Background: Measurement of carbon monoxide in expired air samples (ECO) is a non-invasive, cost-effective biochemical marker for smoking. Cut points of 6. ppm-10. ppm have been established, though appropriate cut-points for pregnant woman have been debated due to metabolic changes. This study assessed whether an ECO cut-point identifying at least 90% of pregnant smokers, and misidentifying fewer than 10% of non-smokers, could be established. Methods: Pregnant women (N=167) completed a validated self-report smoking assessment, a urine drug screen for cotinine (UDS), and provided an expired air sample twice during pregnancy. Results: Half of women reported non-smoking status early (51%) and late (53%) in pregnancy, confirmed by UDS. Using a traditional 8. ppm. +. cut-point for the early pregnancy reading, only 1% of non-smokers were incorrectly identified as smokers, but only 56% of all smokers, and 67% who smoked 5. + cigarettes in the previous 24. h, were identified. However, at 4. ppm. +, only 8% of non-smokers were misclassified as smokers, and 90% of all smokers and 96% who smoked 5. + cigarettes in the previous 24. h were identified. False positives were explained by heavy second hand smoke exposure and marijuana use. Results were similar for late pregnancy ECO, with ROC analysis revealing an area under the curve of 95 for early pregnancy, and 94 for late pregnancy readings. Conclusions: A lower 4. ppm ECO cut-point may be necessary to identify pregnant smokers using expired air samples, and this cut-point appears valid throughout pregnancy. Work is ongoing to validate findings in larger samples, but it appears if an appropriate cut-point is used, ECO is a valid method for determining smoking status in pregnancy.

Background: Measurement of carbon monoxide in expired air samples (ECO) is a non-invasive, cost-effective biochemical marker for smoking. Cut points of 6. ppm-10. ppm have been established, though appropriate cut-points for pregnant woman have been debated due to metabolic changes. This study assessed whether an ECO cut-point identifying at least 90% of pregnant smokers, and misidentifying fewer than 10% of non-smokers, could be established. Methods: Pregnant women (N=167) completed a validated self-report smoking assessment, a urine drug screen for cotinine (UDS), and provided an expired air sample twice during pregnancy. Results: Half of women reported non-smoking status early (51%) and late (53%) in pregnancy, confirmed by UDS. Using a traditional 8. ppm. +. cut-point for the early pregnancy reading, only 1% of non-smokers were incorrectly identified as smokers, but only 56% of all smokers, and 67% who smoked 5. + cigarettes in the previous 24. h, were identified. However, at 4. ppm. +, only 8% of non-smokers were misclassified as smokers, and 90% of all smokers and 96% who smoked 5. + cigarettes in the previous 24. h were identified. False positives were explained by heavy second hand smoke exposure and marijuana use. Results were similar for late pregnancy ECO, with ROC analysis revealing an area under the curve of 95 for early pregnancy, and 94 for late pregnancy readings. Conclusions: A lower 4. ppm ECO cut-point may be necessary to identify pregnant smokers using expired air samples, and this cut-point appears valid throughout pregnancy. Work is ongoing to validate findings in larger samples, but it appears if an appropriate cut-point is used, ECO is a valid method for determining smoking status in pregnancy.

Debris-slides are fast-moving landslides that occur in the Appalachian region including the Great Smoky Mountains National Park (GRSM). Various knowledge and data-driven approaches using spatial distribution of the past slides and associated factors could be used to estimate the region’s debris-slide susceptibility. This study developed two debris-slide susceptibility models for GRSM using knowledge-driven and data-driven methods in GIS. Six debris-slide causing factors (slope curvature, elevation, soil texture, land cover, annual rainfall, and bedrock discontinuity), and 256 known debris-slide locations were used in the analysis. Knowledge-driven weighted overlay and data-driven bivariate frequency ratio analyses were performed. Both models are helpful; however, each come with a set of advantages and disadvantages regarding degree of complexity, time-dependency, and experience of the analyst. The susceptibility maps are useful to the planners, developers, and engineers for maintaining the park’s infrastructures and delineating zones for further detailed geotechnical investigation.

