Methylenetetrahydrofolate reductase gene polymorphisms and risk of acute lymphoblastic leukemia in children

Methylenetetrahydrofolate reductase (MTHFR) is a critical enzyme in folate metabolism and is involved in DNA synthesis, DNA repair and DNA methylation. Genetic polymorphisms of this enzyme have been shown to impact several diseases, including cancer. Leukemias are malignancies arising from rapidly proliferating hematopoietic cells having great requirement of DNA synthesis. This case-control study was undertaken to analyze the association of the MTHFR gene polymorphisms 677 C"T and 1298 A"C and the risk of acute lymphoblastic leukemia in children. Materials and Methods: Eighty-six patients aged below 15 years with a confirmed diagnosis of acute lymphoblastic leukemia (ALL) and 99 matched controls were taken for this study. Analysis of the polymorphisms was done using the polymerase chain reaction -restriction fragment length polymorphism (PCR-RFLP) method. Results: Frequency of MTHFR 677 CC and CT were 85.9% and 14.1% in the controls, and 84.9% and 15.1% in the cases. The 'T' allele frequency was 7% and 7.5% in cases and controls respectively. The frequency of MTHFR 1298 AA, AC, and CC were 28.3%, 55.6% and 16.1% for controls and 23.3%, 59.3% and 17.4% for cases respectively. The 'C' allele frequency for 1298 A→C was 43.9% and 47% respectively for controls and cases. The odds ratio (OR) for C677T was 1.08 (95% CI 0.48- 2.45, p = 0.851) and OR for A1298C was 1.29(95% CI 0.65-2.29, p = 0.46) and OR for 1298 CC was 1.31 (95% CI 0.53-3.26, p =0.56). The OR for the combined heterozygous status (677 CT and 1298 AC) was 1.94 (95% CI 0.58 -6.52, p = 0.286). Conclusion: The prevalence of 'T' allele for 677 MTHFR polymorphism was low in the population studied. There was no association between MTHFR 677 C→T and 1298 A→C gene polymorphisms and risk of ALL, which may be due to the small sample size.

Angel Investing in Finland: An Analysis Based on Agency Theory and the Incomplete Contracting Theory

Wealthy individuals - business angels who invest a share of their net worth in entrepreneurial ventures - form an essential part of an informal venture capital market that can secure funding for entrepreneurial ventures. In Finland, business angels represent an untapped pool of capital that can contribute to fostering entrepreneurial development. In addition, business angels can bridge knowledge gaps in new business ventures by means of making their human capital available. This study has two objectives. The first is to gain an understanding of the characteristics and investment behaviour of Finnish business angels. The strongest focus here is on the due diligence procedures and their involvement post investment. The second objective is to assess whether agency theory and the incomplete contacting theory are useful theoretical lenses in the arena of business angels. To achieve the second objective, this study investigates i) how risk is mitigated in the investment process, ii) how uncertainty influences the comprehensiveness of due diligence as well as iii) how control is allocated post investment. Research hypotheses are derived from assumptions underlying agency theory and the incomplete contacting theory. The data for this study comprise interviews with 53 business angels. In terms of sample size this is the largest on Finnish business angels. The research hypotheses in this study are tested using regression analysis. This study suggests that the Finnish informal venture capital market appears to be comprised of a limited number of business angels whose style of investing much resembles their formal counterparts’. Much focus is placed on managing risks prior to making the investment by strong selectiveness and by a relatively comprehensive due diligence. The involvement is rarely on a day-to-day basis and many business angels seem to see board membership as a more suitable alternative than involvement in the operations of an entrepreneurial venture. The uncertainty involved does not seem to drive an increase in due diligence. On the contrary, it would appear that due diligence is more rigorous in safer later stage investments and when the business angels have considerable previous experience as investors. Finnish business angels’ involvement post investment is best explained by their degree of ownership in the entrepreneurial venture. It seems that when investors feel they are sufficiently rewarded, in terms of an adequate equity stake, they are willing to involve themselves actively in their investments. The lack of support for a relationship between increased uncertainty and the comprehensiveness of due diligence may partly be explained by an increasing trend towards portfolio diversification. This is triggered by a taxation system that favours investments through investment companies rather than direct investments. Many business angels appear to have substituted a specialization strategy that builds on reducing uncertainty for a diversification strategy that builds on reducing firm specific (idiosyncratic) risk by holding shares in ventures whose returns are not expected to exhibit a strong positive correlation.

