Objective
Evaluate and compare the image quality and acceptance of a full MBIR algorithm to that of an earlier full IR hybrid algorithm and filtered back projection (FBP).
Methods
Acquisitions were ...performed with a 320 detector-row CT scanner with seven different dose levels. Images were reconstructed with three algorithms: FBP, full hybrid iterative reconstruction (HIR), and a full model-based iterative reconstruction algorithm (full MBIR). The sensitometry, spatial resolution, image texture, and low-contrast detectability of these algorithms were compared. Subjective analysis of low-contrast detectability was performed. Ten radiologists answered a questionnaire on image quality and confidence in full MBIR images in clinical practice.
Results
The contrast-to-noise ratio of full MBIR was significantly higher than in the other algorithms (
p
< 0.0015). The spatial resolution was also higher with full MBIR at high frequencies (> 0.3 lp/mm). Full MBIR at low dose levels led to better low-contrast detectability and more inserts being identified with a higher confidence (
p
< 0.0001). Full MBIR was associated with a change in image texture compared to HIR and FBP. Eighty percent of radiologists judged general appearance and texture of full MBIR images worse than HIR. Moreover, compared with HIR, for 50% of radiologists, the diagnostic confidence on full MBIR images was worse. Questionnaire reliability was considered acceptable (Cronbach alpha 0.7).
Conclusion
Compared to conventional iterative reconstruction algorithms, full MBMIR presented a higher image quality and low-contrast detectability and a worse acceptance among radiologists.
Key Points
• Full MBIR used led to an overall improvement in image quality compared with FBP and HIR.
• Full MBIR leads to image texture change which reduces the confidence in these images among radiologists.
• Awareness of the image texture change and improved quality of full MBIR reconstructed images could improve the acceptance of this technique in clinical practice.
In this contribution we introduce LoopStructural, a new open-source 3D
geological modelling Python package (http://www.github.com/Loop3d/LoopStructural, last access: 15 June 2021).
LoopStructural ...provides a generic API for 3D geological modelling applications harnessing
the core Python scientific libraries pandas, numpy and scipy. Six different interpolation
algorithms, including three discrete interpolators and 3 polynomial trend
interpolators, can be used from the same model design. This means that
different interpolation algorithms can be mixed and matched within a
geological model allowing for different geological objects, e.g. different
conformable foliations, fault surfaces and unconformities to be modelled using
different algorithms. Geological features are incorporated into the model
using a time-aware approach, where the most recent features are modelled
first and used to constrain the geometries of the older features. For
example, we use a fault frame for characterising the geometry of the fault
surface and apply each fault sequentially to the faulted surfaces. In this
contribution we use LoopStructural to produce synthetic proof of concepts models and a
86 km × 52 km model of the Flinders Ranges in South Australia using map2loop.
We introduce a new method for implicit structural modeling. The main developments in this paper are the new regularization operators we propose by extending inherent properties of the classic ...one-dimensional discrete second derivative operator to higher dimensions. The proposed regularization operators discretize naturally on the Cartesian grid using finite differences, owing to the highly symmetric nature of the Cartesian grid. Furthermore, the proposed regularization operators do not require any special treatment on boundary nodes, and their generalization to higher dimensions is straightforward. As a result, the proposed method has the advantage of being simple to implement. Numerical examples show that the proposed method is robust and numerically efficient.
Nitric oxide (NO) is an important signaling molecule in multicellular organisms. Most animals produce NO from L-arginine via a family of dedicated enzymes known as NO synthases (NOSes). A rare ...exception is the roundworm Caenorhabditis elegans, which lacks its own NOS. However, in its natural environment, C. elegans feeds on Bacilli that possess functional NOS. Here, we demonstrate that bacterially derived NO enhances C. elegans longevity and stress resistance via a defined group of genes that function under the dual control of HSF-1 and DAF-16 transcription factors. Our work provides an example of interspecies signaling by a small molecule and illustrates the lifelong value of commensal bacteria to their host.
Display omitted
► NO produced by gut bacteria diffuses and acts within C. elegance tissues ► NO increases C. elegans lifespan in a DAF-16- and HSF-1-dependent manner ► NO induces heat shock response and thermotolerance in C. elegans ► Transcriptomic analysis reveals the NO regulon under dual control of DAF-16/HSF-1
Nitric oxide produced by B. subtilis, a part of the natural diet of C. elegans, diffuses into the worm’s tissues and activates genes that modulate stress resistance and longevity via the transcription factors HSF-1 and DAF-16.
