Manifestation of the pairing symmetry in the vortex core structure in iron-based superconductors

The superconducting gap is a basic character of a superconductor. While the cuprates and conventional phonon-mediated superconductors are characterized by distinct d- and s-wave pairing symmetries with nodal and nodeless gap distributions respectively, the superconducting gap distributions in iron-based superconductors are rather diversified. While nodeless gap distributions have been directly observed in Ba1–xKxFe2As2, BaFe2–xCoxAs2, LiFeAs, KxFe2–ySe2, and FeTe1–xSex, the signatures of a nodal superconducting gap have been reported in LaOFeP, LiFeP, FeSe, KFe2As2, BaFe2–xRuxAs2, and BaFe2(As1–xPx)2. Due to the multiplicity of the Fermi surface in these compounds s± and d pairing states can be both nodeless and nodal. A nontrivial orbital structure of the order parameter, in particular the presence of the gap nodes, leads to effects in which the disorder is much richer in dx2–y2-wave superconductors than in conventional materials. In contrast to the s-wave case, the Anderson theorem does not work, and nonmagnetic impurities exhibit a strong pair-breaking influence. In addition, a finite concentration of disorder produces a nonzero density of quasiparticle states at zero energy, which results in a considerable modification of the thermodynamic and transport properties at low temperatures. The influence of order parameter symmetry on the vortex core structure in iron-based pnictide and chalcogenide superconductors has been investigated in the framework of quasiclassical Eilenberger equations. The main results of the thesis are as follows. The vortex core characteristics, such as, cutoff parameter, ξh, and core size, ξ2, determined as the distance at which density of the vortex supercurrent reaches its maximum, are calculated in wide temperature, impurity scattering rate, and magnetic field ranges. The cutoff parameter, ξh(B; T; Г), determines the form factor of the flux-line lattice, which can be obtained in _SR, NMR, and SANS experiments. A comparison among the applied pairing symmetries is done. In contrast to s-wave systems, in dx2–y2-wave superconductors, ξh/ξc2 always increases with the scattering rate Г. Field dependence of the cutoff parameter affects strongly on the second moment of the magnetic field distributions, resulting in a significant difference with nonlocal London theory. It is found that normalized ξ2/ξc2(B/Bc2) dependence is increasing with pair-breaking impurity scattering (interband scattering for s±-wave and intraband impurity scattering for d-wave superconductors). Here, ξc2 is the Ginzburg-Landau coherence length determined from the upper critical field Bc2 = Φ0/2πξ2 c2, where Φ0 is a flux quantum. Two types of ξ2/ξc2 magnetic field dependences are obtained for s± superconductors. It has a minimum at low temperatures and small impurity scattering transforming in monotonously decreasing function at strong scattering and high temperatures. The second kind of this dependence has been also found for d-wave superconductors at intermediate and high temperatures. In contrast, impurity scattering results in decreasing of ξ2/ξc2(B/Bc2) dependence in s++ superconductors. A reasonable agreement between calculated ξh/ξc2 values and those obtained experimentally in nonstoichiometric BaFe2–xCoxAs2 (μSR) and stoichiometric LiFeAs (SANS) was found. The values of ξh/ξc2 are much less than one in case of the first compound and much more than one for the other compound. This is explained by different influence of two factors: the value of impurity scattering rate and pairing symmetry.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Prognostic Markers and Prolonged Interferon-alpha Therapy in Renal Cell Carcinoma

