Temporal Characterization of Ossification of the Crania in Australian Subadults: New standards for Age Estimation using Computed Tomography

After attending this presentation, attendees will gain awareness of the ontogeny of cranial maturation, specifically: (1) the fusion timings of primary ossification centers in the basicranium; and (2) the temporal pattern of closure of the anterior fontanelle, to develop new population-specific age standards for medicolegal death investigation of Australian subadults. This presentation will impact the forensic science community by demonstrating the potential of a contemporary forensic subadult Computed Tomography (CT) database of cranial scans and population data, to recalibrate existing standards for age estimation and quantify growth and development of Australian children. This research welcomes a study design applicable to all countries faced with paucity in skeletal repositories. Accurate assessment of age-at-death of skeletal remains represents a key element in forensic anthropology methodology. In Australian casework, age standards derived from American reference samples are applied in light of scarcity in documented Australian skeletal collections. Currently practitioners rely on antiquated standards, such as the Scheuer and Black1 compilation for age estimation, despite implications of secular trends and population variation. Skeletal maturation standards are population specific and should not be extrapolated from one population to another, while secular changes in skeletal dimensions and accelerated maturation underscore the importance of establishing modern standards to estimate age in modern subadults. Despite CT imaging becoming the gold standard for skeletal analysis in Australia, practitioners caution the application of forensic age standards derived from macroscopic inspection to a CT medium, suggesting a need for revised methodologies. Multi-slice CT scans of subadult crania and cervical vertebrae 1 and 2 were acquired from 350 Australian individuals (males: n=193, females: n=157) aged birth to 12 years. The CT database, projected at 920 individuals upon completion (January 2014), comprises thin-slice DICOM data (resolution: 0.5/0.3mm) of patients scanned since 2010 at major Brisbane Childrens Hospitals. DICOM datasets were subject to manual segmentation, followed by the construction of multi-planar and volume rendering cranial models, for subsequent scoring. The union of primary ossification centers of the occipital bone were scored as open, partially closed or completely closed; while the fontanelles, and vertebrae were scored in accordance with two stages. Transition analysis was applied to elucidate age at transition between union states for each center, and robust age parameters established using Bayesian statistics. In comparison to reported literature, closure of the fontanelles and contiguous sutures in Australian infants occur earlier than reported, with the anterior fontanelle transitioning from open to closed at 16.7±1.1 months. The metopic suture is closed prior to 10 weeks post-partum and completely obliterated by 6 months of age, independent of sex. Utilizing reverse engineering capabilities, an alternate method for infant age estimation based on quantification of fontanelle area and non-linear regression with variance component modeling will be presented. Closure models indicate that the greatest rate of change in anterior fontanelle area occurs prior to 5 months of age. This study complements the work of Scheuer and Black1, providing more specific age intervals for union and temporal maturity of each primary ossification center of the occipital bone. For example, dominant fusion of the sutura intra-occipitalis posterior occurs before 9 months of age, followed by persistence of a hyaline cartilage tongue posterior to the foramen magnum until 2.5 years; with obliteration at 2.9±0.1 years. Recalibrated age parameters for the atlas and axis are presented, with the anterior arch of the atlas appearing at 2.9 months in females and 6.3 months in males; while dentoneural, dentocentral and neurocentral junctions of the axis transitioned from non-union to union at 2.1±0.1 years in females and 3.7±0.1 years in males. These results are an exemplar of significant sexual dimorphism in maturation (p<0.05), with girls exhibiting union earlier than boys, justifying the need for segregated sex standards for age estimation. Studies such as this are imperative for providing updated standards for Australian forensic and pediatric practice and provide an insight into skeletal development of this population. During this presentation, the utility of novel regression models for age estimation of infants will be discussed, with emphasis on three-dimensional modeling capabilities of complex structures such as fontanelles, for the development of new age estimation methods.

