Purpose
Diffusion weighted MRI imaging (DWI) is often subject to low signal‐to‐noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but ...these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document.
Methods
The proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter‐scan intensity normalization; susceptibility‐, eddy current‐, and motion‐induced artifact correction; and slice‐wise signal drop‐out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness‐of‐fit and fractional anisotropy analyses.
Results
Raw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility‐, eddy current‐, and motion‐induced artifacts; imputed signal‐lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file‐type conversion errors and was shown to be effective on externally available datasets.
Conclusions
The proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI‐focused software packages with intuitive QA.
Inferring objects and their relationships from an image in the form of a scene graph is useful in many applications at the intersection of vision and language. We consider a challenging problem of ...compositional generalization that emerges in this task due to a long tail data distribution. Current scene graph generation models are trained on a tiny fraction of the distribution corresponding to the most frequent compositions, e.g. <cup, on, table>. However, test images might contain zero- and few-shot compositions of objects and relationships, e.g. <cup, on, surfboard>. Despite each of the object categories and the predicate (e.g. 'on') being frequent in the training data, the models often fail to properly understand such unseen or rare compositions. To improve generalization, it is natural to attempt increasing the diversity of the training distribution. However, in the graph domain this is non-trivial. To that end, we propose a method to synthesize rare yet plausible scene graphs by perturbing real ones. We then propose and empirically study a model based on conditional generative adversarial networks (GANs) that allows us to generate visual features of perturbed scene graphs and learn from them in a joint fashion. When evaluated on the Visual Genome dataset, our approach yields marginal, but consistent improvements in zero- and few-shot metrics. We analyze the limitations of our approach indicating promising directions for future research.
Amyloidosis is a relatively rare human disease caused by the deposition of abnormal protein fibres in the extracellular space of various tissues, impairing their normal function. Proteomic analysis ...of patients' biopsies, developed by Dogan and colleagues at the Mayo Clinic, has become crucial for clinical diagnosis and for identifying the amyloid type. Currently, the proteomic approach is routinely used at National Amyloidosis Centre (NAC, London, UK) and Istituto di Tecnologie Biomediche-Consiglio Nazionale delle Ricerche (ITB-CNR, Milan, Italy). Both centres are members of the European Proteomics Amyloid Network (EPAN), which was established with the aim of sharing and discussing best practice in the application of amyloid proteomics. One of the EPAN's activities was to evaluate the quality and the confidence of the results achieved using different software and algorithms for protein identification. In this paper, we report the comparison of proteomics results obtained by sharing NAC proteomics data with the ITB-CNR centre. Mass spectrometric raw data were analysed using different software platforms including Mascot, Scaffold, Proteome Discoverer, Sequest and bespoke algorithms developed for an accurate and immediate amyloid protein identification. Our study showed a high concordance of the obtained results, suggesting a good accuracy of the different bioinformatics tools used in the respective centres. In conclusion, inter-centre data exchange is a worthwhile approach for testing and validating the performance of software platforms and the accuracy of results, and is particularly important where the proteomics data contribute to a clinical diagnosis.
The mechanisms underlying transthyretin‐related amyloidosis in vivo remain unclear. The abundance of the 49–127 transthyretin fragment in ex vivo deposits suggests that a proteolytic cleavage has a ...crucial role in destabilizing the tetramer and releasing the highly amyloidogenic 49–127 truncated protomer. Here, we investigate the mechanism of cleavage and release of the 49–127 fragment from the prototypic S52P variant, and we show that the proteolysis/fibrillogenesis pathway is common to several amyloidogenic variants of transthyretin and requires the action of biomechanical forces provided by the shear stress of physiological fluid flow. Crucially, the non‐amyloidogenic and protective T119M variant is neither cleaved nor generates fibrils under these conditions. We propose that a mechano‐enzymatic mechanism mediates transthyretin amyloid fibrillogenesis in vivo. This may be particularly important in the heart where shear stress is greatest; indeed, the 49–127 transthyretin fragment is particularly abundant in cardiac amyloid. Finally, we show that existing transthyretin stabilizers, including tafamidis, inhibit proteolysis‐mediated transthyretin fibrillogenesis with different efficiency in different variants; however, inhibition is complete only when both binding sites are occupied.