Molekyylimarkkerit ja pitkäaikainen alfainterferonihoito munuaissyövässä Munuaissyöpäpotilaiden viiden vuoden elossaololuku on noin 50 %. Aikaisempien tutkimuksien mukaan viiden vuoden elossaololuku metastasoituneessa munuaissyövässä on 3-16 %, kun käytettiin alfainterferonia sisältävää hoitoa. Tyypillisesti alfainterferonia on käytetty vähemmäin kuin 6 kuukautta. Avoimia kysymyksiä ovat alfainterferonin optimaalinen hoitoannos ja hoidon kesto yksin tai yhdessä uusien täsmähoitojen kanssa. Tärkeimmät tavoitteet olivat tutkia 1) jaksotetun pitkäaikaisen alfainterferonihoidon tehoa ja siedettävyyttä metastasoituneessa munuaissyövässä ja 2) p53-, Ki-67- ja COX-2-proteiinituotannon ennusteellista merkitystä munuaissyövässä. Tutkimuksessa 117 metastasoituneelle munuaissyöpää sairastaneelle potilaalle etsittiin yksilöllinen hänen sietämänsä maksimaalinen hoitoannos rekombinanttia alfa2a-interferonia (Roferon-ATM). Hoitoa pyrittiin jatkamaan 24 kuukauden ajan. Kolmen hoitoviikon jälkeen pidettiin yhden viikon tauko. Hoito lopetettiin, jos ilmaantui vakavia haittavaikutuksia tai tauti eteni. Toisessa tutkimuksessa proteiinituotanto analysoitiin immunohistokemiallisesti munuaissyöpäpotilaiden kasvainnäytteistä, joita oli säilytetty parafiinissa. Kasvainnäytteet oli otettu talteen munuaisen poistoleikkauksen yhteydessä. Nämä potilaat jaettiin kolmeen eri ryhmään: metastasointi primaarivaiheessa (n=29), metastasointi myöhemmin (n=37) ja ei metastasointia (n=51). Keskimääräinen alfainterferonihoidon kesto oli 11 kuukautta (kk) [0,5 – 32 kk]. Objektiivinen hoitovaste todettiin 17 %:lla, tautitilanne pysyi ennallaan 42 %:lla ja myöhäinen vaste (yli 12 kk:tta hoidon aloittamisesta) todettiin 3 %:lla. Aika vasteen saavuttamisesta taudin etenemiseen oli keskimäärin 8 kk ja elinaika 19,1 kk. Viiden vuoden elossaololuku oli 16 %. Jos metastasoituneella munuaissyöpäpotilaalla oli keuhkometastasointi, hän selvisi todennäköisemmin viisi vuotta kuin muut potilaat. Henkeä uhkaavia sivuvaikutuksia ei todettu. Yli 12 kk:n ajan kestävä alfainterferonihoito on hyödyllistä niille potilaille, jotka ovat saaneet objektiivisen hoitovasteen tai tautitilanne on pysynyt ennallaan. Positiivinen p53- ja Ki-67-ekspressio yhdessä viittaavat suureen metastasoinnin todennäköisyyteen. Positiivinen COX-2-ekspressio viittaa viivästyneeseen metastaasien ilmaantumiseen. Metastasoituneilla potilailla positiiviset p53- ja Ki-67-ekspressiot viittaavat huonoon ennusteeseen, mutta positiivinen COX-2 ekspressio viittaa suotuisaan ennusteeseen. Positiivinen COX-2- ja negatiivinen Ki-67-ekspressio yhdessä viittaavat parantuneeseen ennusteeseen metastasoituneessa munuaissyövässä.

Herpes simplex virus type 1 (HSV-1) pathogenesis and HSV gene therapy of experimental autoimmune encephalomyelitis

The aim of this thesis was to develop new herpes simplex virus (HSV) vectors for gene therapy of experimental autoimmune encephalomyelitis (EAE), the principal model of multiple sclerosis (MS), and to study the pathogenesis of wild-type HSV-1 and HSV-1 vectors in vivo. By introducing potential immunomodulatory factors into mice with EAE we strived to develop therapies and possibly find molecules improving recovery from EAE. We aimed at altering the immune response by inducing favorable Th2-type cytokines, thus shifting the immune response from a Th1- or a Th17-response. Our HSV vector expressing interleukin (IL)-5 modulated the cytokine responses, decreased inflammation and alleviated EAE. The use of a novel method, bacterial artificial chromosome (BAC), for engineering recombinant HSV facilitated the construction of a new vector expressing leukemia inhibitory factor (LIF). LIF is a neurotropic cytokine with broad functions in the central nervous system (CNS). LIF promotes oligodendrocyte maturation and decreases demyelination and oligodendrocyte loss. The BAC-derived HSV-LIF vector alleviated the clinical symptoms, induced a higher number of oligodendrocytes and modulated T cell responses. By administering HSV via different infection routes, e.g. peripherally via the nose or eye, or intracranially to the brain, the effect of the immune response on HSV spread at different points of the natural infection route was studied. The intranasal infection was an effective delivery route of HSV to the trigeminal ganglion and CNS, whereas corneal infection displayed limited spread. The corneal and intranasal infections induced different peripheral immune responses, which might explain the observed differences in viral spread.