Optical Scattering Measurements of Laser Induced Damage in the Intraocular Lens

This study optically determines whether the amount of light scatter due to laser-induced damage to the intraocular lens (IOL) is significant in relation to normal straylight values in the human eye. Two IOLs with laser-induced damage were extracted from two donor eyes. Each IOL had 15 pits and/or cracks. The surface area of each pit was measured using a microscope. For 6 pits per intraocular lens the point spread function (PSF) in terms of straylight was measured and the total straylight for all 15 pits was estimated. The damage in the IOLs was scored as mild/moderate. The total damaged surface areas, for a 3.5 mm pupil, in the two IOLs were 0.13% (0.0127 mm2) and 0.66% (0.064 mm2), respectively. The angular dependence of the straylight caused by the damage was similar to that of the normal PSF. The total average contribution to straylight was log(s) = −0.82 and −0.42, much less than the straylight value of the normal eye

Evaluation of a website providing information on regional health care services for patients with rheumatoid arthritis: an observational study

Studies on the effectiveness of information provision for patients with arthritis through the Internet are scarce. This study aimed to describe rheumatoid arthritis (RA) patients’ knowledge and information needs before and after launching a website providing information on regional health care services for patients with rheumatic conditions. The intervention consisted of a weekly updated website comprising practical information on regional health care services for patients with arthritis. In addition, patients were offered information leaflets and an information meeting. Before (T1) and 24 months after (T2) the website was launched, a random sample of 400 RA patients filled in a questionnaire regarding knowledge and information need (scores 0–18) about accessibility and contents of 18 regional health care services. Two hundred and fifty-one patients returned the questionnaire (response rate 63%) at T1 and 200 patients (50%) at T2, respectively, with 160 paired observations (112 females (70%), mean age 60.4 years (SD 9.9)). The total score for insufficient knowledge about contents decreased from 9.3 (SD 4.9) to 8.5 (SD 4.8; p = 0.03) and for accessibility from 8.6 (SD 4.7) to 8.4 (SD 4.9; p = 0.59). Total score for information need about contents decreased from 4.2 (SD 4.5) to 1.9 (SD 2.9; p < 0.01) and for accessibility from 3.6 (SD 4.5) to 1.4 (SD 2.4; p < 0.01) (paired t-tests)

Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation

In this paper, we present the optimization formulation of the Kalman filtering and smoothing problems, and use this perspective to develop a variety of extensions and applications. We first formulate classic Kalman smoothing as a least squares problem, highlight special structure, and show that the classic filtering and smoothing algorithms are equivalent to a particular algorithm for solving this problem. Once this equivalence is established, we present extensions of Kalman smoothing to systems with nonlinear process and measurement models, systems with linear and nonlinear inequality constraints, systems with outliers in the measurements or sudden changes in the state, and systems where the sparsity of the state sequence must be accounted for. All extensions preserve the computational efficiency of the classic algorithms, and most of the extensions are illustrated with numerical examples, which are part of an open source Kalman smoothing Matlab/Octave package.Comment: 46 pages, 11 figure

Atomic spin chain realization of a model for quantum criticality

The ability to manipulate single atoms has opened up the door to constructing interesting and useful quantum structures from the ground up. On the one hand, nanoscale arrangements of magnetic atoms are at the heart of future quantum computing and spintronic devices; on the other hand, they can be used as fundamental building blocks for the realization of textbook many-body quantum models, illustrating key concepts such as quantum phase transitions, topological order or frustration. Step-by-step assembly promises an interesting handle on the emergence of quantum collective behavior as one goes from one, to few, to many constituents. To achieve this, one must however maintain the ability to tune and measure local properties as the system size increases. Here, we use low-temperature scanning tunneling microscopy to construct arrays of magnetic atoms on a surface, designed to behave like spin-1/2 XXZ Heisenberg chains in a transverse field, for which a quantum phase transition from an antiferromagnetic to a paramagnetic phase is predicted in the thermodynamic limit. Site-resolved measurements on these finite size realizations reveal a number of sudden ground state changes when the field approaches the critical value, each corresponding to a new domain wall entering the chains. We observe that these state crossings become closer for longer chains, indicating the onset of critical behavior. Our results present opportunities for further studies on quantum behavior of many-body systems, as a function of their size and structural complexity.Comment: published online on 18 Apr 2016 in Nature Physic

Galectins as immunoregulators during infectious processes: from microbial invasion to the resolution of the disease

