A model-based direct inversion network (MDIN) for dual spectral computed tomography.

Objective. Dual spectral computed tomography (DSCT) is a very challenging problem in the field of imaging. Due to the nonlinearity of its mathematical model, the images reconstructed by the conventional CT usually suffer from the beam hardening artifacts. Additionally, several existing DSCT methods rely heavily on the information of the spectra, which is often not readily available in applications. To address this problem, in this study, we aim to develop a novel approach to improve the DSCT reconstruction performance.Approach. A model-based direct inversion network (MDIN) is proposed for DSCT, which can directly predict the basis material images from the collected polychromatic projections. The all operations are performed in the network, requiring neither the conventional algorithms nor the information of the spectra. It can be viewed as an approximation to the inverse procedure of DSCT imaging model. The MDIN is composed of projection pre-decomposition module (PD-module), domain transformation layer (DT-layer), and image post-decomposition module (ID-module). The PD-module first performs the pre-decomposition on the polychromatic projections that consists of a series of stacked one-dimensional convolution layers. The DT-layer is designed to obtain the preliminary decomposed results, which has the characteristics of sparsely connected and learnable parameters. And the ID-module uses a deep neural network to further decompose the reconstructed results of the DT-layer so as to achieve higher-quality basis material images.Main results. Numerical experiments demonstrate that the proposed MDIN has significant advantages in substance decomposition, artifact reduction and noise suppression compared to other methods in the DSCT reconstruction.Significance. The proposed method has a flexible applicability, which can be extended to other CT problems, such as multi-spectral CT and low dose CT.

Carbohydrate-binding modules enhance H2O2 tolerance by promoting lytic polysaccharide monooxygenase active site H2O2 consumption.

Lytic polysaccharide monooxygenases (LPMOs) oxidatively depolymerize recalcitrant polysaccharides, which is important for biomass conversion. The catalytic domains of many LPMOs are linked to carbohydrate-binding modules (CBMs) through flexible linkers, but the function of these CBMs in LPMO catalysis is not well understood. In this study, we utilized MtLPMO9L and MtLPMO9G derived from Myceliophthora thermophila to investigate the impact of CBMs on LPMO activity, with particular emphasis on their influence on H2O2 tolerance. Using truncated forms of MtLPMO9G generated by removing the CBM, we found reduced substrate binding affinity and enzymatic activity. Conversely, when the CBM was fused to the C terminus of the single-domain MtLPMO9L to create MtLPMO9L-CBM, we observed a substantial improvement in substrate binding affinity, enzymatic activity, and notably, H2O2 tolerance. Furthermore, molecular dynamics simulations confirmed that the CBM fusion enhances the proximity of the active site to the substrate, thereby promoting multilocal cleavage and impacting the exposure of the copper active site to H2O2. Importantly, the fusion of CBM resulted in more efficient consumption of H2O2 by LPMO, leading to improved enzymatic activity and reduced auto-oxidative damage of the copper active center.

Multi-scale dilated dense reconstruction network for limited-angle computed tomography.

Objective.Due to the incomplete projection data, the image reconstructed by limited-angle computed tomography (CT) usually suffers from significant artifacts, by which the structural details are heavily blurred. In this study, we aim to develop a novel approach to improve the limited-angle CT reconstruction performance, especially for the narrow scanning angular range.Approach.A deep learning based iterative framework for limited-angle tomography is proposed, which is named multi-scale dilated dense reconstruction network (MSDDRNet). The MSDDRNet utilizes a multi-scale dilated dense convolution neural network (MSDD-CNN) with conventional reconstruction algorithm for predicting image from incomplete projection data. The MSDD-CNN enhances the image features in the network by merging the DenseNet-Like structure, which serves to restore invisible singularities and reduce artifacts, as well as introducing constraints on the projection domain data into the iterative process to achieve better image detail recovery. Additionally, to improve the training speed of the network, we use a strategy of pre-training and model migration.Main results.Numerical experiments demonstrate that the proposed MSDDRNet performs well in terms of artifact correction, noise reduction and structure recovery compared to existing methods with limited scan angles, and we also extend the proposed method to more general scanning condition and other application such as dental CT data.Significance.The proposed method is a general framework, which can be applied to other CT problems, such as low dose CT, sparse-data CT and spectral CT.

Comparative studies of two AA10 family lytic polysaccharide monooxygenases from Bacillus thuringiensis.