Molecular Caches: A caching structure for dynamic creation of application-specific Heterogeneous cache regions

CMPs enable simultaneous execution of multiple applications on the same platforms that share cache resources. Diversity in the cache access patterns of these simultaneously executing applications can potentially trigger inter-application interference, leading to cache pollution. Whereas a large cache can ameliorate this problem, the issues of larger power consumption with increasing cache size, amplified at sub-100nm technologies, makes this solution prohibitive. In this paper in order to address the issues relating to power-aware performance of caches, we propose a caching structure that addresses the following: 1. Definition of application-specific cache partitions as an aggregation of caching units (molecules). The parameters of each molecule namely size, associativity and line size are chosen so that the power consumed by it and access time are optimal for the given technology. 2. Application-Specific resizing of cache partitions with variable and adaptive associativity per cache line, way size and variable line size. 3. A replacement policy that is transparent to the partition in terms of size, heterogeneity in associativity and line size. Through simulation studies we establish the superiority of molecular cache (caches built as aggregations of molecules) that offers a 29% power advantage over that of an equivalently performing traditional cache.

Suomalaisen alkuperäiskarjan liha – kuluttajien osto- ja maksuhalukkuus

Tutkielman tavoitteena on selvittää suomalaisen alkuperäiskarjan lihan potentiaalista kysyntää. Alkuperäiskarjan lihan erikoistuotemarkkinat voivat auttaa pitämään uhanalaiset, kotimaiset karjarodut tuotantokäytössä. Näin ollen erikoistuotemarkkinat voivat auttaa arvokkaiden suomalaisten eläingeenivarojen säilyttämisessä. Koska alkuperäiskarjan lihan tuotannon kannattavuus riippuu lihasta saatavasta lisähinnasta, tutkimuksen tavoitteena on myös tutkia, millainen kuluttajien maksuhalukkuus alkuperäiskarjan lihasta on verrattuna tavanomaiseen lihaan. Tutkimusaineisto kerättiin Maa- ja elintarviketalouden tutkimuskeskuksen ja Kuluttajatutkimuskeskuksen suunnittelemalla kyselytutkimuksella keväällä 2010. Tutkimuksessa käytettiin ehdollisen käyttäytymisen ja ehdollisen arvottamisen menetelmiä ja sen otoskoko on 1623. Kuluttajien ostohalukkuutta ja siihen vaikuttavia tekijöitä tutkittiin sekä binäärisen että ordinaalisen regression malleilla. Kuluttajien maksuhalukkuutta alkuperäiskarjan lihasta ja siihen vaikuttavia tekijöitä tutkittiin grouped data -mallin avulla. Malleissa käytettiin selittävinä muuttujina sosioekonomisten muuttujien lisäksi kuluttajien asenteita ja käyttäytymistä kuvaavia muuttujia. Tutkielman tulosten mukaan jopa 86 % vastaajista ostaisi alkuperäiskarjan lihaa, jos sitä olisi tarjolla kaupoissa. Ostohalukkuutta lisää muun muassa, jos vastaajalla on alle 18-vuotiaita lapsia ja vastaaja arvostaa lähellä tuotettua, paikallista ruokaa sekä ympäristöystävällisyyttä. Miehet ostaisivat alkuperäiskarjan lihaa todennäköisemmin kuin naiset. Suurin osa vastaajista ostaisi alkuperäiskarjan lihaa, jos se olisi samanhintaista kuin tavanomainen liha, mutta noin neljäsosa (23,5 %) vastaajista olisi valmis maksamaan alkuperäiskarjan lihasta korkeampaa hintaa kuin tavanomaisesta lihasta. Maksuhalukkuuteen vaikuttivat positiivisesti muun muassa kuuluminen ympäristöjärjestöön ja korkea tulotaso. Negatiivisesti vaikutti puolestaan esimerkiksi se, että vastaaja on nainen. Keskimääräinen maksuhalukkuus alkuperäiskarjan lihasta oli 6,25 % korkeampi kuin tavanomaisesta lihasta. Maksuhalukkuus alkuperäiskarjan lihasta oli selvästi yhteydessä siihen, kuinka usein vastaaja olisi halukas ostamaan sitä. Maksuhalukkuus oli korkein niillä vastaajilla, jotka haluaisivat ostaa lihaa säännöllisesti.