Synopsis
Selective proteolysis of TTR generates a highly amyloidogenic truncated protomer. Shear stress generated by turbulent flow of physiological fluids makes TTR susceptible to cleavage. This mechanism may play a crucial role in the development of cardiac TTR amyloidosis, and offers new therapeutic targets for treating the disease.
Shear forces are required to prime proteolysis of wild‐type and other variant TTRs and to release the amyloidogenic fragment.
These forces are present in the heart, offering an explanation for tissue specificity in cardiac TTR amyloidosis.
TTR stabilizers, currently used to treat amyloidosis, can inhibit this mechanism; however, their efficacy differs for each variant.
Selective proteolysis of TTR generates a highly amyloidogenic truncated protomer. Shear stress generated by turbulent flow of physiological fluids makes TTR susceptible to cleavage. This mechanism may play a crucial role in the development of cardiac TTR amyloidosis, and offers new therapeutic targets for treating the disease.
We report the morphological classification of 3727 galaxies from the Galaxy and Mass Assembly survey with M
r
< −17.4 mag and in the redshift range 0.025 < z < 0.06 (2.1 × 105 Mpc3) into E, S0-Sa, ...SB0-SBa, Sab-Scd, SBab-SBcd, Sd-Irr and little blue spheroid classes. Approximately 70 per cent of galaxies in our sample are disc-dominated systems, with the remaining ∼30 per cent spheroid dominated. We establish the robustness of our classifications, and use them to derive morphological-type luminosity functions and luminosity densities in the ugrizYJHK passbands, improving on prior studies that split by global colour or light profile shape alone. We find that the total galaxy luminosity function is best described by a double-Schechter function while the constituent morphological-type luminosity functions are well described by a single-Schechter function. These data are also used to derive the star formation rate densities for each Hubble class, and the attenuated and unattenuated (corrected for dust) cosmic spectral energy distributions, i.e. the instantaneous energy production budget. While the observed optical/near-IR energy budget is dominated 58:42 by galaxies with a significant spheroidal component, the actual energy production rate is reversed, i.e. the combined disc-dominated populations generate ∼1.3 times as much energy as the spheroid-dominated populations. On the grandest scale, this implies that chemical evolution in the local Universe is currently largely confined to mid-type spiral classes like our Milky Way.
Dissociation of the native transthyretin (TTR) tetramer is widely accepted as the critical step in TTR amyloid fibrillogenesis. It is modelled by exposure of the protein to non-physiological low pH ...in vitro and is inhibited by small molecule compounds, such as the drug tafamidis. We have recently identified a new mechano-enzymatic pathway of TTR fibrillogenesis in vitro, catalysed by selective proteolytic cleavage, which produces a high yield of genuine amyloid fibrils. This pathway is efficiently inhibited only by ligands that occupy both binding sites in TTR. Tolcapone, which is bound with similar high affinity in both TTR binding sites without the usual negative cooperativity, is therefore of interest. Here we show that TTR fibrillogenesis by the mechano-enzymatic pathway is indeed more potently inhibited by tolcapone than by tafamidis but neither, even in large molar excess, completely prevents amyloid fibril formation. In contrast, mds84, the prototype of our previously reported bivalent ligand TTR 'superstabiliser' family, is notably more potent than the monovalent ligands and we show here that this apparently reflects the critical additional interactions of its linker within the TTR central channel. Our findings have major implications for therapeutic approaches in TTR amyloidosis.
Accumulation of amyloid fibrils in the viscera and connective tissues causes systemic amyloidosis, which is responsible for about one in a thousand deaths in developed countries. Localized amyloid ...can also have serious consequences; for example, cerebral amyloid angiopathy is an important cause of haemorrhagic stroke. The clinical presentations of amyloidosis are extremely diverse and the diagnosis is rarely made before significant organ damage is present. There is therefore a major unmet need for therapy that safely promotes the clearance of established amyloid deposits. Over 20 different amyloid fibril proteins are responsible for different forms of clinically significant amyloidosis and treatments that substantially reduce the abundance of the respective amyloid fibril precursor proteins can arrest amyloid accumulation. Unfortunately, control of fibril-protein production is not possible in some forms of amyloidosis and in others it is often slow and hazardous. There is no therapy that directly targets amyloid deposits for enhanced clearance. However, all amyloid deposits contain the normal, non-fibrillar plasma glycoprotein, serum amyloid P component (SAP). Here we show that administration of anti-human-SAP antibodies to mice with amyloid deposits containing human SAP triggers a potent, complement-dependent, macrophage-derived giant cell reaction that swiftly removes massive visceral amyloid deposits without adverse effects. Anti-SAP-antibody treatment is clinically feasible because circulating human SAP can be depleted in patients by the bis-d-proline compound CPHPC, thereby enabling injected anti-SAP antibodies to reach residual SAP in the amyloid deposits. The unprecedented capacity of this novel combined therapy to eliminate amyloid deposits should be applicable to all forms of systemic and local amyloidosis.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
How would you describe the features that a deep learning model composes if you were restricted to measuring observable behaviours? Explainable artificial intelligence (XAI) methods rely on privileged ...access to model architecture and parameters that is not always feasible for most users, practitioners and regulators. Inspired by cognitive psychology research on humans, we present a case for measuring response times (RTs) of a forward pass using only the system clock as a technique for XAI. Our method applies to the growing class of models that use input‐adaptive dynamic inference and we also extend our approach to standard models that are converted to dynamic inference post hoc. The experimental logic is simple: If the researcher can contrive a stimulus set where variability among input features is tightly controlled, differences in RT for those inputs can be attributed to the way the model composes those features. First, we show that RT is sensitive to difficult, complex features by comparing RTs from ObjectNet and ImageNet. Next, we make specific a priori predictions about RT for features present in the SCEGRAM data set, where object recognition in humans depends on complex intrascene object‐object relationships. Finally, we show that RT profiles bear specificity for class identity and therefore the features that define classes. These results cast light on the model's feature space without opening the black box.
Lung cancer is the leading cause of cancer-related death worldwide. Computer-aided diagnosis (CAD) systems have shown significant promise in recent years for facilitating the effective detection and ...classification of abnormal lung nodules in computed tomography (CT) scans. While hand-engineered radiomic features have been traditionally used for lung cancer prediction, there have been significant recent successes achieving state-of-the-art results in the area of discovery radiomics. Here, radiomic sequencers comprising of highly discriminative radiomic features are discovered directly from archival medical data. However, the interpretation of predictions made using such radiomic sequencers remains a challenge. A novel end-to-end interpretable discovery radiomics-driven lung cancer prediction pipeline has been designed, build, and tested. The radiomic sequencer being discovered possesses a deep architecture comprised of stacked interpretable sequencing cells (SISC). The SISC architecture is shown to outperform previous approaches while providing more insight in to its decision making process. The SISC radiomic sequencer is able to achieve state-of-the-art results in lung cancer prediction, and also offers prediction interpretability in the form of critical response maps. The critical response maps are useful for not only validating the predictions of the proposed SISC radiomic sequencer, but also provide improved radiologist-machine collaboration for effective diagnosis.
Renal biopsy series from North America suggest that leucocyte chemotactic factor 2 (ALECT2) amyloid is the third most common type of renal amyloid. We report the first case series from a European ...Centre of prevalence, clinical presentation and diagnostic findings in ALECT2 amyloidosis and report long-term patient and renal outcomes for the first time.
We studied the clinical features, diagnostic investigations and the outcome of all patients with ALECT2 amyloidosis followed systematically at the UK National Amyloidosis Centre (NAC) between 1994 and 2015.
Twenty-four patients, all non-Caucasian, were diagnosed with ALECT2 amyloidosis representing 1.3% of all patients referred to the NAC with biopsy-proved renal amyloid. Diagnosis was made at median age of 62 years, usually from renal histology; immunohistochemical staining was definitive for ALECT2 fibril type. Median estimated glomerular filtration rate (GFR) at diagnosis was 33 mL/min/1.73 m2 and median proteinuria was 0.5 g/24 h. Hepatic amyloid was evident on serum amyloid P component (SAP) scintigraphy in 11/24 cases but was not associated with significant derangement of liver function. No patient had evidence of cardiac amyloidosis or amyloid neuropathy. Median follow-up was 4.8 (range 0.5-15.2) years, during which four patients died and four progressed to end-stage renal disease. The mean rate of GFR loss was 4.2 (range 0.5-9.6) mL/min/year and median estimated renal survival from diagnosis was 8.2 years. Serial SAP scans revealed little or no change in total body amyloid burden.
ALECT2 amyloidosis is a relatively benign type of renal amyloid, associated with a slow GFR decline, which is reliably diagnosed on renal histology. Neither the molecular basis nor the factors underlying the apparent restriction of ALECT2 amyloidosis to non-Caucasian populations have been determined.
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