Whole-genome multiparametric screening to identify modulators of epithelial-to-mesenchymal transition

Metastasis accounts for the poor prognosis of the majority of solid tumors. The phenotypic transition of nonmotile epithelial tumor cells to migratory and invasive “mesenchymal” cells (epithelial-to-mesenchymal transition [EMT]) enables the transit of cancer cells from the primary tumor to distant sites. There is no single marker of EMT; rather, multiple measures are required to define cell state. Thus, the multiparametric capability of high-content screening is ideally suited for the comprehensive analysis of EMT regulators. The aim of this study was to generate a platform to systematically identify functional modulators of tumor cell plasticity using the bladder cancer cell line TSU-Pr1-B1 as a model system. A platform enabling the quantification of key EMT characteristics, cell morphology and mesenchymal intermediate filament vimentin, was developed using the fluorescent whole-cell-tracking reagent CMFDA and a fluorescent promoter reporter construct, respectively. The functional effect of genome-wide modulation of protein-coding genes and miRNAs coupled with those of a collection of small-molecule kinase inhibitors on EMT was assessed using the Target Activation Bioapplication integrated in the Cellomics ArrayScan platform. Data from each of the three screens were integrated to identify a cohort of targets that were subsequently examined in a validation assay using siRNA duplexes. Identification of established regulators of EMT supports the utility of this screening approach and indicated capacity to identify novel regulators of this plasticity program. Pathway analysis coupled with interrogation of cancer-related expression profile databases and other EMT-related screens provided key evidence to prioritize further experimental investigation into the molecular regulators of EMT in cancer cells.

One-step homogeneous C-reactive protein assay for saliva

Background: Cardiovascular disease is the leading cause of death in the world. Human C-reactive protein (CRP) has been used in the risk assessment of coronary events. Human saliva mirrors the body's health and well-being and is non-invasive, easy to collect and ideal for third world countries as well as for large patient screening. The aim was to establish a saliva CRP reference range and to demonstrate the clinical utility of salivary CRP levels in assessing the coronary events in a primary health care setting. Methods: We have used a homogeneous bead based assay to detect CRP levels in human saliva. We have developed a rapid 15 min (vs 90 min), sequential, one-step assay to detect CRP in saliva. Saliva was collected from healthy volunteers (n = 55, ages 20-70 years) as well as from cardiac patients (n = 28, ages 43-86 years). Results: The assay incubation time was optimised from 90 min to 15 mm and generated a positive correlation (n = 29, range 10-2189 pg/mL, r2 = 0.94; Passing Bablok slope 0.885. Intercept 0, p>0.10), meaning we could decrease the incubation time and produce equivalent results with confidence. The mean CRP level in the saliva of healthy human volunteers was 285 pg/mL and in cardiac patients was 1680 pg/mL (p<0.01). Analysis of CRP concentrations in paired serum and saliva samples from cardiac patients gave a positive correlation (r2 = 0.84, p<0.001) and the salivary CRP concentration capable of distinguishing healthy from diseased patients. Conclusions: The results suggest that this minimally invasive, rapid and sensitive assay will be useful in large patient screening studies for risk assessment of coronary events. (C) 2011 Elsevier B.V. All rights reserved.

A new approach to spatial data interpolation using higher-order statistics

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

Investigations of ultrafine particles emitted by ships and other transport modes in the port of Brisbane

This research measured particle and gaseous emissions from ships and trains operating within the Port of Brisbane, and explored their influence on ambient air composition at a downwind suburban measurement site. The ship and train emission factor investigations resulted in the development of novel measurement techniques which permit the quantification of particle and gaseous emission factors using samples collected from post-emission exhaust plumes. The urban influence investigation phase of the project produced a new approach to identifying influences from ship emissions.

Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes

Purpose The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). Methods Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. Results For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm2, 16.0 ± 3.9 mm/mm2, and 16.5 ± 3.6 mm/mm2, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87–0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland–Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). Conclusions Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

Combining opinions for use in Bayesian networks: A measurement error approach

Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasing popular in a range of fields including ecology, computational biology, medical diagnosis, and forensics. In most of these cases, the BNs are quantified using information from experts, or from user opinions. An interest therefore lies in the way in which multiple opinions can be represented and used in a BN. This paper proposes the use of a measurement error model to combine opinions for use in the quantification of a BN. The multiple opinions are treated as a realisation of measurement error and the model uses the posterior probabilities ascribed to each node in the BN which are computed from the prior information given by each expert. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the lack of the conditional independence structure of the BN being maintained, and the provision of only a point estimate for the consensus. The proposed model is applied an existing Bayesian Network and performed well when compared to existing methods of combining opinions.

