In defence of modeling simultaneity for a correct approximation of cultural aspects: implications for food consumers studies with latent variables

Dealing with latent constructs (loaded by reflective and congeneric measures) cross-culturally compared means studying how these unobserved variables vary, and/or covary each other, after controlling for possibly disturbing cultural forces. This yields to the so-called ‘measurement invariance’ matter that refers to the extent to which data collected by the same multi-item measurement instrument (i.e., self-reported questionnaire of items underlying common latent constructs) are comparable across different cultural environments. As a matter of fact, it would be unthinkable exploring latent variables heterogeneity (e.g., latent means; latent levels of deviations from the means (i.e., latent variances), latent levels of shared variation from the respective means (i.e., latent covariances), levels of magnitude of structural path coefficients with regard to causal relations among latent variables) across different populations without controlling for cultural bias in the underlying measures. Furthermore, it would be unrealistic to assess this latter correction without using a framework that is able to take into account all these potential cultural biases across populations simultaneously. Since the real world ‘acts’ in a simultaneous way as well. As a consequence, I, as researcher, may want to control for cultural forces hypothesizing they are all acting at the same time throughout groups of comparison and therefore examining if they are inflating or suppressing my new estimations with hierarchical nested constraints on the original estimated parameters. Multi Sample Structural Equation Modeling-based Confirmatory Factor Analysis (MS-SEM-based CFA) still represents a dominant and flexible statistical framework to work out this potential cultural bias in a simultaneous way. With this dissertation I wanted to make an attempt to introduce new viewpoints on measurement invariance handled under covariance-based SEM framework by means of a consumer behavior modeling application on functional food choices.

Multidimensional item response theory models with general and specific latent traits for ordinal data

The aim of the thesis is to propose a Bayesian estimation through Markov chain Monte Carlo of multidimensional item response theory models for graded responses with complex structures and correlated traits. In particular, this work focuses on the multiunidimensional and the additive underlying latent structures, considering that the first one is widely used and represents a classical approach in multidimensional item response analysis, while the second one is able to reflect the complexity of real interactions between items and respondents. A simulation study is conducted to evaluate the parameter recovery for the proposed models under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameter recovery is particularly sensitive to the sample size, due to the model complexity and the high number of parameters to be estimated. For a sufficiently large sample size the parameters of the multiunidimensional and additive graded response models are well reproduced. The results are also affected by the trade-off between the number of items constituting the test and the number of item categories. An application of the proposed models on response data collected to investigate Romagna and San Marino residents' perceptions and attitudes towards the tourism industry is also presented.

The role of B cells during acute and latent infections with murine cytomegalovirus and Leishmania major

This thesis focuses on the role of B cells in mCMV and Leishmania major infection. B cells are an essential component of the adaptive immune system and play a key role in the humoral immune response. In mCMV infection we analyzed the influence of B cells on the virus-specific CD8 T cell response, in detail the role of B cells as IL-10 secreting cells, as source of immunoglobulin (Ig) and as antigen presenting cells. In Leishmania major infection we investigated the role of Ig in Th1 and Th2 directed disease.rnWe found in mCMV infection that the B cell secreted IL-10 suppresses effectively the acute virus-specific CD8 T cell response, while the IL-10 secreted by dendritic cell has no obvious effect. Ig has no effect in the acute virus-specific CD8 T cell response, but in memory response Ig is essential. If Ig is missing the CD8 T cell population remains high in memory response 135 days post infection. The complete absence of B cells dramatically reduces the acute virus-specific CD8 T cell response, while B cell reconstitution just partially rescues this dramatic reduction. A comparison of this reduction in a B cell free organism to an organism with depleted dendritic cells gave a similar result. To exclude a malfunction of the CD8 T cells in the B cell deficient mice, the decreased virus-specific CD8 T cell population was confirmed in a B cell depletion model. Further, bone marrow chimeras with a B cell compartment deficient for CD40-/- showed a decrease of the virus-specific response and an involvement of CD40 on B cells. Taken together these results suggest a role for B cells in antigen presentation during mCMV infection.rnFurther we took advantage of the altered mCMV specific CD8 T cell memory response in mice without Ig to investigate the memory inflation of CD8 T cells specific for distinct mCMV specifc peptides. Using a SIINFEKL-presenting virus system, we were able to shorten the time until the memory inflation occurs and show that direct presentation stimulates the memory inflation. rnIn Leishmania major infection, Ig of Th2 balanced BALB/c mice has a central role in preventing a systemic infection, although the ear lesions are smaller in IgMi mice without specific Ig. Here the parasite loads of ears and spleen are elevated, and an IMS-reconstitution does not affect the parasite load. In contrast in Th1 balanced C57BL/6 mice, reconstitution of IgMi mice with serum of either untreated or immunized mice decreased the parasite load of spleen and ear, further IMS treatment reduces the size of the spleen and the cytokine-levels of IL-10, IL-4, IL-2 and IFN-γ to a level comparable to wt mice. rn

Apple latent infection caused by Neofabraea alba: host-pathogen interaction and disease management

Apple latent infection caused by Neofabraea alba: host-pathogen interaction and disease management Bull’s eye rot (BER) caused by Neofabraea alba is one of the most frequent and damaging latent infection occurring in stored pome fruits worldwide. Fruit infection occurs in the orchard, but disease symptoms appear only 3 months after harvest, during refrigerated storage. In Italy BER is particularly serious for late harvest apple cultivar as ‘Pink Lady™’. The purposes of this thesis were: i) Evaluate the influence of ‘Pink Lady™’ apple primary metabolites in N. alba quiescence ii) Evaluate the influence of pH in five different apple cultivars on BER susceptibility iii) To find out not chemical method to control N. alba infection iv) Identify some fungal volatile compounds in order to use them as N. alba infections markers. Results regarding the role of primary metabolites showed that chlorogenic, quinic and malic acid inhibit N. alba development. The study based on the evaluation of cultivar susceptibility, showed that Granny Smith was the most resistant apple cultivar among the varieties analyzed. Moreover, Granny Smith showed the lowest pH value from harvest until the end of storage, supporting the thesis that ambient pH could be involved in the interaction between N. alba and apple. In order to find out new technologies able to improve lenticel rot management, the application of a non-destructive device for the determination of chlorophyll content was applied. Results showed that fruit with higher chlorophyll content are less susceptible to BER, and molecular analyses comforted this result. Fruits with higher chlorophyll content showed up-regulation of PGIP and HCT, genes involved in plant defence. Through the application of PTR-MS and SPME GC-MS, 25 volatile organic compounds emitted by N. alba were identified. Among them, 16 molecules were identified as potential biomarkers.

Outcomes of antiretroviral therapy in the Swiss HIV Cohort Study: latent class analysis

An in-depth understanding of the different groups that make up the HIV-infected population should inform prevention and care. Using latent class analysis (LCA) we identified seven groups with similar socio-demographic and behavioral characteristics at enrolment in the Swiss HIV Cohort Study: older gay men, younger gay men, older heterosexual men, injection drug users, single migrants, migrant women in partnerships and heterosexual men and women. Outcomes of combination antiretroviral therapy (ART) were analyzed in 1,633 patients starting ART. Compared to older gay men, the probability of a virologic response to ART was reduced in single migrants, in older heterosexual men and in IDUs. Loss to follow-up was higher in single migrants and IDUs, and mortality was increased in older heterosexual men and IDUs. Socio-behavioral groups identified by LCA allow insights above what can be gleaned from traditional transmission groups, and may identify patients who could benefit from targeted interventions.

Portal levels of latent transforming growth factor-β are related to liver function in patients with liver cirrhosis

Transforming growth factor-β1 (TGFβ1) is a short-lived immune suppressive and profibrotic protein. Its latent precursor is relatively stable and may even protect from fibrosis. Latent TGFβ1 is synthesized by various tissues including the liver and portal, hepatic, and systemic concentrations of latent TGFβ1 were determined in patients with liver cirrhosis and patients with normal liver function to find out whether circulating levels are affected by liver disease.