Recent evidence has implicated galectins, a family of evolutionarily conserved carbohydrate-binding proteins, as regulators of immune cell homeostasis and host-pathogen interactions. Galectins operate at different levels of innate and adaptive immune responses, by modulating cell survival and cell activation or by influencing the Th1/Th2 cytokine balance. Furthermore, galectins may contribute to host-pathogen recognition and may serve as receptors for specific interactions of pathogens with their insect vectors. Here we will explore the influence of galectins in immunological processes relevant to microbial infection and will summarize exciting recent work related to the specific interactions between galectins and their glycoconjugate ligands as critical determinants of pathogen recognition. Understanding the role of galectin-sugar interactions during the course of microbial infections might contribute to defining novel targets for disease prevention and immune intervention.Fil: Rabinovich, Gabriel Adrián. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Gruppi, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentin

DISCO-SCA and Properly Applied GSVD as Swinging Methods to Find Common and Distinctive Processes

BACKGROUND: In systems biology it is common to obtain for the same set of biological entities information from multiple sources. Examples include expression data for the same set of orthologous genes screened in different organisms and data on the same set of culture samples obtained with different high-throughput techniques. A major challenge is to find the important biological processes underlying the data and to disentangle therein processes common to all data sources and processes distinctive for a specific source. Recently, two promising simultaneous data integration methods have been proposed to attain this goal, namely generalized singular value decomposition (GSVD) and simultaneous component analysis with rotation to common and distinctive components (DISCO-SCA). RESULTS: Both theoretical analyses and applications to biologically relevant data show that: (1) straightforward applications of GSVD yield unsatisfactory results, (2) DISCO-SCA performs well, (3) provided proper pre-processing and algorithmic adaptations, GSVD reaches a performance level similar to that of DISCO-SCA, and (4) DISCO-SCA is directly generalizable to more than two data sources. The biological relevance of DISCO-SCA is illustrated with two applications. First, in a setting of comparative genomics, it is shown that DISCO-SCA recovers a common theme of cell cycle progression and a yeast-specific response to pheromones. The biological annotation was obtained by applying Gene Set Enrichment Analysis in an appropriate way. Second, in an application of DISCO-SCA to metabolomics data for Escherichia coli obtained with two different chemical analysis platforms, it is illustrated that the metabolites involved in some of the biological processes underlying the data are detected by one of the two platforms only; therefore, platforms for microbial metabolomics should be tailored to the biological question. CONCLUSIONS: Both DISCO-SCA and properly applied GSVD are promising integrative methods for finding common and distinctive processes in multisource data. Open source code for both methods is provided

A role for CETP TaqIB polymorphism in determining susceptibility to atrial fibrillation: a nested case control study

BACKGROUND: Studies investigating the genetic and environmental characteristics of atrial fibrillation (AF) may provide new insights in the complex development of AF. We aimed to investigate the association between several environmental factors and loci of candidate genes, which might be related to the presence of AF. METHODS: A nested case-control study within the PREVEND cohort was conducted. Standard 12 lead electrocardiograms were recorded and AF was defined according to Minnesota codes. For every case, an age and gender matched control was selected from the same population (n = 194). In addition to logistic regression analyses, the multifactor-dimensionality reduction (MDR) method and interaction entropy graphs were used for the evaluation of gene-gene and gene-environment interactions. Polymorphisms in genes from the Renin-angiotensin, Bradykinin and CETP systems were included. RESULTS: Subjects with AF had a higher prevalence of electrocardiographic left ventricular hypertrophy, ischemic heart disease, hypertension, renal dysfunction, elevated levels of C-reactive protein (CRP) and increased urinary albumin excretion as compared to controls. The polymorphisms of the Renin-angiotensin system and Bradykinin gene did not show a significant association with AF (p > 0.05). The TaqIB polymorphism of the CETP gene was significantly associated with the presence of AF (p < 0.05). Using the MDR method, the best genotype-phenotype models included the combination of micro- or macroalbuminuria and CETP TaqIB polymorphism, CRP >3 mg/L and CETP TaqIB polymorphism, renal dysfunction and the CETP TaqIB polymorphism, and ischemic heart disease and CETP TaqIB polymorphism (1000 fold permutation testing, P < 0.05). Interaction entropy graph showed that the combination of albuminuria and CETP TaqIB polymorphism removed the most entropy. CONCLUSION: CETP TaqIB polymorphism is significantly associated with the presence of AF in the context of micro- or macroalbuminuria, elevated C-reactive protein, renal dysfunction, and ischemic heart disease

The Connectome Visualization Utility: Software for Visualization of Human Brain Networks

In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples