O RADU ALEKSANDRA IZ TRALLESA

Helminthiasis is known to man since antiquity, but it still remains a significant public health problem. In ancient times many plants have been tried as possible therapeutics in search of an effective drug. This manuscript investigates ancient beliefs on parasitic worm infestation. Moreover, Alexander of Tralles’ (525 – 605 CE) suggestions on the treatment of this condition are discussed as found in his lesser-known work “A letter on helminths”, along with comments on the use of those herbal cures by modern medicine.Bolest helmintijaza poznata je još od antičkog doba, ali je i danas značajan javnozdravstveni problem. U davnim su vremenima, u potrazi za učinkovitim lijekom, mnoge biljke iskušane kao mogući terapeutik. Ovaj rad istražuje drevna vjerovanja vezana uza zarazu parazitskim crvima. Štoviše, raspravlja se o prijedlozima Aleksandra iz Trala (525. – 605.) vezanim uz liječenje ovog stanja, koji su izneseni u njegovu manje poznatom djelu Pismo o helminthima, zajedno s komentarima o upotrebi tih biljnih lijekova u suvremenoj medicini

Penalized Likelihood Estimation of Trivariate Additive Binary Models

In many empirical situations, modelling simultaneously three or more outcomes as well as their dependence structure can be of considerable relevance. Trivariate modelling is continually gaining in popularity (e.g., Genest et al., 2013; Król et al., 2016; Zhong et al., 2012) because of the appealing property to account for the endogeneity issue and non-random sample selection bias, two issues that commonly arise in empirical studies (e.g., Zhang et al., 2015; Radice et al., 2013; Marra et al., 2017; Bärnighausen et al., 2011). The applied and methodological interest in trivariate modelling motivates the current thesis and the aim is to develop and estimate a generalized trivariate binary regression model, which accounts for several types of covariate effects (such as linear, nonlinear, random and spatial effects), as well as error correlations. In particular, the thesis focuses on the following targets. First, we address the issue in estimating accurately the correlation coefficients, which characterize the dependence of the binary responses conditional on regressors. We found that this is not an unusual occurrence for trivariate binary models and as far as we know such a limitation is neither discussed nor dealt with. Based on this framework, we develop models for dealing with data suffering from endogeneity and/or nonrandom sample selection. Moreover, we propose trivariate Gaussian copula models where the link functions can in principle be derived from any parametric distribution and the parameters describing the association between the responses can be made dependent on several types of covariate effects. All the coefficients of the model are estimated simultaneously within a penalized likelihood framework based on a carefully structured trust region algorithm with integrated automatic multiple smoothing parameter selection. The developments have been incorporated in the function SemiParTRIV()/gjrm() in the R package GJRM (Marra & Radice, 2017). The extensive use of simulated data as well as real datasets illustrates each development in detail and completes the analysis

Involvement of polyamine metabolism in the response of Medicago truncatula genotypes to salt stress

Salinity constitutes one of the most important causes leading to severe reduction in plant yield. Several reports correlate the accumulation of polyamines in plants with tolerance to abiotic stress cues. The present study examined three Medicago truncatula genotypes with differing sensitivities to salinity (TN1.11, tolerant; Jemalong A17, moderately sensitive; TN6.18, sensitive), with the aim of examining the genotype-specific involvement of the polyamine metabolic pathway in plant response to salinity. The study was carried out with leaves harvested 48 h after watering plants with 200 mM NaCl. A comprehensive profile of free polyamines was determined using high performance liquid chromatography. All genotypes showed spermidine and spermine as the most abundant polyamines under control conditions. In salinity conditions, spermine levels increased at the expense of putrescine and spermidine, indicating a drift of polyamine metabolism towards the synthesis of increasing polycationic forms as a stress response. The increasing balance between high and low polycationic forms was clearly diminished in the salt-sensitive genotype TN6.18, showing a clear correlation with its sensitive phenotype. The polyamine metabolic profile was then supported by molecular evidence through the examination of polyamine metabolism transcript levels by RT-qPCR. General suppression of genes that are involved upstream in the PA biosynthetic pathway was determined. Contrarily, an induction in the expression of genes involved in the biosynthesis of spermine and spermidine was observed, in agreement with the metabolic analysis. A significant induction in diamino oxidase expression, involved in the catabolism of putrescine, was specifically found in the sensitive genotype ΤΝ6.18, indicating a distinct metabolic response to stress. Present findings highlight the involvement of polyamines in the defense response of Medicago genotypes showing sensitivity to salt stress