Improved sensitivity of an interferon-gamma release assay (T-SPOT.TB™) in combination with tuberculin skin test for the diagnosis of latent tuberculosis in the presence of HIV co-infection

Background Interferon-gamma release assays (IGRA) are more specific than the tuberculin skin test (TST) for the diagnosis of Mycobacterium tuberculosis infection. Data on sensitivity are controversial in HIV infection. Methods IGRA (T-SPOT.TB) was performed using lymphocytes stored within 6 months before culture-confirmed tuberculosis was diagnosed in HIV-infected individuals in the Swiss HIV Cohort Study. Results 64 individuals (69% males, 45% of non-white ethnicity, median age 35 years (interquartile range [IQR] 31-42), 28% with prior AIDS) were analysed. Median CD4 cell count was 223 cells/μl (IQR 103-339), HIV-RNA was 4.7 log10 copies/mL (IQR 4.3-5.2). T-SPOT.TB resulted positive in 25 patients (39%), negative in 18 (28%) and indeterminate in 21 (33%), corresponding to a sensitivity of 39% (95% CI 27-51%) if all test results were considered, and 58% (95% CI 43-74%) if indeterminate results were excluded. Sensitivity of IGRA was independent of CD4 cell count (p = 0.698). Among 44 individuals with available TST, 22 (50%) had a positive TST. Agreement between TST and IGRA was 57% (kappa = 0.14, p = 0.177), and in 34% (10/29) both tests were positive. Combining TST and IGRA (at least one test positive) resulted in an improved sensitivity of 67% (95% CI 52-81%). In multivariate analysis, older age was associated with negative results of TST and T-SPOT.TB (OR 3.07, 95% CI 1,22-7.74, p = 0.017, per 10 years older). Conclusions T-SPOT.TB and TST have similar sensitivity to detect latent TB in HIV-infected individuals. Combining TST and IGRA may help clinicians to better select HIV-infected individuals with latent tuberculosis who qualify for preventive treatment.

CYP2E1 genotype and isoniazid-induced hepatotoxicity in patients treated for latent tuberculosis

OBJECTIVE: To determine whether pharmacogenetic tests such as N-acetyltransferase 2 (NAT2) and cytochrome P450 2E1 (CYP2E1) genotyping are useful in identifying patients prone to antituberculosis drug-induced hepatotoxicity in a cosmopolite population. METHODS: In a prospective study we genotyped 89 patients treated with isoniazid (INH) for latent tuberculosis. INH-induced hepatitis (INH-H) or elevated liver enzymes including hepatitis (INH-ELE) was diagnosed based on the clinical diagnostic scale (CDS) designed for routine clinical practice. NAT2 genotypes were assessed by fluorescence resonance energy transfer probe after PCR analysis, and CYP2E1 genotypes were determined by PCR with restriction fragment length polymorphism analysis. RESULTS: Twenty-six patients (29%) had INH-ELE, while eight (9%) presented with INH-H leading to INH treatment interruption. We report no significant influence of NAT2 polymorphism, but we did find a significant association between the CYP2E1 *1A/*1A genotype and INH-ELE (OR: 3.4; 95% CI:1.1-12; p = 0.02) and a non significant trend for INH-H (OR: 5.9; 95% CI: 0.69-270; p = 0.13) compared with other CYP2E1 genotypes. This test for predicting INH-ELE had a positive predictive value (PPV) of 39% (95% CI: 26-54%) and a negative predictive value (NPV) of 84% (95% CI: 69-94%). CONCLUSION: The genotyping of CYP2E1 polymorphisms may be a useful predictive tool in the common setting of a highly heterogeneous population for predicting isoniazid-induced hepatic toxicity. Larger prospective randomized trials are needed to confirm these results.

Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately