Ultrasound-Triggered Controlled Drug Delivery and Biosensing Using Silica Nanotubes

Silica nanotubes (SNTs) have been demonstrated here as a versatile host for controlled drug delivery and biosensing. The sol-gel template synthesized SNTs have a slow rate of drug release. Application of an external stimulus in the form of ultrasound to or chemical functionalization of synthesized SNT results in higher yield of drug release as well as yield of drug release varying linearly with time. In case of controlled drug delivery triggered by ultrasound, drug yield as function of time is found to be heavily dependent on the ultrasound impulse protocol. Impulses of shorter duration (similar to 0.5 min) and shorter time intervals between successive impulses resulted in higher drug yields. Confinement of hemoglobin (Hb) inside nanometer sized channels of SNT does not have any detrimental effect on the native protein structure and function. Observance of significant enhancement in direct electron transfer of Hb makes the SNTs also promising for application in biosensors.

CHEK2 in Breast and Colorectal Cancer

Breast and colorectal cancers, are common types of cancer, with over two million newly diagnosed cases annually worldwide. Cancer is a genetic disease and defects in DNA integrity restoring functions make a significant contribution to cancer risk. CHEK2 is a checkpoint kinase functioning as a regulator of cell cycle checkpoints, apoptosis, and DNA repair in response to DNA double-strand breaks. The aim of this study was to evaluate the role of CHEK2 in breast cancer predisposition in Finnish breast cancer families and in breast cancer risk at the population level. We were interested in the clinical and biological characteristics of the breast tumors associated with the CHEK2 germline mutations or aberrant CHEK2 protein expression and the effect on survival of patients with these CHEK2 defects. We also assessed the role of CHEK2 mutations, namely 1100delC and I157T, in colorectal cancer susceptibility in Finland. CHEK2 I157T was found to be a low-penetrance breast cancer susceptibility allele, conferring a 1.4-fold risk for carriers. Reduced or absent CHEK2 protein expression was observed in one-fifth of breast tumors from patients unselected for family history, implying that defective CHEK2 signaling contributes to tumorigenesis. Reduction in CHEK2 expression was more common in tumors with larger diameter and ER expression, but with regard to other tumor characteristics and prognosis of a patient no association was observed. Results from comparison of CHEK2 1100delC carrier tumors with noncarrier tumors were in line with the findings from the CHEK2 expression study. Tumors from CHEK2 1100delC carriers were more often of higher grade than tumors from noncarriers, and they also tended to be ER-positive more often, although generally 1100delC status does not seem to radically affect the tumor characteristics. Our results suggest that CHEK2 1100delC may not be a susceptibility allele for CRC, although a very small effect cannot be excluded. Furthermore, CHEK2 1100delC is equally frequent in HBCC (hereditary breast and colorectal cancer) phenotype families and in breast cancer families. Over 1000 CRC cases were screened for CHEK2 I157T, and a significantly higher frequency of I157T was observed among both familial and sporadic CRC cases. The relation of CHEK2 I157T with familial CRC has not been studied previously. CHEK2 I157T seems to be a susceptibility allele for both familial and sporadic CRC, conferring a 1.5-fold risk for carriers of this variant. CHEK2 I157T has been proposed to have a role as a multiple cancer susceptibility allele, which is supported by our results since we observed a trend towards higher frequency of the variant among cases with multiple primary tumors or those with a family history of cancer. During the last five years CHEK2 has established its role as an important cancer susceptibility gene. It has become apparent that CHEK2 is a low-penetrance susceptibility gene for several cancer types, significantly contributing to familial cancer risk as well as to cancer risk at the population level.

Frechet distance based approach for searching online handwritten documents

We propose a novel, language-neutral approach for searching online handwritten text using Frechet distance. Online handwritten data, which is available as a time series (x,y,t), is treated as representing a parameterized curve in two-dimensions and the problem of searching online handwritten text is posed as a problem of matching two curves in a two-dimensional Euclidean space. Frechet distance is a natural measure for matching curves. The main contribution of this paper is the formulation of a variant of Frechet distance that can be used for retrieving words even when only a prefix of the word is given as query. Extensive experiments on UNIPEN dataset(1) consisting of over 16,000 words written by 7 users show that our method outperforms the state-of-the-art DTW method. Experiments were also conducted on a Multilingual dataset, generated on a PDA, with encouraging results. Our approach can be used to implement useful, exciting features like auto-completion of handwriting in PDAs.

