Bonding of Lignin and Coniferyl Alcohol by a Redox Shuttle of Low-Molecular-Weight Lignols in Enzymatic Oxidative Dehydrogenative Polymerization.

Lignin is an aromatic polymer that constitutes plant cell walls. The polymerization of lignin proceeds by radical coupling, and this process requires radicalization of the phenolic end of lignin by enzymes. However, due to the steric hindrance between enzymes, lignin, and polysaccharides, the direct oxidation of the phenolic end of lignin by the enzyme would be difficult, and the details of the growth of lignin are still unknown. In this study, enzymatic dehydrogenative polymerization experiments were conducted using coniferyl alcohol (CA) and the deuterium-labeled lignin model compound (D-LM) under a noncontact condition in which horseradish peroxidase cannot directly oxidize D-LM due to separation by a dialysis membrane. Analysis of deuterium-labeled degraded compounds obtained by a combination of methylation and thioacidolysis revealed the formation of the bond between the phenolic end of D-LM and CA, suggesting that membrane-permeable, low-molecular-weight lignols functioned as a redox shuttle mediator.

A lignin-derived material improves plant nutrient bioavailability and growth through its metal chelating capacity.

The lignocellulosic biorefinery industry can be an important contributor to achieving global carbon net zero goals. However, low valorization of the waste lignin severely limits the sustainability of biorefineries. Using a hydrothermal reaction, we have converted sulfuric acid lignin (SAL) into a water-soluble hydrothermal SAL (HSAL). Here, we show the improvement of HSAL on plant nutrient bioavailability and growth through its metal chelating capacity. We characterize HSAL's high ratio of phenolic hydroxyl groups to methoxy groups and its capacity to chelate metal ions. Application of HSAL significantly promotes root length and plant growth of both monocot and dicot plant species due to improving nutrient bioavailability. The HSAL-mediated increase in iron bioavailability is comparable to the well-known metal chelator ethylenediaminetetraacetic acid. Therefore, HSAL promises to be a sustainable nutrient chelator to provide an attractive avenue for sustainable utilization of the waste lignin from the biorefinery industry.

Microscopic distribution of alkaloids in freeze-fixed stems of Phellodendron amurense.

Introduction: Phellodendron amurense Rupr. contains rich alkaloids, which have been extensively applied in clinical treatments for their various biological activities. However, detailed microscopic distribution and roles of such alkaloids in P. amurense stem still need to be clarified. Methods: In this study, the distribution of eight alkaloids in the transverse surface of freeze-fixed P. amurense stems in fall and summer has been visualized by cryo-time-of-flight secondary ion mass spectrometry and scanning electron microscopy (cryo-TOF-SIMS/SEM), which was found in living tissues with relative contents of different alkaloids varying with the position. In addition, the contents of these alkaloids quantified by high-performance liquid chromatography (HPLC) analysis suggested the seasonal variation from fall to the following summer. Results and discussion: Distribution of eight alkaloids in the freeze-fixed stems of P. amurense from fall and summer seasons has been visualized and assigned into specific living tissues, with relative contents varying in different positions with seasons, which suggested their possible roles in the physiological processes of the plant itself or plant responding to changes in the surrounding conditions. Conclusion: This study provided a significant basis for further discussion of the genes or enzymes involved in these processes, which will contribute to investigating biosynthetic pathways and specific in planta roles of alkaloids.

Trueness of the Combined Intra- and Extraoral Scanning Technique for Transferring Subgingival Contours from Provisional Restorations to Definitive Restorations

PURPOSE: To compare the morphologic trueness of provisional and definitive restorations constructed with conventional custom impression techniques to those constructed with intra- and extraoral scanning (IEOS), which can digitally transfer the subgingival morphology of the provisional restoration to the definitive restoration. MATERIALS AND METHODS: Provisional restorations were fabricated on typodonts in which implants were placed. In the conventional method, a customized impression coping was produced by using polymethyl methacrylate resin to transfer the subgingival contour of the provisional restoration. Impressions were taken with silicone impression material, and definitive restorations were made by CAM. The IEOS technique was performed as previously reported. In brief, three individually scanned stereolithography (STL) files were superimposed in CAD software to transfer the morphology of the provisional restoration to the definitive restoration. Definitive restorations were then made by CAM. The provisional and definitive restorations were both scanned by IOS. Scanned data files were superimposed with morphometry software, and the distortions were measured. Student t test was used for statistical analysis. RESULTS: The subgingival morphologies of definitive restorations prepared by the conventional method showed significant negative distortions compared to definitive restorations prepared by the IEOS technique. CONCLUSION: The IEOS technique can more accurately transfer the subgingival contour of provisional restorations to definitive restorations compared to the conventional customized impression coping technique.

