Antigen affinity and antigen dose exert distinct influences on CD4 T-cell differentiation.

Cumulative T-cell receptor signal strength and ensuing T-cell responses are affected by both antigen affinity and antigen dose. Here we examined the distinct contributions of these parameters to CD4 T-cell differentiation during infection. We found that high antigen affinity positively correlates with T helper (Th)1 differentiation at both high and low doses of antigen. In contrast, follicular helper T cell (TFH) effectors are generated after priming with high, intermediate, and low affinity ligand. Unexpectedly, memory T cells generated after priming with very low affinity antigen remain impaired in their ability to generate secondary Th1 effectors, despite being recalled with high affinity antigen. These data challenge the view that only strongly stimulated CD4 T cells are capable of differentiating into the TFH and memory T-cell compartments and reveal that differential strength of stimulation during primary T-cell activation imprints unique and long lasting T-cell differentiation programs.

An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data

1. Few examples of habitat-modelling studies of rare and endangered species exist in the literature, although from a conservation perspective predicting their distribution would prove particularly useful. Paucity of data and lack of valid absences are the probable reasons for this shortcoming. Analytic solutions to accommodate the lack of absence include the ecological niche factor analysis (ENFA) and the use of generalized linear models (GLM) with simulated pseudo-absences. 2. In this study we tested a new approach to generating pseudo-absences, based on a preliminary ENFA habitat suitability (HS) map, for the endangered species Eryngium alpinum. This method of generating pseudo-absences was compared with two others: (i) use of a GLM with pseudo-absences generated totally at random, and (ii) use of an ENFA only. 3. The influence of two different spatial resolutions (i.e. grain) was also assessed for tackling the dilemma of quality (grain) vs. quantity (number of occurrences). Each combination of the three above-mentioned methods with the two grains generated a distinct HS map. 4. Four evaluation measures were used for comparing these HS maps: total deviance explained, best kappa, Gini coefficient and minimal predicted area (MPA). The last is a new evaluation criterion proposed in this study. 5. Results showed that (i) GLM models using ENFA-weighted pseudo-absence provide better results, except for the MPA value, and that (ii) quality (spatial resolution and locational accuracy) of the data appears to be more important than quantity (number of occurrences). Furthermore, the proposed MPA value is suggested as a useful measure of model evaluation when used to complement classical statistical measures. 6. Synthesis and applications. We suggest that the use of ENFA-weighted pseudo-absence is a possible way to enhance the quality of GLM-based potential distribution maps and that data quality (i.e. spatial resolution) prevails over quantity (i.e. number of data). Increased accuracy of potential distribution maps could help to define better suitable areas for species protection and reintroduction.

Improving T2 -weighted imaging at high field through the use of kT -points.

PURPOSE: At high magnetic field strengths (B0 ≥ 3 T), the shorter radiofrequency wavelength produces an inhomogeneous distribution of the transmit magnetic field. This can lead to variable contrast across the brain which is particularly pronounced in T2 -weighted imaging that requires multiple radiofrequency pulses. To obtain T2 -weighted images with uniform contrast throughout the whole brain at 7 T, short (2-3 ms) 3D tailored radiofrequency pulses (kT -points) were integrated into a 3D variable flip angle turbo spin echo sequence. METHODS: The excitation and refocusing "hard" pulses of a variable flip angle turbo spin echo sequence were replaced with kT -point pulses. Spatially resolved extended phase graph simulations and in vivo acquisitions at 7 T, utilizing both single channel and parallel-transmit systems, were used to test different kT -point configurations. RESULTS: Simulations indicated that an extended optimized k-space trajectory ensured a more homogeneous signal throughout images. In vivo experiments showed that high quality T2 -weighted brain images with uniform signal and contrast were obtained at 7 T by using the proposed methodology. CONCLUSION: This work demonstrates that T2 -weighted images devoid of artifacts resulting from B1 (+) inhomogeneity can be obtained at high field through the optimization of extended kT -point pulses. Magn Reson Med 71:1478-1488, 2014. © 2013 Wiley Periodicals, Inc.

Altering α-dystroglycan receptor affinity of LCMV pseudotyped lentivirus yields unique cell and tissue tropism.