Landau-Zener problem with waiting at the minimum gap and related quench dynamics of a many-body system

We discuss a technique for solving the Landau-Zener (LZ) problem of finding the probability of excitation in a two-level system. The idea of time reversal for the Schrodinger equation is employed to obtain the state reached at the final time and hence the excitation probability. Using this method, which can reproduce the well-known expression for the LZ transition probability, we solve a variant of the LZ problem, which involves waiting at the minimum gap for a time t(w); we find an exact expression for the excitation probability as a function of t(w). We provide numerical results to support our analytical expressions. We then discuss the problem of waiting at the quantum critical point of a many-body system and calculate the residual energy generated by the time-dependent Hamiltonian. Finally, we discuss possible experimental realizations of this work.

Pharmacogenetics of SLCO1B1: Population genetics and effect on statins

Kohonneiden kolesterolipitoisuuksien alentamisessa käytettävien statiinien hyödyt sydän- ja verisuonisairauksien estossa on vahvasti osoitettu ja niiden käyttö on niin Suomessa kuin muuallakin maailmassa kasvanut voimakkaasti – Suomessa statiininkäyttäjiä on noin 600 000. Statiinilääkitys on pitkäaikaisessakin käytössä melko hyvin siedetty, mutta yleisimpinä haittavaikutuksina voi ilmetä lihasheikkoutta, -kipua ja -kramppeja, jotka voivat edetä jopa henkeä uhkaavaksi lihasvaurioksi. Lihashaittariski suurenee suhteessa statiiniannokseen ja plasman statiinipitoisuuksiin. Statiinien plasmapitoisuuksissa, tehossa ja haittavaikutusten ilmenemisessä on suuria potilaskohtaisia eroja. SLCO1B1-geenin koodaama OATP1B1-kuljetusproteiini kuljettaa monia elimistön omia aineita ja lääkeaineita verenkierrosta solukalvon läpi maksasoluun, mm. statiineja, joiden kolesterolia alentava vaikutus ja poistuminen elimistöstä tapahtuvat pääosin maksassa. Erään SLCO1B1-geenin nukleotidimuutoksen (c.521T>C) tiedetään heikentävän OATP1B1:n kuljetustehoa. Tässä väitöskirjatyössä selvitettiin SLCO1B1-geenin perinnöllistä muuntelua suomalaisilla ja eri väestöissä maailmanlaajuisesti. Lisäksi selvitettiin SLCO1B1:n muunnosten vaikutusta eri statiinien pitoisuuksiin (farmakokinetiikka) ja vaikutuksiin (farmakodynamiikka) sekä kolesteroliaineenvaihduntaan. Näihin tutkimuksiin valittiin SLCO1B1-genotyypin perusteella terveitä vapaaehtoisia koehenkilöitä, joille annettiin eri päivinä kerta-annos kutakin tutkittavaa statiinia: fluvastatiinia, pravastatiinia, simvastatiinia, rosuvastatiinia ja atorvastatiinia. Verinäytteistä määritettiin plasman statiinien ja niiden aineenvaihduntatuotteiden sekä kolesterolin ja sen muodostumista ja imeytymistä kuvaavien merkkiaineiden pitoisuuksia. Toiminnallisesti merkittävien SLCO1B1-geenimuunnosten esiintyvyydessä todettiin suuria eroja eri väestöjen välillä. Suomalaisilla SLCO1B1 c.521TC-genotyypin (geenimuunnos toisessa vastinkromosomissa) esiintyvyys oli noin 32 % ja SLCO1B1 c.521CC-genotyypin (geenimuunnos molemmissa vastinkromosomeissa) esiintyvyys noin 4 %. Globaalisti geenimuunnosten esiintyvyys korreloi maapallon leveyspiirien kanssa siten, että matalaan transportteriaktiivisuuteen johtavat muunnokset olivat yleisimpiä pohjoisessa ja korkeaan aktiivisuuteen johtavat päiväntasaajan lähellä asuvilla väestöillä. SLCO1B1-genotyypillä oli merkittävä vaikutus statiinien plasmapitoisuksiin lukuun ottamatta fluvastatiinia. Simvastatiinihapon plasmapitoisuudet olivat keskimäärin 220 %, atorvastatiinin 140 %, pravastatiinin 90 % ja rosuvastatiinin 70 % suuremmat c.521CC-genotyypin omaavilla koehenkilöillä verrattuna normaalin c.521TT-genotyypin omaaviin. Genotyypillä ei ollut merkittävää vaikutusta minkään statiinin tehoon tässä kerta-annostutkimuksessa, mutta geenimuunnoksen kantajilla perustason kolesterolisynteesinopeus oli suurempi. Tulokset osoittavat, että SLCO1B1 c.521T>C geenimuunnos on varsin yleinen suomalaisilla ja muilla ei-afrikkalaisilla väestöillä. Tämä geenimuunnos voi altistaa erityisesti simvastatiinin, mutta myös atorvastatiinin, pravastatiinin ja rosuvastatiinin, aiheuttamille lihashaitoille suurentamalla niiden plasmapitoisuuksia. SLCO1B1:n geenimuunnoksen testaamista voidaan tulevaisuudessa käyttää apuna valittaessa sopivaa statiinilääkitystä ja -annosta potilaalle, ja näin parantaa sekä statiinihoidon turvallisuutta että tehoa.

