CT perfusion image processing: analysis of liver tumors

Perfusion CT imaging of the liver has potential to improve evaluation of tumour angiogenesis. Quantitative parameters can be obtained applying mathematical models to Time Attenuation Curve (TAC). However, there are still some difficulties for an accurate quantification of perfusion parameters due, for example, to algorithms employed, to mathematical model, to patient’s weight and cardiac output and to the acquisition system. In this thesis, new parameters and alternative methodologies about liver perfusion CT are presented in order to investigate the cause of variability of this technique. Firstly analysis were made to assess the variability related to the mathematical model used to compute arterial Blood Flow (BFa) values. Results were obtained implementing algorithms based on “ maximum slope method” and “Dual input one compartment model” . Statistical analysis on simulated data demonstrated that the two methods are not interchangeable. Anyway slope method is always applicable in clinical context. Then variability related to TAC processing in the application of slope method is analyzed. Results compared with manual selection allow to identify the best automatic algorithm to compute BFa. The consistency of a Standardized Perfusion Index (SPV) was evaluated and a simplified calibration procedure was proposed. At the end the quantitative value of perfusion map was analyzed. ROI approach and map approach provide related values of BFa and this means that pixel by pixel algorithm give reliable quantitative results. Also in pixel by pixel approach slope method give better results. In conclusion the development of new automatic algorithms for a consistent computation of BFa and the analysis and definition of simplified technique to compute SPV parameter, represent an improvement in the field of liver perfusion CT analysis.

Analysis of the Slow Food movement impact on the farmers and rural areas’ sustainable development

The evaluation of the farmers’ communities’ approach to the Slow Food vision, their perception of the Slow Food role in supporting their activity and their appreciation and expectations from participating in the event of Mother Earth were studied. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was adopted in an agro-food sector context. A survey was conducted, 120 questionnaires from farmers attending the Mother Earth in Turin in 2010 were collected. The descriptive statistical analysis showed that both Slow Food membership and participation to Mother Earth Meeting were much appreciated for the support provided to their business and the contribution to a more sustainable and fair development. A positive social, environmental and psychological impact on farmers also resulted. Results showed also an interesting perspective on the possible universality of the Slow Food and Mother Earth values. Farmers declared that Slow Food is supporting them by preserving the biodiversity and orienting them to the use of local resources and reducing the chemical inputs. Many farmers mentioned the language/culture and administration/bureaucratic issues as an obstacle to be a member in the movement and to participate to the event. Participation to Mother Earth gives an opportunity to exchange information with other farmers’ communities and to participate to seminars and debates, helpful for their business development. The absolute majority of positive answers associated to the farmers’ willingness to relate to Slow Food and participate to the next Mother Earth editions negatively influenced the UTAUT model results. A factor analysis showed that the variables associated to the UTAUT model constructs Performance Expectancy and Effort Expectancy were consistent, able to explain the construct variability, and their measurement reliable. Their inclusion in a simplest Technology Acceptance Model could be considered in future researches.

Analysis of the immunological and functional features of the Neisserial Heparin Binding Antigen (NHBA)

Neisserial Heparin Binding Antigen (NHBA) is a surface-exposed lipoprotein ubiquitously expressed by genetically diverse Neisseria meningitidis strains and is an antigen of the multicomponent protein-based 4CMenB vaccine, able to induce bactericidal antibodies in humans and to bind heparin-like molecules. The aim of this study is to characterize the immunological and functional properties of NHBA. To evaluate immunogenicity and the contribution of aminoacid sequence variability to vaccine coverage, we constructed recombinant isogenic strains that are susceptible to bactericidal killing only by anti-NHBA antibodies and engineered them to express equal levels of selected NHBA peptides. In these recombinant strains, we observed different titres associated with the different peptide variants. These recombinant strains were then further engineered to express NHBA chimeric proteins to investigate the regions important for immunogenicity. In natural strains, anti-NHBA antibodies were found to be cross-protective against strains expressing different peptides. To investigate the functional properties of this antigen, the recombinant purified NHBA protein was tested in in vitro binding studies and was found to be able to bind epithelial cells. The binding was abolished when cells were treated specifically with heparinase III, suggesting that the interaction with the cells is mediated by heparan sulfate proteoglycans (HSPG). Mutation of the Arg-rich tract of NHBA abrogated the binding, confirming the importance of this region in mediating the binding to heparin-like molecules. In a panel of N. meningitidis strains, the deletion of nhba resulted in a reduction of adhesion with respect to each isogenic wild type strain. Furthermore, the adhesion of the wild-type strain was prevented by using anti-NHBA polyclonal sera, demonstrating the specificity of the interaction. These results suggest that NHBA could be a novel meningococcal adhesin contributing to host-cell interaction. Moreover, we analysed NHBA NalP-mediated cleavage in different NHBA peptides and showed that not all NHBA peptides are cleaved.

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.

Quality Control in the Healthcare Industry: An Analysis of Surgery Turnover Times

For virtually all hospitals, utilization rates are a critical managerial indicator of efficiency and are determined in part by turnover time. Turnover time is defined as the time elapsed between surgeries, during which the operating room is cleaned and preparedfor the next surgery. Lengthier turnover times result in lower utilization rates, thereby hindering hospitals’ ability to maximize the numbers of patients that can be attended to. In this thesis, we analyze operating room data from a two year period provided byEvangelical Community Hospital in Lewisburg, Pennsylvania, to understand the variability of the turnover process. From the recorded data provided, we derive our best estimation of turnover time. Recognizing the importance of being able to properly modelturnover times in order to improve the accuracy of scheduling, we seek to fit distributions to the set of turnover times. We find that log-normal and log-logistic distributions are well-suited to turnover times, although further research must validate this finding. Wepropose that the choice of distribution depends on the hospital and, as a result, a hospital must choose whether to use the log-normal or the log-logistic distribution. Next, we use statistical tests to identify variables that may potentially influence turnover time. We find that there does not appear to be a correlation between surgerytime and turnover time across doctors. However, there are statistically significant differences between the mean turnover times across doctors. The final component of our research entails analyzing and explaining the benefits of introducing control charts as a quality control mechanism for monitoring turnover times in hospitals. Although widely instituted in other industries, control charts are notwidely adopted in healthcare environments, despite their potential benefits. A major component of our work is the development of control charts to monitor the stability of turnover times. These charts can be easily instituted in hospitals to reduce the variabilityof turnover times. Overall, our analysis uses operations research techniques to analyze turnover times and identify manners for improvement in lowering the mean turnover time and thevariability in turnover times. We provide valuable insight into a component of the surgery process that has received little attention, but can significantly affect utilization rates in hospitals. Most critically, an ability to more accurately predict turnover timesand a better understanding of the sources of variability can result in improved scheduling and heightened hospital staff and patient satisfaction. We hope that our findings can apply to many other hospital settings.

Analysis of the antibody response to an immunodominant epitope of the envelope glycoprotein of a lentivirus and its diagnostic potential

The envelope glycoprotein of small ruminant lentiviruses (SRLV) is a major target of the humoral immune response and contains several linear B-cell epitopes. We amplified and sequenced the genomic segment encoding the SU5 antigenic site of the envelope glycoprotein of several SRLV field isolates. With synthetic peptides based on the deduced amino acid sequences of SU5 in an enzyme-linked immunosorbent assay (ELISA), we have (i) proved the immunodominance of this region regardless of its high variability, (ii) defined the epitopes encompassed by SU5, (iii) illustrated the rapid and peculiar kinetics of seroconversion to this antigenic site, and (iv) shown the rapid and strong maturation of the avidity of the anti-SU5 antibody. Finally, we demonstrated the modular diagnostic potential of SU5 peptides. Under Swiss field conditions, the SU5 ELISA was shown to detect the majority of infected animals and, when applied in a molecular epidemiological context, to permit rapid phylogenetic classification of the infecting virus.

Phylogenetic analysis of the gag region encoding the matrix protein of small ruminant lentiviruses: comparative analysis and molecular epidemiological applications

Little sequence information exists on the matrix-protein (MA) encoding region of small ruminant lentiviruses (SRLV). Fifty-two novel sequences were established and permitted a first phylogenetic analysis of this region of the SRLV genome. The variability of the MA encoding region is higher compared to the gag region encoding the capsid protein and surprisingly close to that reported for the env gene. In contrast to primate lentiviruses, the deduced amino acid sequences of the N- and C-terminal domains of MA are variable. This permitted to pinpoint a basic domain in the N-terminal domain that is conserved in all lentiviruses and likely to play an important functional role. Additionally, a seven amino acid insertion was detected in all MVV strains, which may be used to differentiate CAEV and MVV isolates. A molecular epidemiology analysis based on these sequences indicates that the Italian lentivirus strains are closely related to each other and to the CAEV-CO strain, a prototypic strain isolated three decades ago in the US. This suggests a common origin of the SRLV circulating in the monitored flocks, possibly related to the introduction of infected goats in a negative population. Finally, this study shows that the MA region is suitable for phylogenetic studies and may be applied to monitor SRLV eradication programs.

Leydig-cell tumour in children: variable clinical presentation, diagnostic features, follow-up and genetic analysis of four cases

BACKGROUND: Testicular tumours are relatively uncommon in infants and children, accounting for only 1-2% of all paediatric solid tumours. Of these approximately 1.5% are Leydig-cell tumours. Further, activating mutations of the luteinizing hormone receptor gene (LHR), as well as of the G protein genes, such as Gsalpha (gsp) and Gialpha (gip2) subunits, and cyclin-dependent kinase gene 4(CDK4) have been associated with the development of several endocrine neoplasms. AIMS/METHODS: In this report, the clinical variability of Leydig-cell tumours in four children is described. The LHR-, gsp-, gip2- and CDK4 genes were investigated to establish the possible molecular pathogenesis of the variable phenotype of the Leydig-cell tumours. RESULTS: No activating mutations in these genes were found in the four Leydig-cell tumours studied. Therefore, the absence of activating mutations in LHR, as well as in both the 'hot spot' regions for activating mutations within the G-alpha subunits and in the regulatory 'hot spot' on the CDK4 genes in these tumours indicates molecular heterogeneity among Leydig-cell tumours. CONCLUSION: Four children with a variable phenotype caused by Leydig-cell tumours are described. A molecular analysis of all the 'activating' genes and mutational regions known so far was performed, but no abnormalities were found. The lessons learnt from these clinically variable cases are: perform ultrasound early and most importantly, consider discrepancies between testicular swelling, tumour size and androgen production.

Enantioselective analysis of ketamine and its metabolites in equine plasma and urine by CE with multiple isomer sulfated beta-CD

CE with multiple isomer sulfated beta-CD as the chiral selector was assessed for the simultaneous analysis of the enantiomers of ketamine and metabolites in extracts of equine plasma and urine. Different lots of the commercial chiral selector provided significant changes in enantiomeric ketamine separability, a fact that can be related to the manufacturing variability. A mixture of two lots was found to provide high-resolution separations and interference-free detection of the enantiomers of ketamine, norketamine, dehydronorketamine, and an incompletely identified hydroxylated metabolite of norketamine in liquid/liquid extracts of the two body fluids. Ketamine, norketamine, and dehydronorketamine could be unambiguously identified via HPLC fractionation of urinary extracts and using LC-MS and LC-MS/MS with 1 mmu mass discrimination. The CE assay was used to characterize the stereoselectivity of the compounds' enantiomers in the samples of five ponies anesthetized with isoflurane in oxygen and treated with intravenous continuous infusion of racemic ketamine. The concentrations of the ketamine enantiomers in plasma are equal, whereas the urinary amount of R-ketamine is larger than that of S-ketamine. Plasma and urine contain higher S- than R-norketamine levels and the mean S-/R-enantiomer ratios of dehydronorketamine in plasma and urine are lower than unity and similar.

