Gravity-induced coronal plane joint moments in the adolescent scoliotic spine

INTRODUCTION Calculating segmental (vertebral level-by-level) torso masses in Adolescent Idiopathic Scoliosis (AIS) patients allows the gravitational loading on the scoliotic spine during relaxed standing to be estimated. METHODS Existing low dose CT scans were used to calculate vertebral level-by-level torso masses and joint moments occurring in the spine for a group of female AIS patients with right-sided thoracic curves. Image processing software, ImageJ (v1.45 NIH USA) was used to reconstruct the torso segments and subsequently measure the torso volume and mass corresponding to each vertebral level. Body segment masses for the head, neck and arms were taken from published anthropometric data. Intervertebral joint moments at each vertebral level were found by summing each of the torso segment masses above the required joint and multiplying it by the perpendicular distance to the centre of the disc. RESULTS AND DISCUSSION Twenty patients were included in this study with a mean age of 15.0±2.7 years and a mean Cobb angle 52±5.9°. The mean total trunk mass, as a percentage of total body mass, was 27.8 (SD 0.5) %. Mean segmental torso mass increased inferiorly from 0.6kg at T1 to 1.5kg at L5. The coronal plane joint moments during relaxed standing were typically 5-7Nm at the apex of the curve (Figure 1), with the highest apex joint of 7Nm. CT scans were performed in the supine position and curve magnitudes are known to be 7-10° smaller than those measured in standing [1]. Therefore joint moments produced by gravity will be greater than those calculated here. CONCLUSIONS Coronal plane joint moments as high as 7Nm can occur during relaxed standing in scoliosis patients, which may help to explain the mechanics of AIS progression. The body mass distributions calculated in this study can be used to estimate joint moments derived using other imaging modalities such as MRI and subsequently determine if a relationship exists between joint moments and progressive vertebral deformity.

Iron(II) spin-transition complexes with dendritic ligands, part II

The dendritic triazole-based complexes \[Fe(G1-BOC)3](triflate) 2·xH2O (1; G1-BOC = tert-butyl {3-\[3-(3-tert- butoxycarbonylaminopropyl)-5-(\[1,2,4]triazol-4-ylcarbamoyl)-phenyl]propyl} carbamate, triflate = CF3SO3-), \[Fe(G1-BOC) 3]-(tosylate)2·xH2O(2;tosylate = p-CH3PhSO3-),\[Fe(G1-DPBE)3]-(triflate) 2·xH2O {3; G1-DPBE = 3,5-bis(3,5- didodecaoxybenzyloxy)-N-\[1,2,4]triazol-4-ylbenzamide}, \[Fe(G1-DPBE) 3]-(tosylate)2·xH2O (4) and \[Fe(G1-DPBE)3](BF4)2·xH2O (5) were designed and synthesized. Magnetic and thermal properties of these novel complexes were characterized by magnetic susceptibility measurements, 57Fe Mössbauer spectroscopy and thermogravimetric analysis or differential scanning calorimetry, respectively. All dendritic complexes under study show different spin-transition behaviour with respect to the nature of different dendritic ligands and counteranions. Complexes 1 and 2 have pronounced effects of a spin-state change during the first heating process and gradual spintransition properties for further temperature treatments, whereas 3 and 4 exhibited a very sharp spin-state change in the first heating procedures. Complex 5 showed a gradual spin-transition curve. In this paper, we report how the magnetic properties of these complexes are correlated with noncoordinated water molecules and their effects on spin states.

Which industry is greener? An empirical study of nine industries in OECD countries

This study analyzed the relationship between the CO2 emissions of different industries and economic growth in OECD countries from 1970 to 2005. We tested an environmental Kuznets curve (EKC) hypothesis and found that total CO2 emissions from nine industries show an N-shaped trend instead of an inverted U or monotonic increasing trend with increasing income. The EKC hypothesis for sector-level CO2 emissions was supported in the (1) paper, pulp, and printing industry; (2) wood and wood products industry; and (3) construction industry. We also found that emissions from coal and oil increase with economic growth in the steel and construction industries. In addition, the non-metallic minerals, machinery, and transport equipment industries tend to have increased emissions from oil and electricity with economic growth. Finally, the EKC turning point and the relationship between GDP per capita and sectoral CO2 emissions differ among industries according to the fuel type used. Therefore, environmental policies for CO2 reduction must consider these differences in industrial characteristics. © 2013 Elsevier Ltd.

World emissions and economic growth: Application of non-parametric methods

The Environmental Kuznets Curve (EKC) hypothesises an inverse U-shaped relationship between a measure of environmental pollution and per capita income levels. In this study, we apply non-parametric estimation of local polynomial regression (local quadratic fitting) to allow more flexibility in local estimation. This study uses a larger and globally representative sample of many local and global pollutants and natural resources including Biological Oxygen Demand (BOD) emission, CO2 emission, CO2 damage, energy use, energy depletion, mineral depletion, improved water source, PM10, particulate emission damage, forest area and net forest depletion. Copyright © 2009 Inderscience Enterprises Ltd.