A trivariate additive regression model with arbitrary link functions and varying correlation matrix

In many empirical situations, modelling simultaneously three or more outcomes as well as their dependence structure can be of considerable relevance. Copulae provide a powerful framework to build multivariate distributions and allow one to view the specification of the marginal responses’ equations and their dependence as separate but related issues. We propose a generalizationof the trivariate additive probit model where the link functions can in principle be derived from any parametric distribution and the parameters describing the residual association between the responses can be made dependent on several types of covariate effects (such as linear, nonlinear, random, and spatial effects). All the coefficients of the model are estimated simultaneously within a penalized likelihood framework that uses a trust region algorithm with integrated automatic multiple smoothing parameter selection. The effectiveness of the model is assessed in simulation as well as empirically by modelling jointly three adverse birth binary outcomes in North Carolina. The approach can be easily employed via the gjrm() function in the R package GJRM

Pervasiveness of Staphylococcus carnosus over Staphylococcus xylosus is affected by the level of acidification within a conventional meat starter culture set-up

Staphylococcus carnosus and Staphylococcus xylosus are commonly used, individually or in combination, within conventional starter cultures for the purposes of colour and flavour development during meat fermentation. Yet, little is known about the relative importance of both species under different processing conditions. The present study aimed at investigating the competitiveness of S. carnosus within a meat starter culture under different acidification profiles. The experimental set-up involved a gradient of decreasing experimental control but increasing realism, ranging from liquid meat fermentation models in a meat simulation medium, over solid mince based meat fermentation models, to fermented sausage production on pilot-scale level. In general, S. carrion's gained a fitness advantage over S. xylosus in the most acidified variants of each set-up. In contrast, increasing persistence of S. xylosus was seen at the mildest acidification profiles, especially when approximating actual meat fermentation practices. Under such conditions, S. carnosus was reduced to co-prevalence in the mince based meat fermentation models and was fully outcompeted on pilot-scale level. The latter was even the case when no S. xylosus starter culture was added, whereby S. carnosus was overpowered by staphylococci that originated from the meat background (mostly S. xylosus strains). The results of the present study suggested that conventional starter cultures behave differently when applied in different technological set-ups or using different recipes, with possible repercussions on fermented meat product quality

Effect of polyamines and synthetic polyamine-analogues on the expression of antizyme (AtoC) and its regulatory genes

BACKGROUND: In bacteria, the biosynthesis of polyamines is modulated at the level of transcription as well as post-translationally. Antizyme (Az) has long been identified as a non-competitive protein inhibitor of polyamine biosynthesis in E. coli. Az was also revealed to be the product of the atoC gene. AtoC is the response regulator of the AtoS-AtoC two-component system and it functions as the positive transcriptional regulator of the atoDAEB operon genes, encoding enzymes involved in short chain fatty acid metabolism. The antizyme is referred to as AtoC/Az, to indicate its dual function as both a transcriptional and post-translational regulator. RESULTS: The roles of polyamines on the transcription of atoS and atoC genes as well as that of atoDAEB(ato) operon were studied. Polyamine-mediated induction was tested both in atoSC positive and negative E. coli backgrounds by using β-galactosidase reporter constructs carrying the appropriate promoters patoDAEB, patoS, patoC. In addition, a selection of synthetic polyamine analogues have been synthesized and tested for their effectiveness in inducing the expression of atoC/Az, the product of which plays a pivotal role in the feedback inhibition of putrescine biosynthesis and the transcriptional regulation of the ato operon. The effects of these compounds were also determined on the ato operon expression. The polyamine analogues were also tested for their effect on the activity of ornithine decarboxylase (ODC), the key enzyme of polyamine biosynthesis and on the growth of polyamine-deficient E. coli. CONCLUSION: Polyamines, which have been reported to induce the protein levels of AtoC/Az in E. coli, act at the transcriptional level, since they cause activation of the atoC transcription. In addition, a series of polyamine analogues were studied on the transcription of atoC gene and ODC activity