Remarkable progress has been made in the development of effective treatments for patients with rheumatoid arthritis (RA). To ensure that a patient is optimally responding to treatment, consistent monitoring of disease activity is recommended. Established composite and individual disease activity measures often cannot be computed due to missing laboratory values. Simplified measures that can be calculated without a lab value have been developed and previous studies have validated these new measures, yet differences in their performance compared with established measures remain. Therefore, the goal of my doctoral research was to examine and evaluate disease activity and composite measures to facilitate monitoring of response in clinical care settings and inclusion of patients with missing laboratory values in epidemiological research. In the first study, the validity of two composite measures, the Clinical Disease Activity Index (CDAI) and the Disease Activity Score with 28 joint count (DAS28) was examined and both were significantly associated with a rheumatologist’s decision to change therapy (CDAI OR=1.58; 95% CI: 1.42, 1.76) (DAS28 OR=1.34; 95% CI 1.27,1.56). However, further evaluation using receiver operating characteristic (ROC) analysis found that they were not strong predictors of physician decisions to change therapy (AUC=0.75, 0.76, respectively). Thus, they should not be used to guide treatment decisions in the clinic. Two measures of disease activity, erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) are often not measured and impede the computation of composite measures of disease activity. In the second study, significant factors which may predict the measurement of the ESR and CRP were identified and included physician and clinical variables but no quantitative disease activity measures. Thus the suitability of the ESR and CRP as measures of disease activity is suspect. In the final study, I created a new composite measure, the modified disease activity score with 28 joint count (mDAS28), by replacing the laboratory value in the DAS28. The mDAS28 was then validated by comparing its performance with the DAS28. The measures were strongly correlated (r=0.87), and strong agreement was found between the two measures when categorizing patients to levels of disease activity (ĸ=0.77) and treatment response (ĸ=0.73). Therefore, the mDAS28 could be used in place of the DAS28 when laboratory values needed to compute the DAS28 are missing. In summary, I found that the CDAI and DAS28 were not strong predictors of the rheumatologist’s decision to change therapy. I also found that the variability in the measurement of ESR and CRP was not associated with disease activity. I was able to modify the DAS28 by replacing the laboratory measure and create a new simplified measure, the mDAS28. I also validated the mDAS28 for use in the clinic and in epidemiological research when the DAS28 is unavailable.

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Utilizing multiple biomarkers in medical research is crucial for the diagnostic accuracy of detecting diseases. An optimal method for combining these biomarkers is essential to maximize the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC). The optimality of the likelihood ratio has been proven but the challenges persist in estimating the likelihood ratio, primarily on the estimation of multivariate density functions. In this study, we propose a non-parametric approach for estimating multivariate density functions by utilizing Smoothing Spline density estimation to approximate the full likelihood function for both diseased and non-diseased groups, which compose the likelihood ratio. Simulation results demonstrate the efficiency of our method compared to other biomarker combination techniques under various settings for generated biomarker values. Additionally, we apply the proposed method to a real-world study aimed at detecting childhood autism spectrum disorder (ASD), showcasing its practical relevance and potential for future applications in medical research. Change point detection for functional time series has attracted considerable attention from researchers. Existing methods either rely on FPCA, which may perform poorly with complex data, or use bootstrap approaches in forms that fall short in effectively detecting diverse change functions. In our study, we propose a novel self-normalized test for functional time series implemented via a non-overlapping block bootstrap to circumvent reliance on FPCA. The SN factor ensures both monotonic power and adaptability for detecting diverse change functions on complex data. We also demonstrate our test's robustness in detecting changes in the autocovariance operator. Simulation studies confirm the superior performance of our test across various settings, and real-world applications further illustrate its practical utility. / Doctor of Philosophy / In medical research, it is crucial to accurately detect diseases and predict patient outcomes using multiple health indicators, also known as biomarkers. Combining these biomarkers effectively can significantly improve our ability to diagnose and treat various health conditions. However, finding the best way to combine these biomarkers has been a long-standing challenge. In this study, we propose a new, easy-to-understand method for combining multiple biomarkers using advanced estimation techniques. Our method takes into account various factors and provides a more accurate way to evaluate the combined information from different biomarkers. Through simulations, we demonstrated that our method performs better than other existing methods under a variety of scenarios. Furthermore, we applied our new method to a real-world study focusing on detecting childhood autism spectrum disorder (ASD), highlighting its practical value and potential for future applications in medical research. Detecting changes in patterns over time, especially shifts in averages, has become an important focus in data analysis. Existing methods often rely on techniques that may not perform well with more complex data or are limited in the types of changes they can detect. In this study, we introduce a new approach that improves the accuracy of detecting changes in complex data patterns. Our method is flexible and can identify changes in both the mean and variation of the data over time. Through simulations, we demonstrate that this approach is more accurate than current methods. Furthermore, we applied our method to real-world climate research data, illustrating its practical value.