BACKGROUND: The envelope glycoprotein of lymphocytic choriomeningitis virus (LCMV) can efficiently pseudotype lentiviral vectors. Some strains of LCMV exploit high affinity interactions with α-dystroglycan (α-DG) to bind to cell surfaces and subsequently fuse in low pH endosomes. LCMV strains with low α-DG affinity utilize an unknown receptor and display unique tissue tropisms. We pseudotyped non-primate feline immunodeficiency virus (FIV) vectors using LCMV derived glycoproteins with high or low affinity to α-DG and evaluated their properties in vitro and in vivo. METHODS: We pseudotyped FIV with the LCMV WE54 strain envelope glycoprotein and also engineered a point mutation in the WE54 envelope glycoprotein (L260F) to diminish α-DG affinity and direct binding to alternate receptors. We hypothesized that this change would alter in vivo tissue tropism and enhance gene transfer to neonatal animals. RESULTS: In mice, hepatic α- and β-DG expression was greatest at the late gestational and neonatal time points. When displayed on the surface of the FIV lentivirus the WE54 L260F mutant glycoprotein bound weakly to immobilized α-DG. Additionally, LCMV WE54 pseudotyped FIV vector transduction was neutralized by pre-incubation with soluble α-DG, while the mutant glycoprotein pseudotyped vector was not. In vivo gene transfer in adult mice with either envelope yielded low transduction efficiencies in hepatocytes following intravenous delivery. In marked contrast, neonatal gene transfer with the LCMV envelopes, and notably with the FIV-L260F vector, conferred abundant liver and lower level cardiomyocyte transduction as detected by luciferase assays, bioluminescent imaging, and β-galactosidase staining. CONCLUSIONS: These results suggest that a developmentally regulated receptor for LCMV is expressed abundantly in neonatal mice. LCMV pseudotyped vectors may have applications for neonatal gene transfer. ABBREVIATIONS: Armstrong 53b (Arm53b); baculovirus Autographa californica GP64 (GP64); charge-coupled device (CCD); dystroglycan (DG); feline immunodeficiency virus (FIV); glycoprotein precursor (GP-C); firefly luciferase (Luc); lymphocytic choriomeningitis virus (LCMV); nuclear targeted β-galactosidase (ntLacZ); optical density (OD); PBS/0.1% (w/v) Tween-20 (PBST); relative light units (RLU); Rous sarcoma virus (RSV); transducing units per milliliter (TU/ml); vesicular stomatitis virus (VSV-G); wheat germ agglutinin (WGA); 50% reduction in binding (C50).

Finite mixture analysis of beauty-contest data using generalised beta distributions

This paper introduces a mixture model based on the beta distribution, without preestablishedmeans and variances, to analyze a large set of Beauty-Contest data obtainedfrom diverse groups of experiments (Bosch-Domenech et al. 2002). This model gives a bettert of the experimental data, and more precision to the hypothesis that a large proportionof individuals follow a common pattern of reasoning, described as iterated best reply (degenerate),than mixture models based on the normal distribution. The analysis shows thatthe means of the distributions across the groups of experiments are pretty stable, while theproportions of choices at dierent levels of reasoning vary across groups.

Decision making techniques with similarity measures and OWA operators

We analyse the use of the ordered weighted average (OWA) in decision-making giving special attention to business and economic decision-making problems. We present several aggregation techniques that are very useful for decision-making such as the Hamming distance, the adequacy coefficient and the index of maximum and minimum level. We suggest a new approach by using immediate weights, that is, by using the weighted average and the OWA operator in the same formulation. We further generalize them by using generalized and quasi-arithmetic means. We also analyse the applicability of the OWA operator in business and economics and we see that we can use it instead of the weighted average. We end the paper with an application in a business multi-person decision-making problem regarding production management

Efficiency of informational transfer in regular and complex networks

We analyze the process of informational exchange through complex networks by measuring network efficiencies. Aiming to study nonclustered systems, we propose a modification of this measure on the local level. We apply this method to an extension of the class of small worlds that includes declustered networks and show that they are locally quite efficient, although their clustering coefficient is practically zero. Unweighted systems with small-world and scale-free topologies are shown to be both globally and locally efficient. Our method is also applied to characterize weighted networks. In particular we examine the properties of underground transportation systems of Madrid and Barcelona and reinterpret the results obtained for the Boston subway network.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation.

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

A cophenetic correlation coefficient for Tocher's method

The objective of this work was to propose a way of using the Tocher's method of clustering to obtain a matrix similar to the cophenetic one obtained for hierarchical methods, which would allow the calculation of a cophenetic correlation. To illustrate the obtention of the proposed cophenetic matrix, we used two dissimilarity matrices - one obtained with the generalized squared Mahalanobis distance and the other with the Euclidean distance - between 17 garlic cultivars, based on six morphological characters. Basically, the proposal for obtaining the cophenetic matrix was to use the average distances within and between clusters, after performing the clustering. A function in R language was proposed to compute the cophenetic matrix for Tocher's method. The empirical distribution of this correlation coefficient was briefly studied. For both dissimilarity measures, the values of cophenetic correlation obtained for the Tocher's method were higher than those obtained with the hierarchical methods (Ward's algorithm and average linkage - UPGMA). Comparisons between the clustering made with the agglomerative hierarchical methods and with the Tocher's method can be performed using a criterion in common: the correlation between matrices of original and cophenetic distances.

Impulse response recovery of linear systems through weighted cumulant slice

Identifiability of the so-called ω-slice algorithm is proven for ARMA linear systems. Although proofs were developed in the past for the simpler cases of MA and AR models, they were not extendible to general exponential linear systems. The results presented in this paper demonstrate a unique feature of the ω-slice method, which is unbiasedness and consistency when order is overdetermined, regardless of the IIR or FIR nature of the underlying system, and numerical robustness.

Multi-analyte detection for biological fluids. Towards continous monitoring of glucose, ionized calcium and pH using a viscometric affinity biosensor.