Interactive Distributed Source Coding in Asymmetric Communication Scenarios

We provide a new unified framework, called "multiple correlated informants - single recipient" communication, to address the variations of the traditional Distributed Source Coding (DSC) problem. Different combinations of the assumptions about the communication scenarios and the objectives of communication result in different variations of the DSC problem. For each of these variations, the complexities of communication and computation of the optimal solution is determined by the combination of the underlying assumptions. In the proposed framework, we address the asymmetric, interactive, and lossless variant of the DSC problem, with various objectives of communication and provide optimal solutions for those. Also, we consider both, the worst-case and average-case scenarios.

Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

Single-resolution and multiresolution extended-Kalman-filter-based reconstruction approaches to optical refraction tomography

The problem of reconstruction of a refractive-index distribution (RID) in optical refraction tomography (ORT) with optical path-length difference (OPD) data is solved using two adaptive-estimation-based extended-Kalman-filter (EKF) approaches. First, a basic single-resolution EKF (SR-EKF) is applied to a state variable model describing the tomographic process, to estimate the RID of an optically transparent refracting object from noisy OPD data. The initialization of the biases and covariances corresponding to the state and measurement noise is discussed. The state and measurement noise biases and covariances are adaptively estimated. An EKF is then applied to the wavelet-transformed state variable model to yield a wavelet-based multiresolution EKF (MR-EKF) solution approach. To numerically validate the adaptive EKF approaches, we evaluate them with benchmark studies of standard stationary cases, where comparative results with commonly used efficient deterministic approaches can be obtained. Detailed reconstruction studies for the SR-EKF and two versions of the MR-EKF (with Haar and Daubechies-4 wavelets) compare well with those obtained from a typically used variant of the (deterministic) algebraic reconstruction technique, the average correction per projection method, thus establishing the capability of the EKF for ORT. To the best of our knowledge, the present work contains unique reconstruction studies encompassing the use of EKF for ORT in single-resolution and multiresolution formulations, and also in the use of adaptive estimation of the EKF's noise covariances. (C) 2010 Optical Society of America

Vector evaluated particle swarm optimization (VEPSO) for multi-objective design optimization of composite structures

We present a generic method/model for multi-objective design optimization of laminated composite components, based on vector evaluated particle swarm optimization (VEPSO) algorithm. VEPSO is a novel, co-evolutionary multi-objective variant of the popular particle swarm optimization algorithm (PSO). In the current work a modified version of VEPSO algorithm for discrete variables has been developed and implemented successfully for the, multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; failure mechanism based failure criteria, Maximum stress failure criteria and the Tsai-Wu failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. (C) 2007 Elsevier Ltd. All rights reserved.

A semi-analytical solution for multilayer diffusion in a composite medium consisting of a large number of layers

Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.

Evidence for an association with type 2 diabetes mellitus at the PPARG locus in a South Indian population

Peroxisome proliferator activated receptor-gamma 2 (PPARG2) is a nuclear hormone receptor of ligand-dependent ranscription factor involved in adipogenesis and a molecular target of the insulin sensitizers thiazolidinediones. We addressed the question of whether the 3 variants (-1279G/A, Pro12Ala, and His478His) in the PPARG2 gene are associated with type 2 diabetes mellitus and its related traits in a South Indian population. The study subjects (1000 type 2 diabetes mellitus and 1000 normal glucose-tolerant subjects) were chosen randomly from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in southern India. The variants were screened by single-stranded conformational variant, direct sequencing, and restriction fragment length polymorphism. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. The -1279G/A, Pro12Ala, and His478His variants of the PPARG2 gene were not associated with type 2 diabetes mellitus. However, the 2-loci analyses showed that, in the presence of Pro/Pro genotype of the Pro12Ala variant, the -1279G/A promoter variant showed increased susceptibility to type 2 diabetes mellitus (odds ratio, 2.092; 95% confidence interval, 1.22-3.59; P = .008), whereas in the presence of 12Ala allele, the -1279G/A showed a protective effect against type 2 diabetes mellitus (odds ratio, 0.270; 95% confidence interval, 0.15-0.49; P < .0001). The 3-loci haplotype analysis showed that the A-Ala-T (-1279G/A-Pro12Ala-His478His) haplotype was associated with a reduced risk of type 2 diabetes mellitus (P < .0001). Although our data indicate that the PPARG2 gene variants, independently, have no association with type 2 diabetes mellitus, the 2-loci genotype analysis involving -1279G/A and Pro12Ala variants and the 3-loci haplotype analysis have shown a significant association with type 2 diabetes mellitus in this South Indian population. (C) 2010 Elsevier Inc. All rights reserved.

Solution of MDPS using simulation-based value iteration

This article proposes a three-timescale simulation based algorithm for solution of infinite horizon Markov Decision Processes (MDPs). We assume a finite state space and discounted cost criterion and adopt the value iteration approach. An approximation of the Dynamic Programming operator T is applied to the value function iterates. This 'approximate' operator is implemented using three timescales, the slowest of which updates the value function iterates. On the middle timescale we perform a gradient search over the feasible action set of each state using Simultaneous Perturbation Stochastic Approximation (SPSA) gradient estimates, thus finding the minimizing action in T. On the fastest timescale, the 'critic' estimates, over which the gradient search is performed, are obtained. A sketch of convergence explaining the dynamics of the algorithm using associated ODEs is also presented. Numerical experiments on rate based flow control on a bottleneck node using a continuous-time queueing model are performed using the proposed algorithm. The results obtained are verified against classical value iteration where the feasible set is suitably discretized. Over such a discretized setting, a variant of the algorithm of [12] is compared and the proposed algorithm is found to converge faster.

Optimal threshold policies for admission control in communication networks via discrete parameter stochastic approximation

The problem of admission control of packets in communication networks is studied in the continuous time queueing framework under different classes of service and delayed information feedback. We develop and use a variant of a simulation based two timescale simultaneous perturbation stochastic approximation (SPSA) algorithm for finding an optimal feedback policy within the class of threshold type policies. Even though SPSA has originally been designed for continuous parameter optimization, its variant for the discrete parameter case is seen to work well. We give a proof of the hypothesis needed to show convergence of the algorithm on our setting along with a sketch of the convergence analysis. Extensive numerical experiments with the algorithm are illustrated for different parameter specifications. In particular, we study the effect of feedback delays on the system performance.

Detection of multiple source locations using a glowworm metaphor with applications to collective robotics

This paper presents a glowworm swarm based algorithm that finds solutions to optimization of multiple optima continuous functions. The algorithm is a variant of a well known ant-colony optimization (ACO) technique, but with several significant modifications. Similar to how each moving region in the ACO technique is associated with a pheromone value, the agents in our algorithm carry a luminescence quantity along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luminescence and have a circular sensor range. The glowworms depend on a local-decision domain to compute their movements. Simulations demonstrate the efficacy of the proposed glowworm based algorithm in capturing multiple optima of a multimodal function. The above optimization scenario solves problems where a collection of autonomous robots is used to form a mobile sensor network. In particular, we address the problem of detecting multiple sources of a general nutrient profile that is distributed spatially on a two dimensional workspace using multiple robots.

Action of N-bromosuccinimide on sperm whale myoglobin

Previously, it was reported from this laboratory that the heme groups of hemoglobin are “buried” within globin at pH 4.0 and not dissociated, on the basis of the obiligatory requirement of urea for the reaction of N-bromosuccinimide with the heme groups of hemoglobin at pH4.0, and also on the basis of the “normalization” of the spectrum of hemoglobin at this pH in the presence of urea or sucrose. In the present study, it has been shown that the behaviour of sperm whale myoglobin with respect to its reaction with N-bromosuccinimide and with respect to spectral “normalization” in urea or sucrose are essentially similar to that of hemoglobin. It has also been demonstrated that the spectral “normalization” obtained with crystalline hemin is not identical with that obtained with either hemoglobin or myoglobin. The bearing of the results of the present study on the earlier work on hemoglobin is indicated.