Paradigms in Statistical Inference for Finite Populations; Up to the 1950s

Modern sample surveys started to spread after statistician at the U.S. Bureau of the Census in the 1940s had developed a sampling design for the Current Population Survey (CPS). A significant factor was also that digital computers became available for statisticians. In the beginning of 1950s, the theory was documented in textbooks on survey sampling. This thesis is about the development of the statistical inference for sample surveys. For the first time the idea of statistical inference was enunciated by a French scientist, P. S. Laplace. In 1781, he published a plan for a partial investigation in which he determined the sample size needed to reach the desired accuracy in estimation. The plan was based on Laplace s Principle of Inverse Probability and on his derivation of the Central Limit Theorem. They were published in a memoir in 1774 which is one of the origins of statistical inference. Laplace s inference model was based on Bernoulli trials and binominal probabilities. He assumed that populations were changing constantly. It was depicted by assuming a priori distributions for parameters. Laplace s inference model dominated statistical thinking for a century. Sample selection in Laplace s investigations was purposive. In 1894 in the International Statistical Institute meeting, Norwegian Anders Kiaer presented the idea of the Representative Method to draw samples. Its idea was that the sample would be a miniature of the population. It is still prevailing. The virtues of random sampling were known but practical problems of sample selection and data collection hindered its use. Arhtur Bowley realized the potentials of Kiaer s method and in the beginning of the 20th century carried out several surveys in the UK. He also developed the theory of statistical inference for finite populations. It was based on Laplace s inference model. R. A. Fisher contributions in the 1920 s constitute a watershed in the statistical science He revolutionized the theory of statistics. In addition, he introduced a new statistical inference model which is still the prevailing paradigm. The essential idea is to draw repeatedly samples from the same population and the assumption that population parameters are constants. Fisher s theory did not include a priori probabilities. Jerzy Neyman adopted Fisher s inference model and applied it to finite populations with the difference that Neyman s inference model does not include any assumptions of the distributions of the study variables. Applying Fisher s fiducial argument he developed the theory for confidence intervals. Neyman s last contribution to survey sampling presented a theory for double sampling. This gave the central idea for statisticians at the U.S. Census Bureau to develop the complex survey design for the CPS. Important criterion was to have a method in which the costs of data collection were acceptable, and which provided approximately equal interviewer workloads, besides sufficient accuracy in estimation.

Effects of gender, and SLCO1B1 and CYP7A1 polymorphisms on plasma bile acids in humans and the pharmacokinetics of therapeutic ursodeoxycholic acid

Bile acids are important steroid-derived molecules essential for fat absorption in the small intestine. They are produced in the liver and secreted into the bile. Bile acids are transported by bile flow to the small intestine, where they aid the digestion of lipids. Most bile acids are reabsorbed in the small intestine and return to the liver through the portal vein. The whole recycling process is referred to as the enterohepatic circulation, during which only a small amount of bile acids are removed from the body via faeces. The enterohepatic circulation of bile acids involves the delicate coordination of a number of bile acid transporters expressed in the liver and the small intestine. Organic anion transporting polypeptide 1B1 (OATP1B1), encoded by the solute carrier organic anion transporter family, member 1B1 (SLCO1B1) gene, mediates the sodium independent hepatocellular uptake of bile acids. Two common SNPs in the SLCO1B1 gene are well known to affect the transport activity of OATP1B1. Moreover, bile acid synthesis is an important elimination route for cholesterol. Cholesterol 7α-hydroxylase (CYP7A1) is the rate-limiting enzyme of bile acid production. The aim of this thesis was to investigate the effects of SLCO1B1 polymorphism on the fasting plasma levels of individual endogenous bile acids and a bile acid synthesis marker, and the pharmacokinetics of exogenously administered ursodeoxycholic acid (UDCA). Furthermore, the effects of CYP7A1 genetic polymorphism and gender on the fasting plasma concentrations of individual endogenous bile acids and the bile acid synthesis marker were evaluated. Firstly, a high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for the determination of bile acids was developed (Study I). A retrospective study examined the effects of SLCO1B1 genetic polymorphism on the fasting plasma concentrations of individual bile acids and a bile acid synthesis marker in 65 healthy subjects (Study II). In another retrospective study with 143 healthy individuals, the effects of CYP7A1 genetic polymorphism and gender as well as SLCO1B1 polymorphism on the fasting plasma levels of individual bile acids and the bile acid synthesis marker were investigated (Study III). The effects of SLCO1B1 polymorphism on the pharmacokinetics of exogenously administered UDCA were evaluated in a prospective genotype panel study including 27 healthy volunteers (Study IV). A robust, sensitive and simple HPLC-MS/MS method was developed for the simultaneous determination of 16 individual bile acids in human plasma. The method validation parameters for all the analytes met the requirements of the FDA (Food and Drug Administration) bioanalytical guidelines. This HPLC-MS/MS method was applied in Studies II-IV. In Study II, the fasting plasma concentrations of several bile acids and the bile acid synthesis marker seemed to be affected by SLCO1B1 genetic polymorphism, but these findings were not replicated in Study III with a larger sample size. Moreover, SLCO1B1 polymorphism had no effect on the pharmacokinetic parameters of exogenously administered UDCA. Furthermore, no consistent association was observed between CYP7A1 genetic polymorphism and the fasting plasma concentrations of individual bile acids or the bile acid synthesis marker. In contrast, gender had a major effect on the fasting plasma concentrations of several bile acids and also total bile acids. In conclusion, gender, but not SLCO1B1 or CYP7A1 polymorphisms, has a major effect on the fasting plasma concentrations of individual bile acids. Moreover, the common genetic polymorphism of CYP7A1 is unlikely to influence the activity of CYP7A1 under normal physiological conditions. OATP1B1 does not play an important role in the in vivo disposition of exogenously administered UDCA.