A high-sugar diet has been associated with reduced lifespan in organisms ranging from worms to mammals. However, the mechanisms underlying the harmful effects of glucose are poorly understood. Here ...we establish a causative relationship between endogenous glucose storage in the form of glycogen, resistance to oxidative stress and organismal aging in Caenorhabditis elegans. We find that glycogen accumulated on high dietary glucose limits C. elegans longevity. Glucose released from glycogen and used for NADPH/glutathione reduction renders nematodes and human hepatocytes more resistant against oxidative stress. Exposure to low levels of oxidants or genetic inhibition of glycogen synthase depletes glycogen stores and extends the lifespan of animals fed a high glucose diet in an AMPK-dependent manner. Moreover, glycogen interferes with low insulin signalling and accelerates aging of long-lived daf-2 worms fed a high glucose diet. Considering its extensive evolutionary conservation, our results suggest that glycogen metabolism might also have a role in mammalian aging.
Physical oncology recognizes tissue stiffness mediated by activation of cancer-associated fibroblasts (CAF) and extracellular matrix remodeling as an active modulator of tumorigenesis, treatment ...resistance, and clinical outcome. Cholangiocarcinoma (CCA) is a highly aggressive and chemoresistant desmoplastic cancer enriched in CAF. CCA’s stroma mechanical properties are considered responsible for its chemoresistant character. To normalize tumor mechanics, we propose a physical strategy based on remotely light-activated nanohyperthermia to modulate the tumor microenvironment. In this study, we report the use of multifunctional iron oxide nanoflowers decorated with gold nanoparticles (GIONF) as efficient nanoheaters to achieve complete tumor regression following three sessions of mild hyperthermia. The preferential uptake of GIONF by CAF allowed targeting this cell population, which resulted in a significant early reduction of tumor stiffness followed by tumor regression. In conclusion, our study highlights a spatially and temporally controlled physical strategy, GIONF-mediated photothermal therapy to deplete CAF and normalize the tumor mechanics that may apply to desmoplastic cancer and CCA treatment.
Glutathione (GSH) is the most abundant cellular antioxidant. As reactive oxygen species (ROS) are widely believed to promote aging and age-related diseases, and antioxidants can neutralize ROS, it ...follows that GSH and its precursor, N-acetyl cysteine (NAC), are among the most popular dietary supplements. However, the long- term effects of GSH or NAC on healthy animals have not been thoroughly investigated. We employed C. elegans to demonstrate that chronic administration of GSH or NAC to young or aged animals perturbs global gene expression, inhibits skn-1-mediated transcription, and accelerates aging. In contrast, limiting the consumption of dietary thiols, including those naturally derived from the microbiota, extended lifespan. Pharmacological GSH restriction activates the unfolded protein response and increases proteotoxic stress resistance in worms and human cells. It is thus advantageous for healthy individuals to avoid excessive dietary antioxidants and, instead, rely on intrinsic GSH biosynthesis, which is fine-tuned to match the cellular redox status and to promote homeostatic ROS signaling.
Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer ...language has relative strong points, making some languages better suited than others for a given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets.
The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent and native use of Bioconductor from Python, without one having to know the R language and with only a small community of translators required to know both. To demonstrate this, we have implemented such Python representations for key infrastructure packages in Bioconductor, letting a Python programmer handle annotation data, microarray data, and next-generation sequencing data.
Bioconductor is now not solely reserved to R users. Building a Python application using Bioconductor functionality can be done just like if Bioconductor was a Python package. Moreover, similar principles can be applied to other languages and libraries. Our Python package is available at: http://pypi.python.org/pypi/rpy2-bioconductor-extensions/.
Motivation: The processing of the Affymetrix GeneChip data has been a recent focus for data analysts. Alternatives to the original procedure have been proposed and some of these new methods are ...widely used. Results: The affy package is an R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. The package is currently in its second release, affy provides the user with extreme flexibility when carrying out an analysis and make it possible to access and manipulate probe intensity data. In this paper, we present the main classes and functions in the package and demonstrate how they can be used to process probe-level data. We also demonstrate the importance of probe-level analysis when using the Affymetrix GeneChip platform.
PDF