The diagnostic and prognostic potential of the EGFR/MUC4/MMP9 axis in glioma patients

Glioblastoma is the most aggressive form of brain cancer, presenting poor prognosis despite current advances in treatment. There is therefore an urgent need for novel biomarkers and therapeutic targets. Interactions between mucin 4 (MUC4) and the epidermal growth factor receptor (EGFR) are involved in carcinogenesis, and may lead to matrix metalloproteinase-9 (MMP9) overexpression, exacerbating cancer cell invasiveness. In this study, the role of MUC4, MMP9, and EGFR in the progression and clinical outcome of glioma patients was investigated. Immunohistochemistry (IHC) and immunofluorescence (IF) in fixed tissue samples of glioma patients were used to evaluate the expression and localization of EGFR, MMP9, and MUC4. Kaplan–Meier survival analysis was also performed to test the prognostic utility of the proteins for glioma patients. The protein levels were assessed with enzyme-linked immunosorbent assay (ELISA) in serum of glioma patients, to further investigate their potential as non-invasive serum biomarkers. We demonstrated that MUC4 and MMP9 are both significantly upregulated during glioma progression. Moreover, MUC4 is co-expressed with MMP9 and EGFR in the proliferative microvasculature of glioblastoma, suggesting a potential role for MUC4 in microvascular proliferation and angiogenesis. The combined high expression of MUC4/MMP9, and MUC4/MMP9/EGFR was associated with poor overall survival (OS). Finally, MMP9 mean protein level was significantly higher in the serum of glioblastoma compared with grade III glioma patients, whereas MUC4 mean protein level was minimally elevated in higher glioma grades (III and IV) compared with control. Our results suggest that MUC4, along with MMP9, might account for glioblastoma progression, representing potential therapeutic targets, and suggesting the ‘MUC4/MMP9/EGFR axis’ may play a vital role in glioblastoma diagnostics

Species pervasiveness within the group of coagulase-negative staphylococci associated with meat fermentation is modulated by pH

During spontaneous meat fermentations, Staphylococcus equorum, Staphylococcus saprophyticus, and Staphylococcus xylosus are generally the most prevailing species within the communities of coagulase-negative staphylococci (CNS). There is an interest to introduce CNS isolates from artisan-style spontaneous meat fermentations as starter cultures in more industrialized processes, as to confer additional quality benefits. However, staphylococcal competitiveness within the meat matrix is affected by the processing conditions, which vary considerably among product types. A major factor of variability relates to the intensity of acidification, driven by the concentration of added carbohydrates. The effect of pH on CNS prevalence was studied in both a mince-based meat fermentation model and in fermented sausages produced on pilot scale. Roughly, from all experiments combined, it appeared that a pH of 5.3 corresponded with a breakpoint for CNS selection. Above this value, a general prevalence by S. xylosus was found, even overruling the addition of starter cultures consisting of S. equorum and S. saprophyticus strains. At pH values below 5.3, S. xylosus was also accompanied by S. equorum (following a mild pH drop) and S. saprophyticus (following a stronger pH drop). Still, addition of starter cultures affected the volatile profile compared to the control batch, even if those starter cultures were not able to dominate during the ripening process. This study nonetheless provides a warning for an overly confident use of specific CNS species as starter cultures, especially when in a given processing context the prevailing conditions do not allow superior growth compared to the CNS from the background microbiota