A projection-domain iterative algorithm for metal artifact reduction by minimizing the total-variation norm and the negative-pixel energy

Metal objects in X-ray computed tomography can cause severe artifacts. The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods. This paper proposes a projection-domain algorithm to reduce the metal artifacts. In this algorithm, the unknowns are the metal-affected projections, while the objective function is set up in the image domain. The data fidelity term is not utilized in the objective function. The objective function of the proposed algorithm consists of two terms: the total variation of the metal-removed image and the energy of the negative-valued pixels in the image. After the metal-affected projections are modified, the final image is reconstructed via the filtered backprojection algorithm. The feasibility of the proposed algorithm has been verified by real experimental data.

The MAP4 Projection Domain Accelerates Hypoxia-Induced Mitophagy Disruption through LIR Motif in Cardiomyocytes

Previously, we and other investigators have demonstrated that phosphorylated microtubule-associated protein 4 (p-MAP4) impacts myocardial hypertrophy and ischemic heart failure. However, the detailed mechanism behind this remains under elucidated. Published studies have suggested that impaired mitophagy contributes to hypoxia-induced myocardial damage, hence the involvement of p-MAP4 in mitophagy in cardiomyocytes was investigated. The results herein revealed that there was increased degradation of mitochondria, accumulated mitophagosomes and disrupted autophagic flux in both neonatal and adult ones of MAP4-knockin (KI) mice. This indicated that p-MAP4 persistently degraded mitochondria through activating mitophagy. Next, Tom70 was found as the importer of p-MAP4 in the context of mitochondrial translocation. And, the LC3-interacting region (LIR) motif (47–50aa) caused p-MAP4-induced mitochondrial engulfment, and the ubiquitin-interacting motif (UIM) domain determined the characteristics of p-MAP4-induced mitophagosomes, which were structure and membrane potential-independent. Moreover, p-MAP4 enhanced hypoxia-induced mitophagic flux impairment, and p-MAP4 LIR (47–50aa) mutation decreased hypoxia-induced autophagy both in MAP4 knockout and wildtype cardiomyocytes. Overall, this study identified that p-MAP4 as a novel mediator and cargo receptor in mitophagy, and that the degradation of the MAP4 PJ domain as a promising therapeutic target for improving the cardiac function of hypoxia-related heart failure or cardiac remodelling.

The Pathogenic R5L Mutation Disrupts Formation of Tau Complexes on the Microtubule by Altering Local N-Terminal Structure

The microtubule-associated protein (MAP) Tau is an intrinsically disordered protein (IDP) primarily expressed in axons, where it functions to regulate microtubule dynamics, modulate motor protein motility, and participate in signaling cascades. Tau misregulation and point mutations are linked to neurodegenerative diseases, including Progressive Supranuclear Palsy (PSP), Pick's Disease and Alzheimer's disease. Many disease-associated mutations in Tau occur in the C-terminal microtubule-binding domain of the protein. Effects of C-terminal mutations in Tau have led to the widely accepted disease-state theory that missense mutations in Tau reduce microtubule-binding affinity or increase Tau propensity to aggregate. Here, we investigate the effect of an N-terminal disease-associated mutation in Tau, R5L, on Tau-microtubule interactions using an in vitro reconstituted system. Contrary to the canonical disease-state theory, we determine the R5L mutation does not reduce Tau affinity for the microtubule using Total Internal Reflection Fluorescence (TIRF) Microscopy. Rather, the R5L mutation decreases the ability of Tau to form larger order complexes, or Tau patches, at high concentrations of Tau. Using Nuclear Magnetic Resonance (NMR), we show that the R5L mutation results in a local structural change that reduces interactions of the projection domain in the presence of microtubules. Altogether, these results challenge both the current paradigm of how mutations in Tau lead to disease and the role of the projection domain in modulating Tau behavior on the microtubule surface.

Altered ribosomal function and protein synthesis caused by tau

The synthesis of new proteins is a fundamental aspect of cellular life and is required for many neurological processes, including the formation, updating and extinction of long-term memories. Protein synthesis is impaired in neurodegenerative diseases including tauopathies, in which pathology is caused by aberrant changes to the microtubule-associated protein tau. We recently showed that both global de novo protein synthesis and the synthesis of select ribosomal proteins (RPs) are decreased in mouse models of frontotemporal dementia (FTD) which express mutant forms of tau. However, a comprehensive analysis of the effect of FTD-mutant tau on ribosomes is lacking. Here we used polysome profiling, de novo protein labelling and mass spectrometry-based proteomics to examine how ribosomes are altered in models of FTD. We identified 10 RPs which were decreased in abundance in primary neurons taken from the K3 mouse model of FTD. We further demonstrate that expression of human tau (hTau) decreases both protein synthesis and biogenesis of the 60S ribosomal subunit, with these effects being exacerbated in the presence of FTD-associated tau mutations. Lastly, we demonstrate that expression of the amino-terminal projection domain of hTau is sufficient to reduce protein synthesis and ribosomal biogenesis. Together, these data reinforce a role for tau in impairing ribosomal function.

Wheel Hub Defects Image Recognition Base on Zero-Shot Learning

In the wheel hub industry, the quality control of the product surface determines the subsequent processing, which can be realized through the hub defect image recognition based on deep learning. Although the existing methods based on deep learning have reached the level of human beings, they rely on large-scale training sets, however, these models are completely unable to cope with the situation without samples. Therefore, in this paper, a generalized zero-shot learning framework for hub defect image recognition was built. First, a reverse mapping strategy was adopted to reduce the hubness problem, then a domain adaptation measure was employed to alleviate the projection domain shift problem, and finally, a scaling calibration strategy was used to avoid the recognition preference of seen defects. The proposed model was validated using two data sets, VOC2007 and the self-built hub defect data set, and the results showed that the method performed better than the current popular methods.

Bi-shifting semantic auto-encoder for zero-shot learning

<abstract><p>Zero-shot learning aims to transfer the model of labeled seen classes in the source domain to the disjoint unseen classes without annotations in the target domain. Most existing approaches generally consider directly adopting the visual-semantic projection function learned in the source domain to the target domain without adaptation. However, due to the distribution discrepancy between the two domains, it remains challenging in dealing with the projection domain shift problem. In this work, we formulate a novel bi-shifting semantic auto-encoder to learn the semantic representations of the target instances and reinforce the generalization ability of the projection function. The encoder aims at mapping the visual features into the semantic space by leveraging the visual features of target instances and is guided by the semantic prototypes of seen classes. While two decoders manage to respectively reconstruct the original visual features in the source and target domains. Thus, our model can capture the generalized semantic characteristics related with the seen and unseen classes to alleviate the projection function problem. Furthermore, we develop an efficient algorithm by the advantage of the linear projection functions. Extensive experiments on the five benchmark datasets demonstrate the competitive performance of our proposed model.</p></abstract>

Activity-dependent refinement of nasal retinal projections drives topographic map sharpening in the teleost visual system

ABSTRACTTopographic maps in the brain are essential for processing information. Yet, our understanding of topographic mapping has remained limited by our inability to observe maps forming and refining directly in vivo. Here, we used Cre-mediated recombination of a new colorswitch reporter in zebrafish to generate the first transgenic model allowing the dynamic analysis of retinotopic mapping in vivo. We found that the antero-posterior retinotopic map forms early but remains dynamic, with nasal and temporal retinal axons expanding their projection domains over time. Nasal projections initially arborize in the anterior tectum but progressively refine their projection domain to the posterior tectum in an activity-dependent manner. This activity-dependent refinement drives retinotopic map sharpening along the antero-posterior axis. Altogether, our study provides the first analysis of a topographic map maturing in real-time in a live animal and opens new strategies for dissecting the intricate mechanisms of precise topographic mapping in vertebrates.