A radiation-damped R -matrix approach to the electron-impact excitation of helium-like ions for diagnostic application to fusion and astrophysical plasmas

Electron-impact excitation collision strengths for transitions between all singly excited levels up to the n = 4 shell of helium-Eke argon and the n = 4 and 5 shells of helium-like iron have been calculated using a radiation-damped R-matrix approach. The theoretical collision strengths have been examined and associated with their infinite-energy limit values to allow the preparation of Maxwell-averaged effective collision strengths. These are conservatively considered to be accurate to within 20% at all temperatures, 3 x 10(5)-3 x 10(8) K forAr(16+) and 10(6)-10(9) K for Fe24+. They have been compared with the results of previous studies, where possible, and we find a broad accord. The corresponding rate coefficients are required for use in the calculation of derived, collisional-radiative, effective emission coefficients for helium-like lines for diagnostic application to fusion and astrophysical plasmas. The uncertainties in the fundamental collision data have been used to provide a critical assessment of the expected resultant uncertainties in such derived data, including redistributive and cascade collisional-radiative effects. The consequential uncertainties in the parts of the effective emission coefficients driven by excitation from the ground levels for the key w, x, y and z lines vary between 5% and 10%. Our results remove an uncertainty in the reaction rates of a key class of atomic processes governing the spectral emission of helium-like ions in plasmas.

Identification of diagnostic biomarkers for infection in premature neonates

Infection is a leading cause of neonatal morbidity and mortality worldwide. Premature neonates are particularly susceptible to infection because of physiologic immaturity, comorbidity, and extraneous medical interventions. Additionally premature infants are at higher risk of progression to sepsis or severe sepsis, adverse outcomes, and antimicrobial toxicity. Currently initial diagnosis is based upon clinical suspicion accompanied by nonspecific clinical signs and is confirmed upon positive microbiologic culture results several days after institution of empiric therapy. There exists a significant need for rapid, objective, in vitro tests for diagnosis of infection in neonates who are experiencing clinical instability. We used immunoassays multiplexed on microarrays to identify differentially expressed serum proteins in clinically infected and non-infected neonates. Immunoassay arrays were effective for measurement of more than 100 cytokines in small volumes of serum available from neonates. Our analyses revealed significant alterations in levels of eight serum proteins in infected neonates that are associated with inflammation, coagulation, and fibrinolysis. Specifically P- and E-selectins, interleukin 2 soluble receptor alpha, interleukin 18, neutrophil elastase, urokinase plasminogen activator and its cognate receptor, and C-reactive protein were observed at statistically significant increased levels. Multivariate classifiers based on combinations of serum analytes exhibited better diagnostic specificity and sensitivity than single analytes. Multiplexed immunoassays of serum cytokines may have clinical utility as an adjunct for rapid diagnosis of infection and differentiation of etiologic agent in neonates with clinical decompensation.

People and places: Understanding geographical accuracy in administrative data from the census and healthcare systems

Administrative systems such as health care registration are of increasing importance in providing information for statistical, research, and policy purposes. There is thus a pressing need to understand better the detailed relationship between population characteristics as recorded in such systems and conventional censuses. This paper explores these issues using the unique Northern Ireland Longitudinal Study (NILS). It takes the 2001 Census enumeration as a benchmark and analyses the social, demographic and spatial patterns of mismatch with the health register at individual level. Descriptive comparison is followed by multivariate and multilevel analyses which show that approximately 25% of individuals are reported to be in different addresses and that age, rurality, education, and housing type are all important factors. This level of mismatch appears to be maintained over time, as earlier migrants who update their address details are replaced by others who have not yet done so. In some cases, apparent mismatches seem likely to reflect complex multi-address living arrangements rather than data error.

Functionality, Accuracy, and Feasibility: Talking with Modelers

Models are an important part of many policy development processes, but meeting policy objectives relies on policy analysts engaging effectively with the modeling process and modelers understanding the policy issues. Furthermore, there are many different modeling methods, each with characteristics that potentially make it more or less suitable for analyzing a particular policy issue.
This paper presents a novel framework to assist policy analysts to engage with modelers so as to make the best use of models. The framework has three dimensions: Functionality, Accuracy and Feasibility. Functionality concerns ways in which modeling can be used to support broader policy objectives, such as promoting negotiation or comparing options. Accuracy concerns how to best represent the fundamental features of the system being modeled, and relies on selecting an appropriate technique. Feasibility concerns practical issues such as access to data and modeling skills.

