Sviluppo di un algoritmo di calibrazione per analisi quantitative di immagini in microscopia a fluorescenza

Questo progetto di tesi ha come obiettivo lo sviluppo di un algoritmo per la correzione e la calibrazione delle immagini in microscopia a fluorescenza e della sua implementazione come programma. Infatti, senza tale calibrazione le immagini di microscopia a fluorescenza sarebbero intrinsecamente affette da molteplici tipi di distorsioni ottiche. Questo limita fortemente la possibilità di effettuare analisi quantitative del livello di fluorescenza osservato. Il difetto sul quale ci siamo soffermati è la disomogeneità di campo, ossia una non uniforme fluorescenza causata dalla forma irregolare del fascio di eccitazione. Per conseguire l'obiettivo da noi proposto è necessaria l'acquisizione, in parallelo al campione in esame, di immagini di calibrazione contenenti sfere nanometriche a fluorescenza nota. A partire da queste, tramite procedure di image processing da noi implementate, abbiamo stimato la funzione di correzione della fluorescenza, localmente per ogni punto dell'immagine. Per la creazione di tale algoritmo abbiamo ipotizzato una possibile distribuzione dell'intensità dovuta alla non omogeneità del fascio ed abbiamo quindi stimato i parametri tramite un'apposita procedura di maximum likelihood. Tale stima è stata eseguita tenendo conto di possibili effetti dovuti alla luminosità di background, alla sovrapposizione di più nanosfere e ad effetti di bordo nel corso dell'elaborazione. Questa procedura è stata ripetuta su quattro diverse immagini di calibrazione, per valutarne la consistenza e la validità. Inoltre, per poter verificare che il software di elaborazione abbia le desiderate proprietà di linearità tra segnale misurato ed intensità nota, ci siamo serviti di un'ulteriore immagine di calibrazione contenente una mistura di sfere nanometriche con intensità variabili su due ordini di grandezza. Il risultato di questo lavoro di tesi verrà incluso in un programma per la calibrazione delle immagini in fluorescenza acquisite al laboratorio di biofisica del Dipartimento di Fisica ed Astronomia di Bologna.

Stacked searches for high-energy neutrinos from blazars with IceCube

In the year 2013, the detection of a diffuse astrophysical neutrino flux with the IceCube neutrino telescope – constructed at the geographic South Pole – was announced by the IceCube collaboration. However, the origin of these neutrinos is still unknown as no sources have been identified to this day. Promising neutrino source candidates are blazars, which are a subclass of active galactic nuclei with radio jets pointing towards the Earth. In this thesis, the neutrino flux from blazars is tested with a maximum likelihood stacking approach, analyzing the combined emission from uniform groups of objects. The stacking enhances the sensitivity w.r.t. the still unsuccessful single source searches. The analysis utilizes four years of IceCube data including one year from the completed detector. As all results presented in this work are compatible with background, upper limits on the neutrino flux are given. It is shown that, under certain conditions, some hadronic blazar models can be challenged or even rejected. Moreover, the sensitivity of this analysis – and any other future IceCube point source search – was enhanced by the development of a new angular reconstruction method. It is based on a detailed simulation of the photon propagation in the Antarctic ice. The median resolution for muon tracks, induced by high-energy neutrinos, is improved for all neutrino energies above IceCube’s lower threshold at 0.1TeV. By reprocessing the detector data and simulation from the year 2010, it is shown that the new method improves IceCube’s discovery potential by 20% to 30% depending on the declination.

