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  • Springer Science and Business Media LLC  (4)
  • Lee, Chun-Teh  (4)
  • 1
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    The apical root canal system microbial communities determined by next-generation sequencing
    Springer Science and Business Media LLC ; 2020
    In:  Scientific Reports Vol. 10, No. 1 ( 2020-07-02)
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    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1 ( 2020-07-02)
    Abstract: The aim of this study was to explore the microbial communities of endodontic infections at their apical portion by 16S rRNA Illumina sequencing and delineate the core microbiome of root canal infections and that of their associated clinical symptomatology. Samples were collected from fifteen subjects presenting one tooth with a root canal infection, and their associated symptoms were recorded. Samples were collected from the apical third of roots using a #10 K file and then amplified using multiple displacement amplification and PCR-amplified with universal primers. Amplicons were sequenced (V3–V4 hypervariable region of the 16S rRNA gene) using MiSeq (Illumina, CA). The microbial composition of the samples was determined using QIIME and HOMINGS. Data were analyzed using t tests and ANOVA. A total of 1,038,656 good quality sequences were obtained, and OTUs were assigned to 10 bacterial phyla, led by Bacteroidetes (51.2%) and Firmicutes (27.1%), and 94 genera were represented primarily by Prevotella (17.9%) and Bacteroidaceae G-1 (14.3%). Symptomatic teeth were associated with higher levels of Porphyromonas ( p   〈  0.05) and Prevotella . P. endodontalis and P. oris were present in both cores. The present study demonstrated the complexity of the root canal microbiome and the “common denominators” of root canal infections and identified taxa whose virulence properties should be further explored. The polymicrobial etiology of endodontic infections has long been established. However, few studies have focused on expanding the breadth and depth of coverage of microbiome-infected root canals at their apical portion.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-020-67828-3
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2615211-3
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  • 2
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    Factors for poor oral health in long-term childhood cancer survivors
    Springer Science and Business Media LLC ; 2023
    In:  BMC Oral Health Vol. 23, No. 1 ( 2023-02-04)
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    In: BMC Oral Health, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2023-02-04)
    Abstract: Survivors of childhood cancer are at risk for therapy-related dental diseases. The purpose of the study was to investigate the associations between clinical, socioeconomic, and demographic factors and oral diseases in the St. Jude Lifetime Cohort (SJLIFE) participants. Methods We performed a retrospective medical chart review and evaluated longitudinal self-reported dental outcomes in 4856 childhood cancer survivors and 591 community controls participating in the St. Jude Lifetime Cohort (SJLIFE) study. Univariate and multivariable logistic regression models were used to assess the impact of socioeconomic factors, treatment exposures and patient demographics on dental outcomes. Results Cancer survivors were more likely to report microdontia (odds ratio (OR) = 7.89, 95% confidence interval (CI) [4.64, 14.90]), abnormal root development (OR = 6.19, CI [3.38, 13.00] ), hypodontia (OR = 2.75, CI [1.83, 4.33]), enamel hypoplasia (OR = 4.24, CI [2.9, 6.49] ), xerostomia (OR = 7.72, CI [3.27, 25.10]), severe gingivitis (OR = 2.04, CI [1.43, 3.03] ), and ≥ 6 missing teeth (OR = 3.73, CI [2.46, 6.00]) compared to controls without cancer history. Survivors who received classic alkylating agents (OR = 1.6, CI [1.36, 1.88] ), anthracycline antibiotics (OR = 1.22, CI [1.04, 1.42] or radiation therapy potentially exposing the oral cavity (OR = 1.48, CI [1.26, 1.72] ) were more likely to report at least one dental health problem after controlling for socioeconomic factors, age at last follow-up and diagnosis, other treatment exposures, and access to dental services. Survivors who had radiation therapy potentially exposing the oral cavity (OR = 1.52, CI [1.25, 1.84]) were also more likely to report at least one soft tissue abnormality after controlling for socioeconomic factors, age at last follow-up and diagnosis, other treatment exposures, and access and utilization of dental services. Conclusions Childhood cancer survivors have a higher prevalence of oral-dental abnormalities than the controls without a cancer history. Cancer treatment, socioeconomic factors, and access to oral health care contribute to the prevalence of dental abnormalities.