En associant un contexte chrono-culturel aux graphismes pariétaux, les abris occupés et sculptés se révèlent être des témoins privilégiés pour aborder la structuration spatio-temporelle du Magdalénien moyen. Fondée sur un travail de relevé analytique, l’étude techno-stylistique de quatre dispositifs pariétaux (Roc-aux-Sorciers, Chaire-à-Calvin, Reverdit, Cap-Blanc) met en lumière un double processus d’unité et de régionalisation. Une tradition de la sculpture pariétale magdalénienne apparaît, inscrite dans la lignée de la sculpture pariétale solutréenne. Deux groupes se distinguent cependant. Le « groupe du Roc-aux-Sorciers » s’étend de la Vienne à l’Est du Périgord. À l’intérieur de celui-ci, les analogies des frises du Roc-aux-Sorciers et de la Chaire-à-Calvin soulèvent la question de leur(s) auteur(s), et au-delà de leurs occupants. Le « groupe de Cap-Blanc » coexiste en Périgord. Cette divergence entre le Roc-aux-Sorciers et Cap-Blanc se retrouve dans le mobilier archéologique. Ces deux groupes symboliques illustreraient-ils plus largement deux groupes socio-culturels ? Enfin, la fonction socio-culturelle des sites à sculpture pariétale est abordée, à travers le choix de la sculpture comme mode d’expression graphique. Au sein des sites ornés de l’Est de la Vienne, la frise sculptée monumentale du Roc-aux-Sorciers fut certainement un art public, associé à de grandes occupations. La frise aurait alors agi comme un élément de cohésion sociale. Elle aurait également pu servir de marqueur territorial face à d’autres populations (groupe de la Garenne ?). / Thanks to the association of rock-art and a chrono-cultural context, the occupied and decorated rock-shelters appear to be particularly appropriate to consider the spatio-temporal structuration of the Middle Magdalenian. Based on analytical tracings, the techno-stylistic study of four rock-art sites (Roc-aux-Sorciers, Chaire-à-Calvin, Reverdit, Cap-Blanc) reveals a double process of unity and regionalization. A tradition of the Magdalenian parietal sculpture appears, in the continuity of the Solutrean sculpture. Two groups can be distinguished however. The “Roc-aux-Sorciers group” spreads from Vienne to Eastern Périgord. Inside, the analogies between the Roc-aux-Sorciers and Chaire-à-Calvin friezes raises the question of their author(s), and beyond their inhabitants. The “Cap-Blanc group” coexists in Périgord. The difference between Roc-aux-Sorciers and Cap-Blanc is also found in the archaeological material. Could these symbolic groups illustrate two socio-cultural groups?Finally, the socio-cultural function of sculptured sites is tackled through the choice of sculpture. Inside the decorated sites of Eastern Vienne, the monumental sculptured frieze of Roc-aux-Sorciers rock-shelter certainly was public art, associated with large occupations. Then the frieze would have acted as an element of social cohesion. It could also have served as a territorial mark facing other populations (La Garenne group?).