We present a viscometric affinity biosensor that can potentially allow continuous multi-analyte monitoring in biological fluids like blood or plasma. The sensing principle is based on the detection of viscosity changes of a polymeric solution which has a selective affinity for the analyte of interest. The chemico-mechanical sensor incorporates an actuating piezoelectric diaphragm, a sensing piezoelectric diaphragm and a flow-resisting microchannel for viscosity detection. A free-standing Anodic Alumina Oxide (AAO) porous nano-membrane is used as selective interface. A glucose-sensitive sensor was fabricated and extensively assessed in buffer solution. The sensor reversibility, stability and sensitivity were excellent during at least 65 hours. Results showed also a good degree of stability for a long term measurement (25 days). The sensor behaviour was furthermore tested in fetal bovine serum (FBS). The obtained results for glucose sensing are very promising, indicating that the developed sensor is a candidate for continuous monitoring in biological fluids. Sensitive solutions for ionized calcium and pH are currently under development and should allow multi-analyte sensing in the near future.

Empirical Tests of Asset Pricing Models in Finnish Stock Market

Tämän tutkielman tavoitteena on selvittää mitkä riskitekijät vaikuttavat osakkeiden tuottoihin. Arvopapereina käytetään kuutta portfoliota, jotka ovat jaoteltu markkina-arvon mukaan. Aikaperiodi on vuoden 1987 alusta vuoden 2004 loppuun. Malleina käytetään pääomamarkkinoiden hinnoittelumallia, arbitraasihinnoitteluteoriaa sekä kulutuspohjaista pääomamarkkinoiden hinnoittelumallia. Riskifaktoreina kahteen ensimmäiseen malliin käytetään markkinariskiä sekä makrotaloudellisia riskitekijöitä. Kulutuspohjaiseen pääomamarkkinoiden hinnoinoittelumallissa keskitytään estimoimaan kuluttajien riskitottumuksia sekä diskonttaustekijää, jolla kuluttaja arvostavat tulevaisuuden kulutusta. Tämä työ esittelee momenttiteorian, jolla pystymme estimoimaan lineaarisia sekä epälineaarisia yhtälöitä. Käytämme tätä menetelmää testaamissamme malleissa. Yhteenvetona tuloksista voidaan sanoa, että markkinabeeta onedelleen tärkein riskitekijä, mutta löydämme myös tukea makrotaloudellisille riskitekijöille. Kulutuspohjainen mallimme toimii melko hyvin antaen teoreettisesti hyväksyttäviä arvoja.

Guidelines for irrigation scheduling of banana crop in São Francisco Valley, Brazil. II - Water consumption, crop coefficient, and physiologycal behavior

The water consumption and the crop coefficient of the banana cv. Pacovan were estimated in Petrolina County, northeastern Brazil, in order to establish guidelines to irrigation water management. Evaluations were carried out since planting in January 1999 to the 3rd harvest in September 2001 on a microsprinkler irrigated orchard, with plants spaced in a 3 x 3 m grid. Average daily water consumption was 3.9, 4.0, and 3.3 mm in the 1st, 2nd and 3rd growing seasons, respectively. Crop coefficient values increased from 0.7 (vegetative growth) to 1.1 (flowering). Even with high soil water availability, transpiration was reduced due to high evaporative demand.

Effect of water velocity on the uptake of polychlorinatedd biphenyls (PCBs) by silicone rubber (SR) and low-density polyethylene (LDPE) passive samplers: an assessment of the efficiency of performance reference compounds (PRCs) in river-like flow conditions

One aim of this study is to determine the impact of water velocity on the uptake of indicator polychlorinated biphenyls (iPCBs) by silicone rubber (SR) and low-density polyethylene (LDPE) passive samplers. A second aim is to assess the efficiency of performance reference compounds (PRCs) to correct for the impact of water velocity. SR and LDPE samplers were spiked with 11 or 12 PRCs and exposed for 6 weeks to four different velocities (in the range of 1.6 to 37.7 cm s−1) in river-like flow conditions using a channel system supplied with river water. A relationship between velocity and the uptakewas found for each iPCB and enables to determine expected changes in the uptake due to velocity variations. For both samplers, velocity increases from 2 to 10 cm s−1, 30 cm s−1 (interpolated data) and 100 cm s−1 (extrapolated data) lead to increases of the uptake which do not exceed a factor of 2, 3 and 4.5, respectively. Results also showed that the influence of velocity decreased with increasing the octanol-water coefficient partition (log Kow) of iPCBs when SR is used whereas the opposite effect was observed for LDPE. Time-weighted average (TWA) concentrations of iPCBs in water were calculated from iPCB uptake and PRC release. These calculations were performed using either a single PRC or all the PRCs. The efficiency of PRCs to correct the impact of velocity was assessed by comparing the TWA concentrations obtained at the four tested velocities. For SR, a good agreement was found among the four TWA concentrations with both methods (average RSD b 10%). Also for LDPE, PRCs offered a good correction of the impact of water velocity (average RSD of about 10 to 20%). These results contribute to the process of acceptance of passive sampling in routine regulatory monitoring programs.