Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Cognitive and emotional effects of carotid stenosis.

PRINCIPLES: Patients with carotid artery stenosis (CAS) are at risk of ipsilateral stroke and chronic compromise of cerebral blood flow. It is under debate whether the hypo-perfusion or embolism in CAS is directly related to cognitive impairment. Alternatively, CAS may be a marker for underlying risk factors, which themselves influence cognition. We aimed to determine cognitive performance level and the emotional state of patients with CAS. We hypo-thesised that patients with high grade stenosis, bilateral stenosis, symptomatic patients and/or those with relevant risk factors would suffer impairment of their cognitive performance and emotional state. METHODS: A total of 68 patients with CAS of ≥70% were included in a prospective exploratory study design. All patients underwent structured assessment of executive functions, language, verbal and visual memory, motor speed, anxiety and depression. RESULTS: Significantly more patients with CAS showed cognitive impairments (executive functions, word production, verbal and visual memory, motor speed) and anxiety than expected in a normative sample. Bilateral and symptomatic stenosis was associated with slower processing speed. Cognitive performance and anxiety level were not influenced by the side and the degree of stenosis or the presence of collaterals. Factors associated with less co-gnitive impairment included higher education level, female gender, ambidexterity and treated hypercholesterolemia. CONCLUSIONS: Cognitive impairment and increased level of anxiety are frequent in patients with carotid stenosis. The lack of a correlation between cognitive functioning and degree of stenosis or the presence of collaterals, challenges the view that CAS per se leads to cognitive impairment.

Cerebral perfusion CT: Current state of the art : P44

Purpose: The aim of this educational poster is to introduce the technical principles of cerebral perfusion CT and to provide examples of its clinical applications and potential limitations in the everyday emergency practice. Methods and materials: Cerebral perfusion CT is a well established investigatory tool for many vascular and parenchymal brain dysfunctions. CT perfusion maps allow a semiquantitative assessment of cerebral perfusion. Results: Currently, cerebral perfusion CT has a pivotal role in differentiating reversible from irreversible ischemic parenchymal insult besides its integral role in grading vasospasm after subarachnoid hemorrhage. Furthermore, cerebral perfusion CT can be coupled to acetazolamide administration in order to assess the cerebrovascular reserve capacity before performing extra-/intra-cranial bypass surgery in patients with cerebral vascular insufficiency. Cerebral perfusion CT can also identify diffuse abnormalities of cerebral perfusion in children with traumatic brain injury showing a low initial GCS in order to predict the final outcome regarding the late occurrence of irreversible parenchymal damage. Cerebral Perfusion CT is also able to detect focal parenchymal perfusion abnormalities in acute epileptic seizures. Conclusion: Cerebral perfusion CT can be integrated in the management of many vascular, traumatic and functional disorders of the brain.

How family caregivers' medical and moral assumptions influence decision making for patients in the vegetative state: a qualitative interview study.

Background Decisions on limiting life-sustaining treatment for patients in the vegetative state (VS) are emotionally and morally challenging. In Germany, doctors have to discuss, together with the legal surrogate (often a family member), whether the proposed treatment is in accordance with the patient's will. However, it is unknown whether family members of the patient in the VS actually base their decisions on the patient's wishes. Objective To examine the role of advance directives, orally expressed wishes, or the presumed will of patients in a VS for family caregivers' decisions on life-sustaining treatment. Methods and sample A qualitative interview study with 14 next of kin of patients in a VS in a long-term care setting was conducted; 13 participants were the patient's legal surrogates. Interviews were analysed according to qualitative content analysis. Results The majority of family caregivers said that they were aware of aforementioned wishes of the patient that could be applied to the VS condition, but did not base their decisions primarily on these wishes. They gave three reasons for this: (a) the expectation of clinical improvement, (b) the caregivers' definition of life-sustaining treatments and (c) the moral obligation not to harm the patient. If the patient's wishes were not known or not revealed, the caregivers interpreted a will to live into the patient's survival and non-verbal behaviour. Conclusions Whether or not prior treatment wishes of patients in a VS are respected depends on their applicability, and also on the medical assumptions and moral attitudes of the surrogates. We recommend repeated communication, support for the caregivers and advance care planning.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.

Spin-labeling coronary MR angiography with steady-state free precession and radial k-space sampling: initial results in healthy volunteers.

The purpose of this study was to prospectively compare free-breathing navigator-gated cardiac-triggered three-dimensional steady-state free precession (SSFP) spin-labeling coronary magnetic resonance (MR) angiography performed by using Cartesian k-space sampling with that performed by using radial k-space sampling. A new dedicated placement of the two-dimensional selective labeling pulse and an individually adjusted labeling delay time approved by the institutional review board were used. In 14 volunteers (eight men, six women; mean age, 28.8 years) who gave informed consent, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel sharpness, vessel length, and subjective image quality were investigated. Differences between groups were analyzed with nonparametric tests (Wilcoxon, Pearson chi2). Radial imaging, as compared with Cartesian imaging, resulted in a significant reduction in the severity of motion artifacts, as well as an increase in SNR (26.9 vs 12.0, P < .05) in the coronary arteries and CNR (23.1 vs 8.8, P < .05) between the coronary arteries and the myocardium. A tendency toward improved vessel sharpness and vessel length was also found with radial imaging. Radial SSFP imaging is a promising technique for spin-labeling coronary MR angiography.

