicated that covalent bond is formed between adsorbed Ag and H atoms on 19H-Si(111)-7 × 7 surface, which increases the adsorption energy of Ag atom on Si surface

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble

<p>Abstract</p> <p>Background</p> <p>Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA interference (RNAi) or small-molecule screens. As such, efficient computational methods are required for automatic cellular phenotype identification capable of dealing with large image data sets. In this paper we investigated an efficient method for the extraction of quantitative features from images by combining second order statistics, or Haralick features, with curvelet transform. A random subspace based classifier ensemble with multiple layer perceptron (MLP) as the base classifier was then exploited for classification. Haralick features estimate image properties related to second-order statistics based on the grey level co-occurrence matrix (GLCM), which has been extensively used for various image processing applications. The curvelet transform has a more sparse representation of the image than wavelet, thus offering a description with higher time frequency resolution and high degree of directionality and anisotropy, which is particularly appropriate for many images rich with edges and curves. A combined feature description from Haralick feature and curvelet transform can further increase the accuracy of classification by taking their complementary information. We then investigate the applicability of the random subspace (RS) ensemble method for phenotype classification based on microscopy images. A base classifier is trained with a RS sampled subset of the original feature set and the ensemble assigns a class label by majority voting.</p> <p>Results</p> <p>Experimental results on the phenotype recognition from three benchmarking image sets including HeLa, CHO and RNAi show the effectiveness of the proposed approach. The combined feature is better than any individual one in the classification accuracy. The ensemble model produces better classification performance compared to the component neural networks trained. For the three images sets HeLa, CHO and RNAi, the Random Subspace Ensembles offers the classification rates 91.20%, 98.86% and 91.03% respectively, which compares sharply with the published result 84%, 93% and 82% from a multi-purpose image classifier WND-CHARM which applied wavelet transforms and other feature extraction methods. We investigated the problem of estimation of ensemble parameters and found that satisfactory performance improvement could be brought by a relative medium dimensionality of feature subsets and small ensemble size.</p> <p>Conclusions</p> <p>The characteristics of curvelet transform of being multiscale and multidirectional suit the description of microscopy images very well. It is empirically demonstrated that the curvelet-based feature is clearly preferred to wavelet-based feature for bioimage descriptions. The random subspace ensemble of MLPs is much better than a number of commonly applied multi-class classifiers in the investigated application of phenotype recognition.</p

Pattern Recognition Software and Techniques for Biological Image Analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays

The impact of lidocaine plaster prescribing reduction strategies: A comparison of two national health services in Europe

AIMS: In 2017, two distinct interventions were implemented in Ireland and England to reduce prescribing of lidocaine medicated plasters. In Ireland, restrictions on reimbursement were introduced through implementation of an application system for reimbursement. In England, updated guidance on items which should not be routinely prescribed in primary care, including lidocaine plasters, was published. This study aims to compare how the interventions impacted prescribing of lidocaine plasters in these countries. METHODS: We conducted an interrupted time-series study using general practice data. For Ireland, monthly dispensing data (2015-2019) from the means-tested General Medical Services (GMS) scheme was used. For England, data covered all patients. Outcomes were the rate of dispensings, quantity and costs of lidocaine plasters, and we modelled level and trend changes from the first full month of the policy/guidance change. RESULTS: Ireland had higher rates of lidocaine dispensings compared to England throughout the study period; this was 15.22/1000 population immediately pre-intervention, and there was equivalent to a 97.2% immediate reduction following the intervention. In England, the immediate pre-intervention dispensing rate was 0.36/1000, with an immediate reduction of 0.0251/1000 (a 5.8% decrease), followed by a small but significant decrease in the monthly trend relative to the pre-intervention trend of 0.0057 per month. CONCLUSIONS: Among two different interventions aiming to decrease low-value lidocaine plaster prescribing, there was a substantially larger impact in Ireland of reimbursement restriction compared to issuing guidance in England. However, this is in the context of much higher baseline rates of use in Ireland compared to England