Sharp Lorentz estimates for dyadic-like maximal operators and related Bellman functions

We precisely evaluate Bellman type functions for the dyadic maximal opeator on $R^n$ and of maximal operators on martingales related to local Lorentz type estimates. Using a type of symmetrization principle, introduced for the dyadic maximal operator in earlier works of the authors we precisely evaluate the supremum of the Lorentz quasinorm of the maximal operator on a function $\phi$ when the integral of $\phi$ is fixed and also the same Lorentz quasinorm of $\phi$ is fixed. Also we find the corresponding supremum when the integral of $\phi$ is fixed and several weak type conditions are given.Comment: 11 page

Dyadic weights on RnR^n and reverse Holder inequalities

We prove that for any weight $\phi$ defined on $[0,1]^n$ that satisfies a reverse Holder inequality with exponent p > 1 and constant $c\ge1$ upon all dyadic subcubes of $[0,1]^n$, it's non increasing rearrangement satisfies a reverse Holder inequality with the same exponent and constant not more than $2^nc-2^n + 1$, upon all subintervals of $[0; 1]$ of the form $[0; t]$. This gives as a consequence, according to the results in [8], an interval $[p; p_0(p; c)) = I{p,c}$, such that for any $q \in I{p,c}$, we have that $\phi$ is in $L^q$.Comment: 10 page

Local lower norm estimates for dyadic maximal operators and related Bellman functions

We provide lower $L^q$ and weak $L^p$-bounds for the localized dyadic maximal operator on $R^n$, when the local $L^1$ and the local $L^p$ norm of the function are given. We actually do that in the more general context of homo- geneous tree-like families in probability spaces.Comment: 9 page

Estimates for Bellman functions related to dyadic-like maximal operators on weighted spaces

We provide some new estimates for Bellman type functions for the dyadic maximal opeator on $R^n$ and of maximal operators on martingales related to weighted spaces. Using a type of symmetrization principle, introduced for the dyadic maximal operator in earlier works of the authors we introduce certain conditions on the weight that imply estimate for the maximal operator on the corresponding weighted space. Also using a well known estimate for the maximal operator by a double maximal operators on different m easures related to the weight we give new estimates for the above Bellman type functions.Comment: 10 pages. arXiv admin note: text overlap with arXiv:1511.0611

Μοντελοποίηση Συμπεριφοράς κυττάρων μέσω ανάλυσης σημάτων

286 σ.Η εν λόγω διδακτορική διατριβή πραγματεύεται την μοντελοποίηση ενδοκυτταρικών σηματοδοτικών μονοπατιών με σκοπό την κατανόηση της λειτουργίας και συμπεριφοράς βιολογικών συστημάτων σε περίπλοκες ασθένειες. Τα σηματοδοτικά μονοπάτια απεικονίζουν αλληλεπιδράσεις μεταξύ πρωτεινών και περιγράφουν πως τα κύτταρα αποκρίνονται σε εξωτερικά ερεθίσματα. Τα μονοπάτια αυτά είναι διαθέσιμα στην βιβλιογραφία, σε διαδικτυακές βάσεις δεδομένων. Τα τελευταία χρόνια η διεθνής κοινότητα κάνει προσπάθιες να τα μοντελοποιήσει υιοθετώντας μεθοδολογίες από την θεωρία συστημάτων, προς την δημιουργία εκτελέσιμων μοντέλων που θα δίνουν την δυνατότητα προσομοίωσης σημαντικών κυτταρικών διεργασιών. Στην παρούσα διδακτορική διατριβή, ο υποψήφιος εφαρμόζει μεθόδους Ακέραιου γραμμικού προγραμματισμού για την μοντελοποίηση ενδοκυτταρικών σηματοδοτικών μονοπατιών και την εκπαίδευση των εν λόγω μοντέλων σε πειραματικά δεδομένα με σκοπό την πιστή απεικόνιση των ενδοκυτταρικών σηματοδοτικών διεργασιών στις υπο εξέταση κυτταρικές σειρές. Αποτελέσματα της έρευνας αυτής δημοσιεύτηκαν σε έγκριτα επιστημονικά περιδικά και διεθνή συνέδρεια.Modeling of signal transduction pathways is of the utmost importance in understanding how cells respond to environmental perturbations. Signaling pathways consist of a set of protein protein interactions, identified via high throughput proteomic experiments and made available through on line pathway databases. Over the past few years a range of methods have been proposed to model these networks in an attempt to gain insight into the cells function and uncover the etiology underlying complex disease. Aim of this work is the development of a novel class of methodologies that model signal transduction networks as logic models, and using regular optimizatino formulations cross reference them with high throughput proteomic data to construct predictive models of the signaling mechanisms of the interrogated cell linesΙωάννης Ν. Μελά

Identification of signaling pathways related to drug efficacy in hepatocellular carcinoma via integration of phosphoproteomic, genomic and clinical data

Hepatocellular Carcinoma (HCC) is one of the leading causes of death worldwide, with only a handful of treatments effective in unresectable HCC. Most of the clinical trials for HCC using new generation interventions (drug-targeted therapies) have poor efficacy whereas just a few of them show some promising clinical outcomes [1]. This is amongst the first studies where the mode of action of some of the compounds extensively used in clinical trials is interrogated on the phosphoproteomic level, in an attempt to build predictive models for clinical efficacy. Signaling data are combined with previously published gene expression and clinical data within a consistent framework that identifies drug effects on the phosphoproteomic level and translates them to the gene expression level. The interrogated drugs are then correlated with genes differentially expressed in normal versus tumor tissue, and genes predictive of patient survival. Although the number of clinical trial results considered is small, our approach shows potential for discerning signaling activities that may help predict drug efficacy for HCC.National Institutes of Health (U.S.) (Grant U54-CA119267)National Institutes of Health (U.S.) (Grant R01-CA96504

Combined logical and data-driven models for linking signalling pathways to cellular response

Background Signalling pathways are the cornerstone on understanding cell function and predicting cell behavior. Recently, logical models of canonical pathways have been optimised with high-throughput phosphoproteomic data to construct cell-type specific pathways. However, less is known on how signalling pathways can be linked to a cellular response such as cell growth, death, cytokine secretion, or transcriptional activity. Results In this work, we measure the signalling activity (phosphorylation levels) and phenotypic behavior (cytokine secretion) of normal and cancer hepatocytes treated with a combination of cytokines and inhibitors. Using the two datasets, we construct "extended" pathways that integrate intracellular activity with cellular responses using a hybrid logical/data-driven computational approach. Boolean logic is used whenever a priori knowledge is accessible (i.e., construction of canonical pathways), whereas a data-driven approach is used for linking cellular behavior to signalling activity via non-canonical edges. The extended pathway is subsequently optimised to fit signalling and behavioural data using an Integer Linear Programming formulation. As a result, we are able to construct maps of primary and transformed hepatocytes downstream of 7 receptors that are capable of explaining the secretion of 22 cytokines. Conclusions We developed a method for constructing extended pathways that start at the receptor level and via a complex intracellular signalling pathway identify those mechanisms that drive cellular behaviour. Our results constitute a proof-of-principle for construction of "extended pathways" that are capable of linking pathway activity to diverse responses such as growth, death, differentiation, gene expression, or cytokine secretion.Marie Curie International Reintegration Grants (MIRG-14-CT-2007-046531)Vertex Pharmaceuticals IncorporatedBundesministerium für Wissenschaft und Forschung (HepatoSys)Massachusetts Institute of Technology (Rockwell International Career Development Professorship)Bundesministerium für Wissenschaft und Forschung (HepatoSys 0313081D

Translational systems pharmacology‐based predictive assessment of drug‐induced cardiomyopathy

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142916/1/psp412272.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142916/2/psp412272_am.pd

Translational Systems Pharmacology-Based Predictive Assessment of Drug-Induced Cardiomyopathy

Drug-induced cardiomyopathy contributes to drug attrition. We compared two pipelines of predictive modeling: (1) applying elastic net (EN) to differentially expressed genes (DEGs) of drugs; (2) applying integer linear programming (ILP) to construct each drug’s signaling pathway starting from its targets to downstream proteins, to transcription factors, and to its DEGs in human cardiomyocytes, and then subjecting the genes/proteins in the drugs’ signaling networks to EN regression. We classified 31 drugs with availability of DEGs into 13 toxic and 18 nontoxic drugs based on a clinical cardiomyopathy incidence cutoff of 0.1%. The ILP-augmented modeling increased prediction accuracy from 79% to 88% (sensitivity: 88%; specificity: 89%) under leave-one-out cross validation. The ILP-constructed signaling networks of drugs were better predictors than DEGs. Per literature, the microRNAs that reportedly regulate expression of our six top predictors are of diagnostic value for natural heart failure or doxorubicin-induced cardiomyopathy. This translational predictive modeling might uncover potential biomarkers

The impact of temperature changes on summer time ozone and its precursors in the Eastern Mediterranean

Changes in temperature due to variability in meteorology and climate change are expected to significantly impact atmospheric composition. The Mediterranean is a climate sensitive region and includes megacities like Istanbul and large urban agglomerations such as Athens. The effect of temperature changes on gaseous air pollutant levels and the atmospheric processes that are controlling them in the Eastern Mediterranean are here investigated. The WRF/CMAQ mesoscale modeling system is used, coupled with the MEGAN model for the processing of biogenic volatile organic compound emissions. A set of temperature perturbations (spanning from 1 to 5 K) is applied on a base case simulation corresponding to July 2004. The results indicate that the Eastern Mediterranean basin acts as a reservoir of pollutants and their precursor emissions from large urban agglomerations. During summer, chemistry is a major sink at these urban areas near the surface, and a minor contributor at downwind areas. On average, the atmospheric processes are more effective within the first 1000 m above ground. Temperature increases lead to increases in biogenic emissions by 9±3% K<sup>−1</sup>. Ozone mixing ratios increase almost linearly with the increases in ambient temperatures by 1±0.1 ppb O<sub>3</sub> K<sup>−1</sup> for all studied urban and receptor stations except for Istanbul, where a 0.4±0.1 ppb O<sub>3</sub> K<sup>−1</sup> increase is calculated, which is about half of the domain-averaged increase of 0.9±0.1 ppb O<sub>3</sub> K<sup>−1</sup>. The computed changes in atmospheric processes are also linearly related with temperature changes