A new information fusion method for land-use classification using high resolution satellite imagery

Satellite image classification involves designing and developing efficient image classifiers. With satellite image data and image analysis methods multiplying rapidly, selecting the right mix of data sources and data analysis approaches has become critical to the generation of quality land-use maps. In this study, a new postprocessing information fusion algorithm for the extraction and representation of land-use information based on high-resolution satellite imagery is presented. This approach can produce land-use maps with sharp interregional boundaries and homogeneous regions. The proposed approach is conducted in five steps. First, a GIS layer - ATKIS data - was used to generate two coarse homogeneous regions, i.e. urban and rural areas. Second, a thematic (class) map was generated by use of a hybrid spectral classifier combining Gaussian Maximum Likelihood algorithm (GML) and ISODATA classifier. Third, a probabilistic relaxation algorithm was performed on the thematic map, resulting in a smoothed thematic map. Fourth, edge detection and edge thinning techniques were used to generate a contour map with pixel-width interclass boundaries. Fifth, the contour map was superimposed on the thematic map by use of a region-growing algorithm with the contour map and the smoothed thematic map as two constraints. For the operation of the proposed method, a software package is developed using programming language C. This software package comprises the GML algorithm, a probabilistic relaxation algorithm, TBL edge detector, an edge thresholding algorithm, a fast parallel thinning algorithm, and a region-growing information fusion algorithm. The county of Landau of the State Rheinland-Pfalz, Germany was selected as a test site. The high-resolution IRS-1C imagery was used as the principal input data.

RFID tag localization with virtual multi-antenna systems

In questa tesi si sono valutate le prestazioni di un sistema di localizzazione multi-antenna di tag radio frequency identification (RFID) passivi in ambiente indoor. Il sistema, composto da un reader in movimento che percorre una traiettoria nota, ha come obiettivo localizzare il tag attraverso misure di fase; più precisamente la differenza di fase tra il segnale di interrogazione, emesso dal reader, e il segnale ricevuto riflesso dal tag che è correlato alla distanza tra di essi. Dopo avere eseguito una ricerca sullo stato dell’arte di queste tecniche e aver derivato il criterio maximum likelihood (ML) del sistema si è proceduto a valutarne le prestazioni e come eventuali fattori agissero sul risultato di localizzazione attraverso simulazioni Matlab. Come ultimo passo si è proceduto a effettuare una campagna di misure, testando il sistema in un ambiente reale. Si sono confrontati i risultati di localizzazione di tutti gli algoritmi proposti quando il reader si muove su una traiettoria rettilinea e su una traiettoria angolare, cercando di capire come migliorare i risultati.

ECM versus ICP for point registration

Iterative Closest Point (ICP) is a widely exploited method for point registration that is based on binary point-to-point assignments, whereas the Expectation Conditional Maximization (ECM) algorithm tries to solve the problem of point registration within the framework of maximum likelihood with point-to-cluster matching. In this paper, by fulfilling the implementation of both algorithms as well as conducting experiments in a scenario where dozens of model points must be registered with thousands of observation points on a pelvis model, we investigated and compared the performance (e.g. accuracy and robustness) of both ICP and ECM for point registration in cases without noise and with Gaussian white noise. The experiment results reveal that the ECM method is much less sensitive to initialization and is able to achieve more consistent estimations of the transformation parameters than the ICP algorithm, since the latter easily sinks into local minima and leads to quite different registration results with respect to different initializations. Both algorithms can reach the high registration accuracy at the same level, however, the ICP method usually requires an appropriate initialization to converge globally. In the presence of Gaussian white noise, it is observed in experiments that ECM is less efficient but more robust than ICP.

Parallel amino acid replacements in the rhodopsins of the rockfishes (Sebastes spp.) associated with shifts in habitat depth

Among various groups of fishes, a shift in peak wavelength sensitivity has been correlated with changes in their photic environments. The genus Sebastes is a radiation of marine fish species that inhabit a wide range of depths from intertidal to over 600 m. We examined 32 species of Sebastes for evidence of adaptive amino acid substitution at the rhodopsin gene. Fourteen amino acid positions were variable among these species. Maximum likelihood analyses identify several of these to be targets of positive selection. None of these correspond to previously identified critical amino acid sites, yet they may in fact be functionally important. The occurrence of independent parallel changes at certain amino acid positions reinforces this idea. Reconstruction of habitat depths of ancestral nodes in the phylogeny suggests that shallow habitats have been colonized independently in different lineages. The evolution of rhodopsin appears to be associated with changes in depth, with accelerated evolution in lineages that have had large changes in depth.