Introdução: Atualmente, o diagnóstico das reações de hipersensibilidade a anti-inflamatórios não esteroidais (AINEs) baseia-se na história relatada pelo paciente e, em determinados casos, é realizado o Teste de Provocação. Todavia, este teste pode expor os pacientes a riscos graves, inclusive anafilaxia. Em busca de ferramenta mais segura, tem-se estudado o Teste de Ativação de Basófilos (BAT). Trata-se de um teste in vitro, no qual é possível testar diversos estímulos em uma única amostra de sangue, avaliando a ativação dos basófilos (indicativo de reação de hipersensibilidade), através do aumento da expressão de moléculas na superfície desses leucócitos, como o CD63. Objetivo: Padronizar e validar o BAT para ácido acetilsalicílico (AAS), diclofenaco, dipirona e paracetamol em pacientes com hipersensibilidade a AINEs. Metodologia: Participaram 20 (testados com os quatro AINEs) + 33 (testados somente com AAS) pacientes atendidos no Serviço de Imunologia Clínica e Alergia do HCFMUSP, que apresentaram manifestações cutâneas em até 24 horas após exposição a um ou múltiplos AINEs, bem como 13 (quatro AINEs) + 26 (AAS) controles. A técnica consistiu em incubar sangue total com os AINEs já mencionados e, depois, marcar as amostras com anticorpos monoclonais (CD45, anti-IgE e CD63) para posterior leitura por citometria de fluxo. Os resultados obtidos foram comparados com as histórias clínicas e os testes de provocação oral, quando realizados. Resultados: Utilizando os critérios de positividade do BAT empregados na literatura (isto é, porcentagem de CD45+IgE+highCD63+ e índice de estimulação), a sensibilidade e a especificidade variaram de acordo com o AINE: para ácido acetilsalicílico foram 75,0% e 16,7%, respectivamente, diclofenaco, 100% e 0%, dipirona, 23,5% e 66,7%, paracetamol, 40,0% e 42,9%. Após a realização de curvas dose-resposta e tempo-resposta somente com AAS, foi encontrado novo critério de positividade: média de intensidade de fluorescência (MFI) menor do que 6575 representava BAT positivo; com isso, os valores de sensibilidade e especificidade foram: 84,4% e 34,6%, respectivamente. O BAT foi mais sensível em pacientes cuja última reação ocorreu há menos de um ano da data de execução do BAT (93,7%). Conclusão: Devido aos baixos valores de sensibilidade e/ou especificidade, não foi possível padronizar e, por conseguinte, validar o BAT para ácido acetilsalicílico, diclofenaco, dipirona e paracetamol. / Introduction: Currently, the diagnosis of nonsteroidal antiinflammatory drugs (NSAIDs) hypersensivitity is based on patients´ clinical history and drug provocation tests, which are done in selected cases. Nevertheless, this test may expose patients to severe risks, including anaphylaxis. Looking for a safer tool, Basophil Activation Test (BAT) for allergy diagnosis has been studied in the last years. It is an in vitro method where a wide variety of stimuli can be tested, incubating them with the patient\'s blood sample, and observing basophil activation (indication of hypersensitivity) through upregulation of CD63 (or other basophil activation markers) on this leucocyte\'s membrane. Objective: To standardize and validate BAT stimulated with acetylsalicylic acid (ASA), diclophenac, dipyrone and paracetamol in NSAID hypersensitive patients. Methods: Patients which reported immediate reactions (less than 24 hours) after exposure to one or multiple NSAIDs, with cutaneous symptoms were enrolled from Clinical Immunology and Allergy outpatient clinic from HC-FMUSP. BAT with the four NSAIDs was tested on 20 patients and 13 controls and BAT with ASA only, on 33 patients and 26 controls. BAT consisted of incubating whole blood with NSAIDs, then triple-labeled with monoclonal antibodies (CD45, anti-IgE, CD63) for analysis by flow cytometry. BAT results were compared to clinical history and oral provocation tests, when available. Results: According to literature\'s positivity criteria (percentage of CD45+IgE+highCD63+ and stimulation index), sensitivity and specificity varied according to the NSAID tested: for ASA was 75.0% and 16.7% respectively, diclophenac, 100.0% and 0.0%, dipyrone, 23.5% and 66.7%, paracetamol, 40.0% and 42.9%. A new positivity criterion was possible to be defined after further dose-response and time-response curves only for ASA: Mean Fluorescence Intensity lower than 6575 (positive BAT). Accordingly, new sensitivity and specificity for BAT in ASA hypersensitivity were 84,4% and 34,6%. Patients that presented the last reaction in the last year were more likely to present a positive BAT (93.7%). Conclusion: Due to low values for sensitivity and/or specificity, it was not possible to standardize and validate BAT for ASA, diclophenac, dipyrone and paracetamol.