Enhancing Raman signal sufficiently for practical sensing applications

Techniques are presented for enhancing weak Raman scattering signals for rapid yet accurate substance detection. Novel surfaces that allow signal enhancement quantification are described as are eye-safe methodologies that maximize the stand-off Raman detection range.

Piecing the puzzle together : enhancing the quality of road trauma surveillance through linkage of police and health data

This program of research linked police and health data collections to investigate the potential benefits for road safety in terms of enhancing the quality of data. This research has important implications for road safety because, although police collected data has historically underpinned efforts in the area, it is known that many road crashes are not reported to police and that these data lack specific injury severity information. This research shows that data linkage provides a more accurate quantification of the severity and prevalence of road crash injuries which is essential for: prioritising funding; targeting interventions; and estimating the burden and cost of road trauma.

Characterization of acyl chain position in unsaturated phosphatidylcholines using differential mobility-mass spectrometry

Glycerophospholipids (GPs) that differ in the relative position of the two fatty acyl chains on the glycerol backbone (i.e., sn-positional isomers) can have distinct physicochemical properties. The unambiguous assignment of acyl chain position to an individual GP represents a significant analytical challenge. Here we describe a workflow where phosphatidylcholines (PCs) are subjected to ESI for characterization by a combination of differential mobility spectrometry and MS (DMS-MS). When infused as a mixture, ions formed from silver adduction of each phospholipid isomer {e.g., [PC (16:0/18:1) + Ag]+ and [PC (18:1/16:0) + Ag]+} are transmitted through the DMS device at discrete compensation voltages. Varying their relative amounts allows facile and unambiguous assignment of the sn-positions of the fatty acyl chains for each isomer. Integration of the well-resolved ion populations provides a rapid method (< 3 min) for relative quantification of these lipid isomers. The DMS-MS results show excellent agreement with established, but time-consuming, enzymatic approaches and also provide superior accuracy to methods that rely on MS alone. The advantages of this DMS-MS method in identification and quantification of GP isomer populations is demonstrated by direct analysis of complex biological extracts without any prior fractionation.

Global variation in the prevalence and incidence of major depressive disorder : a systematic review of the epidemiological literature

Background Summarizing the epidemiology of major depressive disorder (MDD) at a global level is complicated by significant heterogeneity in the data. The aim of this study is to present a global summary of the prevalence and incidence of MDD, accounting for sources of bias, and dealing with heterogeneity. Findings are informing MDD burden quantification in the Global Burden of Disease (GBD) 2010 Study. Method A systematic review of prevalence and incidence of MDD was undertaken. Electronic databases Medline, PsycINFO and EMBASE were searched. Community-representative studies adhering to suitable diagnostic nomenclature were included. A meta-regression was conducted to explore sources of heterogeneity in prevalence and guide the stratification of data in a meta-analysis. Results The literature search identified 116 prevalence and four incidence studies. Prevalence period, sex, year of study, depression subtype, survey instrument, age and region were significant determinants of prevalence, explaining 57.7% of the variability between studies. The global point prevalence of MDD, adjusting for methodological differences, was 4.7% (4.4–5.0%). The pooled annual incidence was 3.0% (2.4–3.8%), clearly at odds with the pooled prevalence estimates and the previously reported average duration of 30 weeks for an episode of MDD. Conclusions Our findings provide a comprehensive and up-to-date profile of the prevalence of MDD globally. Region and study methodology influenced the prevalence of MDD. This needs to be considered in the GBD 2010 study and in investigations into the ecological determinants of MDD. Good-quality estimates from low-/middle-income countries were sparse. More accurate data on incidence are also required.

Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

Mapping Hydrophobicity on the Protein Molecular Surface at Atom-Level Resolution

A precise representation of the spatial distribution of hydrophobicity, hydrophilicity and charges on the molecular surface of proteins is critical for the understanding of the interaction with small molecules and larger systems. The representation of hydrophobicity is rarely done at atom-level, as this property is generally assigned to residues. A new methodology for the derivation of atomic hydrophobicity from any amino acid-based hydrophobicity scale was used to derive 8 sets of atomic hydrophobicities, one of which was used to generate the molecular surfaces for 35 proteins with convex structures, 5 of which, i.e., lysozyme, ribonuclease, hemoglobin, albumin and IgG, have been analyzed in more detail. Sets of the molecular surfaces of the model proteins have been constructed using spherical probes with increasingly large radii, from 1.4 to 20 A˚, followed by the quantification of (i) the surface hydrophobicity; (ii) their respective molecular surface areas, i.e., total, hydrophilic and hydrophobic area; and (iii) their relative densities, i.e., divided by the total molecular area; or specific densities, i.e., divided by property-specific area. Compared with the amino acid-based formalism, the atom-level description reveals molecular surfaces which (i) present an approximately two times more hydrophilic areas; with (ii) less extended, but between 2 to 5 times more intense hydrophilic patches; and (iii) 3 to 20 times more extended hydrophobic areas. The hydrophobic areas are also approximately 2 times more hydrophobicity-intense. This, more pronounced "leopard skin"-like, design of the protein molecular surface has been confirmed by comparing the results for a restricted set of homologous proteins, i.e., hemoglobins diverging by only one residue (Trp37). These results suggest that the representation of hydrophobicity on the protein molecular surfaces at atom-level resolution, coupled with the probing of the molecular surface at different geometric resolutions, can capture processes that are otherwise obscured to the amino acid-based formalism.

High-resolution GNSS-tracked drifter for studying surface dispersion in shallow water

The use of GNSS tracked Lagrangian drifters allows more realistic quantification of fluid motion and dispersion coefficients than Eulerian techniques because such drifters are analogues of particles that are relevant to flow field characterisation and pollutant dispersion. Using the fast growing Real Time Kinematic (RTK) positioning technique derived from Global Satellite Navigation Systems (GNSS), drifters are developed for high frequency (10 Hz) sampling with position estimates to centimetre accuracy. The drifters are designed with small size and less direct wind drag to follow the sub-surface flow which characterizes dispersion in shallow waters. An analysis of position error from stationary observation indicates that the drifter can efficiently resolve motion up to 1 Hz. The result of the field deployments of the drifter in conjunction with acoustic Eulerian devices shows higher estimate of the drifter streamwise velocities. Single particle statistical analysis of field deployments in a shallow estuarine zone yielded dispersion coefficients estimate comparable to those of dye tracer studies. The drifters capture the tidal elevation during field studies in a tidal estuary.

Binding properties of peptidic affinity ligands for plasmid DNA capture and detection

Peptides constructed from α-helical subunits of the Lac repressor protein (LacI) were designed then tailored to achieve particular binding kinetics and dissociation constants for plasmid DNA purification and detection. Surface plasmon resonance was employed for quantification and characterization of the binding of double stranded Escherichia coli plasmid DNA (pUC19) via the lac operon (lacO) to "biomimics" of the DNA binding domain of LacI. Equilibrium dissociation constants (K D), association (k a), and dissociation rates (k d) for the interaction between a suite of peptide sequences and pUC19 were determined. K D values measured for the binding of pUC19 to the 47mer, 27mer, 16mer, and 14mer peptides were 8.8 ± 1.3 × 10 -10 M, 7.2 ± 0.6 × 10 -10 M, 4.5 ± 0.5 × 10 -8 M, and 6.2 ± 0.9 × 10 -6 M, respectively. These findings show that affinity peptides, composed of subunits from a naturally occurring operon-repressor interaction, can be designed to achieve binding characteristics suitable for affinity chromatography and biosensor devices.