Zinc deposits and related mineralization of the Burketown mineral field, including the world-class Century Deposit, Northern Australia: Fluid inclusion and stable isotope evidence for basin fluid sources

The stratiform Century Zn-Pb deposit and the discordant Zn-Pb lode deposits of the Burketown mineral field, northern Australia, host ore and gangue minerals with primary fluid inclusions that have not been affected by the Isan orogeny, thus providing a unique opportunity to investigate the nature of the ore-forming brines. All of the deposits are hosted in shales and siltstones belonging to the Isa superbasin and comprise sphalerite, pyrite, carbonate, quartz, galena, minor chalcopyrite, and minor illite. According to Pb model ages, the main ore stage of mineralization at Century formed at I575 Ma, some 20 m.y. after deposition of the host shale sequence. Microthermometry on undeformed, primary fluid inclusions hosted in porous sphalerite shows that the Zn at Century was transported to the deposit by a homogeneous, Ca2+- and Na+-bearing brine with a salinity of 21.6 wt percent NaCl equiv. delta D-fluid of the fluid inclusion water ranges from -89 to -83 per mil, consistent with a basinal brine that evolved from meteoric water. Fluid inclusion homogenization temperatures range between 74 degrees and 125 degrees C, which are lower than the 120 degrees to 160 degrees C range calculated from vitrinite reflectance and illite crystallinity data from the deposit. This discrepancy indicates that mineralization likely formed at 50 to 85 Mpa, corresponding to a depth of 1,900 to 3,100 m. Transgressive galena-sphalerite veins that cut stratiform mineralization at Century and breccia-filled quartz-dolomite-sphalerite-galena veins in the discordant Zn-Pb lodes have Pb model ages between 1575 and 1485 Ma. Raman spectroscopy and microthermometry reveal that the primary fluid inclusions in these veins contain Ca2+, Na+. but they have lower salinities between 23 and 10 wt percent NaCl equiv and higher delta D-fluid values ranging from -89 to -61 per mil than fluid inclusions in porous sphalerite from Century. Fluid inclusion water from sphalerite in one of the lode deposits has delta O-18(fluid) values of 1.6 and 2.4 per mil, indistinguishable from delta O-18(fluid) values between -0.3 to +7.4 per mil calculated from the isotopic composition of coexisting quartz, dolomite, and illite. The trend toward lower salinities and higher delta D-fluid values relative to the earlier mineralizing fluids is attributed to mixing between the fluid that formed Century and a seawater-derived fluid from a different source. Based on seismic data from the Lawn Hill platform and paragenetic and geochemical results from the Leichhardt River fault trough to the south, diagenetic aquifers in the Underlying Calvert superbasin appear to have been the most likely sources for the fluids that formed Century and the discordant lode deposits. Paragenetically late sphalerite and calcite cut sphalerite, quartz, and dolomite in the lode deposits and contain Na+-dominated fluid inclusions with much lower salinities than their older counterparts. The isotopic composition of calcite also indicates delta O-18(fluid) from 3.3 to 10.7 per mil, which is larger than the range obtained from synmineralization minerals, supporting the idea that a unique fluid source was involved. The absolute timing of this event is unclear, but a plethora of Pb model, K-Ar, and Ar-40/Ar-39 ages between 1440 and 1300 Ma indicate that a significant volume of fluid was mobilized at this time. The deposition of the Roper superbasin from ca. 1492 +/- 4 Ma suggests that these late veins formed from fluids that may have been derived from aquifers in overlying sediments of the Roper superbasin. Clear, buck, and drusy quartz in veins unrelated to any form of Pb-Zn mineralization record the last major fluid event in the Burketown mineral field and form distinct outcrops and ridges in the district. Fluid inclusions in these veins indicate formation from a low-salinity, 300 degrees +/- 80 degrees C fluid. Temperatures approaching 300 degrees C recorded in organic matter adjacent to faults and at sequence boundaries correspond to K-Ar ages spanning 1300 to 1100 Ma, which coincides with regional hydrothermal activity in the northern Lawn Hill platform and the emplacement of the Lakeview Dolerite at the time of assemblage of the Rodinia supercontinent.

MHC class I bound to an immunodominant Theileria parva epitope demonstrates unconventional presentation to T cell receptors

T cell receptor (TCR) recognition of peptide-MHC class I (pMHC) complexes is a crucial event in the adaptive immune response to pathogens. Peptide epitopes often display a strong dominance hierarchy, resulting in focusing of the response on a limited number of the most dominant epitopes. Such T cell responses may be additionally restricted by particular MHC alleles in preference to others. We have studied this poorly understood phenomenon using Theileria parva, a protozoan parasite that causes an often fatal lymphoproliferative disease in cattle. Despite its antigenic complexity, CD8+ T cell responses induced by infection with the parasite show profound immunodominance, as exemplified by the Tp1(214-224) epitope presented by the common and functionally important MHC class I allele N*01301. We present a high-resolution crystal structure of this pMHC complex, demonstrating that the peptide is presented in a distinctive raised conformation. Functional studies using CD8+ T cell clones show that this impacts significantly on TCR recognition. The unconventional structure is generated by a hydrophobic ridge within the MHC peptide binding groove, found in a set of cattle MHC alleles. Extremely rare in all other species, this feature is seen in a small group of mouse MHC class I molecules. The data generated in this analysis contribute to our understanding of the structural basis for T cell-dependent immune responses, providing insight into what determines a highly immunogenic p-MHC complex, and hence can be of value in prediction of antigenic epitopes and vaccine design.

Edges and bars: where do people see features in 1-D images?

There have been two main approaches to feature detection in human and computer vision - based either on the luminance distribution and its spatial derivatives, or on the spatial distribution of local contrast energy. Thus, bars and edges might arise from peaks of luminance and luminance gradient respectively, or bars and edges might be found at peaks of local energy, where local phases are aligned across spatial frequency. This basic issue of definition is important because it guides more detailed models and interpretations of early vision. Which approach better describes the perceived positions of features in images? We used the class of 1-D images defined by Morrone and Burr in which the amplitude spectrum is that of a (partially blurred) square-wave and all Fourier components have a common phase. Observers used a cursor to mark where bars and edges were seen for different test phases (Experiment 1) or judged the spatial alignment of contours that had different phases (e.g. 0 degrees and 45 degrees ; Experiment 2). The feature positions defined by both tasks shifted systematically to the left or right according to the sign of the phase offset, increasing with the degree of blur. These shifts were well predicted by the location of luminance peaks (bars) and gradient peaks (edges), but not by energy peaks which (by design) predicted no shift at all. These results encourage models based on a Gaussian-derivative framework, but do not support the idea that human vision uses points of phase alignment to find local, first-order features. Nevertheless, we argue that both approaches are presently incomplete and a better understanding of early vision may combine insights from both. (C)2004 Elsevier Ltd. All rights reserved.

Bend sensors with direction recognition based on long-period gratings written in D-shaped fibre

The curvature- or bend-sensing response of long-period gratings (LPGs) UV inscribed in D-shaped fiber has been investigated experimentally. Strong fiber-orientation dependence of the spectral response when such LPGs are subjected to bending at different directions has been observed and is shown to form the basis for a new class of single-device sensor with vector-sensing capability. Potential applications utilizing the linear response and unique bend-orientation characteristics of the devices are discussed.

Alzheimer's disease: size class frequency distribution of senile plaques: do they indicate when a brain tissue was affected?

The size class frequency distribution of a sample of senile plaques (SP) was determined in a total of 20 brain regions from 5 elderly cases of Alzheimer's disease (AD). The purpose of the study was to determine whether a comparison of the frequency distributions could be used to determine the chronology of SP development in the AD brain. SP from 10 microns to a maximum diameter of 160 microns were present in the tissue and the size class frequency distributions were positively skewed. The frequency distributions varied between brain regions in: (1) the size class containing the mode, (2) the degree of positive skew, and (3) the ratio of large to small SP. In most patients the ratio of large to small SP was higher in the hippocampus or adjacent gyrus compared with temporal, parietal and frontal neocortex. If the diameter of a SP reflects its age in the tissue than the data suggest that SP formed earlier either in the hippocampus or adjacent gyrus compared with the other neocortical tissues. However, this conclusion rests on a number of assumptions including: (1) that SP diameter is directly related to age, (2) that SP development occurs at similar rates in different brain regions and (3) that, once formed, SP are not removed from the tissue by astrocytes.

Bend sensors with direction recognition based on long-period gratings written in D-shaped fiber

The curvature- or bend-sensing response of long-period gratings (LPGs) UV inscribed in D-shaped fiber has been investigated experimentally. Strong fiber-orientation dependence of the spectral response when such LPGs are subjected to bending at different directions has been observed and is shown to form the basis for a new class of single-device sensor with vector-sensing capability. Potential applications utilizing the linear response and unique bend-orientation characteristics of the devices are discussed.

Toward bacterial protein sub-cellular location prediction:single-class discrimminant models for all gram- and gram+ compartments

Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation - which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

A predictor of membrane class:discriminating α-helical and β-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.