Effects of glenoid component version on humeral head displacement and joint reaction forces: an experimental study

The purpose of this study was to determine whether changes in glenoid version are associated with humeral head displacement and changes in the joint reaction forces, as these might contribute to instability or loosening in total shoulder replacement. A total shoulder prosthesis was implanted in neutral version in 6 cadaveric shoulders. Glenoid version was then changed in steps of 4 degrees toward more anteversion and retroversion. An increase in anteversion resulted in anterior translation of the humeral head and in eccentric loading of the anterior part of the glenoid. Retroversion was associated with posterior displacement and posterior loading of the glenoid. A change in rotation of the humeral component did not compensate for altered version of the glenoid component. These results suggest that both instability and glenoid component loosening may be related to the version of the glenoid component. Therefore, assessment of loosening and instability justifies precise assessment of glenoid component version.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

BOLD correlates of continuously fluctuating epileptic activity isolated by independent component analysis

Combined EEG/fMRI recordings offer a promising opportunity to detect brain areas with altered BOLD signal during interictal epileptic discharges (IEDs). These areas are likely to represent the irritative zone, which is itself a reflection of the epileptogenic zone. This paper reports on the imaging findings using independent component analysis (ICA) to continuously quantify epileptiform activity in simultaneously acquired EEG and fMRI. Using ICA derived factors coding for the epileptic activity takes into account that epileptic activity is continuously fluctuating with each spike differing in amplitude, duration and maybe topography, including subthreshold epileptic activity besides clear IEDs and may thus increase the sensitivity and statistical power of combined EEG/fMRI in epilepsy. Twenty patients with different types of focal and generalized epilepsy syndromes were investigated. ICA separated epileptiform activity from normal physiological brain activity and artifacts. In 16/20 patients, BOLD correlates of epileptic activity matched the EEG sources, the clinical semiology, and, if present, the structural lesions. In clinically equivocal cases, the BOLD correlates aided to attribute proper diagnosis of the underlying epilepsy syndrome. Furthermore, in one patient with temporal lobe epilepsy, BOLD correlates of rhythmic delta activity could be employed to delineate the affected hippocampus. Compared to BOLD correlates of manually identified IEDs, the sensitivity was improved from 50% (10/20) to 80%. The ICA EEG/fMRI approach is a safe, non-invasive and easily applicable technique, which can be used to identify regions with altered hemodynamic effects related to IEDs as well as intermittent rhythmic discharges in different types of epilepsy.

TINF2, a component of the shelterin telomere protection complex, is mutated in dyskeratosis congenita

Patients with dyskeratosis congenita (DC), a heterogeneous inherited bone marrow failure syndrome, have abnormalities in telomere biology, including very short telomeres and germline mutations in DKC1, TERC, TERT, or NOP10, but approximately 60% of DC patients lack an identifiable mutation. With the very short telomere phenotype and a highly penetrant, rare disease model, a linkage scan was performed on a family with autosomal-dominant DC and no mutations in DKCI, TERC, or TERT. Evidence favoring linkage was found at 2p24 and 14q11.2, and this led to the identification of TINF2 (14q11.2) mutations, K280E, in the proband and her five affected relatives and TINF2 R282H in three additional unrelated DC probands, including one with Revesz syndrome; a fifth DC proband had a R282S mutation. TINF2 mutations were not present in unaffected relatives, DC probands with mutations in DKC1, TERC, or TERT or 298 control subjects. We demonstrate that a fifth gene, TINF2, is mutated in classical DC and, for the first time, in Revesz syndrome. This represents the first shelterin complex mutation linked to human disease and confirms the role of very short telomeres as a diagnostic test for DC.

Diesel spray mixing limited vaporization with non-ideal and multi-component fuel thermophysical property effects

Internal combustion engines are, and will continue to be, a primary mode of power generation for ground transportation. Challenges exist in meeting fuel consumption regulations and emission standards while upholding performance, as fuel prices rise, and resource depletion and environmental impacts are of increasing concern. Diesel engines are advantageous due to their inherent efficiency advantage over spark ignition engines; however, their NOx and soot emissions can be difficult to control and reduce due to an inherent tradeoff. Diesel combustion is spray and mixing controlled providing an intrinsic link between spray and emissions, motivating detailed, fundamental studies on spray, vaporization, mixing, and combustion characteristics under engine relevant conditions. An optical combustion vessel facility has been developed at Michigan Technological University for these studies, with detailed tests and analysis being conducted. In this combustion vessel facility a preburn procedure for thermodynamic state generation is used, and validated using chemical kinetics modeling both for the MTU vessel, and institutions comprising the Engine Combustion Network international collaborative research initiative. It is shown that minor species produced are representative of modern diesel engines running exhaust gas recirculation and do not impact the autoignition of n-heptane. Diesel spray testing of a high-pressure (2000 bar) multi-hole injector is undertaken including non-vaporizing, vaporizing, and combusting tests, with sprays characterized using Mie back scatter imaging diagnostics. Liquid phase spray parameter trends agree with literature. Fluctuations in liquid length about a quasi-steady value are quantified, along with plume to plume variations. Hypotheses are developed for their causes including fuel pressure fluctuations, nozzle cavitation, internal injector flow and geometry, chamber temperature gradients, and turbulence. These are explored using a mixing limited vaporization model with an equation of state approach for thermopyhysical properties. This model is also applied to single and multi-component surrogates. Results include the development of the combustion research facility and validated thermodynamic state generation procedure. The developed equation of state approach provides application for improving surrogate fuels, both single and multi-component, in terms of diesel spray liquid length, with knowledge of only critical fuel properties. Experimental studies are coupled with modeling incorporating improved thermodynamic non-ideal gas and fuel

