COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

An introductory review on gravitational-deformation induced structures, fabrics and modeling

Recent studies have pointed out a similarity between tectonics and slope tectonic-induced structures. Numerous studies have demonstrated that structures and fabrics previously interpreted as of purely geodynamical origin are instead the result of large slope deformation, and this led in the past to erroneous interpretations. Nevertheless, their limit seems not clearly defined, but it is somehow transitional. Some studies point out continuity between failures developing at surface with upper crust movements. In this contribution, the main studies which examine the link between rock structures and slope movements are reviewed. The aspects regarding model and scale of observation are discussed together with the role of pre-existing weaknesses in the rock mass. As slope failures can develop through progressive failure, structures and their changes in time and space can be recognized. Furthermore, recognition of the origin of these structures can help in avoiding misinterpretations of regional geology. This also suggests the importance of integrating different slope movement classifications based on distribution and pattern of deformation and the application of structural geology techniques. A structural geology approach in the landslide community is a tool that can greatly support the hazard quantification and related risks, because most of the physical parameters, which are used for landslide modeling, are derived from geotechnical tests or the emerging geophysical approaches.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Transfer factor for carbon monoxide: a glance behind the scene.

The transfer factor for carbon monoxide (TLCO) is widely used in pulmonary function laboratories because it represents a unique non-invasive window on pulmonary microcirculation. The TLCO is the product of two primary measurements, the alveolar volume (VA) and the CO transfer coefficient (KCO). This test is most informative when VA and KCO are examined, together with their product TLCO. In a normal lung, a low VA due to incomplete expansion is associated with an elevated KCO, resulting in a mildly reduced TLCO. Thus, in case of low VA, a seemingly "normal KCO" must be interpreted as an abnormal gas transfer. The most common clinical conditions associated with an abnormal TLCO are characterised by a limited number of patterns for VA and KCO: incomplete lung expansion, discrete loss of alveolar units, diffuse loss of alveolar units, emphysema, pulmonary vascular disorders, high pulmonary blood volume, alveolar haemorrhage.

Relevé des consultations et des transferts de patients par enquête directe auprès des médecins: méthode d'une enquête, acceptabilité et limites d'interprétation. [Summary of consultations and transfer of patients by a direct survey of physicians: survey methods, acceptability and limits of interpretation].

A survey of medical ambulatory practice was carried out in February-March 1981 in the two Swiss cantons of Vaud and Fribourg (total population: 700,000), in which 205 physicians participated. The methodology used was inspired from the U.S. National Ambulatory Medical Care Survey, the data collection instrument of which was adapted to our conditions; in addition, data were gathered on all referrals prescribed by 154 physicians during two weeks. (The instruments used are presented.) The potential and limits of this type of survey are discussed, as well as the representativity of the participating physicians and of the recorded visits, which are a systematic sample of over 43,000 visits.

Plutonium from above-ground nuclear tests in milk teeth: investigation of placental transfer in children born between 1951 and 1995 in Switzerland.

BACKGROUND: Occupational risks, the present nuclear threat, and the potential danger associated with nuclear power have raised concerns regarding the metabolism of plutonium in pregnant women. OBJECTIVE: We measured plutonium levels in the milk teeth of children born between 1951 and 1995 to assess the potential risk that plutonium incorporated by pregnant women might pose to the radiosensitive tissues of the fetus through placenta transfer. METHODS: We used milk teeth, whose enamel is formed during pregnancy, to investigate the transfer of plutonium from the mother's blood plasma to the fetus. We measured plutonium using sensitive sector field inductively coupled plasma mass spectrometry techniques. We compared our results with those of a previous study on strontium-90 ((90)Sr) released into the atmosphere after nuclear bomb tests. RESULTS: Results show that plutonium activity peaks in the milk teeth of children born about 10 years before the highest recorded levels of plutonium fallout. By contrast, (90)Sr, which is known to cross the placenta barrier, manifests differently in milk teeth, in accordance with (90)Sr fallout deposition as a function of time. CONCLUSIONS: These findings demonstrate that plutonium found in milk teeth is caused by fallout that was inhaled around the time the milk teeth were shed and not from any accumulation during pregnancy through placenta transfer. Thus, plutonium may not represent a radiologic risk for the radiosensitive tissues of the fetus.

Host and invader impact of transfer of the clc genomic island into Pseudomonas aeruginosa PAO1

Genomic islands, large potentially mobile regions of bacterial chromosomes, are a major contributor to bacteria evolution. Here, we investigated the fitness cost and phenotypic differences between the bacterium Pseudomonas aeruginosa PAO1 and a derivative carrying one integrated copy of the clc element, a 103-kb genomic island [and integrative and conjugative element (ICE)] originating in Pseudomonas sp. strain B13 and a close relative of genomic islands found in clinical and environmental isolates of P. aeruginosa. By using a combination of whole genome transcriptome profiling, phenotypic arrays, competition experiments, and biofilm formation studies, only few differences became apparent, such as reduced biofilm growth and fourfold stationary phase repression of genes involved in acetoin metabolism in PAO1 containing the clc element. In contrast, PAO1 carrying the clc element acquired the capacity to grow on 3-chlorobenzoate and 2-aminophenol as sole carbon and energy substrates. No fitness loss >1% was detectable in competition experiments between PAO1 and PAO1 carrying the clc element. The genes from the clc element were not silent in PAO1, and excision was observed, although transfer of clc from PAO1 to other recipient bacteria was reduced by two orders of magnitude. Our results indicate that newly acquired mobile DNA not necessarily invoke an important fitness cost on their host. Absence of immediate detriment to the host may have contributed to the wide distribution of genomic islands like clc in bacterial genomes