Discrete Search Photometric Stereo for Fast and Accurate Shape Estimation.

We consider the problem of estimating surface normals of a scene with spatially varying, general bidirectional reflectance distribution functions (BRDFs) observed by a static camera under varying distant illuminations. Unlike previous approaches that rely on continuous optimization of surface normals, we cast the problem as a discrete search problem over a set of finely discretized surface normals. In this setting, we show that the expensive processes can be precomputed in a scene-independent manner, resulting in accelerated inference. We discuss two variants of our discrete search photometric stereo (DSPS), one working with continuous linear combinations of BRDF bases and the other working with discrete BRDFs sampled from a BRDF space. Experiments show that DSPS has comparable accuracy to state-of-the-art exemplar-based photometric stereo methods while achieving 10-100x acceleration.

Prognosis of Implants with Implant-Supported Fixed Dental Prostheses in the Elderly Population: A Retrospective Study with a 5- to 10-Year Follow-Up.

This retrospective study aimed to investigate the survival rate of implants from 5 to 10 years after the placement of implant-supported fixed dental prostheses (ISFDPs) and the management of implant loss in the elderly population. Elderly patients (≥65 years old) who had been treated with ISFDPs and followed up with for at least 5 years between October 2009 and March 2020 were enrolled. Patient profiles and implant-related data were extracted. The survival rate of implants up to 5 years as well as the 10-year cumulative survival rate were evaluated. The management of implant loss and prosthetic interventions were also investigated. In total, 195 patients (mean age: 70.1 ± 4.5 years old) and 687 implants (287 ISFDPs) were assessed. The 5-year survival rate was 99.0% and the 10-year cumulative survival rate was 98.1%. Seven of the eleven implants lost were lost due to peri-implantitis. Only three implants in two patients were placed after the loss of the implants; most were restored using non-invasive procedures. Two patients underwent a conversion from ISFDPs to removable prostheses. This study showed that high survival rates were observed in an elderly population with ISFDPs and that non-invasive procedures were often applied after the loss of an implant.

Distribution of lignans and lignan mono/diglucosides within Ginkgo biloba L. stem.

To investigate the biosynthetic pathways and regulatory mechanisms of lignans in plants, the actual distributions of lignans and lignan glucosides in flash-frozen stems of Ginkgo biloba L. (Ginkgoaceae) were studied using cryo time-of-flight secondary ion mass spectrometry coupled with scanning electron microscopy (cryo-TOF-SIMS/SEM). Four lignans and four lignan glucosides were successfully characterized. Quantitative HPLC measurements were conducted on serial tangential sections of freeze-fixed ginkgo stem to determine the amount and approximate distribution of lignan and lignan glucosides. (-)-Olivil 4,4'-di-O-ß-d-glucopyranoside (olivil DG) was the most abundant lignan glucoside in ginkgo and was distributed mainly in the phloem, ray parenchyma cells, and pith. The comparative accumulation of olivil DG revealed its possible transport pathways and storage sites in ginkgo. Although not all relevant enzymes have been identified, understanding the distributions of lignan and lignan glucosides in ginkgo stems provides significant insight into their biological functions.

Patch-Based Uncalibrated Photometric Stereo Under Natural Illumination.

This paper presents a photometric stereo method that works with unknown natural illumination without any calibration objects or initial guess of the target shape. To solve this challenging problem, we propose the use of an equivalent directional lighting model for small surface patches consisting of slowly varying normals, and solve each patch up to an arbitrary orthogonal ambiguity. We further build the patch connections by extracting consistent surface normal pairs via spatial overlaps among patches and intensity profiles. Guided by these connections, the local ambiguities are unified to a global orthogonal one through Markov Random Field optimization and rotation averaging. After applying the integrability constraint, our solution contains only a binary ambiguity, which could be easily removed. Experiments using both synthetic and real-world datasets show our method provides even comparable results to calibrated methods.

Deep Photometric Stereo Networks for Determining Surface Normal and Reflectances.

This article presents a photometric stereo method based on deep learning. One of the major difficulties in photometric stereo is designing an appropriate reflectance model that is both capable of representing real-world reflectances and computationally tractable for deriving surface normal. Unlike previous photometric stereo methods that rely on a simplified parametric image formation model, such as the Lambert's model, the proposed method aims at establishing a flexible mapping between complex reflectance observations and surface normal using a deep neural network. In addition, the proposed method predicts the reflectance, which allows us to understand surface materials and to render the scene under arbitrary lighting conditions. As a result, we propose a deep photometric stereo network (DPSN) that takes reflectance observations under varying light directions and infers the surface normal and reflectance in a per-pixel manner. To make the DPSN applicable to real-world scenes, a dataset of measured BRDFs (MERL BRDF dataset) has been used for training the network. Evaluation using simulation and real-world scenes shows the effectiveness of the proposed approach in estimating both surface normal and reflectances.