Optimized temperature and deadspace correction improve analysis of multiple breath washout measurements by ultrasonic flowmeter in infants

BACKGROUND: Assessment of lung volume (FRC) and ventilation inhomogeneities with ultrasonic flowmeter and multiple breath washout (MBW) has been used to provide important information about lung disease in infants. Sub-optimal adjustment of the mainstream molar mass (MM) signal for temperature and external deadspace may lead to analysis errors in infants with critically small tidal volume changes during breathing. METHODS: We measured expiratory temperature in human infants at 5 weeks of age and examined the influence of temperature and deadspace changes on FRC results with computer simulation modeling. A new analysis method with optimized temperature and deadspace settings was then derived, tested for robustness to analysis errors and compared with the previously used analysis methods. RESULTS: Temperature in the facemask was higher and variations of deadspace volumes larger than previously assumed. Both showed considerable impact upon FRC and LCI results with high variability when obtained with the previously used analysis model. Using the measured temperature we optimized model parameters and tested a newly derived analysis method, which was found to be more robust to variations in deadspace. Comparison between both analysis methods showed systematic differences and a wide scatter. CONCLUSION: Corrected deadspace and more realistic temperature assumptions improved the stability of the analysis of MM measurements obtained by ultrasonic flowmeter in infants. This new analysis method using the only currently available commercial ultrasonic flowmeter in infants may help to improve stability of the analysis and further facilitate assessment of lung volume and ventilation inhomogeneities in infants.

A unification of models for meta-analysis of diagnostic accuracy studies

Studies of diagnostic accuracy require more sophisticated methods for their meta-analysis than studies of therapeutic interventions. A number of different, and apparently divergent, methods for meta-analysis of diagnostic studies have been proposed, including two alternative approaches that are statistically rigorous and allow for between-study variability: the hierarchical summary receiver operating characteristic (ROC) model (Rutter and Gatsonis, 2001) and bivariate random-effects meta-analysis (van Houwelingen and others, 1993), (van Houwelingen and others, 2002), (Reitsma and others, 2005). We show that these two models are very closely related, and define the circumstances in which they are identical. We discuss the different forms of summary model output suggested by the two approaches, including summary ROC curves, summary points, confidence regions, and prediction regions.

Fluctuation analysis of lung function as a predictor of long-term response to beta2-agonists

The response to beta(2)-agonists differs between asthmatics and has been linked to subsequent adverse events, even death. Possible determinants include beta(2)-adrenoceptor genotype at position 16, lung function and airway hyperresponsiveness. Fluctuation analysis provides a simple parameter alpha measuring the complex correlation properties of day-to-day peak expiratory flow. The present study investigated whether alpha predicts clinical response to beta(2)-agonist treatment, taking into account other conventional predictors. Analysis was performed on previously published twice-daily peak expiratory flow measurements in 66 asthmatic adults over three 6-month randomised order treatment periods: placebo, salbutamol and salmeterol. Multiple linear regression was used to determine the association between alpha during the placebo period and response to treatment (change in the number of days with symptoms), taking into account other predictors namely beta(2)-adrenoceptor genotype, lung function and its variability, and airway hyperresponsiveness. The current authors found that alpha measured during the placebo period considerably improved the prediction of response to salmeterol treatment, taking into account genotype, lung function or its variability, or airway hyperresponsiveness. The present study provides further evidence that response to beta(2)-agonists is related to the time correlation properties of lung function in asthma. The current authors conclude that fluctuation analysis of lung function offers a novel predictor to identify patients who may respond well or poorly to treatment.