Evidence evaluation in fingerprint comparison and automated fingerprint identification systems: modeling between finger variability

In the context of the investigation of the use of automated fingerprint identification systems (AFIS) for the evaluation of fingerprint evidence, the current study presents investigations into the variability of scores from an AFIS system when fingermarks from a known donor are compared to fingerprints that are not from the same source. The ultimate goal is to propose a model, based on likelihood ratios, which allows the evaluation of mark-to-print comparisons. In particular, this model, through its use of AFIS technology, benefits from the possibility of using a large amount of data, as well as from an already built-in proximity measure, the AFIS score. More precisely, the numerator of the LR is obtained from scores issued from comparisons between impressions from the same source and showing the same minutia configuration. The denominator of the LR is obtained by extracting scores from comparisons of the questioned mark with a database of non-matching sources. This paper focuses solely on the assignment of the denominator of the LR. We refer to it by the generic term of between-finger variability. The issues addressed in this paper in relation to between-finger variability are the required sample size, the influence of the finger number and general pattern, as well as that of the number of minutiae included and their configuration on a given finger. Results show that reliable estimation of between-finger variability is feasible with 10,000 scores. These scores should come from the appropriate finger number/general pattern combination as defined by the mark. Furthermore, strategies of obtaining between-finger variability when these elements cannot be conclusively seen on the mark (and its position with respect to other marks for finger number) have been presented. These results immediately allow case-by-case estimation of the between-finger variability in an operational setting.

Modeling stochasticity and robustness in gene regulatory networks.

MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

The long and painful path towards arthroplasty: A qualitative study

Hip or knee arthroplasty is proposed after osteoarthritis or an accident. It is decided after a long path of pain and decrease in the quality of life. This research explores the period of illness until surgery. Twenty-four semi-structured interviews were conducted one month before surgery and a thematic discourse analysis performed. The diversity and complexity of the patient experience, in a commonly performed surgical intervention underlines important topics, requiring attention in order to improve patient preparations and information prior to arthroplasty: information adapted to individual concerns, needs and representations. Psychological and physical acceptance is necessary for integration of the prosthesis.

The cover basement contact beneath the Rawil axial depression (Western Alps) - True amplitude seismic processing, petrophysical properties, and modeling

Since 1986, several near-vertical seismic reflection profiles have been recorded in Switzerland in order to map the deep geologic structure of the Alps. One objective of this endeavour has been to determine the geometries of the autochthonous basement and of the external crystalline massifs, important elements for understanding the geodynamics of the Alpine orogeny. The PNR-20 seismic line W1, located in the Rawil depression of the western Swiss Alps, provides important information on this subject. It extends northward from the `'Penninic front'' across the Helvetic nappes to the Prealps. The crystalline massifs do not outcrop along this profile. Thus, the interpretation of `'near-basement'' reflections has to be constrained by down-dip projections of surface geology, `'true amplitude'' processing, rock physical property studies and modelling. 3-D seismic modelling has been used to evaluate the seismic response of two alternative down-dip projection models. To constrain the interpretation in the southern part of the profile, `'true amplitude'' processing has provided information on the strength of the reflections. Density and velocity measurements on core samples collected up-dip from the region of the seismic line have been used to evaluate reflection coefficients of typical lithologic boundaries in the region. The cover-basement contact itself is not a source of strong reflections, but strong reflections arise from within the overlaying metasedimentary cover sequence, allowing the geometry of the top of the basement to be determined on the basis of `'near-basement'' reflections. The front of the external crystalline massifs is shown to extend beneath the Prealps, about 6 km north of the expected position. A 2-D model whose seismic response shows reflection patterns very similar to the observed is proposed.

Gene transfer of interleukin-18-binding protein attenuates cardiac allograft rejection.

Interleukin (IL) 18 is a potent pro-inflammatory Th1 cytokine that exerts pleiotropic effector functions in both innate and acquired immune responses. Increased IL-18 production during acute rejection has been reported in experimental heart transplantation models and in kidney transplant recipients. IL-18-binding protein (IL-18BP) binds IL-18 with high affinity and neutralizes its biologic activity. We have analyzed the efficacy of an adenoviral vector expressing an IL-18BP-Ig fusion protein in a rat model of heart transplantation. IL-18BP-Ig gene transfer into Fisher (F344) rat donor hearts resulted in prolonged graft survival in Lewis recipients (15.8 +/- 1.4 days vs. 10.3 +/- 2.5 and 10.1 +/- 2.1 days with control virus and buffer solution alone, respectively; P < 0.001). Immunohistochemical analysis revealed decreased intra-graft infiltrates of monocytes/macrophages, CD4(+), CD8alpha(+) and T-cell receptor alphabeta(+) cells after IL-18BP-Ig versus mock gene transfer (P < 0.05). Real-time reverse transcriptase polymerase chain reaction analysis showed decreased cytokine transcripts for the RANTES chemokine and transforming growth factor-beta after IL-18BP-Ig gene transfer (P < 0.05). IL-18BP-Ig gene transfer attenuates inflammatory cell infiltrates and prolongs cardiac allograft survival in rats. These results suggest a contributory role for IL-18 in acute rejection. Further studies aiming at defining the therapeutic potential of IL-18BP are warranted.