Deep Photometric Stereo for Non-Lambertian Surfaces.

This paper addresses the problem of photometric stereo, in both calibrated and uncalibrated scenarios, for non-Lambertian surfaces based on deep learning. We first introduce a fully convolutional deep network for calibrated photometric stereo, which we call PS-FCN. Unlike traditional approaches that adopt simplified reflectance models to make the problem tractable, our method directly learns the mapping from reflectance observations to surface normal, and is able to handle surfaces with general and unknown isotropic reflectance. At test time, PS-FCN takes an arbitrary number of images and their associated light directions as input and predicts a surface normal map of the scene in a fast feed-forward pass. To deal with the uncalibrated scenario where light directions are unknown, we introduce a new convolutional network, named LCNet, to estimate light directions from input images. The estimated light directions and the input images are then fed to PS-FCN to determine the surface normals. Our method does not require a pre-defined set of light directions and can handle multiple images in an order-agnostic manner. Thorough evaluation of our approach on both synthetic and real datasets shows that it outperforms state-of-the-art methods in both calibrated and uncalibrated scenarios.

Shell Theory: A Statistical Model of Reality.

The foundational assumption of machine learning is that the data under consideration is separable into classes; while intuitively reasonable, separability constraints have proven remarkably difficult to formulate mathematically. We believe this problem is rooted in the mismatch between existing statistical techniques and commonly encountered data; object representations are typically high dimensional but statistical techniques tend to treat high dimensions a degenerate case. To address this problem, we develop a dedicated statistical framework for machine learning in high dimensions. The framework derives from the observation that object relations form a natural hierarchy; this leads us to model objects as instances of a high dimensional, hierarchal generative processes. Using a distance based statistical technique, also developed in this paper, we show that in such generative processes, instances of each process in the hierarchy, are almost-always encapsulated by a distinctive-shell that excludes almost-all other instances. The result is shell theory, a statistical machine learning framework in which separability constraints (distinctive-shells) are formally derived from the assumed generative process.

Active Transport of Lignin Precursors into Membrane Vesicles from Lignifying Tissues of Bamboo.

Lignin is the second most abundant natural polymer on Earth and is a major cell wall component in vascular plants. Lignin biosynthesis has three stages: biosynthesis, transport, and polymerization of its precursors. However, there is limited knowledge on lignin precursor transport, especially in monocots. In the present study, we aimed to elucidate the transport mode of lignin monomers in the lignifying tissues of bamboo (Phyllostachys pubescens). The growth manners and lignification processes of bamboo shoots were elucidated, which enabled us to obtain the lignifying tissues reproducibly. Microsomal membrane fractions were prepared from tissues undergoing vigorous lignification to analyze the transport activities of lignin precursors in order to show the ATP-dependent transport of coniferin and p-glucocoumaryl alcohol. The transport activities for both precursors depend on vacuolar type H+-ATPase and a H+ gradient across the membrane, suggesting that the electrochemical potential is the driving force of the transport of both substrates. These findings are similar to the transport properties of these lignin precursors in the differentiating xylem of poplar and Japanese cypress. Our findings suggest that transport of coniferin and p-glucocoumaryl alcohol is mediated by secondary active transporters energized partly by the vacuolar type H+-ATPase, which is common in lignifying tissues. The loading of these lignin precursors into endomembrane compartments may contribute to lignification in vascular plants.

A 3-Year Prospective Study on Radiographic Marginal Bone Evaluation Around Platform-Shifting Implants with Internal Conical Connections.

PURPOSE: To evaluate marginal bone level changes over 3 years around platform-shifting implants with internal conical connections, and to identify the factors relating to bone level changes. MATERIALS AND METHODS: Systemically healthy patients who lost one tooth or two consecutive teeth were enrolled in the study. The subjects received one or two implants with platform-shifting and internal conical connections in healed bone in a submerged manner. Digital standardized periapical radiographs were obtained at the time of implant placement, at prosthesis delivery, at 1 year, and at 3 years after the definitive restorations. Marginal bone level changes were measured at the mesial and distal aspects of each implant. Spearman correlation coefficients were calculated to examine the correlation between marginal bone level changes and clinical factors (age, vertical mucosal thickness, implant length and diameter, insertion torque value, and vertical implant position). RESULTS: Twenty-five patients with 30 implants (8 men and 17 women, mean age: 61.24 ± 13.18 years) were followed up to 3 years after the definitive restorations. The implant survival rate was 100%, and no remarkable complications were found. Mean peri-implant marginal bone level changes were -0.41 ± 0.61 mm (from placement to prosthesis delivery: C1); -0.08 ± 0.54 mm (from prosthesis delivery to 1 year: C2); -0.04 ± 0.95 mm (from prosthesis delivery to 3 years: C3); and 0.04 ± 0.60 mm (from 1 year to 3 years: C4), respectively. Statistically significant differences in bone level changes were observed between C1 and C3, and C1 and C4. Significant correlations of marginal bone level changes with implant diameter in C1 and with vertical implant position in C2 and C3 were observed. CONCLUSION: Within the limitations of this study, platform-shifting implants with internal conical connections appeared to prevent marginal bone resorption, especially after delivery of definitive prostheses, although marginal bone resorption attributed to the reestablishment of biologic width following subcrestal placement might be unavoidable.

In Vitro Assessment of the Effect of Implant Position on Biomechanical Behaviors of Implant-Supported Removable Partial Dentures in Kennedy Class II Condition.

The purpose of this study was to investigate the effects of implant position and loading position on biomechanical behaviors using implant-supported removable partial denture (ISRPD) models in a simulated Kennedy class Ⅱ partially edentulous mandible. Three types of Kennedy class Ⅱ mandibular acrylic resin models (a conventional RPD without support by an implant-CRPD; models with an implant placed at first molar (#46)-MP-ISRPD- and second molar (#47)-DP-ISRPD) were used to measure vertical displacement of the RPD, mesio-distal displacement of the abutment tooth, and bending moment of the abutment tooth and implant under one-point loading. The variables at three respective loading points (#45, #46 and #47) were compared statistically. Vertical displacement was suppressed in ISRPDs compared to the CRPD, and significant effects were identified under loading at the implant position. The largest meiso-distal displacement was observed in MP-ISRPD under #47 loading. Bending moments of the abutment tooth and implant were significantly higher in MP-ISRPD than in DP-ISPRD. In MP-ISRPD, a higher bending moment of the abutment tooth under #45 and #47 loading was detected, although the bending moment in DP-ISRPD was almost zero. The results of this study suggested that MP-ISRPD shows the specific biomechanical behaviors, although DP-ISRPD might provide biomechanical benefits under all one-point loading conditions.

Localised laccase activity modulates distribution of lignin polymers in gymnosperm compression wood.

The woody stems of coniferous gymnosperms produce specialised compression wood to adjust the stem growth orientation in response to gravitropic stimulation. During this process, tracheids develop a compression-wood-specific S2 L cell wall layer with lignins highly enriched with p-hydroxyphenyl (H)-type units derived from H-type monolignol, whereas lignins produced in the cell walls of normal wood tracheids are exclusively composed of guaiacyl (G)-type units from G-type monolignol with a trace amount of H-type units. We show that laccases, a class of lignin polymerisation enzymes, play a crucial role in the spatially organised polymerisation of H-type and G-type monolignols during compression wood formation in Japanese cypress (Chamaecyparis obtusa). We performed a series of chemical-probe-aided imaging analysis on C. obtusa compression wood cell walls, together with gene expression, protein localisation and enzymatic assays of C. obtusa laccases. Our data indicated that CoLac1 and CoLac3 with differential oxidation activities towards H-type and G-type monolignols were precisely localised to distinct cell wall layers in which H-type and G-type lignin units were preferentially produced during the development of compression wood tracheids. We propose that, not only the spatial localisation of laccases, but also their biochemical characteristics dictate the spatial patterning of lignin polymerisation in gymnosperm compression wood.

The need for polishing and occlusal adjustment of zirconia prostheses for wear on antagonist teeth.

The attrition of enamel when opposed by ceramics is of great concern. The purpose of this study was to evaluate enamel wear against high translucent zirconia (Zr), lithium disilicate (LD), gold (Au), and enamel (E) with different surface and contact conditions. The materials were divided into two groups: polished and ground (n=8 each). Two-body wear tests were performed against human enamel with vertical and horizontal, horizontal, and vertical repetitive movements as experiments 1 to 3 respectively. The surface roughness of all materials except Zr changed throughout the experiments. In experiment 1, Zr and Au showed less antagonist wear when polished than when ground. In experiment 2, polished groups showed less antagonist wear than ground groups in all materials. In experiment 3, Zr and LD exerted greater antagonist wear than E, regardless of Ra. These findings confirm the importance of polishing and occlusal adjustment of zirconia.

RotationNet for Joint Object Categorization and Unsupervised Pose Estimation from Multi-View Images.

We propose a Convolutional Neural Network (CNN)-based model "RotationNet," which takes multi-view images of an object as input and jointly estimates its pose and object category. Unlike previous approaches that use known viewpoint labels for training, our method treats the viewpoint labels as latent variables, which are learned in an unsupervised manner during the training using an unaligned object dataset. RotationNet uses only a partial set of multi-view images for inference, and this property makes it useful in practical scenarios where only partial views are available. Moreover, our pose alignment strategy enables one to obtain view-specific feature representations shared across classes, which is important to maintain high accuracy in both object categorization and pose estimation. Effectiveness of RotationNet is demonstrated by its superior performance to the state-of-the-art methods of 3D object classification on 10- and 40-class ModelNet datasets. We also show that RotationNet, even trained without known poses, achieves comparable performance to the state-of-the-art methods on an object pose estimation dataset. Furthermore, our object ranking method based on classification by RotationNet achieved the first prize in two tracks of the 3D Shape Retrieval Contest (SHREC) 2017. Finally, we demonstrate the performance of real-world applications of RotationNet trained with our newly created multi-view image dataset using a moving USB camera.

Combinations of the Aromatic Rings in ß-1 Structure Formation of Lignin Based on Quantitative Analysis by Thioacidolysis.

The amount of ß-1 structures in lignin is small; however, they are assumed to significantly affect the reactivity of lignin because they form dienone structures. A method employing thioacidolysis and subsequent desulfurization yields products that can be analyzed via gas chromatography-mass spectrometry (GC-MS) to quantify these ß-1 structures. However, the retention times and response factors of the reaction products have not been accurately determined thus far. Here, 12 standard compounds combined with p-hydroxyphenyl (H), guaiacyl (G), and syringyl (S) units were synthesized, and their retention times and response factors were determined through GC-MS, using selective ions. Based on these data, we also investigated the ß-1 structures of lignocellulosic lignin samples. Our results clarified that the successful formation of the ß-1 structure was dependent on the type of aromatic rings present; there were very few ß-1 structures containing H units; and the amount of G-G type was higher and that of the heterotype, i.e., G-S type, was lower than the stochastic value.

Factors associated with discontinuation and resumption of implant maintenance therapy.

Discontinuation of implant maintenance is the main risk factor for implant failure. The purpose of this study was to identify factors associated with previous discontinuation and resumption of maintenance among implant patients. A questionnaire survey was sent to 171 patients receiving implant maintenance at a university hospital; 169 patients responded. To assess the effect of job status, 26 patients (15.4%) with a history of maintenance discontinuation were classified as employed and nonemployed. The main reasons for previously discontinuing maintenance were work issues (in employed respondents) and dissatisfaction with treatment skill or chairside manner (in nonemployed respondents). The main reasons for resuming maintenance were those related to dental treatment (in employed respondents) and awareness of the importance of maintenance (in nonemployed respondents). There were significant differences in relation to job status in the reasons reported for discontinuing and resuming maintenance (both P < 0.05). The present findings suggest that oral health professionals should consider these factors when assisting patients in reducing the risk of implant failure.

Identification of Naturally Occurring Polyamines as Root-Knot Nematode Attractants.

Root-knot nematodes (RKNs; genus Meloidogyne) are a class of plant parasites that infect the roots of many plant species. It is believed that RKNs target certain signaling molecules derived from plants to locate their hosts; however, currently, no plant compound has been unambiguously identified as a universal RKN attractant. To address this question, we screened a chemical library of synthetic compounds for Meloidogyne incognita attractants. The breakdown product of aminopropylamino-anthraquinone, 1,3-diaminopropane, as well as its related compounds, putrescine and cadaverine, were found to attract M. incognita. After examining various polyamines, M. incognita were found to be attracted specifically by natural compounds that possess three to five methylene groups between two terminal amino groups. Using cryo-TOF-SIMS/SEM, cadaverine was indeed detected in soybean root cortex cells and the surrounding rhizosphere, establishing a chemical gradient. In addition to cadaverine, putrescine and 1,3-diaminopropane were also detected in root exudate by HPLC-MS/MS. Furthermore, exogenously applied cadaverine is sufficient to enhance M. incognita infection of Arabidopsis seedlings. These results suggest that M. incognita is likely attracted by polyamines to locate the appropriate host plants, and the naturally occurring polyamines have potential applications in agriculture in developing protection strategies for crops from RKN infection.