    Type of Medium: Online Resource
    ISSN: 1472-6831
    URL: Article
    DOI: 10.1186/s12903-023-02762-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2091511-1
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  • 3
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    Antimicrobial Efficacy Assessment of Human Derived Composite Amnion-Chorion Membrane
    Springer Science and Business Media LLC ; 2019
    In:  Scientific Reports Vol. 9, No. 1 ( 2019-10-30)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2019-10-30)
    Abstract: Human derived composite amnion-chorion membrane (ACM) has been used to facilitate wound healing due to reported anti-inflammatory properties and promotion of cell proliferation. This study aimed to assess the antimicrobial properties of the ACM using novel methods to visualize the antimicrobial efficacy of membranes in situ at different time points. Porcine Pericardium Collagen Membranes (PPCM) served as membrane controls. Circular pieces of the membranes were used in three different assays: insert, agar contact and glass-bottom well assays. Streptococcus gordonii were spotted onto the membranes and the plates were subsequently centrifuged to ensure direct bacterial contact with the membranes in the insert and agar contact assays, thus better mimicking bacterial adherence in the oral cavity. After incubation at 37 °C for 8, 24, and 48 hours, the membranes were dyed with the Live/Dead BacLight Bacterial Viability fluorescence stain and analyzed via confocal microscopy. The results demonstrated that the ACM completely inhibited bacterial growth at all time points, whereas the PPCM did not demonstrate any antimicrobial properties. Within the limits of this study, the ACM showed extremely high antimicrobial efficacy against oral streptococci. In addition, our methods may be useful in assessing antimicrobial properties for biomaterials with minimum diffusion ability, when traditional assessment methods are not applicable.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-019-52150-4
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2615211-3
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  • 4
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    A comprehensive artificial intelligence framework for dental diagnosis and charting
    Springer Science and Business Media LLC ; 2022
    In:  BMC Oral Health Vol. 22, No. 1 ( 2022-11-09)
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    In: BMC Oral Health, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2022-11-09)
    Abstract: The aim of this study was to develop artificial intelligence (AI) guided framework to recognize tooth numbers in panoramic and intraoral radiographs (periapical and bitewing) without prior domain knowledge and arrange the intraoral radiographs into a full mouth series (FMS) arrangement template. This model can be integrated with different diseases diagnosis models, such as periodontitis or caries, to facilitate clinical examinations and diagnoses. Methods The framework utilized image segmentation models to generate the masks of bone area, tooth, and cementoenamel junction (CEJ) lines from intraoral radiographs. These masks were used to detect and extract teeth bounding boxes utilizing several image analysis methods. Then, individual teeth were matched with a patient’s panoramic images (if available) or tooth repositories for assigning tooth numbers using the multi-scale matching strategy. This framework was tested on 1240 intraoral radiographs different from the training and internal validation cohort to avoid data snooping. Besides, a web interface was designed to generate a report for different dental abnormalities with tooth numbers to evaluate this framework’s practicality in clinical settings. Results The proposed method achieved the following precision and recall via panoramic view: 0.96 and 0.96 (via panoramic view) and 0.87 and 0.87 (via repository match) by handling tooth shape variation and outperforming other state-of-the-art methods. Additionally, the proposed framework could accurately arrange a set of intraoral radiographs into an FMS arrangement template based on positions and tooth numbers with an accuracy of 95% for periapical images and 90% for bitewing images. The accuracy of this framework was also 94% in the images with missing teeth and 89% with restorations. Conclusions The proposed tooth numbering model is robust and self-contained and can also be integrated with other dental diagnosis modules, such as alveolar bone assessment and caries detection. This artificial intelligence-based tooth detection and tooth number assignment in dental radiographs will help dentists with enhanced communication, documentation, and treatment planning accurately. In addition, the proposed framework can correctly specify detailed diagnostic information associated with a single tooth without human intervention.
    Type of Medium: Online Resource
    ISSN: 1472-6831
    URL: Article
    DOI: 10.1186/s12903-022-02514-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2091511-1
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