385 research outputs found
Long-Read-Resolved, Ecosystem-Wide Exploration of Nucleotide and Structural Microdiversity of Lake Bacterioplankton Genomes
環境微生物のゲノム多様性を高解像度に検出 --「似て非なるゲノム」から生物多様性の源泉に迫る--. 京都大学プレスリリース. 2022-08-10.Same same but different. 京都大学プレスリリース. 2022-09-22.Reconstruction of metagenome-assembled genomes (MAGs) has become a fundamental approach in microbial ecology. However, a MAG is hardly complete and overlooks genomic microdiversity because metagenomic assembly fails to resolve microvariants among closely related genotypes. Aiming at understanding the universal factors that drive or constrain prokaryotic genome diversification, we performed an ecosystem-wide high-resolution metagenomic exploration of microdiversity by combining spatiotemporal (2 depths × 12 months) sampling from a pelagic freshwater system, high-quality MAG reconstruction using long- and short-read metagenomic sequences, and profiling of single nucleotide variants (SNVs) and structural variants (SVs) through mapping of short and long reads to the MAGs, respectively. We reconstructed 575 MAGs, including 29 circular assemblies, providing high-quality reference genomes of freshwater bacterioplankton. Read mapping against these MAGs identified 100 to 101, 781 SNVs/Mb and 0 to 305 insertions, 0 to 467 deletions, 0 to 41 duplications, and 0 to 6 inversions for each MAG. Nonsynonymous SNVs were accumulated in genes potentially involved in cell surface structural modification to evade phage recognition. Most (80.2%) deletions overlapped with a gene coding region, and genes of prokaryotic defense systems were most frequently (>8% of the genes) overlapped with a deletion. Some such deletions exhibited a monthly shift in their allele frequency, suggesting a rapid turnover of genotypes in response to phage predation. MAGs with extremely low microdiversity were either rare or opportunistic bloomers, suggesting that population persistency is key to their genomic diversification. The results concluded that prokaryotic genomic diversification is driven primarily by viral load and constrained by a population bottleneck
Chirality induction using circularly polarized light into a branched oligofluorene derivative in the presence of an achiral aid molecule
Chirality induction into a uniform, star-shaped fluorene oligomer with a central truxene moiety (T3) was achieved using circularly polarized light in the presence of achiral fluorene or phenanthrene. Induction into T3 alone was difficult, suggesting that close chain packing realized through interactions of T3 with small molecules plays a role in chirality induction
Multivariate analysis of the effect of keratinized mucosa on peri-implant tissues with platform switching: A retrospective study
Suzuki A., Nakano T., Inoue M., et al. Multivariate analysis of the effect of keratinized mucosa on peri-implant tissues with platform switching: A retrospective study. Clinical Implant Dentistry and Related Research , (2024); https://doi.org/10.1111/cid.13318.Background: In recent years, platform switching implant treatment has been increasing, which is believed to minimize bone loss around the implant after placement. However, there have been no reports on the relationship between keratinized mucosa width (KMW) and bone loss and soft tissue recession in platform switching implants. Objective: We evaluated the effect of the KMW on the amount of bone loss and soft tissue recession around a platform switching implant retrospectively using multivariate analysis. Materials and Methods: This one-year retrospective study included 91 implants in 48 patients. Age, sex, a history of periodontitis, implant location, oral hygiene status, and the KMW were included as explanatory variables to evaluate bone loss (BL) and buccal gingival height (GH). Generalized estimating equations (GEEs) were used to evaluate the effect of the KMW on platform switching peri-implant tissues. Results: The mean bone loss on the mesial (ΔBLm), distal (ΔBLd), and buccal (ΔBLb) sides of the implant were 0.16 ± 0.27 mm, 0.19 ± 0.34 mm, and 0.24 ± 0.50 mm, respectively, at 1 year after superstructure placement. The mean amount of change of GH (ΔGH) on the buccal side was 0.30 ± 0.47 mm. After correcting for confounders using GEEs, the results suggested that KMW <1.5 mm was a significant factor (P < 0.001) for bone loss over time in ΔBLm, ΔBLd, and ΔBLb. In addition, for soft tissues on the buccal side, KMW <1.5 mm was a significant factor for ΔGH reduction over time (P < 0.001). Conclusions: Keratinized mucosa width ≥1.5 mm was associated with a higher probability less hard and soft tissue recession around the platform switching implant after 1 year from superstructure placement
Influences of implant neck design and implant–abutment joint type on peri-implant bone stress and abutment micromovement: Three-dimensional finite element analysis
Objectives: Occlusal overloading is one of the causes of peri-implant bone resorption, and many studies on stress distribution in the peri-implant bone by three-dimensional finite element analysis (3D FEA) have been performed. However, the FEA models previously reported were simplified and far from representing what occurs in clinical situations. In this study, 3D FEA was conducted with simulation of the complex structure of dental implants, and the influences of neck design and connections with an abutment on peri-implant bone stress and abutment micromovement were investigated. Methods: Three types of two-piece implant CAD models were designed: external joint with a conical tapered neck (EJ), internal joint with a straight neck (IJ), and conical joint with a reverse conical neck (CJ). 3D FEA was performed with the setting of a “contact” condition at the component interface, and stress distribution in the peri-implant bone and abutment micromovement were analyzed. Results: The shear stress was concentrated on the mesiodistal side of the cortical bone for EJ. EJ had the largest amount of abutment micromovement. While the von Mises and shear stresses around the implant neck were concentrated on the labial bone for IJ, they were distributed on the mesiodistal side of the cortical bone for CJ. CJ had the least amount of abutment micromovement. Significance: Implants with a conical joint with an abutment and reverse conical neck design may effectively control occlusal overloading on the labial bone and abutment micromovement.Yamanishi Y., Yamaguchi S., Imazato S., et al. Influences of implant neck design and implant–abutment joint type on peri-implant bone stress and abutment micromovement: Three-dimensional finite element analysis. Dental Materials 28, 1126 (2012); https://doi.org/10.1016/j.dental.2012.07.160
Effects of the implant design on peri-implant bone stress and abutment micromovement: Three-dimensional finite element analysis of original computer-aided design models
Background: Occlusal overloading causes peri-implant bone resorption. Previous studies examined stress distribution in alveolar bone around commercial implants using three-dimensional (3D) finite element analysis. However, the commercial implants contained some different designs. The purpose of this study is to reveal the effect of the target design on peri-implant bone stress and abutment micromovement. Methods: Six 3D implant models were created for different implant-abutment joints: 1) internal joint model (IM); 2) external joint model (EM); 3) straight abutment (SA) shape; 4) tapered abutment (TA) shapes; 5) platform switching (PS) in the IM; and 6) modified TA neck design (reverse conical neck [RN]). A static load of 100 N was applied to the basal ridge surface of the abutment at a 45-degree oblique angle to the long axis of the implant. Both stress distribution in peri-implant bone and abutment micromovement in the SA and TA models were analyzed. Results: Compressive stress concentrated on labial cortical bone and tensile stress on the palatal side in the EM and on the labial side in the IM. There was no difference in maximum principal stress distribution for SA and TA models. Tensile stress concentration was not apparent on labial cortical bone in the PS model (versus IM). Maximum principal stress concentrated more on peri-implant bone in the RN than in the TA model. The TA model exhibited less abutment micromovement than the SA model. Conclusion: This study reveals the effects of the design of specific components on peri-implant bone stress and abutment displacement after implant-supported single restoration in the anterior maxilla.This is the pre-peer reviewed version of the following article:Yamanishi Y., Yamaguchi S., Imazato S., et al. Effects of the implant design on peri-implant bone stress and abutment micromovement: Three-dimensional finite element analysis of original computer-aided design models. Journal of Periodontology 85, (2014), which has been published in final form at https://doi.org/10.1902/jop.2014.140107. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving
Influence of implant length and diameter, bicortical anchorage, and sinus augmentation on bone stress distribution: Three-dimensional finite element analysis
Purpose: Clarification of the protocol for using short implants is required to enable widespread use of short implants as an available treatment option. The purpose of this study was to investigate the influences of implant length and diameter, bicortical anchorage, and sinus augmentation on peri-implant cortical bone stress by three-dimensional finite element analysis. Materials and Methods: For bone models with bone quantity A and C in the maxillary molar region, three-dimensional finite element analysis was performed using different lengths and diameters of implant computer-aided design models, and the degree of maximum principal stress distribution for each model was calculated. Results: For bone quantity A models, the degree of stress distribution of the 4-mm-diameter, 6-mm-length implant was the greatest. For bone quantity C models, the degree of stress distribution of the 5-mm-diameter, 6-mm-length implant with bicortical anchorage was much smaller than that for the 4-mm-diameter, 13-mm-length implant with sinus augmentation. Conclusion: The results of this study suggest that 6-mm-length implants should be selected in cases with bone quantity C where the bone width permits increasing implant diameter from 4 mm to 5 mm.Moriwaki H., Yamaguchi S., Nakano T., et al. Influence of implant length and diameter, bicortical anchorage, and sinus augmentation on bone stress distribution: Three-dimensional finite element analysis. International Journal of Oral and Maxillofacial Implants 31, 84 (2016); https://doi.org/10.11607/jomi.4217
Optical impression method to measure three-dimensional position and orientation of dental implants using an optical tracker
Objectives: The aim of this study was to devise an optical impression method that could make impressions of dental implants accurately and rapidly. Materials and methods: Four paper markers (4 × 3 mm, 8 × 6 mm, 16 × 12 mm, and 24 × 18 mm) and one titanium marker (8 × 6 mm) were prepared to determine the measuring accuracy of the three-dimensional optical tracker. For a proposed and conventional impression taking method, we compared the reproduction accuracies of the positions and orientations of dental implants and the times to obtain impressions. Finally, we fabricated computer-aided designing (CAD)/computer-aided manufacturing (CAM) superstructure frameworks to determine the adaptation accuracy. Results: The 8 × 6-mm titanium marker was optimal among the prepared markers. Dental implants made by the proposed and conventional impression taking methods had measurement errors of 71 ± 31 μm and 32 ± 18 μm, respectively. The proposed method took a significantly shorter time to obtain an impression than did the conventional method. The connection between the CAD/CAM superstructure frameworks and four implant analogs had uplifts of 55 ± 10 μm, 94 ± 35 μm, 2 ± 1 μm, and 66 ± 3 μm. Conclusion: Our proposed method and fabricated titanium markers enabled us to measure the positions and orientations of dental implants both accurately and rapidly. We then used the reproducible measurement results for the positions and orientations of the dental implants to fabricate CAD/CAM superstructure frameworks within an acceptable accuracy range. © 2012 John Wiley & Sons A/S.This is the pre-peer reviewed version of the following article: Ono S., Yamaguchi S., Kusumoto N., et al. Optical impression method to measure three-dimensional position and orientation of dental implants using an optical tracker. Clinical Oral Implants Research 24, 1117 (2013), which has been published in final form at https://doi.org/10.1111/j.1600-0501.2012.02519.x.. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving
Effects of implant–abutment connection type and inter-implant distance on inter-implant bone stress and microgap: Three-dimensional finite element analysis
The attainment of a good aesthetic outcome in dental implant treatment requires inter-implant papilla reconstruction, which is very difficult to perform. Maintenance of the inter-implant bone is essential for maintenance of the inter-implant papilla. The aim of this study was to investigate the mechanical influences of the implant–abutment connection type and inter-implant distance on the inter-implant bone by using three-dimensional finite element analysis. Three computer-aided design models of two-piece implants were designed: external connection (EC), internal connection (IC), and conical connection (CC). In each model, two identical implants were placed with inter-implant distances of 3.0, 2.5, and 2.0 mm. The maximum principal stress and microgap were evaluated. The stress values of the inter-implant bone decreased in the following order: IC, EC, and CC. The microgap decreased in the following order: EC, IC, and CC. Regardless of the type of implant– abutment connection, the stress of the inter-implant bone increased as the inter-implant distance decreased. The microgap barely changed as the inter-implant distance decreased. A CC implant is a mechanically advantageous implant–abutment connection type for maintenance of the inter-implant bone. With an inter-implant distance of less than 3.0 mm, use of a CC implant might suppress absorption of the inter-implant bone.Matsuoka T., Nakano T., Yamaguchi S., et al. Effects of implant–abutment connection type and inter-implant distance on inter-implant bone stress and microgap: Three-dimensional finite element analysis. Materials 14, 2421 (2021); https://doi.org/10.3390/ma14092421
Isolation and phototransformation of enantiomerically pure iridium(iii) bis[(4,6-difluorophenyl)pyridinato-N,C2]picolinate
Here we report the resolution of phosphorescent light-emitting iridium(III) bis[(4,6-difluorophenyl)pyridinato-N,C2]-picolinate into its respective enantiomers by using chiral HPLC and the photo-induced transformation of the isolated enantiomers
Development of artificial intelligence model for supporting implant drilling protocol decision making
Purpose: This study aimed to develop an artificial intelligence (AI) model to support the determination of an appropriate implant drilling protocol using cone-beam computed tomography (CBCT) images. Methods: Anonymized CBCT images were obtained from 60 patients. For each case, after implant placement, images of the bone regions at the implant site were extracted from 20 slices of CBCT images. Based on the actual drilling protocol, the images were classified into three categories: protocols A, B, and C. A total of 1,200 images were divided into training and validation datasets (n = 960, 80%) and a test dataset (n = 240, 20%). Another 240 images (80 images for each type) were extracted from the 60 cases as test data. An AI model based on LeNet-5 was developed using these data sets. The accuracy, sensitivity, precision, F-value, area under the curve (AUC) value, and receiver operating curve were calculated. Results: The accuracy of the trained model is 93.8%. The sensitivity results for drilling protocols A, B, and C were 97.5%, 95.0%, and 85.0%, respectively, while those for protocols A, B, and C were 86.7%, 92.7%, and 100%, respectively, and the F values for protocols A, B, and C were 91.8%, 93.8%, and 91.9%, respectively. The AUC values for protocols A, B, and C are 98.6%, 98.6%, and 99.4%, respectively. Conclusions: The AI model established in this study was effective in predicting drilling protocols from CBCT images before surgery, suggesting the possibility of developing a decision-making support system to promote primary stability.Sakai T., Li H., Shimada T., et al. Development of artificial intelligence model for supporting implant drilling protocol decision making. Journal of Prosthodontic Research 67, 360 (2023); https://doi.org/10.2186/jpr.JPR_D_22_00053
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