The costs and benefits of estimating T-1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling

Multi-post-labeling-delay pseudo-continuous arterial spin labeling (multi-PLD PCASL) allows for absolute quantification of the cerebral blood flow (CBF) as well as the arterial transit time (ATT). Estimating these perfusion parameters from multi-PLD PCASL data is a non-linear inverse problem, which is commonly tackled by fitting the single-compartment model (SCM) for PCASL, with CBF and ATT as free parameters. The longitudinal relaxation time of tissue T-1t is an important parameter in this model, as it governs the decay of the perfusion signal entirely upon entry in the imaging voxel. Conventionally, T-1t is fixed to a population average. This approach can cause CBF quantification errors, as T-1t can vary significantly inter- and intra-subject. This study compares the impact on CBF quantification, in terms of accuracy and precision, of either fixing T-1t, the conventional approach, or estimating it alongside CBF and ATT. It is shown that the conventional approach can cause a significant bias in CBF. Indeed, simulation experiments reveal that if T-1t is fixed to a value that is 10% off its true value, this may already result in a bias of 15% in CBF. On the other hand, as is shown by both simulation and real data experiments, estimating T-1t along with CBF and ATT results in a loss of CBF precision of the same order, even if the experiment design is optimized for the latter estimation problem. Simulation experiments suggest that an optimal balance between accuracy and precision of CBF estimation from multi-PLD PCASL data can be expected when using the two-parameter estimator with a fixed T-1t value between population averages of T-1t and the longitudinal relaxation time of blood T-1b

Hybrid system modeling and identification of cell biology systems: perspectives and challenges

Abstract: Some perspectives and challenges in research on the crossing of system biology, hybrid system formulations and system identification are outlined. Emphasis is given on the hybrid, gray box modeling of interactions between the different abstract levels of organization typically recognized in (micro-)organisms, its associated identification problem and optimal experimental (input) design

DELTA-MRI: Direct deformation Estimation from LongiTudinally Acquired k-space data

Longitudinal MRI is an important diagnostic imaging tool for evaluating the effects of treatment and monitoring disease progression. However, MRI, and particularly longitudinal MRI, is known to be time consuming. To accelerate imaging, compressed sensing (CS) theory has been applied to exploit sparsity, both on single image as on image sequence level. State-of-the-art CS methods however, are generally focused on image reconstruction, and consider analysis (e.g., alignment, change detection) as a post-processing step. In this study, we propose DELTA-MRI, a novel framework to estimate longitudinal image changes {\it directly} from a reference image and subsequently acquired, strongly sub-sampled MRI k-space data. In contrast to state-of-the-art longitudinal CS based imaging, our method avoids the conventional multi-step process of image reconstruction of subsequent images, image alignment, and deformation vector field computation. Instead, the set of follow-up images, along with motion and deformation vector fields that describe their relation to the reference image, are estimated in one go. Experiments show that DELTA-MRI performs significantly better than the state-of-the-art in terms of the normalized reconstruction error.Comment: 5 pages, 4 figures, Submitted to ISBI 202

Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling

Purpose To determine whether sacrificing part of the scan time of pseudo-continuous arterial spin labeling (PCASL) for measurement of the labeling efficiency and blood T1 is beneficial in terms of CBF quantification reliability. Methods In a simulation framework, 5-minute scan protocols with different scan time divisions between PCASL data acquisition and supporting measurements were evaluated in terms of CBF estimation variability across both noise and ground truth parameter realizations taken from the general population distribution. The entire simulation experiment was repeated for a single-post-labeling delay (PLD), multi-PLD, and free-lunch time-encoded (te-FL) PCASL acquisition strategy. Furthermore, a real data study was designed for preliminary validation. Results For the considered population statistics, measuring the labeling efficiency and the blood T1 proved beneficial in terms of CBF estimation variability for any distribution of the 5-minute scan time compared to only acquiring ASL data. Compared to single-PLD PCASL without support measurements as recommended in the consensus statement, a 26%, 33%, and 42% reduction in relative CBF estimation variability was found for optimal combinations of supporting measurements with single-PLD, free-lunch, and multi-PLD PCASL data acquisition, respectively. The benefit of taking the individual variation of blood T1 into account was also demonstrated in the real data experiment. Conclusions Spending time to measure the labeling efficiency and the blood T1 instead of acquiring more averages of the PCASL data proves to be advisable for robust CBF quantification in the general population

Lithographically fabricated nanopore-based electrodes for electrochemistry

We report a new technique for fabricating electrodes for electrochemical applications with lateral dimensions in the range 15−200 nm and a reproducible, well-defined geometry. This technique allows determining the electrode size by electron microscopy prior to electrochemical measurements and without contamination of the metal electrode. We measured the diffusion-limited current with stepped-current voltammetry and showed that its dependence on electrode size can be quantitatively understood if the known geometry of the electrodes is explicitly taken into account

Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis

Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis

Genetic association studies have identified 21 loci associated with atopic dermatitis risk predominantly in populations of European ancestry. To identify further susceptibility loci for this common, complex skin disease, we performed a meta-analysis of >15 million genetic variants in 21,399 cases and 95,464 controls from populations of European, African, Japanese and Latino ancestry, followed by replication in 32,059 cases and 228,628 controls from 18 studies. We identified ten new risk loci, bringing the total number of known atopic dermatitis risk loci to 31 (with new secondary signals at four of these loci). Notably, the new loci include candidate genes with roles in the regulation of innate host defenses and T cell function, underscoring the important contribution of (auto)immune mechanisms to atopic dermatitis pathogenesis

Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88

The filamentous fungus Aspergillus niger is widely exploited by the fermentation industry for the production of enzymes and organic acids, particularly citric acid. We sequenced the 33.9-megabase genome of A. niger CBS 513.88, the ancestor of currently used enzyme production strains. A high level of synteny was observed with other aspergilli sequenced. Strong function predictions were made for 6,506 of the 14,165 open reading frames identified. A detailed description of the components of the protein secretion pathway was made and striking differences in the hydrolytic enzyme spectra of aspergilli were observed. A reconstructed metabolic network comprising 1,069 unique reactions illustrates the versatile metabolism of A. niger. Noteworthy is the large number of major facilitator superfamily transporters and fungal zinc binuclear cluster transcription factors, and the presence of putative gene clusters for fumonisin and ochratoxin A synthesis

Model-Based Optical Resolution,” in

Abstract — This paper considers the two-point resolution of imaging systems from the viewpoint of model fitting theory. Earlier results have been extended to include (partially) coherent sources of unknown intensity. Furthermore, it is shown how the probability of resolution can be computed. This probability can be used to compare the performance of different imaging systems. Index Terms—Bifurcation, image resolution, image restoration, modeling, nonlinear estimation, parameter estimation. I