Bacillus thuringiensis, known to be one of the most important biocontrol microorganisms, contains three AA10 family lytic polysaccharide monooxygenases (LPMOs) in its genome. In previous reports, two of them, BtLPMO10A and BtLPMO10B, have been preliminarily characterized. However, some important biochemical features and substrate preference, as well as their potential applications in chitin degradation, still deserve further investigation. Results from present study showed that both BtLPMO10A and BtLPMO10B exhibit similar catalytic domains as well as highly conserved substrate-binding planes. However, unlike BtLPMO10A, which has comparable binding ability to both crystalline and amorphous form of chitins, BtLPMO10B exhibited much stronger binding ability to colloidal chitin, which mainly attribute to its carbohydrate-binding module-5 (CBM5). Interestingly, the relative high binding ability of BtLPMO10B to colloidal chitin does not lead to high catalytic activity of the enzyme. In contrast, the enzyme exhibited higher activity on ß-chitin. Further experiments showed that the binding of BtLPMO10B to colloidal chitin was mainly non-productive, indicating a complicated role for CBM5 in LPMO activity. Furthermore, synergistic experiments demonstrated that both LPMOs boosted the activity of the chitinase, and the higher efficiency of BtLPMO10A can be overridden by BtLPMO10B.

Distinct Interaction of Lytic Polysaccharide Monooxygenase with Cellulose Revealed by Computational and Biochemical Studies.

A distinct interaction pattern of lytic polysaccharide monooxygenases (LPMOs) with their insoluble substrate, cellulose, was revealed through the combination of computational and biochemical approaches. The results indicated that the enzymes can stably bind on the flat hydrophobic surface of cellulose via the interactions of the key residues located in the axis across the conserved distal tyrosine residue and copper ion with two adjacent cellulose chains. Further studies on the correlation of substrate binding and H2O2 accumulation suggested that LPMOs involved in the productive binding on the insoluble polysaccharides not only fail to accumulate H2O2 but also consume the H2O2 produced by the unbound molecules under the lab condition. This was further substantiated by quantum-mechanical calculations. These findings broadened our knowledge of the interaction between enzymes and insoluble substrates and deepened our understanding of the role that H2O2 plays in LPMO activity.

A lytic polysaccharide monooxygenase from Myceliophthora thermophila and its synergism with cellobiohydrolases in cellulose hydrolysis.

Lytic polysaccharide monooxygenases (LPMOs) have attracted vast attention because of their unique mechanism of oxidative degradation of carbohydrate polymers and the potential application in biorefineries. This study characterized a novel LPMO from Myceliophthora thermophila, denoted MtLPMO9L. The structure model of the enzyme indicated that it belongs to the C1-oxidizing LPMO, which has neither an extra helix in the L3 loop nor extra loop region in the L2 loop. This was confirmed subsequently by the enzymatic assays since MtLPMO9L only acts on cellulose and generates C1-oxidized cello-oligosaccharides. Moreover, synergetic experiments showed that MtLPMO9L significantly improves the efficiency of cellobiohydrolase (CBH) II. In contrast, the inhibitory rather than synergetic effect was observed when combining used MtLPMO9L and CBHI. Changing the incubation time and concentration ratio of MtLPMO9L and CBHI could attenuate the inhibitory effects. This discovery suggests a different synergy detail between MtLPMO9L and two CBHs, which implies that the composition of cellulase cocktails may need reconsideration.

A new regulator RsdA mediating fungal secondary metabolism has a detrimental impact on asexual development in Pestalotiopsis fici.

Secondary metabolite (SM) production and development are correlated processes in fungi that are often coordinated by pleiotropic regulators. The eukaryotic regulators are critical players in mediating SM production related to fungal development, yet little data are available to support this hypothesis. In this study, a global regulator, RsdA (regulation of secondary metabolism and development), was identified through genome-wide analysis and deletion of the regulator gene in the endophytic fungus Pestalotiopsis fici. Here, we established that RsdA regulation of SMs is accompanied by the repression of asexual development. Deletion of rsdA significantly reduces not only asexual development, resulting in low sporulation and abnormal conidia, but also the major SM production, while remarkably increasing the melanin production. Overproduction of melanin leads to the formation of unusual, heavily pigmented hyphae. Transcriptome analysis data provide the evidence that RsdA globally regulates genes involved in secondary metabolism and asexual development. Double deletion of rsdA and the melanin polyketide synthase gene PfmaE confirm that RsdA regulation of asexual development is independent of the melanin biosynthetic pathway. Finally, our results demonstrate that RsdA can be used for the discovery of secondary metabolites in filamentous fungi.

Polyketide Production of Pestaloficiols and Macrodiolide Ficiolides Revealed by Manipulations of Epigenetic Regulators in an Endophytic Fungus.

Regarding targeted disruption of epigenetic regulators, histone methyltransferase and deacetylase in a plant endophytic fungus Pestalotiopsis fici have been uncovered as an unexplored chemical repertoire. Manipulation of epigenetic regulators led to the isolation of 15 new polyketides, including pestaloficiols T-W (1-3 and 5), as well as 11 macrodiolide ficiolides A-K (6-16). Ficiolide K (16) was found to contain a very rare 1,6-anhydro-pyranose moiety. Finally, the biosynthetic origin of macrodiolide was characterized by isotope-labeling experiments.