Challenging the cancer molecular stratification dogma: Intratumoral heterogeneity undermines consensus molecular subtypes and potential diagnostic value in colorectal cancer

Purpose:
A number of independent gene expression profiling studies have identified transcriptional subtypes in colorectal cancer (CRC) with potential diagnostic utility, culminating in publication of a CRC Consensus Molecular Subtype classification. The worst prognostic subtype has been defined by genes associated with stem-like biology. Recently, it has been shown that the majority of genes associated with this poor prognostic group are stromal-derived. We investigated the potential for tumor misclassification into multiple diagnostic subgroups based on tumoral region sampled.

Experimental Design:
We performed multi-region tissue RNA extraction/transcriptomic analysis using Colorectal Specific Arrays on invasive front, central tumor and lymph node regions selected from tissue samples from 25 CRC patients.

Results:
We identified a consensus 30 gene list which represents the intratumoral heterogeneity within a cohort of primary CRC tumors. Using a series of online datasets, we showed that this gene list displays prognostic potential (HR=2.914 (CI 0.9286-9.162) in stage II/III CRC patients, but in addition we demonstrated that these genes are stromal derived, challenging the assumption that poor prognosis tumors with stem-like biology have undergone a widespread Epithelial Mesenchymal Transition (EMT). Most importantly, we showed that patients can be simultaneously classified into multiple diagnostically relevant subgroups based purely on the tumoral region analysed.

Conclusions:
Gene expression profiles derived from the non-malignant stromal region can influence assignment of CRC transcriptional subtypes, questioning the current molecular classification dogma and highlighting the need to consider pathology sampling region and degree of stromal infiltration when employing transcription-based classifiers to underpin clinical decision-making in CRC.

Radiological imaging in digital systems: the effect of exposure parameters in diagnostic quality and patient dose

Esta tese pretende contribuir para o estudo e análise dos factores relacionados com as técnicas de aquisição de imagens radiológicas digitais, a qualidade diagnóstica e a gestão da dose de radiação em sistema de radiologia digital. A metodologia encontra-se organizada em duas componentes. A componente observacional, baseada num desenho do estudo de natureza retrospectiva e transversal. Os dados recolhidos a partir de sistemas CR e DR permitiram a avaliação dos parâmetros técnicos de exposição utilizados em radiologia digital, a avaliação da dose absorvida e o índice de exposição no detector. No contexto desta classificação metodológica (retrospectiva e transversal), também foi possível desenvolver estudos da qualidade diagnóstica em sistemas digitais: estudos de observadores a partir de imagens arquivadas no sistema PACS. A componente experimental da tese baseou-se na realização de experiências em fantomas para avaliar a relação entre dose e qualidade de imagem. As experiências efectuadas permitiram caracterizar as propriedades físicas dos sistemas de radiologia digital, através da manipulação das variáveis relacionadas com os parâmetros de exposição e a avaliação da influência destas na dose e na qualidade da imagem. Utilizando um fantoma contrastedetalhe, fantomas antropomórficos e um fantoma de osso animal, foi possível objectivar medidas de quantificação da qualidade diagnóstica e medidas de detectabilidade de objectos. Da investigação efectuada, foi possível salientar algumas conclusões. As medidas quantitativas referentes à performance dos detectores são a base do processo de optimização, permitindo a medição e a determinação dos parâmetros físicos dos sistemas de radiologia digital. Os parâmetros de exposição utilizados na prática clínica mostram que a prática não está em conformidade com o referencial Europeu. Verifica-se a necessidade de avaliar, melhorar e implementar um padrão de referência para o processo de optimização, através de novos referenciais de boa prática ajustados aos sistemas digitais. Os parâmetros de exposição influenciam a dose no paciente, mas a percepção da qualidade de imagem digital não parece afectada com a variação da exposição. Os estudos que se realizaram envolvendo tanto imagens de fantomas como imagens de pacientes mostram que a sobreexposição é um risco potencial em radiologia digital. A avaliação da qualidade diagnóstica das imagens mostrou que com a variação da exposição não se observou degradação substancial da qualidade das imagens quando a redução de dose é efectuada. Propõe-se o estudo e a implementação de novos níveis de referência de diagnóstico ajustados aos sistemas de radiologia digital. Como contributo da tese, é proposto um modelo (STDI) para a optimização de sistemas de radiologia digital.

Metabolic signature of lung cancer: a metabolomic study of human tissues and biofluids

This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.

The Influence of Causal Explanations and Diagnostic Labeling on Psychology Students’ Beliefs About Treatments, Prognosis, Dangerousness and Unpredictability in Schizophrenia

This study explored views of 566 Italian psychology students about schizophrenia. The most frequently cited causes were psychological traumas (68%) and heredity (54%). Thirty-three percent of students firmly believed that people with the condition could recover. Reporting heredity among the causes, and identifying schizophrenia were both associated with prognostic pessimism, greater confidence in pharmacological treatments and lower confidence in psychological treatments. Schizophrenia labeling was also associated with higher perception of unpredictability and dangerousness. Compared to first year students, fourth/fifth year students more frequently reported heredity among the causes, and were more pessimistic about schizophrenia recovery. Stigma topics should be included in future psychologists’ education.

An evaluation of the accuracy of models for the determination of the weighted mean temperature of the atmosphere

The estimates of the zenith wet delay resulting from the analysis of data from space techniques, such as GPS and VLBI, have a strong potential in climate modeling and weather forecast applications. In order to be useful to meteorology, these estimates have to be converted to precipitable water vapor, a process that requires the knowledge of the weighted mean temperature of the atmosphere, which varies both in space and time. In recent years, several models have been proposed to predict this quantity. Using a database of mean temperature values obtained by ray-tracing radiosonde profiles of more than 100 stations covering the globe, and about 2.5 year’s worth of data, we have analyzed several of these models. Based on data from the European region, we have concluded that the models provide identical levels of precision, but different levels of accuracy. Our results indicate that regionally-optimized models do not provide superior performance compared to the global models.

Optimisation of an aptamer-biosensor to detect C-reactive protein

Dissertação de Mestrado, Engenharia Biológica, Faculdade de Engenharia de Recursos Naturais, Universidade do Algarve, 2009

New method for the simultaneous identification of pathogenic human viruses using multiplex PCR

Tese de mestrado. Biologia (Biologia Molecular e Genética). Universidade de Lisboa, Faculdade de Ciências, 2014

Improvement in the Accuracy of Back Trajectories Using WRF to Identify Pollen Sources in Southern Iberian Peninsula

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Accuracy assessment of depth estimates from variation in pre- and post-processing of multi-beam SONAR surveys in a fjord environment

Senior thesis written for Oceanography 445

Lyophilisation of influenza, rabies and Marburg lentiviral pseudotype viruses for the development and distribution of a neutralisation-assay based diagnostic kit

Pseudotype viruses (PVs) are chimeric, replication-deficient virions that mimic wild-type virus entry mechanisms and can be safely employed in neutralisation assays, bypassing the need for high biosafety requirements and performing comparably to established serological assays. However, PV supernatant necessitates -80°C long-term storage and cold-chain maintenance during transport, which limits the scope of dissemination and application throughout resource-limited laboratories. We therefore investigated the effects of lyophilisation on influenza, rabies and Marburg PV stability, with a view to developing a pseudotype virus neutralisation assay (PVNA) based kit suitable for affordable global distribution. Infectivity of each PV was calculated after lyophilisation and immediate reconstitution, as well as subsequent to incubation of freeze-dried pellets at varying temperatures, humidities and timepoints. Integrity of glycoprotein structure following treatment was also assessed by employing lyophilised PVs in downstream PVNAs. In the presence of 0.5M sucrose-PBS cryoprotectant, each freeze-dried pseudotype was stably stored for 4 weeks at up to 37°C and could be neutralised to the same potency as unlyophilised PVs when employed in PVNAs. These results confirm the viability of a freeze-dried PVNA-based kit, which could significantly facilitate low-cost serology for a wide portfolio of emerging infectious viruses.