Determining bridge deck deterioration through the use of 3D photogrammetry

The bridge inspection industry has yet to utilize a rapidly growing technology that shows promise to help improve the inspection process. This thesis investigates the abilities that 3D photogrammetry is capable of providing to the bridge inspector for a number of deterioration mechanisms. The technology can provide information about the surface condition of some bridge components, primarily focusing on the surface defects of a concrete bridge which include cracking, spalling and scaling. Testing was completed using a Canon EOS 7D camera which then processed photos using AgiSoft PhotoScan to align the photos and develop models. Further processing of the models was done using ArcMap in the ArcGIS 10 program to view the digital elevation models of the concrete surface. Several experiments were completed to determine the ability of the technique for the detection of the different defects. The cracks that were able to be resolved in this study were a 1/8 inch crack at a distance of two feet above the surface. 3D photogrammetry was able to be detect a depression of 1 inch wide with 3/16 inch depth which would be sufficient to measure any scaling or spalling that would be required be the inspector. The percentage scaled or spalled was also able to be calculated from the digital elevation models in ArcMap. Different camera factors including the distance from the defects, number of photos and angle, were also investigated to see how each factor affected the capabilities. 3D photogrammetry showed great promise in the detection of scaling or spalling of the concrete bridge surface.

Long-term gas exchange characteristics as marker of deterioration in patients with cystic fibrosis

Background and Aim In patients with cystic fibrosis (CF) the architecture of the developing lungs and the ventilation of lung units are progressively affected, influencing intrapulmonary gas mixing and gas exchange. We examined the long-term course of blood gas measurements in relation to characteristics of lung function and the influence of different CFTR genotype upon this process. Methods Serial annual measurements of PaO2 and PaCO2 assessed in relation to lung function, providing functional residual capacity (FRCpleth), lung clearance index (LCI), trapped gas (VTG), airway resistance (sReff), and forced expiratory indices (FEV1, FEF50), were collected in 178 children (88 males; 90 females) with CF, over an age range of 5 to 18 years. Linear mixed model analysis and binary logistic regression analysis were used to define predominant lung function parameters influencing oxygenation and carbon dioxide elimination. Results PaO2 decreased linearly from age 5 to 18 years, and was mainly associated with FRCpleth, (p < 0.0001), FEV1 (p < 0.001), FEF50 (p < 0.002), and LCI (p < 0.002), indicating that oxygenation was associated with the degree of pulmonary hyperinflation, ventilation inhomogeneities and impeded airway function. PaCO2 showed a transitory phase of low PaCO2 values, mainly during the age range of 5 to 12 years. Both PaO2 and PaCO2 presented with different progression slopes within specific CFTR genotypes. Conclusion In the long-term evaluation of gas exchange characteristics, an association with different lung function patterns was found and was closely related to specific genotypes. Early examination of blood gases may reveal hypocarbia, presumably reflecting compensatory mechanisms to improve oxygenation.

Stability of liposomes in circulation is markedly enhanced by structural modification of their phospholipid component

Replacement of the C-2 ester group in phosphatidylcholine by the carbamyloxy function rendered its liposomes completely stable and longer living in the circulation of rats.

A General Solution Framework for Component-Commonality Problems

Component commonality - the use of the same version of a component across multiple products - is being increasingly considered as a promising way to offer high external variety while retaining low internal variety in operations. However, increasing commonality has both positive and negative cost effects, so that optimization approaches are required to identify an optimal commonality level. As components influence to a greater or lesser extent nearly every process step along the supply chain, it is not surprising that a multitude of diverging commonality problems is being investigated in literature, each of which are developing a specific algorithm designed for the respective commonality problem being considered. The paper on hand aims at a general framework which is flexible and efficient enough to be applied to a wide range of commonality problems. Such a procedure based on a two-stage graph approach is presented and tested. Finally, flexibility of the procedure is shown by customizing the framework to account for different types of commonality problems.

Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).