Time scales for transitions between free-energy minima of a dense hard-sphere system

Time scales associated with activated transitions between glassy metastable states of a free-energy functional appropriate for a dense hard-sphere system are calculated by using a new Monte Carlo method for the local density variables. In particular, we calculate the time the system, initially placed in a shallow glassy minimum of the free-energy, spends in the neighborhood of this minimum before making a transition to the basin of attraction of another free-energy minimum. This time scale is found to increase as the average density is increased. We find a crossover density near which this time scale increases very sharply and becomes longer than the longest times accessible in our simulation. This time scale does not show any evidence of increasing with sample size

Cyclic Prefix Based Cooperative Sequential Spectrum Sensing Algorithms for OFDM

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user is using Orthogonal Frequency Division Multiplexing (OFDM). For this we develop cooperative sequential detection algorithms that use the autocorrelation property of cyclic prefix (CP) used in OFDM systems. We study the effect of timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. We also modify the detector to mitigate the effects of these impairments. The performance of the proposed algorithms is studied via simulations. We show that sequential detection can significantly improve the performance over a fixed sample size detector.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

A Randomized Algorithm for Large Scale Support Vector Learning

We propose a randomized algorithm for large scale SVM learning which solves the problem by iterating over random subsets of the data. Crucial to the algorithm for scalability is the size of the subsets chosen. In the context of text classification we show that, by using ideas from random projections, a sample size of O(log n) can be used to obtain a solution which is close to the optimal with a high probability. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up SVM learners, without loss in accuracy. 1

Molecular Epidemiology of HIV-1 Subtypes in India: Origin and Evolutionary History of the Predominant Subtype C

Background: India has the third largest HIV-1 epidemic with 2.4 million infected individuals. Molecular epidemiological analysis has identified the predominance of HIV-1 subtype C (HIV-1C). However, the previous reports have been limited by sample size, and uneven geographical distribution. The introduction of HIV-1C in India remains uncertain due to this lack of structured studies. To fill the gap, we characterised the distribution pattern of HIV-1 subtypes in India based on data collection from nationwide clinical cohorts between 2007 and 2011. We also reconstructed the time to the most recent common ancestor (tMRCA) of the predominant HIV-1C strains. Methodology/Principal Findings: Blood samples were collected from 168 HIV-1 seropositive subjects from 7 different states. HIV-1 subtypes were determined using two or three genes, gag, pol, and env using several methods. Bayesian coalescent-based approach was used to reconstruct the time of introduction and population growth patterns of the Indian HIV-1C. For the first time, a high prevalence (10%) of unique recombinant forms (BC and A1C) was observed when two or three genes were used instead of one gene (p<0.01; p = 0.02, respectively). The tMRCA of Indian HIV-1C was estimated using the three viral genes, ranged from 1967 (gag) to 1974 (env). Pol-gene analysis was considered to provide the most reliable estimate 1971, (95% CI: 1965-1976)]. The population growth pattern revealed an initial slow growth phase in the mid-1970s, an exponential phase through the 1980s, and a stationary phase since the early 1990s. Conclusions/Significance: The Indian HIV-1C epidemic originated around 40 years ago from a single or few genetically related African lineages, and since then largely evolved independently. The effective population size in the country has been broadly stable since the 1990s. The evolving viral epidemic, as indicated by the increase of recombinant strains, warrants a need for continued molecular surveillance to guide efficient disease intervention strategies.

