Improving the fermentable sugar yields of wheat straw by high-temperature pre-hydrolysis with thermophilic enzymes of Malbranchea cinnamomea.

BACKGROUND: Enzymatic hydrolysis is a key step in the conversion of lignocellulosic polysaccharides to fermentable sugars for the production of biofuels and high-value chemicals. However, current enzyme preparations from mesophilic fungi are deficient in their thermostability and biomass-hydrolyzing efficiency at high temperatures. Thermophilic fungi represent promising sources of thermostable and highly active enzymes for improving the biomass-to-sugar conversion process. Here we present a comprehensive study on the lignocellulosic biomass-degrading ability and enzyme system of thermophilic fungus Malbranchea cinnamomea N12 and the application of its enzymes in the synergistic hydrolysis of lignocellulosic biomass. RESULTS: Malbranchea cinnamomea N12 was capable of utilizing untreated wheat straw to produce high levels of xylanases and efficiently degrading lignocellulose under thermophilic conditions. Temporal analysis of the wheat straw-induced secretome revealed that M. cinnamomea N12 successively degraded the lignocellulosic polysaccharides through sequential secretion of enzymes targeting xylan and cellulose. Xylanase-enriched cocktail from M. cinnamomea N12 was more active on native and alkali­pretreated wheat straw than the commercial xylanases from Trichoderma reesei over temperatures ranging from 40 to 75 °C. Integration of M. cinnamomea N12 enzymes with the commercial cellulase preparation increased the glucose and xylose yields of alkali­pretreated wheat straw by 32 and 166%, respectively, with pronounced effects at elevated temperature. CONCLUSIONS: This study demonstrated the remarkable xylanase-producing ability and strategy of sequential lignocellulose breakdown of M. cinnamomea N12. A new process for the hydrolysis of lignocellulosic biomass was proposed, comprising thermophilic enzymolysis by enzymes of M. cinnamomea N12 followed with mesophilic enzymolysis by commercial cellulases. Developing M. cinnamomea N12 as platforms for thermophilic enzyme mixture production will provide new perspectives for improved conversion yields for current biomass saccharification schemes.

A weakly supervised learning-based segmentation network for dental diseases.

With the development of deep learning, medical image segmentation has become a promising technique for computer-aided medical diagnosis. However, the supervised training of the algorithm relies on a large amount of labeled data, and the private dataset bias generally exists in previous research, which seriously affects the algorithm's performance. In order to alleviate this problem and improve the robustness and generalization of the model, this paper proposes an end-to-end weakly supervised semantic segmentation network to learn and infer mappings. Firstly, an attention compensation mechanism (ACM) aggregating the class activation map (CAM) is designed to learn complementarily. Then the conditional random field (CRF) is introduced to prune the foreground and background regions. Finally, the obtained high-confidence regions are used as pseudo labels for the segmentation branch to train and optimize using a joint loss function. Our model achieves a Mean Intersection over Union (MIoU) score of 62.84% in the segmentation task, which is an effective improvement of 11.18% compared to the previous network for segmenting dental diseases. Moreover, we further verify that our model has higher robustness to dataset bias by improved localization mechanism (CAM). The research shows that our proposed approach improves the accuracy and robustness of dental disease identification.

A global optimization generation method of stitching dental panorama with anti-perspective transformation.

To address the limitation of narrow field-of-view in local oral cavity images that fail to capture large-area targets at once, this paper designs a method for generating natural dental panoramas based on oral endoscopic imaging that consists of two main stages: the anti-perspective transformation feature extraction and the coarse-to-fine global optimization matching. In the first stage, we increase the number of matched pairs and improve the robustness of the algorithm to viewpoint transformation by normalizing the anti-affine transformation region extracted from the Gaussian scale space and using log-polar coordinates to compute the gradient histogram of the octagonal region to obtain the set of perspective transformation resistant feature points. In the second stage, we design a coarse-to-fine global optimization matching strategy. Initially, we incorporate motion smoothing constraints and improve the Fast Library for Approximate Nearest Neighbors (FLANN) algorithm by utilizing neighborhood information for coarse matching. Then, we eliminate mismatches via homography-guided Random Sample Consensus (RANSAC) and further refine the matching using the Levenberg-Marquardt (L-M) algorithm to reduce cumulative errors and achieve global optimization. Finally, multi-band blending is used to eliminate the ghosting due to unalignment and make the image transition more natural. Experiments show that the visual effect of dental panoramas generated by the proposed method is significantly better than that of other methods, addressing the problems of sparse splicing discontinuities caused by sparse keypoints, ghosting due to parallax, and distortion caused by the accumulation of errors in multi-image splicing in oral endoscopic image stitching.

Increased enzyme activities and fungal degraders by Gloeophyllum trabeum inoculation improve lignocellulose degradation efficiency during manure-straw composting.