Steady-state expression of self-regulated genes.

MOTIVATION: Regulatory gene networks contain generic modules such as feedback loops that are essential for the regulation of many biological functions. The study of the stochastic mechanisms of gene regulation is instrumental for the understanding of how cells maintain their expression at levels commensurate with their biological role, as well as to engineer gene expression switches of appropriate behavior. The lack of precise knowledge on the steady-state distribution of gene expression requires the use of Gillespie algorithms and Monte-Carlo approximations. METHODOLOGY: In this study, we provide new exact formulas and efficient numerical algorithms for computing/modeling the steady-state of a class of self-regulated genes, and we use it to model/compute the stochastic expression of a gene of interest in an engineered network introduced in mammalian cells. The behavior of the genetic network is then analyzed experimentally in living cells. RESULTS: Stochastic models often reveal counter-intuitive experimental behaviors, and we find that this genetic architecture displays a unimodal behavior in mammalian cells, which was unexpected given its known bimodal response in unicellular organisms. We provide a molecular rationale for this behavior, and we implement it in the mathematical picture to explain the experimental results obtained from this network.

Steady-state brain glucose transport kinetics re-evaluated with a four-state conformational model.

Glucose supply from blood to brain occurs through facilitative transporter proteins. A near linear relation between brain and plasma glucose has been experimentally determined and described by a reversible model of enzyme kinetics. A conformational four-state exchange model accounting for trans-acceleration and asymmetry of the carrier was included in a recently developed multi-compartmental model of glucose transport. Based on this model, we demonstrate that brain glucose (G(brain)) as function of plasma glucose (G(plasma)) can be described by a single analytical equation namely comprising three kinetic compartments: blood, endothelial cells and brain. Transport was described by four parameters: apparent half saturation constant K(t), apparent maximum rate constant T(max), glucose consumption rate CMR(glc), and the iso-inhibition constant K(ii) that suggests G(brain) as inhibitor of the isomerisation of the unloaded carrier. Previous published data, where G(brain) was quantified as a function of plasma glucose by either biochemical methods or NMR spectroscopy, were used to determine the aforementioned kinetic parameters. Glucose transport was characterized by K(t) ranging from 1.5 to 3.5 mM, T(max)/CMR(glc) from 4.6 to 5.6, and K(ii) from 51 to 149 mM. It was noteworthy that K(t) was on the order of a few mM, as previously determined from the reversible model. The conformational four-state exchange model of glucose transport into the brain includes both efflux and transport inhibition by G(brain), predicting that G(brain) eventually approaches a maximum concentration. However, since K(ii) largely exceeds G(plasma), iso-inhibition is unlikely to be of substantial importance for plasma glucose below 25 mM. As a consequence, the reversible model can account for most experimental observations under euglycaemia and moderate cases of hypo- and hyperglycaemia.

Navigator-gated coronary magnetic resonance angiography using steady-state-free-precession: comparison to standard T2-prepared gradient-echo and spiral imaging.

RATIONALE AND OBJECTIVES: Recent developments of magnetic resonance imaging enabled free-breathing coronary MRA (cMRA) using steady-state-free-precession (SSFP) for endogenous contrast. The purpose of this study was a systematic comparison of SSFP cMRA with standard T2-prepared gradient-echo and spiral cMRA. METHODS: Navigator-gated free-breathing T2-prepared SSFP-, T2-prepared gradient-echo- and T2-prepared spiral cMRA was performed in 18 healthy swine (45-68 kg body-weight). Image quality was investigated subjectively and signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and vessel sharpness were compared. RESULTS: SSFP cMRA allowed for high quality cMRA during free breathing with substantial improvements in SNR, CNR and vessel sharpness when compared with standard T2-prepared gradient-echo imaging. Spiral imaging demonstrated the highest SNR while image quality score and vessel definition was best for SSFP imaging. CONCLUSION: Navigator-gated free-breathing T2-prepared SSFP cMRA is a promising new imaging approach for high signal and high contrast imaging of the coronary arteries with improved vessel border definition.

Free-breathing renal magnetic resonance angiography with steady-state free-precession and slab-selective spin inversion combined with radial k-space sampling and water-selective excitation.

The impact of radial k-space sampling and water-selective excitation on a novel navigator-gated cardiac-triggered slab-selective inversion prepared 3D steady-state free-precession (SSFP) renal MR angiography (MRA) sequence was investigated. Renal MRA was performed on a 1.5-T MR system using three inversion prepared SSFP approaches: Cartesian (TR/TE: 5.7/2.8 ms, FA: 85 degrees), radial (TR/TE: 5.5/2.7 ms, FA: 85 degrees) SSFP, and radial SSFP combined with water-selective excitation (TR/TE: 9.9/4.9 ms, FA: 85 degrees). Radial data acquisition lead to significantly reduced motion artifacts (P < 0.05). SNR and CNR were best using Cartesian SSFP (P < 0.05). Vessel sharpness and vessel length were comparable in all sequences. The addition of a water-selective excitation could not improve image quality. In conclusion, radial k-space sampling reduces motion artifacts significantly in slab-selective inversion prepared renal MRA, while SNR and CNR are decreased. The addition of water-selective excitation could not improve the lower CNR in radial scanning.