The evolution of antennal courtship in diplazontine parasitoid wasps (Hymenoptera, Ichneumonidae, Diplazontinae)

Background As predicted by theory, traits associated with reproduction often evolve at a comparatively high speed. This is especially the case for courtship behaviour which plays a central role in reproductive isolation. On the other hand, courtship behavioural traits often involve morphological and behavioural adaptations in both sexes; this suggests that their evolution might be under severe constraints, for instance irreversibility of character loss. Here, we use a recently proposed method to retrieve data on a peculiar courtship behavioural trait, i.e. antennal coiling, for 56 species of diplazontine parasitoid wasps. On the basis of a well-resolved phylogeny, we reconstruct the evolutionary history of antennal coiling and associated morphological modifications to study the mode of evolution of this complex character system. Results Our study reveals a large variation in shape, location and ultra-structure of male-specific modifications on the antennae. As for antennal coiling, we find either single-coiling, double-coiling or the absence of coiling; each state is present in multiple genera. Using a model comparison approach, we show that the possession of antennal modifications is highly correlated with antennal coiling behaviour. Ancestral state reconstruction shows that both antennal modifications and antennal coiling are highly congruent with the molecular phylogeny, implying low levels of homoplasy and a comparatively low speed of evolution. Antennal coiling is lost on two independent occasions, and never reacquired. A zero rate of regaining antennal coiling is supported by maximum parsimony, maximum likelihood and Bayesian approaches. Conclusions Our study provides the first comparative evidence for a tight correlation between male-specific antennal modifications and the use of the antennae during courtship. Antennal coiling in Diplazontinae evolved at a comparatively low rate, and was never reacquired in any of the studied taxa. This suggests that the loss of antennal coiling is irreversible on the timescale examined here, and therefore that evolutionary constraints have greatly influenced the evolution of antennal courtship in this group of parasitoid wasps. Further studies are needed to ascertain whether the loss of antennal coiling is irreversible on larger timescales, and whether evolutionary constraints have influenced courtship behavioural traits in a similar way in other groups.

Timing of progression from Chlamydia trachomatis infection to pelvic inflammatory disease: a mathematical modelling study

Background Pelvic inflammatory disease (PID) results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia) might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection. Methods We develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT) and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT. Results The predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13%) in both processes. Conclusions The findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID.

Heritability, determinants and reference values of renal length: a family-based population study

OBJECTIVES: In this population-based study, reference values were generated for renal length, and the heritability and factors associated with kidney length were assessed. METHODS: Anthropometric parameters and renal ultrasound measurements were assessed in randomly selected nuclear families of European ancestry (Switzerland). The adjusted narrow sense heritability of kidney size parameters was estimated by maximum likelihood assuming multivariate normality after power transformation. Gender-specific reference centiles were generated for renal length according to body height in the subset of non-diabetic non-obese participants with normal renal function. RESULTS: We included 374 men and 419 women (mean ± SD, age 47 ± 18 and 48 ± 17 years, BMI 26.2 ± 4 and 24.5 ± 5 kg/m(2), respectively) from 205 families. Renal length was 11.4 ± 0.8 cm in men and 10.7 ± 0.8 cm in women; there was no difference between right and left renal length. Body height, weight and estimated glomerular filtration rate (eGFR) were positively associated with renal length, kidney function negatively, age quadratically, whereas gender and hypertension were not. The adjusted heritability estimates of renal length and volume were 47.3 ± 8.5 % and 45.5 ± 8.8 %, respectively (P < 0.001). CONCLUSION: The significant heritability of renal length and volume highlights the familial aggregation of this trait, independently of age and body size. Population-based references for renal length provide a useful guide for clinicians. KEY POINTS: • Renal length and volume are heritable traits, independent of age and size. • Based on a European population, gender-specific reference values/percentiles are provided for renal length. • Renal length correlates positively with body length and weight. • There was no difference between right and left renal lengths in this study. • This negates general teaching that the left kidney is larger and longer.

Does a pleiotropic gene explain deafness and blue irises in white cats?

The prevalence of deafness is high in cat populations in which the dominant white gene is segregating. The objective of this study was to investigate whether there is a gene that is responsible for deafness as well as for blue eyes and to establish a plausible mode of inheritance. For this purpose, data from an experimental colony with deaf cats were analyzed. The hearing status was determined by acoustically evoked brain stem responses (BAER). Complex segregation analyses were conducted to find out the most probable mode of inheritance using maximum likelihood procedures. The prevalence of deafness and partial hearing in the experimental colony was 67% and 29%, respectively. The results of the bivariate segregation analysis support the hypothesis of a pleiotropic major gene segregating for deafness and blue iris colour. The high heritability coefficients for both traits, 0.55 and 0.75 respectively, indicate that beside the major gene there is an important influence of polygenic effects.

Large Sample Theory for Semiparametric Regression Models with Two-Phase, Outcome Dependent Sampling

Outcome-dependent, two-phase sampling designs can dramatically reduce the costs of observational studies by judicious selection of the most informative subjects for purposes of detailed covariate measurement. Here we derive asymptotic information bounds and the form of the efficient score and influence functions for the semiparametric regression models studied by Lawless, Kalbfleisch, and Wild (1999) under two-phase sampling designs. We show that the maximum likelihood estimators for both the parametric and nonparametric parts of the model are asymptotically normal and efficient. The efficient influence function for the parametric part aggress with the more general information bound calculations of Robins, Hsieh, and Newey (1995). By verifying the conditions of Murphy and Van der Vaart (2000) for a least favorable parametric submodel, we provide asymptotic justification for statistical inference based on profile likelihood.

Efficient and Ad Hoc Estimation in the Bivariate Censoring Model

A large number of proposals for estimating the bivariate survival function under random censoring has been made. In this paper we discuss nonparametric maximum likelihood estimation and the bivariate Kaplan-Meier estimator of Dabrowska. We show how these estimators are computed, present their intuitive background and compare their practical performance under different levels of dependence and censoring, based on extensive simulation results, which leads to a practical advise.

Smooth Estimation of a Monotone Density

We investigate the interplay of smoothness and monotonicity assumptions when estimating a density from a sample of observations. The nonparametric maximum likelihood estimator of a decreasing density on the positive half line attains a rate of convergence at a fixed point if the density has a negative derivative. The same rate is obtained by a kernel estimator, but the limit distributions are different. If the density is both differentiable and known to be monotone, then a third estimator is obtained by isotonization of a kernel estimator. We show that this again attains the rate of convergence and compare the limit distributors of the three types of estimators. It is shown that both isotonization and smoothing lead to a more concentrated limit distribution and we study the dependence on the proportionality constant in the bandwidth. We also show that isotonization does not change the limit behavior of a kernel estimator with a larger bandwidth, in the case that the density is known to have more than one derivative.

On the Accelerated Failure Time Model for Current Status and Interval Censored Data

This paper introduces a novel approach to making inference about the regression parameters in the accelerated failure time (AFT) model for current status and interval censored data. The estimator is constructed by inverting a Wald type test for testing a null proportional hazards model. A numerically efficient Markov chain Monte Carlo (MCMC) based resampling method is proposed to simultaneously obtain the point estimator and a consistent estimator of its variance-covariance matrix. We illustrate our approach with interval censored data sets from two clinical studies. Extensive numerical studies are conducted to evaluate the finite sample performance of the new estimators.

A Diagnostic Test for the Mixing Distribution in a Generalised Linear Mixed Model

We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimates of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-square distribution under the null hypothesis that the mixing distribution is correctly specified. For the important special case of the logistic regression model with random intercepts, we evaluate via simulation the power of the test in finite samples under several alternative distributional forms for the mixing distribution. We illustrate the method by applying it to data from a clinical trial investigating the effects of hormonal contraceptives in women.