The present study investigated the effect of brown-rot fungus Gloeophyllum trabeum inoculation on lignocellulose degradation, enzyme activities and fungal community during co-composting of swine manure and wheat straw. G. trabeum inoculation shortened the maturation period of composting from 39 to 30 days. Composting piles inoculated with G. trabeum showed a higher degree of maturity as indicated by 31.6% lower C/N ratio and 29.4% higher GI. The decomposition rate of cellulose, hemicellulose and lignin was increased by 181.1%, 49.4% and 109.4%, respectively, due to higher activities of filter paper enzyme, xylanase, manganese peroxidase and laccase. Redundancy analysis showed that inoculating G. trabeum influenced the succession of fungal communities by changing the main physicochemical parameters, resulting in the increased relative abundance of Aspergillus, Mycothermus and Melanocarpus. Pearson correlation analysis indicated that more dominant fungal genera were involved in the production of lignocellulose-degrading enzymes after G. trabeum inoculation.

Thermal pretreatment enhances the degradation and humification of lignocellulose by stimulating thermophilic bacteria during dairy manure composting.

This study investigated the effect of thermal pretreatment (TP) on the lignocellulose degradation and humification during dairy manure composting and the underlying microbial mechanism. The results showed that TP accelerated temperature rise and elevated composting temperature by increasing 26% initial content of simple organics. The degradation of cellulose, hemicellulose and lignin was 78, 10 and 109% higher in thermal pretreatment composting (TPC) than traditional composting (TC), respectively. Moreover, TP significantly improved the humification degree of composts, as indicated by 14 and 38% higher humus content and humification indexes in TPC, respectively. 16S rRNA sequencing showed that TP increased the relative abundance of thermophilic bacteria in TPC, of which Thermobifida, Planifilum, Truepera and Thermomonospora were potentially involved in lignocellulose biodegradation and humification. Canonical correspondence analysis revealed that TP changed the main factor determining the bacterial community evolution from dissolved organic carbon (DOC) in TC to temperature in TPC.

The dynamics in implantation for patients with clefts.

OBJECTIVE: To investigate the stresses and strains of an endosseous dental implant in patients with different types of cleft palate in a finite element model. MATERIALS AND METHODS: Seven three-dimensional (3D) maxillary models were designed on a personal computer according to computed tomography slice data obtained from seven dry skulls. Next, computer-aided modification was performed on each model to produce three other 3D models with different cleft patterns. Thus, four model types with different cleft patterns were designed and termed NORM (without cleft), ALVEOLAR (only alveolar cleft), PALATAL (only palatal cleft), and COMPLETE (complete cleft). An implant was embedded into the molar region of each model, and a 300-N vertical load and 50-N horizontal load were applied to simulate mastication. Under these conditions, the stresses occurring at the implant-bone interface were calculated by finite element analysis. RESULTS: Different stress patterns were observed between the models with a palatal cleft (PALATAL and COMPLETE) and those without palatal cleft (NORM and ALVEOLAR). Regarding vertical load application, greater stresses occurred in PALATAL and COMPLETE types than in NORM and ALVEOLAR types. On application of a horizontal load, though the stresses did not show quantitative difference, their vector patterns differed. CONCLUSION: In patients with palatal clefts, characteristic stress patterns occur on the bone-implant interface during mastication. This should be taken into consideration when performing an implant treatment in patients with clefts.

The dynamic role of buttress reconstruction after maxillectomy.

BACKGROUND: The purpose of this study was to investigate the dynamic effect of maxillary reconstruction after partial resection of the maxilla. METHODS: On a personal computer, three-dimensional maxilla models were designed based on computed tomographic data obtained from 10 edentulous skull models. Simulation surgery was performed on each model, creating 10 pairs of half-removed maxilla models and corresponding models after reconstruction with a rib. The three different patterns seen in the 10 models were termed normal maxilla, half-removed maxilla, and reconstructed maxilla. After an implant was fixed on the molar region of each model, a 300-N vertical load and a 50-N horizontal load were applied. Using finite element analysis software, the deviation and stress on each model were calculated and compared between different model patterns. RESULTS: Regarding deformity of the maxilla, when a vertical load was applied, no significant difference was observed among the three model patterns. However, a difference was observed in response to a horizontal load in that there was a tendency for deformation to occur, with that of half-removed maxilla being the greatest followed by reconstructed and normal maxilla. Regarding stresses around the implant, when the vertical and horizontal loads were applied, no significant difference was observed among the three model patterns in maximum stress around the implant. CONCLUSIONS: A buttress reconstruction is effective in increasing the stability of the maxilla against a horizontal load. However, the maximum stress around the implant in the molar region is unaffected whether or not removal or reconstruction is performed.