Does energy substitution affect carbon dioxide emissions : income relationship?

Considerable discussion has taken place during the last decade regarding the role of economic growth in determining environmental quality. Using data from 30 OECD countries for the period 1960-2003 and the nonparametric method of generalized additive models, which enables us to use flexible functional forms, this paper examines the environmental Kuznets curve hypothesis for carbon dioxide (CO2). We find that the reduction of coal share in energy use has a significant effect on CO2. Our results imply that economic growth is not sufficient to decrease CO2 emissions.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

Flexural–torsional buckling behaviour and design of cold-formed steel compression members at elevated temperatures

Current design rules for the member capacities of cold-formed steel columns are based on the same non-dimensional strength curve for both fixed and pinned-ended columns at ambient temperature. This research has investigated the accuracy of using current ambient temperature design rules in Australia/New Zealand (AS/NZS 4600), American (AISI S100) and European (Eurocode 3 Part 1.3) standards in determining the flexural–torsional buckling capacities of cold-formed steel columns at uniform elevated temperatures using appropriately reduced mechanical properties. It was found that these design rules accurately predicted the member capacities of pin ended lipped channel columns undergoing flexural torsional buckling at elevated temperatures. However, for fixed ended columns with warping fixity undergoing flexural–torsional buckling, the current design rules significantly underestimated the column capacities as they disregard the beneficial effect of warping fixity. This paper has therefore recommended the use of improved design rules developed for ambient temperature conditions to predict the axial compression capacities of fixed ended columns subject to flexural–torsional buckling at elevated temperatures within AS/NZS 4600 and AISI S100 design provisions. The accuracy of the proposed fire design rules was verified using finite element analysis and test results of cold-formed lipped channel columns at elevated temperatures except for low strength steel columns with intermediate slenderness whose behaviour was influenced by the increased nonlinearity in the stress–strain curves at elevated temperatures. Further research is required to include these effects within AS/NZS 4600 and AISI S100 design rules. However, Eurocode 3 Part 1.3 design rules can be used for this purpose by using suitable buckling curves as recommended in this paper.

Fire performance and design of cold-formed steel wall systems

Traditionally, the fire resistance rating of Light gauge steel frame (LSF) wall systems is based on approximate prescriptive methods developed using limited fire tests. These fire tests are conducted using standard fire time-temperature curve given in ISO 834. However, in recent times fire has become a major disaster in buildings due to the increase in fire loads as a result of modern furniture and lightweight construction, which make use of thermoplastics materials, synthetic foams and fabrics. Therefore a detailed research study into the performance of load bearing LSF wall systems under both standard and realistic design fires on one side was undertaken to develop improved fire design rules. This study included both full scale fire tests and numerical studies of eight different LSF wall systems conducted for both the standard fire curve and the recently developed realistic design fire curves. The use of previous fire design rules developed for LSF walls subjected to non-uniform elevated temperature distributions based on AISI design manual and Eurocode 3 Parts 1.2 and 1.3 was investigated first. New simplified fire design rules based on AS/NZS 4600, North American Specification and Eurocode 3 Part 1.3 were then proposed with suitable allowances for the interaction effects of compression and bending actions. The importance of considering thermal bowing, magnified thermal bowing and neutral axis shift in the fire design was also investigated and their effects were included. A spread sheet based design tool was developed based on the new design rules to predict the failure load ratio versus time and temperature curves for varying LSF wall configurations. The accuracy of the proposed design rules was verified using the fire test and finite element analysis results for various wall configurations, steel grades, thicknesses and load ratios under both standard and realistic design fire conditions. A simplified method was also proposed to predict the fire resistance rating of LSF walls based on two sets of equations developed for the load ratio-hot flange temperature and the time-temperature relationships. This paper presents the details of this study on LSF wall systems under fire conditions and the results.