Slope stability analysis of the Pacaya Volcano, Guatemala, using limit equilibrium and finite element method

The Pacaya volcanic complex is part of the Central American volcanic arc, which is associated with the subduction of the Cocos tectonic plate under the Caribbean plate. Located 30 km south of Guatemala City, Pacaya is situated on the southern rim of the Amatitlan Caldera. It is the largest post-caldera volcano, and has been one of Central America’s most active volcanoes over the last 500 years. Between 400 and 2000 years B.P, the Pacaya volcano had experienced a huge collapse, which resulted in the formation of horseshoe-shaped scarp that is still visible. In the recent years, several smaller collapses have been associated with the activity of the volcano (in 1961 and 2010) affecting its northwestern flanks, which are likely to be induced by the local and regional stress changes. The similar orientation of dry and volcanic fissures and the distribution of new vents would likely explain the reactivation of the pre-existing stress configuration responsible for the old-collapse. This paper presents the first stability analysis of the Pacaya volcanic flank. The inputs for the geological and geotechnical models were defined based on the stratigraphical, lithological, structural data, and material properties obtained from field survey and lab tests. According to the mechanical characteristics, three lithotechnical units were defined: Lava, Lava-Breccia and Breccia-Lava. The Hoek and Brown’s failure criterion was applied for each lithotechnical unit and the rock mass friction angle, apparent cohesion, and strength and deformation characteristics were computed in a specified stress range. Further, the stability of the volcano was evaluated by two-dimensional analysis performed by Limit Equilibrium (LEM, ROCSCIENCE) and Finite Element Method (FEM, PHASE 2 7.0). The stability analysis mainly focused on the modern Pacaya volcano built inside the collapse amphitheatre of “Old Pacaya”. The volcanic instability was assessed based on the variability of safety factor using deterministic, sensitivity, and probabilistic analysis considering the gravitational instability and the effects of external forces such as magma pressure and seismicity as potential triggering mechanisms of lateral collapse. The preliminary results from the analysis provide two insights: first, the least stable sector is on the south-western flank of the volcano; second, the lowest safety factor value suggests that the edifice is stable under gravity alone, and the external triggering mechanism can represent a likely destabilizing factor.

Risk of severe asthma episodes predicted from fluctuation analysis of airway function

Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.

In vivo analysis of efavirenz metabolism in individuals with impaired CYP2A6 function

INTRODUCTION: The antiretroviral drug efavirenz (EFV) is extensively metabolized into three primary metabolites: 8-hydroxy-EFV, 7-hydroxy-EFV and N-glucuronide-EFV. There is a wide interindividual variability in EFV plasma exposure, explained to a great extent by cytochrome P450 2B6 (CYP2B6), the main isoenzyme responsible for EFV metabolism and involved in the major metabolic pathway (8-hydroxylation) and to a lesser extent in 7-hydroxylation. When CYP2B6 function is impaired, the relevance of CYP2A6, the main isoenzyme responsible for 7-hydroxylation may increase. We hypothesize that genetic variability in this gene may contribute to the particularly high, unexplained variability in EFV exposure in individuals with limited CYP2B6 function. METHODS: This study characterized CYP2A6 variation (14 alleles) in individuals (N=169) previously characterized for functional variants in CYP2B6 (18 alleles). Plasma concentrations of EFV and its primary metabolites (8-hydroxy-EFV, 7-hydroxy-EFV and N-glucuronide-EFV) were measured in different genetic backgrounds in vivo. RESULTS: The accessory metabolic pathway CYP2A6 has a critical role in limiting drug accumulation in individuals characterized as CYP2B6 slow metabolizers. CONCLUSION: Dual CYP2B6 and CYP2A6 slow metabolism occurs at significant frequency in various human populations, leading to extremely high EFV exposure.