Multi-script and multi-oriented text localization from scene images

This paper describes a new method of color text localization from generic scene images containing text of different scripts and with arbitrary orientations. A representative set of colors is first identified using the edge information to initiate an unsupervised clustering algorithm. Text components are identified from each color layer using a combination of a support vector machine and a neural network classifier trained on a set of low-level features derived from the geometric, boundary, stroke and gradient information. Experiments on camera-captured images that contain variable fonts, size, color, irregular layout, non-uniform illumination and multiple scripts illustrate the robustness of the method. The proposed method yields precision and recall of 0.8 and 0.86 respectively on a database of 100 images. The method is also compared with others in the literature using the ICDAR 2003 robust reading competition dataset.

Strength and Deformation Characteristics of Fly Ash Mixed with Randomly Distributed Plastic Waste

In order to explore the potential use of fly ash and plastic waste in bulk quantities in civil engineering applications, it is necessary to understand the behavior of fly ash and fly ash mixed with plastic waste. These materials are considered as wastes and in this study, it is shown that combination of fly ash and plastic waste is very useful. In this regard, various tests such as classification tests, unconfined compressive strength and compressibility tests, consolidated undrained tests, and California bearing ratio tests were conducted. The results indicated that the inclusion of plastic waste in fly ash is effective in improving the engineering properties of fly ash in terms of compressive strength, shear strength parameters, and CBR values. In order to understand the effect of sample size on the shear strength parameters of fly ash and fly ash mixed with plastic waste, consolidated undrained tests were conducted with sample sizes of 38x76mm and 50x100mm. The results of the tests indicate that the shear strength increases with the increase in sample size. The implication of the use of fly ash mixed with plastic waste in unpaved roads is presented in terms of reduction of carbon print.

Noise Detected NMR Spectroscopy

Spin noise phenomenon was predicted way back in 1946. However, experimental investigations regarding spin noise became possible only recently with major technological improvements in NMR hardware. These experiments have several potential novel applications and also demand refinements in the existing theoretical framework to explain the phenomenon. Elegance of noise spectroscopy in gathering information about the properties of a system lies in the fact that it does not require external perturbation, and the system remains in thermal equilibrium. Spin noise is intrinsic magnetic fluctuations, and both longitudinal and transverse components have been detected independently in many systems. Detection of fluctuating longitudinal magnetization leads to field of Magnetic Resonance Force Microscopy (MRFM) that can efficiently probe very few spins even down to the level of single spin utilizing ultrasensitive cantilevers. Transverse component of spin noise, which can simultaneously monitor different resonances over a given frequency range enabling one to distinguish between different chemical environments, has also received considerable attention, and found many novel applications. These experiments demand a detailed understanding of the underlying spin noise phenomenon in order to perform perturbation-free magnetic resonance and widen the highly promising application area. Detailed investigations of noise magnetization have been performed recently using force microscopy on equilibrium ensemble of paramagnetic alkali atoms. It was observed that random fluctuations generate spontaneous spin coherences which has similar characteristics as generated by macroscopic magnetization of polarized ensemble in terms of precession and relaxation properties. Several other intrinsic properties like g-factors, isotope-abundance ratios, hyperfine splitting, spin coherence lifetimes etc. also have been achieved without having to excite the sample. In contrast to MRFM-approaches, detection of transverse spin noise also offers novel applications, attracting considerable attention. This has unique advantage as different resonances over a given frequency range enable one to distinguish between different chemical environments. Since these noise signatures scale inversely with sample size, these approaches lead to the possibility of non-perturbative magnetic resonance of small systems down to nano-scale. In this review, these different approaches will be highlighted with main emphasis on transverse spin noise investigations.

A rapid method to assess reactive oxygen species in yeast using H2DCF-DA

A protocol to efficiently assess Reactive Oxygen Species (ROS) levels in yeast cells using H2DCF-DA is described here. This method employs lithium acetate to permeate the cell wall, and thus, augments the release of the fluorescent product, dichlorofluorescein from the cells. This protocol obviates the need for both physical and enzymatic lysis methods that are arduous and time consuming. This method is simple, less time consuming and reproducible, especially while dealing with a large sample size. The lithium acetate method gave significantly reproducible and linear results (P < 0.0001), as compared with direct measurement (P = 0.0005), sonication (P = 0.1466) and bead beating (P = 0.0028).