Weight-related differences in glucose metabolism and free fatty acid production in two South African population groups

OBJECTIVE The effects of free fatty acids (FFA), leptin, tumour necrosis factor (TNF) alpha and body fat distribution on in vivo oxidation of a glucose load were studied in two South African ethnic groups. DESIGN AND MEASUREMENTS Anthropometric and various metabolic indices were measured at fasting and during a 7h oral glucose tolerance test (OGTT). Body composition was measured using bioelectrical impedance analysis and subcutaneous and visceral fat mass was assessed using a five- and two-level CT-scan respectively. Glucose oxidation was evaluated by measuring the ratio of (13)CO(2) to (12)CO(2) in breath following ingestion of 1-(13)C-labelled glucose. SUBJECTS Ten lean black women (LBW), ten obese black women (OBW), nine lean white women (LWW) and nine obese white women (OWW) were investigated after an overnight fast. RESULTS Visceral fat levels were significantly higher (P < 0.01) in obese white than black women, despite similar body mass indexes (BMIs). There were no ethnic differences in glucose oxidation however; in the lean subjects of both ethnic groups the area under the curve (AUC) was higher than in obese subjects (P < 0.05 for both) and was found to correlate negatively with weight (r = -0.69, P < 0.01) after correcting for age. Basal TNF alpha concentrations were similar in all groups. Percentage suppression of FFAs at 30 min of the OCTT was 24 +/- 12% in OWW and - 38 +/- 23% (P < 0.05) in OBW, ie the 30 min FFA level was higher than the fasting level in the latter group. AUC for FFAs during the late postprandial period (120 - 420 min) was significantly higher in OWW than OBW (P < 0.01) and LWW (P < 0.01) and correlated positively with visceral fat mass independent of age (r = 0.78, P < 0.05) in the OWW only. Leptin levels were higher (P < 0.01) both at fasting and during the course of the OCTT in obese women from both ethnic groups compared to the lean women. CONCLUSIONS Glucose oxidation is reduced in obese subjects of both ethnic groups; inter- and intra-ethnic differences were observed in visceral fat mass and FFA production and it is possible that such differences may play a role in the differing prevalences of obesity-related disorders that have been reported in these two populations.

A novel saliva-based microRNA biomarker panel to detect head and neck cancers

Background MicroRNAs (miRNAs) are known to play an important role in cancer development by post-transcriptionally affecting the expression of critical genes. The aims of this study were two-fold: (i) to develop a robust method to isolate miRNAs from small volumes of saliva and (ii) to develop a panel of saliva-based diagnostic biomarkers for the detection of head and neck squamous cell carcinoma (HNSCC). Methods Five differentially expressed miRNAs were selected from miScript™ miRNA microarray data generated using saliva from five HNSCC patients and five healthy controls. Their differential expression was subsequently confirmed by RT-qPCR using saliva samples from healthy controls (n = 56) and HNSCC patients (n = 56). These samples were divided into two different cohorts, i.e., a first confirmatory cohort (n = 21) and a second independent validation cohort (n = 35), to narrow down the miRNA diagnostic panel to three miRNAs: miR-9, miR-134 and miR-191. This diagnostic panel was independently validated using HNSCC miRNA expression data from The Cancer Genome Atlas (TCGA), encompassing 334 tumours and 39 adjacent normal tissues. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic capacity of the panel. Results On average 60 ng/μL miRNA was isolated from 200 μL of saliva. Overall a good correlation was observed between the microarray data and the RT-qPCR data. We found that miR-9 (P <0.0001), miR-134 (P <0.0001) and miR-191 (P <0.001) were differentially expressed between saliva from HNSCC patients and healthy controls, and that these miRNAs provided a good discriminative capacity with area under the curve (AUC) values of 0.85 (P <0.0001), 0.74 (P < 0.001) and 0.98 (P < 0.0001), respectively. In addition, we found that the salivary miRNA data showed a good correlation with the TCGA miRNA data, thereby providing an independent validation. Conclusions We show that we have developed a reliable method to isolate miRNAs from small volumes of saliva, and that the saliva-derived miRNAs miR-9, miR-134 and miR-191 may serve as novel biomarkers to reliably detect HNSCC. © 2014 International Society for Cellular Oncology.

Choice impulsivity: Definitions, measurement issues, and clinical implications

Background Impulsivity critically relates to many psychiatric disorders. Given the multifaceted construct that impulsivity represents, defining core aspects of impulsivity is vital for the assessment and understanding of clinical conditions. Choice impulsivity (CI), involving the preferential selection of smaller sooner rewards over larger later rewards, represents one important type of impulsivity. Method The International Society for Research on Impulsivity (InSRI) convened to discuss the definition and assessment of CI and provide recommendations regarding measurement across species. Results Commonly used preclinical and clinical CI behavioral tasks are described, and considerations for each task are provided to guide CI task selection. Differences in assessment of CI (self-report, behavioral) and calculating CI indices (e.g., area-under-the-curve, indifference point, steepness of discounting curve) are discussed along with properties of specific behavioral tasks used in preclinical and clinical settings. Conclusions The InSRI group recommends inclusion of measures of CI in human studies examining impulsivity. Animal studies examining impulsivity should also include assessments of CI and these measures should be harmonized in accordance with human studies of the disorders being modeled in the preclinical investigations. The choice of specific CI measures to be included should be based on the goals of the study and existing preclinical and clinical literature using established CI measures.